Download LCF5883 - Species Distribution Modeling for Biology

LCF5883 - Species Distribution Modeling for Biology Conservation
Objective
To provide bases for students to develop species distribution models considering
different spatial scales, and for fauna and flora organisms, incorporating concepts,
methods and applications;
To enable students in using various spatial data modeling and analysis software;
and To discuss the implications of using modeling for biodiversity conservation.
Content
Introduction to the Species Distribution Models, presenting historical and theoretical
reference;
Potentialities, limitations and applications;
Sources of biodiversity data;
Sources of environmental data;
Quality assessment of biodiversity and environmental data;
Software and methods used for modeling; Modeling procedures, considering algorithms,
validation and sources of error; Consensus models;
Introduction to the landscape ecology for modeling purposes; Preparation of data on the
landscape scale.
Bibliography
Species abundance modeling
Elith, J., Graham, C.H., Anderson, R.P., Dudík, M., Ferrier, S., Guisan, A., Hijmans, R.J.,
Huettmann, F., Leathwick, J.R., Lehmann, A., Li, J., Lohmann, L.G., Loiselle, B.A.,
Manion, G., Moritz, C., Nakamura, M., Nakazawa, Y., Overton, J. McC., Peterson, A.T.,
Phillips, S.J., Richardson, K.S., Scachetti-Pereira, R., Schapire, R.E., Soberón, J.,
Williams, S., Wisz, M.S., Zimmermann, N.E. 2006. Novel methods improve prediction of
species´ distribution models. Ecography 32, 66-77.
Elith, J., Leathwick, J.R. 2009. Species distribution models: ecological explanation and
prediction across space and time. Annual Review of Ecololy, Evolution and Systematics
40:677-697.
Elith, J., Graham, C.H. 2009. Do they? How do they? WHY do they differ? On finding
reasons for differing performances of species distribution models. Ecography 32:66-77.
Ferraz, K.M.P.M.B., Siqueira, M.F., Alexandrino, E.R., Luz, D.T.A., Couto, H.T.Z. 2012.
Environmental suitability of a highly fragmented and heterogeneous landscape for forest
bird species in south-eastern Brazil. Environmental Conservation 1-9.
Ferraz, K.M.P.M.B., Siqueira, M.F., Martin, P.S., Esteves, C.F., Couto, H.T.Z. 2010.
Assessment of Cerdocyon thous distribution in an agricultural mosaic, southeastern
Brazil. Mammalia 74:275-280.
Fielding, A.H., J.F. Bell. 1997. A review of methods for the assessment of prediction
errors in conservation presence/absence models. Environmental Conservation, 24(1):
38-49.
Liu, C., Berry, P.M., Dawson, T.P., Pearson, R.G. 2005. Selecting thresholds of
occurrence in the prediction of species distributions. Ecography 28: 385–393.
Liu, C., White, M., Newell, G. (2011) Measuring and comparing the accuracy of species
distribution models with presence-absence data. Ecography 34: 232–243.
Loiselle, B.A., Graham, C.H., Goerck, J.M., Ribeiro, M.C., 2010. Assessing the impact of
deforestation and climate change on the range size and environmental niche of bird
species in the Atlantic forests, Brazil. Journal of Biogeography, doi:10.1111/j.13652699.2010.02285.x.
Marmion, M., Parviainen, M., Luoto, M., Heissinen, R.K., Thuiller, W. 2009. Evaluation of
consensus methods in predictive species distribution modeling. Diversity and Distribution
15:59-69.
Pearson, R. G. 2007. Species’ Distribution Modeling for Conservation Educators and
Practitioners. Synthesis. American Museum of Natural History. Available at
http://ncep.amnh.org.
Phillips, S. J., Dudík, M. 2008. Modeling of species distributions with Maxent: new
extensions and a comprehensive evaluation. Ecography 31: 161-175.
Phillips, S.J., Anderson, R.P., Schapire, R.E. 2006. Maximum entropy modeling of
species geographic distributions. Ecological Modelling 190:231-259.
Phillips, S.J., Dudík, M., Elith, J., Graham, C.H., Lehmann, A., Leathwick, J., Ferrier, S.
2009. Sample selection bias and presence-only distribution models: implications for
background and pseudo-absence data. Ecological Applications 19:181-197.
Rodriguez-Soto, C., Monroy-Vilchis, O., Maiorano, L., Boitani, L., Faller, J.C., Briones,
M.A., Nunez, R., Rosas-Rosas, O., Ceballos, G., Falcucci, A., 2011. Predicting potential
distribution of the jaguar (Panthera onca) in Mexico: identification of priority areas for
conservation. Diversity and Distributions 17:350-361.
Remote sensing and geoprocessing applied to biodiversity:
Nagendra, H., gadgil, M. 1999. Biodiversity assessment at multiple scales: Linking
remotely sensed data with field information. Proc. Natl. Acad. Sci. (PNAS) 96:9154-9158.
Wiens, J., Sutter, R., Anderson, M., Blanchard, J., Barnett, A., Aguilar-Amuchastegui, N.,
Avery, C., Laine, S. 2009. Selecting and conserving lands for biodiversity: The role of
remote sensing. Remote Sensing of Enviroment.
Landscape Ecology:
Metzger, J.P. 2001. O que é ecologia de paisagens? Biota Neotropica 1(12).
Metzger, J.P. 2006. How to deal with non-obvious rules for biodiversity conservation in
fragmented landscapes? Natureza & Conservação 4(2):11-23.
Boscolo, D., Candia-Gallardo, C., Awade, M., Metzger, J.P. 2008. Importance of
Interhabitat Gaps and Stepping-Stones for Lesser Woodcreepers (Xiphorhynchus
fuscus) in the Atlantic Forest, Brazil. Biotropica 40(3):273-276.
Fahrig, L., 2003. Effects of habitat fragmentation on biodiversity. Annual Review of
Ecology, Evolution and Systematics 34:487-515.
Martensen, A.C., Pimentel, R.G., Metzger, J.P. 2008. Relative effects of fragment size
and connectivity on bird community in the Atlantic Rain Forest: Implications for
conservation. Biological Conservation 2184-2192.
Muchailh, M.C., Roderjan, C.V., Campos, J.B., Machado, A.L.T., Curcio, G.R. 2010.
Metodologia de planejamento de paisagens fragmentadas visando a formação de
corredores ecológicos. Floresta 40(1):147-162.
Ribeiro, M.C., Metzger, J.P., Marensen, A.C., Ponzoni, F., Hirota, M. 2009. Brazilian
Atlantic forest: how much is left, and how is the remaining forest distributed? Implications
for conservation. Biological Conservation 142:1141-1153.
Turner, M. G., Gardner, R.H., O’ Neill, R.V. 2001. Landscape ecology in theory and
practice- pattern and process. Springer, USA. 401pp.