(Rodentia: Cricetidae: Sigmodontinae): an integrative approach

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Zoological Journal of the Linnean Society, 2014, 171, 842–877. With 12 figures
Taxonomic review of genus Sooretamys Weksler,
Percequillo & Voss (Rodentia: Cricetidae:
Sigmodontinae): an integrative approach
ELISANDRA DE ALMEIDA CHIQUITO1, GUILLERMO D’ELÍA2 and
ALEXANDRE REIS PERCEQUILLO1*
1
Departamento de Ciências Biológicas, Escola Superior de Agricultura ‘Luiz de Queiroz’, Universidade
de São Paulo, Av. Pádua Dias, 11, Caixa Postal 9, 13418-900 Piracicaba, São Paulo, Brazil
2
Instituto de Ciencias Ambientales y Evolutivas, Universidad Austral de Chile, campus Isla Teja s/n,
Valdivia, 5090000 Chile
Received 26 July 2013; revised 5 February 2014; accepted for publication 7 February 2014
Sooretamys is a monotypic genus of the family Cricetidae, subfamily Sigmodontinae, that is distributed throughout eastern South America in the Atlantic Forest Biome, including Argentina, Brazil, and Paraguay. The taxonomic history of the forms associated with this genus is long and relatively complex, and few studies have evaluated
the taxonomic problems of this genus. To this end, our goal was to describe the degree and geographical pattern
of morphological and molecular variation in this genus to test the current hypothesis that the genus is monotypic,
and, as a consequence, to determine the status of the nominal forms associated with Sooretamys. Accordingly, we
employed morphometric, morphological, and molecular tools, according to an integrative taxonomy approach. The
results show that some level of morphometric discontinuity is present between the individuals from Paraguay and
those from adjacent localities in Brazil and Argentina; sharp discontinuities were not observed in qualitative traits.
Molecular analyses of the mitochondrial cytochrome b gene showed that the Paraguayan populations have some
degree of genetic differentiation, but the haplotypic variants do not form a monophyletic group. Thus, the evidence so far suggests a difference in the genes and morphology of the Paraguayan population, but there is no
consistent resolution (e.g. lack of monophyly) to show that specimens from Paraguay represent a distinct population that would merit taxonomic recognition. Thus, we recognize a single species within the genus Sooretamys,
named Sooretamys angouya. The pattern of morphological and genetic differentiation of Sooretamys could be the
result of divergence with gene flow. However, our data also correspond in some aspects with the model advanced
by Carnaval & Moritz, which claims the existence of stable Atlantic Forest areas where the forest biota persisted
during the Quaternary climatic fluctuations. Whatever process has occurred, S. angouya represents one species
with a complex evolutionary history, and the analysis of additional samples would be welcome to further elucidate the process of diversification of this taxon.
© 2014 The Linnean Society of London, Zoological Journal of the Linnean Society, 2014, 171, 842–877.
doi: 10.1111/zoj.12146
ADDITIONAL KEYWORDS: biogeography – cytochrome b – geographical variation – morphology – morphometry
– Neotropical region – Oryzomyini – phylogeography – South America – taxonomy.
INTRODUCTION
The tribe Oryzomyini consists of 30 living genera and
c. 125 species (Weksler, Percequillo & Voss, 2006;
*Corresponding author. E-mail: [email protected]
842
Percequillo, Weksler & Costa, 2011; Weksler &
Percequillo, 2011) and is the most diverse and widely
distributed of the subfamily Sigmodontinae (Cricetidae).
Its area of distribution ranges from the south-eastern
USA to Tierra del Fuego and neighbouring islands in
the southernmost portion of South America. Species
© 2014 The Linnean Society of London, Zoological Journal of the Linnean Society, 2014, 171, 842–877
INTEGRATIVE TAXONOMY OF GENUS SOORETAMYS
of Oryzomyini occupy all biomes existing in this large
area (Prado & Percequillo, 2013), and most species are
terrestrial, although scansorial, arboreal, and semiaquatic forms also exist (Musser et al., 1998; Weksler,
2006).
The oryzomyine genus Sooretamys (Weksler et al.,
2006) inhabits the Atlantic Forest, one of the most
diverse tropical forests in the world (Fonseca, 1985;
Myers et al., 2000; Ribeiro et al., 2009; Percequillo et al.,
2011). Known collecting localities for this genus extend
from southern Espírito Santo to northern Rio Grande
do Sul in eastern Brazil, reaching Misiones in northeastern Argentina and several departments in western
and eastern Paraguay (Myers, 1982; Musser & Carleton,
2005; D’Elía et al., 2008; Prado & Percequillo, 2013).
The species, Sooretamys angouya (sensu Musser &
Carleton, 2005; Weksler et al., 2006), and its associated name Mus angouya Fischer, 1814, has a long and
relatively complex taxonomic history. Other names currently associated with Sooretamys, namely Hesperomys
leucogaster Wagner, 1845, Hesperomys ratticeps Hensel,
1872, Calomys rex Winge, 1888, Oryzomys ratticeps
tropicius Thomas, 1924, and Oryzomys ratticeps
paraganus Thomas, 1924, have simpler histories, and
their link to Sooretamys resulted from type specimenbased studies (Musser et al., 1998; Musser & Carleton,
2005). However, detailed morphometric and morphological comparisons have not yet been performed.
Currently, all aforementioned names are considered
to be synonyms of S. angouya, and no subspecies are
recognized (Musser & Carleton, 2005; Weksler &
Percequillo, 2011). The unique hypothesis regarding
the evolutionary history of this species and molecular variation amongst populations (Miranda et al., 2007)
considers, mainly, the southern portion of the
species’ distribution in Brazil and does not discuss taxonomic and nomenclatural issues. Instead, only
phylogeographical issues have been evaluated,
focusing on geographical structure and genetic divergence. Consequently, in the absence of a formal
revision of the genus, the status of the species-group
names associated with this generic taxon is pending
assessment.
Recently, a ‘new’ taxonomic approach, so-called integrative taxonomy (Dayrat, 2005; Padial et al., 2009),
suggests the combination of several sources of evidence and evolutionary theories to clarify taxonomic
questions and evolutionary history (see also Patton et al.,
1997). However, it must be noted that this approach
is by no means new to sigmodontine taxonomy: for more
than two decades, researchers have integrated morphological, karyotypic, and molecular data (e.g. Patton
& Hafner, 1983; Patton, da Silva & Malcolm, 2000;
Pardiñas, D’Elía & Cirignoli, 2003; D’Elía & Pardiñas,
2004; Pardiñas et al., 2005; Percequillo, Hingst-Zaher
& Bonvicino, 2008; Percequillo et al., 2011).
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Our goal in this study was to describe the degree
and geographical pattern of morphological and molecular variation in the genus Sooretamys to test the
current hypothesis that the genus is monotypic and,
as such, to determine the status of the nominal forms
associated with Sooretamys. Similarly, we aim to provide
information on the evolutionary history of this endemic
Atlantic Forest genus.
MATERIAL AND METHODS
SPECIMENS AND SAMPLING
We studied 478 specimens (Appendix 1) of the genus
Sooretamys housed in the following museums and institutional collections: American Museum of Natural
History, New York (AMNH); Departamento de Genética
da Universidade Federal do Rio Grande do Sul, Porto
Alegre (UFRGS); Departamento de Sistemática e
Ecologia da Universidade Federal da Paraíba, João
Pessoa (UFPB); Facultad de Ciencias Naturales y
Museo, Universidad Nacional La Plata, La Plata (MLP);
Fundação Universidade Regional de Blumenau,
Blumenau (FURB); Fundação Zoobotânica, Porto Alegre
(FZB/RS); Instituto Nacional de Pesquisas da Amazônia,
Manaus (INPA); Laboratório de Mamíferos Aquáticos,
Universidade Federal de Santa Catarina, Florianópolis
(UFSC); Museo Argentino de Ciencias Naturales
‘Bernardino Rivadavia’, Buenos Aires (MACN); Museu
de Ciências Naturais da Universidade Luterana do
Brasil, Canoas (MCNU); Museu de Historia Natural
Capão da Imbuia, Curitiba (MHNCI); Museu de Zoologia
da Universidade de São Paulo, São Paulo (MZUSP);
Museu Nacional da Universidade Federal do Rio de
Janeiro, Rio de Janeiro (MN); Museu Paraense Emilio
Goeldi, Belém (MPEG); Museum of Comparative Zoology,
Harvard University, Cambridge (MCZ); Museum of Vertebrate Zoology, University of California, Berkeley (MVZ);
Museum of Zoology of University of Michigan, Ann Arbor
(UMMZ); National Museum of Natural History,
Smithsonian Institution, Washington, D.C. (NMNH);
Naturistorisches Museum Wien, Wien (NMW); The
Natural History Museum, London (NHM). We also analysed un-catalogued specimens provided by Meika
Alessandra Mustrangi (MAM), Alexandre Uarth
Christoff (AUC), Renata Pardini (RP), Ana Cristina
Monteiro Leonel (ACL), and Estação Ecológica do
Bananal (EEB), housed at MZUSP and Guillermo D’Elía
(GD), housed at Colección de Mamíferos, Universidad
Austral de Chile. In addition, tissue samples were loaned
by institutions, such as Texas Tech Museum (TK), and
collectors, such as Marcelo Passamani (MP), Ricardo
Siqueira Bovendorp (RSB), and Cibele Rodrigues
Bonvicino (CRB). Two acronyms of sequences downloaded from GenBank could not be identified: AFV
(Miranda et al., 2007) and EM (Bonvicino & Moreira,
2001).
844
E. A. CHIQUITO ET AL.
Not all specimens were included in both approaches: the morphological (either quantitative or
qualitative) and molecular ones. For instance, 22 specimens were analysed by both approaches, 29 only for
the molecular one because of local small sample
sizes or age criteria not being useful in the morphological approach, and 427 only morphologically,
with no tissues available, represented by old specimens from museums. Appendix 1 lists the samples
used in each analysis performed throughout this study.
Type specimens of most nominal forms associated with
S. angouya were assessed in the study. Regrettably,
no tissue samples from these specimens were available; however, specimens from localities close to the
type localities of most nominal forms were included
in the analyses.
For all collecting localities, we obtained information on geographical coordinates and altitude (when
available) from collector labels, online databases (National Geospatial-Intelligence Agency website: http://
geonames.nga.mil/namesgaz), or gazetteers (Paynter Jr.,
1989, 1995; Paynter Jr. & Traylor Jr., 1991); data were
organized in a Gazetteer (Appendix 2). To obtain larger
sample sizes with at least four adult individuals for
the statistical analyses, specimens from different collecting localities were pooled according to the criteria
established by Vanzolini & Williams (1970): close geographical proximity, absence of major geographical barriers amongst localities, such as altitudinal levels or
major rivers, and lack of obvious discrepancy in size
and shape amongst contiguous samples. Considering
these criteria, we were able to group specimens into
15 samples that cover most of the geographical distribution of the genus (Table 1, Fig. 1).
Comparative analyses amongst geographical samples
were performed using the method of transects (Vanzolini,
1970; Vanzolini & Williams, 1970), which are a ‘series
of localities more or less linearly arranged between,
and including, major samples’. This method is used
to recognize sharp discontinuities throughout the geographical range of collection samples. In addition, we
mapped the frequency of qualitative and quantitative characters throughout the geographical samples
available, as performed previously by Musser (1968).
We established two transects: the first, which connects samples along the Atlantic Forest, is associated
with the hills and highlands of Serra do Mar across
a latitudinal gradient, ranging from warmer evergreen forest (in the northern localities) to colder evergreen forests, some mixed with Brazilian Pine,
Araucaria angustifolia, in the south; the second transect
is orientated along a vegetation and moisture gradient, from the coastal region, with evergreen forests,
to the interior forests, with drier and semideciduous
forests, as well as riparian grasslands of the Paraná
and Paraguay river basins.
MORPHOLOGICAL-BASED ANALYSES
Several qualitative traits were surveyed, but after discarding those that were nonvariable and those that
showed no informative variation, we analysed the following characteristics: colour of dorsal and ventral body
surfaces, length of tufts of ungual hair relative to the
length of claws, dorsoventral countershading of the tail,
presence of anteromedian flexus in the anterocone
of molar 1 (M1), and length of incisive foramina relative to M1 alveoli. To describe the qualitative character variation, we used the character states proposed
by Hooper & Musser (1964), Carleton (1973, 1980), Reig
(1977), Voss & Linzey (1981), Voss (1988, 1993), Carleton
& Musser (1989), Voss & Carleton (1993), Steppan
(1995), and Weksler (2006). Qualitatively, the samples
exhibit a marked variation in relation to specimen age
regarding pelage colour and texture, molar wear, suture
fusion, and other cranial features. To standardize this
variation, we used four age classes based on molar wear,
modified from Voss (1991) as follows. Age class 1: first
and second molars with no apparent wear, third molar
usually non-erupted or newly erupted with main cusps
still closed, labial lophs well developed and isolated,
labial and lingual flexus deep and distinct. Age class
2: first and second molars with minor wear and small
exposure of dentine, third molar already showing
minimal to moderate wear, anteroloph and mesoloph
may be connected to paracone through marginal
lophules, posteroloph nearly fused to metacone, marginally. Age class 3: first and second molars with moderate wear; third molar with marked wear and a nearly
flat surface; anteroloph and mesoloph fused marginally to paracone, forming long anterofosset and
mesofosset, respectively; posteroloph completely fused
to metacone, forming a distinct mesofosset. Age class
4: first and second molars with heavy wear, indistinct cusps, and massive exposure of dentine; third molar
quite flat, with major exposure of dentine; anteroloph,
mesoloph, and posteroloph indistinct, fused to major
cusps. However, no noticeable variation in shape is
present regarding sex, with males and females being
quite similar.
For morphometric analyses, 15 cranial measurements (Fig. 2) were obtained with digital callipers to
the nearest 0.01 mm: occipitonasal length (ONL);
condylo-incisive length (CIL), measured from the greater
curvature of one upper incisor to the articular surface
of the occipital condyle on the same side; length of
diastema (LD), from the crown of the first upper molar
to the lesser curvature of the upper incisor on the same
side; length of molars (CLM1−3), crown length from
molar 1 (M1) to molar 3 (M3); breadth of M1 (BM1),
greatest crown breadth of the first maxillary molar
across the paracone−protocone; length of incisive
foramen (LIF), greatest anterior−posterior dimension
845
Table 1. Available samples pooled to allow the definition of 15 large-size samples and the localities included. The numbers
in parentheses are the sample size of adults in each pooled sample, and the numbers before the locality name correspond to the gazetteer
Pooled samples (N)
Localities (N)
South of Minas Gerais (15)
43
46
48
49
135
139
156
169
173
142
147
155
170
131
136
137
144
145
146
152
153
154
162
55
65
104
108
111
112
120
102
103
114
117
119
124
128
129
82
85
95
96
99
100
79
84
92
78
83
87
88
59
Boracéia-Casa Grande (16)
Riacho Grande (8)
Cotia-Piedade (18)
Upper Rio Paranapanema (22)
Upper Rio Iguaçú (11)
Rio Itajaí-Açú Basin (16)
Rio Tramandaí Basin (8)
RioTaquari-Antas Basin (9)
North-west Rio Grande do Sul (4)
Ponta Grossa (5)
Alto da Consulta, Poços de Caldas (3)
Morro do Ferro, Poços de Caldas (3)
Poços de Caldas (7)
Posses, 13 km south-east of Itanhandú (2)
Boracéia, Estação Biológica de Boracéia (7)
Casa Grande, Biritiba-Mirim (9)
Furnas, Riacho Grande (5)
Paranapiacaba (2)
Ribeirão Pires (1)
Caucaia do Alto (7)
Cotia (8)
Furnas, Piedade (1)
Piedade, São Paulo (2)
Apiaí (7)
Canaleta AB, Companhia de Cimento Nassau, Ribeirão Grande (1)
Canaleta T3,4, Ribeirão Grande (1)
Corrego Água Limpa, C C Nassau, Ribeirão Grande (1)
Corrego Barracão, Ribeirão Grande (1)
Corrego Fernandes, C C Nassau, Ribeirão Grande (1)
Fazenda Intervales Sede (2)
Fazenda Intervales, Base da Bocaina (2)
Fazenda Intervales, Base do Carmo (3)
Itararé (3)
Guaricana, São José dos Pinhais (1)
Usina de Guaricana, São José dos Pinhais (1)
Bugre, Três Barras (1)
Estação Ecológica Bracinho/Piraí, Joinville (4)
Fazenda Sta Alice, Rio Negrinho (2)
Floresta Nacional Três Barras (1)
Reserva Biológica Sassafrás, Dr. Pedrinho (1)
Barragem do Garcia, Angelina (1)
Barragem do Rio São Bento, Siderópolis (1)
Hotel Plaza Caldas da Imperatriz, Caldas da Imperatriz (1)
Mono, Parque das Nascentes, Indaial (4)
Pinheiro Alto, Anitápolis (= Pinheiros, Alto-Anitápolis) (1)
Terceira Vargem, Parque das Nascentes, Blumenau (2)
Vale do Espingarda, Parque das Nascentes, Indaial (4)
Vale da Indústria de Fosfatados Catarinense, Anitápolis (2)
Faxinal, Norte da Lagoa Itapeva, Torres (2)
Itapeva, Parque Estadual de Itapeva, Torres (1)
Pontal do Norte, Lagoa Palmital, Osório (2)
Pró-Mata, São Francisco de Paula (1)
Tramandaí, Lenha Seca, Lagoa de Tramandaí (1)
Vale da Encantada/Barra do Ouro, Maquiné (1)
Cruzeiro do Sul (6)
Guaporé (1)
Nova Roma do Sul (2)
Cruz Alta (1)
Fazenda Aldo Pinto, São Nicolau (1)
Lajeado Grande, Alpestre (1)
Lajeado Grande, Rio dos Índios (1)
Parque Estadual Vila Velha, Ponta Grossa (5)
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Table 1. Continued
Pooled samples (N)
Localities (N)
Lower Rio Iguaçú (5)
54
61
64
66
106
107
116
126
127
7
8
12
26
39
184
185
186
188
189
190
192
195
West Santa Catarina (17)
Misiones (9)
Río Tebicuary Basin (27)
Foz do Rio Capoteiro, Pinhão (2)
Reserva, Pinhão (1)
Usina Hidroelétrica Salto Caxias, Foz do Chopim, Cruzeiro do Iguaçú (1)
Vila UHE Segredo, Copel, Pinhão (1)
Canteiro de Obras, Pequena Central Hidroelétrica Alto Irani, Arvoredo (2)
Canteiro de Obras, Pequena Central Hidroelétrica Plano Alto, Xavantina (1)
Linha Voltão, Xaxim (1)
Usina Hidroelétrica Itá (2)
Usina Hidroelétrica Quebra Queixo, Rio Xapecó, São Domingos/Ipuaçú (11)
30 km from Puerto Bemberg, Rio Uruguay (Rio Urugua-í) (7)
60 km from Puerto Iguazú, Rio Iguazú (1)
Arroyo Uruguay, Departamento General Belgrano (1)
Junção dos rios Iguazú e Alto Paraná, Puerto Aguirre (1)
Tobuna, Depto. San Pedro (5)
Orillas del Río Tebicuary (1)
2.7 km by road north of San Antonio (9)
Ayolas, 5 km by road east-north-east of Ayolas (4)
Costa del Río Tebicuary (1)
Orillas del Río Tebicuary (1)
San Ignacio (3)
Costa del Río Tebicuary (4)
Sapucay (4)
S Minas Gerais
BRAZIL
Boracéia-Casa Grande
PARAGUAY
Ponta Grossa
Rio Tebricuary
basin
Misiones
Riacho Grande
Cotia-Piedade
Lower
Rio Iguaçú
Upper Rio Paranapanema
Upper Rio Iguaçú
W Santa Catarina
ARGENTINA
Rio Itajaí-Açú basin
NW Rio Grande do Sul
ATLANTIC
OCEAN
Rio Taquari-Antas basin
Rio Tramandaí basin
Figure 1. Samples of genus Sooretamys used in the morphometric and morphological analysis of geographical variation. Ovals indicate the samples that were pooled to allow the definition of 15 large-size samples (as explained in the
text and Table 1).
of one incisive foramen; breadth of incisive foramen
(BIF), greatest dimension measured across the internal surface of both incisive foramen; breadth of rostrum
(BR), greatest dimension measured across the exter-
nal border of the nasolacrimal capsules; length of nasals
(LN), greatest anterior−posterior dimension of one
nasal bone; length of palatal bridge (LPB), measured
from the posterior border of the incisive foramen to
LIF
LN
BR
BIF
BM1
CLM1-3
LPB
LOF
ZB
ONL
CZL
HBC
BZP
CIL
LD
Figure 2. Skull of an adult specimen of genus Sooretamys
depicting the craniodental measurements employed in the
morphometric analysis [specimen MZUSP 21919, from Casa
Grande, Salesópolis, São Paulo, Brazil (ONL: 42.05 mm)].
Abbreviations: BIF, breadth of incisive foramen (greatest
dimension measured across the internal surface of both incisive foramen); BM1, breadth of molar 1 (greatest crown
breadth of the first maxillary molar across the
paracone−protocone); BR, breadth of rostrum (greatest dimension measured across the external border of the
nasolacrimal capsules); BZP, breadth of zygomatic plate
(across central area of zygomatic plate); CIL, condyloincisive length (measured from the greater curvature of one
upper incisor to the articular surface of the occipital condyle
on the same side); CLM1−3, length of molars (crown length
from molar 1 to molar 3); CZL, condylozygomatic length;
HBC, height of braincase; LD, length of diastema (from the
crown of the first upper molar to the lesser curvature of
the upper incisor on the same side); LIF, length of incisive foramen (greatest anterior−posterior dimension of one
incisive foramen); LN, length of nasals (greatest
anterior−posterior dimension of one nasal bone); LOF, length
of orbital fossa (greatest length of the orbital fossa between
the squamosal and maxillary roots of the zygomatic arch);
LPB, length of palatal bridge (measured from the posterior border of the incisive foramen to the anterior border of
the mesopterygoid fossa); ONL, occipitonasal length; ZB,
zygomatic breadth (greatest dimension across the squamosal
root of zygomatic arches).
