Tópicos em Estatística Espacial para Ecologia 1º semestre/2013

Tópicos em Estatística Espacial para Ecologia
1º semestre/2013
1.
Docente
Dr. Pedro V. Eisenlohr ([email protected])
http://www.pedroeisenlohr.webnode.com.br
2.
Objetivo principal
Apresentar, discutir e processar alguns métodos de análise espacial em Ecologia a partir de uma abordagem essencialmente
prática, evitando, sempre que possível, o uso de pormenores matemáticos.
3.
Proposta de dinâmica
- Manhãs: aulas teóricas (2 horas) e práticas (2 horas).
- Tardes: discussão de artigos*, resolução de exercícios e de dúvidas e outras atividades a definir.
* sugiro a leitura prévia dos artigos destacados em negrito no item “Principais referências”. São artigos interessantes
para discussão durante o curso.
4.
Conteúdo programático
Data
Tópicos
2af
- O pressuposto de independência estatística entre as observações de uma amostragem ou experimento.
- Autocorrelação espacial e estrutura espacial: conceito, definições e implicações.
- Correlogramas.
- Coeficientes indicadores de estrutura espacial.
- A tomada de decisão.
3af
- Regressão Múltipla em um contexto espacial: o paradigma “red herrings”.
4af
- Lidando com a estrutura espacial: princípios e métodos inferenciais clássicos.
- Teste t com correção de Duttileul.
- Filtros espaciais (PCNM e métodos relacionados): conceitos, fundamentos e aplicação.
- Seleção de modelos na presença de estrutura espacial.
5af
- Partição da variância: método polinomial (1992) vs. PCNM e métodos relacionados (após 2002).
- Partição da variância: método univariado e método multivariado.
6af
- Teste de Mantel. Teste de Mantel Parcial.
- O pressuposto de estacionariedade e o método GWR – Geographically Weighted Regression.
5.
Principais referências
5.1 Beale, C.M., Lennon, J.J., Yearsley, J.M., Brewer, M.J. & Elston, D.A. (2010) Regression analysis of spatial data.
Ecology Letters 13: 246–264.
5.2 Blanchet et al. (2008). Modelling directional spatial processes in ecological data. Ecological Modelling 215: 325–336.
5.3 Borcard, D. & Legendre, P. (2002) All-scale spatial analysis of ecological data by means of principal coordinates of
neighbor matrices. Ecological Modelling 153: 51–68.
5.4 Borcard, D., Legendre, P., Avois-Jacquet, C. & Tuomisto, H. (2004) Dissecting the spatial structure of ecological data
at multiple scales. Ecology 85: 1826–1832.
5.5 Cassemiro, F.A.S., Barreto, B.S., Rangel, T.F.L.V.B. & Diniz-Filho, J.A.F. (2007) Non-stationarity, diversity
gradients and the metabolic theory of ecology. Global Ecology and Biogeography 16: 820-822.
5.6 Diniz-Filho, J.A.F., Bini, L.M. & Hawkins, B.A. (2003) Spatial autocorrelation and red herrings in geographical
ecology. Global Ecology and Biogeography 12: 53–64.
5.7 Diniz-Filho, J.A.F. & Bini, L.M. (2005) Modelling geographical patterns in species richness using eigenvectorbased spatial filters. Global Ecology and Biogeography 14: 177–185.
5.8 Diniz-Filho, J.A., Rangel, T.F.L.V.B. & Bini, L.M. (2008) Model selection and information theory in
geographical ecology. Global Ecology and Biogeography 17: 479–488.
5.9 Dormann, C.F. (2007) Effects of incorporating spatial autocorrelation into the analysis of species distribution data.
Global Ecology and Biogeography 16: 129-138.
5.10 Dormann, C.F. et al. (2007). Methods to account for spatial autocorrelation in the analysis of species distributional
data: a review. Ecography 30: 609-628.
5.11 Dray, S.P., Legendre, P. & Peres-Neto, P. (2006) Spatial modelling: a comprehensive framework for principal
coordinate analysis of neighbor matrices (PCNM). Ecological Modelling 196: 483-493.
