estrutura dos sistemas radicais

UNIVERSIDADE TÉCNICA DE LISBOA
INSTITUTO SUPERIOR DE AGRONOMIA
ESTRUTURA DOS SISTEMAS RADICAIS E DINÂMICA DA
ÁGUA NO SOLO NUMA COMUNIDADE ARBUSTIVA DA
TAPADA NACIONAL DE MAFRA
JOAQUIM MANUEL SANDE SILVA
ORIENTADOR:
Doutor Francisco Manuel Cardoso de Castro Rego
CO-ORIENTADOR:
Doutor Stefano Mazzoleni
JURI: Presidente
Reitor da Universidade Técnica de Lisboa.
Vogais
Doutor Stefano Mazzoleni, full professor da Facoltà di Agraria da
Università di Napoli Frederico II, Itália;
Doutora Maria Amélia Botelho de Paulo Martins Campos Loução,
professora catedrática da Faculdade de Ciências da Universidade de
Lisboa;
Doutor Manuel Armando Valeriano Madeira, professor catedrático do
Instituto Superior de Agronomia da Universidade Técnica de Lisboa;
Doutor Francisco Manuel Cardoso de Castro Rego, professor associado
do Instituto Superior de Agronomia da Universidade Técnica de Lisboa;
Doutor António Manuel Dorotêa Fabião, professor associado do Instituto
Superior de Agronomia da Universidade Técnica de Lisboa;
Doutor José Miguel Oliveira Cardoso Pereira, professor associado
convidado do Instituto Superior de Agronomia da Universidade Técnica
de Lisboa.
DOUTORAMENTO EM ENGENHARIA FLORESTAL
LISBOA
2002
ii
AGRADECIMENTOS
Muito embora uma tese de doutoramento tenha apenas um autor, ela é normalmente o
resultado de inúmeras colaborações. A tese que agora se apresenta não é, a esse respeito,
uma excepção. Por isso esta secção de agradecimentos, muito mais que uma mera
formalidade ou um dever moral, é sobretudo o resultado de uma vontade sincera de
manifestar a minha gratidão a todas as pessoas que contribuíram para tornar possível este
trabalho. O meu muito obrigado a todas elas!
Em particular impõe-se um agradecimento especial:
-
-
-
ii
Ao meu orientador Professor Francisco Castro Rego, companheiro constante deste e de
outros desafios passados e esperemos que futuros também.
Ao meu co-orientador Professor Stefano Mazzoleni, pelo acompanhamento e conselhos
prestados, apesar da distância a separar-nos.
À Professora Mariana Amato, pela co-orientação na fase incial desta tese.
À Professora Amélia Martins-Loução, pela colaboração prestada nos capítulos 2 e 3
desta tese e pelo interesse geral demonstrado.
Ao Francesco Giannino pela colaboração no capítulo 6 e pelo apoio logístico em
Nápoles.
Ao Engenheiro Ricardo Paiva, pela autorização em realizar este estudo na Tapada
Nacional de Mafra e ainda pelo apoio logístico prestado.
Aos funcionários da Tapada Nacional de Mafra: Sr. José Domingos, guarda Luis Filipe,
guarda João Louro e a todos os outros não referidos aqui, pelo apoio prestado no
trabalho de campo.
À Doutora Paula Gonçalves, pela colaboração relativamente aos dados da Serra da
Malcata.
Aos alunos da ESAC: Ana Salomé David, Cristina Monteiro, Nuno Lobo e Inês Lopes,
pela colaboração em várias fases do trabalho de campo.
Ao Victor Abadia, pela colaboração no trabalho de campo.
Aos estagiários do programa Sócrates: Ioana Chitu e Costel Petku, pela colaboração no
trabalho de campo e de laboratório.
Ao técnico da DRABL Sérgio Correia, pelo precioso apoio no planeamento e na
realização do fogo experimental.
Ao colega da UTAD Paulo Fernandes, pela bibliografia disponibilizada.
Aos colegas da ESAC: Carmo Magalhães, David Rodrigues, Hélia Marchante, José
Maia, Manuel Nunes, Óscar Crispim e a outros colegas e funcionários não referidos,
pela colaboração prestada em diversas fases deste trabalho.
À instituição a que pertenço, a Escola Superior Agrária de Coimbra, pela dispensa de
serviço docente no âmbito de uma bolsa PRODEP durante a metade final da realização
deste trabalho.
iii
RESUMO
São abordados diferentes aspectos da estrutura das raízes e da dinâmica da água no
solo numa comunidade arbustiva da Tapada Nacional de Mafra. Numa amostra de plantas
escavadas incluindo várias espécies, é realizada uma análise de diferentes variáveis
estruturais revelando uma distribuição das plantas de acordo com grupos funcionais e
estádios de desenvolvimento. São apresentadas relações alométricas consistentes entre a
secção basal das plantas e as biomassas da raiz e da parte aérea. É desenvolvido e testado
com sucesso um novo modelo de distribuição vertical de raízes. Este modelo é utilizado
para caracterizar a distribuição das raízes ao nível do indivíduo e ao nível da comunidade.
São estimadas a profundidade máxima de enraizamento, a distribuição vertical e os valores
absolutos de biomassa e comprimento de raízes finas da comunidade arbustiva. É estudado
o efeito de curto prazo do fogo na água do solo, sendo observado um aumento do teor de
humidade na parcela queimada relativamente à parcela testemunha. É apresentado e testado
com sucesso um novo modelo de simulação da dinâmica da água no solo, utilizando para
tal medições de humidade no solo realizadas a diferentes profundidades ao longo de 18
meses.
Palavras chave: Vegetação mediterrânica, sistemas radicais, distribuição das raízes, efeitos
do fogo, dinâmica da água no solo, modelação.
iii
iv
ABSTRACT
(Root system structure and soil water dynamics in a shrub community at Tapada Nacional
de Mafra)
The present thesis approaches different aspects of the root structure and the soil
water dynamics of a shrub community at Tapada Nacional de Mafra. Using a sample of
excavated plants including different species, an analysis of different structural variables is
performed, revealing a distribution of plants according to functional groups and
developmental stages. Consistent allometric relationships between basal section and root
and shoot biomass are presented. A new root distribution model is developed and
successfully tested. This model is used to characterise root distributions at the individual
and at the community level. The maximum rooting depth, the vertical distribution and the
absolute values of fine root biomass and length are estimated at the community level. The
short-term effect of fire on soil water dynamics is studied, revealing an increase on soil
moisture at the burned plot when compared to the control plot. A new soil water dynamics
model is presented and successfully tested, for which a set of soil water measurements
taken at different depths during an 18-month period, is used.
Keywords: Mediterranean vegetation, root systems, root distribution, fire effects,
soil water dynamics, modelling.
iv
v
ÍNDICE
AGRADECIMENTOS........................................................................................................... ii
RESUMO .............................................................................................................................. iii
ABSTRACT .......................................................................................................................... iv
ÍNDICE .................................................................................................................................. v
LISTA DE FIGURAS .......................................................................................................... vii
LISTA DE TABELAS .......................................................................................................... xi
1
INTRODUÇÃO.......................................................................................................... 1
1.1
As comunidades arbustivas das regiões mediterrânicas................ 1
1.2
O papel dos sistemas radicais nas estratégias evolutivas das plantas
mediterrânicas ........................................................................................... 3
1.3
O estudo das raízes das plantas mediterrânicas............................. 7
1.4
Os efeitos do fogo na dinâmica da água do solo ......................... 10
1.5
A modelação da dinâmica da água no solo ................................. 12
1.6
Justificação, objectivos e estrutura da presente tese.................... 16
Bibliografia.............................................................................................. 20
2
BELOWGROUND TRAITS OF MEDITERRANEAN WOODY PLANTS IN A
PORTUGUESE SHRUBLAND........................................................................................... 27
2.1
Introduction ................................................................................. 28
2.2
Methods ....................................................................................... 29
2.3
Results ......................................................................................... 32
2.4
Discussion ................................................................................... 38
References ............................................................................................... 40
3
ROOT
DISTRIBUTION
OF
MEDITERRANEAN
WOODY
PLANTS;
INTRODUCING A NEW EMPIRICAL MODEL .............................................................. 43
3.1
Introduction ................................................................................. 44
3.2
Methods ....................................................................................... 45
3.3
Results ......................................................................................... 49
3.4
Discussion ................................................................................... 54
References ............................................................................................... 57
v
vi
4
ROOT
DISTRIBUTION
OF
A
MEDITERRANEAN
SHRUBLAND
IN
PORTUGAL......................................................................................................................... 60
4.1
Introduction ................................................................................. 61
4.2
Methods ....................................................................................... 62
4.3
Results ......................................................................................... 67
4.4
Discussion ................................................................................... 74
References ............................................................................................... 77
5
FIRE EFFECTS ON SOIL WATER DYNAMICS IN A MEDITERRANEAN
SHRUBLAND...................................................................................................................... 81
3.1
Introduction ................................................................................. 82
3.2
Methods ....................................................................................... 83
3.3
Results ......................................................................................... 85
3.4
Discussion ................................................................................... 92
References ............................................................................................... 94
6
MODELLING
SOIL
WATER
DYNAMICS
IN
A
MEDITERRANEAN
SHRUBLAND...................................................................................................................... 96
6.1
Introduction ................................................................................. 97
6.2
Methods ....................................................................................... 98
6.3
Results ....................................................................................... 105
6.4
Discussion ................................................................................. 111
References ............................................................................................. 114
7
DISCUSSÃO E CONCLUSÕES ........................................................................... 117
7.1
Estudo das raízes de plantas individuais ................................... 117
7.2
Estudo das raízes ao nível da comunidade de plantas ............... 124
7.3
Estudo da dinâmica da água no solo ......................................... 128
Bibliografia............................................................................................ 134
vi
vii
LISTA DE FIGURAS
Fig. 1.1 Aspecto geral do matagal de urze (Erica scoparia e Erica lusitanica) na Tapada
Nacional de Mafra, onde decorreram os trabalhos relatados nos capítulos 4, 5 e 6 e
onde foram escavadas algumas das plantas estudadas nos capítulos 2 e 3. .......... 18
Fig. 2.1 PCA diagrams. A represents the components loadings for each variable and B
represents the components scores for each plant individual. Legend for variables:
DIAMETER – Average root diameter; BIOMASS – Root biomass; DEPTH –
Maximum rooting depth; WIDTH – Root system width; LENGTH – Root length;
R/S – Root-to-shoot ratio; SRL – Specific root length. Legend for species: Cc –
Cistus crispus; Cs – Cistus salvifolius; Cm – Crataegus monogyna; Dg – Daphne
gnidium; El – Erica lusitanica; Es – Erica scoparia; Ll – Lavandula luisieri; Mc –
Myrtus communis; Pl – Pistacia lentiscus; Ru – Rubus ulmifolius; Uj – Ulex
jussiaei. Symbols in bold correspond to obligate seeders. The developmental stage,
as obtained by the respective basal section, is indicated by the number following the
species symbol. Stage 1: 0 to 5 mm2; stage 2: 5 to 25 mm2; stage 3: 25 to 125 mm2;
stage 4: > 125 mm2................................................................................................ 34
Fig. 2.2 Relationships between Basal Section and two root system indices: Specific Root
Length (SRL) and Root-to-Shoot ratio (Root-Shoot), for two obligate seeders (
Cistus crispus and Lavandula luisieri; represented in bold) and two resprouters
(Daphne gnidium and Crataegus monogyna; normal lettering). .......................... 36
Fig. 2.3 Images of 16 plants representing different developmental stages (as defined in
Figure 1) of two resprouters: A – Daphne gnidium (stages 1,2,3 and 4), B –
Crataegus monogyna (stages 1,2,3 and 4); and two obligate seeders: C – Lavandula
luisieri (stages 1,2,3 and 4), D – Cistus crispus (stages 1,2,2 and 3). The vertical
bars represent 0.5 m. Arrows indicate the ground surface .................................... 37
Fig. 3.1 Root distribution of nine plants excavated at Tapada Nacional de Mafra as
represented by the fitted MLDR model (see text and equation 4). D and c are the
model parameters. The solid line represents the cumulative root biomass distribution
and the dotted line represents the cumulative root length distribution.................. 52
vii
viii
Fig. 3.2 Root systems of nine plants excavated at Tapada Nacional de Mafra. The
corresponding cumulative root distributions are shown on Fig. 3.1. The vertical bar
represents 0.5 m..................................................................................................... 53
Fig. 4.1 Relationship between root diameter and the vertical distance to the root tip for
Erica ...................................................................................................................... 66
Fig. 4.2 Average density of root counts for each species including all diameters. (mean±SE,
n=6). Insets represent the MLDR model fitted to the cumulative root fraction.
Horizontal lines and corresponding depths indicate the value of D50. .................. 70
Fig. 4.3 Average density of root counts for each diameter, including all species (mean±SE,
n=6). Insets represent the MLDR model fitted to the cumulative root fraction.
Horizontal lines and corresponding depths indicate the value of D50. .................. 71
Fig. 4.4 Schematic representation of the estimated average maximum rooting depth (mean
of the deepest 28 roots) of Erica plants at each trench. The solid line represents the
soil surface. The broken straight line represents the maximum depth of excavation
(bottom of the trenches). Both the above and the belowground parts of each plant
have been drawn to scale in order to represent the average height and the average
maximum rooting depth respectively. Each trench is represented by an image
obtained from an Erica scoparia individual.......................................................... 72
Fig. 4.5 Distribution of the estimated maximum rooting depths of Erica (mean±SE; n=2,
n=3 and n=4 for the first, second and third depth classes, respectively; n=6 for the
remaining classes). ................................................................................................ 72
Fig. 4.6 Biomass and length of fine roots per unit of soil volume (mean±SE, n=10) as
obtained from core samples. Gaps at 50 cm, 70 cm and 90 cm on the y axis
correspond to non-sampled depths. Insets represent the MLDR model fitted to the
cumulative root fraction. Horizontal lines and corresponding depths indicate the
value of D50. .......................................................................................................... 73
Fig. 5.1 Evolution of plant cover during the treatment period. Triangles and diamonds
represent Erica and P. aquilinum respectively. Open symbols/dashed lines refer to
plant height whereas closed symbols/solid lines are the density of P. aquilinum
fronds or resprouting of Erica plants. ................................................................... 86
Fig. 5.2 Root density (number of root counts/dm2) at the control and the burned plots
(mean±SE). Data collected before fire. ................................................................. 87
viii
ix
Fig. 5.3 Values of soil moisture for each plot in the two study periods with the
corresponding meteorological data (bars and solid line represent rainfall and
average daily temperature, respectively)............................................................... 87
Fig. 5.4 Average soil moisture of the control and the burned plots during the treatment
period and two weeks before fire. ......................................................................... 90
Fig. 5.5 Differences in soil water storage between the treatment and the reference periods in
the burned (Dbi) and the control (Dci) plots. Si = Dbi - Dci represents the effect of
fire on soil water. Si is represented by a moving average (n=7). Estimation for 0-180
cm is an integration using 20 cm increments. ....................................................... 91
Fig. 6.1 Schematic diagram of model SWADY drawn using the modelling environment
Simile. The compartment SWC represents the Soil Water Content, circles with a
cross represent variables, thick arrows represent flows to and from the compartment
and the curved thin arrows represent influences between the different model entities.
............................................................................................................................. 100
Fig. 6.2 Comparison between soil water content values obtained from laboratorydetermined water retention relationships (measured) and the corresponding values
obtained using the soil water retention sub-model (modelled) based in the method
proposed by Wösten et al., (1999) for computing the parameters of the MualemVan-Genuchten equation. Soil water content values correspond to three pressure
head levels applied to samples from six different depths, from both plots. The solid
line represents the linear regression (n=36) and the broken line represents a
reference y=x relationship. .................................................................................. 108
Fig. 6.3 Water content at six different depths at the control plot. Circles represent actual
measurements and the continuous lines represent model simulations. The histogram
shows the rainfall during the two years (separated by a broken line) of
measurements. Horizontal broken lines represent saturation, field capacity and
wilting point, respectively, as obtained by the model. ........................................ 109
Fig. 6.4 Water content at six different depths at the burned plot. Circles represent actual
measurements and the continuous lines represent model simulations. The histogram
shows the rainfall during the two years (separated by a broken line) of
measurements. Horizontal broken lines represent saturation, field capacity and
ix
x
wilting point, respectively, as obtained by the model. The arrow indicates the date
of fire. .................................................................................................................. 110
Fig. 6.5 Modelled (line) and measured (circles) net effect of fire in terms of soil water
storage (Si). Si=Dbi- Dci, where Dbi represents the soil water storage difference for
each day (i) between the treatment period and the reference period in the burned
plot and (Dci) represents the same difference for the control plot. The estimation
refers to the layer 0-180 cm and results from an integration using 20 cm increments.
Fire occurred at the beginning of the time series (Julian day 155, 4th of June).. 111
x
xi
LISTA DE TABELAS
Table 2.1 Descriptive parameters (mean ± SE) of the root systems of 33 plants excavated at
Tapada Nacional de Mafra, distributed by species. Legend for abbreviations: n –
number of plants; Reg. strat. – regenerative strategy; Maxim. root. depth maximum rooting depth; Aver. root diam. – average root diameter; R/S – root-toshoot ratio; SRL – specific root length; s – obligate seeder; r – resprouter. ......... 33
Table 2.2 Allometric relationships obtained by linear regression between basal section
(mm2) and four different root variables: root biomass, shoot biomass, root system
length and root system width. All variables were log-transformed. Biomass data is
indicated in decigrams in order to obtain only positive values. For each linear
regression it is indicated the intercept (a), the slope (b), the coefficient of
determination (r2) and the associated probability (p). ........................................... 35
Table 3.1 Comparison of average ranks (1 to 4) and mean r2 of four models fitted to root
biomass and root length data, as obtained by the Friedman Anova (p<0.001 for both
root biomass and root length distributions). Values of mean r2 followed by the same
letter did not present significant differences (p>0.05) as obtained by paired
comparisons using the Mann-Whitney U test. ...................................................... 49
Table 3.2 Maximum rooting depth averaged by species and basal section class. Maximum
rooting depth represents the depth achieved by the deepest root. Values are averages
and the number of plants is shown in brackets. The range was obtained as the
difference between the maximum and the minimum values observed. Basal section
classes are defined as: BS1 ≤ 12.6 mm2, 12.6 mm2< BS2 ≤ 50.3 mm2, BS3 > 50.3
mm2. ...................................................................................................................... 50
Table 3.3 Values of db50 and dl50 averaged by species and by basal section (BS) class. Basal
section classes are defined as: BS1 ≤ 12.6 mm2, 12.6 mm2< BS2 ≤ 50.3 mm2, BS3 >
50.3 mm2. The range was obtained as the difference between the maximum and the
minimum values observed within all plants from each species. ........................... 51
Table 4.1 General soil characteristics (mean±SE, n=6). ................................................... 67
Table 4.2 Aboveground plant cover before trench excavation. Basal area is the sum of
individual cross sections measured at the stem base per m2 (mean±SE, n=6)...... 68
xi
xii
Table 4.3 Average root density (number of root counts/dm2) including all depths
(mean±SE, n=6). Means followed by the same letter are not significantly different
(p<0.05) according to the Mann-Whitney U test. The first letter refers to differences
among diameter classes (columns) and the second letter refers to differences among
species (rows). Symbol “_” represents no data...................................................... 69
Table 5.1 Mean ± SE values of Di (soil moisture differences in terms of % volume, between
the treatment and the reference periods). Means sharing the same letter are not
statistically different (p >0.05, n=4). Letters in the first column refer to comparisons
between plots within each season (t tests). Letters in the second column refer to
multiple comparisons between depths (Tuckey tests)........................................... 90
Table 6.1 List of input variables..................................................................................... 101
Table 6.2 Descriptive statistics of soil water measurements (% vol.) representing 318 days
between May 2000 to December 2001, for the control and the burned plots. SD –
Standard Deviation; SE – Standard Error............................................................ 106
Table 6.3 Results of linear regressions (n=318) for comparison between measured
(abscissa) vs. modelled (ordinate) soil water data for the two plots and each depth.
............................................................................................................................. 108
xii
1
1 INTRODUÇÃO
1.1
As comunidades arbustivas das regiões mediterrânicas
A
designação
de
ecossistema
mediterrânico,
apesar
de
utilizada
recorrentemente, nem sempre recolhe unanimidade quando aplicada aos ecossistemas
existentes em Portugal. Em parte devido à situação geográfica do nosso país, exterior à
Bacia
Mediterrânea,
há
frequentemente
dificuldade
em
classificar
clara
e
inequivocamente um determinado tipo de clima e de comunidade vegetal como
possuindo características mediterrânicas. Esta dificuldade é tanto maior quanto maior é
a influência dita atlântica, que em Portugal se faz sentir sobretudo junto ao litoral e em
particular na Região Norte. Esta dicotomia Mediterrâneo - Atlântico, embora tendo na
sua essência causas de natureza climática, reflecte-se não só ao nível da vegetação mas
num leque alargado de características físicas e humanas, tal como é retratado em
Ribeiro (1991). Apesar da situação geográfica do território português, o facto de o autor
apenas dedicar 28 páginas ao Portugal Atlântico e 99 páginas ao Portugal
Mediterrâneo, diz bem da predominância do segundo sobre o primeiro.
No entanto não se pense que esta indefinição constitui uma dificuldade apenas
relativa ao território português. Tendo em conta a necessidade de delimitar as zonas de
influência mediterrânica, diversos autores tentaram utilizar critérios objectivos de forma
a estabelecer limites claros e definidos, para a Região Mediterrânea e/ou para outras
regiões do Planeta com clima mediterrânico (Aschmann, 1973; Daget, 1977; Quézel,
1985). Para além da Região Mediterrânea existem quatro outras regiões no Mundo onde
é possível encontrar um clima e uma vegetação com características semelhantes
(Walter, 1979): a California nos EUA, a região litoral Centro do Chile, a costa sudoeste
da África do Sul e a costa sul e sudoeste da Austrália. No caso concreto da Região
Mediterrânea, Quézel (1985) compara a utilização de critérios florísticos, critérios
fitossociológicos, critérios climáticos e critérios bioclimáticos para definir os seus
limites. Através dos mapas resultantes da aplicação destes critérios constata-se que
todos eles resultam na inclusão de todo ou quase todo o território português, na Região
Mediterrânea. Também Le Houérou (1992) refere como possuindo clima mediterrânico
os dois terços sul do território português. Vale enfim a pena reter a definição mais ou
menos consensual de bioclima mediterrânico avançada por Daget (1977). Segundo este
autor um clima é mediterrânico nas regiões em que o Verão é a estação mais seca e em
1
2
que existe um período de stress fisiológico para as plantas. Uma referência final para o
trabalho de Costa et al. (1998) onde o território português é, em termos fitogeográficos,
quase todo incluído na Região Mediterrânica. Exceptua-se apenas a região situada
sensivelmente a norte de Aveiro-Viseu e a oeste de Vila Real, a qual é incluída na
Região Eurosiberiana.
Parecendo assim clara a marcada influência mediterrânica no território
Português, há no entanto que ter em conta as especificidades dos nossos ecossistemas e
em particular das formações arbustivas quando comparadas com as de outras zonas da
Região Mediterrânea. Aqui há que entrar sem dúvida em conta com o efeito moderador
da vizinhança do oceano sobre o nosso território, o qual se traduz essencialmente em
precipitações mais elevadas e em menores amplitudes térmicas que noutras zonas da
Região Mediterrânea com uma influência mais continental. Este aspecto é responsável
em boa medida pelo carácter mais mésico e menos xérico da vegetação que compõe
uma boa parte das comunidades arbustivas em Portugal. De acordo com a simplificação
da classificação climática de Emberger adoptada por Di Castri (1981), estas regiões são
classificadas como sub-húmidas (5-6 meses secos) ou húmidas (3-4 meses secos) dentro
do universo de climas mediterrânicos. A este carácter mésico estão normalmente
associadas comunidades arbustivas mais altas e mais densas, normalmente englobadas
na designação francesa de maquis a qual não tem um equivalente claro no vocabulário
Português. De entre as diferentes designações aplicadas em Portugal podemos referir as
de mato alto ou matagal. Este tipo de formações tem equivalente noutras regiões
mediterrânicas do Globo, recebendo a designação de fynbos na África do Sul, de mallee
na Austrália, de chaparral na California e de matorral no Chile. Na Bacia Mediterrânea
estas comunidades são geralmente consideradas etapas intermédias da sucessão, ou
antes como etapas intermédias de degradação relativamente a formações climácicas
dominadas por espécies arbóreas do género Quercus (Le Houérou, 1981). No outro
extremo encontram-se as formações altamente degradadas de vegetação arbustiva
esparsa e baixa, designadas em França como garrigue, na Grécia como phrygana e em
Espanha como tomillares. A sua ocorrência no nosso país está normalmente associada a
zonas do Sul com um grau elevado de aridez ou a zonas de serra com uma frequência
elevada de fogo e pastoreio. Ao contrário, os matagais altos resultam inevitavelmente da
ocorrência de períodos relativamente prolongados com ausência de perturbações. De um
modo geral caracterizam-se por uma baixa diversidade florística sendo normalmente
dominados por uma ou duas espécies arbustivas constituindo populações com elevada
2
3
densidade e também altamente susceptíveis ao fogo (Naveh, 1994). De entre as
diferentes espécies que se podem apresentar como dominantes neste tipo de formações
arbustivas importa referir, devido à sua importância em Portugal, as dos géneros Erica,
Quercus (sobretudo Q. coccifera), Pistacia, Arbutus, Cytisus e Cistus (sobretudo C.
ladanifer).
O local escolhido para a realização do presente estudo, a Tapada Nacional de
Mafra, encontra-se maioritariamente coberto por matagais dominados por Erica
scoparia e Erica lusitanica sendo igualmente comum o aparecimento de plantas do
género Ulex. Em termos fitogeográficos, Costa et al. (1998) inclui esta região no
Superdistrito Olissiponense apontando como formações climácicas para esta região,
bosques de Quercus suber e de Quercus faginea. e como etapa sucessional de
substituição, matagais dominados por Ulex.
1.2
O papel dos sistemas radicais nas estratégias evolutivas das plantas
mediterrânicas
De entre os diferentes critérios utilizados para definir o clima mediterrânico,
resulta das considerações anteriores que o traço fundamental é a existência de um
período de secura estival. A ocorrência de uma estação quente e seca tem duas
consequências principais as quais se constituem como forças modeladoras, essenciais
para a compreensão das características evolutivas das plantas mediterrânicas: a
ocorrência do fogo e a deficiência de água no solo durante uma parte do ano.
Em relação ao primeiro aspecto é comum agrupar as plantas dos ecossistemas
mediterrânicos em tipos funcionais resultantes dos mecanismos de adaptação ao fogo. A
este respeito são numerosas as tentativas de encontrar sistemas de classificação que
permitam agrupar as plantas de forma a reflectir características comuns de adaptação ao
fogo (Le Houérou, 1973; Naveh, 1975; Noble & Slatyer, 1980; Gill, 1981; Keeley,
1991; Trabaud, 1992, Keeley, 1995; Noble & Gitay, 1996; Pausas, 1999). De todos
estes sistemas ressalta um aspecto comum fundamental que consiste na separação das
diferentes espécies em dois grandes grupos funcionais de acordo com a sua capacidade
para regenerar ou não vegetativamente. Deste modo, o estudo dos mecanismos
ecológicos que envolvem as espécies mediterrânicas passa assim em boa parte pela
abordagem das suas características regenerativas enquanto adaptações ao fogo.
Podemos assim de forma simplista considerar um grupo constituído pelas espécies com
aptidão para regenerar vegetativamente (resprouters) e um outro constituído pelas
3
4
espécies que apenas podem regenerar por semente (seeders). O primeiro grupo inclui
todas as espécies cuja regeneração imediatamente após o fogo é garantida através do
lançamento de novos rebentos com origem em tecidos que resistiram, ou não foram
atingidos, pelas altas temperaturas. Estes tecidos localizam-se no caule ou em órgãos
subterrâneos tais como rizomas, bolbos ou tubérculos. No segundo grupo incluem-se
todas as espécies cujos indivíduos morrem após a ocorrência do fogo e que, como tal,
estão completamente dependentes da regeneração por via seminal para poder assegurar
a sua continuidade. Apesar de se tratar apenas de uma característica regenerativa, esta
diferença de estratégias tem sido associada a uma multiplicidade de outros aspectos da
morfologia, da fisiologia e da ecologia das respectivas espécies (Margaris, 1981;
Ferreira, 1996; Bell, 2001). Em termos gerais as espécies de regeneração vegetativa
podem atingir um porte mais elevado e possuem um ciclo de vida mais longo, têm uma
taxa de crescimento mais baixa, têm uma menor produção de sementes e têm um
sistema radical mais extenso. Estão normalmente associadas a etapas mais avançadas da
sucessão, nomeadamente a matagais altos e apenas regeneram por semente quando estão
reunidas condições ambientais mais favoráveis à germinação e ao crescimento das
plântulas (Silva & Rego, 1998a). O recrutamento é feito de forma gradual dando origem
a baixas densidades de plântulas (Silva & Rego, 1998b; Clemente et al., 1994). Dadas
estas características, é normal referir estas espécies como estrategas K (Ferreira, 1996;
Díaz Barradas et al., 1999) no âmbito das definições para as estratégias populacionais
propostas por McArthur & Wilson (1967). Ao nível das espécies existentes em Portugal
são incluídas neste grupo quase todas as espécies normalmente apontadas como
dominantes das formações climácicas referidas para o nosso país, nomeadamente os
géneros Quercus, Arbutus, Pistacia, Rhamnus, Viburnum, Phyllirea e Laurus, entre
outros. As espécies de regeneração obrigatória por semente têm de um modo geral as
características opostas às anteriores e exibem frequentemente adaptações morfológicas e
anatómicas à secura tais como indumento, menor área foliar, produção de óleos voláteis,
cutícula e mesófilo mais espessos e um mais eficiente controlo estomático (Keeley,
1986). Estas espécies têm tendência a dominar em zonas mais secas e menos férteis e
em fases pouco evoluídas da vegetação, sendo frequentemente associadas a matos
baixos e dispersos do tipo phrygana (Margaris, 1981). Muitas delas dão origem a um
banco de sementes que se podem manter no solo em estado de dormência durante vários
anos. Em oposição ao grupo anterior e dado o intenso recrutamento que ocorre sempre
que estejam reunidas as condições necessárias à germinação, nomeadamente o calor
4
5
proporcionado pelo fogo (Christensen & Muller, 1974; Papanastasis & Romanas, 1977;
Arianoutsou & Margaris, 1982; Mazzoleni, 1989; Valbuena et al., 1990; GonzalezRabanal & Casal, 1993) ou a simples abertura de clareiras, estas espécies são
normalmente conotadas com a estratégia r. De entre as espécies que ocorrem no nosso
país são importantes representantes deste grupo as plantas dos géneros Cistus,
Lavandula, Rosmarinus e Halimium. No entanto existem numerosas espécies que, muito
embora estando obrigatoriamente incluídas numa das duas categorias referidas, não
correspondem minimamente ao padrão de características descrito. Daí a necessidade
constatada por vários autores de identificar sub-grupos que tivessem um número
mínimo de semelhanças funcionais nomeadamente no que toca às adaptações ao fogo.
De entre os trabalhos já citados parece-nos interessante o modelo proposto por Pausas
(1999) o qual simplesmente sub-divide os dois grupos de acordo com a existência ou
não de um recrutamento de plântulas directamente favorecido pelo fogo, dando assim
origem a quatro categorias distintas.
No que toca aos mecanismos de sobrevivência ao stress hídrico ou tolerância à
secura (drought tolerance) também diferentes autores têm proposto diferentes sistemas
de agrupamento das estratégias adoptadas pelas várias espécies. Muito embora exista
alguma inconsistência em torno da terminologia adoptada (Kozlowski et al., 1991), é
mais ou menos clássica a distinção entre mecanismos para evitar a secura
(drought/dessication avoidance) e mecanismos de resistência/tolerância à secura
(drought/dessication resistance/tolerance) (Larcher, 1975; Kozlowski, 1982, Kozlowski
et al., 1991). O primeiro tipo de mecanismos tem a ver com adaptações estruturais ao
passo que o segundo tem a ver com adaptações fisiológicas ao nível celular. Enquanto
que no segundo caso se tratam de mecanismos que permitem à planta resistir a baixos
potenciais hídricos, o primeiro tipo de estratégia consiste essencialmente em evitar a
ocorrência desses níveis de potencial hídrico. Jones (1992) distingue ainda num grupo à
parte os mecanismos de eficiência directa e indirecta do uso da água e Fitter (2002)
divide os mecanismos para evitar a secura, em adaptações para a aquisição da máxima
quantidade de água e adaptações para a conservação e uso eficiente da água. Esta última
interpretação corresponde a considerar a existência de espécies que resistem à secura
essencialmente gastando água (water spenders) e um outro grupo de espécies que
essencialmente resistem à secura poupando água (water savers).
