Species Distribution Modeling

[1]  T. Hastie,et al.  Bias correction in species distribution models: pooling survey and collection data for multiple species , 2014, Methods in ecology and evolution.

[2]  Jane Elith,et al.  What do we gain from simplicity versus complexity in species distribution models , 2014 .

[3]  Michael R Kearney,et al.  Realized niche shift during a global biological invasion , 2014, Proceedings of the National Academy of Sciences.

[4]  M. Kearney,et al.  microclim: Global estimates of hourly microclimate based on long-term monthly climate averages , 2014, Scientific Data.

[5]  Laura J. Pollock,et al.  Understanding co‐occurrence by modelling species simultaneously with a Joint Species Distribution Model (JSDM) , 2014 .

[6]  David I. Warton,et al.  Model-Based Control of Observer Bias for the Analysis of Presence-Only Data in Ecology , 2013, PloS one.

[7]  Tatsuya Amano,et al.  Four barriers to the global understanding of biodiversity conservation: wealth, language, geographical location and security , 2013, Proceedings of the Royal Society B: Biological Sciences.

[8]  Damaris Zurell,et al.  Collinearity: a review of methods to deal with it and a simulation study evaluating their performance , 2013 .

[9]  José J. Lahoz‐Monfort,et al.  Designing studies to detect differences in species occupancy: power analysis under imperfect detection , 2012 .

[10]  Charles Troupin,et al.  Bio‐ORACLE: a global environmental dataset for marine species distribution modelling , 2012 .

[11]  Robert P. Anderson,et al.  Ecological Niches and Geographic Distributions , 2011 .

[12]  Andrew K. Skidmore,et al.  Finessing atlas data for species distribution models , 2011 .

[13]  Thomas G. Dietterich,et al.  Incorporating Boosted Regression Trees into Ecological Latent Variable Models , 2011, AAAI.

[14]  M. Gregory,et al.  Mapping gradients of community composition with nearest-neighbour imputation: extending plot data for landscape analysis , 2011 .

[15]  A. Prasad,et al.  Lessons Learned While Integrating Habitat, Dispersal, Disturbance, and Life-History Traits into Species Habitat Models Under Climate Change , 2011, Ecosystems.

[16]  A. Peterson.  Ecological niche conservatism: a time‐structured review of evidence , 2011 .

[17]  S. Dobrowski,et al.  Modeling plant ranges over 75 years of climate change in California, USA: temporal transferability and species traits , 2011 .

[18]  Janet Franklin,et al.  Geospatial tools address emerging issues in spatial ecology: a review and commentary on the Special Issue , 2011, Int. J. Geogr. Inf. Sci..

[19]  Niklaus E. Zimmermann,et al.  Co‐occurrence patterns of trees along macro‐climatic gradients and their potential influence on the present and future distribution of Fagus sylvatica L. , 2011 .

[20]  M. Austin,et al.  Improving species distribution models for climate change studies: variable selection and scale , 2011 .

[21]  Jane Elith,et al.  Use of generalised dissimilarity modelling to improve the biological discrimination of river and stream classifications , 2011 .

[22]  Wilfried Thuiller,et al.  Sampling in ecology and evolution – bridging the gap between theory and practice , 2010 .

[23]  D. Fink,et al.  Spatiotemporal exploratory models for broad-scale survey data. , 2010, Ecological applications : a publication of the Ecological Society of America.

[24]  C. Cox.  Underpinning global biogeographical schemes with quantitative data , 2010 .

[25]  Walter Jetz,et al.  A framework for delineating biogeographical regions based on species distributions , 2010 .

[26]  M. Kéry,et al.  Predicting species distributions from checklist data using site‐occupancy models , 2010 .

[27]  Otso Ovaskainen,et al.  Modeling species co-occurrence by multivariate logistic regression generates new hypotheses on fungal interactions. , 2010, Ecology.

[28]  Gary Gereffi,et al.  Sustainable Product Indexing: Navigating the Challenge of Ecolabeling , 2010 .

[29]  M. White,et al.  How Useful Are Species Distribution Models for Managing Biodiversity under Future Climates , 2010 .