847
the anterior border of the mesopterygoid fossa; height
of braincase (HBC); zygomatic breadth (ZB), greatest
dimension across the squamosal root of zygomatic
arches; breadth of zygomatic plate (BZP), across central
area of zygomatic plate; condylozygomatic length (CZL);
length of orbital fossa (LOF), greatest length of the
orbital fossa between the squamosal and maxillary roots
of the zygomatic arch.
Initially, quantitative variables were tested for uniand multivariate normality using Kolmogorov−Smirnov
and Mardia’s Kurtosis tests, respectively. Statistical
differences amongst age and sexual classes were diagnosed by ANOVA and Tukey’s test. In addition, sexual
differences were also tested in adults using the
Student’s t test. We used a level of significance of 0.05
for all statistical analyses performed. We used distinct sample sizes depending on the analysis performed: to evaluate normality, we used samples with
more than 25 specimens; to test dimorphism, our
samples included at least eight specimens and contained equal proportions of males and females; and to
study age variation, we used samples with more than
one individual for each age class.
Musser (1968) employed the frequency of morphological character states, both quantitative and qualitative, to assess the geographical variation of Sciurus
aureogaster, establishing an important means of coupling geographical variation with nomenclatural attribution. Therefore, variation for each qualitative
morphological character was codified in character states.
Polymorphic traits were summarized by the frequency at which the state is observed in each geographical sample studied (Musser, 1968). We employed
inferential error-bar diagrams (mean ± 95% of confidence interval; Simpson, Roe & Lewontin, 2003;
Cumming, Fidler & Vaux, 2007) for the largest available samples of skull measurements (external dimensions were not included in statistical analyses as they
were recorded by distinct collectors; descriptive statistics of external dimensions were used only in general
comparisons). Multivariate analyses were performed
with geographically pooled samples (Table 1, Fig. 1).
Discriminant analyses (DA) using natural base logtransformed cranial measurements were performed comparing the 15 geographical samples simultaneously
(Simpson et al., 2003; Manly, 2008). We also generated error bars with the scores of the first canonical
function to evaluate the multivariate structure
along the distribution of geographical samples. Specimens with missing values were discarded from both
the univariate and multivariate analyses.
To test the hypothesis that the differences amongst
geographical samples could be explained by the isolationby-distance model (Wright, 1943), we compared geographical and morphometric distance matrices with
a Mantel test (Mantel, 1967; Manly, 2008; Moreira &
848
Oliveira, 2011) with 10 000 random permutations. Both
matrices used in this test were calculated based on
sample centroids, with geographical distances in kilometres and Mahalanobis distance for the morphometric
matrix. The statistical analyses were performed in R
2.13.1 (R Development Core Team, 2005), SPSS 13.0
for Windows (SPSS, Inc., 2004), and STATISTICA v.
9 (StatSoft, Inc. 2009).
PHYLOGEOGRAPHICAL ANALYSIS
The genetic analyses are based on 53 DNA sequences
of Sooretamys (Table 2), 15 from GenBank, and from
specimens gathered from 31 localities, covering almost
entirely the geographical distribution of the genus
(Fig. 3, Appendices 1, 2). The tree was rooted with the
outgroup criterion, which was composed of sequences
of one specimen of Nectomys squamipes (GenBank accession number AF181283), one of Aegialomys
xanthaeolus (EU340015), and one of Cerradomys
subflavus (AF181274), all of which are oryzomyines that
are closely related to Sooretamys (Percequillo et al.,
2011).
DNA was extracted from liver samples using the
ChargeSwitch gDNA Mini Tissue Kit (Invitrogen). A
675-bp region of the cytochrome b gene was amplified via PCR using primers MVZ05 and MVZ16 (Smith
& Patton, 1993). The annealing temperature was
52.5 °C, the PCR programme was the same as D’Elía
(2003), and the PCR reaction mixture was as follows
for a 25-μL total reaction volume: 2.5 μL primers
(10 mol μL−1), 2.5 μL buffer (Invitrogen), 1.5 μL MgCl2
(50 mM), 0.25 μL deoxynucleotide triphosphates (10 mM),
0.20 μL Platinum Taq DNA Polymerase, 1 μL DNA,
and 17.05 μL ultrapure water. Amplicons were purified with the UltraClean PCR Clean-Up Kit (Mo
Bio Laboratories, Inc.) and sequenced using the
DYEnamic ET Dye Terminator Kit (MegaBACE) in
an ABI Prism 3100 Genetic Analyzer sequencer (Applied
Biosystems) following the manufacturer’s protocols.
Chromatograms were checked and manually edited
in CHROMAS LITE 2.01 software (Technelysium Pty
Ltd, 2007).
DNA sequences were aligned with ClustalW
(Thompson, Higgins & Gibson, 1994) using the default
alignment parameters and were corrected manually.
Pairwise genetic distances were calculated in MEGA
5 (Tamura et al., 2011) as p-distances and Kimura two
parameters (K2p) (Supporting Information Table S1).
Gene trees were constructed using maximum parsimony (MP; Farris, 1982) and Bayesian analysis (BA;
Yang & Rannala, 1997). MP analysis was performed
in PAUP* (Swofford, 2000) with characters treated as
unordered and equally weighted, 500 replicates of heuristic searches with random addition of sequences, and
tree bisection reconnection branch swapping. The rela-
tive support of the recovered clades was calculated by
performing 1000 bootstrap (BS) replications with five
replicates of random sequence addition each. BA analysis was performed using MrBayes 3.1 (Ronquist &
Huelsenbeck, 2003) by implementing a model of sequence evolution that includes six categories of base
substitutions, a gamma-distributed rate parameter and
a proportion of invariant sites. Uniform-interval priors
were assumed for all parameters except base composition and generalized time-reversible parameters, which
assumed a Dirichlet prior process. Two independent
runs with four chains were allowed to proceed for
10 000 000 generations with trees sampled every 100
generations. The first 25% of the trees were discarded as burn-in, and the remaining trees, sampled well
after stationarity was reached, were used to compute
posterior probability (PP) estimates for each clade.
In addition, as another method of visualizing relationships amongst haplotypes of Sooretamys, a haplotype
network was created via statistical parsimony
(Templeton, Crandall & Sing, 1992) using the program
TCS (Clement, Posada & Crandall, 2000).
Finally, to further explore how the observed genetic
variation is geographically structured, hierarchical analyses were conducted in the form of analysis of molecular variance (AMOVA; Excoffier, Smouse & Quattro,
1992) using ARLEQUIN v. 3.1 (Excoffier, Laval &
Schneider, 2005). Distinct hierarchical haplotype arrangements were defined based on sampling localities (Fig. 3), and these were grouped by geographical
regions, by groups found in the morphological analyses (see below), or to match the traditional taxonomic scheme of Thomas (1924).
SPECIES AND
SUBSPECIES DEFINITION
We employed all of the aforementioned phenotypic traits
to recover unique combinations of diagnostic characters and monophyletic lineages in order to recognize
species in the genus Sooretamys, which is a procedure akin to the phylogenetic species concept
advocated by Cracraft (1983). This concept favours
diagnosability, as species are the smallest diagnosable cluster of organisms that exhibit a parental pattern
of ancestry and descent. Although not in common usage
under the phylogenetic species concept (e.g. Frost, Kluge
& Hillis, 1992), the subspecies category could be employed eventually, upon the recognition of geographical lineages. According to Mayr (1963), subspecies are
evolutionary unities only when they coincide with geographical isolates; otherwise, they represent a convenient system of taxonomic classification. Similarly,
Frost et al. (1992) affirmed that subspecies can be either
invented (mere ‘artifacts of idealizing diagnosis’) or discoverable items (‘temporarily isolated lineages’); if they
represent discoverable entities, they are elements of
849
Table 2. List of mitochondrial DNA sequences downloaded from GenBank and sequenced in the present study, with the
respective accession number. Localities are mapped in Figure 3
Voucher/tissue
no.
GenBank
accession no.
BP
Locality (locality number)
Reference
Ingroup
RSB6595
AFV21
AFV22
CNP1998
CNP2524
CRB1271
EM1207
FURB12041
KF976464
EF455034
EF455035
KF976492
KF976493
AF181281
AF181280
KF976467
675
1143
1143
675
675
801
801
675
Present study
Miranda et al., 2007
Miranda et al., 2007
Present study
Present study
Bonvicino & Moreira, 2001
Present study
FURB12151
FURB477
FURB5070
FURB5900
KF976468
KF976469
KF976470
KF976471
675
675
675
675
FURB9230
FURB9238
FURB9252
FURB9696
FURB9749
KF976472
KF976473
KF976474
KF976475
KF976476
675
675
675
675
675
FURB9790
FURB9836
FURB9867
GD257
GD265
GD273
GD274
GD52
GD543
MCNU1229
MCNU1230
MCNU1291
MCNU1292
MCNU1625
MCNU622
MHNCI4781
MN37777
MN37778
MN37780
MN37783
MN37785
MN37786
MN37789
MN37790
MN37794
MN50234
MP301
TK61763
UFPB335
UFPB338
UMMZ174979
UMMZ174984
UMMZ175077
UMMZ175081
UMMZ175083
UMMZ175099
Outgroup
CRB540
KF976477
KF976478
KF976479
KF976480
KF976481
KF976482
KF976483
KF976487
KF976490
KF976494
KF976495
KF976496
KF976497
KF976498
KF976499
KF976466
EF455036
EF455037
EF455038
EF455039
EF455040
EF455041
EF455042
EF455043
EF455044
EU579511
KF976500
EU579512
EF455046
KF976465
KF976488
KF976491
KF976486
KF976484
KF976485
KF976489
675
675
675
675
675
675
675
675
675
675
675
675
675
675
675
675
801
801
1143
801
801
801
801
801
1143
1143
675
1143
801
675
675
675
675
675
675
675
Cotia, São Paulo, Brazil (147)
Caxias do Sul, Rio Grande do Sul, Brazil (76)
Caxias do Sul, Rio Grande do Sul, Brazil (76)
Refúgio Moconá, Misiones, Argentina (30)
Refúgio Moconá, Misiones, Argentina (30)
Teresópolis, Rio de Janeiro, Brazil (69)
Fazenda Intervales, São Paulo, Brazil (152)
Terceira Vargem, Parque das Nascentes, Blumenau, Santa Catarina,
Brazil (124)
Reserva Biológica Sassafrás, Dr. Pedrinho, Santa Catarina, Brazil (120)
Vale do IFC, Anitápolis, Santa Catarina, Brazil (129)
UHE Itá, Itá, Santa Catarina, Brazil (126)
Vale do Espingarda, Parque das Nascentes, Indaial, Santa Catarina,
Brazil (128)
UHE Quebra Queixo, São Domingos, Santa Catarina, Brazil (127)
Mono, Parque das Nascentes, Indaial, Santa Catarina, Brazil (117)
Reserva Particular do Patrimônio Natural Figueira Branca, Gaspar,
Santa Catarina, Brazil (121)
Paraguari, Paraguari, Paraguay (194)
Centu-Cue, Misiones, Paraguay (187)
Costa Norte, Paraguari, Paraguay (193)
Nova Roma do Sul, Rio Grande do Sul, Brazil, (92)
Nova Roma do Sul, Rio Grande do Sul, Brazil (92)
Encruzilhada do Sul, Rio Grande do Sul, Brazil (81)
Encruzilhada do Sul, Rio Grande do Sul, Brazil (81)
Cachoeirinha, Rio Grande do Sul, Brazil (74)
Maquiné, Rio Grande do Sul, Brazil (89)
Córrego Barracão, Ribeirão Grande, São Paulo, Brazil (145)
Florianópolis, Santa Catarina, Brazil (113)
Torres, Rio Grande do Sul, Brazil (98)
Tainhas, Rio Grande do Sul, Brazil (97)
Mostardas, Rio Grande do Sul, Brazil (90)
Mostardas, Rio Grande do Sul, Brazil (90)
Tramandaí, Rio Grande do Sul, Brazil (99)
Osório, Rio Grande do Sul, Brazil (93)
Teresópolis, Rio de Janeiro, Brazil (69)
Itamonte, Minas Gerais, Brazil (44)
Yacare, Ñeembucu, Paraguay (191)
Hotel Fazenda Monte Verde, Venda Nova, Espírito Santo, Brazil (41)
Hotel Fazenda Monte Verde, Venda Nova, Espírito Santo, Brazil (41)
Costa del Rio Tebicuary, Paraguari, Paraguay (192)
Fazenda Da Mata, Maracajú, Mato Grosso do Sul, Brazil
Bosque Protector Cerro Blanco, Guayas, Ecuador
Hanson & Bradley, 2008
Parque Nacional do Rio Doce, Minas Gerais, Brazil
TK134912
CEG42
AF181283.1
(Nectomys
rattus)
EU340015.1
(Aegialomys
xanthaeolus)
AF181274.1
(Cerradomys
subflavus)
801
1143
801
Present
Present
Present
Present
study
study
study
study
Present
Present
Present
Present
Present
study
study
study
study
study
Present study
Present study
Present study
Present study
Present study
Present study
Present study
Present study
Present study
Present study
Present study
Present study
Present study
Present study
Present study
Present study
Miranda et al.,
Miranda et al.,
Miranda et al.,
Miranda et al.,
Miranda et al.,
Miranda et al.,
Miranda et al.,
Miranda et al.,
Miranda et al.,
Hanson, 2008
Present study
Hanson, 2008
Miranda et al.,
Present study
Present study
Present study
Present study
Present study
Present study
Present study
2007
2007
2007
2007
2007
2007
2007
2007
2007
2007
850
)
BRAZIL
PARAGUAY
ATLANTIC
OCEAN
ARGENTINA
Figure 3. Samples of genus Sooretamys used in phylogeographical analyses. The numbers correspond to the gazetteer,
and those in parentheses are the sample size in each locality.
evolutionary biology. Therefore, we aimed to identify
diagnosable monophyletic lineages, whether species or
subspecies (as geographical isolated lineages), through
the morphological and molecular integrative approach here employed.
RESULTS
AGE AND
SEX MORPHOLOGICAL VARIATION
The nongeographical tests (age and sex variation) were
applied to the largest available samples, depending on
the analysis. Normality was verified in all of the samples
tested: Boracéia-Casa Grande (N = 39), Cotia-Piedade
(N = 59), Upper Rio Paranapanema (N = 38), Rio ItajaíAçú Basin (N = 27), and Río Tebicuary Basin (N = 30).
Only one variable (BIF) from Río Tebicuary Basin did
not exhibit normal distribution (Z = 2.552, P < 0.05),
but we chose not to exclude it from analysis because
in all other samples BIF was normally distributed.
Mardia’s Kurtosis test was applied for all adult individuals and all variables; the coefficient obtained was
355.798 (P > 0.05), which also indicated the multivariate normality of the data.
ANOVA together with post hoc Tukey tests showed
that the samples of age classes 3 and 4 from BoracéiaCasa Grande (N = 39) and Cotia-Piedade (N = 59) are
not significantly different (P > 0.05). Therefore, individuals assigned to both age classes were pooled for
subsequent analyses of variation for all of the samples;
individuals of these classes are, presumably, mature
adults.
Sexual dimorphism was investigated in adult
individuals in the samples from Boracéia-Casa
Grande (N = 16), Cotia-Piedade (N = 18), Upper Rio
Paranapanema (N = 22), Upper Rio Iguaçú (N = 11),
Rio Itajaí-Açú Basin (N = 16), Rio Tramandaí Basin
(N = 8), Rio Taquari-Antas Basin (N = 9), and Río
Tebicuary Basin (N = 27). Six variables of seven samples
showed significant differences: CLM1-3, HBC, and BZP
for Rio Itajaí-Açú Basin; BR for Rio Taquari-Antas Basin
and Río Tebicuary Basin; LPB for Upper Rio
Paranapanema; and LOF for Rio Tramandaí Basin.
These results show a lack of a consistent pattern of
sex variation across the species’ geographical range.
The absence of sexual dimorphism was verified
in several other oryzomyine species, including
Transandinomys talamancae (Musser & Williams, 1985),
Microryzomys minutus and Microryzomys altissimus
(Carleton & Musser, 1989), species of Cerradomys
(Percequillo et al., 2008), Aegialomys xanthaeolus (Prado
& Percequillo, 2011), and other oryzomyine genera (see
Musser et al., 1998; Abreu-Junior et al., 2012). Therefore, as our analysis did not reveal a pattern of sexual
dimorphism, geographical analyses were conducted with
adult individuals from both sexes pooled together.
MORPHOGEOGRAPHICAL
VARIATION
Qualitative characteristics
The few traits that showed consistent variation within
and amongst samples in Sooretamys are described and
summarized below, and represented graphically on
Figure 4:
G
G
TRB
RGR
URI
IAB
TEB
MIS
WSC
LRI
TEB
PTG
WSC
MIS
CPI
RGR
PTG
CPI BCG
URP
LRI
RGR
URP
BCG
Figure 4. Morphological variation in Sooretamys throughout South America, expressed in frequency histograms, for 14 of the 15 pooled samples studied here
(except Southern Minas Gerais) divided in two transects: left, north−south transect; right, east−west. Each sample is represented by three letters: BoracéiaCasa Grande (BCG); Riacho Grande (RGR); Cotia-Piedade (CPI); Upper Rio Paranapanema (URP); Ponta Grossa (PTG); Upper Rio Iguaçú (URI); Rio Itajaí-Açú
Basin (IAB); Rio Tramandaí-Basin (TRB); Rio Taquari-Antas Basin (TAB); north-west of Rio Grande do Sul (NRS); Lower Rio Iguaçú (LRI); W Santa Catarina
(WSC); Misiones; Argentina (MIS); and Río Tebicuary Basin (TEB). The bars represent the frequency of each characteristic (0 to 100%). A: colour of upper parts
(1, yellow; 2, reddish; 3, dark; 4, greyish). B: colour pattern of under parts (1, grizzled; 2, pure). C: colour of hind feet (1, brown; 2, white). D: length of ungual
tufts (1, do not reach the top of the claws; 2, reach the top of the claws). E: countershading of tail (1, unicoloured; 2, slightly bicoloured). F: incisive foramina
(1, anterior to the alveolus of molar 1 (M1); 2, in the same plane of the alveolus of M1; 3, exceeds the plane of the alveolus of M1). G: posterolateral palatal pits
(1, unique; 2 multiple). The empty spaces in the figure indicate that there is no information for certain qualitative characteristic in a given sample.
NRS
TAB
URP
F
F
CPI BCG
E
E
BCG
D
RGR
D
CPI
C
URP
C
URI
B
IAB
B
TRB
A
TAB
A
NRS
851
852
Colour of upper parts (N = 111): Four patterns of dorsal
colours were recognized: yellowish-brown, reddishbrown, dark-brown, and greyish-brown. In most of the
samples, the predominant colour is yellowish-brown,
but samples from eastern Santa Catarina (Rio Itajaí
and Upper Rio Iguaçu) have reddish-brown upper parts,
whereas samples from São Paulo state (Boracéia,
Riacho Grande, and Cotia-Piedade) are predominantly greyish-brown.
Colour of under-parts (N = 112): This characteristic is
associated with the presence of hairs with a grey basal
portion and a white or buffy apical portion, or hairs
entirely white or buffy, resulting in grizzled and pure
white or pure buffy appearance, respectively. The predominant pattern of the colour of the under-parts is
grizzled, whereas a pure colour was observed only in
Río Tebicuary sample.
Colour of hind feet (N = 76): Two states were observed: hind feet predominantly white or brown. Hind
feet that are predominantly brown occurred in Boracéia
and Río Tebicuary only; in all other samples, the hind
feet colour of most of the specimens is white.
Ungual tufts (N = 67): Ungual tufts are dense and variable in length on digits II to V, usually concealing the
claws, but very short or even absent on digit I. Two
states were recognized: short tufts not reaching the
tip of the claws and long tufts reaching or surpassing the tip of the claws. The ungual tufts are predominantly long on populations to the south and north
of the genus distribution.
Colour of tail (N = 98): Two states were observed: not
countershaded dorsoventrally, resulting in a unicoloured
tail, or countershaded dorsoventrally, with the ventral
surface slightly paler than dorsal surface, resulting in
a weakly bicoloured tail. We recorded the countershaded
tail as a predominant state only in specimens from
Misiones.
Length of incisive foramen (N = 62): Three states were
observed: posterior margins of incisive foramen that
do not reach the plane of first molars, posterior margins
that reach but do not surpass the plane of molars, and
posterior margins that surpass the plane of first upper
molars and reach the anterocone. In most of the specimens of the upper Rio Paranapanema in São Paulo
and Tramandaí, in the north of Rio Grande do Sul, the
posterior margin of the incisive foramen lies anteriorly to the M1 alveolus. In all other samples, the posterior margin of the foramen is aligned to the anterior
margin of the M1 alveolus. The long incisive foramen
surpassing the molar planes occurs only in the northern portion of the distribution, in samples from São
Paulo state.