São inúmeras as descrições das adaptações estruturais desenvolvidas pelas
plantas para evitarem o stress hídrico. Algumas delas foram atrás referidas dado existir
5
6
alguma correspondência entre as estratégias regenerativas das espécies mediterrânicas
após o fogo e as estratégias de adaptação das mesmas espécies ao stress hídrico. Um
dos principais aspectos a ter em conta a este respeito tem a ver com a estrutura do
sistema radical dado esta estar intimamente ligada à possibilidade de regeneração
vegetativa e simultaneamente, à capacidade de exploração do solo e de extracção de
água e nutrientes. No caso das espécies que possuem regeneração vegetativa é
fundamental a existência de um sistema de raízes extenso e profundo que permita
responder às necessidades em água e nutrientes dos rebentos que surgem após o fogo. A
este nível algumas espécies como as ericáceas desenvolveram paralelamente a formação
de órgãos tuberosos de reserva onde são armazenados hidratos de carbono sob a forma
de amido (lignotubers). Nas espécies de regeneração vegetativa é frequente a formação
de raízes pivotantes (tap roots) as quais podem atingir profundidades de dezenas de
metros (Kummerow, 1981; Canadell et al., 1996). Estas raízes têm um papel
fundamental durante a estação seca dado permitirem à planta aceder a camadas de solo
com teores de humidade bastante superiores aos da superfície, onde existe uma muito
maior concentração de raízes finas e onde se fazem sentir os efeitos directos da
evaporação (Nepstad et al., 1994; Canadell & Zedler, 1995). Esta possibilidade de
aceder a camadas de solo mais húmido permite que estas espécies não necessitem das
adaptações estruturais já referidas (indumento, folhas reduzidas, cutícula espessa, entre
muitas outras) normalmente associadas à poupança de água, típicas das plantas mais
xerofíticas. No caso das espécies de regeneração por semente tudo se passa de modo a
permitir que durante o seu relativamente curto ciclo de vida as plantas consigam crescer
e produzir sementes, o seu único meio de assegurar a continuidade da espécie. Deste
modo o investimento faz-se preferencialmente na parte aérea em detrimento do
desenvolvimento radical, dando normalmente origem a relações raíz-parte aérea mais
baixas (Kummerow, 1981). Dado apenas poderem aceder a camadas de solo sujeitas a
uma intensa dessecação durante os meses de Verão, estas plantas necessitam de
adaptações estruturais de defesa contra a secura no sentido de evitar ao máximo as
percas de água de forma a manter o seu equilíbrio hídrico. A tipificação de sistemas
radicais que foi referida para os dois grandes grupos funcionais em que se podem incluir
as plantas mediterrânicas, tem no entanto inúmeras variantes. Estas variantes têm a ver
não só com as características próprias de espécies “menos típicas” mas bastante com a
influência dos factores ambientais, nomeadamente do solo (Fitter, 1996). A existência
de diferentes condições ambientais pode ser responsável por importantes diferenças no
6
7
sistema radical de plantas da mesma espécie (Kummerow, 1981, Canadell & Zedler,
1995). Deste modo o estudo comparativo dos sistemas radicais de espécies com
diferentes estratégias adaptativas apenas pode ser completamente conclusivo quando as
condições de solo, nomeadamente em termos de profundidade e distribuição de
horizontes, são semelhantes.
As características da distribuição das raízes das plantas individuais reflectem-se
directamente ao nível das comunidades de plantas. O estudo da distribuição das raízes
no solo de uma comunidade de plantas permite assim conhecer o potencial de absorção
para a água e para os nutrientes ao longo do perfil do solo e de certa forma enquadrar
dentro das estratégias referidas as espécies que a compõem. O conhecimento da
distribuição das raízes no solo reveste-se de uma importância fundamental sempre que
se pretendem representar através de modelos, os fluxos de água, carbono ou nutrientes
numa comunidade de plantas (Feddes et al., 2001). A este nível, quando não é possível
conhecer a distribuição vertical das raízes, é pelo menos fundamental o conhecimento
da profundidade máxima de enraizamento dado que tal permite avaliar a extensão do
perfil de solo no qual ocorrem os processos de absorção de água e nutrientes (Schenk &
Jackson, 2002b). Quando estudamos uma comunidade de plantas há ainda que ter em
conta o factor competição o qual pode ser responsável por importantes modificações ao
nível da distribuição das raízes no solo (Atkinson, 1978; Casper & Jackson, 1997;
Casper et al., no prelo).
1.3
O estudo das raízes das plantas mediterrânicas
Quase todos os autores são unânimes em reconhecer as dificuldades associadas
ao estudo das raízes no solo (e.g. Kummerow, 1981; Box, 1996; Atkinson, 2000).
Mesmo tendo em conta as inovações tecnológicas que podem ser utilizadas actualmente,
o estudo das raízes das plantas continua a ser um desafio muitas vezes recusado, dada a
baixíssima relação entre os resultados obtidos e o esforço investido. De acordo com
Jackson et al. (1996), os primeiros estudos relatados sobre raízes terão começado há
mais de 250 anos através das investigações levadas a cabo por S. Hales em 1727 com
plantas cultivadas. Desde cedo foram tentadas técnicas várias para observar as raízes
das plantas. Um dos primeiros relatos sobre a utilização de água sob pressão para a
escavação de raízes data de 1857 e a utilização de paneis de vidro para a observação do
crescimento radicular data de 1873. No entanto foi já no século XX que foram
estabelecidas metodologias consistentes para o estudo das raízes das plantas. A este
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8
respeito merecem referência os trabalhos pioneiros de alguns ecologistas notáveis do
início do século passado tais como J. Weaver e W. Cannon (Fitter, 1996; Guowei et al.,
1997). Dada a panóplia de técnicas e métodos entretanto especificamente desenvolvidos
para o estudo das raízes das plantas durante o século XX, alguns autores dedicaram-se a
reunir essa informação de forma sistematizada. Consultando alguma dessa bibliografia é
curioso verificar a evolução sofrida ao nível dos métodos para o estudo de raízes,
através dos trabalhos de Schuurman & Goedewaagen (1971), Böhm (1979), Caldwell &
Virginia (1989) e do recente trabalho editado por Smit et al. (2000). Essa evolução está
sobretudo relacionada com os avanços tecnológicos verificados entre cada uma das
publicações referidas. Estes avanços têm-se verificado em diferentes direcções no
sentido de facilitar a recolha de informações sobre a estrutura e o funcionamento das
raízes. De entre as diferentes inovações tecnológicas recentes podemos referir a título de
exemplo:
-
A utilização de técnicas até há pouco reservadas a outros campos da ciência
como a Tomgografia Assistida por Computador e a Ressonância Magnética
(Asseng et al., 2000) ou o uso de detecção através de radar (Butnor et al.,
2001).
-
O melhoramento e a generalização do uso de sistemas ópticos para
observação e registo de imagens destinadas a estudar o crescimento de raízes
através de mini-rizotrões e outros sistemas afins (Smit et al., 2000).
-
A utilização de radio-isótopos permitindo o estudo dos fluxos de água
nutrientes e dióxido de carbono ou mesmo da distribuição das raízes no solo
(Milchunas et al., 1992; Bingham et al., 2000, Casper et al., no prelo).
-
A utilização de técnicas de identificação de DNA (Linder et al., 2000). Esta
técnica permite associar as raízes observadas em cavernas ou outros locais
abaixo da superfície do solo às as respectivas plantas.
-
A utilização de técnicas de aquisição e tratamento de imagens digitais
incluindo
o
desenvolvimento
de
novas
ferramentas
informáticas
especificamente direccionadas para o estudo de raízes (Richner et al., 2000).
-
O desenvolvimento de novos sistemas possibilitando a escavação de raízes in
situ, como o Air Spade® (Concept Engineering Group, Inc. Verona, E.U.A.)
ou o registo tridimensional da sua arquitectura como o Fastrak® (Polhemus
Inc. Colchester), (Danjon et al., 1998).
8
9
-
De referir ainda de um modo geral as enormes capacidades computacionais
existentes hoje em dia quando comparadas por exemplo com aquelas
existentes na altura da publicação do clássico (ainda hoje seguido) trabalho
sobre métodos de estudo dos sistemas radicais por W. Böhm em 1979.
No entanto apesar de todas as inovações tecnológicas referidas, uma grande
parte dos estudos de raízes de plantas desenvolvidas em condições naturais continua, e
continuará (veja-se o presente trabalho por exemplo) provavelmente durante muito
tempo, a ser realizada com base em métodos que na sua essência pouco diferem dos
métodos clássicos utilizados desde há mais de cem anos. Talvez por esse motivo é
bastante elevado o número de trabalhos de investigação utilizando plantas
desenvolvidas em condições controladas, dada a maior facilidade do estudo das suas
raízes. No entanto este tipo de trabalhos tem importantes limitações, quer ao nível da
dificuldade em reproduzir as condições naturais, quer em relação à possibilidade de
estudar plantas lenhosas adultas. Por outro lado são conhecidas as dificuldades do
estudo de raízes em condições naturais em particular quando é necessário estudar
plantas com sistemas radicais profundos. Tais limitações fazem com que não sejam
abundantes, em termos relativos, os exemplos de estudos sobre as raízes de plantas
lenhosas adultas. Devido a todas estas limitações, a esmagadora maioria dos trabalhos
diz respeito a espécies com interesse agrícola devido à sua maior importância
económica, e uma boa parte da metodologia para o estudo de raízes foi desenvolvida
com este tipo de plantas.
No caso concreto dos estudos de raízes realizados em regiões com características
mediterrânicas, é normal contar com dificuldades acrescidas. Entre essas dificuldades
contam-se as características de uma boa parte dos solos destas regiões, frequentemente
pouco profundos e com elevada pedregosidade. Por outro lado as características das
próprias plantas e das comunidades que constituem são igualmente pouco favoráveis,
nomeadamente no caso de espécies com raízes profundas e no caso de formações de
matagal denso tipo maquis onde é difícil separar as raízes de diferentes indivíduos ou
mesmo de diferentes espécies. Estes são alguns dos motivos apontados por Kummerow
(1981) para justificar a escassez de estudos destinados ao conhecimento da estrutura dos
sistemas radicais das espécies que compõem os ecossistemas mediterrânicos. Se é
verdade que alguns trabalhos têm sido desenvolvidos noutras regiões com
características mediterrânicas, em particular na California, no que toca à Região
Mediterrânea têm sido muito poucos os estudos com plantas não cultivadas. Nas
9
10
compilações sobre trabalhos relativos à distribuição das raízes no solo constantes em
Canadell et al. (1996), Jackson et al. (1996), Schenk & Jackson (2002a) e Schenk &
Jackson (2002b) é notável a escassez de trabalhos relativos aos países da Região
Mediterrânea. Restringindo-nos em particular à Peninsula Ibérica, as espécies Quercus
ilex (Canadell & Rodà, 1991; Djema, 1995) e Quercus coccifera (Kummerow et al.,
1990; Cañellas & Ayanz, 2000) têm merecido especial atenção. Vale também a pena
mencionar os trabalhos de Martinez & Rodriguez (1988) e Martinez et al. (1998) em
comunidades arbustivas do Sul de Espanha.
O conhecimento sobre as características estruturais das raízes das comunidades
arbustivas mediterrânicas em Portugal e sobre as espécies que as constituem é ainda
mais escasso na medida em que deverão ser, tanto quanto sabemos, praticamente
inexistentes os estudos a este respeito. Em linguagem comum podemos dizer que
conhecemos razoavelmente o que está à vista mas desconhecemos quase completamente
o que está escondido abaixo da superfície do solo. Se bem que contemplando outros
aspectos e outro tipo de espécies, devemos no entanto referir alguns trabalhos pioneiros
sobre raízes realizados no nosso país. É esse o caso dos trabalhos realizados por A.
Fabião (e.g. Fabião et al., 1985; Fabião et al., 1987; Fabião et al., 1991) sobre
Eucalyptus globulus e ainda o trabalho realizado por M. Tavares (Tavares, 1989) sobre
Pinus pinaster. Porventura outros trabalhos existirão mas apesar dos nossos esforços,
deles não tivemos conhecimento. Já no que toca ao estudo dos sistemas radicais das
plantas agrícolas, o número de trabalhos realizados em Portugal é bastante superior
podendo servir de exemplo os estudos realizados por C.A. Portas e M.C. Oliveira (e.g.
Portas, 1973; Portas & Taylor, 1976; Oliveira & Portas, 1987), e ainda por C.A.
Pacheco (Pacheco, 1989; Rodrigues et al., 1995).
1.4
Os efeitos do fogo na dinâmica da água do solo
Os efeitos do fogo nos ecossistemas mediterrânicos são estudados desde há
bastante tempo e em múltiplas vertentes. Dado o acumular de conhecimentos nesta área,
o estudo dos efeitos do fogo transformou-se numa espécie de sub-disciplina dentro do
âmbito mais alargado da investigação sobre incêndios florestais. É normal dividir as
questões ligadas aos efeitos do fogo em: efeitos na vegetação, efeitos na fauna e efeitos
no solo. Dada a crescente importância das questões ligadas às previsões de aquecimento
do planeta devido às emissões de CO2, o estudo dos efeitos dos incêndios na atmosfera
tem também vindo a ganhar um peso crescente. De entre as várias categorias de efeitos,
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11
o estudo dos efeitos na vegetação tem merecido especial atenção por parte dos
investigadores, tal como se pode por exemplo constatar pelo número de trabalhos
apresentados nas quatro edições da International Conference on Forest Fire Research.
No entanto para uma compreensão integrada dos mecanismos envolvidos na dinâmica
da vegetação após o fogo, é fundamental saber o que se passa abaixo da superfície do
solo. De entre os estudos sobre os efeitos do fogo no solo, muitos têm sido aqueles
dedicados às alterações verificadas ao nível dos nutrientes ou da erosão superficial mas
muito poucos têm sido os trabalhos publicados sobre as alterações verificadas na
dinâmica da água no solo. Tal lacuna no conhecimento da dinâmica dos ecossistemas
mediterrânicos e da chamada ecologia do fogo, poderá dever-se ao facto de só desde há
relativamente poucos anos estarem disponíveis meios técnicos economicamente
acessíveis, fiáveis e inócuos para permitir a monitorização da humidade do solo ao
longo do tempo e a diferentes profundidades. Este conhecimento é fundamental na
medida em que o teor de água no solo funciona como factor limitante relativamente ao
crescimento das plantas em clima mediterrânico. Deste modo podemos afirmar que todo
o processo de recuperação da vegetação após o fogo está estreitamente associado ao teor
de água no solo, quer enquanto causa quer enquanto consequência. Assim o
desaparecimento dos órgãos aéreos da vegetação devido ao fogo tem como efeito
imediato uma eliminação temporária da transpiração através das folhas e,
consequentemente, uma redução drástica na absorção de água pelas raízes. No entanto o
conjunto de mecanismos que se verificam após a ocorrência de um incêndio é bem mais
complexo na medida em que a evaporação à superfície do solo aumenta devido ao
desaparecimento do coberto vegetal (Pyne et al., 1996; Zwolinsky, 2000). Por outro
lado a infiltração no solo, da água proveniente da precipitação, pode sofrer uma
diminuição associada a um aumento do escoamento superficial. Estes fenómenos
poderão ser devidos à eliminação do coberto vegetal e ainda à frequentemente relatada
formação no solo de uma camada hidrófoba em incêndios de grande intensidade
(DeBano, 1966; Ferreira, 1990; Midoun et al., 1998; DeBano, 2000). Finalmente há
ainda que ter em conta a diminuição da intercepção da precipitação pelas copas o que
faz com que a quantidade de água que chega à superfície do solo seja maior. O peso
relativo de cada um destes mecanismos depende de vários factores, nomeadamente: da
intensidade do fogo, do tipo de vegetação, dos factores meteorológicos, das
características do solo e da topografia local.
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12
Para além de escassa, a bibliografia existente relatando o efeito do fogo no teor
de água no solo é contraditória. Na origem dos diferentes resultados obtidos estão
diferenças ao nível dos métodos aplicados mas também diferenças em termos das
condições estudadas. Uma boa parte dos estudos existentes neste domínio, como em
muitos outros relacionados com a ecologia do fogo, foram realizados pelos Serviços
Florestais dos Estados Unidos, em povoamentos florestais. Alguns dos trabalhos
publicados relatam uma diminuição do teor de água no solo após o fogo quando
comparado com o de parcelas testemunha. É esse o caso do estudo relatado por
Campbell et al. (1977) num povoamento de Pinus ponderosa e também o caso de
alguns dos estudos relatados na revisão feita por Wells et al. (1979). Resultados opostos
foram relatados por Klock & Helvey (1976) numa experiência levada a cabo num
povoamento misto de resinosas e por Soto & Diaz-Fierros (1997) num matagal
dominado por Ulex europaeus. Também em Portugal, Rego & Botelho (1992) chegaram
a resultados semelhantes ao verificar a existência de teores ligeiramente mais elevados
de humidade no solo durante o Verão após a realização de um fogo controlado num
povoamento jovem de Pinus pinaster. Grande parte dos trabalhos constituem apenas
uma abordagem parcial do problema, quer por não fazerem o acompanhamento da
situação durante um período suficientemente alargado quer, mais frequentemente, por
não efectuarem o estudo ao longo de todo o perfil explorado pelas raízes. Deste modo
para uma abordagem completa dos fenómenos envolvidos é importante ter em conta as
variações da água no solo quer em termos temporais quer em termos espaciais. Este
segundo aspecto deverá ser analisado em paralelo com a distribuição das raízes no solo
de forma a poder ser avaliado o peso dos mecanismos de absorção de água pelas plantas
no balanço de percas e ganhos.
1.5
A modelação da dinâmica da água no solo
O estudo dos ecossistemas passa cada vez mais pela criação e utilização de
modelos matemáticos de simulação dos diferentes processos associados ao
funcionamento das comunidades vegetais e animais. Tal deve-se, entre outros aspectos,
a uma crescente facilidade associada à criação de modelos e à cada vez maior
necessidade de avaliar o impacto das actividades humanas nos processos naturais. Em
relação ao primeiro aspecto tem sido vertiginosa a evolução verificada ao nível do
desempenho quer dos computadores quer dos programas informáticos. No tocante a este
último aspecto importa referir o aparecimento desde há alguns anos, de programas
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interactivos destinados a facilitar a tarefa da construção de um modelo. Tratam-se de
programas gráficos de modelação que permitem ao utilizador a construção intuitiva de
modelos através da simples utilização de ícones gráficos. Estes ícones podem ser
arrastados num diagrama e interligados de forma a representar por exemplo, fluxos
entre compartimentos e relações entre variáveis. Tal permite reduzir bastante a
morosidade do trabalho de modelação relativamente ao que acontecia anteriormente
devido à necessidade de utilização de linguagens de programação. Exemplos deste tipo
de ferramentas de modelação são os programas STELLA® (High Performance Systems
Inc., Hanover, E.U.A.), SIMILE (Simulistics Ltd., Edinburgh, R.U.), SIMULINK® (The
MathWorks, Inc., Natick, E.U.A) ou ainda DYMEX (CSIRO Publishing). Pormenores
sobre os dois primeiros podem ser encontrados respectivamente em Hannon & Ruth
(2001) e Muetzelfeldt & Taylor (2001). Relativamente ao segundo aspecto é de salientar
a importância das alterações climáticas globais devido ao chamado “efeito de estufa”.
Este tipo de alterações globais atribuídas ao aumento do teor de CO2 na atmosfera tem
sido um dos principais incentivos à criação de modelos de circulação global (GCM –
Global Circulation Models) os quais por sua vez são utilizados em modelos de
simulação do funcionamento dos ecossistemas, de forma a prever alterações futuras na
vegetação e restantes organismos. Para além deste, existem muitos outros efeitos das
actividades humanas nos ecossistemas que têm sido estudados através de modelos tais
como o impacto da poluição nos solos e no crescimento das plantas ou o impacto dos
incêndios florestais. No entanto é importante referir que a utilidade da criação de
modelos ultrapassa bastante a possibilidade de previsão de novos cenários e situações
(Ford, 1999). Na verdade a utilização de modelos no estudo dos ecossistemas tem
sobretudo a grande virtualidade de permitir uma melhor compreensão dos fenómenos
associados ao funcionamento desses mesmos ecossistemas. Esta compreensão é
frequentemente necessária a diferentes escalas quer temporais quer espaciais, pelo que a
criação de modelos tem muitas vezes em conta essa necessidade. Um exemplo
largamente difundido de um modelo de dinâmica de ecossistemas delineado para
funcionar a diferentes escalas no tempo e no espaço é o modelo FOREST-BGC
(Running & Cougham, 1988; Running & Gower, 1991). Trata-se de um modelo geral
de funcionamento dos ecossistemas florestais baseado nos três ciclos biogeoquímicos
básicos associados ao desenvolvimento das plantas: o ciclo do carbono, o ciclo dos
nutrientes e o ciclo da água. Este último ciclo tem uma importância fundamental a nível
de todos os ecossistemas terrestres e em particular nos ecossistemas mediterrânicos, já
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que a disponibilidade de água no solo é um factor limitante relativamente ao
crescimento das plantas em clima mediterrânico (Daget, 1977). O modelo de
crescimento GOTILWA - Growth of Trees is Limited by Water (Gracia et al., 1999) é
um exemplo da importância atribuída ao ciclo da água no funcionamento dos
ecossistemas mediterrânicos dado ter sido desenvolvido e validado em particular para
este tipo de condições. Dada a importância da água para as plantas, para além dos submodelos incorporados em modelos mais abrangentes como os dois exemplos referidos,
existe uma profusão de modelos estritamente destinados à simulação da dinâmica da
água no solo e nas interfaces solo-planta-atmosfera. Para além de todos os modelos
desenvolvidos especificamente para culturas agrícolas, existem ainda alguns modelos
particularmente vocacionados para a simulação da dinâmica da água nos ecossistemas
florestais. De um modo geral o solo é encarado como um compartimento sujeito a
entradas e saídas de água. Nos modelos mais desenvolvidos este compartimento pode
ser dividido em sub-compartimentos homogéneos (horizontes ou simplesmente camadas
de solo) em que as entradas e saídas de água afectam e são afectadas pelos subcompartimentos vizinhos. A partir desta estrutura geral, diferentes soluções têm sido
encontradas para a representação dos diferentes fluxos de água nas interfaces soloplanta-atmosfera. Tal implica uma selecção criteriosa das variáveis com maior
influência no processo a simular e das respectivas relações, sendo este sem dúvida o
aspecto mais crítico de qualquer trabalho de modelação de sistemas naturais (Jones,
1992).
A simulação da dinâmica da água no solo implica a resolução de diferentes
questões relacionadas por um lado, com os processos de evapotranspiração e por outro
com os fluxos de água no solo. Para além destes, outros aspectos podem ou não ser
tidos em conta tais como a intercepção da precipitação pelas copas e pela folhada a
avaliação do escorrimento superficial, ou a libertação gradual de água pelo manto de
neve no caso de climas onde tal ocorre. Existem ainda mecanismos que, tanto quanto
sabemos, nunca foram contabilizados neste tipo de simulações devido à escassez de
dados a este nível. É esse o caso, por exemplo, dos mecanismos de absorção e posterior
libertação de água pelas raízes, permitindo o transporte de água entre diferentes
profundidades no solo (Caldwell et al., 1991; Burgess et al., 1998).
No tocante à evapotranspiração esta pode ser calculada de diferentes formas,
sendo a mais generalizada a equação de Penman-Monteith (Monteith, 1965; Tiktak &
Bouten, 1992; Heidmann et al., 2000; Williams et al, 2001). Outros autores optam por
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soluções mais simples como a equação de Makkink (Makkink, 1957; Tiktak & Bouten,
1994) ou a equação de Priestley-Taylor (Priestley & Taylor, 1972; Krysanova et al.,
1998). A componente transpiração pode ser calculada como uma função de MichaelisMenten relativamente à radiação fotossintéticamente activa (e.g. Gracia et al., 1999).
No tocante aos processos de evaporação da água do solo e de superfícies húmidas é
frequentemente utilizada a aproximação proposta por Ritchie (1972) para culturas
agrícolas, a qual se baseia numa relação empírica entre a transpiração potencial e o
índice de área foliar (e.g. Paruelo e Sala, 1995; Krysanova et al., 1998). Para a
simulação dos fluxos de água no solo é necessário determinar as propriedades
hidráulicas do solo. Trata-se aqui fundamentalmente de determinar as curvas de
retenção de humidade e a condutividade hidráulica não saturada em função do teor de
humidade para cada horizonte ou tipo de solo (Hillel, 1998; Porta et al., 1999). Com
este objectivo diversos autores desenvolveram relações empíricas baseadas na textura
do solo e em alguns casos também no teor de matéria orgânica (Mualem, 1976; Gupta
& Larson, 1979; Van Genuchten, 1980; Saxton et al., 1986; Vereecken et al., 1989). A
absorção de água pelas plantas é uma componente com uma abordagem normalmente
simplificada dada a frequente inexistência de dados sobre a distribuição das raízes no
solo. Deste modo alguns autores optam por utilizar simplesmente uma densidade
homogénea (Feddes et al., 1978), outros representam o decréscimo da densidade de
raízes ao longo do perfil através de uma função linear (Heidmann et al., 2000), de uma
função potência (Monteith et al., 1989), ou ainda de uma função exponencial (Williams
et al., 2001). Outros autores utilizam valores específicos de densidade relativa de raízes
para cada camada de solo considerada (e.g. Tiktak & Bouten, 1992; Sala & Paruelo,
1995). O fluxo de água entre camadas de solo é calculado para condições de saturação
através da lei de Darcy (e.g. Gracia et al., 1999) e para o solo não saturado através da
equação de Richards (Feddes e Koopmans, 1995; Tiktak e Bouten, 1992). Dada a
profusão de modelos que foram sendo elaborados ao longo dos anos, podem também ser
encontradas revisões comparativas incluindo diferentes modelos (e.g. Feddes et al.,
1988; Tiktak & Grinsven, 1995).
No entanto, apesar de toda a actividade de modelação desenvolvida, trata-se de
um esforço direccionado sobretudo para servir objectivos relacionados com a produção
agrícola ou florestal. Tanto quanto sabemos nenhum dos modelos descritos na literatura
disponível foi delineado ou validado com dados obtidos a partir de matagais
mediterrânicos. Deste modo o desenvolvimento de modelos com esta vocação poderá
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constituir-se como uma mais-valia, nomeadamente tendo em conta a milenar relação
entre este tipo de ecossistemas e os factores de perturbação de natureza antrópica como
o fogo, o corte e o pastoreio.
1.6
Justificação, objectivos e estrutura da presente tese
Todos os trabalhos de investigação desenvolvidos no âmbito da presente tese
tiveram como origem a participação portuguesa no projecto ModMED III-Modelling
Vegetation Dynamics in Mediterranean Ecosystems (contrato ENV4-CT97-0680),
através da Estação Florestal Nacional (EFN). Este projecto Europeu (DG XII) foi
coordenado pelo Professor Stefano Mazzoleni da Universidade de Nápoles e teve o seu
funcionamento entre Janeiro de 1998 e Março de 2001, dando sequência aos projectos
ModMED I (1995-1996) e ModMED II (1996-1997). As outras instituições
participantes através de contrato directo foram as Universidades de Edimburgo, de
Atenas e de Pisa, sendo a participação portuguesa realizada em associação com a
Universidade de Edimburgo e coordenada pelo Professor Francisco de Castro Rego. Em
termos gerais, os projectos ModMED tiveram como objectivos o estudo dos
ecossistemas mediterrânicos a diferentes escalas (a paisagem, a comunidade de plantas e
o indivíduo) e a modelação do seu funcionamento através da utilização de ferramentas
de modelação desenvolvidas no âmbito do próprio projecto. A este nível foi dada
particular ênfase ao efeito das perturbações (fogo, pastoreio, corte) nos ecossistemas,
dada a importância deste tipo de mecanismos na Região Mediterrânea. Os projectos
ModMED I e II permitiram identificar a existência de lacunas importantes de
conhecimento ao nível do funcionamento dos ecossistemas, em particular naquilo que
se refere aos fenómenos que ocorrem abaixo da superfície do solo. Deste modo um dos
grandes desígnios do projecto ModMED III foi o de tentar colmatar algumas dessas
lacunas através do estudo de aspectos aparentemente tão elementares como a
distribuição das raízes no solo, as características estruturais das raízes das diferentes
espécies ou a dinâmica da água no solo. Os temas e a estrutura da presente tese surgem
assim como uma consequência directa da tentativa de responder aos desafios colocados
a este projecto de investigação. Dado o enorme vazio de conhecimento sobre a estrutura
e o funcionamento das raízes dos ecossistemas mediterrânicos, foi necessário
estabelecer prioridades e deixar de lado muitos aspectos de inegável interesse e
importância. Essas prioridades passaram pela identificação dos factores cuja
importância se poderia vir a tornar fundamental para o desenvolvimento de modelos de
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simulação de funcionamento dos ecossistemas, tendo em conta as diferentes escalas a
abordar. Os trabalhos de investigação foram assim focados em dois aspectos distintos se
bem que complementares: as características estruturais das raízes e a dinâmica da água
no solo. Em relação ao primeiro aspecto foi decidido trabalhar à escala da comunidade e
à escala da planta individual. Em particular foram tidos em conta os aspectos relativos à
distribuição vertical das raízes no solo e à identificação de características que
permitissem relacionar as diferentes espécies com as respectivas estratégias em termos
ecológicos. Dado o enorme esforço que sabíamos ser necessário investir na recolha e
preparação das plantas para a abordagem à escala individual, foi necessário optar entre
um estudo mais intensivo de uma ou duas espécies e um estudo mais exploratório
incluindo um leque mais alargado de espécies. Tendo em conta o carácter, tanto quanto
sabemos inédito, deste tipo de estudos em Portugal, optou-se pela segunda hipótese,
apesar dos riscos que acarretava em termos das dificuldades associadas ao tratamento
estatístico dos dados e à posterior obtenção de resultados conclusivos. Por outro lado foi
necessário alargar a amostragem para além da comunidade de plantas inicialmente
escolhida como objecto de estudo de forma a incluir-mos um leque mais alargado de
espécies. Neste leque de espécies apenas foram incluídas espécies lenhosas dado as
espécies herbáceas estarem quase ausentes ou terem uma importância funcional
reduzida nos matagais mediterrânicos. De forma a rentabilizar o esforço investido, as
mesmas plantas foram utilizadas para dois estudos distintos, um dedicado à tipificação
das principais características estruturais das respectivas raízes e um outro dedicado a
estudar a distribuição vertical das raízes no solo. Ao nível da comunidade foi
preocupação fundamental a obtenção de dados também sobre a distribuição vertical das
raízes de forma a apoiar os estudos de água no solo. A este respeito foi igualmente tida
em conta a profundidade máxima de enraizamento da comunidade estudada dada a
importância deste parâmetro na avaliação das possibilidades de extracção de água das
camadas mais profundas do solo. Em termos do estudo das raízes foi necessário deixar
de fora aspectos fundamentais que mereceriam sem dúvida ter sido estudados tais como
a dinâmica das raízes no solo, a influência dos factores ambientais na diferenciação dos
sistemas radicais ou as relações hídricas das plantas. As razões para não o termos feito
prenderam-se com óbvias limitações materiais e de tempo.
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Fig. 1.1 Aspecto geral do matagal de urze (Erica scoparia e Erica lusitanica) na Tapada Nacional de
Mafra, onde decorreram os trabalhos relatados nos capítulos 4, 5 e 6 e onde foram escavadas algumas das
plantas estudadas nos capítulos 2 e 3.