[30]  Jennifer A. Miller,et al.  Mapping Species Distributions: Spatial Inference and Prediction , 2010 .

[31]  Tim Newbold,et al.  Applications and limitations of museum data for conservation and ecology, with particular attention to species distribution models , 2010 .

[32]  R. Pearson.  Species’ Distribution Modeling for Conservation Educators and Practitioners , 2010 .

[33]  Robert K. Colwell,et al.  Hutchinson's duality: The once and future niche , 2009, Proceedings of the National Academy of Sciences.

[34]  J. Elith,et al.  Species Distribution Models: Ecological Explanation and Prediction Across Space and Time , 2009 .

[35]  Steven J. Phillips,et al.  Sample selection bias and presence-only distribution models: implications for background and pseudo-absence data. , 2009, Ecological applications : a publication of the Ecological Society of America.

[36]  Brendan A. Wintle,et al.  When have we looked hard enough? A novel method for setting minimum survey effort protocols for flora surveys , 2008 .

[37]  R. Norris,et al.  Irreplaceability of river networks: towards catchment-based conservation planning , 2008 .

[38]  C. Graham,et al.  Integrating GIS-based environmental data into evolutionary biology. , 2008, Trends in ecology & evolution.

[39]  Bernie J. McConnell,et al.  Estimating space‐use and habitat preference from wildlife telemetry data , 2008 .

[40]  R. G. Davies,et al.  Methods to account for spatial autocorrelation in the analysis of species distributional data : a review , 2007 .

[41]  D. M. Leslie,et al.  Testing a Mahalanobis Distance Model of Black Bear Habitat Use in the Ouachita Mountains of Oklahoma , 2007 .

[42]  Thiago F. Rangel,et al.  Towards an integrated computational tool for spatial analysis in macroecology and biogeography , 2006 .

[43]  Antoine Guisan,et al.  Spatial modelling of biodiversity at the community level , 2006 .

[44]  Mark S. Boyce,et al.  Modelling distribution and abundance with presence‐only data , 2006 .

[45]  Darryl I. MacKenzie,et al.  Designing occupancy studies: general advice and allocating survey effort , 2005 .

[46]  J. L. Parra,et al.  Very high resolution interpolated climate surfaces for global land areas , 2005 .

[47]  B. L. Baker,et al.  Regional vegetation mapping in Australia: a case study in the practical use of statistical modelling , 2002, Biodiversity & Conservation.

[48]  J. Pausas,et al.  Coarse-scale plant species richness in relation to environmental heterogeneity , 2003 .

[49]  T. Dawson,et al.  Predicting the impacts of climate change on the distribution of species: are bioclimate envelope models useful? , 2003 .

[50]  M. Austin.  Spatial prediction of species distribution: an interface between ecological theory and statistical modelling , 2002 .

[51]  Robert Tibshirani,et al.  The Elements of Statistical Learning: Data Mining, Inference, and Prediction, 2nd Edition , 2001, Springer Series in Statistics.

[52]  J. Leathwick,et al.  COMPETITIVE INTERACTIONS BETWEEN TREE SPECIES IN NEW ZEALAND'S OLD‐GROWTH INDIGENOUS FORESTS , 2001 .

[53]  D. Lindenmayer,et al.  Towards a hierarchical framework for modelling the spatial distribution of animals , 2001 .

[54]  Antoine Guisan,et al.  Predictive habitat distribution models in ecology , 2000 .

[55]  Michael F. Goodchild,et al.  Integrating GIS and remote sensing for vegetation analysis and modeling: methodological issues , 1994 .

[56]  P. Legendre.  Spatial Autocorrelation: Trouble or New Paradigm? , 1993 .

[57]  D. Currie.  Energy and Large-Scale Patterns of Animal- and Plant-Species Richness , 1991, The American Naturalist.

[58]  J. Busby.  BIOCLIM - a bioclimate analysis and prediction system , 1991 .

[59]  Simon A. Levin,et al.  Niche, Habitat, and Ecotope , 1973, The American Naturalist.

[60]  L. Holdridge.  Determination of World Plant Formations From Simple Climatic Data. , 1947, Science.