Posterolateral palatal pits (N = 115): These perforations on the posterior portion on the palatine are unique
or multiple. When single, the pits are usually positioned on the palate level; when multiple, pits are recessed in deep and well-delimited palatine fossa. In
all samples, multiple posterolateral palatal pits recessed in deep palatine fossa are the most common state,
indeed larger specimens from São Paulo state and Paraguay present even deeper and wider fossa.
In general, some trends of morphological variation
can be recognized throughout the geographical samples
studied. Regarding the colour of upper parts, there is
a predominance of greyish-brown specimens amongst
the northern samples and a predominance of yellowishbrown samples towards the south. Long ungual tufts
are present in high frequency in the northern samples,
whereas short tufts are usually found in the southern localities. White hind feet are the most common
characteristic throughout the entire geographical distribution, but predominantly brown hind feet occur in
high frequency in some groups from Paraguay and
eastern Brazil. An incisive foramen with a posterior
margin that does not penetrate between molar series
is more frequently observed in samples from São Paulo,
southern Paraná, and northern Santa Catarina States,
in the central portion of the geographical distribution. These patterns of characteristic variation indicate that Sooretamys lacks sharp morphological
discontinuities across its geographical distribution.
Quantitative characters
ONL, LD, CIL, LIF, LN, LPB, CZL, and LOF (Fig. 5):
A strong clinal variation is observed in all these variables (although not shown in Fig. 5, all variables share
the same clinal pattern) related to the anteroposterior
axis of the skull, with mean values decreasing from
the north (south of Minas Gerais) to the south (Rio
Grande do Sul State) and south-west (Argentina and
Paraguay), with the smallest values observed in Santa
Catarina. A comparison between the northern and southern samples, southern Minas Gerais and Río Tebicuary
Basin, respectively, showed that there are no significant differences (P = 0.05) in these variables, despite
the clinal variation [ONL (t = −1.204, P = 0.243),
LD (t = 0.663, P = 0.515), CIL (t = −1.386, P = 0.180),
LIF (t = −1.288, P = 0.212), LN (t = −0.486, P = 0.632),
LPB (t = −0.136, P = 0.893), CZL (t = −1.656, P = 0.113),
and LOF (t = −1.352, P = 0.191)]. The only sharp discontinuity in this general trend is located at the western
part of the geographical range, between the samples
of Misiones and Río Tebicuary Basin, with the latter
being noticeably larger. In fact, specimens from the
south-western Río Tebicuary Basin are as large as those
from the north-eastern region; for instance, specimens of Boracéia-Casa Grande and Río Tebicuary Basin
are not significantly different (P = 0.05) in most cranial
853
S Minas Gerais (SMG)
S Minas Gerais (SMG)
(BCG)
(BCG)
Riacho Grande (RGR)
Cotia-Piedade (CPI)
Upper Rio Paranapanema (URP)
Ponta Grossa (PTG)
Lower Rio Iguaçú (LRI)
Upper Rio Iguaçú (URI)
(NRS)
Rio Itajaí-Açú basin (IAB)
Rio Taquari-Antas basin (TAB)
11
21
18
6
18
n= 4
15
8
16
11
19
17
6
16
n= 4
9
8
16
11
21
18
6
18
15
I
P PI
R G G
S B B B
NR TA TR IA UR UR C RG BC SM
n= 27
14
95% CI BM1
95% CI CLM1-3
9
I
P PI
R G G
S B B B
9
5
17
5
21
18
16
18
n= 15
18
6
18
21
11
16
8
9
4
I
P PI
R G G
S B B B
9
n= 26
15
P PI
R G G
G
B IS SC RI
TE M W L PT UR C RG BC SM
17
5
5
19
17
6
16
14
P PI
R G G
G
B IS SC RI
TE M W L PT UR C RG BC SM
95% CI BM1
16
95% CI CLM1-3
8
I
P PI
R G G
S B B B
95% CI BR
95% CI CIL
95% CI BR
9
W Santa Catarina
(WSC)
Rio Tebicuary basin
(TEB)
RioTramandaí basin (TRB)
95% CI CIL
n= 4
Riacho Grande (RGR)
Cotia-Piedade (CPI)
Upper Rio Paranapanema (URP)
Misiones (MIS)
n= 27
9
17
5
5
21
18
6
18
15
P PI
R G G
G
B IS SC I
TE M W LR PT UR C RG BC SM
n= 27
9
17
5
5
21
18
6
18
15
P PI
R G G
G
B IS SC I
TE M W LR PT UR C RG BC SM
Figure 5. Graphs, including error bars [mean ± 95% confidence interval (CI)], of the 15 pooled samples; the error bars
represent four patterns of geographical variation observed in univariate geographical analysis. The figure on the top
represents the north−south transect; the figure on the bottom, the east−west transect, as described in detail in the text.
Abbreviations: BM1, breadth of molar 1 (greatest crown breadth of the first maxillary molar across the paracone−protocone);
BR, breadth of rostrum (greatest dimension measured across the external border of the nasolacrimal capsules); CIL, condyloincisive length (measured from the greater curvature of one upper incisor to the articular surface of the occipital condyle
on the same side); CLM1−3, length of molars (crown length from molar 1 to molar 3).
measurements [ONL (t = −0.005, P = 0.996), LD
(t = −0.192, P = 0.849), CIL (t = 0.949, P = 0.348),
LIF (t = −1.375, P = 0.176), LN (t = 0.069, P = 0.946),
LPB (t = 1.775, P = 0.083), CZL (t = 1.188, P = 0.241),
and LOF (t = −0.091, P = 0.928)].
BIF, BR, HBC, ZB, and BZP (Fig. 5): These measurements also exhibit clinal variation with an abrupt discontinuity between the Argentinean and Paraguayan
samples, at the western range of the species. However,
for these variables, the specimens from Río Tebicuary
Basin are significantly larger (BIF: t = −3881, P = 0.00;
BR: t = −2639, P = 0.01; and BZP: t = −3625, P = 0.00)
than the north-eastern specimens from BoracéiaCasa Grande. For the variable ZB, the P-value
(P = 0.063) is not significant; for HBC, there is no significant difference between the two samples (P = 0.167).
In general, these two geographically separate samples
are very similar in length, but Paraguayan specimens exhibit wider and more robust rostra, with wider
incisive foramina (BR and BIF) and more robust
zygomasseteric apparatus (ZB and BZP).
854
Table 3. Descriptive statistics of the external dimensions for the 15 pooled samples of the genus Sooretamys. First line,
mean ± standard error; second line, sample size (minimum and maximum)
Variable
Length of head
Length of
and body (in mm) tail (in mm)
Sample*
South of Minas Gerais
172.8 ± 9.28
5 (157–180)
156.3 ± 15.90
13 (125–185)
Cotia-Piedade
160.1 ± 13.54
8 (145–180)
182.5 ± 43.12
13 (136–309)
Upper Rio Iguaçú
167.2 ± 14.06
7 (149.35–189)
Rio Itajaí-Açú Basin
159.2 ± 13.89
16 (126–177)
Rio Tramandaí Basin
158.3 ± 17.69
6 (136–190)
RioTaquari-Antas Basin
159.1 ± 20.28
8 (137–190)
North-west Rio Grande do Sul 167.0 ± 6.24
3 (162–174)
Ponta Grossa
155.8 ± 21.38
3 (131–169)
West Santa Catarina
150.5 ± 16.82
14 (108–180.5)
Misiones
162.0 ± 12.23
8 (135–177)
Río Tebicuary Basin
184.3 ± 8.54
25 (164–198)
204.2 ± 11.26
(187–215)
199.9 ± 7.43
13 (187–210)
206.2 ± 9.68
8 (195–220)
201.4 ± 16.32
13 (171–227)
220.1 ± 17.84
7 (194–246)
210.3 ± 14.83
16 (187–240)
218.3 ± 12.61
6 (206–240)
178.7 ± 29.57
4 (137–206)
190.3 ± 4.51
3 (186–195)
200.3 ± 22.01
3 (178–222)
187.4 ± 19.44
14 (167–240)
188.4 ± 11.62
8 (160–195)
210.4 ± 15.25
26 (159–230)
Length of hind foot,
Length of
including claw (in mm) ear (in mm)
Weight
(in grams)
38.7 ± 1.97
6 (35–40)
36.0 ± 1.53
13 (33–38)
37.2 ± 2.66
8 (35–41)
35.5 ± 4.33
13 (25–42)
38.0 ± 2.42
7 (35–41.9)
37.6 ± 2.91
16 (33.3–43)
36.2 ± 4.46
6 (27.5–40)
36.7 ± 1.67
8 (35–39)
35.6 ± 1.41
4 (34–37)
34.7 ± 3.05
3 (32–38)
35.7 ± 1.69
15 (32.7–38.6)
34.7 ± 2.05
8 (32–38)
38.5 ± 2.09
26 (35–43)
113.3 ± 21.83
6 (80–135)
–
23.2 ± 1.72
6 (21–26)
21.6 ± 3.28
13 (13–25)
22.6 ± 4.82
9 (18–34)
21.9 ± 2.22
13 (18–26)
22.6 ± 2.02
7 (18.8–25)
23.1 ± 1.86
16 (18–26.5)
22.1 ± 3.67
6 (15–25.5)
19.7 ± 3.41
8 (13–23)
22.7 ± 1.32
4 (21–24)
22.0 ± 1.41
2 (21–23)
21.0 ± 2.20
15 (16–24.5)
22.6 ± 2.57
7 (18–25)
24.6 ± 1.30
25 (22–26.5)
100
1
126.2 ± 51.97
10 (79–220)
113.1 ± 25.09
7 (84–158)
108.2 ± 26.52
12 (74–164)
108.2 ± 55.02
5 (31–172)
83.00
1
107.3 ± 23.69
3 (80–122)
100.0 ± 14.14
2 (90–110)
93.5 ± 19.24
15 (56–138)
97.00
1
128.7 ± 21.13
14 (91–157)
*There are no available external measurements for specimens of the samples from Riacho Grande and Lower Rio Iguaçu.
CLM1−3 (Fig. 5): The length of the upper molar series
has a mosaic variation, with the greatest mean values
observed in the Upper Rio Iguaçú and Lower Rio Iguaçú
samples and the smallest in Cotia-Piedade and northwest Rio Grande do Sul. Thus, there is no clear pattern
of variation across the geographical range, although
the sample from Río Tebicuary Basin also exhibits a
clear discontinuity from the samples from Misiones.
BM1 (Fig. 5): The breadth of M1 also shows a mosaic
variation, with larger mean sizes observed in Riacho
Grande and smaller in north-west Rio Grande do Sul
and west Santa Catarina, although the samples from
Upper Rio Paranapanema also have narrower molars.
For this characteristic, the samples from Río Tebicuary
Basin have one of the lowest averages (contrasting with
previous traits), but it is still larger than the closer
geographical samples of Misiones and west Santa
Catarina.
Considering the external dimensions (Table 3), the
specimens from Río Tebicuary Basin are larger in body
and tail length, and have larger ears and hind feet.
In contrast, smaller specimens were recorded in the
samples from the central-western region of southern
Brazil (Taquari-Antas Basin, north-west Rio Grande
do Sul, Ponta Grossa, west Santa Catarina, and
Misiones).
The DA performed with all 15 samples showed that
78.65% of the variation is distributed throughout the
four first discriminant functions, and CZL is the variable that predominately explains the variation amongst
groups, with strong discriminant function coefficients
in these functions (Table 4). In the first discriminant
function (DF1), which accounts for 36.71% of the variation, the most influential variables are the condyloincisive and the condylo-zygomatic length, which are
associated with the anteroposterior axis of the skull
and directly correlated to the rostral and neurocranium
855
Table 4. Standardized discriminant function coefficients for 15 log-transformed cranial variables for the 15 pooled samples
Standardized canonical discriminant function coefficients
Variable
First
Second
Third
Fourth
ONL
CIL
LD
CLM1−3
BM1
LIF
BIF
BR
LN
LPB
HBC
ZB
BZP
CZL
LOF
Canonical correlation
Function Wilk’s lambda
Eigenvalue
% Variance
−0.599
−2.516
1.131
0.223
−0.022
0.721
−0.319
0.362
0.228
0.042
0.283
−0.499
0.374
1.620
0.204
0.804
0.029**
1.827
36.71
0.598
−0.557
−0.699
0.133
−0.456
−0.081
0.561
0.503
0.154
−0.216
0.161
0.788
0.493
−1.162
0.189
0.720
0.081**
1.079
21.67
0.994
0.215
0.837
−0.607
0.878
−0.877
−0.016
0.392
−0.394
−0.258
0.018
0.598
0.226
−1.675
−0.201
0.627
0.169**
0.647
13.00
−0.332
3.503
−0.699
0.007
0.401
0.146
0.388
−0.600
−0.234
−0.226
0.068
−0.019
0.333
−1.721
−0.298
0.515
0.279ns
0.361
7.26
*Wilk’s lambda significant at P < 0.05; **Wilk’s lambda significant at P ≤ 0.001; nsWilk’s lambda not significant.
BIF, breadth of incisive foramen (greatest dimension measured across the internal surface of both incisive foramen);
BM1, breadth of molar 1 (greatest crown breadth of the first maxillary molar across the paracone−protocone); BR, breadth
of rostrum (greatest dimension measured across the external border of the nasolacrimal capsules); BZP, breadth of zygomatic
plate (across central area of zygomatic plate); CIL, condylo-incisive length (measured from the greater curvature of one
upper incisor to the articular surface of the occipital condyle on the same side); CLM1−3, length of molars (crown length
from molar 1 to molar 3); CZL, condylozygomatic length; HBC, height of braincase; LD, length of diastema (from the
crown of the first upper molar to the lesser curvature of the upper incisor on the same side); LIF, length of incisive
foramen (greatest anterior−posterior dimension of one incisive foramen); LN, length of nasals (greatest anterior−posterior
dimension of one nasal bone); LOF, length of orbital fossa (greatest length of the orbital fossa between the squamosal
and maxillary roots of the zygomatic arch); LPB, length of palatal bridge (measured from the posterior border of the
incisive foramen to the anterior border of the mesopterygoid fossa); ONL, occipitonasal length; ZB, zygomatic breadth
(greatest dimension across the squamosal root of zygomatic arches).
regions. The length of the diastema is also highly associated with DF1 and correlated to the rostral region.
Moreover, as coefficients exhibit different directions
across all variables, we assume that in addition to
size variation, there is also shape variation amongst
the samples for the most influential variables discussed above. In the second function (DF2), responsible for 21.67% of the variation, the variables ZB and
CZL explain most of the variation and are associated
with the zygomasseteric apparatus. The dispersion of
the individual scores amongst the three discriminant
functions (Fig. 6) does not allow the recognition of distinct groups, except for samples from Boracéia-Casa
Grande, Rio Taquari-Antas Basin, west Santa Catarina,
and Río Tebicuary Basin, which are enclosed by an
ellipsis that represents 67.5% of the distribution of
points for these four samples. Figure 6 shows that
the samples from Boracéia-Casa Grande and Río
Tebicuary Basin are similar (DF1), but there is a
difference in the cranial shape (DF2 mainly, but
also DF1). The scatterplot between the first and the
third discriminant function revealed no significant
pattern of variation, with wide superimposition of all
samples.
Figure 7 shows that there is a clear decrease in the
mean values of individual scores of the first discriminant function from north to south and from north to
west. Samples from southern Minas Gerais and
Boracéia-Casa Grande have average scores between
0.5 and 1. In contrast, samples from Riacho Grande,
Cotia-Piedade, Upper Rio Paranapanema, Upper Rio
Iguaçú, Rio Itajai-Açú Basin, Rio Tramandaí Basin, Rio
Taquari-Antas Basin, north-west Rio Grande do Sul,
Ponta Grossa, Lower Rio Iguaçú, and Misiones exhibit
856
4
4
3
2
2
1
1
0
-3
S Minas Gerais
Riacho Grande
Cotia-Piedade
Upper Rio Iguaçú
Rio Tramandaí Basin
Rio Taquari-Antas Basin
Ponta Grossa
Lower Rio Iguaçú
W Santa Catarina
Misiones
Rio Tebicuary Basin
0
-2
Rio Taquari-Antas
Basin
-3 Rio Taquari-Antas
-3
-2
-1
0
1
2
Basin
-4
-4
Rio Tebicuary
Basin
-1
-1
-2
Western Santa
Catarina
Samples
DF3
DF2
3
Rio Tebicuary
Basin
Western Santa
Catarina
3
4
-4
-4
-3
-2
-1
0
1
2
3
4
DF1
DF1
Figure 6. Scatterplot of the individual discriminant scores of the three first discriminant functions (DFs), obtained through
discriminant analysis, conducted with log-transformed data of 15 craniodental variables from 15 pooled samples. These
three functions (DF1, DF2, and DF3) are responsible for 36.71, 21.67, and 13% of the variation, respectively. The
ellipses cover 67.5% of the distribution of points for four samples.
S Minas Gerais
(SMG)
(BCG)
(URP)
Riacho Grande
(RGR)
(IAB)
(NRS)
Rio Taquari-Antas Basin
(TAB)
95% CI DF1
Upper Rio Iguaçú
(URI)
Misiones
(MIS)
Uper Rio Paranapanema
(URP)
Lower Rio Iguaçú
(LRI)
2
0
Rio Tebicuary Basin
(TEB)
-2
Rio Tramandaí
Basin (TRB)
NRS TRB URI CPI BCG
TAB IAB URP RGR SMG
W Santa Catarina
(WSC)
Cotia-Piedade
(CPI)
(BCG)
Riacho Grande
(RGR)
95% CI DF1
Cotia-Piedade
(CPI)
S Minas Gerais
(SMG)
2
0
-2
TEB WSC URP RGR SMG
MIS LRI CPI BCG
Figure 7. Graphs, including error bars [mean ± 95% confidence interval (CI)], of the scores of the first discriminant function (DF1) for 14 of the 15 pooled samples studied here. The figure on the left represents the north−south transect, and
the figure on the right represents the east−west transect.
certain similarity, with mean scores between 0 and −1.
The lowest average, approximately −2.5, is from the
west Santa Catarina sample. However, moving west
from west Santa Catarina, mean scores are higher again
(c. 2) in the sample from Río Tebicuary Basin, with an
average higher than the eastern samples.
A Mantel test performed for the pairwise comparison between the geographical and Mahalanobis distance matrices resulted in a marginally significant
P-value (r = 0.206, P = 0.053). This result suggests that
there is a correlation, although nonsignificant, between
size variation and geographical distances.
For craniometrical traits, some noticeable discontinuities occur between southern (Rio Tramandaí Basin,
Rio Taquari-Antas Basin, and north-west Rio Grande
do Sul) and western samples (west Santa Catarina,
Misiones and Río Tebicuary Basin). Additionally, there
is strong clinal variation, with a decrease in the overall
size of the skull amongst samples in the north−south
and east−west directions. In the westernmost samples
(west Santa Catarina, Misiones and Río Tebicuary
Basin), an opposite clinal trend is observed, with an
increase in the overall size of the skull from east to
west. Multivariate analyses provided similar results
to those obtained in the univariate analysis, pointing
to a reduction in the skull size southwards, with a major
and consistent discontinuity between most samples and
the sample from Paraguay.
Minas Gerais and Rio de Janeiro states
Espírito Santo state
São Paulo state
W Santa Catarina state
Rio Grande do Sul state
Paraguay
Santa Catarina state
Argentina
857
Figure 8. Unrooted network of 34 haplotypes of 675 bp of the mtDNA cytochrome b gene obtained from 53 individuals
of Sooretamys. Dots between adjacent haplotypes represent missing haplotypes. The symbol fill type indicates the geographical region in which the haplotypes were sampled; the symbol size indicates the frequency of this haplotype at the
collection location.
PHYLOGEOGRAPHICAL
VARIATION
The 53 sequences of Sooretamys have 59 variable sites
that define 34 haplotypes (Fig. 8). Eleven haplotypes
were retrieved from more than one specimen; from these,
six haplotypes were collected at more than one locality. Observed p-distances amongst all pairwise sequence comparisons range from 0 to 3.0% (average:
1.6%). For the 12 localities with more than one specimen sequenced, the observed variation average is 0.5%
(range: 0 to 1.2%); whereas the observed divergence
between locality pairs averages 1.4% (range: 0 to 2.8%).
Genetic distances within localities (p-distance) and
between locality pairs (p-distance and K2p) are presented as supporting information (Table S1). Results
of the AMOVAs are presented in Table 5. Of the four
locality grouping schemes used, the one that maximizes the differences amongst groups (44.8%) and minimizes the differences amongst populations within groups
(31.4%) is a scheme with two locality groups: east (Paraguay) and west (Argentina and Brazil) of the Parana
River.
The recovered genealogies, obtained by maximum parsimony and Bayesian inference (Fig. 9), revealed that
all Sooretamys sequences showed several polytomies,
with most clades lacking significant support in both
analyses. The genus is strongly supported (BS = 100;
PP = 1) and shows at its base a polytomy involving four
lineages in the Bayesian analysis and 28 (21 formed
by a single sequence each) in the parsimony analysis. Of these lineages, the only one that is strongly supported (BS = 91; PP = 0.95) is exclusively constituted
by haplotypes recovered from the Paraguayan specimens. However, not all Paraguayan variants are part
of this clade; two others are located in a marginally
supported clade (PP = 0.65; not found in the MP analysis), with one variant found at nearby Misiones Argentina, and from two geographically distant localities
in the Brazilian states of Espírito Santo and Minas
Gerais. As such, this is a widely distributed phylogroup.
The other two main lineages have low support and are
distributed in the central portion of the geographical
distribution; both overlap at several localities.