Em relação aos aspectos ligados à dinâmica da água no solo, foram tidas
sobretudo em conta as necessidades associadas ao desenvolvimento de um modelo de
simulação integrando informações climáticas, pedológicas, e de caracterização da
comunidade de plantas. A este respeito pareceu-nos óbvia a inclusão do factor fogo
enquanto variável a estudar, dada a sua importância neste tipo de ecossistemas. A
escolha da Tapada Nacional de Mafra (Fig. 1.1) para a realização dos estudos, teve
como origem razões de natureza institucional (a ligação da EFN à Tapada Nacional de
Mafra), razões de natureza prática (zona protegida com apoios ao nível de infraestruturas e equipamento) e ainda razões de natureza científica (comunidades arbustivas
mediterrânicas do tipo matagal ou maquis). Tendo em conta a linha geral de
investigação traçada em função dos objectivos do projecto europeu a que já fizemos
referência, os objectivos da presente tese foram os seguintes:
-
Contribuir para um melhor conhecimento dos sistemas radicais das plantas
lenhosas mediterrânicas, nomeadamente no que se refere: ao relacionamento
entre diferentes parâmetros caracterizadores das raízes, às alterações sofridas
por esses parâmetros ao longo de diferentes estádios de desenvolvimento e à
relação entre esses parâmetros e as estratégias regenerativas das plantas
estudadas.
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-
Caracterizar a distribuição vertical de uma série de plantas lenhosas
mediterrânicas utilizando um modelo inédito e desenvolvido com esse
objectivo. Em particular pretendeu-se: comparar o desempenho do modelo
proposto com outros modelos existentes e utilizar esse modelo para
descrever e interpretar a distribuição vertical das raízes de diferentes plantas
lenhosas mediterrânicas.
-
Caracterizar a distribuição vertical das raízes da comunidade arbustiva
estudada nomeadamente no que diz respeito: às diferentes espécies, às
diferentes classes de diâmetro, à profundidade máxima de enraizamento e à
biomassa e comprimento total das raízes finas.
-
Determinar o efeito de curto prazo de um fogo experimental na dinâmica da
água do solo a diferentes profundidades, na comunidade arbustiva.
-
Apresentar e testar através de duas séries de dados reais, um novo modelo de
simulação da dinâmica da água no solo, assim como interpretar os resultados
obtidos no sentido de conhecer melhor os mecanismos de funcionamento do
ecossistema estudado.
Os cinco capítulos base que compõem a tese (para além do presente capítulo
introdutório e de um capítulo de conclusões) foram redigidos em Inglês, ou seja na
língua original em que foram submetidos para publicação. A referência a cada uma das
publicações encontra-se incluída numa nota de rodapé na primeira página de cada
capítulo. As razões que nos levaram a optar por esta modalidade tiveram a ver com dois
aspectos. Por um lado, o facto de a Língua Inglesa ser cada vez mais a forma universal
de expressão nos meios científicos, possibilitando assim uma maior garantia de
divulgação do trabalho realizado. O outro aspecto prendeu-se com a possibilidade de
poder contar com uma revisão adicional dos diferentes capítulos por especialistas
ligados às revistas ou comissões cientificas às quais os trabalhos foram submetidos. Tal
possibilidade constitui à partida um potencial contributo para aumentar a qualidade do
trabalho apresentado, enquanto tese de doutoramento.
Deste modo, à parte pequenas correcções introduzidas posteriormente, o
conteúdo de cada capítulo reflecte no seu essencial o conteúdo dos trabalhos submetidos
e publicados. O preço a pagar por esta fidelidade ao trabalho original traduz-se
sobretudo na constatação de pequenas incoerências e na repetição de aspectos
metodológicos, quando se comparam os diferentes capítulos entre si. Algumas
incoerências devem-se sobretudo ao facto de cada capítulo ter incluído, à data a que foi
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submetido ou revisto (pela ordem apresentada nesta tese), novos elementos ou soluções
que não estavam ainda presentes nos capítulos anteriores. Tal é o caso do presente
capítulo de introdução, o qual inclui uma revisão bibliográfica mais actualizada e em
alguns casos mais aprofundada que nos capítulos submetidos a publicação e terminados
há bastante mais tempo. No tocante ao capítulo final trata-se fundamentalmente de uma
tradução para Português da secção Discussion dos capítulos submetidos a publicação.
Não podemos aqui deixar de referir as dificuldades enfrentadas para conseguir uma
tradução correcta para Português, nos capítulos inicial e final desta tese, de alguma
terminologia utilizada nos capítulos publicados em Inglês e pouco utilizada fora dos
meios científicos.
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2 BELOWGROUND TRAITS OF MEDITERRANEAN WOODY
PLANTS IN A PORTUGUESE SHRUBLAND1
Abstract: Belowground traits vary widely. Apart from the influence of the environment
both genetic and ontogenic factors are responsible for this variation. For mediterranean
woody plants there is also evidence of a relationship between regenerative strategies and
root system characteristics. With the general aim of studying these different aspects, the
root systems of 17 obligate seeders and 16 resprouters from 10 different species and
different developmental stages were excavated at Tapada Nacional de Mafra in Central
West Portugal. Root systems were photographed, weighted and measured. Root length
and the average root diameter were determined using digital image software. Root-toshoot ratio (R/S) and the specific root length (SRL) were computed for all plants. Basal
section was used as an indicator of plant development. A principal component analysis
(PCA) was performed in order to study the relationships between variables and between
plants. The analysis showed a clear distinction of plants according to the respective
developmental stage but also according to the regenerative characteristics of the
different species. Allometric relationships were found between root biomass, shoot
biomass and basal section. Statistical tests showed that resprouters had higher maximum
rooting depth, average root diameter and R/S and lower SRL, than obligate seeders. A
decrease of R/S and SRL with basal section was verified for a sub-sample of four
species.
Key words: Root development, mediterranean shrublands, regenerative strategies, root
systems, allometric relationships.
1 Based on paper: Silva J.S., Rego F.C. & Martins-Loução M.A. (2002). Belowground traits of mediterranean woody
plants in a portuguese shrubland. Ecologia Mediterranea 28: 5-13.
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Introduction
The origins of the diversity of root systems can be seen as an optimisation of two
primary functions: acquisition of soil-based resources (water and nutrients) and
anchorage (Fitter, 1996). In the specific case of the Mediterranean regions of the world,
root systems have probably evolved to deal with the strong spatial and temporal
limitations on availability of water, which are typical of these regions (Canadell &
Zedler, 1995). This evolution has resulted in various root type morphologies,
characteristic of mediterranean woody species. Several attempts were made to classify
root systems in terms of basic structural characteristics (Cannon, 1949; Hellmers et al.,
1955; Specht & Rayson, 1957). However the well known plasticity of root systems as a
result of environmental conditions, has limited the use of these classifications (Fitter,
1996). Bengough et al. (2000) suggested the study of variability as an alternative to
seeking for homogeneous features. A simple classification of plants into deep rooted
and shallow rooted is generally accepted, although no strict limits are normally
established to define the two types. These two basic types of root systems correspond to
different adaptations to the highly seasonal water availability typical of Mediterraneantype climates and have been associated with the strategy to regenerate after natural
disturbances (fire and grazing). Typical resprouters normally present deep root systems
whereas seeders are shallow rooted (Keeley, 1986; Correia & Catarino, 1994; Bell,
2001). In fact, resprouters need to have deep root systems to supply the growth of new
shoots since they can not rely on a seed bank to regenerate after fire or other kind of
disturbance (Keeley & Zedler, 1978; Clemente et al., 1996). Although sharing the same
climatic conditions as resprouters, obligate seeders present specific water saving
adaptations such as a higher stomatal control or leaf hairs, allowing these species to
survive in drier conditions (Keeley, 1986; Correia, 1988; Correia & Catarino; 1994;
Silva & Rego, 1998). These water saving mechanisms partly explain why obligate
seeders withstand summer drought without the use of deep root systems.
The study of root systems have also showed the existence of different patterns of
root development. In the case of many mediterranean plants it is known the preferential
allocation of resources to roots at early stages (Canadell & Zedler, 1995) and there is
evidence that woody plants in general present a decreasing trend of root-to-shoot ratio
with age (Kozlowski et al., 1991). The fact that many species, especially those under
dry conditions, may develop deep tap roots at early stages preceding the development of
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lateral roots (Spurr & Barnes, 1980) is an evidence of the specificity of rooting patterns
at different developmental stages. Ontogeny seems then to be at least as important as
phylogeny to the overall variation of root systems and the respective traits.
It is an obvious fact that root systems are difficult to study. These difficulties of
root studies increase in the case of plants from mediterranean ecosystems because soils
are frequently shallow and heterogeneous and also because many species are growing
deep root systems (Kummerow, 1981). Additional problems are found with plants from
dense shrub communities because different individuals form an intricate root net which
makes it extremely difficult to trace individual root systems. Consequently there is a
considerable lack of knowledge of basic root system characteristics of mediterranean
woody plants, and no information at all could be found concerning the belowground
traits of the species studied in the present work. The relative scarcity of root studies in
mediterranean ecosystems is well reflected in the planetary compilation of root
distribution data by Jackson et al. (1996) where the Mediterranean Region is
represented by only 4 studies out of 250. However it is generally recognised the
importance of obtaining information on root systems for modelling the functions of
ecosystems both at the plant as at the community level (Caldwell & Richards, 1986;
Pagès, 2000) or even in global scale simulation models (Zeng, 2001).
The general objective of this paper is to assess the existence of relationships
concerning the belowground traits of mediterranean woody plants. In particular the
present paper is focused on: a) the relationships between different belowground traits, b)
the relationships between plant development and belowground traits, c) the relationships
between regenerative strategies and belowground traits.
Methods
Plants were collected at Tapada Nacional de Mafra, a public estate located in the
Central West region of Portugal. Tapada Nacional de Mafra, is a protected area with
827 ha, about 30 km Northwest of Lisbon and 12 km East from the coast (38º 56’ 37’’
to 38º 58’ 30’’ N and 9º 15’ 52’’ to 9º 18’ 43’’ W). The lowest altitude is 90 m and the
highest is 358 m. Soil is a sandy loam classified as a humic cambisol (FAO
classification) derived from sandstone. Bedrock is normally located below 2 meters.
Mean annual precipitation is 798 mm and mean annual temperature is 14.6 ºC. Summer
precipitation (June, July, August) accounts for only 3.1 % of the total annual rainfall.
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Most of the area is constituted by shrublands dominated by Erica scoparia L. and Erica
lusitanica Rudolphi.
Between September 2000 and April 2001 the complete root systems of 33 plants
from 10 woody species were hydraulically excavated (Böhm, 1979). Although we have
tried to include a wide variety of woody species, our choice was limited by the floristic
composition of the study area. Within these limits plants were chosen according to their
developmental stage and regenerative characteristics. From the ensemble of plants, 17
were obligate seeders (Lavandula luisieri (Rozeira) Rivas Martinez (4 plants), Cistus
crispus L. (9 plants) and Cistus salvifolius L. (4 plants)) and 16 were resprouters (Erica
scoparia L. (2 plants), Erica lusitanica Rudolphi (1 plant), Crataegus monogyna Jacq.
(4 plants), Ulex jussiaei Webb (3 plants), Daphne gnidium L. (4 plants), Pistacia
lentiscus L. (1 plant) and Myrtus communis L. (1 plant)). In order to obtain 4 individuals
representative of 4 classes of basal section, 2 obligate seeders (L. luisieri and C. crispus)
and 2 resprouters (D. gnidium and C. monogyna) were sampled more intensively,
constituting a pooled sub-sample of 16 plants. These 4 species apparently represented
different root system types, within the obligate seeder and resprouter strategies. Basal
section was used as an indicator of the plants developmental stage. The 4 classes of
basal section were defined as: class 1 for plants up to 5 mm2, class 2 from 5 to 25 mm2,
class 3 from 25 to 125 mm2 and class 4 for plants showing a basal section higher than
125 mm2. Despite having sampled nine C. crispus plants, no plants were collected at
class 4, given the small size of the individuals present at the excavation site. No
replications could be obtained for each combination species/basal section class due to
the enormous amount of work required for the excavation and processing of complete
root systems. All plants were excavated in spots where soil depth did not seem to limit
the vertical development of roots, thus allowing the full expression of potential growth
of deep roots. Besides having observed the plants used in this study, we were able to
observe in the field other partially excavated individuals from the same species. This
allowed to recognise some basic morphological characteristics, enabling a more
complete description of root systems.
After excavation, the maximum rooting depth, the maximum average root width
and the basal section of each plant were measured. Maximum rooting depth represents
the depth achieved by the deepest root, maximum average root width was computed as
the average between the maximum horizontal width and the respective orthogonal width
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and basal section was obtained as the cross sectional area at the stem base. In the case of
plants with several stems, basal section was obtained by summing all the stem sections.
In order to obtain the total root length and the average root diameter, root
systems were photographed using a Fujifilm MX 2900 Zoom (Fuji Photo Film Co.,
Ltd., Tokyo) digital camera, featuring a maximum resolution of 2.3 millions of pixels.
Digital images were analysed using software WinRhizo 4.1b (Regent Instruments,
Quebéc). Some remarks have to be made on the determination of root length. Root
length is difficult to measure when dealing with extensive root systems. Since most of
the root length is associated with fine roots, it is extremely difficult to have an accurate
estimate of total root length from shrubs or trees collected in the field. The main source
of errors is the excavation process (Böhm, 1979, Caldwell & Virginia, 1989), where
considerable amounts of fine roots are inevitably lost. Therefore root length was
determined for comparison purposes only and it should be strictly interpreted on a
relative basis and not as absolute values.
For biomass determination plants were oven-dried at 85 ºC for 48 hours and
weighted, separately for root and shoot fractions. In addition to these variables the
specific root length (SRL; cm of total root length/g of root dry weight) and the root-toshoot ratio (R/S; root dry weight/shoot dry weight) were computed for each plant.
All root variables (including R/S ratio) were log transformed and used to
perform a principal components analysis (PCA) for all plants. The principal components
(PC’s) extracted by the analysis were related to the different individual plants collected,
in order to evaluate which were the main variables responsible for the variation found
and their relationship with species strategies and plant development. Allometric
relationships between variables were established considering the results obtained from
the PCA.
Given that most variables did not follow a normal distribution (Shapiro Wilk W
test), the Mann-Whitney U test was used to determine the significance of differences
between obligate seeders and resprouters, for all variables. Tests were performed both
with pooled samples of obligate seeders and resprouters and within developmental
stages 2 and 3 (not enough plants within stages 1 and 4).
The sub-sample of 16 plants referred above was used to assess the effect of the
developmental stage on R/S and SRL for the different species.
Species nomenclature followed Castroviejo (1999).
31
32
Results
All C. monogyna plants presented thick, structural roots, with a smooth pale
brownish bark. L. luisieri was characterised by a fibrous root system composed of an
intricate horizontal network of very thin pale roots. Despite having only collected young
U. jussiaei plants, our observation of partially excavated roots from adult individuals
revealed that this species presented deep, thick, poorly lignified tap roots, showing a
wrinkled white bark. C. salvifolius
and C. crispus plants showed very similar
characteristics. Roots of both species were relatively simple in terms of branching, with
few dark brown structural roots exploring surface soil layers. The two Erica species
were also very similar in terms of root system characteristics. Both presented a
lignotuber to which a few deep, black, strongly lignified, tap roots were connected. Both
species were also showing an intricate network of horizontal, not very widelly spreading
fine roots exploring surface soil layers. D. gnidium plants showed a rooting pattern
similar to the Erica plants with reddish, deep, tap roots and with only a few horizontal
roots. Root tissues were poorly lignified which made coarse roots soft and rubber-like,
similar to some succulent shrubs. All D. gnidium plants showed a swelling region,
similar to typical lignotubers, just below the stem base. M. communis was characterised
by the presence of coarse, pale brown laterally spreading roots, connected to a main
deep reaching root. Given the impossibility of observing more than one root system in
the field we did not retain the morphological characteristics of P. lentiscus.
A quantitative description of all plants grouped by species is presented in Table
2.1. Considering all excavated plants, root biomass ranged from 111.8 g (E. scoparia) to
0.2 g (C. crispus) and shoot biomass ranged from 141.8 g (E. scoparia) to 0.3 g (C.
crispus). Maximum rooting depth ranged from 185 cm (D. gnidium) to 12 cm (C.
crispus). Other species, E. lusitanica and E. scoparia, also showed deep roots (160 cm
and 140 cm, respectively). Root system width ranged from 95 cm (L. luisieri) to 5 cm
(C. monogyna). Total measured root length ranged from 2791.0 cm (L. luisieri) to 65.7
cm (C. monogyna). Another C. monogyna plant had the second highest length of roots
(1956.8 cm). The average root diameter ranged from 3.6 mm (C. monogyna) to 0.7 mm
(C. crispus). R/S ratio ranged from 3.2 (D. gnidium) to 0.2 (L. luisieri). The three
highest values of R/S ratio were from D. gnidium and the three lowest were from L.
luisieri. Only seven plants presented values of R/S higher than 1. SRL ranged from
848.4 cm.g-1 (C. crispus) to 15.6 cm.g-1 (E. scoparia). The six highest values of SRL
were from three C. crispus plants and three L. luisieri plants.
32
Table 2.1 Descriptive parameters (mean ± SE) of the root systems of 33 plants excavated at Tapada Nacional de Mafra, distributed by species. Legend for abbreviations: n –
number of plants; Reg. strat. – regenerative strategy; Maxim. root. depth - maximum rooting depth; Aver. root diam. – average root diameter; R/S – root-to-shoot ratio; SRL
– specific root length; s – obligate seeder; r – resprouter.
Species
n Reg. Basal section
strat.
(mm2)
Shoot biomass
Maxim. root.
Root system
Root length
Aver. root
Root biomass
R/S
SRL
(g)
depth (cm)
width (cm)
(cm)
diam. (mm)
(g)
(g.g-1)
(cm.g-1)
9
s
16.7 ± 3.6
2.6 ± 1.0
30.2 ± 5.0
19.1 ± 3.6
302.5 ± 66.1
1.0 ± 0.1
1.4 ± 0.4
0.7 ± 0.1
322.8 ± 88.7
C. salvifolius 4
s
17.0 ± 10.7
3.1 ± 0.9
26.5.0 ± 5.0
15.6 ± 2.2
165.2 ± 29.8
1.4 ± 0.2
1.9 ± 0.9
0.5 ± 0.2
162.6 ± 56.2
C. monogyna 4
r
86.4 ± 51.8
25.3 ± 16.9
45.3 ± 11.9
34.3 ± 15.2
610.7 ± 452.8
2.3 ± 0.3
19.7 ± 12.8
0.9 ± 0.1
51.3 ± 24.4
D. gnidium
4
r
101.8 ± 82.3
31.2 ± 28.5
120.0 ± 36.6
31.8 ± 6.4
652.9 ± 225.7
2.1 ± 0.3
18.3 ± 13.8
1.8 ± 0.6
109.6 ± 41.0
E. lusitanica
1
r
152.1 ± nd.3
43.1 ± nd.5
160.0 ± nd.6
48.5 ± nd.
1738.6 ± 4nd.4
1.5 ± nd.
36.7 ± nd.8
0.9 ± nd.
47.4 ± nd.4
E. scoparia
2
r
94.7 ± 78.4
72.9 ± 68.9
90.0 ± 50.0
25.8 ± 11.8
1253.6 ± 494.4
1.5 ± 0.6
57.0 ± 54.8
0.7 ± 0.1
179.6 ± 163.9
L. luisieri
4
s
66.4 ± 51.0
27.6 ± 23.9
28.3 ± 2.3
50.1 ± 16.9
1077.7 ± 585.9
1.2 ± 0.2
5.1 ± 4.1
0.3 ± 0.1
475.1 ± 120.2
M. communis 1
r
41.4 ± nd.0
8.3 ± nd .
120.0 ± nd.6
73.5 ± nd.
676.0 ± 2nd.4
2.0 ± nd.
11.0 ± nd.8
1.3 ± nd.
61.4 ± nd.4
P. lentiscus
1
r
19.4 ± nd.0
2.7 ± nd .
50.0 ± nd.7
20.0 ± nd.
393.5 ± 2nd.4
1.5 ± nd.
2.2 ± nd .
0.8 ± nd.
176.4 ± nd.4
U. jussiaei
3
r
11.5 ± 2.9
3.3 ± 1.7
67.7 ± 28.7
14.0 ± 4.5
562.9 ± 212.4
1.1 ± 0.2
2.6 ± 1.5
0.8 ± 0.1
284.3 ± 57.2
C. crispus
33
34
PC2
1
DIAMETER
R/S
BIOMASS
DEPTH
WIDTH
PC1
LENGTH
SRL
1.1
B
PC2
2,5
Cm2
Cm3
1,5
Dg3
Es4
Dg4
Dg1
Cm1
Mc3
Dg2
Cs3
Cc3
Cm4
El4
Cs2
0,5
Cc2
Pl2
Cc2
Uj2
PC1
Uj2
Cc2
Cc2
-0,5
Cs2
Cs1
Cc2
Cc1
Cc3
Uj2
Es2
Cc2
Ll2
Ll4
Ll1
-1,5
Ll3
-2,5
-2,5
-1,5
-0,5
0,5
1,5
2,5
Fig. 2.1 PCA diagrams. A represents the components loadings for each variable and B represents the
components scores for each plant individual. Legend for variables: DIAMETER – Average root diameter;
BIOMASS – Root biomass; DEPTH – Maximum rooting depth; WIDTH – Root system width; LENGTH
– Root length; R/S – Root-to-shoot ratio; SRL – Specific root length. Legend for species: Cc – Cistus
crispus; Cs – Cistus salvifolius; Cm – Crataegus monogyna; Dg – Daphne gnidium; El – Erica
lusitanica; Es – Erica scoparia; Ll – Lavandula luisieri; Mc – Myrtus communis; Pl – Pistacia lentiscus;
Ru – Rubus ulmifolius; Uj – Ulex jussiaei. Symbols in bold correspond to obligate seeders. The
developmental stage, as obtained by the respective basal section, is indicated by the number following the
species symbol. Stage 1: 0 to 5 mm2; stage 2: 5 to 25 mm2; stage 3: 25 to 125 mm2; stage 4: > 125 mm2.
35
The first two principal components extracted by the PCA (Fig. 2.1A) explained
80 % of the total variance. Root length and root width were best correlated with PC1
(loadings 0.94 and 0.89, respectively). Root diameter and SRL were best correlated with
PC2 (loadings 0.83 and –0.84, respectively). Root biomass was best correlated with
PC1 (loading 0.82) and R/S was best correlated with PC2 (loading 0.74). Maximum
rooting depth was poorly correlated with both principal components (loadings 0.69 and
0.44 for PC1 and PC2, respectively). The plot of component scores (Fig. 2.1B)
presented a clear arrangement of plants according to their developmental stage, as
defined by the basal section classes, with the only exceptions of a C. crispus and a C.
salvifolius plant. Plants were also arranged according to the respective species and the
two regenerative strategy groups. Most obligate seeders presented lower scores for PC2
(specially L. luisieri and C. crispus) while most resprouters presented higher scores for
PC2 (specially D. gnidium and C. monogyna). This pattern was less evident at
developmental stage 2.
Given the results obtained with the PCA, allometric relationships were
established through linear regression using the log-transformed values of root biomass,
shoot biomass, root system length and root system width as independent variables and
the log-transformed values of basal section as the dependent variable (Table 2.2). The
linear regressions for root and shoot biomass presented coefficients of determination of
0.79 and 0.83 (p<0.001 for both regressions), respectively. The linear regression slopes
were very similar (1.003 and 1.046, respectively). In the cases of root system length and
root system width the relationships were still highly significant (p<0.001) showing
coefficients of determination of 0.61 and 0.55, respectively.
Table 2.2 Allometric relationships obtained by linear regression between basal section (mm2) and four
different root variables: root biomass, shoot biomass, root system length and root system width. All
variables were log-transformed. Biomass data is indicated in decigrams in order to obtain only positive
values. For each linear regression it is indicated the intercept (a), the slope (b), the coefficient of
determination (r2) and the associated probability (p).
a
b
r2
p
Root biomass (0.1g))
0.335
1.003
0.79
< 0.001
Shoot biomass (0.1g)
0.615
1.046
0.83
< 0.001
Root system length (cm)
4.383
0.528
0.61
< 0.001
Root system width (cm)
2.059
0.357
0.55
< 0.001
Variables
36
According to the Mann-Whitney U test, the ensemble of obligate seeders
presented significantly lower values than the ensemble of resprouters for maximum
rooting depth (p<0.001), average root diameter (p<0.01), root biomass (p<0.01) and R/S
(p<0.01). Resprouters presented significantly lower values than obligate seeders for
SRL (p< 0.01). Basal section, shoot biomass, root width and root length were not
significantly different. Due to the smaller number of individuals, these differences could
be only partially confirmed within developmental stages 2 (maximum rooting depth,
p<0.05; root biomass, p<0.05) and 3 (maximum rooting depth, p<0.05).
The graph of SRL plotted against the log-transformed values of basal section
(Fig. 2.2) showed decreasing values for all four species and a clear separation between
the two obligate seeders (C. crispus and L. luisieri) and the two resprouters. The same
decreasing trend was observed for the R/S ratio values of the four species but in
particular for D. gnidium. This trend can also be observed in the images of Fig. 2.3.
Root-S hoot (g.g-1)
3,5
3,0
2,5
2,0
1,5
1,0
0,5
S R L (cm .g-1)
0,0
1000
C. crispus
800
L. luisieri
C. m onogyna
600
D. gnidium
400
200
0
0
1
2
3
4
5
Log [B as al S ection (m m 2)]
6
7
Fig. 2.2 Relationships between Basal Section and two root system indices: Specific Root Length (SRL)
and Root-to-Shoot ratio (Root-Shoot), for two obligate seeders ( Cistus crispus and Lavandula luisieri;
represented in bold) and two resprouters (Daphne gnidium and Crataegus monogyna; normal lettering).
37
Fig. 2.3 Images of 16 plants representing different developmental stages (as defined in Figure 1) of two
resprouters: A – Daphne gnidium (stages 1,2,3 and 4), B – Crataegus monogyna (stages 1,2,3 and 4); and
two obligate seeders: C – Lavandula luisieri (stages 1,2,3 and 4), D – Cistus crispus (stages 1,2,2 and 3).
The vertical bars represent 0.5 m. Arrows indicate the ground surface
38
Discussion
The study of a very heterogeneous group of individuals normally has to deal
with important constraints in terms of statistical analysis. However it may allow to
study the factors responsible for the existing variability, as shown by the PCA using
different belowground traits. Although apparently obvious in some aspects, the results
obtained allow a better understanding of the different role of phylogeny and ontogeny in
the differentiation of roots. The PCA showed that the developmental stage/basal section
of the individuals was the basic cause for root system differentiation within our set of
plants and studied variables. This trend was essentially related to increasing values of
root length, root system width and root biomass. Root diameter and root length were
associated with different principal components, suggesting that these two variables
represent two separate factors in the distinction of the root systems of our set of plants.
According to this, plants should be distinguished either by root length or by root
diameter. However, root length was essentially able to distinguish different
developmental stages, whereas root diameter was more related with species
differentiation. Obligate seeders C. crispus and L. luisieri had in general lower scores
of PC2 than resprouters suggesting that the average root diameter may be a distinctive
trait between the two groups, as confirmed by the statistical test. The symmetric
position of SRL relative to root diameter is in accordance with the use of this coefficient
as an indicator of root diameter (Fitter, 1985). Another distinctive trait between seeders
and resprouters seems to be the maximum rooting depth which was poorly correlated
with either axis of the PCA. Thus, depth seems to work quite independently from the
remaining root system variables including basal section. Two possible reasons may
explain the weak relationship between maximum rooting depth and other traits, namely
basal section. One is related to the fact that some species (e.g. D. gnidium and L.
luisieri) seem to achieve maximum rooting depth early in the development, and then
decrease or stop the vertical growth of roots (Fig. 2.3). The other, results from the
existence of an inherent maximum rooting depth attained by each species. The early
achievement of maximum rooting depth is undoubtedly an ecological advantage and
seems to be a common feature of many mediterranean woody species (Canadell and
Zedler, 1995). Although representing just a small fraction of the total root system, deep
roots play a fundamental role to deal with water stress during the dry season especially
at early developmental stages (Canadell et al., 1996). These roots reach deeper layers
where water depletion is not so frequent as at the surface soil layers. Deep roots may be
39
responsible for more than 75% of the total water extracted during dry periods (Nepstad
et al., 1994). Within the same developmental stage, differences concerning maximum
rooting depth seem to be associated with the regenerative strategy of each species
(Keeley, 1986; Correia & Catarino, 1994). In general and for similar developmental
stages, obligate seeders presented relatively shallow root systems whereas resprouters
presented deeper root systems. Within our database, L. luisieri and D. gnidium
represented two extremes of this opposed trends. Root growth was essentially directed
horizontally for L. luisieri and vertically for D. gnidium. In ecological terms, the
significantly higher values found for root biomass, root diameter, and R/S ratio of
resprouters may be interpreted just as a consequence of the existence of deep roots,
despite the weak relationships found within the PCA diagram. Studies from other
Mediterranean-type regions of the World refer relationships between belowground traits
and regenerative strategies similar to those reported here, namely in Australia (Bell,
2001), California (Hellmers et al., 1955) and South Africa (Higgins et al., 1987).
The decreasing trend of the R/S ratio and SRL for increasing values of basal
section is to be expected. An increasing allocation of resources to the shoot as plants
grow has been referred by different authors (Nobel, 1996; Bazzaz, 1997; Grace, 1997)
and it is specially important in mediterranean plants for which the early development of
roots may be critical for surviving the first dry season after germination. The expected
decreasing trend observed for SRL (Fitter, 1985) was much more marked for the two
obligate seeder species, which may hint at different strategies of root growth.
Apparently, differences are due to the preferential investment on structural roots and
storage tissues of the two resprouters at early developmental stages, contrasting with the
preferential investment on fine roots of the two obligate seeders at similar
developmental stages.
Despite the existence of a broad range of R/S ratios corresponding to different
species and different developmental stages, root biomass and shoot biomass were
similarly and consistently correlated with basal section. This was confirmed by both the
linear regressions and the PCA. The existence of close relationships between stem
variables (diameter and/or basal section) and root biomass, has been found in different
studies on tree species ( e.g. Santantonio et al., 1977; Drexhage & Colin, 2001;
Hoffmann & Usoltsev, 2001; Ranger & Gelhaye, 2001). The establishment of a single
consistent allometric relationship for different species between root biomass and stem
variables (Santantonio et al., 1977), is in accordance with the widespread pipe model
40
theory (Shinozaki et al., 1964). Stem section seems to limit root and shoot development
in a similar way for different species and different developmental stages. Given the
different sample sizes of each developmental stage and each species, it must be pointed
out that the allometric relationships found are only valid within the scope of the present
work. Sampling limitations have also to be kept in mind when interpreting the
differences obtained between regenerative strategies. The similarity of belowground
traits among obligate seeders certainly reflected the phylogenetic relationships between
plants since only two genera could be sampled. Thus, the existence of common traits
can be associated to a common regenerative strategy, or just simply to the fact that part
of the plants were closely related in terms of phylogeny. Special sampling designs have
been established to overcome this difficulty (Nicotra et al., 2002) but they are not
always applicable within a single plant community as in our case. Therefore, the
significant differences found between the two regenerative groups have to be interpreted
also in view of the role of phylogeny. However our results are supported by similar
findings (Hellmers et al., 1955; Higgins et al., 1987; Bell, 2001) in other
Mediterranean-type regions, which lead us to assume that the same adaptive
mechanisms existing elsewhere are also valid in the plant community where this study
was undertaken. One of the aspects lacking in our study was the assessment of the
influence of site conditions on belowground traits. Most authors agree on the
fundamental influence of environmental factors on root systems characteristics (e.g.
Spurr & Barnes, 1980; Kummerow, 1981; Fitter, 1996; Atkinson, 2000). In our case the
absence of evident soil constraints for the development of roots and the proximity of the
excavation sites, lead us to assume the existence of relatively homogeneous
environmental conditions allowing the comparison of root systems on a genetic and an
ontogenic basis. Nevertheless we have to admit that the existence of differences in plant
density or micro-relief may have definitely contributed to the overall variance of
belowground traits.