5.12 Dutilleul, P. (1993) Modifying the t test for assessing the correlation between two spatial processes. Biometrics 49:
305–314.
5.13 Eisenlohr, P.V. (2013) Challenges in Data Analysis: pitfalls and suggestions for a statistical routine in
Vegetation Ecology. Brazilian Journal of Botany 2. Soon available at: http://dx.doi.org/10.1007/s40415-013-00029.
5.14 Fortin, M.-J. & Dale, M.R.T. (2005) Spatial analysis. A guide for ecologists. Cambridge University Press, Cambridge.
5.15 Fortin, M.-J. & Gurevitch, J. (2005). Mantel Tests: Spatial Structure in Field Experiments. In: S.M. Scheiner & J.
Gurevitch (eds.). Design and analysis of ecological experiments. 2 ed. Oxford University Press, Oxford.
5.16 Fotheringham, A.S., Brunsdon, C. & Charlton, M. (2002). Geographically weighted regression: the analysis of
spatially varying relationships. John Wiley & Sons, Chichester.
5.17 Griffith, D.A. (2003) Spatial autocorrelation and spatial filtering - gaining understanding through theory and
visualization. Springer-Verlag, Berlin.
5.18 Griffith, D.A. & Peres-Neto, P.R. (2006) Spatial Modelling in Ecology: the flexibility of eigenfunction spatial
analyses. Ecology 87: 2603-2613.
5.19 Hawkins, B.A., Diniz-Filho, J.A.F., Bini, L.M., De Marco, P. & Blackburn, T.M. (2007) Red herrings revisited:
spatial autocorrelation and parameter estimation in geographical ecology. Ecography 30: 375-384.
5.20 Heffner, R.A., Butler, M.J. & Reilly, C.K. (1996) Pseudoreplication revisited. Ecology 77: 2558-2562.
5.21 Hurlbert, S.H. (1984) Pseudoreplication and the design of ecological field experiments. Ecological Monographs 54:
187-211.
5.22 Kupfer, J.A. & Farris, C.A. (2007) Incorporating spatial non-stationarity of regression coefficients into predictive
vegetation models. Landscape Ecology 22:837–852.
5.23 Legendre, P. & Fortin, M.-J. (1989) Spatial pattern and ecological analysis. Vegetatio 80: 107–138.
5.24 Legendre, P. (1993) Spatial autocorrelation: trouble or new paradigm? Ecology 74: 1659–1673.
5.25 Legendre, P., Dale, M.R.T., Fortin, M.-J., Gurevitch, J., Hohn, M. & Myers, D. (2002) The consequences of
spatial structure for the design and analysis of ecological field surveys. Ecography 25: 601-615.
5.26 Legendre, P., Borcard, D & Robertsm D.W. (2012) Variation partitioning involving orthogonal spatial eigenfunction
submodels. Ecology 93: 1234–1240.
5.27 Peres-Neto, P.R. & Legendre, P. (2010) Estimating and controlling for spatial structure in the study of ecological
communities. Global Ecology and Biogeography 19: 174-184.
5.28 Rangel, T.F., Diniz-Filho, J.A.F. & Bini, L.M. (2010) SAM: a comprehensive application for Spatial Analysis in
Macroecology. Ecography 33: 46-50.
5.29 Santos, R.M., Oliveira-Filho, A.T., Eisenlohr, P.V., Queiroz, L.P., Cardoso, D.B.O.S. and Rodal, M.J.N. (2012)
Identity and relationships of the Arboreal Caatinga among other floristic units of seasonally dry tropical forests
(SDTFs) of north-eastern and Central Brazil. Ecology and Evolution 2: 409–428.
5.30 Ver Hoef, J.M. & Cressie, N. (2001) Spatial statistics: analysis of field experiments. In: S.M. Scheiner & J. Gurevitch
(eds.). Design and analysis of ecological experiments. 2 ed. Oxford University Press, Oxford.