The haplotype network (Fig. 8) has only two loops
and shows several missing haplotypes. As expected given
the MP and BA trees, no clear geographical groups
(clans sensu Wilkinson et al., 2007) can be delimited
in the network. However, it is of interest to note that
haplotypes from the easternmost (i.e. Argentina, Paraguay, west Santa Catarina in Brazil) and northernmost localities (i.e. northern Brazil) occupy external
positions in the network; however, the centre of the
network is formed by variants collected in the centre
and south-eastern parts of the distributional range of
Sooretamys (e.g. coastal Santa Catarina, Rio Grande
do Sul, São Paulo).
DISCUSSION
GEOGRAPHICAL
DIFFERENTIATION: MORPHOLOGICAL
AND MOLECULAR EVIDENCE
Nearly a century ago, Thomas (1924) detected differences in this genus throughout its geographical distribution and used the names Oryzomys ratticeps
ratticeps, O. r. paraganus (= S. angouya), and
O. r. tropicius to account for this variation. According
to Thomas, the typical subspecies O. r. ratticeps
0.30*
0.72*
0.60*
27.5
0.45*
0.76*
0.57*
23.8
0.38*
27.1
0.56*
0.73*
0.37*
0.72*
0.56*
41.7
30.8
31.4
44.8
2
2
Paraná River
Geographical
groups 2
*P-values < 0.0001.
3
Geographical
groups 1
3
Thomas’ (1924)
classification
scheme
G1: Paraguay
G2: Argentina, Rio Grande do Sul,
Santa Catarina
G3: rest f the distribution
G1: Paraguay
G2: Argentina, west Santa Catarina
G3: rest of the distribution
G1: Paraguay
G2: Argentina, Brazil
G1: Paraguay, Argentina,
west Santa Catarina
G2: rest of the distribution
37.8
35.1
35.0
37.4
G1: 187, 191–194
G2: 30, 74, 76, 81, 89, 90, 92, 93, 97–99,
117, 120, 121, 124, 126, 127–129
G3: all the others
G1: 187, 191–194
G2: 30, 126, 127
G·3: all the others
G1: 187, 191–194
G2: all the others
G1: 30, 126, 127, 187, 191–194
G2: all the others
27.6
FST
FSC
WP
APWG
AG
Percentage of variation
Localities in each group
Group: description
Number
of groups
F-statistics
FCT
Grouping
criteria
Table 5. AMOVA results for four arrangements of locality samples (see Fig. 3 and Appendices 1 and 2). Percentage of variation amongst groups (AG), amongst
populations within groups (APWG), within populations (WP) F-statistics sensu Wright (1950)
858
inhabits Rio Grande do Sul and Santa Catarina (Brazil)
and Misiones (Argentina) and is characterized by a small
size and a general greyish-brown colour. Oryzomys
r. paraganus is restricted to Paraguay and is defined
by a large size and a general buffy-brown colour that
is richer and brighter, with lighter buffy sides and a
buffy-whitish under surface. Oryzomys r. tropicius is
found in the Brazilian states of Paraná and São Paulo
and is recognized by a size similar to that of
O. r. ratticeps and general buffy-brown colour with dark
buffy sides and a buffy under-surface (Thomas, 1924).
More recently, Musser et al. (1998), overlooking this
variation, synonymized these taxa, plus Mus leucogaster
Brandt, 1835 and Calomys rex Winge, 1887, under the
senior available name Mus angouya Fischer, 1814.
Our qualitative results point to a direction different from that of Thomas (1924) that is similar, but
not identical, to that of Musser et al. (1998). Individuals with a greyish-brown upper surface were more
frequently found in the northern part of the distribution (São Paulo), a region corresponding to O. r. tropicius;
however, Thomas (1924) suggested that specimens from
the southern part of the range (O. r. ratticeps) are greyish
brown. Specimens from Paraguay, corresponding to
O. r. paraganus, have two exclusive characteristics according to Thomas (1924): nongrizzled under-parts, a
trait that we observed in only 28.6% of specimens, and
a bright dorsum, which was not more frequent than
in specimens from other localities in our work (see
above).
We are confident in the adequacy of the methodological approach used in this study (see also Moreira
& Oliveira, 2011) for evaluating intra- and interpopulation variation and, therefore, species boundaries. Our
results suggest the existence of only one living species
of Sooretamys. The geographical variation approach
allowed us to recognize subtle and gradual differences amongst populations that would be not evident
when a taxonomic study is based on taxa delimited a
priori, based on previous knowledge published on the
group (e.g. Percequillo et al., 2008).
Aiming to enhance the importance of a geographical approach, we tested the subspecific taxa proposed
by Thomas (1924) to contrast with our results. Thomas
(1924), after recognizing the subspecies, established geographical boundaries for them, mentioning the state,
province, or country as the geographical limit: all taxa
are parapatric and replace one another from north to
south and the south-west. Therefore, the specimens included in this analysis are assembled from the political unities mentioned in the original description of the
subspecies: specimens from Rio Grande do Sul and
Santa Catarina States in Brazil and Misiones Province in Argentina correspond to O. r. ratticeps; specimens from the Brazilian states of São Paulo and Paraná
correspond to O. r. tropicius; and specimens from
64
60
82
91
61
61
58
56
61
99
100
64
outgroup
A
GD257 PY 194
GD265 PY 194
UMMZ175081 PY 194
UMMZ175077 PY 194
GD52 PY 194
UMMZ175099 PY 193
GD543 PY 193
GD274 PY 187
UMMZ174979 PY 193
UMMA174984 PY 192
TK61763 PY 191
FURB9230 SC 127
FURB9238 SC 127
6595 SP 147
FURB5900 SC 128
FURB9836 SC 117
MHNCI4781 SP 145
FURB9790 SC 117
FURB477 SC 129
FURB9252 WSC 127
FURB9749 SC 121
MCNU1229 RS 92
MN37786 RS 90
MN37789 RS 90
UFPB338 ES 41
UFPB335 ES 41
CRB1271 RJ 69
MN50234 RJ 69
MCNU1625 RS 74
MN37778 RS 98
AFV21 RS 76
AFV22 RS 76
EM1207 SP 152
FURB12041 SC 124
FURB12151 SC 120
FURB5070 WSC 126
FURB9696 SC 117
FURB9867 SC 117
GD273 PY 187
UMMZ15083 PY 187
CNP1998 AR 30
CNP2524 AR 30
MCNU1230 RS 92
MCNU1291 RS 81
MCNU1292 RS 81
MCNU622 RS 89
MN37777 SC 113
MN37780 RS 98
MN37783 RS 98
MN37785 RS 97
MN37790 RS 99
MN37794 RS 93
MP301 MG 44
1
outgroup
B
859
EM1207 SP 152
FURB9867 SC 117
MCNU1230 RS 92
0.75
MCNU1291 RS 81
MCNU1292 RS 82
MN37790 RS 99
MN37794 RS 93
MCNU1229 RS 92
0.89
MN37786 RS 90
MN37789 RS 90
1
CRB1271 RJ 69
MN50234 RJ 69
0.83
MCNU1625 RS 74
0.64
MN37778 RS 98
FURB12041 SC 124
FURB5070 SC 126
0.68
MN37777 SC 113
MN37780 RS 98
MN37785 RS 97
MN37783 RS 98
0.96
FURB9230 SC 127
FURB9238 SC 127
0.93
6595 SP 147
FURB5900 SC 128
FURB9836 SC 117
0.92
MHNCI4781 SP 145
0.8
FURB9790 SC 117
FURB477 SC 129
FURB9252 SC 127
FURB9749 SC 121
0.72
AFV21 RS 76
0.82
FURB12151 SC 120
FURB9696 SC 117
0.64
AFV22 RS 76
CNP2524 AR 30
MCNU622 RS 89
GD257 PY 194
GD265 PY 194
0.95
UMMZ 175081 PY 194
UMMZ175077 PY 194
GD52 PY 194
0.97
UMMZ175099 PY 193
0.95
GD543 PY 193
GD274 PY 187
0.95
UMMZ174979 PY 193
UMMZ174984 PY 192
TK61763 PY 191
0.83
GD273 PY 187
0.58
UMMZ175083 PY 187
CNP1998 AR 30
0.65
1
UFPB338 ES 41
UFPB335 ES 41
MP301 MG 44
0.3
Figure 9. Gene genealogies for 675 bp of the mtDNA cytochrome b gene obtained from 53 individuals of Sooretamys
recovered through maximum parsimony (A) and Bayesian (B) methods. The terminal branches are individuals, each represented by the institution number, followed by the Brazilian state or country acronym (AR, Argentina; PY, Paraguay;
ES, Espírito Santo; RJ, Rio de Janeiro; MG, Minas Gerais, SP, São Paulo; SC, Santa Catarina; and RS, Rio Grande do
Sul) and the locality number, according to Appendix 2 and Figure 3. In A, the numbers represent the support for each
branch; bootstrap values under 50 are not shown. In B, the numbers represent the posterior probability support for each
branch; support values under 0.50 are not shown. Outgroups used for both analyses were Cerradomys subflavus, Nectomys
squamipes, and Aegialomys xanthaeolus.
860
Paraguay correspond to O. r. angouya/paraganus. We
performed univariate comparisons and discriminant
analysis amongst these three ‘samples’; we found that
specimens assigned the name O. r. ratticeps exhibit the
smallest mean values, whereas the species identified
as O. r. paraganus have the largest means, and the
specimens from São Paulo and Paraná, named
O. r. tropicius, are characterized by intermediate mean
values. Wilks’ lambda indicates that the projection of
individual scores along the first and second discriminant functions revealed little overlap between specimens assigned to O. r. ratticeps and O. r. paraganus
(Table 6). However, individuals identified as O. r. tropicius
are completely overlapped to those of O. r. ratticeps and
only marginally superimposed to those of O. r. paraganus
(Fig. 10). An error bar exhibiting the mean values of
the scores of the first discriminant function (Fig. 11)
showed three quite distinct groups, as suggested by
many of the craniodental variables individually in the
univariate analysis. These results partially corroborate those obtained by Thomas (1924): specimens from
Paraguay, called O. r. angouya/paraganus, are consistently and significantly larger than the other two taxa;
however, between O. r. ratticeps and O. r. tropicius, size
variation is subtler, as it does not exist for some variables. These results are supported by analyses of molecular variance: the differences amongst the population
groups are higher (44.8%) when localities are grouped
into two groups, Paraguay vs. the rest (i.e. O. r. angouya/
paraganus vs. O. r. ratticeps and O. r. tropicius) than
when localities are grouped into three groups corresponding to the subspecific arrangement of Thomas
(37.4%). These results suggest that an a priori recognition of putative different biological units (either species
or subspecies) could be potentially misleading and that
careful and detailed analysis of variation, both genetic
and morphological, and employing geographical samples
is essential for appropriate species recognition.
Wright (1943) and Gould & Johnston (1972) postulated that geographically distant samples would accumulate more differences (through selection or genetic
drift) than closely located samples. Furthermore, if a
taxon represents a morphologically continuous unit with
gradual differences accumulated throughout its geographical distribution, it is expected that a positive relationship will exist between morphological and
geographical distances (Moreira & Oliveira, 2011). In
the case of Sooretamys, the low but still nonsignificant
P-value in the Mantel test (P = 0.053) rejects the hypothesis of the isolation-by-distance model and indicates that Sooretamys represents a continuous unit.
This trend is apparently broken by the similarity in
size between the two most distant samples from BoraceiaCasa Grande and Río Tebicuary Basin, approximately
800 km apart, and by the high discrepancy between
two very close samples, west Santa Catarina and Río
Table 6. Standardized discriminant function coefficients of
the log-transformed data of 15 craniodental variables, using
as grouping variables the three subspecies proposed by Thomas
(1924): Oryzomys ratticeps tropicius, Oryzomys ratticeps
ratticeps, and Oryzomys ratticeps angouya/paraganus
Standardized
canonical
discriminant
function
coefficients
Tests of
equality
of group
means
Variable
First
Second
Wilk’s
lambda
ONL
CIL
LD
CLM1−3
BM1
LIF
BIF
BR
LN
LPB
HBC
ZB
BZP
CZL
LOF
Canonical correlation
Function Wilk’s lambda
Eigenvalue
% Variance
−0.11
−2.69
0.95
0.17
−0.16
0.39
−0.07
0.60
0.38
−0.04
0.34
0.06
0.68
0.67
0.03
0.73
0.40**
1.16
88
−1.74
1.88
0.81
−0.13
0.54
−0.64
−0.24
0.15
0.73
−0.03
0.51
−0.55
−0.46
0.26
−0.78
0.371
0.86ns
0.16
12
0.89**
0.91**
0.75**
0.99ns
0.99ns
0.80**
0.91**
0.81**
0.86**
0.98ns
0.78**
0.87**
0.75**
0.92*
0.90**
*Wilk’s lambda significant at P < 0.05; **Wilk’s lambda significant at P ≤ 0.001; nsWilk’s lambda not significant.
BIF, breadth of incisive foramen (greatest dimension measured across the internal surface of both incisive foramen);
BM1, breadth of molar 1 (greatest crown breadth of the
first maxillary molar across the paracone−protocone); BR,
breadth of rostrum (greatest dimension measured across
the external border of the nasolacrimal capsules); BZP,
breadth of zygomatic plate (across central area of zygomatic
plate); CIL, condylo-incisive length (measured from the
greater curvature of one upper incisor to the articular surface
of the occipital condyle on the same side); CLM1−3, length
of molars (crown length from molar 1 to molar 3); CZL,
condylozygomatic length; HBC, height of braincase; LD,
length of diastema (from the crown of the first upper molar
to the lesser curvature of the upper incisor on the same
side); LIF, length of incisive foramen (greatest
anterior−posterior dimension of one incisive foramen); LN,
length of nasals (greatest anterior−posterior dimension of
one nasal bone); LOF, length of orbital fossa (greatest length
of the orbital fossa between the squamosal and maxillary
roots of the zygomatic arch); LPB, length of palatal bridge
(measured from the posterior border of the incisive foramen
to the anterior border of the mesopterygoid fossa); ONL,
occipitonasal length; ZB, zygomatic breadth (greatest dimension across the squamosal root of zygomatic arches).
4
3
tropicius
2
DF2
1
0
-1
ratticeps
-2
-3
-4
paraganus
-3
-2
-1
0
1
2
3
4
DF1
Figure 10. Scatterplots of the individual scores from the
first two discriminant functions (DF1 and DF2), obtained
through discriminant analysis, conducted with logtransformed data of 15 craniodental variables, using as grouping variables the three subspecies proposed by Thomas (1924):
Oryzomys ratticeps tropicius (squares), Oryzomys ratticeps
ratticeps (triangles), and Oryzomys ratticeps angouya/
paraganus (circles). These two functions (DF1 and DF2) are
responsible for 88 and 12% of the variation, respectively.
The ellipses cover 67.5% of the distribution of points.
Figure 11. Graph, including error bars [mean ± 95% confidence interval (CI)], of the scores from the first discriminant function (DF1) conducted amongst the three subspecies
proposed by Thomas (1924), plotted against the alleged geographical distribution of these three taxa.
Tebicuary Basin, approximately 400 km apart, as indicated by the nonsignificant P-value of the Mantel test.
Qualitatively, there is no consistent discontinuity throughout the geographical range for any of the traits evaluated. The morphological variation that is observed is
861
not concordant with geographical distribution, as aspects
of coat colour and cranial morphology are highly variable within samples and also within the subspecies postulated by Thomas (1924).
Genetically, Paraguayan populations differentiate from
samples from other locations. No haplotype is shared
between Paraguayan and non-Paraguayan localities.
In addition, four of five haplotypes (recovered from 11
of 13 sequenced specimens) from Paraguay form a highly
supported clade that constitutes one of the four main
lineages of S. angouya recovered in the Bayesian analysis. Meanwhile, the remaining Paraguayan haplotype
(found in two of 13 specimens) forms a clade together with haplotypes found in nearby Misiones, Argentina (locality 30), and the Brazilian states of Espirito
Santo (41) and Minas Gerais (44). If haplotypes from
Paraguay were recovered as a monophyletic group, even
without reciprocal monophyly, one scenario would be
to recognize Paraguayan populations as a subspecies
of the more inclusive clade, as a geographically and
temporarily isolated lineage or sublineage (Frost et al.,
1992). However, Paraguayan haplotypes do not form
a monophyletic group: two haplotypes from Centu Cue,
Paraguay (locality 187 on map) are closely related to
haplotypes from Itamonte (locality 44), Venda Nova (locality 41), and Refúgio Moconá (locality 30), rather than
to other Paraguayan haplotypes. The biological reason
behind this pattern is currently unclear: it may be indicative of current gene flow throughout the geographical range of Sooretamys or it just may be the reflect
of incomplete lineage sorting. The study of additional
specimens and the sequencing of nuclear markers may
clarify this issue.
The molecular results are similar to the morphological and morphometric results: our integrative approach suggests a certain degree of variation in the
genes and morphology of the Paraguayan population,
but there is no consistent resolution to suggest that
the specimens from Paraguay represent a distinct lineage
that would merit taxonomic recognition. As such, we
recognize only one ‘unique diagnosable unit and
monophyletic cluster of individuals’ as proposed by
Cracraft (1983). Consequently, we conclude that
Sooretamys is a monotypic genus (for taxonomic account,
see Appendix 3).
Considering that the genus Sooretamys exhibits only
one evolutionary lineage at the species level, an important point is to designate the appropriate name for
this species. Direct morphological and morphometric
(principal components analysis, results not shown) comparisons of the nominal specimens of Mus angouya
Fisher, 1814 (2.7 km north of San Antonio by road, Paraguay, neotype); Hesperomys ratticeps Hensel, 1872 (Rio
Grande do Sul, lectotype); O. r. tropicius Thomas, 1924
(Piquete, São Paulo, lectotype); and O. r. paraganus
Thomas, 1924 (Sapucay, Paraguay, holotype) re-
862
vealed that these name-bearing types overlap with the
cloud of points of this genus. The M. angouya and
O. r. paraganus types are scattered amongst the specimens from Paraguay, and the O. r. tropicius and
H. ratticeps types overlap with specimens from the
eastern area of the geographical distribution of the
genus. Therefore, all names could be confidently applied
to this species. As M. angouya is the oldest of these
available names, it should therefore be used to refer
to this species.
The pattern of the morphological (clines and sharp
discontinuities) and genetic (absence of phylogeographical
structure) differences within Sooretamys could be the
result of divergence with gene flow (Endler, 1982;
Schneider et al., 1999; Moritz et al., 2000) experienced across an ecological gradient from east to west
during past glacial events, in which the humidity and
forest cover were reduced from the coastal region
towards the interior (Clapperton, 1993; Carnaval &
Moritz, 2008). Presently, there is also a moisture gradient from coastal evergreen forests to interior
semideciduous forests (Hueck, 1973; Thomé et al., 2010)
that could represent a selective gradient for Sooretamys.
However, our data also correspond in some aspects with
the model advanced by Carnaval & Moritz (2008; see
also Carnaval et al., 2009), which claims the existence of stable Atlantic Forest areas where the forest
biota persisted during the Quaternary climatic fluctuations [i.e. the Carnaval-Moritz (CM) model sensu
Martins, 2011]. Genetic variants of S. angouya from
populations along the Brazilian coast, which were areas
of stability according to the model, form a paraphyletic
group with respect to variants recovered in western
populations (i.e. Argentina, Paraguay, and west Santa
Catarina, Brazil), which were reconstructed as unstable areas. Similarly, western variants occupy the periphery of the haplotype network, whereas haplotypes
from coastal Brazil are across the network, including
its centre. In other words, western haplotypes of
S. angouya seem to be younger than those from the
coast. In this regard, it is of interest to note that the
phylogeographical pattern of S. angouya differs from
that of other Atlantic forest mammals (e.g. Akodon
cursor Colombi et al., 2010; Blarinomys breviceps Ventura
et al., 2012; Akodon montensis Valdez & D’Elía 2013;
see reviews in Martins, 2011; Costa & Leite, 2012),
which show distinct degrees and patterns of structure across the Atlantic Forest, but resembles those
of others (i.e. Akodon paranaensis D’Elía et al., 2008;
Marmosa paraguayana de la Sancha et al., 2012) that
lack structure. The latter, in the context of the CM
model, could be interpreted as persistence of the current
genetic diversity of S. angouya at a single refugium
when the Atlantic forest fragmented; that is, S. angouya
would have reached its current distribution from the
expansion of a single refugium. Future demographic
studies could test this scenario, and if it proves to
be the case, would determine whether S. angouya expanded, considering its current distribution, from the
São Paulo refugium (Carnaval et al., 2009) or from the
Rio Grande do Sul refugium (Valdez & D’Elía, 2013).
Generally, as studies on the Atlantic Forest mammalian assemblage accumulate, the notion that the recent
history of the group is complex is being consolidated
and emphasizes the need for additional studies before
a robust synthesis can be reached.
Reassessing Musser et al.’s (1998) concluding remarks
on their account of the genus Sooretamys, in which
they stated that a new assessment of geographical variation, including modern samples, is needed to understand the taxonomic composition of the genus, we believe
that S. angouya represents one species with a complex
evolutionary history. The analysis of additional samples
would be welcome to provide even more light on the
process of diversification of this taxon.