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43
3 ROOT DISTRIBUTION OF MEDITERRANEAN WOODY
PLANTS; INTRODUCING A NEW EMPIRICAL MODEL2
Abstract: The root distributions of 42 plants from 18 mediterranean woody species
were characterised by using an adjustable new empirical model. Plants were classified
in terms of developmental stage and regenerative strategy. Vertical distributions of root
length and root biomass were determined, standardised, and computed as cumulative
data. The root distribution data were used to test the new proposed model against three
other models taken from the literature. Tests have shown that the new model presented
the best performance among the four. Significant differences were obtained between
developmental stages and between regenerative strategies, using model-derived
parameters. Despite the heterogeneous characteristics within the group of studied plants,
different rooting patterns could be detected using the new modelling approach. The
paper discusses these patterns in terms of the ecological characteristics of the different
species.
Key words: Mediterranean woody plants, root biomass, root distribution models, root
length, rooting patterns.
2
Based on paper: Silva J.S., Rego F.C. & Martins-Loução M.A. (2003). Root distribution of mediterranean woody
plants. Introducing a new empirical model. Plant Biosystems 137(1) in press.
44
3.1
Introduction
The different rooting patterns that exist in nature are the result of both
genetically and environmentally determined characteristics. As a consequence, root
systems may show a wide variation both between and within species, depending on site
conditions, the presence of neighbouring plants, developmental stage and genotype
(Canadell & Zedler, 1995; Fitter, 1996). However it is recognised that different species
are associated with different rooting patterns (Spurr & Barnes, 1980) and that these have
a direct influence on the distribution of roots in the soil (Fitter, 1996). Studies on root
distribution are normally concerned with root biomass and/or with root length, as a
function of depth (Lynch, 1995). In physiological terms, root biomass is a measure of
the role of roots as sinks, whereas root length is a direct indicator of the potential for the
absorption of nutrients and water (Atkinson, 2000). Given the importance of these two
root variables, most plant community models that quantify the uptake of water and
solutes or the carbon partitioning within the plant, use root biomass and/or root length
distributions as an input (e. g. Caldwell & Richards, 1986; Klepper & Rickman, 1990;
Shani & Dudley, 1996). In this way, most root distribution models were developed for
plant communities but only very few were designed for plant individuals (Hoffmann &
Usoltsev, 2001). However, the high diversity of root systems that exists in natural
conditions should also favour a single plant approach (Bengough et al., 2000). Models
at the individual plant level may allow the study of the factors that determine root
distribution patterns, just because each individual is a direct unique result of those
factors.
Some of the simplest root distribution models were developed to calculate the
distribution of roots with depth under non-limiting growing conditions (Pagès et al.,
2000). The model by Monteith (1989) defines root length density (the length of roots
per volume of soil) as a simple inverse square root function of depth. Other models can
be adjusted to a particular species or plant community by changing one single
parameter, such as those developed by Gerwitz & Page (1974) and Gale & Grigal
(1987). A similar approach was also used to describe the horizontal biomass decay with
distance from the stem base of individual trees (Drexhage & Gruber, 1998). More
flexible models have been adjusted to root distributions at the community level such as
the logistic dose-response curve (LDR) which includes two parameters (Schenk &
Jackson, 2002). The parameterisation obtained by fitting a model to a certain root
distribution allows a simple characterisation of the respective rooting pattern.
45
In the specific case of mediterranean woody plants there is evidence of a
relationship between rooting patterns and regenerative strategies. Regenerative
strategies are very important for mediterranean shrublands since they assure their
resilience to frequent disturbances such as fire or grazing (Naveh, 1975). Studies have
shown that resprouting species have extensive root systems and are often deep rooted
whereas seeder species have less developed root systems and are normally shallow
rooted (Keeley, 1986; Bell, 2001).
The adaptive strategies of plants in terms of root system characteristics have also
been related to different patterns of root development. The fact that many species,
especially those from dry conditions, may develop deep tap roots at early stages
preceding the development of lateral roots (Spurr & Barnes, 1980) is an evidence of the
specificity of root distributions at different developmental stages.
Few efforts have been made to characterise in a quantitative manner the complete root
systems of woody plants. Most works dealing with root systems have been developed
on agricultural plants and/or plants at the seedling stage, given the considerable efforts
involving the excavation of roots in the field.
This paper aims to characterise the root distributions of a set of mediterranean
woody plants using a new modelling approach. The dual objective of the present paper
is to: a) compare the performance of a new empirical model with other known models,
at fitting root distribution data; b) use the proposed modelling approach to describe and
interpret the root distributions of different mediterranean woody plants according to the
respective species, regenerative strategy and developmental stage.
3.2
Methods
Study regions
The study site was at Tapada Nacional de Mafra in the Central West Region of
Portugal, where 34 plants were excavated. Tapada Nacional de Mafra is a protected area
with 827 ha, about 30 km Northwest of Lisbon and 12 km East from the coast (38º 58’
30’’ N and 9º 15’ 52’’ W). The lowest altitude is 90 m and the highest is 358 m. Soils
are humic cambissols derived from sandstone. Mean annual precipitation is 798 mm and
mean annual temperature is 14.6 ºC. Summer precipitation (June, July, August)
accounts for only 3.1 % of total annual rainfall. The area is mostly covered by
shrublands and dominant species are Erica scoparia L. and Erica lusitanica Rudolphi.
46
Other important species are Crataegus monogyna Jacq., Ulex Ulex jussiaei Webb,
Daphne gnidium L., Pistacia lentiscus L., Myrtus communis L. and Rubus ulmifolius
Schott. On more xeric sites and open areas we also find Lavandula luisieri (Rozeira)
Rivas Martinez and different species of Cistus.
In order to increase the data set used for testing the root distribution models, we
have also included unpublished data concerning 8 plants collected at Serra da Malcata
in a previous work. Serra da Malcata is a natural reserve located in the Central East
Region of Portugal close to the Spanish border (40o 19’ N and 7o 09’ W). Soils are
mostly schist lithossols. The annual average rainfall is 812 mm and mean annual
temperature is 11.8 ºC. Within the Reserve boundaries the lowest altitude is 425 m and
the highest is 1078 m. Vegetation is essentially constituted by shrublands dominated by
Chamaespartium tridentatum (L.) P. Gibbs, Erica australis L., Erica umbellata L.,
Cytisus multiflorus (L’Hér.) Sweet, Cytisus striatus (Hill) Rothm. and Cistus ladanifer
L.
Sampling procedures
The general sampling objective was to obtain a broad set of woody species
typical from the studied regions including different developmental stages. We have
preferred to collect few individuals from many species instead of replications of a few
species because of the exploratory nature of the research task supporting this study. A
total of 42 plants from 18 species were studied. Plants from Mafra were hydraulically
excavated (Böhm, 1979), using a pump from a fire truck and an adjustable nozzle,
whereas in Malcata only hand tools were used. In both cases the root systems of all
plants were integrally excavated. Much care was taken in order to minimise the loss of
fine roots. Plant stems were wired in order to hold root systems in their original position
and photos were taken before the complete soil removal. The vertical distance from the
soil surface to the tip of the furthest root was measured in order to determine the
maximum rooting depth.
Basal section was used as an indicator of the developmental stage of the plants.
Plants were assigned to three different classes of basal section (the cross sectional area
at the stem base). The class limits were defined according to BS=π.r2 which is the
formula for calculating the basal section (BS), using an increasing stem radius r: BS1 ≤
12.6 mm2 (13 plants), 12.6 mm2< BS2 ≤ 50.3 mm2 (15 plants), BS3 > 50.3 mm2 (14
47
plants). Plants were also classified according to the respective regenerative strategy into
obligate seeders (5 species) and resprouters (13 species).
After excavation, the root systems of Mafra were photographed and dry
weighted. Photos were taken using a Fugifilm MX 2900 Zoom digital camera (Fuji
Photo Film Co., Ltd., Tokyo), featuring a maximum resolution of 2.3 million pixels.
Digital images were analysed using software WinRhizo 4.1b (Regent Instruments,
Quebéc). Module “Root distribution”, was used to measure the root length of each plant
within 4 cm deep horizontal sample layers separated by 1 cm (the minimum value
accepted by the program), corresponding to approximately 80% of the total root length.
In the case of plants from Malcata the procedures were similar for root biomass but root
length was not measured.
Biomass distribution was determined for individuals from both regions, by
cutting plants in 5 cm sections. Each section was limited by two lines perpendicular to
the vertical axe of each plant. Biomass was oven-dried at 85º C for 48 hours and
weighted.
Data analysis
For each layer, root length and root biomass were standardised as a fraction of
total root length and total root biomass respectively, assuming values between 0 and 1.
Using the standardised data, the cumulative root biomass and cumulative root length
were computed from the surface layer to the maximum rooting depth. Cumulative root
length and cumulative root biomass are thus non-dimensional variables and are referred
to as cumulative root fraction (Yr), assuming values of 0 at the soil surface and 1 at the
maximum rooting depth. Yr=0.5 corresponds to half of the cumulative root fraction and
the corresponding depth was used as a root distribution parameter identified as d50.
When referring to root biomass, this parameter was identified as db50 and when
referring to root length it was identified as dl50.
Two models used for representing the cumulative distribution of roots as a
function of depth (d) at the community level, were adjusted to the data: the Gale &
Grigal model (Gale & Grigal, 1987; Jackson et al., 1996; Schenk & Jackson, 2002),
Yr = 1 − β d
(1)
and the logistic dose-response curve (LDR), (Schenk & Jackson, 2002).
48
Yr =
1
⎛ d
1 + ⎜⎜
⎝ d 50
⎞
⎟⎟
⎠
(2)
c
Symbol β is an adjustable parameter in the Gale & Grigal model. It assumes
lower values for higher concentrations of roots at surface layers and values closer to 1
for more homogeneous root distributions. The parameter d50 can be determined as
d50=logβ0.5. In the LDR model symbol c is a dimensionless curve shape parameter and
d50 is obtained directly from the equation.
We have also tested a standard logistic model. This model was used by Rego et
al. (1994) for representing the cumulative biomass distribution of the canopy of single
plants:
Yr =
1
1 + e a +bd
(3)
Symbols a and b are both adjustable parameters depending on the curve shape.
The value of d50 is given by d50=–a/b (Rego et al., 1994).
Due to the limitations shown by these functions, namely in what concerns the
adjustment to data at the beginning and at the end of the biomass and root length
distributions, we have developed a modification of the LDR model, hereafter identified
as MLDR:
Yr =
1
⎛ Maxd − d ⎞
1+ ⎜
⎟
⎝ d .D ⎠
c
(4)
where c and D are adjustable parameters and Maxd is the actual maximum rooting
depth. In this model d50 can be obtained as d50=Maxd/(D+1). According to this
definition, D >1 corresponds to distributions where Yr=0.5 is attained above Maxd/2,
whereas D <1 corresponds to distributions where Yr=0.5 is attained below Maxd/2.
The performance of the four models was evaluated by non-linear regression by
computing the percentage of variation explained by each model (r2) when fitted to root
distribution data. Since data from cumulative distributions are not independent, the high
values obtained for the r2 have to be interpreted having this fact in mind. Although the
significance of the adjustments can not be estimated as for independent data, the value
of r2 can still be used for comparison purposes, in order to determine which model fits
best a given data set. The distribution of the r2 did not follow a normal distribution as
shown by the Shapiro-Wilk W test. According to this, the Friedman Anova was used to
49
compare the values of r2 obtained with the four models, complemented for paired
comparisons by the Mann-Whitney U test (Sokal & Rohlf, 1995). The results were used
to choose the best model among the four under test.
Values of db50 and dl50 were computed for all plants from Mafra and Malcata
using the chosen model. The Mann-Whitney U test was used to compare the db50 and
dl50 values of each regenerative strategy and each basal section class. Since species were
sampled unequally, paired comparisons were performed using the mean values of each
species.
Different rooting patterns were analysed by plotting the model fitted to the root
length and root biomass data of nine plants from Mafra, each one corresponding to the
highest basal section of the respective species. In this case the depth scale was
standardised for comparing the different plants, thus allowing the analysis of relative
root distributions.
3.3
Results
Testing the models
The Friedman Anova (Table 3.1) showed that the values of r2 of the four models
were significantly different for both root length (p<0.001; n=34) and root biomass
(p<0.001; n=42). The logistic model presented the highest average rank for root
biomass (3.40; mean r2=0.98) whereas the MLDR presented the highest rank for root
length (3.76; mean r2=0.99). The comparisons between the logistic and the MLDR
models showed that only the results obtained for root length data set were significantly
different (p<0.001) as shown by the Mann-Whitney U test. According to the
significance of the tests we concluded that the MLDR model should be preferred to the
other three models given that a significantly higher percentage of variation could be
explained by the MLDR model. This decision has affected all further steps of the study
since only the MLDR was used to characterise root biomass and root length
distributions.
Root distributions
Within the whole set of plants the values of Maxd, db50 and dl50 reflected the
diversity of root distribution patterns (Table 3.2 and Table 3.3).
Table 3.1 Comparison of average ranks (1 to 4) and mean r2 of four models fitted to root biomass and root
length data, as obtained by the Friedman Anova (p<0.001 for both root biomass and root length
50
distributions). Values of mean r2 followed by the same letter did not present significant differences
(p>0.05) as obtained by paired comparisons using the Mann-Whitney U test.
Model
Root biomass
Root length
Average rank
Mean r2
0.86 a
1.38
0.84 a
1.70
0.93 a
2.08
0.95 b
Logistic
3.40
0.98 b
2.77
0.97 c
MLDR
3.26
0.98 b
3.76
0.99 d
Average rank
Mean r
Gale and Grigal
1.65
LDR
2
Table 3.2 Maximum rooting depth averaged by species and basal section class. Maximum rooting depth
represents the depth achieved by the deepest root. Values are averages and the number of plants is shown
in brackets. The range was obtained as the difference between the maximum and the minimum values
observed. Basal section classes are defined as: BS1 ≤ 12.6 mm2, 12.6 mm2< BS2 ≤ 50.3 mm2, BS3 > 50.3
mm2.
Species
Regenerat. Region
strategy
Maximum rooting depth (cm)
BS1
BS2
BS3
Range
respr.
Malcata
−
−
301(2)
30
Chamaespartium tridentatum respr.
Malcata
−
401(1)
−
0
Cistus crispus
seeder
Mafra
251(4)
401(4)
−
39
Cistus salvifolius
seeder
Mafra
251(2)
401(1)
−
15
Crataegus monogyna
respr.
Mafra
261(1)
−
651(2)
47
Cytisus multiflorus
seeder
Malcata
−
−
601(1)
0
Cytisus striatus
seeder
Malcata
−
−
351(1)
0
Daphne gnidium
respr.
Mafra
751(2)
−
1651(2)
170
Erica australis
respr.
Malcata
−
−
351(1)
0
Erica lusitanica
respr.
Mafra
−
−
1601(1)
0
Erica scoparia
respr.
Mafra
−
401(1)
1401(1)
100
Lavandula luisieri
seeder
Mafra
261(2)
261(1)
351(1)
10
Myrtus communis
respr.
Mafra
−
1201(1)
−
0
Pistacia lentiscus
respr.
Mafra
−
501(1)
−
0
Quercus faginea
respr.
Mafra
551(1)
−
−
0
Quercus pyrenaica
respr.
Malcata
−
−
601(2)
10
Rubus ulmifolius
respr.
Mafra
−
661(3)
−
51
Ulex jussiaei
respr.
Mafra
401(1)
821(2)
−
87
36(13)
56(15)
79(14)
170
Arbutus unedo
All species
51
Table 3.3 Values of db50 and dl50 averaged by species and by basal section (BS) class. Basal section
classes are defined as: BS1 ≤ 12.6 mm2, 12.6 mm2< BS2 ≤ 50.3 mm2, BS3 > 50.3 mm2. The range was
obtained as the difference between the maximum and the minimum values observed within all plants from
each species.
db50 (cm)
Species
dl50 (cm)
BS1
BS2
BS3
Range
BS1
BS2
BS3
Range
Arbutus unedo
−
−
1.7
2.7
−
−
−
−
Chamaespartium tridentatum
−
11.0
−
0.0
−
−
−
−
Cistus crispus
3.3
4.9
−
5.6
12.1
19.0
−
13.7
Cistus salvifolius
2.8
3.7
−
1.5
10.0
15.9
−
6.6
Crataegus monogyna
1.9
−
9.7
9.5
17.2
−
37.1
33.2
Cytisus multiflorus
−
−
9.0
0.0
−
−
−
−
Cytisus striatus
−
−
3.4
0.0
−
−
−
−
4.0
−
6.9
4.7
28.0
−
58.2
76.5
Erica australis
−
−
5.8
0.0
−
−
−
−
Erica lusitanica
−
−
3.3
0.0
−
−
31.9
0.0
Erica scoparia
−
4.6
0.5
4.1
−
21.4
43.3
21.9
Lavandula luisieri
3.3
1.9
3.9
2.2
7.9
19.1
26.0
18.4
Myrtus communis
−
5.0
−
0.0
−
26.3
−
0.0
Pistacia lentiscus
−
2.9
−
0.0
−
22.7
−
0.0
7.1
−
−
0.0
24.6
−
−
0.0
Quercus pyrenaica
−
−
10.8
0.2
−
−
−
−
Rubus ulmifolius
−
7.5
−
12.2
−
23.4
−
32.0
Ulex jussiaei
7.6
15.8
−
20.8
17.9
40.9
−
46.2
All species
4.3
6.4
5.5
25.8
16.8
23.6
39.3
76.5
Daphne gnidium
Quercus faginea
The highest values of Maxd were observed for D. gnidium (185 cm), E
lusitanica (160 cm) and E. scoparia (140 cm), at BS3 and the lowest values of Maxd
were observed for C. crispus (16 cm), C. salvifolius (16 cm) and D. gnidium (15 cm) at
BS1. The lowest value of db50 was observed for A. unedo (0.4 cm) at BS3 and the
highest for U. jussiaei (26.2 cm) at BS2. The lowest value of dl50 was observed for C.
salvifolius (3.2 cm) at BS1 and the highest for D. gnidium (79.9 cm) at BS3.
Tests between regenerative strategies including all plants, have shown that resprouters
had significantly higher values of dl50 than obligate seeders (p<0.01) but no significant
results were obtained for db50. When restricting the tests to plants from the first two BS
classes, tests have shown that resprouters had significantly higher values of db50
(p<0.05) and dl50 (p<0.01).
52
Tests between BS classes have shown that BS3 had significantly higher values of dl50
than BS2 (p<0.05) and BS1 (p<0.01). The comparison between BS1 and BS2 for dl50
was not significant. None of the comparisons between BS classes for db50 was
statistically significant.
The cumulative root distributions of nine plants plotted using a standardised
depth scale (0-100 % of Maxd) are shown in Fig. 3.1 together with the MLDR model
fitted to the data. The corresponding root system images are shown in Fig. 3.2.
Fig. 3.1 Root distribution of nine plants excavated at Tapada Nacional de Mafra as represented by the
fitted MLDR model (see text and equation 4). D and c are the model parameters. The solid line represents
the cumulative root biomass distribution and the dotted line represents the cumulative root length
distribution.
53
C. crispus and C. salvifolius plants revealed a remarkable resemblance of root
biomass (D = 9.06 and D = 9.93, respectively) and root length (D = 1.06 and D = 1.89,
respectively) distributions. C. monogyna presented a considerable separation between
the two curves showing distinct distribution patterns for biomass (D = 6.03) and length
(D = 0.47). D. gnidium presented a considerable accumulation of root biomass close to
the surface (D = 18.94) but a much deeper concentration of root length (D = 0.88).
Fig. 3.2 Root systems of nine plants excavated at Tapada Nacional de Mafra. The corresponding
cumulative root distributions are shown on Fig. 3.1. The vertical bar represents 0.5 m.
54
E. lusitanica and E. scoparia plants showed very similar rooting patters with a
very high accumulation of root biomass close to the surface (D = 48.06 and D = 266.87,
respectively) and not very different root length distribution curves (D = 4.47 and D =
2.72, respectively). L. luisieri showed very different patterns for root biomass (D =
8.09) and root length (D = 0.39). M. communis showed a high accumulation of root
biomass (D = 23.19) and root length (D = 4.19) at the surface layers. A similar result
was obtained for R. ulmifolius, with the two curves almost overlapping (D = 13.13 for
root biomass and D = 7.54 for root length).
3.4
Discussion
Methodology
Among the four models tested, the MLDR showed a considerable flexibility and
capacity to fit root distribution data from a broad range of woody plants. The use of this
simple mathematical function allowed a very close description of root distribution
patterns as obtained with the described sampling procedures. Also the joint use of root
biomass and root length coefficients reflected the diversity of root systems present
within the data set. Although this approach could potentially lead to an empirical
classification of root systems by establishing class limits for the two parameters, such an
attempt was not followed here given the need of a much broader root distribution
database. A comprehensive classification would only be possible with replications for
each species, each developmental stage and different environmental conditions. The
enormous amount of work required for the excavation of woody plants in the field was a
serious obstacle to obtain such a complete set of data.
If the MLDR model is to be used to fit root distributions of plant communities
where the maximum rooting depth is often unknown, it should be taken into account the
fact that the deepest root data always correspond to Yr=1. If this condition is considered
and accepted, the use of the MLDR model for fitting root distribution data at the
community level is perfectly possible. Silva & Rego (unpublished) have fitted the
MLDR model to the vertical distribution of root counts from trench profiles, obtaining
similar results in terms of the explained variance, as those obtained in the present study.
Thus there is a potential use of the MLDR model to work as an input in functional
models both at the community as at the individual plant level.
Some remarks have to be made on the methods used to obtain root distribution
data specially in what concerns root length. Root length distribution was affected to an
55
unknown degree by the methodology used to excavate the individual root systems,
given the inevitable loss of fine roots (Wallace et al., 1974; Böhm, 1979; Caldwell &
Virginia, 1989; Bengough et al., 2000) which are responsible for most of the total root
length. Although we may assume an equal effect along the whole root system, the loss
of fine roots during the excavation works has eventually contributed to hide some of the
normal accumulation of root length at surface layers. Another aspect to take into
account is the possibility of changes in the plants root system structure after excavation,
compared to the original root arrangement in undisturbed soil, with consequences on the
overall root distribution. However, our perception of the field work says that very little
changes are introduced when dealing with coarse structural roots of woody plants.
Possible deformations on the arrangement of thinner roots were prevented by a careful
observation and image registration of the plants in the field and with a careful handling
and disposal for biomass and root length determination. Finally we should also mention
the existence of possible errors associated with the process of image taking, processing
and analysis. However, deviations on root length measurements may be either in the
sense of diminishing or increasing the actual values (Richner et al., 2000). Despite the
obvious limitations of the methodology used for measuring the length of roots of woody
plants, we have assumed that the referred errors were similarly distributed among all
plants and within each plant. Moreover, the use of standardised data and the
comparative nature of the present study are reasons for considering the possible errors
as acceptable in view of the goals pursued.
Root distribution patterns
Root distribution data revealed in particular for adult plants, a separation
between seeders and resprouters. Within the resprouters group, plants with deep roots
showed a distinct root distribution pattern (Daphne, Erica, Myrtus, Ulex). In particular
the lignotuberous species E. lusitanica and E. scoparia presented a high biomass
concentration close to the soil surface which accounts for the importance of the
lignotuber on biomass partitioning in these plants. Some authors question the decision
of considering the lignotuber as part of the root system since it works as a storage organ
for starch, normally located very close to the soil surface or even at the stem base
(Kummerow, 1981; Canadell & Zedler, 1995), and not exactly as a structural root. This
decision is obviously critical for the resulting root distribution pattern. Two other
resprouting species with a relatively high concentration of biomass close to the surface,
56
D. gnidium and M. communis, did not present typical woody lignotubers but similar
swollen-less-lignified root crowns, which apparently play the same role of storing
resources and dormant buds for plant resprouting. With the exception of M. communis,
all deep rooted species presented nearly vertical tap roots. Tap roots although having a
strategic role on plant survival during the dry season, they often have little importance
both in terms of length and biomass (Kummerow et al., 1990; Nepstad et al., 1994;
Canadell & Zedler, 1995; Canadell et al., 1996). The implication of this rooting pattern
is a higher relative concentration of roots close to the surface (as can be observed in Fig.
3.1) for increasing maximum rooting depths. Most deep rooted plants presented also a
lateral expansion of roots close to the surface in what can be considered as a dual root
system (Canadell & Zedler, 1995) composed of tap roots and surface roots. Different
studies have shown that in drought-prone regions this rooting pattern may be
advantageous and is present in several species (Hellmers et al., 1955; Specht & Rayson,
1957; Kummerow,1981; Krämer et al., 1996). In the particular case of the two
phylogenetically close Erica species (Castroviejo (1999) despite the similar root
biomass distribution pattern, a different root length distribution pattern was observed
due to the less pronounced lateral expansion of the root system of E. scoparia (at BS3).
This may be explained by the fact that this individual was part of a dense maquis
whereas the E. lusitanica plant was an isolated individual. Although we could not test
this hypothesis, it is known that plant interaction may have a determinant effect on root
distribution (Atkinson, 2000). The resprouters C. monogyna and R. ulmifolius followed
distinct strategies when compared to the remaining species of this group. The first
presented only thick structural roots at the surface and an almost complete absence of
fine roots at this level. This rooting pattern explains the difference between the root
biomass and the root length curves observed in Fig. 3.1. In the case of R. ulmifolius this
species only presented fine roots both at the surface as at deeper layers. This explains
the similarity of the root biomass and root length curves. The fact of being a climber
species explains the absence of structural roots and consequently the rooting patterns
exhibited by this species.
In the case of seeders there was a remarkable resemblance of rooting patterns of
C. crispus and C. salvifolius plants, corresponding to shallow root systems as it is
common of most seeder species (Keeley, 1986; Bell, 2001). In particular the case of L
luisieri is paradigmatic since this highly specialised seeder manages to survive in very
dry conditions with a shallow root system. The strategy of this species, seems to be the
57
development of a fibrous root system at the maximum rooting depth, with the
consequent increase in water uptake efficiency.
In terms of developmental stages, only root length distribution seemed to be
particularly affected as a consequence of increasing maximum rooting depth. The
absence of consistent differences of root biomass distribution among BS classes was
partially due to the concentration of biomass in storage surface organs by resprouters.
On the contrary, the values of dl50 showed a consistent increase for all species along
developmental stages, as a consequence of increasing values of maximum rooting
depth.
The present work showed that the parameterisation of root distributions using an
adjustable model such as the MLDR may be an interesting way of characterising species
and functional groups according to their adaptation to environmental conditions. Further
research is need in what concerns the study of the intra-specific variability of individual
root distributions according to different environmental conditions, for which the
approach presented here may also be used.
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60
4 ROOT DISTRIBUTION OF A MEDITERRANEAN SHRUBLAND
IN PORTUGAL3
Abstract: The distribution of roots of an Erica (Erica scoparia and Erica lusitanica)
dominated mediterranean maquis was studied using three different approaches: root
counts on trench walls (down to 120 cm), estimation of the maximum rooting depth
using an allometric relationship and estimation of fine root biomass and fine root length
using soil cores (down to 100 cm). Roots were classified according to diameter (fine, <
1.0 mm; small, 1.0-5.0 mm; medium, 5.1-10.0 mm; coarse, >10.0 mm) and species
(Erica sp., Pteridium aquilinum, Rubus ulmifolius and Ulex jussiaei). The depth
corresponding to 50% of all roots (D50) was determined by fitting a new model to the
cumulative root distribution. Fine roots represented 96% of root counts. Root counts of
Erica represented 59%, Ulex 34%, Rubus 6% and Pteridium 1%. Overall root counts
showed a D50 of 26 cm. D50 was higher for Ulex (40 cm) and Erica (22 cm), and lower
for Pteridium (9 cm) and Rubus (3 cm). D50 for fine roots was 27 cm, for small roots 11
cm, for medium roots 6 cm and for coarse roots 4 cm. The estimated average maximum
rooting depth of the 28 deepest Erica roots was 222 cm. The deepest Erica root was
estimated to reach 329 cm. 82% of roots growing deeper than 125 cm were not reaching
more than 175 cm. Root length density ranged from 4.6 cm/cm3 at 10 cm to 0.8 cm/cm3
at 80 cm. Root biomass ranged from 7.7 mg/cm3 at 10 cm to 0.6 mg/cm3 at 40 cm. D50
for root biomass was 12 cm and D50 for root length was 14 cm. Fine root biomass was
estimated as 1.6 kg/m2 and the respective root length as 18.7 km/m2.
Key words: Root distribution, maximum rooting depth, root biomass, root length,
mediterranean shrubland, Erica.
3 Submitted to Plant and Soil by J.S. Silva & F.C. Rego 2002.
61
4.1
Introduction
The distribution of roots in the soil has a direct influence on the capability of
plants to extract water and solutes (Fitter, 1996). Because of its vital role, information
on root distribution is essential for a comprehensive understanding of the ecophysiology
of plants. Root distribution data are frequently used as an input in water and nutrient
uptake models (e.g. Caldwell & Richards, 1986; Monteith et al., 1989; Klepper &
Rickman, 1990; Shani & Dudley, 1996; Pagès et al., 2000) or even in global scale
simulation models (Zeng et al., 1998; Zeng, 2001). Models of root distribution have
been developed normally under the form of a function which, in most cases, has
adjustable parameters in order to suit the specificity of the crop or the plant community.
Many root distribution models have been proposed in the literature in order to represent
root distribution patterns (Gerwitz & Page, 1974; Gale & Grigal, 1987; Monteith et al.,
1989; Drexhage & Gruber, 1998; Jobbágy & Jackson, 2000; Shenk & Jackson, 2002a).
Similarly many different methodologies have been used to obtain root distribution data:
root maps, soil cores, soil monoliths, complete root excavation. These different
techniques allow to express the distribution of roots under different forms: root counts,
root length, root biomass, root surface, root volume (Schuurman & Goedewaaggen,
1971; Böhm, 1979; Caldwell & Virginia, 1989; Atkinson, 2000).
In the specific case of mediterranean ecosystems not many studies have been
concerned with belowground processes and especially with the distribution of roots in
the soil. Besides the normal difficulties encountered when working with roots, this lack
of studies is also motivated by the existence of extensive root systems, the frequent
existence of shallow bedrock or the intricate network of roots present in dense maquistype shrublands (Kummerow, 1981; Canadell & Zedler, 1995). The relative scarcity of
studies for this type of ecosystems is well reflected in the planetary compilation of root
distribution data by Jackson et al. (1996) where mediterranean ecosystems are
represented by only 11 (less than 5%) out of 250 studies and all the Mediterranean
Region is represented by only 4 studies. Among the root distribution studies in the
Mediterranean Region, the species Quercus ilex (Canadell & Rodà, 1991; Djema, 1995)
and Quercus coccifera (Kummerow et al., 1990; Cañellas & Ayanz, 2000) have
deserved special attention. It is also worth to mention the works of Martinez &
Rodriguez (1988) and Martinez et al. (1998) in shrublands of Southern Spain.
Few works have been focused on the root distribution of different species from
the same plant community, thus sharing the same soil and climate conditions. In a
62
common environment, different rooting patterns should reflect different ecological
adaptive strategies but also the competition between plants with different characteristics
(Casper & Jackson, 1997). Another aspect lacking in most previous works is the
comprehensive study of maximum rooting depth. This is critical for mediterranean
conditions since deep roots are fundamental for many plant species to overcome the
water stress typical of the dry season and also to be able to survive after a natural
disturbance such as fire or grazing (Kummerow, 1981; Nepstad et al., 1994; Canadell &
Zedler, 1995; Shenk & Jackson, 2002b). Moreover, in order to understand the uptake
mechanisms of a community of plants, it is important to know the distribution of deep
roots along the soil profile. Although many works refer values of the maximum rooting
depth observed for a certain species, it is rare that studies approach the distribution of
deep roots at the community level (Canadell et al., 1996). This is most of all explained
by the tremendous difficulties to access this information, especially when dealing with
deep rooted species.
In order to contribute to a better knowledge of mediterranean ecosystems, the
present paper approaches different aspects of the root distribution of a typical
mediterranean maquis. In particular this study aims to: i) determine and compare the
vertical root distribution of the different species and the different diameter classes, ii)
estimate the maximum rooting depth and the distribution of deep roots, iii) determine
the distribution of fine roots in terms of root length and root biomass.
