Jane Elith

Research interests

Publications

• A standard protocol for reporting species distribution models

  Ecography · 2020 · https://doi.org/10.1111/ecog.04960

• A comprehensive evaluation of predictive performance of 33 species distribution models at species and community levels

  Ecological Monographs · 2019 · https://doi.org/10.1002/ecm.1370

• Outstanding Challenges in the Transferability of Ecological Models

  Trends in Ecology & Evolution · 2018 · 10.1016/j.tree.2018.08.001

• Building essential biodiversity variables ( EBV s) of species distribution and abundance at a global scale

  Biological reviews/Biological reviews of the Cambridge Philosophical Society · 2017 · https://doi.org/10.1111/brv.12359

• What do we gain from simplicity versus complexity in species distribution models?

  Ecography · 2014 · https://doi.org/10.1111/ecog.00845

• Predicting species distributions for conservation decisions

  Ecology Letters · 2013 · https://doi.org/10.1111/ele.12189

• Collinearity: a review of methods to deal with it and a simulation study evaluating their performance

  Ecography · 2012 · https://doi.org/10.1111/j.1600-0587.2012.07348.x

• Boosted Regression Trees for ecological modeling

  Zenodo (CERN European Organization for Nuclear Research) · 2011 · https://doi.org/10.5281/zenodo.19669586

• A statistical explanation of MaxEnt for ecologists

  Diversity and Distributions · 2010 · https://doi.org/10.1111/j.1472-4642.2010.00725.x

• Use of generalised dissimilarity modelling to improve the biological discrimination of river and stream classifications

  Freshwater Biology · 2010 · https://doi.org/10.1111/j.1365-2427.2010.02414.x

• The Contribution of Species Distribution Modelling to Conservation Prioritization

  Journal · 2009 · https://doi.org/10.1093/oso/9780199547760.003.0006

• Species Distribution Models: Ecological Explanation and Prediction Across Space and Time

  Annual Review of Ecology Evolution and Systematics · 2009 · https://doi.org/10.1146/annurev.ecolsys.110308.120159

• Sample selection bias and presence‐only distribution models: implications for background and pseudo‐absence data

  Ecological Applications · 2009 · https://doi.org/10.1890/07-2153.1

• A working guide to boosted regression trees

  Journal of Animal Ecology · 2008 · https://doi.org/10.1111/j.1365-2656.2008.01390.x

• Dispersal, disturbance and the contrasting biogeographies of New Zealand’s diadromous and non‐diadromous fish species

  Journal of Biogeography · 2008 · https://doi.org/10.1111/j.1365-2699.2008.01887.x

• Presence‐Only Data and the EM Algorithm

  Biometrics · 2008 · https://doi.org/10.1111/j.1541-0420.2008.01116.x

• Novel methods for the design and evaluation of marine protected areas in offshore waters

  Conservation Letters · 2008 · https://doi.org/10.1111/j.1755-263x.2008.00012.x

• WHAT MATTERS FOR PREDICTING THE OCCURRENCES OF TREES: TECHNIQUES, DATA, OR SPECIES' CHARACTERISTICS?

  Ecological Monographs · 2007 · https://doi.org/10.1890/06-1060.1

• Predicting species distributions from museum and herbarium records using multiresponse models fitted with multivariate adaptive regression splines

  Diversity and Distributions · 2007 · https://doi.org/10.1111/j.1472-4642.2007.00340.x

• A method for spatial freshwater conservation prioritization

  Freshwater Biology · 2007 · https://doi.org/10.1111/j.1365-2427.2007.01906.x

• Sensitivity of predictive species distribution models to change in grain size

  Diversity and Distributions · 2007 · https://doi.org/10.1111/j.1472-4642.2007.00342.x

• The influence of spatial errors in species occurrence data used in distribution models

  Journal of Applied Ecology · 2007 · https://doi.org/10.1111/j.1365-2664.2007.01408.x

• Comparative performance of generalized additive models and multivariate adaptive regression splines for statistical modelling of species distributions

  Ecological Modelling · 2006 · https://doi.org/10.1016/j.ecolmodel.2006.05.022

• Novel methods improve prediction of species’ distributions from occurrence data

  Ecography · 2006 · https://doi.org/10.1111/j.2006.0906-7590.04596.x

• The evaluation strip: A new and robust method for plotting predicted responses from species distribution models

  Ecological Modelling · 2005 · https://doi.org/10.1016/j.ecolmodel.2004.12.007

• Using multivariate adaptive regression splines to predict the distributions of New Zealand's freshwater diadromous fish

  Freshwater Biology · 2005 · https://doi.org/10.1111/j.1365-2427.2005.01448.x

Current projects

No projects listed.