ACKNOWLEDGEMENTS
We sincerely thank all of the curators that granted us
access to the collection under their care, and to the
researchers that donated tissue samples – their generous help was essential to the development of this
study. We would like to acknowledge Robert Owen and
Lucy Aquino for valuable logistic support and Cesar
Manchini and Ismael Mora for field assistance during
fieldwork in Paraguay. We also are indebted to Ulyses
Pardiñas and Marcelo Weksler, who carefully read an
earlier version of the manuscript and greatly contributed to its improvement; to Erika Hingst-Zaher and
Felipe Grazziotin, who provided important insights on
statistical and molecular approaches. We are also grateful to the personnel and coordinators of Laboratório
de Biologia Celular e Molecular (CENA/USP) and to
the Laboratório de Biologia Evolutiva e Conservação
de Vertebrados (IB/USP) for allowing us access to their
premises and equipment. We also would like to thank
the three anonymous reviewers for suggestions that
greatly improved our manuscript; problems that may
have persisted are, of course, our own. A. R. P. and
E. A. C.’s research was sponsored by American Museum
of Natural History, The Field Museum, Smithsonian
Institution, and Museum of Comparative Zoology grants
and Conselho Nacional de Pesquisa e Desenvolvimento
(CNPq Process 476249/2008-2) and Fundação de Amparo
à Pesquisa do Estado de São Paulo fellowships and
grants (FAPESP Process 2007/05859-9, FAPESP Biota
Program Process 98/05075-7, FAPESP Young Investigators in Emerging Institutions Process 2009/160091). FONDECYT 1110737, MECESUP AUS1203, and
University of Michigan Museum of Zoology grants
financially supported G. D.’s research.
REFERENCES
Abreu-Junior EF, Brennand PGG, Chiquito EA, JorgeRodrigues CR, Libardi G, Prado JR, Percequillo AR.
2012. Dimorfismo sexual na tribo Oryzomyini. In: Freitas
TRO, Vieira EM, eds. Mamíferos do Brasil: Genética,
Sistemática, Ecologia e Conservação. Rio de Janeiro: Sociedade
Brasileira de Mastozoologia, 115–134.
Alho CJR. 1982. Brazilian rodents: their habitat and habits.
In: Mares MA, Genoways HH, eds. Mammalian biology in
South America. Pymatuning Laboratory of Ecology, Special
Publication Series, vol. 6. Pittsburgh, PA: University of Pittsburgh, 143–166.
Allen JA. 1916. Mammals collected on the Roosevelt
Brazilian expedition, with field notes by Leo E. Miller.
Bulletin of the American Museum of Natural History 35: 559–
610.
Andrades-Miranda J, Zanchin NIT, Oliveira LFB,
Langguth A, Mattevi MS. 2000. Cytogenetic studies in nine
taxa of the genus Oryzomys (Rodentia, Sigmodontinae) from
Brazil. Mammalia 65: 461–472.
Ávila-Pires FD. 1960a. Roedores colecionados na região de
Lagoa Santa, Minas Gerais, Brasil. Arquivos do Museu
Nacional 50: 25–45.
Ávila-Pires FD. 1960b. Sobre Oryzomys do grupo ratticeps.
In: Congreso Sudamericano de Zoologia, 1°. Actas y Trabajos,
Tomo IV, Sectión V. La Plata: Comision de Investigacion
Cientifica de la Provincia de Buenos Aires y Consejo Nacional
de Investigaciones Cientificas y Tecnicas, 3–7.
Azara F. 1801. Essais sur L’ Histoire Naturelle des Quadrupedes
de la Province du Paraguay. Tome second. Traduits sur le
manuscrit inédit de l’Auteur, pra M. L. E. Moreau-SaintMéry. Paris: C. Pougens.
Azara F. 1802. Apuntamientos para la Historia Natural de
los Quadrúpedos del Paraguay y Rio de La Plata. Madri: Em
la imprenta de la viuda de Ibarra.
Bonvicino CR, Moreira MA. 2001. Molecular phylogeny of
the genus Oryzomys (Rodentia: Sigmodontinae) based on
cytochrome b DNA sequences. Molecular Phylogenetics and
Evolution 18: 282–292.
Brandt JF. 1835. Mammalium Rodentium Exoticorum Novorum
Vel Minus Rite Cognitorum, Musei Academici Zoologici
Descriptiones et Icones. Sectio II. Sciuri langsdorfii, Muris
leucogastri, Muris anguyae, Hypudaei guiara et Criceti fuscati
ilustraciones. Mémoires L’ Académie Imperiale des Sciences
de Saint Pétesbourg, Ser. 6 3: 425–436 + 4 plates.
Carleton MD. 1973. A survey of gross stomach morphology
in new world Cricetinae (Rodentia, Muroidea), with comments on functional interpretations. Miscellaneous Publications, Museum of Zoology, University of Michigan 146:
1–43.
Carleton MD. 1980. Phylogenetic relationships in neotomineperomyscine rodents (Muroidea) and a reappraisal of the
dichotomy within New World Cricetinae. Miscellaneous Publications, Museum of Zoology, University of Michigan 157:
1–146.
Carleton MD, Musser GG. 1989. Systematic studies of
oryzomyine rodents (Muridae, Sigmodontinae): a synopsis of
863
Microryzomys. Bulletin of the American Museum of Natural
History 191: 1–83.
Carnaval AC, Moritz C. 2008. Historical climate modelling
predicts patterns of current biodiversity in the Brazilian
Atlantic forest. Journal of Biogeography 35: 1187–1201.
Carnaval AC, Hickerson MJ, Haddad CFB, Rodrigues MT,
Moritz C. 2009. Stability predicts genetic diversity in the
Brazilian Atlantic Forest hotspot. Science 323: 785–789.
Clapperton C. 1993. Quaternary geology and geomorphology
of South America. Amsterdam: Elsevier.
Clement M, Posada D, Crandall KA. 2000. TCS: a computer program to estimate gene genealogies. Molecular Ecology
9: 1657–1660.
Colombi VH, Lopes SR, Fagundes V. 2010. Testing the Rio
Doce as a riverine barrier in shaping the Atlantic rainforest population divergence in the rodent Akodon cursor.
Genetics and Molecular Biology 33: 785–789.
Costa LP, Leite YLR. 2012. Historical fragmentation shaping
vertebrate diversification in the Atlantic Forest biodiversity hotspot. In Patterson B, Costa LP, eds. Bones, Clones
and Biomes: The history and geography of recent Neotropical
mammals. Chicago: The University of Chicago Press, 283–
306.
Costa LP, Leite YLR, Patton JL. 2003. Phylogeography and
systematic notes on two species of gracile mouse opossums,
genus Gracilinanus (Marsupialia: Didelphidae) from Brazil.
Proceedings of the Biological Society of Washington 116: 275–
292.
Cracraft J. 1983. Species concepts and speciation analysis.
Current Ornithology 1: 159–187.
Cumming G, Fidler F, Vaux DL. 2007. Error bars in experimental biology. Journal of Cell Biology 177: 7–11.
D’Elía G. 2003. Phylogenetics of Sigmodontinae (Rodentia,
Muroidea, Cricetidae), with special reference to the akodont
group, and with additional comments on historical biogeography. Cladistics 19: 307–323.
D’Elía G, Mora I, Myers P, Owen RD. 2008. New and noteworthy records of Rodentia (Erethizontidae, Sciuridae, and
Cricetidae) from Paraguay. Zootaxa 1784: 39–57.
D’Elía G, Pardiñas UFJ. 2004. Systematics of Argentinean,
Paraguayan, and Uruguayan swamp rats of the genus
Scapteromys (Rodentia, Cricetidae, Sigmodontinae). Journal
of Mammalogy 85: 897–910.
Dayrat B. 2005. Towards integrative taxonomy. Biological
Journal of the Linnean Society 87: 407–415.
Desmarest AG. 1804. Tableau Méthodique des Mammifères.
In: Nouveau Dictionnaire d’Histoire Naturelle, Appliquée aux
Arts, Principalement à l’Agriculture, à l’Économie Rurale et
Domestique. Vol. XXIV. Paris: Deterville, 5–38.
Desmarest AG. 1819. Rat, rat Angouya, Rat a Grosse
Tete (entries). In: Nouveau Dictionnaire d’Histoire
Naturelle, appliquèe aux art, principalement à l’agriculture
et à l’economie rurale et domestique. Vol. XXIX. Paris:
Deterville, 40–71.
Desmarest AG. 1820. Mammalogie ou Description des Espèces
de mammmifères, Premiere Partie, contenant les Ordres des
Bimanes, des Quadrumanes et des Carnassiers. Paris: Veuve
Agasse, Imprimeur-Libraire.
864
Emmons LH, Vucetich MG. 1996. The identity of Winge’s
Lasiuromys villous and the description of a new genus of
echmyid genus. American Museum Novitates 3223: 1–12.
Endler JA. 1982. Problems in distinguishing historical from
ecological factors in biogeography. American Zoologist 22: 441–
452.
Excoffier L, Laval G, Schneider S. 2005. Arlequin ver. 3.0:
an integrated software package for population genetics
data analysis. Evolutionary Bioinformatics Online 1: 47–
50.
Excoffier L, Smouse PE, Quattro JM. 1992. Analysis of molecular variance inferred from metric distances among DNA
haplotypes – Application to human mitochondrial-DNA restriction data. Genetics 131: 479–491.
Farris JS. 1982. The logical basis of phylogenetic analysis.
In: Platnick N, Funk V, eds. Advances in cladistics: Proceedings of the Second Meeting of the Willi Hennig Society.
New York: Columbia University Press, 7–36.
Fischer G. 1814. Zoognosia Tabulis Synopticis illustrata. Vol.
II. Moscow: N.S. Vsevolozky.
Fonseca GAB. 1985. The vanishing Brazilian Atlantic Forest.
Biological Conservation 33: 1–18.
Fonseca GAB, Redford KH. 1984. The mammals of IBGE’S
ecological reserve, Brasília, and analysis of the role of gallery
forest in increasing diversity. Revista Brasileira de Biologia
44: 517–523.
Frost DR, Kluge AG, Hillis DM. 1992. Species in contemporary herpetology: comments on phylogenetic inference and
taxonomy. Herpetological Review 23: 46–54.
Gould SJ, Johnston RF. 1972. Geographic variation. Annual
Review of Ecology and Systematics 3: 457–498.
Hanson JD. 2008. Molecular phylogenetics of Oryzomyini: does
a multi-gene approach help resolve a systematic conundrum? DPhil Thesis, Texas Tech University.
Hanson JD, Bradley RD. 2008. Molecular diversity within
Melanomys caliginosus (Rodentia: Oryzomyini): evidence for
Multiple Species. Occasional Papers The Museum Texas Tech
University 275: 1–11.
Hensel R. 1872. Beiträge zur Kenntniss der Säugethiere SüdBrasiliens. Abhandl König Akad Wiss Berlin 1872: 1–130.
Hershkovitz P. 1955. South American marsh rats, genus
Holochilus, with a summary of Sigmodontinae rodents.
Fieldiana Zoology 37: 639–673.
Hooper ET, Musser GG. 1964. The glans penis in Neotropical
cricetines (Family Muridae), with comments on classification of muroid rodents. Miscellaneous Publications of the
Museum of Zoology, University of Michigan 123: 1–57.
Hueck K. 1973. As florestas da América do Sul. São Paulo:
Editora Polígono, Editora da Universidade de Brasília.
von Ihering H. 1893. Os mammiferos do Rio Grande do Sul.
Annuário do Estado do Rio Grande do Sul 1893: 96–123.
Illiger K. 1815. Uebelblick der Säugethiere nach ihrer
vertheilung über die welttheile. Abhandlungen Akademie
Wissenschaften zu Berlin 1804–1811: 39–159.
Jayat JP, Ortiz PE, Teta P, Pardiñas UFJ, D’Elía G. 2006.
Nuevas localidades argentinas para algunos roedores
sigmodontinos (Rodentia:Cricetidae). Mastozoología Neotropical
13: 51–67.
Langguth A. 1966. Application to place on the appropriate
official list the names given by G. Fischer 1814 to the cricetid
described by Felix de Azara in the french translation of ‘Essais
sur l’histoire naturelle des quadrupedes du Paraguay’ 1801.
Bulletin of Zoological Nomenclature 23: 285–288.
Manly BJF. 2008. Métodos estatísticos multivariados: uma
introdução, 3rd edn. Porto Alegre: Bookman.
Mantel N. 1967. The detection of disease clustering and a
generalized regression approach. Cancer Research 27: 209–
220.
Mares MA, Braun JK. 2000. Three new species of
Brucepattersonius (Rodentia: Sigmodontinae) from Misiones
Province, Argentina. Occasional Papers of the Sam Noble
Oklahoma Museum of Natural History 9: 1–13.
Martins FM. 2011. Historical biogeography of the Brazilian
Atlantic forest and the Carnaval-Moritz model of Pleistocene refugia: what do phylogeographical studies tell us? Biological Journal of Linnean Society 104: 499–509.
Massoia E. 1993. Los Roedores misioneros -1- Lista sistemática
comentada y geonemia provincial conocida. Boletín científico
Asociación para la Protección de la Naturaleza 25: 42–51.
Mayr E. 1963. Animal species and evolution. Cambridge: The
Belknnap Press at Harvard University Press.
Miranda GB, Andrades-Miranda J, Oliveira LFB, Langguth
A, Mattevi MS. 2007. Geographic patterns of genetic variation and conservation consequences in three South American rodents. Biochemical Genetics 45: 839–856.
Moreira JC, Oliveira JA. 2011. Evaluating diversification
hypotheses in the South American cricetid Thaptomys
nigrita (Lichtenstein, 1829) (Rodentia: Sigmodontinae): an
appraisal of geographical variation based on different character systems. Journal of Mammalian Evolution 18: 201–
214.
Moritz C, Patton JL, Schneider CJ, Smith TB. 2000.
Diversification of rainforest faunas: an integrated molecular approach. Annual Review of Ecology and Systematics 31:
533–563.
Musser GG. 1968. A systematic study of the Mexican and Guatemalan gray squirrel, Sciurus aureogaster F. Cuvier (Rodentia:
Sciuridae). Miscellaneous Publications, Museum of Zoology,
University of Michigan 137: 1–112.
Musser GG, Carleton MD. 2005. Superfamily Muroidea. In:
Wilson DE, Reeder DA, eds. Mammal species of the world.
A taxonomic and geographic reference, 3rd edn. Baltimore,
MD: The Johns Hopkins University Press, 894–1531.
Musser GG, Carleton MD, Brothers E, Gardner AL. 1998.
Systematic studies of Oryzomyine rodents (Muridae,
Sigmodontinae): diagnoses and distributions of species formerly assigned to Oryzomys ‘capito’. Bulletin of the American Museum of Natural History 236: 1–376.
Musser GG, Williams MM. 1985. Systematic studies of
Oryzomyine rodents (Muridae): definition of Oryzomys villosus
and Oryzomys talamancae. American Museum Novitates 2810:
1–22.
Myers N, Mittermeier RA, Mittermeier CG, da Fonseca
GAB, Kent J. 2000. Biodiversity hotspots for conservation
priorities. Nature 403: 853–858.
Myers P. 1982. Origins and affinities of the mammal fauna
of Paraguay. In: Mares MA, Genoways HH, eds. Mammalian biology in South America. Pymatuning Laboratory of
Ecology, Special Publication Series, vol. 6. Pittsburgh: University of Pittsburgh, 85–93.
Myers P, Lundrigan B, Tucker PK. 1995. Molecular
phylogenetics of oryzomyine rodents: the genus Oligoryzomys.
Molecular Phylogenetics and Evolution 4: 372–382.
National Geospatial-Intelligence Agency. 2014. Available
at: http://geonames.nga.mil/namesgaz/
Olfers I. 1818. Bemerkungen zu Illiger’s Ueberblik der
Säugethiere, nach ihrer bertheilung über die belttheile,
rucksichtlich der Südamericanischen arten. Abhandlung X.
In: von Eschwege WL, ed. Journal von Brasilien oder
vermischte Nachrichten aus Brasilien, auf Wissenschaftlichen
Reisen Gesammelt. Weimar, Im Verlag des Gr. H. S. pr. LandesIndustries-Comptoirs. Heft 2. (Bertuch, F. J. (ed.), Neue
Bibliotek der Wichtigsten Reisebeschreibungen zur Erweitwrung
der Erd- und Volkerkunde, Band 15: 192–237).
Olmos F. 1991. Observations on the behaviour and population dynamics of some Brazilian Atlantic Forest rodents.
Mammalia 55: 555–565.
Padial JM, Castroviejo-Fisher S, Köler J, Vilà C, Chaparro
JC, De La Riva I. 2009. Deciphering the products of
evolution at the species level: the need for an integrative
taxonomy. Zoologica Scripta 38: 331–447.
Pardiñas UFJ, D’Elía G, Cirignoli S. 2003. The genus Akodon
(Muroidea: Sigmodontinae) in Misiones, Argentina. Mammalian Biology 68: 129–143.
Pardiñas UFJ, D’Elía G, Cirignoli S, Suarez P. 2005. A
new species of Akodon (Rodentia, Cricetidae) from the Northern Campos grasslands of Argentina. Journal of Mammalogy
86: 462–474.
Pardiñas UFJ, Teta P. 2011. On the taxonomic status of the
Brazilian mouse Calomys anoblepas Winge, 1887 (Mammalia,
Rodentia, Cricetidae). Zootaxa 2788: 38–44.
Pardini R, Umetsu F. 2006. Pequenos mamíferos nãovoadores da Reserva Florestal do Morro Grande: distribuição
das espécies e da diversidade em uma área de Mata Atlântica.
Biota Neotropica 6: 1–22.
Patton JL, Hafner MS. 1983. Biosystematics of the native
rodents of the Galapagos Archipelago, Ecuador. In: Bowman
RI, Benson M, Leviton AE, eds. Patterns of evolution in
Galapagos organisms. San Francisco, CA: American Association for the Advancement of Science, Pacific Division, 539–
568.
Patton JL, da Silva MNF, Lara MC, Mustrangi MA. 1997.
Diversity, differentiation, and the historical biogeography of
nonvolants small mammals of the Neotropic forests. In: Laurence WF, Bierregaard RO Jr, eds. Tropical forest remnants:
ecology, management, and conservation of fragment communities. Chicago, IL: University of Chicago Press, 455–465.
Patton JL, da Silva MNF, Malcolm JR. 2000. Mammals
of the Rio Juruá and the evolutionary and ecological diversification of Amazonia. Bulletin of the American Museum of
Natural History 244: 1–306.
Paynter RA Jr. 1989. Ornithological gazetteer of Paraguay.
Cambridge: Bird Department, Museum of Comparative Zoology,
Harvard University.
865
Paynter RA Jr. 1995. Ornithological gazetteer of Argentina.
Cambridge: Bird Department, Museum of Comparative Zoology,
Harvard University.
Paynter RA Jr, Traylor MA. 1991. Ornithological gazetteer
of Brazil. Cambridge: Bird Department, Museum of Comparative Zoology, Harvard University.
Percequillo AR, Hingst-Zaher E, Bonvicino CR. 2008. Systematic review of genus Cerradomys Weksler, Percequillo &
Voss, 2006 (Rodentia: Cricetidae: Sigmodontinae: Orizomyini),
with description of two new species from Eastern Brazil. American Museum Novitates 3622: 1–46.
Percequillo AR, Weksler M, Costa LP. 2011. A new genus
and species of rodent from the Brazilian Atlantic Forest
(Rodentia: Cricetidae: Sigmodontinae: Oryzomyini), with comments on oryzomyine biogeography. Zoological Journal of
Linnean Society 161: 357–390.
Pinto O. 1945. Cinquenta anos de investigação ornitológica.
Arquivos de Zoologia 4: 261–340 + 1 map.
Prado JR, Percequillo AR. 2011. Ontogenetic and sexual variation in cranial characters of Aegialomys xanthaeolus (Thomas,
1894) (Cricetidae: Sigmodontinae) from Ecuador and Peru.
Papéis Avulsos de Zoologia 51: 155–177.
Prado JR, Percequillo AR. 2013. Geographic distribution of
the genera of the Oryzomyini tribe (Rodentia: Cricetidae) in
South America: patterns of distribution and diversity. Arquivos
de Zoologia São Paulo 44: 1–124.
R Development Core Team. 2005. R: a language and environment for statistical computing. Vienna: R Foundation for
Statistical Computing.
Reig OA. 1977. A proposed unified nomenclature for the enamelled components of the molar teeth of the Cricetidae
(Rodentia). Journal of Zoology 181: 227–241.
Rengger JR. 1830. Naturgeschichte der Saeügethiere von Paraguay. Basel, in der Schweighauserschen Buchhandlung.
Ribeiro MC, Metzger JP, Martensen AC, Ponzoni FJ,
Hirota MM. 2009. The Brazilian Atlantic forest: how much
is left, and how is the remaining forest distributed? Implications for conservation. Biological Conservation 142: 1141–
1153.
Ronquist F, Huelsenbeck JP. 2003. MRBAYES 3: Bayesian phylogenetic inference under mixed models. Bioinformatics
19: 1572–1574.
Sabrosky CW. 1967. Comment on the application to place
Fischer’s names for D’Azara’s rodents on the Official
List. Z. N. (S.) 1774. Bulletin of Zoological Nomenclature 24:
141.
de la Sancha NU, D′Elía G, Teta P. 2012. Systematics of
the subgenus of mouse opossum Marmosa (Micoureus)
(Didelphimorphia, Didelphidae) with noteworthy records from
Paraguay. Mammalian Biology 77: 229–236.
Schneider CJS, Smith TB, Larison B, Moritz C. 1999. A
test of alternative models of diversification in tropical rainforests: ecological gradients vs. refugia. Proceedings of the
National Academy of Sciences, USA 96: 13869–13873.
Silva CR, Percequillo AR, Iack-Ximenes GE, Vivo M.
2003. New distributional records of Blarinomys breviceps
(Winge, 1888) (Sigmodontinae, Rodentia). Mammalia 67: 147–
152.