4.2
Methods
The study was conducted at Tapada Nacional de Mafra, a protected area with
1187 ha, about 30 km Northwest of Lisbon (38º 56’ 37’’ to 38º 58’ 30’’ N and 9º 15’
52’’ to 9º 18’ 43’’ W). The studied plant community was largely dominated by Erica
scoparia L. forming a dense maquis with an average plant height around 180 cm. Other
species present were: Erica lusitanica Rudolphi, Rubus ulmifolius Schott, and Ulex
jussiaei Webb. The only important herbaceous species was Pteridium aquilinum (L.)
Kuhn. According to growth ring counts, the age of the oldest shrubs was estimated to be
around 46 years, although we suppose that important disturbances may have occurred
during this period. Mean annual precipitation is 798 mm and mean annual temperature
is 14.6 ºC. The rare occurrence of rocks and the existence of a deep soil facilitate the
natural development of roots.
The methodology developed to study the roots of this plant community was
based on the trench profile method complemented by the extraction of soil cores
63
(Schuurman & Goedewaagen, 1971; Böhm, 1979; Caldwell & Virginia, 1989; Van
Noordwijk et al., 2000). The trench profile method allowed the extensive sampling of
the shrub community in terms of root counts and maximum rooting depth, whereas the
soil cores were specifically used to estimate the biomass and length of fine roots. Six
trenches (numbered 1 to 6) were excavated with a backhoe equipment in June 1999. The
site was chosen close to a forest road following a contour line on a 15% slope. The
excavation was performed on the upper roadside and perpendicularly to the road axis.
Trenches were separated by 8 m except trenches 3 and 4 which were separated by 27 m.
Trenches were 3 m long x 1 m wide and were excavated down to the road level. The
bottom of each trench was kept flat but depth in relation to soil surface varied among
the trenches and within each trench according to the local relief characteristics. The
minimum depth achieved was 120 cm and the maximum depth was 230 cm. Before the
trench excavation, all plants inside the area to be excavated and 0.5 m on both sides
were identified and the respective diameters at the stem base were measured. The fronds
of Pteridium aquilium were measured exactly as the other species, despite its particular
growing characteristics. For each trench we have disposed of the two side walls except
for trench 5 where only one wall presented suitable conditions for root studies. Trench
walls were also used to collect soil samples at different depths. Before root counting
each wall surface was flattened and smoothed using hand tools and then referenced by
means of a system of co-ordinates. On each prepared wall the basic procedure consisted
on mapping the section of cut roots down to 120 cm deep on a transparent plastic sheet.
Since parts of the trench walls have collapsed during and after excavation, the length of
each root map was different according to the length of prepared wall. A total area of
16.4 m2 of soil profile was sampled using vertical maps. Cut roots were drawn on a 1:1
scale using different colours to distinguish the different species. Given the impossibility
to distinguish in the field the roots of the two Erica species it was decided to register
only the respective genus. This resulted in the differentiation of four categories: Erica
(Erica scoparia and Erica lusitanica), Pteridium (Pteridium aquilinum), Rubus (Rubus
ulmifolius) and Ulex (Ulex jussiaei), hereafter referred to as “species” for simplification
purposes. Roots from Erica presented a black coloured bark and a light brown strongly
lignified cortex, even in the smallest diameters. Roots from Pteridium were soft and
brown coloured. Rhizomes presented hairs at the surface and a white cortex. The bark of
Rubus roots was light brown becoming whitish coloured for finer roots. Ulex roots were
white and poorly lignified, in all diameter classes, coarser roots presenting a rough
64
surface with a typical wrinkle-like texture. Specific root organs such as lignotubers from
Erica and rhizomes from Pteridium were also included in the root mapping. No
attempts were made to separate dead from live roots given the difficulties to distinguish
these two categories in the field. However, obviously decaying roots and rhizomes were
discarded from the root distribution counts. These criteria were consistent for all
sampling procedures. After mapping, roots were counted over a 10x10 cm grid and
registered according to species and diameter. Four diameter classes were considered: <
1.0 mm (fine roots), 1.0-5.0 mm (small roots), 5.1-10.0 mm (medium roots), >10.0 mm
(coarse roots). The number of root counts of each grid square was used as a measure of
root density (number of roots/dm2). The average root density by species and by
diameter class was computed separately for each trench. The mean values for the plant
community were computed as the weighted averages of the six trenches, using the
sampled surface of each trench as the respective weight. Statistical comparisons were
preceded by a Kolmogorov-Smirnov test in order to check the normal distribution of the
variables under study. As most of them did not verify the normality assumptions, the
existence of statistical differences in root density among species and among diameter
classes was tested as paired comparisons by the Mann-Whitney U test. The distribution
of roots along the soil profile was separately computed for each species and each
diameter class following the procedure just described for the average root densities. In
order to compare the different root distribution patterns, a two parameter logistic-type
function specifically developed with this purpose, was fitted to the cumulative root
fraction (Yr) as a function of depth (d). The cumulative root fraction was obtained by
dividing the root density at each depth by the sum of root densities of the profile and
then computing the cumulative series of these values for all depths. This cumulative
standardised root distribution is equal to 0 at the soil surface and is equal to 1 at the
maximum depth of the profile. The fitted model (hereafter referred to as MLDR) takes
the form:
Yr =
1
⎛ Maxd − d ⎞
1+ ⎜
⎟
⎝ d .D ⎠
c
(1)
where c and D are the model parameters and Maxd is the maximum depth of the
studied profile (120 cm). The depth corresponding to 50% of the cumulative root
fraction (Yr = 0.5) is given by:
65
D50 =
Maxd
( D + 1)
(2)
High values of D50 are associated to deep root distributions whereas low values
of D50 are associated to a higher concentration of roots close to the soil surface.
Maximum rooting depth of deep rooted plants was estimated by mapping the cut
roots at the bottom of the trenches according to a procedure similar to the one used on
the trench walls. A total area of 9.9 m2 was sampled using this technique. In this case
the diameters of cut roots were measured instead of being assigned to classes. The
possible existence of a relationship correlating the diameter of cut roots and the
respective maximum rooting depth was on the basis of this procedure. This relationship
was determined by measuring the diameter of tap roots from excavated plants at regular
intervals and the respective vertical distance to the root tip. This procedure could only
be used for Erica since no adult Ulex plants (also deep rooted) could be excavated at the
study site. Tap roots from three individuals (two E. scoparia and one E. lusitanica) were
measured with a digital calliper every 5 cm, starting from the root tip and continuing
upwards. An asymptotic equation of the form:
L=
a
⎛R ⎞
1+ ⎜ d ⎟
⎝ b ⎠
c
(3)
where a, b and c are constants, Rd is the root diameter and L is the correspondent
vertical distance to the root tip, was fitted to the observed data (n = 63). The non-linear
regression revealed a consistent relationship between Rd and L, being able to explain
89% of the variance (Fig. 4.1). Estimations of maximum rooting depth using this
relationship were made under the assumptions that: Erica tap roots were in general
following an orientation similar to the sampled roots (4.1±0.4 degrees from the
vertical), and that no solid sandstone (found on 8% of the mapped surface) was
preventing roots to grow following their natural orientation. Both assumptions were
reasonably confirmed by field observations of partially excavated individuals and road
cuts in the study area. The estimation of maximum rooting depth was computed
separately for each individual root by summing L to the depth at which the root was cut
(i.e. the trench depth at that point).
66
160
Vertical distance to root tip (cm)
140
120
100
80
60
40
[
y = 144.3 1 + ( x 1.8)
20
− 2.5
]
r 2 = 0.89
0
2
4
6
8
10
12
Root diameter (mm)
Fig. 4.1 Relationship between root diameter and the vertical distance to the root tip for Erica
Roots were assigned to 25 cm classes of maximum rooting depth in order to
determine the distribution of deep roots at the plant community level. Another feature
which has deserved some attention was the spatial distribution of deep roots at the
bottom of the trenches. With this purpose a chi-square goodness-of-fit test for
randomness was performed separately on each of the six trenches, complemented by the
computation of dispersion coefficients (Sokal & Rohlf, 1995).
In order to complement the information given by the vertical root maps, core
samples were extracted from two trenches (trenches 2 and 5). On each trench, 5 vertical
transects were established, each consisting of 7 depths (10, 20, 30, 40, 60, 80, and 100
cm) for core extraction. This technique was used specifically to sample fine roots, for
which a small soil core of 68,7 cm3 was extracted using a metal ring (inner diameter of
5.4 cm) at every sampling depth. In the laboratory soil was removed using water and
roots were retained by a fine mesh sieve. Root dry weight was obtained after ovendrying the roots for 48 hours at 85 º C. Root length was obtained by counting the
intersections of the roots disposed on a grid of 1 cm x 1 cm using the line intercept
method (Marsh, 1971; Tennant, 1975). In this case no distinction was made between
species. In order to obtain an estimation of biomass and root length per unit area of soil
surface, a simple exponential model of type:
y = a.d b
(4)
67
was adjusted to the root distribution data. In this model y is the root variable
(biomass or length) at a certain depth, a and b are the model parameters and d is depth.
The model was adjusted to the means of 10 transects (r2 = 0.92 for root biomass and r2 =
0.97 for root length). Each model was integrated according to 10 cm increments from 0
to the estimated maximum rooting depth. This allowed to extrapolate the values of root
density beyond 100 cm, which was the depth limit for actual data. Similarly to the
procedure described for the distribution of root counts, an estimation of D50 was also
computed for root biomass and root length. In order to detect differences between the
two methodology approaches, values of D50 from soil cores were statistically compared
with values of D50 of root counts (only fine roots) from the same trenches.
4.3
Results
Soil characterisation
Organic matter decreased exponentially (Table 4.1) with depth, showing very
low values at 120 cm. The average thickness of the A horizon (including A1 and A2)
ranged from 39 cm (trench 6) to 102 cm (trench 4) with an overall value of 67.2±9.4
cm. Trenches 4 and 5 were presenting a thick organic layer due to relatively poor
drainage conditions at these spots. Values of pH increased with depth revealing a
decrease in exchangeable cations. According to an analysis performed on non-replicated
samples (from trench 6), the sum of exchangeable cations (Ca2+, Mg2+, Na+ and K+)
ranged between 7.87 cmol/ kg at 10 cm to 5.9 cmol/ kg at 120 cm. The same decreasing
trend could be observed in particular for potassium (K2O) but not for phosphorus (P2O5)
which was present in very low concentrations at all soil layers. Texture was relatively
homogenous along the soil profile and within trenches (sandy loam), although relatively
higher percentages of silt were observed at trench 2 and relatively higher percentages of
clay were observed at trench 4.
Table 4.1 General soil characteristics (mean±SE, n=6).
pH
K2O (mg/kg)
5.4±0.5
6.1±0.3
354.9±78.1
<8
Sandy loam
30
2.1±0.2
6.5±0.2
214.1±41.9
<8
Sandy loam
60
0.6±0.2
7.1±0.2
73.3±09.4
<8
Sandy loam
120
0.3±0.1
7.3±3.0
37.2±15.2
<8
Sandy loam
Depth (cm)
Org. mat. (%)
10
P2O5 (mg/kg)
Texture
68
Aboveground characterisation of the plant community
The two Erica species were largely dominant (Table 4.2) both in terms of stem
density (64% of the total) as in terms of basal area (84% of the total). Among the two
Erica species, E. scoparia presented the highest stem density and the highest basal area
(representing 82% and 63% of both species, respectively). The remaining three species
were far less important, Pteridium being the second most dense species (16%) and Ulex
representing the second highest basal area (9%).
Vertical mapping
Root counts on vertical maps revealed that the average root density at the
community level within the studied profile was 19.24±4.31 roots/dm2 (Table 4.3).
According to the adjustment of the MLDR model to the overall root counts, 50% of all
roots were found within the top 26 cm of soil (i.e.. D50 = 26 cm). Considering all root
counts distributions, the MLDR model was able to explain between 96.9% and 99.9% of
the variance.
When considering the different species separately, the results for the two Erica
species represented the highest average density of roots (59%), followed by Ulex (34%),
Rubus (6%) and Pteridium (1%). Root densities of the four species were significantly
different (p<0.05) for fine and for small but not for medium and coarse roots. Fine roots
represented 96% of the overall (all species) root density. This proportion of fine roots
was similar in all species except in the case of Pteridium (76%). With the exception of
Pteridium, all species presented significantly higher root densities for fine and small
roots and non-significant differences for medium and coarse roots. Most part of
rhizomes from Pteridium were classified as decaying roots (65%). Decaying roots
represented only 3 to 4% for the remaining species.
Table 4.2 Aboveground plant cover before trench excavation. Basal area is the sum of individual cross
sections measured at the stem base per m2 (mean±SE, n=6).
Species
Erica
Stem density (n/m2)
Basal area (cm2/m2)
17.4±4.6
29.5±5.6
Pteridium
4.5±1.8
1.7±0.6
Rubus
3.2±0.8
0.7±0.2
Ulex
2.1±0.7
3.0±0.9
27.2±3.2
34.9±4.3
All species
69
Table 4.3 Average root density (number of root counts/dm2) including all depths (mean±SE, n=6). Means
followed by the same letter are not significantly different (p<0.05) according to the Mann-Whitney U test.
The first letter refers to differences among diameter classes (columns) and the second letter refers to
differences among species (rows). Symbol “_” represents no data.
Species
< 1 mm
Erica
1-5 mm
5-10 mm
> 10 mm
All diameters
11.16±4.06 a,ax 0.22±0.06 bb,ax
0.01±0.00 c,ax
0.01±0.00 c,ax 11.41±4.11 ax
Pteridium
0.10±0.04 a,cx 0.02±0.01 ab,cx
0.00±0.00 b,ax
0.00±0.00 b,ax
Rubus
1.12±0.38 a,bx 0.04±0.01 bb,cx
0.00±0.00 c,ax
Ulex
6.36±1.87 a,ab 0.10±0.02 bb,bx
0.01±0.00 c,ax
0.01±0.00 c,ax
18.75±4.23 a,xx 0.39±0.06 bb,xx
0.03±0.01 c,xx
0.02±0.01 c,xx 19.24±4.31xx
All species
_
0.13±0.05 cx
1.16±0.39 bx
6.48±1.89 ab
The vertical distribution of root counts (Fig. 4.2) was considerably different for
each species. Erica presented the highest root densities at all depths with a single
exception at the 90-100 cm layer where Ulex presented a higher value. The values of
D50 obtained from the mean root distribution were higher for Ulex (40 cm) and Erica
(22 cm), and lower for Pteridium (9 cm) and Rubus (3 cm). All species presented roots
at all studied depths except Pteridium which did not present roots below 80 cm of soil
depth, as obtained from vertical map counts. All species have shown a consistently
decreasing trend with depth except Ulex, which presented a peak of root counts at the
20-30 cm layer.
Roots were more concentrated at upper layers for increasing root diameter (Fig.
4.3). The value of D50 for fine roots was considerably higher (25 cm) when compared to
the other classes (10 cm for small roots, 6 cm for medium roots and 4 cm for coarse
roots). Roots from all diameter classes were found down to 120 cm except coarse roots
which were not found below 110 cm in any of the studied trenches.
When considering trenches separately a significant positive correlation was
observed between the overall D50 of each trench and the average thickness of the A
horizon (r2 = 0.68; n = 6).
Estimation of maximum rooting depth
The horizontal maps revealed that 77% of all roots detected at the bottom of the
trenches were roots from Erica and 23% were roots from Ulex. The mean estimated
maximum rooting depth of all Erica plants was 222.1±10.1 cm (n=6). This value was
obtained using the averages of the 28 deepest roots of each trench.
70
Root dens ity (n/dm2 )
0
10
20
30
Root dens ity (n/dm2 )
0
40
1
2
3
4
5
0-10
Depth (c m)
20-30
40-50
Pteridium
Erica
9 cm
60-70
22 cm
80-90
100-110
0,0
0
2,5
0,5
5
1,0
7,5
10
0,0
0
5
0,5
10
15
1,0
20
0-10
Depth (c m)
20-30
40-50
60-70
Rubus
Ulex
3 cm
40 cm
80-90
100-110
0,0
0,5
1,0
0,0
0,5
1,0
Fig. 4.2 Average density of root counts for each species including all diameters. (mean±SE, n=6). Insets
represent the MLDR model fitted to the cumulative root fraction. Horizontal lines and corresponding
depths indicate the value of D50.
The value 28 corresponded to the minimum number of deep roots mapped in a
single trench (trench 2) within the six trenches. The estimated maximum rooting depth
for the deepest root was 329 cm. When considering the 6 trenches separately, the
estimated maximum rooting depth ranged from 192.8±5.5 cm at trench 4 to 256.1±5.9
cm (n=28) at trench 1 (Fig. 4.4).Although we could not find an equation to estimate the
maximum rooting depth of Ulex, most observed plants had very deep reaching tap roots
and the deepest root mapped was at 214 cm deep.
71
Root dens ity (n/dm2 )
Root dens ity (n/dm2 )
0
10
20
30
40
50
0
1
2
3
4
5
0-10
Depth (c m)
20-30
40-50
< 1 mm
1-5 mm
10 cm
60-70
25 cm
80-90
100-110
0,0
0
0,2
0,4
0,5
0,6
0,8
1,0
0,0
0
1
0,1
0,5
0,2
0,3
1,0
0,4
0-10
Depth (c m)
20-30
> 10 mm
5-10 mm
40-50
4 cm
6 cm
60-70
80-90
100-110
0,0
0,5
1,0
0,0
0,5
1,0
Fig. 4.3 Average density of root counts for each diameter, including all species (mean±SE, n=6). Insets
represent the MLDR model fitted to the cumulative root fraction. Horizontal lines and corresponding
depths indicate the value of D50.
Moreover the average diameter of Ulex roots was higher (11.3±2.4 mm) than the
average root diameter of Erica (7.3±0.5 mm) although the difference was not
statistically significant. The estimated distribution of maximum rooting depths (Fig. 4.5)
indicated that 82% of roots growing deeper than 125 cm were not reaching more than
175 cm in depth. A chi-square test for a Poisson distribution goodness-of-fit, showed for
each trench that the distribution of roots was not random (distribution rejected at
p<0.001). The coefficient of dispersion (estimated variance/estimated mean) ranged
from 3.0 to 7.1, thus indicating a markedly clumped distribution of deep roots.
72
Fig. 4.4 Schematic representation of the estimated average maximum rooting depth (mean of the deepest
28 roots) of Erica plants at each trench. The solid line represents the soil surface. The broken straight line
represents the maximum depth of excavation (bottom of the trenches). Both the above and the
belowground parts of each plant have been drawn to scale in order to represent the average height and the
average maximum rooting depth respectively. Each trench is represented by an image obtained from an
Erica scoparia individual.
Root density (n/dm2)
0
0,5
1
1,5
125-149
150-174
Depth (cm)
175-199
200-224
225-249
250-274
275-299
300-325
> 325
Fig. 4.5 Distribution of the estimated maximum rooting depths of Erica (mean±SE; n=2, n=3 and n=4 for
the first, second and third depth classes, respectively; n=6 for the remaining classes).
73
Core samples
Values of root length density ranged from 4.6±0.7 cm/cm3 at 10 cm of soil depth
to 0.8±0.2 cm/cm3 at 80 cm of soil depth. Values of root biomass ranged from 7.7±2.8
mg/cm3 at 10 cm of soil depth to 0.6±0.2 mg/cm3 at 40 cm of soil depth. According to
the results shown on Fig. 4.6, the distribution of fine root biomass was similar (D50 = 12
cm) to the distribution of fine root length (D50 = 14 cm), although displaying a much
higher variability. The MLDR model was able to explain 99.6% (biomass) and 99.7%
(length) of the variance. Values of D50 were significantly lower (p<0.001 ) than the
value obtained with root counts for fine roots. The integration of the exponential model
fitted to the average root distribution from core samples, allowed to estimate fine root
biomass per unit area as 1.6 kg/m2 and the respective root length as 18.7 km/m2.
Root biomas s (mg/c m3 )
0
2
4
6
8
Root length (c m/c m3 )
10
12
0
2
4
6
8
10
20
30
Depth (c m)
40
60
12 cm
14 cm
80
100
0,0
0,5
1,0
0,0
0,5
1,0
Fig. 4.6 Biomass and length of fine roots per unit of soil volume (mean±SE, n=10) as obtained from core
samples. Gaps at 50 cm, 70 cm and 90 cm on the y axis correspond to non-sampled depths. Insets
represent the MLDR model fitted to the cumulative root fraction. Horizontal lines and corresponding
depths indicate the value of D50.
74
4.4
Discussion
Our results have showed the existence of quite distinct patterns of root
distribution for the species present at the plant community. The different root
distribution patterns may be associated to the existence of distinct ecological strategies
for water and solute uptake. In fact the results suggest the existence of a niche
separation (Casper & Jackson, 1997) among the four species associated to different
adaptive strategies. Root distribution patterns from vertical maps essentially reflected
the root distribution of individual plants from each species as could be observed at the
study site. Erica plants were showing what was described by Canadell & Zedler (1995)
as a dual root system consisting of deep tap roots and laterally spreading roots at the
upper layers. Plants of Ulex, were also deep rooted but not showing an important lateral
root development at upper layers. The consequent lower development of fine roots at
upper layers accounted for the peak of root counts below the first 20 cm and the higher
value of D50. The clumping distribution of roots at the bottom of the trenches is in
accordance with the root system architecture of individual Erica and Ulex plants. In fact
tap roots were growing in a nearly vertical direction, thus originating a patchy
distribution of roots on the horizontal maps, each patch apparently belonging to one
individual plant. Deep roots are fundamental for plants to overcome the water stress
verified in the upper soil layers typical of mediterranean conditions during the dry
season (Canadell et al., 1996). This rooting pattern has been found to be typical of
climates with a dry summer and important winter rainfall (Shenk & Jackson, 2002b)
which is in accordance with the conditions of the study site. However in this specific
case it is possible that more roots have been preferentially growing vertically due to
neighbour competition (Atkinson, 1978) because of the extreme density of the stand.
Besides the competition between plants of the same species, it is very likely the
existence of inter-specific competition. Although we have not approached this specific
aspect, different works refer the existence of asymmetric competition in mixed stands
(e.g. McKay, 1988; Casper & Jackson, 1997; Leuschner et al., 2000) as a result of
distinct levels of soil exploitation efficiency by different species. In the case of Rubus,
individual plants were showing a high density of fine roots close to the soil surface but
also having a few deeper roots. This explains the low value of D50 and the decreasing
pattern obtained with vertical root counts. Pteridium plants were showing a dense
network of horizontally oriented rhizomes very close to the soil surface, to which
relatively sparsely distributed fine roots were directly connected. About this species we
75
should take into account its particular characteristics in terms of life cycle. In fact the
life cycle of Pteridium is highly seasonal (Pakeman & Marrs, 1994) leading to a high
variability in aboveground structures (fronds decay at the beginning of the cold season),
but apparently also belowground as could be observed in this study by the high
percentage of decaying rhizomes. In this way our results should be interpreted taking
into account the fact that they report observations made during the growth period (June
- August), thus reflecting the characteristics of this species in this particular season.
Root distribution differences between each diameter class are partially a
consequence of the preferential location of structural roots from the different species at
upper soil layers. In the particular case of medium and coarse roots there was a
considerable contribution of Pteridium rhizomes for the obtained results. These roots
located at upper soil layers play a fundamental role in plant anchorage (Coutts, 1983;
Fitter & Ennos, 1989) and in soil stability (Ziemer, 1981). Thus the deeper and more
uniform distribution of finer roots and the shallower and more heterogeneous
distribution of coarser roots is not surprising even if different species were contributing
to this pattern. Since this is, to our knowledge, the only study about the root distribution
of an Erica-dominated shrub community, it is difficult to have other references for
comparison. Moreover among the panoply of methods which can be found in the
literature, most of them are based on biomass estimation rather than root counts. This is
evident in the compilation of eleven sclerophyllous shrubland root distribution studies
of different regions presented by Jackson et al. (1996), where all of them are biomass
studies. In this work and also in the seventeen studies compilation by Shenk & Jackson
(2002a) the overall root distribution for sclerophyllous shrublands provided an average
D50 estimate of 19 cm which is lower than our estimate based on root counts (26 cm).
Another compilation of fine root (in this case, roots ≤ 2 mm diameter) data from six
sclerophyllous vegetation studies by Jackson et al. (1997) indicated a value of 14 cm for
D50 which is much lower than our estimate for fine roots based on root counts (27 cm),
but exactly the same as our estimate for fine roots based on root length. In fact we have
observed a remarkable difference between the results obtained with core samples and
those obtained with root counts. There is not always a direct relationship between root
counts and root length or root biomass and the differences between the two variables
observed in our study seem to confirm this aspect reported in other studies (Van
Noordwijk et al., 2000). Besides any methodological constraints, the final root count
distribution definitely resulted from the influence of trenches 4 and 5 which were
76
presenting a thick organic A horizon. In these trenches roots were in general more
uniformly distributed following the organic matter distribution along the profile.
In what concerns the estimation of total (dead and live) fine root biomass, our
estimates are higher than the six study average of 0.52 kg/m2 referred by Jackson et al.
(1997) and higher than the value of 0.78 kg/m2 estimated by Martinez et al. (1998) for a
mediterranean sand dune shrub community in Spain. Apparently the intricate root mat
composed of lignified Erica roots represents a higher biomass than what is reported by
the referred studies. We also admit that a small percentage of thicker roots (> 1mm)
have been included in the soil cores, hence contributing to this comparatively high
value. On the other hand, our estimates of root length density (18.7 km/m2) match well
with the estimation of 17.5 km/m2 (Jackson et al., 1997) for sclerophyllous shrubs and
trees. It is remarkable the fact that both estimates are in general higher than values
reported for forest ecosystems (e.g. Jackson et al., 1997; Vande Walle et al., 1998;
Wiesenmüller, 1998). In our case this is not surprising if we consider that the basal area
of the shrubland under study was higher than the normal values of adult forest stands
conducted for timber production (20-30 m2/ha for most species of the temperate region).
Many works express the root occupation in the soil by computing the average distance
between roots instead of the root length density. Distance between roots can be
computed as the inverse of root length density (Miller & Ng, 1977). In our case the
distance between roots estimated for the first meter of soil depth was 0.9 cm. This is a
much lower value than the 2.0 cm estimated by Kummerow et al. (1977) for a
Californian chaparral, the 2.8 cm estimated by Hoffmann & Kummerow et al. (1978)
for a Chilean matorral and the values of 1.9 cm and 1.7 cm estimated by Martinez &
Rodriguez (1988) and Martinez et al. (1998) for shrub communities in Southern Spain.
The higher soil occupation by roots verified in this study reveals an important difference
in terms of the belowground characteristics of a thick maquis when compared with the
sparser shrub communities studied in the referred studies. Besides the different floristic
composition of our shrub community, we may speculate that the existence of such an
important soil occupation is only possible because of the relatively high nutrient content
and the high (for Mediterranean standards) values of precipitation verified. Thus there
seems to exist a different pattern of belowground occupation at more mesic
mediterranean sites such as in our case.
Our estimates of maximum rooting depth for the two Erica species are
reasonably close to the values reported by Canadell et al. (1996) for other Ericaceae
77
(Arbutus unedo, 350 cm; Erica arborea, 200 cm). The estimated distribution of
maximum rooting depths suggests that the bulk of deep roots was roughly located
within a 50 cm soil layer between 125 cm and 175 cm, and that only few roots reached
deeper soil layers. The reasons for this distribution were not assessed within the scope
of the present study but we may speculate that deeper roots can be associated to higher
aboveground biomass and leaf surface (i.e. bigger plants) as suggested by Schenk &
Jackson (2002b). Since this are the first data to our knowledge on the root distribution
of Ulex, no additional information was available from the literature reporting the
maximum rooting depth of Ulex plants or even of other phylogenetically close
leguminous shrubs. However our results strongly suggest the existence of root systems
at least as deep as those studied for Erica. When applying the same allometric
relationship found for Erica to Ulex, we have obtained an absolute maximum rooting
depth of 349 cm and an average for the 28 deepest roots of each trench of 221 cm. The
importance of water uptake by deep roots was confirmed by Silva et al. (2002) for this
same shrub community. Moisture measurements have revealed a cumulative soil water
depletion at the end of the dry season of 18 mm at the 160-180 cm depth layer and 12
mm at the 120-140 cm depth layer.
Although many questions will remain to be answered concerning the
belowground structure of mediterranean shrublands and its vital role for the functioning
of these plant communities, the present work may help understanding some of these
aspects, in particular for Erica dominated maquis, common in the western
Mediterranean Region. Further studies on this type of plant communities, namely those
directed to belowground physiological processes, may benefit from the results presented
here.
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81
5 FIRE EFFECTS ON SOIL WATER DYNAMICS IN A
MEDITERRANEAN SHRUBLAND4
Abstract: With the purpose of studying the effects of fire on the natural dynamics of
soil water, an experiment was set in a mediterranean shrubland in Central West
Portugal. Soil moisture was measured in two closely located plots at six depths down to
170 cm, during 2000 (reference period) and after an experimental fire set on one of the
plots in June 2001 (treatment period). Moisture differences between homologous days
(i) of the treatment and the reference periods were computed both for the control (Dci)
and for the burned (Dbi) plots. Results showed significantly higher values of Dbi both at
the dry and at the rainy seasons. Values of Dci were subtracted from Dbi in order to
estimate the net effect of fire on soil water storage (Si). Values of Si showed a maximum
of 108.2 mm in the dry season and a maximum of 145.2 mm in the rainy season. At the
upper soil layers values of Si decreased as vegetation recovery proceeded along the dry
season.
Key words: Fire effects, soil water, mediterranean ecosystems, Root distribution
4
Based on paper: Silva J.S., Rego F.C. & Mazzoleni S. (2002). Fire effects on soil water dynamics in a
mediterranean shrubland. In Proceedings of the 4th International Conference on Forest Fire Research. Luso,
Portugal.
82
5.1
Introduction
The effects of fire on mediterranean ecosystems have been thoroughly studied
all over the five Mediterranean Regions of the World. However the knowledge
concerning the effects of fire belowground is still very limited. One of the major aspects
to be understood is the effect of fire on the natural dynamics of soil water, since it is the
basic limiting factor for plant growth in mediterranean ecosystems. Immediate
consequences of fire are the elimination of the transpiring surface of plants and the
exposure of soil to the direct action of meteorological agents. These two basic
consequences have opposed effects in terms of soil water (Pyne et al., 1996; Zwolinski,
2000). When compared to undisturbed situations, the elimination of plant transpiration
leads to an increase of soil water storage (Tiedmann et al., 1979), whereas the exposure
of soil to rain, wind and solar radiation contributes to a lower water content. At the
surface soil layers water is lost by direct evaporation. Also the effect of rainfall on soil
water recharge is diminished due to a decrease in infiltration accompanied by an
increase in runoff. Different works report the formation of an hydrophobic soil layer
after intense fires (e.g. DeBano, 1966; Ferreira, 1990; Midoun et al., 1998). This
process works together with the absence of vegetation cover and both are responsible
for the lower infiltration rate, thus contributing to reduce water content and to increase
runoff (DeBano, 2000). The relative importance of each of these processes depends on
fire intensity, vegetation type, soil/relief characteristics and meteorological conditions.
Few works report on the consequences of fire on soil water storage. Rego &
Botelho (1992) found slightly higher moisture contents during summer at a high
intensity prescribed burning plot, when compared with a low intensity and a control
plot, in a young Pinus pinaster stand. Klock & Helvey (1976) have detected
considerably lower soil water deficits in a mature mixed conifer forest during the years
following a wildfire. Similar results were obtained by Soto & Diaz-Fierros (1997) in a
mediterranean shrubland dominated by Ulex europaeus. However Campbell et al.
(1977) reported a lower soil water content one year after a wildfire in a Pinus ponderosa
burned stand, when compared to an undisturbed nearby plot. In this case only surface
(down to 30 cm) moisture was measured and soil water differences in the burned area
were attributed to increased evaporation and runoff. Contradictory conclusions about
the effects of fire on soil water where reported by Wells et al. (1979) referring to studies
from various sources. The existence of different conclusions from different studies
83
reflects two opposite processes: the increase of evaporation from the immediate subsurface and the decrease of plant transpiration affecting the whole profile. Given that
these two mechanisms have different expression at different soil layers it is important to
study the whole soil profile, if possible down to the maximum rooting depth and taking
into account the root distribution of plants.