866
Silva MJJ. 1994. Estudos cromossômicos e de complexos
sinaptonêmicos em roedores brasileiros da tribo Oryzomyini
(Cricetidae, Rodentia). Unpublished Ms. Biol. Thesis
Universidade de São Paulo.
Simpson GG, Roe A, Lewontin RC. 2003. Quantitative
zoology, 3rd edn. New York: Dover Publications.
Smith MF, Patton JL. 1993. The diversification of South
American murid rodents: evidence from mitochondrial DNA
sequence data for akodontini tribe. Biological Journal of the
Linnean Society 50: 149–177.
SPSS, Inc. Released 2004. SPSS for Windows, v. 13.0. Chicago,
IL: SPSS, Inc.
StatSoft, Inc. 2009. Statistica (data analysis software system),
version 7.0. Tulsa, OK: Statsoft, Inc.
Steppan SJ. 1995. Revision of tribe Phyllotini (Rodentia:
Sigmodontinae), with a phylogenetic hypothesis for
the Sigmodontinae. Fieldiana, Zoology, New Series 80:
1–112.
Swofford D. 2000. PAUP*: phylogenetic analysis using parsimony (*and other methods), version 4.0. Sunderland, MA:
Sinauer Associates Inc.
Tamura K, Peterson D, Peterson N, Stecher G, Nei M,
Kumar S. 2011. MEGA5: molecular evolutionary genetics
analysis using maximum likelihood, evolutionary distance,
and maximum parsimony methods. Molecular Biology and
Evolution 28: 2731–2739.
Tate GHH. 1932. The taxonomic history of the South and
Central American cricetid rodents of the genus Oryzomys.
Part 1: subgenus Oryzomys. American Museum Novitates 579:
1–18.
Technelysium Pty Ltd. 2007. Chromas lite v. 2.01.
Available at: http://www.technelysium.com.au/chromas_lite
.html
Templeton AR, Crandall KA, Sing CF. 1992. A cladistic
analysis of phenotypic associations with haplotypes
inferred from restriction endonuclease mapping and DNA
sequence data. III. Cladogram estimation. Genetics 132: 619–
633.
Teta P, Pardiñas UFJ, Andrade A, Cirignoli S. 2007.
Distribución de los géneros Euryoryzomys y Sooretamys
(Rodentia, Cricetidae) en Argentina. Mastozoologia Neotropical
14: 279–284.
Thomas O. 1884. On a collection of Muridae from Central Peru.
Proceedings of the Zoological Society of London 1884: 447–
458 + 3 plates.
Thomas O. 1921. Two new Muridae discovered in Paraguay
by the Marquis de Wavrin. Annals and Magazine of Natural
History, Series 9 7: 177–179.
Thomas O. 1924. The geographical races of Oryzomys ratticeps.
Annals and Magazine of Natural History, Series 9 14: 143–
144.
Thomé MTC, Zamudio KR, Giovanelli JGR, Haddad CFB,
Baldissera Jr FA, Alexandrino J. 2010. Phylogeography
of endemic toads and post-Pliocene persistence of the Brazilian Atlantic Forest. Molecular Phylogenetics and Evolution 55: 1018–1031.
Thompson JD, Higgins DG, Gibson TJ. 1994. CLUSTAL
W: improving the sensitivity of progressive multiple se-
quence alignment through sequence weighting, positionspecific gap penalties and weight matrix choice. Nucleic Acids
Research 22: 4673–4680.
Travassos Filho L, Camargo HFA. 1958. A Estação Biológica
de Boracéia. Arquivos de Zoologia do Estado de São Paulo
11: 1–21.
Trouessart EL. 1897. Catalogus Mammalium tam Viventium
quam Fossilium. Nova Editio (Prima Completa). Fascicullus
III. Rodentia II (Myomorpha, Hystricomorpha, Lagomorpha).
Berolini: H. Friedländer & Sohn.
Trouessart EL. 1904. Catalogus Mammalium tam Viventium
quam Fossilium. Quinquennale Supplementum. Berolini: H.
Friedländer & Sohn.
Valdez L, D′Elía G. 2013. Differentiation in the Atlantic Forest:
phylogeography of Akodon montensis (Rodentia, Sigmodontinae)
and the Carnaval-Moritz model of Pleistocene refugia. Journal
of Mammalogy 94: 911–922.
Vanzolini PE. 1970. Zoologia sistemática, geografia e a origem
das espécies. Série Teses e Monografias. Instituto de Geografia
da USP 3: 1–56.
Vanzolini PE, Williams EE. 1970. South American anoles:
the geographic differentiation and evolution of the Anolis
chrysolepis species group (Sauria, Iguanidae). Arquivos de
Zoologia, São Paulo 19: 1–298.
Ventura K, Sato-Kuwabara Y, Fagundes V, Geise L, Leite
YLR, Costa LP, Silva MJJ, Yonenaga-Yassuda Y,
Rodrigues MT. 2012. Phylogeographic structure and
karyotypic diversity of the Brazilian shrew mouse (Blarinomys
breviceps, Sigmodontinae) in the Atlantic Forest. Cytogenetic
and Genome Research 138: 19–30.
Vieira COC. 1953. Roedores e lagomorfos do estado de
São Paulo. Arquivos de Zoologia, São Paulo 8: 129–
168.
Voss RS. 1988. Systematics and ecology of ichthyomyine rodents
(Muroidea): patterns of morphological evolution in a small
adaptive radiation. Bulletin of the American Museum of
Voss RS. 1991. An introduction to the Neotropical muroid rodent
genus Zygodontomys. Bulletin of the American Museum of
Voss RS. 1993. A revision of the Brazilian muroid rodent genus
Delomys with remarks on ‘Thomasomyine’ characters. American Museum Novitates 3073: 1–44.
Voss RS, Carleton MD. 1993. A new genus for Hesperomys
molitor Winge and Holochilus magnus Hershkovitz (Mammalia,
Muridae) with an analysis of its phylogenetic relationships.
American Museum Novitates 3085: 1–39.
Voss RS, Linzey AV. 1981. Comparative gross morphology of
male accessory glands among Neotropical Muridae (Mammalia:
Rodentia) with comments on systematic implications.
Miscellaneous Publications, Museum of Zoology, University
of Michigan 159: 1–41.
Voss RS, Myers P. 1991. Pseudoryzomys simplex (Rodentia:
Muridae) and the significance of Lund’s collections from the
caves of Lagoa Santa, Brazil. Bulletin of the American Museum
of Natural History 206: 415–432.
Wagner JA. 1843. Fünfte ordung der Säugethiere. Rodentia,
nager. In: von Schreber JCD, ed. Die Säugethiere in
Abbildungen nach der natur mit Beschreibugen. Leipzig:
Erlangen, Suppl. 3, p. 135–614.
Wagner JA. 1845. Diagnosen einiger neuen arten von Nagern
und Handflüglern. Archiv für Naturgeschichte, 10 Jahrgang
1: 145–149.
Waterhouse GR. 1837. Characters of new species of the genus
Mus, from the collection of Mr. Darwin. Proceedings of the
Zoological Society of London 1837: 15–21, 27–32.
Weksler M. 1996. Revisão sistemática do grupo de espécies
nitidus do gênero Oryzomys (Rodentia: Sigmodontinae).
Unpublished MSc. Thesis. Universidade Federal do Rio de
Janeiro.
Weksler M. 2006. Phylogenetic relationships of the oryzomine
rodents (Muroidea: Sigmodontinae): separate and combined
analyses of morphological and molecular data. Bulletin of the
American Museum of Natural History 296: 1–149.
Weksler M, Percequillo AR. 2011. Key to the genera of the
Tribe Oryzomyini (Rodentia: Cricetidae: Sigmodontinae).
Mastozoologia Neotropical 18: 281–292.
Weksler M, Percequillo AR, Voss RS. 2006. Ten new genera
of oryzomyine rodents (Cricetidae: Sigmdontinae). American Museum Novitates 3537: 1–29.
Wilkinson M, McInerney JO, Hirt RP, Foster PG, Embley
TM. 2007. Of clades and clans: terms for phylogenetic
relationships in unrooted trees. Trends in Ecology and Evolution 22: 114–115.
Winge H. 1887. Jordfundne og nulevende Gnavere (Rodentia)
fra Lagoa Santa, Minas Geraes, Brasilien. E Museo Lundii
1: 1–200.
Winge H. 1888. Jordfunde og nulevende Gnavere (Rodentia)
fra Lagoa Santa, Minas Geraes, Brasilien: med udsigt over
gnavernes indbyrdes slatskab. E. Museo Lundii 1: 1–178 +
8 plates.
Wright S. 1943. Isolation by distance. Genetics 114: 114–
138.
Wright S. 1950. Genetical structure of populations. Nature 166:
247–249.
Yang Z, Rannala B. 1997. Bayesian phylogenetic inference
using DNA sequence: a Markov chain Monte Carlo method.
Molecular Biology and Evolution 14: 717–724.
APPENDIX 1
Specimens examined and specimens employed in each
analysis. Code a, indicates specimens used in morphological; b, specimens employed in morphological and
molecular analyses; c, specimens studied in molecular analyses; d, record of locality. Countries are typed
in bold uppercase, provinces (Argentina), states (Brazil),
and departments (Paraguay) in underline upper/
lowercase, departments (Argentina), municipalities
(Brazil) and districts (Paraguay) are typed in bold upper/
lowercase, and specific localities are in upper/lowercase.
ARGENTINA: Corrientes: Ituzaingó: Santa Tecla:
Ruta Nacional 12, km 1287: MLP 110945 (a). Formosa:
Pilcomayo: Paso Pomelo, Parque Nacional Pilcomayo:
MACN 20781 (a). Misiones: MACN 49388 (a). 30 km
867
de Puerto Bemberg, Rio Uruguay: MACN 49447 (a).
60 km de Puerto Iguazú, Rio Iguazú: MACN 52 (a).
Junction of Iguaçú and Alto Paraná Rivers, Puerto
Aguirre: MCZ 18648 (a). Refúgio Moconá: CNP 1998
(c) and 2524 (c). Rio Uruguay: MACN 19217 (a). Rio
Paraná, 100 mi S of Rio Iguassú: MCZ 27025 (a).
General Belgrano: Arroyo Uruguay: MACN 18885
(a). Azara: Balneário de Azara: MPEG 22649 (a).
Cainguás: Dos de Mayo: MACN 15588 (a). San Pedro:
San Pedro: MACN 15451 (a). Tobuna: MACN 54.15 (a),
54.20 (a), 54.29 (a), 54.37 (a), 54.47 (a), 54.48 (a), 54.49
(a), 54.50 (a), 54.57 (a), 54.62 (a), 54.94 (a), 54.74 (a)
and 54.81 (a).
BRAZIL: Espírito Santo: Serra do Caparaó, Fazenda
Cardoso: AMNH 61850 (a). Hotel Fazenda Monte Verde,
24 km SE de Venda Nova: UFPB 334 (a), 335 (b), 336
(a), 338 (a) and 339 (a). Minas Gerais: Conceição do
Mato Dentro: Boca da Mata, 104 km N of Lagoa Santa:
MN 13378 (a). Itamonte: MP301 (c). Passos: MN 32745
(a) and 11638 (a). Poços de Caldas: ACL 114 (a), 126
(a), 240 (a), 302 (a), 321 (a), 378 (a), 494 (a) and 526
(a). Alto da Consulta: MN 32629 (a), 32628 (a) and
32627 (a). Morro do Ferro: AMNH 207954 (a) and
207955 (a), MN 32626 (a). Posses: 13 km SE de
Itanhandú: INPA 11 (a), 12 (a) and 14 (a), UFMG 1880
(a), 1881 (a) and 1882 (a). Paraná: Arapoti: Horto São
Nicolau MHNCI 5372 (a), 5364 (a), 5365 (a), 5366 (a),
5368 (a), 5370 (a), 5374 (a), 5376 (a), 5407 (a), 5413
(a), 5418 (a) and 5422 (a). Cianorte: P. M. do Cinturão
Verde: MHCNI 6043 (a). Cruzeiro do Iguaçú: U. H.
Salto Caxias, Foz do Chopim, MHCNI 4838 (a). Fênix:
Fazenda Cagibi: MHCNI 5465 (a). Londrina: Mata
dos Godoy: MHCNI 5332 (d). Mangueirinha: Barragem
U.H.E. Segredo: MHCNI 2629 (a). Foz do Rio
Caçadorzinho: MHCNI 2630 (a). Morretes: Rio Sagrado:
MHCNI 3428 (d). Pinhão: Barragem U.H.E. Segredo,
Copel: MHCNI 5100 (a). Foz do Rio Capoteiro: MHCNI
2631 (a) and 2632 (a). Reserva: MHCNI 2445 (a). Vila
U.H.E. Segredo, Copel: MHCNI 2628 (a). Ponta Grossa:
P. E. Vila Velha: MHCNI 526 (d), 533 (a), 537 (d), 566
(a), 713 (a), 730 (a), 731 (a) and 733 (a). Quatro Barras:
Anhangava: MHCNI 4989 (a) and 4990 (a). Taquari
(Casa Garbers): MHCNI 3055 (a), 3120 (a) and 3133
(a). São José dos Pinhais: Guaricana: MHCNI 1349
(a), 1350 (a), 1473 (a) and 1582 (d). Usina de Guaricana:
MHCNI 1612 (a). Rio de Janeiro: Parati: Pedra Branca:
MN 6208 (a), 6215 (a), 6281 (a), 6397 (a), 6398 (a) and
8400 (a). São João de Marcos: Fazenda Tenente: MN
5762 (a). Teresópolis: CRB1271 (c), MN 50234 (c). Rio
Grande do Sul: Arroio Grande: MCNU 770 (a), 772
(a), 775 (a). Cachoeirinha: MCNU 1625 (b). Campo
Belo do Sul: MCNU 1802 (a). Canela: MCNU 1506
(a). Caxias do Sul: AFV 21 (c) and 22 (c). Cristal:
MCNU 1213 (a). Cruz Alta: FZB 436 (a), 426 (a), 444
(a) and 448 (a). 35 km NE de Cruz Alta: FZB 464 (a).
Cruzeiro do Sul: MCNU 1133 (a), 1134 (a), 1135 (a),
868
1136 (a), 1137 (a), 1138 (a), 1140 (a), 1143 (a), 1144
(a), 1146 (a), 1147 (a), 1148 (a), 1152 (a), 1157 (a), 1158
(a), 1159 (a). Encruzilhada do Sul: MCNU 1291 (b),
1292 (b). Guaporé: MCNU 983 (a). Lajeado Grande:
Alpestre: UFSC 3903 (a) and 3904 (a). Rio dos Índios:
UFSC 3900 (a), 3901 (a) and 3902 (a). Maquiné: MCNU
622 (b). Vale da Encantada/Barra do Ouro: MCNU 1540
(a). Mostardas: MN 37786 (c), 37789 (c). Capão do
Leão: UFRGS 595 (a) and 596 (a). Muitos Capões:
MCNU 1624 (a). Nova Roma do Sul: MCNU 1229
(b) and 1230 (b). Osório: MN 37794 (c). Lagoa
Emboaba: UFRGS 944 (a). Pontal do Norte, Lagoa
Palmital: UFRGS 971 (a), 1008 (a). Pelotas: Distrito
de Arroio do Padre: MCNU 1609 (a). São Francisco
de Paula: MCNU 1614 (a). São Nicolau: Fazenda Aldo
Pinto: MPEG 23273 (a), 23275 (a). Serafina Corrêa:
Boa Fé: MCNU 1586 (a). Tainhas: MN 37785 (c).
Torres: MN 37778 (c), 37780 (c) and 37783 (c), UFRGS
2088 (a), 2108 (a), 2114 (a) and 2130 (a), MCNU 1626
(a). Faxinal, Norte da Lagoa Itapeva: UFRGS 646 (a),
GD 69 (a) and 158 (a), UFRGS 656 (a), UMMZ 175072
(a) and 175073 (a). Parque Estadual Itapeva: MCNU
34 (a) and 670 (a). Tramandaí: Lenha Seca, Lagoa
de Tramandaí: MN 37790 (c), UFRGS 8 (a). Três
Barras: Aratiba, 3 m. da margem do R. Uruguai: AUC
14 (a). Santa Catarina: Água Doce: FURB 12071 (a),
12072 (a). Angelina: Garcia: UFSC 641 (a). Anitápolis:
Roça de Repolho: FURB 519 (a). Vale do IFC: FURB
472 (a) and 477 (b). Arvoredo: P. C. H. Alto Irani:
UFSC 3775 (a), 3776 (a) and 3831 (a). Blumenau:
Parque das Nascentes: Terceira Vargem: FURB 9798
(a), 9918 (a), 12041 (a, c), 12279 (a), 12286 (a). Caldas
da Imperatriz: Hotel Plaza Caldas da Imperatriz:
UFSC 3812 (a). Parque Estadual da Serra do Tabuleiro:
UFSC 721 (a) and 722 (a). Campo Belo do Sul:
Fazenda Gateados, Usina Hidroelétrica (U. H. E.) Barra
Grande: FURB 12174 (a). Canoinhas: Três Barras:
UFSC 763 (a). Pinheiros, Alto-Anitápolis: UFSC 488
(b). Dr. Pedrinho: Reserva Biológica Sassafrás: FURB
926 (a), 12151 (b) and 12100 (a). Florianópolis: MN
37777 (c). UFRGS 2042 (a). Lagoa do Peri: UFSC 2006
(a), 2007 (a), 2008 (a), 2009 (a), 2010 (a), 3021 (a) and
3022 (d). Gaspar: Reserva Particular do Patrimônio
Natural (RPPN) Figueira Branca: FURB 9749 (b). Ilha
de Santa Catarina: Ribeirão da Ilha: UFSC 2897 (a)
and 2898 (a). Indaial: Parque das Nascentes, Mono:
FURB 9696 (b), 9790 (b), 9836 (b), 9867 (b), 9906 (a),
9927 (a) and 9957 (a). Parque das Nascentes, Vale do
Espingarda: FURB 5900 (b), 5982 (a), 6472 (a), 6558
(a), 9570 (a) and 12086 (a). Itá: U. H. E. Itá: FURB
5035 (a), 5070 (b) and 5194 (a). Joinville: Estação
Ecológica Bracinho Piraí: FURB 138 (a), 927 (a), 928
(a) and 929 (a). Rio Negrinho: Fazenda Sta. Alice:
MHCNI 6062 (a) and 6064 (a). São Cristóvão do Sul:
Fazenda Cerro Verde: MHCNI 5863 (a). São Domingos:
U. H. E. Quebra Queixo: FURB 9230 (b), 9233 (a), 9238
(b), 9251 (a), 9252 (b) and 9256 (a), UFSC 3589 (a),
3590 (a), 3591 (a), 3592 (a), 3593 (a) and 3594 (a).
Siderópolis: Barragem São Bento: UFSC 3129 (a). Três
Barras: Floresta Nacional Três Barras: UFSC 951 (a)
and 3712 (a). Xavantina: P. C. H. Plano Alto: UFSC
3998 (a) and 3999 (a). Xaxim: Linha Voltão: UFSC 3897
(a). São Paulo: Apiaí: MZUSP 3168 (a), MN 9478 (a),
9912 (a), 9966 (a), 9967 (a), 9974 (a), 9976 (a), 9977
(a), 9980 (a), 9981 (a), 9982 (a), 9983 (a) and 9985 (a).
Bananal: Estação Ecológia de Bananal. MZUSP 33708
(a), 33709 (a), 33710 (a), EEB 646 (a), 691 (a). Capão
Bonito: Lira: RP 1888 (a) and 1889 (a). Carlos
Botelho: MZUSP 32850 (a), 32851 (a) and 32854 (a).
Cotia: RSB 6595 (c), MZUSP 9759 (a), 9772 (a), 9777
(a), 9798 (a), 9857 (a), 9879 (a), 9882 (a), 9884 (a), 9900
(a), 9915 (a), 9917 (a), 10200 (a), 25295 (a), 25296 (a)
and 25318 (a). Caucaia do Alto: MAM 153 (a), MZUSP
33172 (a), 33173 (a), 33174 (a), 33175 (a), 33176 (a),
33177 (a), 33178 (a), 33179 (a), 33180 (a), 33181 (a),
33182 (a), 33183 (a), 33184 (a), 33185 (a), 33186
(a), 33187 (a), 33188 (a), 33189 (a), 33190 (a), 33191
(a), 33192 (a), 33193 (a), 33194 (a), 33195 (a),
33196 (a), 33197 (a), 33198 (a), 33199 (a), 33200 (a),
33201 (a), 33202 (a), 33203 (a), 33204 (a), 33205
(a), 33206 (a), 33207 (a), 33208 (a), 33209 (a), 33210
(a) and 33211 (a). Iguape: MZUSP 26799 (a). Ipanema:
NMW B450 (a). Iporanga: MZUSP 25755 (a).
Itapetininga: UFMG 182 (d), MZUSP 1785 (a), 1786
(a), 1790 (a) and 23967 (a). Itapevi: Condomínio
TranSurb: MHNCI 3603 (a). Itararé: MZUSP 1124 (a)
and 1125 (a). Piedade: RP 217 (a), 254 (a) and 255
(a), MZUSP 31079 (d), 31140 (a), 31168 (d), 31169 (a),
31175 (d), 31181 (d), 31191 (d) and 31197 (a). Alce: RP
2355 (a). Baleia: RP 695 (a). Cristo: RP 855 (a) and
910 (a). Eme: RP 829 (a) and 2580 (a). Estrada: RP
2752 (a). Furnas: MZUSP 31089 (a). Teomar: RP 2339
(a). Piquete: AMNH 36497 (a), NHM 16634 (a). Riacho
Grande: MZUSP 30672 (a). Furnas: MZUSP 30666 (a),
30687 (a), 30704 (a), 30707 (a) and 30762 (a). Ribeirão
Grande: Boiadeiro: RP 133 (a). Canaleta AB, C. C.
Nassau: MHNCI 5623 (a), 5624 (a) and 5625 (a).
Canaleta T3,4: MHNCI 5606 (a). Corrego Água Limpa,
C. C. Nassau: MHNCI 5597 (a), MHNCI 5636 (a).
Corrego Barracão, C. C. Nassau: MHNCI 5599 (a) and
5600 (a). Corrego Barracão: MHNCI 4781 (b). Corrego
Fernandes, C. C. Nassau: MHNCI 5596 (a). Fazenda
Intervales, Base da Bocaina: MZUSP 27253 (a) and
27254 (a). Fazenda Intervales, Base do Carmo: MAM
312 (a), MVZ 182083 (a), MZUSP 27252 (a). Fazenda
Intervales, Sede: EM 1207 (c), MZUSP 27250 (a) and
27251 (a). Mato da Mina, C. C. Nassau: MHNCI 5635
(a). Moacir: RP 2045 (a). Mulheres: RP 333 (a). Museros:
RP 323 (a). Paraguai: RP 1263 (a). Ribeirão Pires:
MZUSP 584 (a). Salesópolis: Boracéia, Estação
Biológica de Boracéia do Museu de Zoologia da USP:
MAMustrangi 423 (a), MZUSP 9470 (a), 9727 (a), 9740
(a), 9741 (a), 9887 (a), 9888 (a), 10201 (a), 10368 (a),
10820 (a), 20575 (a), 20578 (a), 20579 (a), 21930 (a),
21956 (a), 22467 (a), 23933 (a), 23934 (a), 23945
(a), 23949 (a), 25511 (a), 32035 (a) and 32036 (a). Casa
Grande, Biritiba-Mirim: MZUSP 11065 (a), 11443 (a),
20572 (a), 21919 (a), 21924 (a), 21938 (a), 25370
(a), 25372 (a) and 27407 (a). Casa Grande: INPA 145
(a), 174 (a), 871 (a). UFMG 132 (d), 145 (d), 168 (a),
174 (d) and 871 (d). Salto Grande do Rio
Paranapanema: Fazenda Caioá: MZUSP 1273 (a).
Teodoro Sampaio: MZUSP 25324 (a). Ubatuba: Ilha
do Mar Virado: AUC 164 (a) and 165 (a). Unknown
municipality: Rio Feio: MZUSP 1910 (a), 1911 (a) and
1947 (a).
PARAGUAY: Amambay: Cerro Corá: 4 km by road
SW: UMMZ 125457 (a). Canendiyu: Canendiyu: GD
100 (d), UMMZ 175079 (d). Central: Asunción: Jardim
Botanico: AMNH 66784 (a). Trinidad: AMNH 36513
(a). Itapúa: San Rafael: 3.5 km E: UMMZ 126007 (a).
Orillas del Rio Tebicuary: UMMZ 174974 (a). Misiones:
Ayolas: 5 km ENE: AMNH 248409 (a) and 248411 (a),
UMMZ 125458 (a) and 125459 (a). Centu-Cue: GD
007 (d), 027 (d), 255 (d), 273 (c), 274 (c), 304 (d) and
306 (d), UMMZ 174817 (d), 174818 (a), 174834 (d),
175068, (d) 175069 (d), 175070 (d), 175071(d), 175082
(d) and 175083 (c). Costa del Rio Tebicuary: UMMZ
174989 (a). Junção dos rios Iguazu and Yaqueri: MCZ
28625 (a). Orillas del Rio Tebicuary: UMMZ 174870
(a). San Antonio: 2.7 km N: UMMZ 124196 (a), 124198
(a), 124201 (a), 124202 (a), 124204 (a), 124205 (a) and
124206 (a), MVZ 169997 (a). San Ignacio: NMNH
390129 (a), 390130 (a) and 390131 (a). Ñeembucú:
Estância Yacare: UMMZ 174845 (a), TK 61763 (c).
Paraguarí: Costa del Rio Tebicuary: GD 554 (a), UMMZ
174980 (a), 174984 (b) and 174987 (a). Costa Norte:
GD 552 (d), 560 (d), 536 (d), 537 (d), 543 (c) and 544
(d), UMMZ 174979 (c), 174982 (a), 175098 (d) and
175099 (c). Paraguari: GD 038 (d), 050 (d), 052 (c),
059 (d), 062 (d), 257 (c), 265 (c), 266 (d) and 285 (d),
UMMZ 175074 (d), 175075 (d), 175076 (d), 175077 (c),
175078 (d), 175080 (d) and 175081 (d). Sapucay: MCZ
217 (a), MZUSP 2372 (a), NHM 4.1.5.24 (a), NMNH
172968 (a). San Pedro: Ganadera La Carolina: GD
370 (d), 371 (d), 372 (d), 374 (d), 375 (d) and 376 (d),
UMMZ 174908 (d).
APPENDIX 2
Collecting localities for the genus Sooretamys in South
America, organized alphabetically by country; province (Argentina), state (Brazil), and department (Paraguay); and locality.
GAZETTEER
Argentina
Chaco
869
1. General Vedia, Bermejo. 26°56′S, 58°40′W. (Jayat
et al., 2006).
Corrientes
2. Santa Tecla, Ruta Nacional 12, km 1287,
Departamento Ituzaingó. 27°38′S, 56°22′W.
3. Santa Tecla, Ituzaingó. 27°37′S, 56°22′W. (Teta
et al., 2007).
Entre Ríos
4. Isla El Chapetón, Paraná. 31°33′S, 60°17′W (Teta
et al., 2007).
Formosa
5. Estancia Guaycolec, Formosa. 25°58′S, 58°10′W
(Teta et al., 2007).
6. Paso Pomelo, Parque Nacional Pilcomayo. 25°12′S,
58°00′W.
Misiones
7. 30 km de Puerto Bemberg, Rio Uruguay (Rio
Urugua-í). 25°58′S, 54°12′W (Teta et al., 2007).
8. 60 km de Puerto Iguazú, Rio Iguazú. 25°36′S,
54°11′W.
9. Apóstoles, Apóstoles. 27°55′S, 55°45′W (Massoia,
1993; Teta et al., 2007).
10. Arroyo Oveja Negra, en la intersección con la ruta
21, Parque Provincial Moconá, Guaraní. 27°22′S,
54°12′W (Mares & Braun, 2000; Teta et al., 2007).
11. Arroyo Paraíso, en la intersección com la ruta 2,
Guaraní. 27°16′S, 54°04′W (Mares & Braun, 2000;
Teta et al., 2007).
12. Arroyo Uruguay, Departamento General Belgrano.
26°08′S, 53°55′W.
13. Arroyo Uruzú, Sierra Victoria, General Manuel
Belgrano. 25°55′S, 54°17′W (Teta et al., 2007).
14. Arroyo Yabebyri, Candelaria. 27°17′S, 55°31′W
(Mares & Braun, 2000; Teta et al., 2007)
15. Balneario Arroyo Cuña Pirú, Misiones,
Argentina. 26°57′S, 55°07′W.
16. Balneário de Azara, Azara. 28°04′S, 55°42′W.
17. Bonpland, Candelaria. 27°29′S, 55°28′W (Massoia,
1993; Teta et al., 2007).
18. Campo Ramón, Oberá. 27°28′S, 54°59′W (Massoia,
1993; Teta et al., 2007).
19. Centro de Investigaciones Ecológicas Subtropicales,
Parque Nacional Iguazú, Iguazú. 25°41′S, 54°26′W.
20. Cuartel Río Victoria, Guarani. 26°46′S, 54°18′W
(Massoia, 1993; Teta et al., 2007).
21. Dos de Mayo, Departamento Cainguás. 27°02′S,
54°39′W.
22. El Dorado, El Dorado. 26°24′S, 54°34′W.
23. Escuela, 51, 4 km N de Loreto, Candelaria.
27°19′S, 55°32′W.
870
24. Establecimiento San Jorge, Iguazú. 25°52′S,
54°22′W.
25. Gobernador J. J. Lanusse, Iguazú. 25°28′S,
54°16′W.
26. Junção dos rios Iguazú e Alto Paraná, Puerto
Aguirre. 25°36′S, 54°35′W.
27. Misiones. 27°00′S, 55°00′W.
28. Puerto Península, Iguazú. 25°41′S, 54°39′W (Teta
et al., 2007).
29. Puerto Schwuelm, El Dorado. 26°26′S, 54°41′W
(Massoia, 1993; Teta et al., 2007).
30. Refugio Moconá. 27°8′S, 53°55′W.
31. Reserva de Usos Múltiples Guaraní, Departamento
Guaraní. 26°55′S, 54°13′W.
32. Reserva de Usos Múltiples Valle del Cuña Pirú,
Cainguás-Libertador General San Martín. 27°05′S,
54°57′W (Teta et al., 2007).
33. Reserva Privada de Vida Silvestre Urugua-í,
General Manuel Belgrano. 25°59′S, 54°05′W (Teta
et al., 2007).
34. Rio Paraná, 100 mi S of Rio Iguassú, Caraguatay,
C. C. Sanborn (col.), Setembro de 1926. 26°37′S,
54°46′W.
35. Rio Uruguay. N of Misiones Province, Rio Uruguay
is a tributary of left bank of Rio Paraná. 25°54′S,
54°36′W.
36. San Pedro, Departamento San Pedro. 26°38′S,
54°08′W.
37. Sendero Macuco, Parque Nacional Iguazú, Iguazú.
25°41′S, 54°26′W (Teta et al., 2007).
38. Sendero Yacaratiá, Parque Nacional Iguazú,
Iguazú. 25°41′S, 54°26′W (Teta et al., 2007).
39. Tobuna, Depto. San Pedro. 26°28′S, 53°54′W.
40. Yriguay, 30 km de Puerto Libertad, Iguazú.
26°06′S, 54°33′W.
Paraná
50. Anhangava, Quatro Barras. 25°23′S, 49°00′W.
51. Barragem U.H.E. Segredo, Mangueirinha
(= Barragem U.H.E. Segredo, Copel, Pinhão).
25°48′S, 52°07′W.
52. Fazenda Cagibi, Fênix. 27°19′S, 50°18′W.
53. Foz do Rio Caçadorzinho, Manguerinha. 27°19′S,
50°18′W.
54. Foz do Rio Capoteiro, Pinhão. 25°52′S, 52°10′W.
55. Guaricana, São José dos Pinhais. 25°43′S, 48°58′W.
56. Horto Barra Mansa, Arapoti. Not located. Arapoti
is located at 24°10′S, 49°40′W.
57. Horto São Nicolau, Arapoti Not located. Arapoti
58. Mata dos Godoy, Londrina. 23°27′S, 51°16′W.
59. Parque Estadual Vila Velha, Ponta Grossa.
25°15′S, 50°02′W.
60. Parque Municipal do Cinturão Verde, Cianorte.
23°40′S, 52°38′W.
61. Reserva, Pinhão. 25°43′S, 51°38′W.
62. Rio Sagrado, Morretes. 25°05′S, 048°49′W.
63. Taquari (Casa Garbers), Quatro Barras. 25°20′S,
48°50′W.
64. U.H. Salto Caxias, Foz do Chopim, Cruzeiro do
Iguaçú. 25°33′S, 53°06′W.
65. Usina de Guaricana, São José dos Pinhais. 25°43′S,
48°58′W.
66. Vila U.H.E. Segredo, Copel, Pinhão. 25°43′S,
48°58′W.
Rio de Janeiro
67. Fazenda Tenente, São João de Marcos. Not located.
Rio Claro, 22°46′S, 44°01′W.
68. Pedra Branca, Parati. 23°13′S, 44°43′W.
69. Teresópolis. 22°26′S, 42°59′W.
Brazil
Rio Grande do Sul
Espírito Santo
41. Hotel Fazenda Monte Verde, 24 km SE of Venda
Nova. 20°28′S, 40°56′W.
42. Serra do Caparaó, Fazenda Cardoso; 3360 ft.
20°22′S, 41°48′W.
Minas Gerais
43. Alto da Consulta, Poços de Caldas. Not located.
See Poços de Caldas coordinates.
44. Itamonte. 22°17′S, 44°53′W.
45. Boca da Mata, 104 km N de Lagoa Santa,
Conceição do Mato Dentro. 19°00′S, 43°26′W.
46. Morro do Ferro, Poços de Caldas. Not located. See
Poços de Caldas coordinates.
47. Passos. 20°42′S, 46°36′W.
48. Poços de Caldas, 21°47′S, 46°34′W.
49. Posses, 13 km SE of Itanhandú. 22°22′S, 44°51′W.
70. 35 km NE de Cruz Alta. 28°26′S, 53°20′W.
71. Aratiba, Três Barras, Rio Uruguai. c. 27°19′S,
52°14′W.
72. Arroio Grande. 32°14′S, 53°05′W.
73. Boa Fé, Serafina Corrêa. Not located. Serafina
Corrêa is located at 28°43′S, 51°56′W.
74. Cachoeirinha. 29°57′S, 51°05′W.
75. Capão do Leão, Mostardas. 31°06′S, 50 55′W.
76. Caxias do Sul. 29°10′S, 51°11′W.
77. Cristal. 30°05′S, 51°14′W.
78. Cruz Alta. 28°39′S, 53°36′W.
79. Cruzeiro do Sul. 29°31′S, 51°59′W.
80. Distrito de Arroio do Padre, Pelotas. 31°27′S,
52°27′W.
81. Encruzilhada do Sul. 30°32′S, 52°31′W.
82. Faxinal, Norte da Lagoa Itapeva, Torres. 29°22′S,
49°48′W.
83. Fazenda Aldo Pinto, São Nicolau. 28°11′S, 55°16′W.
84. Guaporé. 28°51′S, 51°54′W.
85. Itapeva, Parque Estadual de Itapeva, Torres.
29°21′S, 49°45′W.
86. Lagoa Emboaba, Osório. Not located. Osório is
located at 29°53′S, 50°16′W.
87. Lajeado Grande, Alpestre. Not located. Alpestre
88. Lajeado Grande, Rio dos Índios. Not located. Rio
dos Índios is located at 27°19′S, 52°53′W.
89. Maquiné. 29°41′S, 50°11′W.
90. Mostardas. 31°10′S, 51°31′W.
91. Muitos Capões. 28°19′S, 51°11′W.
92. Nova Roma do Sul. 28°59′S, 51°24′W.
93. Osório. 29°53′S, 50°16′W.
94. Parque da Ferradura, Canela. 29°16′S, 50°50′W.
95. Pontal do Norte, Lagoa Palmital, Osório. 50°06′S,
29°50′W.
96. Pró-Mata, São Francisco de Paula. 29°27′S,
50°08′W.
97. Tainhas. 29°16′S, 50°18′W.
98. Torres; 29°20′S, 49°43′W.
99. Tramandaí, Lenha Seca, Lagoa de Tramandaí
(= Lenha Seca, W Lagoa de Tramandaí). Not
located. Tramandaí is located at 29°59′S,
50°08′W.
100. Vale da Encantada/Barra do Ouro, Maquiné.
29°33′S, 50°16′W.
Santa Catarina
101. Água Doce. 27°00′S, 51°33′W.
102. Barragem do Garcia, Angelina. Not located.
Angelina is located at 27°35′S, 48°59′W.
103. Barragem do Rio São Bento, Siderópolis. Not
located. Siderópolis is located at 28°35′S, 49°03′W.
104. Bugre, Três Barras. 26°04′S, 50°14′W.
105. Campo Belo do Sul. 27°54′S, 50°45′W.
106. Canteiro de Obras, PCH Alto Irani, Arvoredo.
27°00′S, 52°25′W.
107. Canteiro de Obras, PCH Plano Alto, Xavantina.
26°57′S, 52°20′W.
108. Estação Ecológica Bracinho/Piraí, Joinville. Not
located. Joinville is located at 26°18′S; 48°50′W.
109. Fazenda Cerro Verde, São Cristóvão do Sul.
27°19′S, 50°18′W.
110. Fazenda Gateados, Usina Hidroelétrica (U. H. E.)
Barra Grande, Campo Belo do Sul. 27°54′S;
50°45′W.
111. Fazenda Sta. Alice, Rio Negrinho. 26°28′S. 49°30′W.
112. Floresta Nacional Três Barras. 26°12′S, 50°12′W.
113. Florianópolis. 27°36′S, 48°33′W.
114. Hotel Plaza Caldas da Imperatriz, Caldas da
Imperatriz, Santo Amaro da Imperatriz. 27°40′S,
48°46′W.
115. Lagoa do Peri, Florianópolis. 27°43′S, 48°32′W.
871
116. Linha Voltão, Xaxim. Not located. Xaxim is located
at 26°56′S, 52°31′W.
117. Mono, Parque das Nascentes, Indaial. 27°02′S;
49°08′W.
118. Parque Estadual da Serra do Tabuleiro, Santo
Amaro da Imperatriz. 27°44′S, 48°49′W.
119. Pinheiro Alto, Anitápolis (= Pinheiros, AltoAnitápolis). Not located. Anitápolis is located at
27°54′S; 49°08′W.
120. Reserva Biológica Sassafrás, Dr. Pedrinho. 26°42′S;
49°40′W.
121. Reserva Particular do Patrimônio Natural Figueira
Branca, Gasparinho, Gaspar. Not located. Gaspar
is located at 26°56′S; 48°58′W.
122. Ribeirão da Ilha, Ilha de Santa Catarina. 27°43′S,
48°35′W.
123. Roça de Repolho, Anitápolis. Not located. Anitápolis
124. Terceira Vargem, Parque das Nascentes,
Blumenau. 27°03′S, 49°06′W.
125. Três Barras. The correct location for this
locality is Canoinhas municipality, near to Floresta
Nacional de Três Barras. 26°06′S, 50°19′W.
126. U. H. E. Itá. 27°16′S, 52°22′W.
127. U. H. E. Quebra Queixo, Rio Xapecó, São
Domingos/Ipuaçú (= Aheqq, São Domingos).
26°40′S, 53°33′W.
128. Vale do Espingarda, Parque das Nascentes, Indaial
(= Parque das Nascentes, Sub-Sede). 27°01′S;
49°09′W.
129. Vale do IFC, Anitápolis. 27°54′S; 49°08′W.
São Paulo
130.
131.
132.
133.
134.
135.
136.
137.
138.
139.
140.
141.
142.
143.
Alce, Piedade. 66°16′S, 50°35′W.
Apiaí. 24°30′S, 48°51′W.
Baleia, Piedade. 23°53′S, 47°27′W.
Bauru (Jacutinga). 22°19′S, 49°04′W.
Boiadeiro, Ribeirão Grande. 24°05′S, 48°19′W.
Boracéia. Estação Biológica de Boracéia, Salesópolis
(see Travassos Filho & Camargo, 1958), 23°38′S,
45°52′W.
Canaleta AB, C. C. Nassau, Ribeirão Grande. Not
located. Ribeirão Grande is located at 24°05′S,
48°21′W.
Canaleta T3,4, Ribeirão Grande. Not located.
Ribeirão Grande is located at 24°05′S,
48°21′W.
Carlos Botelho 24°03′S, 47°49′W.
Casa Grande; Casa Grande, Biritiba-Mirim.
23°22′S, 45°56′W.
Casa Grande, Salesópolis. 23°22′S, 45°56′W.
Caucaia do Alto, Cotia, 23°42′S, 47°00′W.
Caucaia do Alto, SP. 23°41′S, 47°02′W.
Condomínio TranSurb, Itapevi. 23°35′S,
46°57′W.
872
144. Corrego Água Limpa, C. C. Nassau, Ribeirão
Grande. Not located. Ribeirão Grande is located
at 24°05′S, 48°21′W.
145. Corrego Barracão, Ribeirão Grande (= Córrego
Barracão, C. C. Nassau). Not located. Ribeirão
Grande is located at 24°05′S, 48°21′W.
146. Corrego Fernandes, C. C. Nassau, Ribeirão
Grande. Not located. Ribeirão Grande is located
at 24°05′S, 48°21′W.
147. Cotia, 23°37′S, 46°56′W.
148. Cristo, Piedade. 23°50′S, 47°28′W.
149. Eme, Piedade. 23°52′S, 47°28′W.
150. Estação Ecológia do Bananal. 22°41′S,
44°19′W.
151. Estrada, Piedade. 23°52′S, 47°29′W.
152. Fazenda Intervales (= Fazenda Intervales, Sede).
24°16′S, 48°24′W.
153. Fazenda Intervales, Base da Bocaina, 24°16′S,
48°27′W.
154. Fazenda Intervales, Base do Carmo, 24°18′S,
48°24′W.
155. Furnas, Piedade. Not located. Piedade is located
at 23°43′S, 47°24′W.
156. Furnas, Riacho Grande. Not located. Riacho
Grande is located at 23°48′S, 46°35′W.
157. Iguape, Costão dos Engenhos, 24°41′S, 47°28′W.
158. Ilha do Mar Virado, 23°34′S, 45°10′W.
159. Ipanema. 23°26′S, 47°36′W.
160. Iporanga, 24°36′S, 48°35′W.
161. Itapetininga, 23°35′S, 48°03′W.
162. Itararé, 24°06′S, 49°20′W.
163. Lira, Capão Bonito. 24°02′S, 48°18′W.
164. Mato da Mina, C. C. Nassau, Ribeirão Grande.
Not located. Ribeirão Grande is located at 24°05′S,
48°21′W.