The study of fire effects on soil water may help understanding the frequently
studied dynamics of vegetation in the post-fire period. This knowledge is particularly
important for mediterranean ecosystems where soil water is the basic limiting factor for
plant growth. The present study aims to contribute to a better knowledge of this specific
aspect of fire effects in mediterranean ecosystems. In particular, we aim to determine
the effect of a simulated wildfire on soil moisture dynamics at different soil layers in a
typical mediterranean shrubland in Central West Portugal.
5.2
Methods
The study was carried out at Tapada Nacional de Mafra in the Central West
Region of Portugal. Tapada Nacional de Mafra is a protected area with 827 ha, about 30
km Northwest of Lisbon and 12 km East from the coast (38º 58’ 30’’ N and 9º 15’ 52’’
W). The lowest altitude is 90 m and the highest is 358 m. Soils are humic cambissols
derived from sandstone. Mean annual precipitation is 798 mm and mean annual
temperature is 14.6 ºC. June, July and August are the three driest months accounting for
only 3.1% of total annual rainfall.
The study area was a shrubland dominated by Erica scoparia L. and Erica
lusitanica Rudolphi, both species being hereafter referred to as Erica. Other important
species were Crataegus monogyna Jacq., Ulex jussiaei Webb, Daphne gnidium L.,
Rubus ulmifolius Schott. and Pteridium aquilinum (L) Kuhn. The experiment was
designed as two neighbouring plots with four internal replications, each replication
consisting of one tube for moisture measurement. Plots and replications were disposed
linearly along a contour line on a 15% slope. One plot was kept intact as a control
(control plot) and the other was burned (burned plot) by an experimental fire on the 4th
of June 2001. Fire was planned to simulate a typical summer fire for which an area of
approximately 0,2 ha was burned using fire torches. During the fire treatment air
temperature ranged from 23.3 ºC to 28.7 ºC, relative humidity ranged from 81% to 82%
and wind ranged from 1.5 m/s to 2.8 m/s. Within each plot replications were separated
by 8 meters and the 2 plots were separated by 27 meters including a fire-break, 10 m
84
wide. On each plot soil moisture (% volume) was measured using a TDR (Time Domain
Reflectometry) equipment consisting on a measuring device (TRIME-FM3; IMKO
GmbH, Ettlingen) connected to a tube-access probe (TRIME-T3). The probe was driven
inside Tecanat tubes inserted in the soil, 2 m deep, in order to measure moisture at
different soil layers. During fire, tubes (the remaining aboveground top) were covered
with sacs filled with soil in order to insulate them from high temperatures. For each tube
two crossed measurements were made at 15 cm, 30 cm, 50 cm, 90 cm, 130 cm and 170
cm, from April 2000 to December 2001. Moisture measurements were part of a broader
study, but for the purpose of the present study two measuring periods were considered:
a reference period from the 4th of June 2000 to the 20th of December 2000 and a
treatment (post-fire) period from the 4th of June 2001 to the 20th of December 2001.
Within each period we have distinguished a dry season going from the 4th of June to the
19th of September and a rainy season going from the 21st of September to the 20th of
December. The 19th and the 21st of September were coincident with the first significant
rain (> 10 mm precipitation) marking the end of the dry season, for 2000 and 2001,
respectively. In average measurements were made once every two days although during
periods with no precipitation only one measurement per week was made. Due to
equipment problems the largest interval between consecutive measurements was 17
days in July 2000. Meteorological data was obtained on a daily basis along the whole
period of measurements using a Weather Monitor II station (Davis Instruments Co., San
Francisco) located 2 km away from the experiment.
According to laboratory analysis of the 48 samples taken at all measurement
depths of all replications, soil texture was classified as a sandy loam although a few
samples have been classified as loams (3 samples from the burned plot and 2 samples
from the control plot) and silt loams (2 samples from the control plot). The vertical root
distribution for each of the two plots was determined by counting the number of root
tips on 3 m long trench walls located at the lower part of the slope, 4 m away from each
tube. Roots were drawn and counted on plastic sheets down to 120 cm. Besides the
exclusion of obviously decaying roots, no distinction between dead and live roots was
attempted. Maximum rooting depth was indirectly accessed for the two dominant Erica
species by using an allometric relationship between root diameter and vertical distance
down to the root apex. Estimation of maximum rooting depth was obtained by
measuring the diameters of the cut root at the bottom of the trenches and then using the
allometric relationship to determine the correspondent vertical distance (Silva & Rego,
85
unpublished). Vegetation was characterised in terms of plant height, number of stems
and basal area (sum of cross sectional areas per square meter) on each of the two plots.
The colonisation of the burned area was followed until October 2001 simply by
counting the number of P. aquilinum fronds, the number of resprouting Erica plants and
by estimating the respective average height on a 1,6 m2 plot close to each tube.
All statistical comparisons between plots, between periods and between depths
were performed using one mean value for each replication (i.e. sample size=4). Gaps
between measurements were filled using linear interpolations. The effect of fire on soil
water was assessed by comparing the moisture differences between each day (i) of the
treatment period (Mti) and the homologous Julian day of the reference period (Mri),
obtained at the two plots. The use of moisture differences from two years to compare
plots was preferred to the simple use of raw data from one year. In fact given the
reduced number of replications, even small variability levels within plots would have
been sufficient to hide the effects of fire. The distribution of moisture differences
(Di=Mti-Mri) was tested for normality using a Kolmogorov-Smirnov test. The mean
values of Di of the control plot (Dci) were compared with the mean values of Di of the
burned plot (Dbi) for each depth using t tests. Multiple comparisons between depths
were performed using Tuckey tests. Values of Dbi and Dci were converted into mm of
soil water and estimated down to 180 cm deep, by integrating measurements using 20
cm increments. Since the distinct meteorological conditions of the two periods have also
accounted for part of Dbi, these values were compared with Dci. Given that
meteorological conditions were similar in both plots, the difference (Si) between Dbi
and Dci was assumed to correspond to the net effect of fire on soil water storage.
5.3
Results
Before fire the two plots showed a similar plant cover. The average shrub height
was 196±20.6 cm for the control plot and 187±34.8 cm for the burned plot. The average
stem densities were 26±3.2 stems/m2 and 29±5.2 stems/m2, respectively. The average
basal area (the sum of cross sectional areas at the stem base, per unit area) were 41±5.4
cm2/m2 and 29±5.0 cm2/m2, respectively. The two Erica species were largely dominant
both in terms of stem density (58±12.7% and 56±24.7% for the control and the burned
plots respectively) as in terms of basal area (87±5.8% and 71±16.2%, respectively). The
remaining species were far less important, P. aquilinum being the second most dense
86
species (18±8.0% and 20±16.6%, respectively) and U. jussiaei representing the second
highest basal area (10±3.8% and 16±7.6% respectively).
Fire killed nearly all aerial parts of plants and the litter/duff layer was reduced
by 1.5 to 4 cm. Resprouting of plants started two weeks after fire. Fronds of P.
aquilinum and resprouts from the two Erica species were the first signs of vegetation
recovery (Fig. 5.1). Seven weeks after fire the number of resprouting plants of Erica
had stabilized and the number of P. aquilinum fronds attained 83% of the maximum
registered. Erica attained a maximum of 3.5 resprouting plants per square meter and a
maximum average height of 14.2 cm. P. aquilinum attained a maximum average density
of 8.6 fronds per square meter and a maximum average height of 63.7 cm. This
maximum size for P. aquilinum was followed by a decrease in October, when fronds
started decaying.
In both plots roots were distributed following a typical exponentially decreasing
curve. The first 20 cm of soil contained 36% and 28% of all roots counted respectively
in the control and the burned plots (Fig. 5.2). However roots extended much below the
120 cm deep studied profile. The relationship used to estimate the maximum rooting
depth (r2 = 0.89, n = 64) was a typical logistic function of form y=a/[1+(x/b)c] where a,
b and c are constants, x is the root diameter and y is the correspondent vertical distance
to the root apex. The rooting depth of the 28 deepest Erica roots of each trench was
estimated to be 242±12.8 cm for the control plot and 206±7.4 cm for the burned plot.
According to the observations made on completely excavated individual root systems of
Average height (cm)
250
2
200
1,5
150
1
100
0,5
50
0
0
Nr. plants or fronds/m2
Erica spp. and U. jussiaei plants, both species present nearly vertical deep tap roots.
1
1
1
3
2
1
2
4
pre
-fir -6-01 8-6-0 7-7-0 5-7-0 -8-01 0-8-0 1-9-0 9-10
-01
e
1
1
1
1
1
Fig. 5.1 Evolution of plant cover during the treatment period. Triangles and diamonds represent Erica and
P. aquilinum respectively. Open symbols/dashed lines refer to plant height whereas closed symbols/solid
lines are the density of P. aquilinum fronds or resprouting of Erica plants.
87
Root dens ity (n/dm 2)
0
10
20
30
40
Root dens ity (n/dm 2)
50
0
10
20
30
40
50
0-10
Depth (c m )
20-30
40-50
60-70
80-90
100-110
Control plot
B urned plot
Fig. 5.2 Root density (number of root counts/dm2) at the control and the burned plots (mean±SE). Data
collected before fire.
50
40
30
20
10
0
60
50
15 c m
30 c m
50 c m
90 c m
130 c m
170 c m
40
30
20
10
0
30
70
25
60
20
50
15
40
30
10
20
5
10
0
04-06
0
01-07
28-07
24-08
20-09
Tim e
17-10
13-11
10-12
04-06
01-07
28-07
24-08
20-09
17-10
13-11
A ver. daily tem p. (º C)
S oil m ois ture (% vol.)
S oil m ois ture (% vol.)
BURNED PLOT
TREATMENT PERIOD (2001)
80
Rainfall(m m )
CONTROL PLOT
REFERENCE PERIOD (2000)
60
10-12
Tim e
Fig. 5.3 Values of soil moisture for each plot in the two study periods with the corresponding
meteorological data (bars and solid line represent rainfall and average daily temperature, respectively).
88
Rhizomes from P. aquilinum did not go deeper than 80 cm with 50% of all roots located
within the first 7 cm of soil.
The values registered for precipitation were quite different when comparing the
rainy season of the reference (2000) and the treatment (2001) periods, but very similar
during the dry season. Total rainfall was 29.3 mm during the dry season of the reference
period and 561.4 mm during the rainy season. In the treatment period total rainfall was
25.2 mm in the dry season and 242.6 mm in the rainy season (Fig. 5.3). In both plots
and in both periods, soil moisture followed a general pattern which can be described as
a decreasing trend along the dry season and a sudden increase as the wetting front
reached the different soil layers along the rainy season. This pattern varied according to
each of the studied depths. The 15 cm soil layer presented the highest variation of water
content in both study periods (SD =9.6), whereas the 170 cm soil layer presented the
lowest variation (SD=3.2). In general each layer presented a typical moisture pattern
along each study period in particular during the dry season. In average the wetting front
took between 44 (15 cm) and 74 days (170 cm) to reach the different soil layers after the
beginning of the rainy season. In general terms fire caused a change in the typical
decreasing patterns of soil moisture in the dry season, in particular at deeper soil layers,
where roughly constant values were observed at the burned plot. At the beginning of
each period (4th of July) the average moisture content was very similar (36.2% for the
reference period and 35.9% for the treatment period; see Fig. 5.4) and not significantly
different. Although no analysis concerning the hydraulic properties of the soil had been
performed at this stage, the method developed by Saxton et al. (1986) using texture
based empirical relationships, indicated a field capacity between 18% and 26%, a
wilting point between 8% and 14% and a saturation water content between 39% and 47
%. The average values of Dbi were higher than the average values of Dci, both within
the dry and the rainy seasons (Table 5.1). These values were significantly higher at all
depths except at 130 cm and 170 cm in the dry season and at 15 cm in the rainy season.
When considering both seasons together, all depths provided significantly higher values
of Dbi. During the dry season the average Dbi showed a maximum at 50 cm
(5.93±0.43%) and a minimum at 130 cm (3.08±0.95%). During the rainy season the
average Dbi showed a maximum at 170 cm (8.29±2.23%) and a minimum at 15 cm
(2.83±0.58%). The values of Dci ranged from -1.93±0.68% (15 cm, dry season) to
89
3.08±0.29% (30 cm, rainy season). Comparisons between depths provided significant
differences for both plots at both seasons except for the burned plot in the dry season.
Moisture differences between periods for the control (Dci) and the burned (Dbi) plots
revealed distinct patterns at all soil layers (Fig. 5.5). In general Dbi showed consistently
higher values than Dci, thus positive values of Si. The exceptions were the first two soil
layers where negative values of Si were observed by middle November and also the
initial period after fire at all layers. In general Dbi curves showed positive values while
Dci showed values close to zero. The exceptions were the last 28- 16 days (depending
on the soil layer) of the study, when a strong decrease was exhibited by the two curves
due to heavy rainfall in the reference period. At the first soil layer (0-20 cm) there was
an initial strong increase of Si followed by a decrease after middle July. This decreasing
trend started later for the 20-40 cm layer (early August) and the 40-60 cm layers
(middle August) and it was practically absent at deeper layers during the whole study
period. At the 80-100 cm soil layer and below this depth, Si has basically increased
along the whole study period. In particular the deepest layer (160-180 cm) showed a
stabilisation around 16 mm of soil water after the end of the dry period. The overall (0180 cm) values of Si have increased until middle August and then have stabilised around
100 mm until October. Eight days before the end of the dry season the overall values of
Si showed a maximum of 108.2 mm. However the highest values of the overall Si were
attained by middle October showing a peak of 145.2 mm. By the end of the study
period, the overall Si had stabilised around 107 mm of soil water.
90
45
S oil moisture (% vol.)
40
35
30
Fire
25
20
Control plot
B urned plot
15
10
03-05-01
18-06-01
03-08-01
18-09-01
03-11-01
19-12-01
Time
Fig. 5.4 Average soil moisture of the control and the burned plots during the treatment period and two
weeks before fire.
Table 5.1 Mean ± SE values of Di (soil moisture differences in terms of % volume, between the treatment
and the reference periods). Means sharing the same letter are not statistically different (p >0.05, n=4).
Letters in the first column refer to comparisons between plots within each season (t tests). Letters in the
second column refer to multiple comparisons between depths (Tuckey tests).
Depth
Dry season
Control
Rainy season
Burned
Control
Burned
15 cm
-1.93±0.68 a, a
3.71±0.74 b, a
1.94±0.20 a, bc
2.83±0.58 a, a
30 cm
-0.07±0.22 a, ab
4.38±0.84 b, a
3.08±0.29 a, c
4.72±0.56 b, ab
50 cm
0.09±0.33 a, ab
5.93±0.43 b, a
2.69±0.75 a, bc
7.12±0.44 b, ab
90 cm
1.78±0.99 a, b
4.96±0.45 b, a
0.53±0.50 a, abc
6.26±0.70 b, ab
130 cm
1.35±0.52 a, b
3.08±0.95 a, a
170 cm
1.84±0.75 a, b
4.76±0.98 a, a
-0.73±0.99 a, a
0.12±0.40 a, ab
6.13±0.97 b, ab
8.29±2.23 b, b
91
0 - 20 cm
30
10
-10
-30
20 - 40 cm
30
10
-10
-30
40 - 60 c m
30
10
-10
-30
80 - 100 cm
SOIL WATER (mm)
30
10
-10
-30
120 - 140 cm
30
10
-10
-30
160 - 180 cm
30
10
-10
-30
250
0 - 180 c m
150
Si
50
-50
-150
Dbi
04
-0
6
01
-0
7
28
-0
7
24
-0
8
20
-0
9
17
-1
0
13
-1
1
10
-1
2
Dci
Fig. 5.5 Differences in soil water storage between the treatment and the reference periods in the burned
(Dbi) and the control (Dci) plots. Si = Dbi - Dci represents the effect of fire on soil water. Si is represented
by a moving average (n=7). Estimation for 0-180 cm is an integration using 20 cm increments.
92
5.4
Discussion
According to our results fire has definitely modified the soil water dynamics of
the studied shrub community. These differences could be detected not only during the
dry season where it would be more obvious due to the strong decrease in transpiration,
but in general along the whole study period. The establishment of a dry season and a
rainy season based on a precipitation threshold, had the simple purpose of separating the
period with no significant water inputs, from the period of typical soil water recharge
due to rainfall. However this distinction had a different meaning for different layers
since the deepest layers had continued the same dry season trend much beyond its end
whereas the upper soil layers had a more immediate response to the first Autmn rains.
In fact each soil layer has a specific drying period followed by a wetting period as the
wetting front reaches the corresponding depth. Another aspect to take into account in
what concerns the timings established within this study, has to do with the date of
burning. Results could had been considerably different if fire was set later in the dry
season. For example, a September fire would certainly have a different effect because of
a lower vegetation recovery due to a shorter growth period and lower water availability
for plant growth. In such a case, the effects verified in this study could be expected to
occur in the following growing season, as observed by Klock & Helvey (1976) after an
August wildfire.
The distinct patterns observed for soil water dynamics in the dry season within
the different soil layers are basically explained by the direct effect of evaporation, the
soil water extraction by roots and the water flows in the soil. All three effects
potentially contribute for a higher water depletion in the upper soil layers. As shown by
the root distribution data, most of the roots were located at the upper layers. In
particular the species which have presented the most important regenerative response to
fire, P. aquilinum, had very shallow rhizomes. In contrast to this, deeper soil layers did
not suffer the effects of direct evaporation at the soil surface and the only roots present
were essentially from Erica. This apparently explains the fact that while at the upper
layers there was a marked decrease of soil water, especially after the flush of P.
aquilinum fronds in July, at deeper soil layers there was a roughly constant soil water
content. At the upper layers this corresponded to a decrease in Dbi, presumably due to
an increasing water extraction by roots from new P. aquilinum fronds but also from new
Erica shoots. In contrast, deeper layers have shown increasingly high values of Dbi,
which is conclusive about the importance of water extraction by deep roots from Erica
93
during the dry season of the reference year. This in accordance to what has been
reported for other deep rooted species in different Mediterranean Regions (Canadell &
Zedler, 1995) and in general for the role of deep roots in most ecosystems (Canadell et
al., 1996).
During the rainy season, different patterns of soil water recharge could be
associated to different soil layers. These patterns basically reflected the time that the
wetting front took to reach the different depths. Again it was observed a much quick
and sensitive response from the upper layers (0-40 cm) at both plots. However
differences between plots were not so consistent during the rainy season at these layers,
given the oscillation between negative and positive values of Si. Also given the diversity
of factors acting at the upper layers it is not straightforward to determine which was the
basic cause for the lower values of Si at this period and at this zone of the soil. Although
we have not been able to prove this hypothesis within the scope of the present study, we
can speculate that soil exposure at the burned plot was responsible for a higher
evaporation in the treatment period during the unusually dry November and December
months, than at the control plot.
One important consequence of our findings is related to the influence of soil
water on plant regrowth in the post-fire period. The high soil water content verified in
the present study apparently explains the quick increase of plant cover at the burned
plot. Similar post-fire conditions may be at the origin of the high water potentials and
transpiration rates observed for regenerating seeder and resprouter species (Clemente, in
prep.) in another mediterranean shrubland. However the results of this study also
suggest that the unusual dry period in late Autmn 2001 was related to comparatively
lower soil moisture levels in surface layers of the burned area, although the same area
was characterised by a higher moisture level in the previous period. Unusually dry
periods have been reported as possible critical factors which explain, in interaction with
fire, the mortality of plants during regrowth periods (Mazzoleni & Pizzolongo, 1990).
Experiments under controlled conditions showed that individuals of Erica arborea are
sensitive to water conditions during resprouting after disturbance (Mazzoleni &
Esposito, 1993). Our results confirm the interest of interactions between fire and
climatic conditions in relation to vegetation dynamics processes.
Some works report a detrimental effect of fire on soil water content (Campbell et
al., 1977; Redmann, 1978; Wells et al., 1979) in the immediate post fire period, thus
apparently showing opposite conclusions to those presented in this study. However
94
several reasons may be at the origin of these different results. In fact none of these
works was performed under the same experimental conditions as our work, namely in
what concerns the studied depths, the vegetation type, the climate and the burning
season. One of the few works confirming an increase in soil water storage after fire was
presented by Klock & Helvey (1976). The estimated increase of 108.2 mm of soil water
storage due to fire effects in September is very similar to the 116 mm reported by Klock
& Helvey (1976) for a mixed conifer forest one year after fire. However it is difficult to
take conclusions from these similar results since the study conditions were distinct in
what concerns the sampling design (no pre-fire measurements available) the burning
period (August), climate and type of vegetation. We should note that the values of Si
obtained in our study were probably overestimated at the first soil layer (0-20 cm)
during the dry season and underestimated during the rainy season. These estimations
were probably affected by the use of a 20 cm integration increment because of the
highly variable and heterogeneous nature of this first soil layer. On the other hand the
estimation for the whole profile (0-180 cm) should not be faced as the total impact of
fire on soil water storage. In fact both the water uptake by the deepest roots during the
reference period and the higher water percolation to soil layers below the studied depth
during the treatment period, may have contributed to even higher increases in soil water
storage as an effect of fire.
The results of the present study unequivocally showed the existence of a much
higher soil water content along the studied soil profile during the dry season, likely as a
consequence of the reduction of transpiring vegetation by fire. Furthermore this effect
was consistent along the whole studied period including the rainy season. Therefore, the
more thoroughly studied detrimental effects of wildfires on infiltration rates do not
seem to be the driving force controlling soil water dynamics, at least for our study
conditions. Further research will be addressed to the evaluation of these effects under
distinct field conditions and different fire characteristics and to the development of a
model of water relations in relation to fire disturbance.
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Zwolinski M.J. (2000). The role of Fire in Management of Watershed Responses. In Proceedings of
Conference Land stewardship in the 21st Century. The contributions of watershed management,.
Tucson,
U.S.A.,
367-370
pp.
96
6 MODELLING SOIL WATER DYNAMICS IN A
MEDITERRANEAN SHRUBLAND5
Abstract: A new soil water model was used to interpret the results of two extensive sets
of measurements performed in 2000 and 2001 in a mediterranean shrubland in Portugal.
One set corresponded to undisturbed vegetation (control plot) and the other to adjacent
vegetation burned by an experimental fire in the 4th of June 2001 (burned plot). The
variability in soil water was very high at the surface layers and decreased for deeper soil
levels. The comparison of the soil hydraulic properties predicted by the model against
real data provided reasonable agreements in both control and burned plots with a
coefficient of determination of 0.82. The comparison of measured and modelled soil
water measurements for 6 depths in both plots provided coefficients of determination
ranging from 0.85 to 0.69. When assessing the effects of fire, the model and actual data
showed the same basic trend (r2=0.69), revealing an increase in soil water storage.
Key words: Soil water dynamics, mediterranean shrublands, modelling, soil hydraulic
properties, fire.
5
Submitted to Annals of Forest Science by Giannino F., Silva J.S., Amato M., Mazzoleni S., Rego F.C. & Magalhães
M.C. 2003.
97
6.1
Introduction
In mediterranean ecosystems the basic limiting factor for plant growth is the
availability of water (Daget, 1977). In these conditions the distribution of rain along the
year and particularly during the dry season is critical for plant survival and plant
growth. Therefore, a comprehensive understanding of the mechanisms involving
mediterranean ecosystems has necessarily to include the study of soil water dynamics.
Given the difficulties inherent to the acquisition of soil water data along the soil profile
and during long periods of time, the possibility of using models for the simulation of
soil water dynamics, is undoubtedly attractive.
Soil water models have been developed as standalone models, but also many
times as components of larger models of crop/ecosystem dynamics. This latter
application partly explains the profusion of soil water models developed during the last
two decades. Most of these models were developed for crops and forest ecosystems,
many of them as modules of more comprehensive models, also including carbon and
nutrient flows. Reviews on ecosystem models including soil water dynamics can be
found in Ågren et al. (1991), Tiktak & Grinsven (1995), Ryan et al. (1996), and Waring
& Running (1998).
One of the problems which a soil water modeller has to solve is the
establishment of soil hydraulic properties. This is basically a problem of finding how
soil water potential varies with the soil water content. This relationship is fundamental
for determining the different water flows in the soil. With this purpose many authors
have developed empirical relationships (Mualem, 1976; Gupta & Larson, 1979; Van
Genuchten, 1980; Saxton et al., 1986;Vereecken et al., 1989) which are supposed to
apply to a wide range of soil types. Another fundamental component of soil water
models is the simulation of evapotranspiration and its relationship with water uptake by
plants and with evaporation. Also for evaprotranspiration there are multiple solutions
which can be implemented in a soil water model (e.g. Makkink, 1957; Monteith, 1965;
Priestley & Taylor, 1972). Other components may or not be included in a soil water
model depending on its importance for the target situations to be simulated. This is the
case of the role of the canopy and the litter layers on water interception before it reaches
the soil, the simulation of runoff, the simulation of water leaving the system as seepage
or even the contribution of the snowpack to soil water recharge. Also for modelling
these processes different alternatives can be found in the literature in terms of
relationships representing each one of them.
98
Few authors have been concerned with the simulation of the dynamic
mechanisms of mediterranean ecosystems (e.g. Gracia et al., 1999; Sabaté et al., 2002)
in particular in what concerns the soil water dynamics. To our knowledge none of the
soil water models described in the literature was developed or validated using data from
mediterranean shrublands. This lack of scientific information concerning the
mediterranean ecosystems was at the origin of the development of the European project
ModMED - Modelling Vegetation Dynamics in Mediterranean Ecosystems (DG XII).
The present paper is a direct result of the work developed within the frame of this
project and it approaches different aspects of soil water dynamics using data from a
shrubland in Central Portugal.
This paper aims to: i) present a new model of soil water dynamics designed for
mediterranean ecosystems, ii) test the proposed model using two data sets from
experimental plots in a mediterranean maquis in Portugal, iii) describe and interpret the
soil water dynamics of the studied shrubland, including the disturbance caused by an
experimental fire.
6.2
Methods
The model
Overview
The model SWADY – Soil Water Dynamics, presented here, was developed
using the modelling software Simile ver. 2.2 (Simulistics Ltd., Edinburgh). Details
about this modelling environment can be found in Muetzelfeldt & Taylor (2001) and at
http://www.ierm.ed.ac.uk/simile/. The model basically calculates the water content at
different soil layers along a period of time using a daily time-step. For this purpose the
soil is divided into layers each one defined by specific characteristics: thickness, organic
matter, bulk density and texture. Two sub-models allow to compute the fluxes to and
from each soil layer. The first sub-model computes the soil water retention curve
according to the soil texture and organic matter content of each layer, whereas the other
sub-model computes the evapotranspiration processes. The water inputs and outputs for
the compartment Soil water content of each defined layer are: surface infiltration (only
to the top layer), drainage-in (from each layer above), drainage-out (to each layer
below), evaporation (from the top layer) and water uptake by plants (from all defined
layers which include roots). The model diagram is shown in Fig. 6.1 and the input
99
variables necessary to run the model are listed in Table 6.1. The equations used in the
model are grouped according to the two sub-models and the five different flows.
Soil water retention curve
The soil water retention curves for each layer are estimated using the MualemVan Genuchten equation (Mualem, 1976; Van Genuchten, 1980) which allow to obtain
the soil water content (θ) as a function of the pressure head (h). This equation is defined
as:
θ(h ) = θ r
θs − θr
(1 + αh )
n m
(1)
where
θr
residual soil water content in m3 m-3(the soil water that is not bound by
capillary forces when h and dθ dh become very small)
θs
saturated soil water content in m3 m-3
α
shape parameter in m-1
n
dimensionless shape parameter
m
equal to 1 − 1 n
The parameters for this equation are estimated using the empirical pedotransfer
functions described in Wösten et al. (1999) which require information on texture, bulk
density and organic matter content. As a result, each defined soil layer is characterised
by a specific water retention curve. Threshold values for θ are computed to establish
conditions for water uptake, drainage and surface infiltration.
Auxiliary variables
DrainageLayers
ThetaAll
Differencemm
mmMax7Lay
DifferenceTheta
Climatic Input
TemperatureRH
Radiation
Precipitation
Wind
ThetaMax
n
Water Input
SOIL PARAMETERS
Uptake
Penman Monteith
Vegetation Input
EP
ETP
LAI
Clay
Org Matter
Silt
Drainage Out
Evaporation
Bulk Dens
SWC
Layers Input
TP
Potential
Drainage In
ThetaSat
Layer Thickness
ThetaLim
m
Traspiration
Theta
Root Density
Soil layers
Fig. 6.1 Schematic diagram of model SWADY drawn using the modelling environment Simile. The compartment SWC represents the Soil Water Content, circles with a cross
represent variables, thick arrows represent flows to and from the compartment and the curved thin arrows represent influences between the different model entities.
100
101
Table 6.1 List of input variables.
Type of input
Variable
Units
Climatic inputs
Air temperature
°C
Air relative humidity
%
Radiation
W m-2
Rainfall
mm
Wind
m s-1
Vegetation input
Leaf area index
m2 m-2
Soil layer inputs
Layer thickness
m
Root length density (% of total)
%, (cm cm3)
Bulk density
g cm-3
% clay
%
% silt
%
Organic matter
%
Evapotranspiration processes
Potential evapotranspiration (Etp) is estimated using the climatic inputs of Table
6.1 and the FAO-Penman-Monteith equation (Allen et al., 1998). The partitioning
between potential soil evaporation (Ep) and potential transpiration (Tp) is obtained
according to the method proposed by Ritchie (1972) using the leaf area index (LAI). Tp
was computed as follows:
(
LAI ≤ 3
Tp = Etp 1 − e −0.5 LAI
LAI > 3
Tp = Etp
)
(2)
Then Ep is computed as the difference between Tp and Etp.
Water input
Before rainfall reaches the soil surface, the model considers the influence of
canopy interception. This is computed as a proportion of LAI using an interception
coefficient equal to 0.1 mm LAI-1day-1 (Hillel, 1998). The remaining precipitation is
considered equal to throughfall plus stemflow. Then water enters the soil only until
saturation. Water above saturation is lost from the system as runoff.
102
Drainage-in
For the top layer it is the result of flow Water input. For all other layers it is a
direct consequence of the Drainage-out flow from the above layer.
Evaporation
Soil evaporation is only considered for the top layer of soil and only for a water
content above θlim. This soil water threshold corresponds to h=1020 cm. Actual
evaporation is computed from Ep using a logistic-type reduction function.
Uptake
Water uptake by plants is calculated for each layer by partitioning the overall
transpiration according to the relative root length present in that layer. Transpiration is
zero when water content drops to θlim, as calculated for each layer using the
pedotransfer functions.
Drainage-out
Drainage-out is computed using a simplified approach. For all layers drainageout occurs for all moisture in excess of saturated soil water content (θs). When soil
moisture θi is below θs, (unsaturated soil conditions) the amount of water (di) leaving a
layer i with a thickness wi to the layer i+1 is equal to:
di =
(θ i − θ i +1 )wi
2
(3)
where θi and θi+1 represent the soil water content of layers i and i+1,
respectively. Drainage-out from the bottom layer occurs when the pressure head drops
bellow 50 cm, and is lost from the system as deep percolation.
Study site
The model was tested using data collected at Tapada Nacional de Mafra in the
Central West Region of Portugal. Tapada Nacional de Mafra is a protected area with
827 ha, about 30 km Northwest of Lisbon and 12 km East from the coast (38º 58’ 30’’
N and 9º 15’ 52’’ W). The lowest altitude is 90 m and the highest is 358 m. Soils are
humic cambissols (FAO classification) derived from sandstone. According to laboratory
analysis using samples from the study site, texture was classified as a sandy loam,
although 5 samples (out of 48) have been classified as loams and 2 samples have been
classified as silt loams (FAO classification). Mean annual precipitation is 798 mm and
103
mean annual temperature is 14.6 ºC. June, July and August are the three driest months
accounting for only 3.1 % of total annual rainfall. The study area is a maquis-type shrub
community dominated by Erica scoparia L. and Erica lusitanica Rudolphi, both species
being hereafter referred to as Erica. Other important species are Ulex jussiaei Webb,
Rubus ulmifolius Schott. and Pteridium aquilinum (L) Kuhn. Two sets of data were
obtained: one from undisturbed vegetation (control plot) and another from adjacent
vegetation burned by an experimental fire in the 4th of June 2001 (burned plot).