165. Moacir, Ribeirão Grande. 24°13′S, 48°21′W.
166. Mulheres, Ribeirão Grande. 24°13′S, 48°23′W.
167. Museros, Ribeirão Grande. 24°13′S, 48°23′W.
168. Paraguai, Ribeirão Grande. 24°13′S, 48°23′W.
169. Paranapiacaba. 23°47′S, 46°19′W.
170. Piedade, São Paulo. 23°43′S, 47°24′W.
171. Piquete, 600–900 m, 22°36′S, 45°09′W. Type
locality of Oryzomys ratticeps tropicius.
172. Riacho Grande, SP. 23°48′S, 46°35′W.
173. Ribeirão Pires, 23°42′S, 46°24′W.
174. Rio Feio, 22°01′S, 49°39′W. Also called Rio Aguapeí
(see Pinto, 1945: 18).
175. Salto Grande do Rio Paranapanema, Fazenda
Caioá. 22°56′S, 49°59′W.
176. Teodoro Sampaio, 52°10′S, 22°31′W.
177. Teomar, Piedade. 23°49′S, 47°26′W.
Paraguay
Amambay
178. 4 km by road SW Cerro Corá. c. 22°37′S, 55°59′W.
Caaguazu
179. Junction of Yguazú and Yuqueri rivers. 25°15′S,
55°39′W.
Canindeyú
180. Canindeyú. 24°15′S, 55°36′W.
Central
181. Jardim Botânico, Assunción. 25°16′S, 57°40′W
182. Trinidad. 25°15′S, 57°38′W
Itapúa
183. 3.5 km E San Rafael. c. 27°08′S, 56°21′W.
184. Orillas del Río Tebicuary. 26°45′S, 56°33′W.
Misiones
185. 2.7 km by road N of San Antonio. 26°41′S, 56°53′W.
Type locality of Sooretamys angouya.
186. Ayolas, 5 km by road ENE Ayolas. 27°24′S,
56°54′W.
187. Centu-Cue. 26°28′S, 56°57′W.
188. Costa del Río Tebicuary, 26°30′S, 57°14′W.
189. Orillas del Río Tebicuary, 26°24′S, 57°02′W.
190. San Ignacio. 26°52′S, 57°03′W.
Ñeembucú
191. Yacare, Ñeembucu. 26°34′S, 58°07′W.
Paraguarí
192.
193.
194.
195.
Costa del Río Tebicuary, 26°30′S, 57°14′W.
Costa Norte, Paraguari. 26°00′S, 57°10′W.
Paraguari. 25°38′S, 57°09′W.
Sapucay, 25°40′S, 56°55′W. Type locality of
Oryzomys ratticeps paraganus.
San Pedro
196. Ganaderia La Carolina, 23°54′S, 56°36′W.
APPENDIX 3
Taxonomic account.
SOORETAMYS ANGOUYA (FISCHER, 1814)
Mus angouya Fischer, 1814:71; no type locality given;
based on Azara’s (1801: 86) ‘Rat Troìsieme ou Rat
Angouya’; type locality ‘Paraguay east of the Río Paraguay, Departamento de Misiones, 2.7 km (by road) N
of San Antonio,’ based on Neotype designation (Musser
et al., 1998: 300).
Mus? buccinatus Illiger, 1815:70; nomem nudum.
M[us]. buccinatus Olfers, 1818: 209; validation of Mus
buccinatus Illiger 1815; based on Azara’s (1801, 1802)
‘Rat Troìsieme ou Rat Angouya’ and ‘Del Anguyá,’
respectively.
Mus angouya Desmarest, 1819:62; based on Azara’s
(1801, 1802) ‘Rat Troìsieme ou Rat Angouya’ and ‘Del
Anguyá,’ respectively; part.
Mus angouya: Desmarest, 1820:305; incorrect
subsequent spelling of Mus Linnaeus.
Mus Anguya: Rengger, 1830:229; unjustified emendation of Mus angouya Fischer.
Mus (Holochilus) Anguya: Brandt, 1835:96; part; name
combination and unjustified emendation of Mus angouya
Desmarest.
Hesperomys Anguya: Wagner, 1843:534; name combination and unjustified emendation of Mus angouya
Fischer.
H[olochilus]. canellinus Wagner, 1843:552; substitute name for Mus anguya Brandt,which was a
misspelling of Mus angouya Desmarest and thus a
homonym of Mus angouya G. Fischer [ = Sooretamys
angouya (G. Fischer)].
Mus canellinus: Schinz, 1845:192; name
combination.
Hesperomys leucogaster Wagner, 1845:147; type
locality ‘Ypanema’ (= Floresta Nacional de Ipanema,
20 km NW Sorocaba, São Paulo, Brazil, 23°26′7′S
47°37′41′W, 701 m; Costa, Leite & Patton, 2003).
Hesperomys ratticeps Hensel, 1872:36, plate 1, fig. 25a,
b; plate 2, fig. 15a, b; type locality ‘Rio Grande do Sul,
Brasil’.
H[esperomys (Oryzomys)]. angouya: Thomas, 1884:448;
name combination.
Calomys rex Winge, 1888:50, plate 3, fig. 8; type locality ‘Rio das Velhas, Lagoa Santa, Minas Gerais, Brasil.’
Hesperomys (Calomys) ratticeps: von Ihering, 1893:15
(108); name combination.
[Oryzomys] anguya: Trouessart, 1897:525; name combination and unjustified emendation of Mus angouya
Fischer.
[Oryzomys] ratticeps: Trouessart, 1897:525; name
combination.
[Oryzomys (Oryzomys)] anguya: Trouessart, 1904:420;
name combination and unjustified emendation of Mus
angouya Fischer.
[Oryzomys (Oryzomys)] ratticeps: Trouessart, 1904:420;
name combination.
Oryzomys angouya: J. A. Allen, 1916:570; name combination, reference to Mus angouya Desmarest, 1819;
not Mus angouya Fischer, 1814.
O[ryzomys]. angouya: Thomas, 1921:177; name
combination.
Oryzomys ratticeps ratticeps: Thomas, 1924:143; name
combination.
Oryzomys ratticeps tropicius Thomas, 1924:143; type
locality ‘Piquete, São Paulo, Brasil.’
873
Oryzomys ratticeps paraganus Thomas, 1924:144; type
locality ‘Sapucay, Paraguari, Paraguai.’
Oryzomys [(Oryzomys)] angouya: Tate, 1932:18; name
combination.
Oryzomys [(Oryzomys)] ratticeps ratticeps: Tate,
1932:18; name combination.
Oryzomys [(Oryzomys)] ratticeps tropicius: Tate,
Oryzomys [(Oryzomys)] ratticeps paraganus: Tate,
Holochilus physodes physodes: Vieira, 1953: 134; part;
erroneous identification.
Oryzomys buccinatus: Hershkovitz, 1955:660; name
combination.
[Holochilus] anguyu: Musser and Carleton, 2005: 1119;
lapsus calami.
[Sooretamys] angouya: Weksler, Percequillo, & Voss,
2006:23; first use of current name combination.
Type locality
Paraguay, east of the Rio Paraguay, Departamento de
Misiones, 2.7 km (by road) north of San Antonio
(locality 185 on map in Fig. 12).
Neotype
UMMZ 124201, a young adult male collected by
P. Myers on 22.viii.1976; the skin, skull, and carcass
are well preserved in fluid.
Geographical distribution
Sooretamys angouya is distributed along the forested
foothills and slopes of the Serra do Mar, Serra da
Mantiqueira, and eastern hillsides of the Serra do
Espinhaço (all in the Atlantic Forest), and coastal lowland
forests (Restinga) from Espírito Santo to Rio Grande
do Sul, Brazil, including some of the coastal islands in
Santa Catarina and São Paulo states. To the west, this
species reaches the Argentine provinces of Misiones,
Corrientes, and Entre Ríos on the east bank of Rio Parana,
and the Argentinean provinces of Formosa and Chaco
and the Paraguayan state of Presidente Hayes on the
west bank of Rio Paraguay. Figure 12 shows all the
recorded localities for the genus.
Most current records of this species are associated
with the Atlantic Forest, more precisely the evergreen
tropical montane and lowland rainforest and semideciduous tropical and subtropical forests. Alho (1982)
and Fonseca & Redford (1984) erroneously assigned
this species to the Cerrado of Central Brazil. We sorted
hundreds of specimens of Oryzomyini in museums and
collections and were not able to find a single specimen
of this species collected in the open and drier (e.g. Cerrado
sensu stricto) or even on the more mesic (cerradão and
gallery forest) habitats of the Cerrado.
Specimens of S. angouya obtained by P. Lund came
exclusively from the caves of Lagoa Santa, Minas Gerais
874
BRAZIL
PARAGUAY
B
A
ARGENTINA
A
B
Figure 12. Known collection localities of Sooretamys angouya (Fischer, 1814) in South America. The numbers associated
with the collection sites are given in the gazetteer in Appendix 2. Figures A and B (below) represent maps with the detailing
of the collection localities of the gray boxes A and B in the upper map, of Misiones, Argentina and East of São Paulo, Brazil.
(reported as Calomys rex by Winge, 1888), preserved
as fossil or subfossil material. To the best of our knowledge, however, there are no recent records of this species
from this region. Specimens recorded by Ávila-Pires
(1960a) from the ‘Lagoa Santa region’ actually came
from Conceição do Mato Dentro, which is located nearly
110 km north-east of Lagoa Santa on the eastern slope
of Serra do Espinhaço, a more humid area predominantly covered by forests. At present, the region of Lagoa
Santa is covered mostly by Cerrado vegetation or is
transitional between semideciduous forest and Cerrado,
and we believe that this habitat is not suitable for
S. angouya. The same distributional pattern of typical
dwelling-forest species recorded in the caves of Lagoa
Santa as fossils and subfossils is also observed for many
other sigmodontines and echymyids, such as Blarinomys
breviceps, Delomys sp., Euryoryzomys russatus,
Callistomys pictus, Juliomys sp., and Lundomys molitor
(Voss, 1993; Voss & Carleton, 1993; Emmons & Vucetich,
1996; Musser et al., 1998; Pardiñas & Teta, 2011; Silva
et al., 2003; see also Voss & Myers, 1991 for a summary
of a Lagoa Santa cave fauna).
Genus and species diagnosis and description
Sooretamys angouya can be easily distinguished
from other sympatric species of the tribe Oryzomyini
(such as Euryoryzomys russatus, Hylaeamys laticeps,
Nectomys squamipes, Drymoreomys albimaculatus) by
its large body size (head and body length ranging
from 125 to 215 mm), tail much larger than head and
body length (ranging from 160 to 240 mm), and
nonwebbed, robust, and wide hind feet (length ranges
from 25 to 42 mm). The skull of Sooretamys is unique
amongst genera of the tribe, easily recognized by its
large size (skull length ranging from 35.6 to 44.3 mm).
Long and wide incisive foramina (length ranging from
7.3 to 9.5 mm) reaching the alveolus of M1 in many
specimens, wider medially, with anterior and posterior margins acute; palate long with deep and complex
posterolateral palatal pits; narrow and long hourglass shaped interorbital region, with squared
supraorbital margins (interorbital breadth ranging from
4.9 to 6.0 mm). Molars very robust (toothrow length
varies from 5.6 to 6.5 mm; M1 breadth ranging from
1.5 to 1.8 mm).
Body pelage soft, long, and very dense, with numerous and short viliforms ranging from 7 to 10 mm in
length, thin and wavy, grey-based (5 to 8 mm) with a
buffy to yellowish/reddish subterminal band and darkbrown terminal band. Setiforms numerous and longer,
ranging from 12 to 14 mm, thin, grey-based (6 to 10 mm)
with a buffy to yellowish/reddish subterminal band
and a dark-brown, entirely brown, or entirely yellowish to orangish terminal band. Aristiforms scarce and
very long, ranging from 15 to 18 mm, thicker, greybased (6 to 10 mm) with a dark-brown or black distal
portion and golden tip. Dorsal body colour varies from
buffy yellowish brown, to reddish, greyish, and darkbrown. Ventral pelage shorter and dense. Viliforms
are numerous and dense, ranging from 7 to 9 mm,
grey-based (3 to 5 mm) with a whitish, buffy, or yellowish distal portion or entirely whitish, buffy, or yellowish. Setiforms dense, ranging from 11 to 13 mm,
grey-based (3 to 5 mm) with a whitish, buffy, or yellowish distal portion. Aristiforms rare, longer, ranging
from 13 to 14 mm, with a colour pattern as described
for the viliforms and setiforms. Ventral colour ranges
from whitish or buff weakly grizzled with grey to an
almost pure white, buffy, or buffy-yellow. Tail much
longer than head and body and covered with short
hairs, which do not conceal the large scales; tail scales
and hairs are blackish or dark brown, with no
countershading or only slightly countershading in
samples from São Paulo, Misiones, and eastern Paraguay. Internal and external surfaces of the ears well
furred, with entirely brown hairs. Fore and hind feet
long and robust, with digits II to IV similar in size
and longer than digits I and V. Feet covered by short
brown or brown-based and white-tipped hairs; the
875
ungual tufts of fore feet are dense and long, almost
concealing the claws in digits II to V; digit I with a
short tuft or without tuft. Ungual tufts of hind feet
long and dense, sometimes extending beyond top of
claws, with a brown proximal band and a white distal
tip. Mystacial vibrissae very dense and long, surpassing the ears when laid back; most dorsal vibrissae
dark brown with golden tips and the most ventral
entirely white.
Skull long and robust, with a long and wide rostrum
flanked by well-inflated capsular projections of the
nasolacrimal foramen. Zygomatic plate with free anterior margin well projected anteriorly and laterally, configuring a deep and wide zygomatic notch; the rostral
margin of the zygomatic notch with a well-marked depression, through maxillar. Zygomatic arches expanded laterally, wider near squamosal root, and jugal well
developed. Interorbital region long and narrow, long
hourglass shaped, with rounded to squared supraorbital
margins, which project posteriorly, continuous with the
temporal crest. Braincase with rounded profile, with
the temporal border squared but without crests or beads.
Lambdoidal and nuchal crests acute and well developed. Zygomatic plate wide, with a straight or concave
free anterior margin, well projected anteriorly. Squamosoalisphenoid groove and sphenofrontal foramen absent,
and the minute or absent stapedial foramen configures the derived carotid circulatory pattern 3 (sensu
Voss, 1988). Bucinator-masticatory and accessory oval
foramina confluent, and alisphenoid strut absent.
Postglenoid foramen and subsquamosal fenestra large
and wide. Auditory bulla moderately projected ventrally, with a wide auditory external meatus; wide tegmen
tympanii, reaching or not the squamosal; long and wide
stapedial process, overlapped or not to the parapterygoid
plate; long and wide dorsostapedial process, overlapped with the squamosal; and narrow mastoid, without
mastoid fenestra in adults. Incisive foramina long and
narrow, occupying most of the diastema, with
anteroposterior extremities acute to round, and convex
lateral margins wider medially or posteromedially; the
posterior margin of the foramina reaches or not the
anterior margin of the molar series. Palate long and
wide, with small posterolateral palatal pits at the palate
level in young specimens, and deep and complex
posterolateral palatal pits recessed in the deep palatine fossa in adult specimens; palatal excrescences absent.
Mesopterygoid fossa as wide as the lateral parapterygoid
plates. Anterior margin rounded or nearly triangular,
with posterolateral palatal pits not reaching the molar
series in adults (in young specimens, the fossa may
reach the hypocone of M3). Roof of the mesopterygoid
fossa perforated by long and wide sphenopalatine vacuities, exposing the orbitosphenoid bone. Parapterygoid
plate wide, moderately excavated, with a straight or
slightly concave profile. Posterior opening of the
876
alisphenoid canal large and rounded; medium lacerate
foramen wide. Auditory bullae large and globose, with
a short and wide Eustachian tube.
Mandible with a low coronoid process, nearly triangular in shape and equal in height to the condyloid
process; angular process rounded, not exceeding the
condyloid process; capsular process of the lower incisor
present and well developed; superior and inferior notches
shallow.
Upper incisors opisthodont and wide. Upper molar
series long and parallel and pentalophodont and lowcrowned; main cusps arranged in opposite pairs, and
the labial and lingual flexi interpenetrate only slightly at the median molar plane. On M1 and M2, paracone
connected medially to the protocone, not to the median
mure, defining a long and obliquely orientated
parafosset, fusing to the metacone only with heavy wear.
Mesoloph long and wide and connected to the mesostyle.
Metacone connected to the posteroloph by a posterior
metalophule and connected to the hypocone by a medial
metalophule. Posteroloph well developed and separated from the metacone, even with moderate wear. First
upper molar with four roots, one labial anterior, one
labial posterior, one lingual, and one accessory root,
positioned below the paracone. M2 and M3 with three
roots, two labials (anterior and porterior) and one
lingual.
Lower incisors long and sharp. Lower molar series
parallel; cusps arranged in opposite pairs, with lingual
cusps slightly anterior to labials. First lower molar with
an anterocone divided or not by small and shallow medial
flexus or flexi, restricted to the enamel surface. M2
with a well-developed anterolophid, sometimes with
ectolophid. M1 with one anterior and one posterior root,
with accessory labial and lingual rootlets. M2 and M3
with three roots.
Axial skeleton composed of seven cervical, 12 to 13
thoracic, six to seven lumbar, four sacral, and 31 to
36 caudal vertebrae. Haemal arches with distinct
median posterior processes. Anapophyses present on
the 17th thoracico-lumbar vertebra. Entepicondylar
foramen of the humerus absent, and a supratrochlear
foramen present. Trochlear process of the calcaneum
gap between the proximal edge of the trochlear process
and the posterior articular facet.
Stomach unilocular and hemiglandular; bordering fold
between the gastric and glandular epithelium well developed and orientated 45° to the right of the stomach.
Gall bladder absent.
Glans penis complex. Proximal bony baculum with
a wide and flattened basal portion and a long and
rounded apical portion. Cartilaginous terminal baculum
tridigitated and well developed, approximately half the
length of bony baculum. Central cartilaginous digit
longer than lateral, with the distal apex lying outside
the glans body.
Taxonomic history
The taxonomic history of S. angouya is long and confusing, especially regarding the several names proposed for the rat described by D. Felix de Azara (1801,
1802), the ‘Rat Troìsieme ou Rat Angouya’ or ‘Del
Anguyá,’ the specimens of which have been lost since
the 19th century (see also Desmarest, 1804, who also
referred to Azara’s ‘Rat Angouya’). Some authors suggested that the epithet angouya should refer to a Paraguayan species of the genus Cerradomys (specifically,
Cerradomys maracajuensis; e.g. Ávila-Pires, 1960b;
Myers, Lundrigan & Tucker, 1995) or should be considered a nomen dubium (Weksler, 1996; Musser et al.,
1998). However, the conundrum was resolved by selecting a neotype for Mus angouya Fischer, 1814 and
associating it to the species then formerly known as
‘Oryzomys’ ratticeps Hensel, 1872. This nomenclatural act brought stability to this taxon, although the
official availability of Fischer’s names has not yet been
accepted by explicit action of the ICZN (see Langguth,
1966; Sabrosky, 1967; and Musser et al., 1998). Musser
et al. (1998) also provided a detailed and comprehensive description of the taxonomic history of the names
associated with this species.
Vieira (1953: 134) identified specimens of this species
from São Paulo state, Brazil, as Holochilus physodes
physodes, a name combination confusingly applied historically to both the genera Holochilus and Reithrodon
(see Musser et al., 1998: 280–284).
Karyology
Silva (1994) recorded two distinct cytotypes from
Iporanga (São Paulo, Brazil; locality 160) with diploid
number (2n) = 58/60 and autosomal arm number
(NF) = 60/64. Andrades-Miranda et al. (2000) found
2n = 58 and NF = 60 for Espírito Santo (locality 41),
Santa Catarina (locality 122), and Rio Grande do Sul
states (localities 75, 76, 97, 98, 99).
Natural history
Sooretamys angouya is a scansorial species that can be
captured both on the ground and in trees and vines
(data from skin tags and collector field notes). Olmos
(1991) reported that S. angouya is an aggressive species:
when caught in the same trap with another species,
S. angouya always killed and ate the individuals; when
caught with individuals of the same species, Olmos (op.
cit.) observed fights amongst them. Olmos also reported that this species moved on the ground by metrelong leaps and that individuals were good climbers of
both trees and rock walls, as well as good diggers, producing ‘extensive tunnels, even in hard, rocky ground’
(Olmos, 1991: 561).
In the eastern part of its range, S. angouya inhabits
mature and undisturbed portions of the Atlantic Forest,
but it is more commonly observed in secondary forests
(Pardini & Umetsu, 2006). In westernmost regions
(Formosa, Argentina, and Presidente Hayes, Paraguay), the species occurs in patches and remnants of
semideciduous, dense Chacoan forest (also gallery forests)
amidst Chaco vegetation (this contribution; Myers, 1982).
In a study of 3150 trap-nights over 13 months, between
December 1988 and December 1989 at Fazenda
877
Intervales, Olmos (1991) verified that the females were
reproductively active during October and November,
with juveniles being trapped in June (dry season). The
predominant vegetation in the study site was mature
forest, but there was an old secondary forest specifically in the site where the traps were placed (Olmos,
1991).
SUPPORTING INFORMATION
Additional Supporting Information may be found in the online version of this article at the publisher’s web-site:
Table S1. Genetic distances of the cytochrome b gene within ( p-distance: second column, “intra”) and among
( p-distance: below the diagonal; Kimura 2 parameters: above the diagonal) localities of Sooretamys angouya
(the first column shows the country and the State/Province/Department abbreviation, see Figure 3 and Appendix II for locality details).

(Rodentia: Cricetidae: Sigmodontinae): an integrative approach

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