Vegetation data
Vertical root length distributions were determined using core samples. For each
plot, 5 vertical transects were established each one consisting of 7 depths (10, 20, 30,
40, 60, 80, and 100 cm) for core extraction. Root length density (cm.cm-3) was
determined by counting the number of root intersections from each sample on a 1 cm
grid, using the line intercept method (Marsh, 1971; Tennant, 1975). Extrapolation to
deeper soil layers was achieved by adjusting a simple exponential function of type:
y = a.d b
(4)
where y is the estimated root length density, a and b are adjustable parameters
and d is depth. Leaf area index (LAI) was estimated for Erica (the dominant species) as
2.8. This value was obtained using the weight of 5 plants and then estimating the weight
and the surface of leaves using relationships from d’Armand et al. (1993) and
Fernandes & Pereira (1993) for Erica arborea. This method was preferred to the use of
direct measurements since for these species a considerable amount of radiation is
intercepted by small twigs and not by leaves. At the burned plot plant growth was
followed after fire by measuring the average plant height.
Validation data
For each plot, soil moisture was measured at 4 access tubes. All 8 tubes were
disposed linearly along a contour line on a 15 % slope. Within each plot tubes were
separated by 8 meters, and the two plots were separated by 27 meters. On each tube, soil
water content (% volume) was measured using a TDR (Time Domain Reflectometry)
equipment consisting on a measuring device (TRIME-FM3; IMKO GmbH, Ettlingen)
connected to a tube-access probe (TRIME-T3). The probe was driven inside the tubes
inserted in the soil 2 m deep, in order to measure moisture at different soil layers. Tubes
were inserted with and angle of 30º from the vertical in order to minimise the influence
104
on root development and water flows in the soil (Maertens & Clauzel, 1982; Merril,
1992). For each tube two crossed measurements were performed at 15 cm, 30 cm, 50
cm, 90 cm, 130 cm and 170 cm, from May 2000 to December 2001. For modelling
purposes layer thickness were inputted as: 7.5 cm-22.5 cm; 22.5 cm-40 cm; 40 cm-70
cm; 70 cm-110 cm; 110 cm-150 cm and 150 cm-190 cm. The layer 0 cm-7.5 cm could
not be measured given the limitations of the TDR technique used. The whole study
period represented a total of 587 days between the 13th of May 2000 and the 20th of
December 2001. Within this period, soil water content was measured for a total of 318
days. As a rule, measurements were more frequent (daily, whenever possible) during
rainy periods and less frequent during periods with no precipitation (weekly, during
summer). The largest interval between consecutive measurements was 17 days in July
2000, because of equipment problems.. Meteorological data was obtained on a daily
basis along the whole study period using a Weather Monitor II station (Davis
Instruments Co., San Francisco) located 2 km away from the experiment.
In order to verify the suitability of the pedrotransfer functions and the Mualemvan-Genuchten equation to determine the soil water retention curve to our specific case,
soil samples were submitted to different pressures using a Richards plate. Soil water
content was gravimetrically determined at different levels of pressure head in order to
obtain the soil water retention relationships for 3 x 6 samples (6 depths replicated 3
times) at each plot.
Model evaluation
Water retention curves
In order to check the accuracy of the simulated soil water retention curves
obtained with the pedotransfer functions and the Mualem-Van Genuchten equation, the
resulting water content values were plotted against measurements obtained in the
laboratory using the same values of pressure head.
Soil water content
The SWADY model was run using actual data as starting values for the first day.
Model simulations for both sets of data (control and burned plots) were plotted against
actual data and linear regressions were established to evaluate the model. The time
series of actual data was the average of 4 replications (4 tubes).
105
Predicting the effect of fire
The performance of the model was also evaluated at predicting the effects of fire
on soil water storage. In order to perform this simulation, LAI recovery after fire was
roughly estimated. Based on ground cover estimations, it was assumed a maximum
recovery up to 0.8 cm2.cm-2, due to the rapid colonisation of the burned plot by P.
aquilinum fronds and to the resprouting of most Erica plants soon after fire. This
recovery was assumed to follow a typical logistic growth curve similar to the one found
for plant height after the fire experiment. The effect of fire on soil water was assessed
using the procedure described in Silva et al. (2002) for the same study site. Two
measuring periods were considered: a reference (pre-fire) period from the 4th of June
2000 to the 20th of December 2000 and a treatment (post-fire) period from the 4th of
June 2001 to the 20th of December 2001. Differences (Di) between soil moisture
measurements at each day (i) of the treatment period (Mti) and the homologous Julian
day of the reference period (Mri), were obtained at the two plots (Di=Mti-Mri). The use
of moisture differences from two years to compare plots was preferred to the simple use
of raw data from one year. In fact given the reduced number of replications, even small
variability within plots would have been sufficient to hide the effects of fire. Values of
Dbi (moisture differences in the burned plot) and Dci (moisture differences in the
control plot) were converted into mm of soil water and estimated down to 180 cm
depth, by integrating measurements using 20 cm increments. Since the distinct
meteorological conditions of the two periods have also accounted for part of Dbi, these
values were compared with Dci. Given that meteorological conditions were similar in
both plots, the difference between Dbi and Dci (Si=Dbi-Dci) was assumed to correspond
to the net effect of fire on soil water storage. This procedure was used both for the
measured and the modelled data and the resulting time series was compared. Dry season
was defined as the period from the 4th of June (burning experiment) to the day of the
first September rain event >10 mm (19th of September in 2000 and 21th of September
in 2001).
6.3
Results
Soil water measurements
The precipitation patterns along the whole study period were very different when
comparing the rainy season of 2000 (561.4 mm) with the same period of 2001 (242.6
mm). This lead to different soil water recharge patterns in both periods. On the contrary,
106
the amounts of precipitation during the dry season were very similar in both years (29.3
mm and 25.2 mm, respectively). In both plots and in both years, soil moisture followed
a general pattern typical of mediterranean climates, which can be described as a
markedly decreasing trend along the dry season followed by a sudden increase as the
wetting front reached the different soil layers along the rainy season. In average the
wetting front took between 44 (15 cm) and 74 days (170 cm) to reach the different
depths after the first significant rain event (>10 mm) marking the beginning of the rainy
season in September. This pattern varied according to each of the studied depths.
According to Table 6.2, at 15 cm soil water content presented the highest variation in
both the control and the burned plots (SD=9.0% and SD=10.6%, respectively), whereas
at 170 cm it presented the lowest variation (SD=3.7% and SD=3.5%, respectively). At
15 cm, soil water content ranged from 15.4% to 50.0% at the control plot and from 15.3
to 51.6% at the burned plot. At 170 cm, soil water content ranged from 20.3% to
36.5% at the control plot and from 22.0% to 35.9% at the burned plot.
Table 6.2 Descriptive statistics of soil water measurements (% vol.) representing 318 days between May
2000 to December 2001, for the control and the burned plots. SD – Standard Deviation; SE – Standard
Error.
Plot
Depth
Mean
SD
SE
Max.
Min.
Range
Control
15 cm
31.5
9.0
0.5
50.0
15.4
34.6
30 cm
33.3
7.6
0.4
46.8
21.4
25.4
50 cm
30.8
6.8
0.4
40.6
20.1
20.5
90 cm
33.0
6.5
0.4
42.2
22.7
19.5
130 cm
29.3
4.7
0.3
35.6
21.5
14.1
170 cm
28.6
3.7
0.2
36.5
20.3
16.2
15 cm
32.4
10.6
0.6
51.6
15.3
36.2
30 cm
32.4
8.6
0.5
45.1
17.9
27.3
50 cm
33.5
6.5
0.4
43.0
22.6
20.4
90 cm
30.2
5.0
0.3
37.5
21.4
16.2
130 cm
27.1
3.9
0.2
33.0
19.4
13.6
170 cm
28.8
3.5
0.2
35.9
22.0
14.0
Burned
107
Model evaluation
Water retention curves
Fig. 6.2 shows the graph of the measured vs. modelled data for the soil water
retention curves. It includes both plots, all depths and three points of the curves
(pressure head (h) equal to: 15700 cm, 100 cm and 1 cm). The linear regression slope
was 0.98, the intercepts was -6.70 and the coefficient of determination was 0.82.
Soil water content
Graphs of modelled and measured soil water contents are shown in Fig. 6.3 and
Fig. 6.4, together with threshold lines, representing the wilting point (h=15700 cm),
field capacity (h=100 cm) and saturation (h=1 cm), as obtained by the model. Each
graph represents a total of 587 days between the 13th of May 2000 and the 20th of
December 2001. Within this period, soil water content was measured in a total of 318
days. Measured data were compared with the corresponding modelled data using linear
regressions, and the results of this analysis are shown in Table 6.3. The coefficients of
determination ranged from 0.85 to 0.74 for the control plot and from 0.78 to 0.69 for the
burned plot. Values of regression slopes ranged from 0.94 to 0.58 for the control plot
and from 0.71 to 0.49 for the burned plot. Values of regression intercepts ranged from
6.73 to 0.11 for the control plot and from 12.74 to 8.82 for the burned plot. There was a
reasonably good fit between both data sets although with a general underestimation of
the soil water content, as expected from the relationships observed for the soil water
retention curves (see Fig. 6.2). In general the modelled data sets presented lower levels
of variability than the actual data.
When comparing the modelled data series with the modelled soil water content
thresholds (the horizontal lines in Fig. 6.3 and Fig. 6.4), we verify that, with few
exceptions, values remained between the two extremes (saturation and wilting point. On
the other hand soil water content has exceeded the soil saturation capacity at different
depths during the 2000/2001 rainy period. According to the simulation exercise, this
happened especially at deeper layers (50 cm and 130 cm both in the control plot and the
burned plots). The deepest layers (130 cm and 170 cm) revealed considerably high
minimum levels of soil water content. The autumnal minimum was specially high in the
burned plot, after the experimental burning.
108
Modeled soil water content (% vol.)
80
70
y = 0.98x - 6.70; r2 = 0,82
60
50
40
30
20
10
0
0
10
20
30
40
50
60
70
80
Measured soil w ater content (% vol.)
Fig. 6.2 Comparison between soil water content values obtained from laboratory-determined water
retention relationships (measured) and the corresponding values obtained using the soil water retention
sub-model (modelled) based in the method proposed by Wösten et al., (1999) for computing the
parameters of the Mualem-Van-Genuchten equation. Soil water content values correspond to three
pressure head levels applied to samples from six different depths, from both plots. The solid line
represents the linear regression (n=36) and the broken line represents a reference y=x relationship.
Table 6.3 Results of linear regressions (n=318) for comparison between measured (abscissa) vs. modelled
(ordinate) soil water data for the two plots and each depth.
Depth
Control
15 cm
0.94
0.11
0.74
30 cm
0.88
1.70
0.80
50 cm
0.76
2.57
0.85
90 cm
0.58
6.12
0.80
130 cm
0.63
6.73
0.81
170 cm
0.66
6.48
0.75
15 cm
0.71
9.17
0.74
30 cm
0.65
8.82
0.78
50 cm
0.57
9.00
0.70
90 cm
0.61
9.00
0.74
130 cm
0.62
10.44
0.76
170 cm
0.49
12.74
0.69
Burned
Slope
Intercept
r2
Plot
109
15 cm
60
50
40
30
20
10
0
60
30 cm
50
40
30
20
SOIL WATER CONTENT (% volume)
10
0
60
50 cm
50
40
30
20
10
0
60
90 cm
50
40
30
20
10
0
60
130 c m
50
40
30
20
10
0
60
170 c m
50
40
30
20
RAINFALL (mm)
10
0
80
60
2000
2001
40
20
0
133
177
221
265
309
353
32
76
120
164
208
252
296
340
Julian day s (y ears 2000 and 2001)
Fig. 6.3 Water content at six different depths at the control plot. Circles represent actual measurements
and the continuous lines represent model simulations. The histogram shows the rainfall during the two
years (separated by a broken line) of measurements. Horizontal broken lines represent saturation, field
capacity and wilting point, respectively, as obtained by the model.
110
60
15 c m
50
40
30
20
10
0
60
30 c m
50
40
30
20
10
SOIL WATER CONTENT (% volume)
0
60
50 cm
50
40
30
20
10
0
60
90 c m
50
40
30
20
10
0
60
130 c m
50
40
30
20
10
0
60
170 c m
50
40
30
20
10
RAINFALL (mm)
0
80
60
2000
2001
40
20
0
133
177
221
265
309
353
32
76
120
164
208
252
296
340
Julian day s (y ears 2000 and 2001)
Fig. 6.4 Water content at six different depths at the burned plot. Circles represent actual measurements
and the continuous lines represent model simulations. The histogram shows the rainfall during the two
years (separated by a broken line) of measurements. Horizontal broken lines represent saturation, field
capacity and wilting point, respectively, as obtained by the model. The arrow indicates the date of fire.
111
180
150
S i (mm)
120
90
60
30
0
-30
-60
150
185
220
255
Julian day
290
325
360
Fig. 6.5 Modelled (line) and measured (circles) net effect of fire in terms of soil water storage (Si).
Si=Dbi- Dci, where Dbi represents the soil water storage difference for each day (i) between the treatment
period and the reference period in the burned plot and (Dci) represents the same difference for the control
plot. The estimation refers to the layer 0-180 cm and results from an integration using 20 cm increments.
Fire occurred at the beginning of the time series (Julian day 155, 4th of June).
Predicting the effect of fire
Fig. 6.5 presents the results of simulating the net effects of fire on total water
storage (Si) in the 0-180 cm soil layer compared to actual data The actual soil water
storage data was taken from Silva et al. (2002). Both curves presented an increase in
soil water storage along the considered period (4th of June to 20th of December), due
the reduction of transpiration activity from plants. This effect was not restricted to the
dry season but it continued throughout the study period (i.e. before and after Julian day
264). The maximum moisture difference in the dry season was 79.4 mm for the model
and 108.2 for real data. The maximum moisture difference in the rainy season was 82.3
mm for the model and 145.2 for real data. In average both curves showed the same basic
trend (r2=0.69, for the linear regression between both data sets) although the simulation
had underestimated soil water storage increment by 24.5 mm (average for the whole
period), when compared to actual data.
6.4
Discussion
Precipitation patterns along the study period are well an example of the
irregularity of the mediterranean climate specially during the rainy season. The
conditions during the dry season are more regular and very little rainfall contributes for
the soil water recharge until the first September rains. Plant species have evolved with
these conditions and have developed adaptations to overcome the risks of water
shortage. One of the adaptations is the development of deep root systems. This
characteristic was found to be associated with climates with important winter rainfall
(Schenk & Jackson, 2002) and dry summers, as it is the case of our study site. Important
112
rainfall in winter allows water to recharge the deeper soil layers, which can be used by
deep roots during the dry season. This agrees well with the fact that the values obtained
with soil moisture measurements revealed rather constant and favourable moisture
conditions at 170 cm depth. This is very important for plant survival since it allows the
deep rooted species to keep relatively high transpiration and growth rates during the dry
season. According to this, plants have the possibility of maintaining a constant
evapotranspirative flux because of deep rooting (Williams et al., 2001). The shrub
community under study, is basically composed of deep rooted Erica and Ulex plants.
Silva & Rego (unpublished) have found that these plants had roots going much bellow
the studied profile (deeper than 240 cm in the control plot and deeper than 200 cm in the
burned plot). Apparently these plants make use of their deep root system to tap water
during the dry summer months when moisture is not available at more superficial
layers. As soon as the dry season ends, these plants use the high root density of the
upper layers to take advantage of the higher water and mineral content of the soil. In our
case, the also abundant Pteridium aquilinum did not present a deep root system (Silva &
Rego, unpublished) having to rely on the superficial rhizomes as long as water was
available. Simultaneously with the lowest water content and the decrease in air
temperature, fronds normally start decaying in September and only reappear when soil
moisture conditions and temperature became again favourable in the spring. Despite the
mediterranean characteristics of the climate, we should mention the mesic
characteristics of the study site. In fact the lowest soil moisture values encountered at
the surface layer during summer, were always far from reaching the wilting point.
Nevertheless at the lowest moisture levels verified at 15 cm, both in the control and the
burned plots, plants certainly have much difficulty extracting water, thus having to rely
on deeper roots. Thus it is apparent that the uppermost and the lowest soil layers are
critical for mediterranean plants since they represent respectively the preferential uptake
zone in moist and dry conditions (Canadell & Zedler, 1995). This was confirmed by the
root distribution and the maximum rooting depth found for the shrub community. In fact
plants tend to optimise their root distribution as a function of soil water content
distribution along the year. This have allowed some authors to use soil water models for
inferring about the potential distribution of roots in the soil (Musters & Bouten, 1999;
Wijk & Bouten, 2001).
The empirical pedotransfer functions and the Mualem-Van Genuchten equations
used in Wösten et al. (1999) for the establishment of an European Database of Soil
113
Hydraulic Properties (HYPRES) revealed an underestimation of soil moisture when
compared to laboratory values at similar pressure head levels. A deviation was to be
expected since the pedotransfer equations resulted from empirical laws developed to
suit a wide range of european soils. This underestimation of soil water content by the
modelled soil water retention curves was the basic reason for the general
underestimation trend of modelled soil moisture values along the year, when compared
to field measurements. This means that a different model performance (better or worst)
may be expected according to the accuracy of the water retention curve estimation,
when applied to other soils. In this aspect the model is no exception within the universe
of soil water models, where the dependence on empirical relationships derived from soil
texture to estimate hydraulic properties, constitutes an important weakness (Feddes et
al., 2001). Otherwise errors could also result from measurements, contributing to
increase the misfit between modelled and measured data (Musters, 1998). Errors in soil
water measurements have origin in many sources, from operating errors, to changes
caused by the tubes in the soil structure (Rothe et al., 1997) and preferential growth of
roots (Maertens & Clauzel, 1982; Merril, 1992), or even calibrating errors. From the
model side there are simplifications which may also have contributed for some
deviations observed. In particular we should mention the absence of input information
on root distribution dynamics along the year and the fact that some soil hydraulic
characteristics are not considered such as hydraulic conductivity or the hysteresis of the
water retention curves (Feddes & Koopmans, 1998). Finally the model could also
consider the particular effect of the litter and the duff layers in soil infiltration and
evaporation. In fact the results (measured and modelled) obtained for the first depth (15
cm) are not representative of the processes occurring close to the surface. Together with
the existence of specific mechanisms controlling water flows influenced by the
existence of a litter and a duff layer, this region of the soil is highly and directly
influenced by all meteorological agents. The existence of a wide range of different
mechanisms influencing the inflows and the outflows of water, leads to a high
variability of this first layer in terms of soil water content, which could not be simulated
by our model. In modelling terms it acted essentially as a buffer layer, which is
definitely a considerable simplification considering its specificity in terms of the water
balance. This buffer layer was responsible for example for the delay between the first
significant September rain event and the arrival of the wetting front at 15 cm depth.
However in general terms the model was able to reproduce the soil water dynamics as
114
obtained with the measurements. In particular we should refer the results obtained for
the simulation of the fire effect on soil water storage. These results have confirmed that
the major short term fire effect in terms of soil water changes, is the reduction of plant
transpiration. Thus both the model and the actual data revealed that the more thoroughly
studied effects of fire such as runoff, lower infiltration, and higher evaporation do not
seem to be the driving force controlling short term fire effects in terms of soil water
dynamics.
Although we may consider the simulation results quite encouraging, further
developments of the SWADY model are to be expected. These should include a more
soil-physics-based approach in order to provide a better simulation of the soil water
flows according to different soil hydraulic characteristics. With this purpose a further
development is planned to include the widely applied Richards equation (Feddes &
Koopmans, 1998; Hillel, 1998). Another important improvement will consist in the
adoption of modified pedotranfer empirical functions allowing to obtain a better
estimate of soil hydraulic characteristics.
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7 DISCUSSÃO E CONCLUSÕES
Neste capítulo final tentam agrupar-se, de uma forma tanto quanto possível
consistente e harmonizada, a discussão dos resultados e as principais conclusões do
trabalho desenvolvido no âmbito da presente tese. Apesar de algumas alterações
introduzidas de forma a dar uma sequência lógica à leitura, uma boa parte deste capítulo
final é fundamentalmente uma assumida transcrição para Português da secção
Discussion dos cinco capítulos anteriores. Deste modo, o objectivo base do presente
capítulo é tão somente o de se constituir como uma súmula em Língua Portuguesa do
conhecimento adquirido no âmbito deste trabalho.
7.1
Estudo das raízes de plantas individuais
Características
estruturais
das
raízes
de
algumas
plantas
lenhosas
mediterrânicas
A decisão de estudar um grupo heterogéneo de plantas quer ao nível da espécie
quer ao nível do estado de desenvolvimento, embora acarretando importantes limitações
ao nível do tratamento estatístico, permitiu por outro lado o estudo da variabilidade
exibida pelas plantas amostradas. Pensamos que este objectivo foi conseguido tendo em
conta os resultados obtidos pela Análise por Componentes Principais (PCA – Principal
Component Analysis) utilizando diferentes parâmetros caracterizadores dos sistemas
radicais. Esta análise demonstrou que o estado de desenvolvimento dos indivíduos
amostrados foi o principal factor responsável pela variabilidade exibida pelos diferentes
sistemas radicais. Tal como esperado, estados de desenvolvimento mais avançados
corresponderam tendencialmente a um maior comprimento total das raízes, a uma maior
extensão lateral do sistema radical e a uma maior biomassa radical. De acordo com o
diagrama da PCA o diâmetro médio das raízes aparece em posição ortogonal
relativamente ao comprimento total das raízes, sugerindo que estas duas variáveis
representam formas diferentes e não correlacionadas de distinguir os sistemas radicais
do conjunto de plantas amostrado. No entanto a segunda variável foi sobretudo capaz de
distinguir estados de desenvolvimento ao passo que a primeira se apresentou mais
relacionada com a diferenciação das várias espécies. Embora não exista uma separação
clara entre as espécies de regeneração exclusiva por semente (géneros Cistus e
Lavandula) e as espécies de regeneração vegetativa (restantes géneros), as primeiras
obtiveram em geral maiores valores na segunda componente principal (PC2 – Principal
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Component 2) sugerindo que o diâmetro médio das raízes pode ser uma característica
distintiva entre os dois grupos, tal como foi confirmado pelo teste estatístico. A posição
simétrica da variável comprimento radical específico(SRL – Specific Root Lenght)
relativamente ao respectivo diâmetro está de acordo com a utilização deste último
coeficiente como indicador do diâmetro das raízes (Fitter, 1985). Um outro parâmetro
distintivo entre espécies de regeneração exclusiva por semente e espécies de
regeneração vegetativa parece ser a profundidade máxima de enraizamento a qual, por
outro lado, não teve grande correlação com qualquer dos eixos da PCA. Aparentemente
a profundidade máxima de enraizamento parece ser uma variável bastante independente
dos outros parâmetros estudados, incluindo a área basal. Podemos avançar duas razões
possíveis para explicar o fraco relacionamento entre a profundidade máxima de
enraizamento e a área basal. Por um lado o facto de os nossos resultados sugerirem que
algumas espécies (como a D. gnidium e a L. luisieri) parecerem alcançar relativamente
cedo a profundidade máxima de enraizamento. Por outro lado, a cada espécie parece
estar associada uma profundidade máxima de enraizamento característica para cada
espécie. Em relação ao primeiro aspecto o desenvolvimento precoce das raízes em
profundidade é com certeza uma vantagem competitiva e parece ser uma característica
comum a muitas espécies lenhosas mediterrânicas (Canadell & Zedler, 1995). Muito
embora representando apenas uma pequena fracção de todo o sistema radical, as raízes
profundas têm um papel fundamental na capacidade das plantas para ultrapassar os
déficits hídricos verificados durante a estação seca, em particular durante os estádios
iniciais de desenvolvimento. (Canadell et al., 1996). Estas raízes conseguem alcançar
camadas de solo onde o teor de água é mais elevado que nos horizontes superficiais. As
raízes profundas podem ser responsáveis por mais de 75% de toda a água extraída
durante a época seca (Nepstad et al., 1994). As diferenças de profundidade máxima de
enraizamento parecem estar também associadas às estratégias regenerativas das
diferentes espécies (Keeley, 1986; Correia & Catarino, 1994). Todos os indivíduos de
C. crispus, C. salvifolius e de L. luisieri (regeneração exclusiva por semente)
apresentavam sistemas radicais relativamente superficiais enquanto todas as outras
espécies (regeneração vegetativa) apresentavam sistemas radicais mais profundos. De
entre as espécies estudadas as plantas de L. luisieri e de D. gnidium representam duas
tendências opostas. O crescimento das raízes é essencialmente horizontal no primeiro
caso e essencialmente vertical no segundo. Em termos da ecologia das espécies, os
valores significativamente mais altos encontrados para a biomassa radical, para o
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diâmetro médio das raízes e para a relação raíz-parte aérea das plantas de regeneração
vegetativa, podem ser interpretados apenas como uma consequência da existência de
raízes profundas, apesar da fraca correlação evidenciada pela PCA. Estudos de outras
regiões mediterrânicas têm confirmado a relação entre as características das raízes e as
estratégias regenerativas, nomeadamente na Austrália (Bell, 2001), na California
(Hellmers et al., 1955) e na África do Sul (Higgins et al., 1987).
A tendência decrescente observada para a razão raíz-parte aérea e para a SRL
relativamente a valores crescentes de secção basal, está de acordo com as expectativas.
Diferentes autores têm descrito a existência de uma estratégia no sentido de atribuir uma
fracção cada vez menor de recursos às raízes à medida que o desenvolvimento das
plantas prossegue (Nobel, 1996; Bazzaz, 1997; Grace, 1997). Esta fenómeno é
particularmente importante nas plantas mediterrânicas, nas quais o desenvolvimento
precoce das raízes é um factor crítico para sobreviver à primeira estação seca após a
germinação. A tendência decrescente observada para a SRL (Fitter, 1985), foi mais
importante para as duas espécies com regeneração exclusiva por semente, o que pode
revelar diferentes estratégias de crescimento radical. Estas diferenças poderão ser
atribuídas a um investimento preferencial em raízes estruturais e orgãos de
armazenamento de hidratos de carbono das duas espécies de regeneração vegetativa
durante os primeiros estádios de desenvolvimento, contrastando com o investimento
preferencial em raízes finas por parte das duas espécies de regeneração exclusiva por
semente durante estas mesmas fases de crescimento.
Apesar da existência de uma grande amplitude de valores da relação raíz-parte
aérea correspondendo a diferentes espécies e diferentes estádios de desenvolvimento, a
biomassa das raízes e a biomassa da parte aérea apresentaram uma relação semelhante e
igualmente consistente com a secção basal das plantas. Este aspecto pôde ser
confirmado tanto pela regressão linear como pela PCA, apesar da diversidade de
espécies e de estádios de desenvolvimento das plantas utilizadas nas análises. A
existência deste tipo de relação tem sido relatada em diferentes estudos com espécies
arbóreas (e.g. Santantonio et al., 1977; Drexhage & Colin, 2001; Hoffmann & Usoltsev,
2001; Ranger & Gelhaye, 2001). O estabelecimento de uma única relação alométrica
entre medições no caule e medições na raiz utilizando indivíduos de diferentes espécies
(Santantonio et al., 1977) está de acordo com o amplamente difundido pipe model,
apresentado por (Shinozaki et al., 1964). A secção do tronco parece de facto limitar o
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desenvolvimento da raiz e da parte aérea de forma semelhante para diferentes espécies e
para diferentes estádios de desenvolvimento.
Algumas observações devem ser feitas relativamente à interpretação dos
resultados obtidos, tendo em conta as duas estratégias regenerativas. As semelhanças
encontradas ao nível dos parâmetros caracterizadores dos sistemas radicais das espécies
de regeneração exclusiva por semente reflectem também a existência de relações
filogenéticas estreitas entre algumas plantas (mesmo género ou mesma espécie). Deste
modo, a existência de características comuns pode dever-se apenas aos laços
filogenéticos existentes entre as plantas. Para contornar esta questão foram
desenvolvidos esquemas de delineamento de amostragem (Nicotra et al., 2002) os quais
no entanto não podem ser aplicados a situações como aquela aqui estudada, com uma
diversidade de espécies disponíveis relativamente limitada. Deste modo as diferenças
significativas encontradas entre os dois grupos de plantas representantes de duas
estratégias regenerativas distintas, devem ser interpretadas também tendo em
consideração os laços filogenéticos existentes. No entanto os nossos resultados são
apoiados por resultados semelhantes noutras regiões mediterrânicas do Mundo, o que
nos leva a assumir que os mesmos mecanismos adaptativos encontrados noutras regiões
são também válidos para as comunidades de plantas aqui estudadas.
Um dos aspectos não abordados no âmbito do presente estudo foi o estudo da
influência dos factores ambientais nas características das raízes. É consensual a
influência determinante dos factores ambientais nas características dos sistemas radicais
das plantas (e.g. Spurr & Barnes, 1980; Kummerow, 1981; Fitter, 1996; Atkinson,
2000). No nosso caso a ausência de limitações evidentes ao desenvolvimento das raízes
e a proximidade do locais onde as plantas se encontravam levaram-nos a assumir a
existência de condições ambientais relativamente homogéneas, permitindo a
comparação dos sistemas radicais com base na respectiva espécie e estado de
desenvolvimento. No entanto devemos admitir que a existência de diferenças em termos
de densidade de plantas ou em termos de micro-topografia poderão ter contribuído de
forma importante para a variabilidade geral da amostra.
Distribuição das raízes de algumas plantas mediterrânicas. Proposta de um
novo modelo
De entre os quatro modelos testados, o MLDR revelou uma considerável
flexibilidade e capacidade para se ajustar aos dados relativos à distribuição das raízes de
121
um leque alargado de plantas lenhosas. A utilização desta função matemática permitiu
descrever de forma muito aproximada a distribuição vertical das raízes das plantas
amostradas, em termos de biomassa e de comprimento. Da mesma forma, a utilização
conjunta de um coeficiente de biomassa e de um coeficiente de comprimento de raízes,
permitiu reflectir a diversidade de sistemas radicais existentes no conjunto de plantas
amostradas. Muito embora esta abordagem pudesse potencialmente conduzir a um
sistema de classificação empírica de sistemas radicais, tal como a apresentada por
Guowei et al. (1997) tal não foi feito devido à necessidade de um conjunto de dados
bastante mais extenso. Uma classificação abrangente apenas seria possível dispondo de
repetições para cada espécie, para cada estádio de desenvolvimento e para diferentes
condições ambientais. O enorme esforço exigido para a escavação de raízes completas
em condições naturais fez com que não fosse possível conseguir este objectivo.
Na utilização do modelo MLDR para o ajustamento de dados relativos à
distribuição de raízes de uma comunidade de plantas com uma profundidade máxima de
enraizamento desconhecida, deverá ter-se em conta o facto de que os dados referentes
aos valores de maior profundidade correspondem a Yr=1. Se este aspecto for tido em
conta, a utilização do modelo proposto para o ajustamento de dados de distribuição de
raízes ao nível da comunidade de plantas é perfeitamente possível (ver capítulo 4).
Algumas observações devem ser feitas relativamente à metodologia utilizada
para obter dados de distribuição de raízes, em particular no que se refere à determinação
do comprimento das raízes. A distribuição vertical do comprimento das raízes foi com
certeza afectada, embora não se sabendo até que ponto, pelo processo de escavação
utilizado, dada a inevitável perca de raízes finas (Wallace et al., 1974; Böhm, 1979;
Caldwell & Virginia, 1989; Bengough et al., 2000) as quais são responsáveis pela maior
parte do comprimento de raízes no solo. Muito embora possamos assumir que este erro
se repartiu de forma idêntica em cada sistema radical, a perca de raízes finas poderá
eventualmente ter contribuído para esconder parte da acumulação normal de raízes nas
camadas superficiais do solo. Um outro aspecto a ter em conta é a possibilidade de
terem ocorrido alterações importantes no arranjo arquitectural das raízes, em particular
das mais finas, relativamente à disposição original no solo, antes da escavação. No
entanto pensamos que muito poucas alterações substanciais foram introduzidas dado se
tratarem de plantas lenhosas com raízes estruturais sólidas e não deformáveis. Por outro
lado durante o trabalho de escavação tentou-se evitar este tipo de erros através do
registo fotográfico das plantas no campo e de uma cuidadosa disposição das raízes para
122
a determinação estratificada da biomassa e do comprimento radicais. Uma outra fonte
possível de erro é todo o processo de captação e processamento das imagens digitais.
No entanto, os erros derivados deste processo podem resultar tanto num aumento como
de uma diminuição dos valores reais a determinar (Richner et al., 2000). Apesar das
óbvias limitações da metodologia utilizada, foi assumido que os erros referidos terão
sido igualmente distribuídos por todas as plantas estudadas e ao longo de cada planta.
Por outro lado, a utilização de valores normalizados e a natureza comparativa do
presente estudo fazem-nos considerar que os erros existentes serão aceitáveis tendo em
vista os objectivos em vista.
De um modo geral os dados de distribuição de raízes revelaram uma separação
entre espécies de regeneração exclusiva por semente e espécies de regeneração
vegetativa. De entre as plantas do último grupo aquelas com raízes profundas revelaram
um padrão de distribuição de raízes distinto (Daphne, Erica, Myrtus, Ulex). Em
particular as espécies com tubérculo lenhoso ou lignotuber (E. lusitanica e E. scoparia)
apresentaram uma elevada concentração de biomassa junto à superfície do solo. Estes
resultados reflectem bem a importância destas estruturas enquanto órgãos de
armazenamento de hidratos de carbono sob a forma de amido. No entanto alguns
autores questionam a decisão de considerar os tubérculos lenhosos como partes
integrantes do sistema radical, dado que este funciona essencialmente como órgão de
armazenamento, normalmente localizado muito perto ou mesmo acima da superfície do
solo, e não exactamente como uma raiz estrutural (Kummerow, 1981; Canadell &
Zedler, 1995). Esta decisão é obviamente determinante nos resultados obtidos em
termos da distribuição vertical da biomassa das plantas e da determinação da relação
raíz-parte aérea. Duas outras espécies de regeneração vegetativa com uma elevada
concentração de biomassa junto à superficie, D. gnidium e M. communis, não
apresentavam um tubérculo lenhoso típico mas antes intumescências não lenhificadas,
possivelmente desempenhando o mesmo papel de armazenamento de hidratos de
carbono. Com a excepção do único exemplar recolhido de M. communis, todas as
plantas com raízes profundas apresentavam raízes pivotantes com orientação
aproximadamente vertical. Tal como já foi referido relativamente ao estudo anterior,
estas raízes pivotantes têm um papel fundamental para a captação de água durante a
estação seca, muito embora representem uma pequena fracção da biomassa e do
comprimento total das raízes (Kummerow et al., 1990; Canadell & Zedler, 1995). A
consequência deste padrão de distribuição é uma mais elevada concentração relativa de
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raízes junto à superfície, para maiores profundidades máximas de enraizamento. A
maior parte das plantas com raízes profundas apresentavam uma expansão lateral dos
respectivos sistemas radicais, constituindo um sistema típico de outras regiões
mediterrânicas (Canadell & Zedler, 1995) composto por raízes pivotantes e por raízes
superficiais ou pastadeiras. Estudos diversos têm demonstrado que este padrão de
distribuição pode ser vantajoso em regiões sujeitas a períodos de seca, estando presente
em várias espécies destas regiões (Hellmers et al., 1955; Specht & Rayson, 1957;
Kummerow, 1981; Krämer et al., 1996). No caso particular das duas espécies do
género Erica, apesar das semelhanças do padrão de distribuição das raízes, algumas
diferenças podem ser observadas devido à menor expansão lateral das raízes do único
exemplar adulto de E. scoparia. As razões para esta diferença podem ter a ver com o
facto de esta planta ter sido escavada numa comunidade com elevada densidade, ao
passo que a planta de E. lusitanica se encontrava num local aberto. Muito embora não
nos fosse possível testar esta hipótese, é sabido que as interacções entre as plantas têm
um efeito determinante na distribuição das raízes no solo, tal como foi demonstrado por
(Atkinson, 2000). Os sistemas radicais das espécies de regeneração vegetativa C.
monogyna e R. ulmifolius, apresentam estruturas distintas quando comparadas com as
restantes espécies deste grupo. No primeiro caso existem apenas raízes estruturais à
superfície e quase nenhumas raízes finas, o que explica a diferença entre as curvas de
biomass e de comprimento das raízes. No segundo caso apenas existem raízes finas ao
longo de todo o perfil ocupado o que explica a semelhança entre as curvas de biomassa
e de comprimento de raízes. O facto de se tratar de uma espécie escandente deverá
explicar em parte a ausência de raízes estruturais para a sustentação da planta.
Relativamente às espécies de regeneração exclusiva por semente, existe uma
semelhança notável nos padrões de distribuição exibidos pelas plantas do género Cistus,
todas elas com raízes pouco profundas tal como é comum nas espécies exibindo esta
estratégia regenerativa (Keeley, 1986; Bell, 2001). O caso particular da L. luisieri é
paradigmático já que se trata de uma espécie altamente adaptada à secura apesar de
apenas dispor de um sistema de raízes superficial. A estratégia desta espécie parece ser
o desenvolvimento de um sistema de raízes finas com uma ramificação extrema na
profundidade máxima de enraizamento, o que deverá permitir um aumento da eficiência
na extracção de água.
Em termos dos diferentes estádios de desenvolvimento, apenas a distribuição do
comprimento das raízes parece ter sofrido alterações como consequência do aumento da
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profundidade máxima de enraizamento (Maxd). A ausência de diferenças consistentes
em termos da distribuição da biomassa das raízes ao longo dos estádios de
desenvolvimento parece dever-se em parte à grande concentração da biomassa em
órgãos de armazenamento por parte das espécies de regeneração vegetativa. Pelo
contrário os valores do coeficiente dl50 apresentaram um aumento consistente para todas
as espécies ao longo dos diferentes estádios de desenvolvimento, como consequência
dos valores mais elevados da profundidade máxima de enraízamento.
7.2
Estudo das raízes ao nível da comunidade de plantas
Distribuição das raízes de um matagal mediterrânico na Tapada Nacional de
Mafra
Os resultados obtidos demonstraram a existência de padrões de distribuição de
raízes bastante distintos para as diferentes espécies presentes na comunidade de plantas.
Estes diferentes padrões de distribuição podem estar associados a diferentes estratégias
para a captação de água e nutrientes. De facto os resultados sugerem a existência de
uma separação de nichos (Casper & Jackson, 1997) entre as quatro espécies associado a
diferentes estratégias adaptativas. Os padrões de distribuição de raízes obtidos através
do mapeamento das paredes das trincheiras reflectem sobretudo os padrões de
distribuição das plantas individuais tal como puderam ser observados no local de
estudo. As plantas da espécie Erica exibiam raízes pivotantes mas também raízes
laterais junto à superfície. As plantas de Ulex embora também como raízes profundas
não apresentavam este padrão devido à ausência de raízes laterais à superfície. Este
facto fez com que o pico de contagens para esta espécie não fosse atingido junto à
superfície mas sim abaixo dos primeiros 20 cm com o consequente aumento do valor de
do coeficiente D50. A disposição em grupos das raízes mapeadas no fundo das
trincheiras está também de acordo com a arquitectura das plantas individuais de Erica e
de Ulex. Na realidade as raízes pivotantes destas plantas foram observadas crescendo
praticamente na vertical, desta forma dando origem a uma disposição das raízes no
plano horizontal formando grupos, supostamente referentes a uma única planta. Tal
como foi referido anteriormente, estas raízes profundas são fundamentais para a
absorção de água durante a estação seca. Este padrão de distribuição de raízes
pivotantes é associado a climas com um Verão seco e com bastante chuva no Inverno,
como é o caso do local estudado (Schenk & Jackson, 2002b). No entanto no nosso caso
específico o elevado número de raízes pivotantes é provavelmente o resultado da intensa
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competição (Atkinson, 1978) originada pela elevada densidade de plantas. Para além da
competição intra-específica há que considerar igualmente a competição entre espécies
diferentes. Apesar de não termos abordado este aspecto específico, vários trabalhos
referem a existência de competição assimétrica em povoamentos mistos (e.g. McKay,
1988; Casper & Jackson, 1997; Leuschner et al., 2000) como resultado da diferente
eficiência na exploração de recursos do solo evidenciada pelas espécies presentes. No
caso das plantas de Rubus os indivíduos observados evidenciavam uma elevada
densidade de raízes finas junto ao solo, mas também algumas raízes profundas. Esta
disposição das raízes explica o baixo valor de D50 e a tendência decrescente obtida com
as contagens verticais. No caso das raízes de Pteridium estas dispunham-se de acordo
com uma rede horizontal muito densa de rizomas, junto à superfície do solo, aos quais
se encontravam ligadas raízes finas relativamente dispersas. Em relação a esta espécie
deve ter-se em conta a sua fenologia, caracterizada por grandes alterações sazonais
(Pakeman & Marrs, 1994). Esta sazonalidade traduz-se fundamentalmente na morte das
frondes durante a estação fria e no seu reaparecimento na Primavera. Estas flutuações
em termos da biomassa viva da parte aérea parecem ter correspondência abaixo da
superfície do solo, dada a elevada percentagem de rizomas em diferentes estádios de
decomposição. Desta forma há que ter em conta, relativamente a esta espécie, que os
nossos resultados dizem respeito ao período de crescimento (Junho-Agosto) e que por
isso apenas reflectem as características da espécie durante este período.
As diferenças na distribuição das raízes entre classes de diâmetro são em parte
uma consequência da localização preferencial das raízes estruturais nas camadas mais
superficiais do solo. No caso particular das raízes médias (5-10 mm) e grossas (>10
mm) existiu uma contribuição relativamente importante dos rizomas de Pteridium para
os resultados obtidos. As raízes estruturais localizadas junto à superfície do solo têm
uma importância fundamental na sustentação da parte aérea (Coutts, 1983; Fitter &
Ennos, 1989) e na estabilidade do solo (Ziemer, 1981). Deste modo a distribuição mais
uniforme e mais profunda das raízes mais finas e a distribuição mais superficial e
heterogénea das raízes mais grossas não surpreende, mesmo tendo em conta que os
resultados foram obtidos com quatro espécies distintas. Dado que este é, tanto quanto
sabemos, o único estudo realizado sobre a distribuição das raízes de uma comunidade
dominada por plantas do género Erica, é difícil dispor de outros estudos para
comparação. Por outro lado, por entre a panóplia de métodos que podem ser
encontrados na literatura, a maior parte baseiam-se em medições de biomassa e não em
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contagens de raízes. Este facto é bem patente na compilação de dezassete estudos
realizados em comunidades arbustivas esclerófilas levada a cabo por Schenk & Jackson
(2002a) onde quase todos os estudos se baseiam em medições de biomassa. O D50
médio destes estudos é de 19 cm o que representa um valor inferior ao do presente
estudo (26 cm). Uma outra compilação de seis estudos em vegetação esclerófila
presente em Jackson et al. (1997) incluindo apenas raízes finas (neste caso raízes
maiores que 2 mm) forneceu um valor médio de D50 igual a 14 cm, o que é bastante
inferior à nossa estimativa de 27 cm baseada em contagens, mas exactamente igual à
nossa estimativa baseada em comprimento das raízes. Na verdade pudemos verificar
uma diferença considerável entre os resultados obtidos com as amostragens de biomassa
e o comprimento de raízes, quando comparadas com a contagem. A verdade é que
dificilmente se encontra uma relação directa entre contagens e medições de biomassa ou
comprimento radical (Van Noordwijk et al., 2000). Para além das limitações da
metodologia utilizada, a distribuição final das contagens de raízes foi influenciada de
forma decisiva pelas trincheiras 4 e 5, as quais apresentavam um horizonte A espesso.
Nestas trincheiras as raízes estavam em geral mais uniformemente distribuídas,
aparentemente acompanhando a distribuição da matéria orgânica ao longo do perfil.
No que diz respeito à estimativa da biomassa total (viva e morta) de raízes finas,
as nossas estimativas são mais elevadas que a média de seis estudos de 0.52 kg/m2
referidos por Jackson et al. (1997) e mais elevada que o valor de 0.78 kg/m2 referido por
Martinez et al. (1998) referido para uma comunidade arbustiva mediterrânica em dunas
no Sul de Espanha. Aparentemente a densa rede de raízes lenhificadas de Erica
representa uma biomassa mais elevada que o relatado nos outros estudos. Devemos
também admitir que uma pequena percentagem de raízes com diâmetro acima de 1mm
possa ter sido incluída na amostragem influenciando dessa forma o resultado. Por outro
lado, a estimativa do comprimento de raízes por unidade de superfície (18.7 km/m2) é
comparável com a estimativa de 17.5 km/m2 (Jackson et al., 1997) referente a
comunidades esclerófilas lenhosas. É notável o facto de a nossa estimativa ser mais
elevada que os valores referidos em alguns estudos realizados em povoamentos
florestais (e.g. Jackson et al., 1997; Vande Walle et al., 1998; Wiesenmüller, 1998). Tal
não surpreende se considerarmos que a área basal da comunidade arbustiva estudada é
maior que a de um povoamento florestal com uma lotação normal conduzido para
produção de madeira (20-30 m2/ha para a maior parte das espécies da região
temperada). Muitos autores expressam a ocupação radical do solo através do cálculo da
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distância média entre raízes em vez de utilizar o comprimento por unidade de área ou de
volume. Esta distância pode ser calculada através do inverso da densidade de raízes por
unidade de volume (Miller & Ng, 1977). No nosso caso a distância entre raízes
estimada para o primeiro metro de solo foi de 0.9 cm. Trata-se de um valor muito
inferior aos 2.0 cm estimados por Kummerow et al. (1977) para um chaparral na
California, inferior aos 2.8 cm estimados por Hoffmann & Kummerow (1978) para um
matorral no Chile e ainda inferior aos valores de 1.9 cm e 1.7 cm estimados por
Martinez & Rodriguez (1988) e por Martinez et al. (1998) para uma comunidade
arbustiva no Sul de Espanha. A maior ocupação do solo verificada neste estudo revela
diferenças importantes em termos da massa e do comprimento de raízes de um matagal
tipo maquis quando comparado com outras comunidades arbustivas com menor
densidade de plantas tais como as dos estudos referidos. Apesar da diferente
composição florística da comunidade de plantas estudada, relativamente aos restantes
trabalhos consultados, podemos especular que a existência de uma tão elevada ocupação
do solo apenas é possível devido à existência de condições mais favoráveis ao
crescimento, nomeadamente em termos de nutrientes e de água no solo. Deste modo
parece existir um padrão distinto de ocupação do solo pelas raízes em condições
mediterrânicas mais mésicas tal como no nosso caso.
As nossas estimativas de profundidade máxima de enraizamento para as duas
espécies de Erica são razoávelmente próximas dos valores referidos por Canadell et al.
(1996) para outras ericáceas (Arbutus unedo, 350 cm; Erica arborea, 200 cm). A
distribuição estimada para a profundidade máxima de enraizamento das diferentes
plantas sugere que a grande maioria das raízes atinge profundidades localizadas numa
faixa de 50 cm entre os 125 cm e os 175 cm, e que apenas algumas raízes atingem
profundidades superiores. As razões para esta distribuição não foram analisadas no
âmbito do presente trabalho, mas podemos especular que as raízes mais profundas
deverão estar associadas a plantas de maiores dimensões e maior biomassa, tal como
sugerido por Schenk & Jackson (2002b). Dado não termos conhecimento de estudos
semelhantes com espécies do género Ulex, não podemos obter informações sobre a
profundidade máxima de enraizamento destas plantas ou mesmo de outras
filogenéticamente próximas. No entanto os nossos resultados sugerem de forma
consistente a existência de sistemas radicais pelo menos tão profundos como os de
Erica. Se aplicarmos a mesma equação obtida para ajustar os dados das plantas de
Erica, às raízes de Ulex, obtemos uma profundidade máxima absoluta de 349 cm e uma
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média para as 28 raízes mais profundas de cada trincheira, igual a 221 cm. A
importância destas raízes profundas para a captação de água no Verão é confirmada nos
capítulos 5 e 6 desta tese. As medições de humidade revelaram uma perca de água pelo
solo no final da estação seca igual a 18 mm na camada 160-180 cm e igual a 12 mm na
camada 120-140 cm.
7.3
Estudo da dinâmica da água no solo
Efeitos do fogo na dinâmica da água do solo
De acordo com os resultados obtidos, a ocorrência do fogo alterou de forma
notável a dinâmica da água no solo da comunidade estudada. Estas alterações foram
detectadas não apenas na estação seca, durante a qual seria normal fazer-se sentir a
redução drástica da evapotranspiração, mas em geral ao longo de todo o período
estudado. A definição de uma estação seca e de uma estação húmida, baseada num
limite de precipitação, teve como único objectivo o estabelecimento de uma a separação
do período em que não existe recarga da água no solo, do período em que essa recarga
se verifica. No entanto esta diferenciação teve um significado distinto para as diferentes
camadas de solo consideradas, já que as camadas mais profundas mantiveram a mesma
tendência na variação dos valores de humidade muito para além do fim da estação seca
ao passo que a reacção das camadas mais superficiais foi muito mais imediata, como
seria natural. Deste modo cada região do solo tem as suas épocas seca e húmida,
dependendo da profundidade a que se encontra. Um outro aspecto a ter em conta tem a
ver com a data em que foi realizado o fogo experimental. Os resultados teriam sido
bastante diferentes caso o fogo tivesse tido lugar mais tarde na estação seca. Por
exemplo um fogo em Setembro teria como consequências uma menor recuperação na
vegetação devido ao menor tempo disponível para o crescimento e a uma menor
disponibilidade de água para o crescimento. Neste caso os efeitos verificados neste
estudo deveriam ocorrer essencialmente durante a estação seca seguinte tal como foi
constatado por Klock & Helvey (1976) e Soto & Diaz-Fierros (1997) após fogos
ocorridos em Agosto e Setembro, respectivamente.
De um modo geral os diferentes padrões de dinâmica da água no solo
observados durante a estação seca nas diferentes camadas de solo, podem ser explicados
pelo efeito directo da evaporação, pela extracção de água pelas raízes e pelos
movimentos de água no solo. Qualquer dos três processos contribui para uma
diminuição do teor de água à superfície comparativamente com as outras camadas de
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solo. Tal como pôde ser verificado através dos dados de distribuição das raízes, a maior
parte destas ocorre nas camadas superficiais. Em particular a espécie com resposta mais
imediata e vigorosa ao fogo, a Pteridium aquilinum, possui rizomas muito superficiais.
Por outro lado as camadas mais profundas não sofreram o efeito da evaporação e as
únicas raízes presentes eram raízes de Erica e Ulex (ver capítulo 4). Estes aspectos
aparentemente podem contribuir para explicar o facto de nas camadas superiores de solo
se verificar uma diminuição importante do teor de água no solo, especialmente após o
crescimento súbito das frondes de P. aquilinum em Julho, ao passo que em
profundidade o teor de humidade foi sofrendo um decréscimo muito gradual e quase
imperceptível a partir de certa altura. Nas camadas superiores tal correspondeu a um
decréscimo de Dbi, presumivelmente devido ao crescimento do coberto vegetal (P.
aquilinum e Erica). Pelo contrário as camadas mais profundas revelaram valores
progressivamente mais elevados de Dbi, o que é conclusivo acerca da importância da
extracção de água pelas raízes profundas durante a estação seca do ano de referência.
Tal está de acordo com o que é referido por diversos autores sobre o papel das raízes
profundas no solo (Canadell & Zedler, 1995; Canadell et al., 1996).
Durante a estação húmida, diferentes padrões de recarga da água no solo podem
ser associados a diferentes camadas de solo. Estes padrões reflectem fundamentalmente
o momento em que a frente de humedecimento demora a atingir as diferentes
profundidades. Novamente se pôde observar uma muito mais rápida resposta á queda de
precipitação por parte das camadas superiores (0-40 cm) em ambas as parcelas. No
entanto as diferenças entre parcelas nestas camadas não foram tão consistentes durante a
estação húmida, dada a oscilação entre valores positivos e negativos de Si. Por outro
lado dada a diversidade de factores que actuam nas camadas superiores torna-se difícil
tentar determinar qual a causa essencial para os mais baixos valores de Si. neste período
e nesta região do solo. Muito embora não o tenhamos podido provar, podemos especular
que a exposição do solo na parcela queimada terá sido responsável por uma mais
elevada evaporação durante o período pós-fogo durante os invulgarmente secos meses
de Novembro e Dezembro de 2001.
Uma importante consequência dos nossos resultados tem a ver com a
importância do teor de humidade no solo no crescimento das plantas durante o período
pós-fogo. O elevado teor de água verificado após o fogo aparentemente permite explicar
o rápido aumento do coberto vegetal na parcela queimada. Condições semelhantes pósfogo poderão estar na origem dos elevados potencial hídrico e taxa de transpiração
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verificados em espécies de regeneração por semente e em espécies de regeneração
vegetativa (Clemente, em prep.) numa outra comunidade arbustiva estudada na Serra da
Arrábida. No entanto os resultados deste estudo também sugerem que a invulgar seca
verificada no final do Outono de 2001 está relacionada com teores comparativamente
baixos de humidade junto à superfície, na parcela queimada, embora a mesma área se
tenha caracterizado por um teor de humidade superior durante o período seco. Períodos
invulgarmente secos têm sido referidos como factores críticos que explicam, em
interacção com o fogo, a mortalidade das plantas durante o período de recuperação da
vegetação (Mazzoleni & Pizzolongo, 1990). Experiências em situações controladas
mostraram que as plantas de Erica arborea são sensíveis á existência de condições de
humedecimento durante a rebentação, após perturbação (Mazzoleni & Esposito, 1993).
Os nossos resultados confirmam o interesse das interacções entre o fogo e as condições
climáticas relativamente à dinâmica da vegetação.
Alguns trabalhos relatam uma diminuição no teor de água no solo devido ao
fogo (Campbell et al., 1977; Redmann, 1978; Wells et al., 1979) durante o período
imediatamente a seguir à sua ocorrência, e portanto apresentando conclusões
exactamente opostas às do presente estudo. No entanto múltiplas razões podem estar na
origem destes diferentes resultados. Na verdade nenhum destes trabalhos foi realizado
nas mesmas condições que o nosso, nomeadamente no que diz respeito às
profundidades estudadas, ao tipo de vegetação, ao clima e à época de queima. Um dos
trabalhos confirmando um aumento no teor de água no solo após fogo é apresentado em
Klock & Helvey (1976). O aumento estimado de 108.2 mm de água no solo em
Setembro devido ao fogo, é semelhante aos 116 mm referidos por aqueles autores
relativamente a uma floresta mista de coníferas, um ano após o fogo. No entanto é
difícil tirar conclusões sólidas desta semelhança de resultados, na medida em que as
condições em que os estudos decorreram foram bastante distintas, nomeadamente no
que diz respeito ao delineamento experimental (sem medições antes do fogo), à época
de queima (Agosto), ao clima e ao tipo de vegetação. Devemos referir que os valores de
Si obtidos no nosso estudo estão provavelmente sobrestimados na camada superficial (020 cm) durante a estação seca e subestimados durante a estação húmida. Estas
estimativas foram provavelmente afectadas pelo uso de um intervalo de 20 cm na
integração da série de valores, devido à muito variável e heterogénea natureza desta
região do solo. Por outro lado a estimativa para todo o perfil (0-180 cm) não deverá ser
encarada com o impacto total do fogo na água do solo armazenada. De facto tanto a
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extracção de água durante o período de referência por raízes abaixo do perfil estudado,
como a possível percolação de água para camadas de solo mais profundas durante o
período pós-fogo, podem ter contribuído para uma ainda maior diferença no
armazenamento de água no solo em consequência do fogo.
Os resultados deste estudo mostraram inequivocamente a existência de um muito
maior teor de água no solo ao longo do perfil estudado durante a estação seca,
provavelmente como consequência da redução da transpiração da vegetação devido ao
fogo. Adicionalmente este efeito revelou-se consistente ao longo de todo o período
estudado, incluindo a estação húmida. Deste modo, os repetidamente estudados efeitos
negativos dos incêndios na taxa de infiltração não parecem ser a causa determinante no
balanço final da água no solo, pelo menos para as condições estudadas neste trabalho.
O uso da modelação para simular a dinâmica da água do solo
Os padrões de precipitação verificados durante o período estudado são bem o
exemplo da irregularidade do clima mediterrãnico, em especial durante a estação
chuvosa. A estação seca apresenta normalmente condições mais regulares, em que a
escassa chuva que cai, pouco contribuí para a recarga do teor de água no solo, até à
chegada das primeiras chuvas em Setembro. As espécies das comunidades arbustivas
mediterrânicas evoluíram de acordo com estas condições de clima e desenvolveram
adaptações para fazer face à secura estival. Uma das adaptações desenvolvidas por estas
espécies consiste no desenvolvimento de sistemas radicais profundos. Esta característica
é apontada como estando associada a climas com Invernos muito chuvosos (Schenk &
Jackson, 2002b) e Verões secos, tal como acontece na região estudada. Os valores de
humidade do solo obtidos estão de acordo com estas considerações, tendo revelado
teores de água bastante elevados e relativamente constantes ao longo do ano, a 170 cm
de profundidade. Este aspecto é crucial para a sobrevivência das plantas dado permitir
às espécies com raízes profundas a manutenção de taxas relativamente elevadas de
transpiração e de crescimento durante a estação seca. Deste modo, estas plantas têm a
possibilidade de manter um fluxo sensivelmente constante de transpiração devido à
existência de raízes profundas (Williams et al., 2001). A comunidade estudada é, tal
como vimos anteriormente, essencialmente composta por plantas com raízes profundas
dos géneros Ulex e Erica. Silva & Rego (não publ.) verificaram que estas plantas
possuíam raízes com profundidades muito para além do perfil estudado (superior a 240
cm e 200 cm nas parcelas testemunha e queimada, respectivamente). Aparentemente
132
estas plantas utilizam o seu sistema radical profundo de forma a extrair água durante a
estação seca, quando a água não está disponível na região mais superficial do solo. Logo
que começa a estação húmida, estas plantas utilizam a elevada densidade de raízes que
possuem junto à superfície para tirar então partido dos mais elevados teores de
humidade e de minerais do solo. No nosso caso, a espécie Pteridium aquilinum, embora
igualmente abundante, não apresentava um sistema radical profundo, (Silva & Rego,
não publ.) estando a absorção de água limitada pela relativamente superficial rede de
rizomas. Tal explica em parte a sazonalidade desta espécie a qual mantém frondes
verdes apenas enquanto a água e a temperatura do ar se situam a níveis favoráveis,
começando a secar antes do início da estação húmida. Os nossos dados confirmaram de
certa forma o carácter mésico ou mediterrânico atenuado do clima. Na verdade os
valores mais baixos de humidade no solo encontrados junto à superfície mantiveram-se
sempre bastante afastados do ponto de emurchecimento. Estes teores de humidade
verificados, deverão ser no entanto suficientemente baixos para implicar o recurso a
raízes mais profundas. Aparentemente as camadas mais superficial e mais profunda do
perfil explorado pelas raízes têm uma importância fundamental para as plantas
mediterrânicas, dado que representam as zona preferenciais de extracção de água
durante as estações húmida e seca, respectivamente (Canadell & Zedler, 1995). Este
aspecto pôde ser confirmado pela distribuição de raízes encontrada na comunidade
arbustiva dado que as plantas tendem a optimizar a sua distribuição radical em função
da disponibilidade de água e também de nutrientes. Este facto tem levado alguns autores
a estimar a distribuição das raízes a partir de modelos de água no solo (Musters &
Bouten, 1999; Wijk & Bouten, 2001).
As funções de pedotransferência e as equações de Mualem-Van Genuchten
utilizadas em Wösten et al. (1999) para o estabelecimento da European Database of
Soil Hydraulic Properties (HYPRES), revelaram uma subestimação da humidade do
solo quando comparada com os valores obtidos em laboratório para valores semelhantes
de pressão hidrostática equivalente. Há que referir que seria de esperar à partida alguma
discrepância dado que as equações de pedotransferência utilizadas resultaram de
relações empíricas destinadas a funcionar com um leque alargado de tipos de solo da
Europa. Esta subestimação esteve na origem dos desvios verificados em termos da
modelação da dinâmica da água no solo pelo modelo SWADY. É de supor que a
aplicação do modelo a outro tipo de solo possa dar origem ou não a desvios de maior ou
menor amplitude, dependendo do grau de adequação das funções empíricas utilizadas,
133
ao solo em questão. A este respeito o modelo aqui apresentado não constitui uma
excepção dentro do universo de modelos de água no solo, já que quase todos
apresentam alguma dependência relativamente à utilização de funções empíricas para
estimar as propriedades hidráulicas do solo (Feddes et al., 2001). Em todo o caso os
desvios verificados podem ser devidos a outro tipo de razões incluindo o próprio
processo de medição (Musters, 1998). Os erros de medição podem ter sido originados
de diversas formas, desde erros de medição, a alterações causadas na estrutura do solo
(Rothe et al., 1997) até ao crescimento preferencial das raízes junto aos tubos(Maertens
& Clauzel, 1982; Merril, 1992), ou ainda a erros de calibração. No que toca ao modelo,
algumas das simplificações utilizadas contribuirão seguramente para uma parte dos
desvios observados. Em particular há que referir a não contabilização dos processos de
dinâmica radícular ao longo do ano e o facto de algumas propriedades hidráulicas do
solo não serem contabilizadas tais como a condutividade hidráulica ou a histerese
característica das curvas de retenção de humidade (Feddes & Koopmans, 1998). Para
finalizar este aspecto, há que referir que o modelo poderia igualmente ter em conta as
características particulares da camada de folhada/húmus nos processos de infiltração e
evaporação. Na verdade os resultados (medidos e modelados) obtidos para a primeira
profundidade estudada (15 cm) não podem ser considerados representativos dos
fenómenos que ocorrem junto à superfície do solo. Para além da existência de
mecanismos específicos que controlam os fluxos de água, esta zona do solo é
directamente influenciada por todos os agentes meteorológicos. A existência de um
leque alargado de mecanismos influenciando as entradas e as saídas de água, conduz a
uma elevada variabilidade desta primeira camada em termos de teor de água, a qual não
pôde ser simulada pelo modelo. Basicamente o papel da camada superficial foi o de
actuar como uma camada tampão, relativamente às camadas abaixo, o que é sem dúvida
uma considerável simplificação tendo em conta a sua especificidade em termos do
balanço de água no solo. Este efeito tampão foi por exemplo responsável pelo atraso
verificado, entre a primeira chuvada de Setembro e a chegada da frente de
humedecimento a 15 cm de profundidade. No entanto, em termos gerais o modelo foi
capaz de reproduzir a dinâmica da água no solo tal como foi obtida através das
medições. Em particular são de referir os resultados obtidos na simulação do efeito do
fogo no armazenamento de água no solo. Estes resultados basicamente confirmaram
que, para situações semelhantes à estudada, o maior efeito de curto prazo de um
incêndio em termos de água no solo, é a redução da transpiração pelas plantas. Deste
134
modo, tanto o modelo como os dados reais
revelaram que os mais intensamente
estudados efeitos do fogo na redução da infiltração, no aumento do escoamento
superficial e no aumento da evaporação, não parecem ser a causa fundamental que
controla a dinâmica da água no solo, no curto prazo.
Muito embora possamos considerar encorajadores os resultados das simulações
utilizando o modelo SWADY, estão programados alguns melhoramentos a introduzir
futuramente. Estes melhoramentos deverão incluir uma abordagem mais baseada em
aspectos fundamentais da física do solo. Tal permitirá uma melhor simulação dos fluxos
de água, possibilitando a aplicação do modelo a um leque alargado de situações ao nível
das características hidráulicas do solo. Com este objectivo, um dos desenvolvimentos
futuros deverá ser a inclusão da amplamente utilizada equação de Richards (Feddes &
Koopmans, 1998; Hillel, 1998). Uma outra importante alteração destinada a melhorar a
performance do modelo consistirá na adopção de versões modificadas das funções
empíricas de pedotransferência, de forma a permitir a obtenção de uma melhor
estimativa das propriedades hidráulicas do solo.
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