Jane Elith

70.5k total citations · 16 hit papers
89 papers, 42.0k citations indexed

About

Jane Elith is a scholar working on Ecological Modeling, Nature and Landscape Conservation and Ecology. According to data from OpenAlex, Jane Elith has authored 89 papers receiving a total of 42.0k indexed citations (citations by other indexed papers that have themselves been cited), including 66 papers in Ecological Modeling, 64 papers in Nature and Landscape Conservation and 49 papers in Ecology. Recurrent topics in Jane Elith's work include Species Distribution and Climate Change (66 papers), Ecology and Vegetation Dynamics Studies (52 papers) and Wildlife Ecology and Conservation (39 papers). Jane Elith is often cited by papers focused on Species Distribution and Climate Change (66 papers), Ecology and Vegetation Dynamics Studies (52 papers) and Wildlife Ecology and Conservation (39 papers). Jane Elith collaborates with scholars based in Australia, United States and New Zealand. Jane Elith's co-authors include John R. Leathwick, Trevor Hastie, Steven J. Phillips, Miroslav Dudı́k, Catherine H. Graham, Colin J. Yates, Yung En Chee, Steven Phillips, Michael Kearney and José J. Lahoz‐Monfort and has published in prestigious journals such as Ecology, Remote Sensing of Environment and Biometrics.

In The Last Decade

Jane Elith

87 papers receiving 40.8k citations

Hit Papers

Collinearity: a review of methods to deal with it and a s... 2007 2026 2013 2019 2012 2009 2010 2008 2009 2.0k 4.0k 6.0k
What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

  1. Collinearity: a review of methods to deal with it and a simulation study evaluating their performance
    2012 7.5k citations Jane Elith, Boris Schröder et al. Ecography profile →
  2. Species Distribution Models: Ecological Explanation and Prediction Across Space and Time
    2009 5.2k citations Jane Elith, John R. Leathwick profile →
  3. A statistical explanation of MaxEnt for ecologists
    2010 5.0k citations Jane Elith, Steven J. Phillips et al. Diversity and Distributions profile →
  4. A working guide to boosted regression trees
    2008 5.0k citations Jane Elith, John R. Leathwick et al. Journal of Animal Ecology profile →
  5. Sample selection bias and presence‐only distribution models: implications for background and pseudo‐absence data
    2009 2.2k citations Steven J. Phillips, Miroslav Dudı́k et al. profile →
  6. The art of modelling range-shifting species
    2010 2.2k citations Jane Elith, Michael Kearney et al. Methods in Ecology and Evolution profile →
  7. Cross‐validation strategies for data with temporal, spatial, hierarchical, or phylogenetic structure
    2016 1.3k citations Jane Elith, Gurutzeta Guillera‐Arroita et al. Ecography profile →
  8. Do they? How do they? WHY do they differ? On finding reasons for differing performances of species distribution models
    2009 900 citations Jane Elith et al. Ecography profile →
  9. Using generalized dissimilarity modelling to analyse and predict patterns of beta diversity in regional biodiversity assessment
    2007 774 citations Simon Ferrier, Glenn Manion et al. Diversity and Distributions profile →
  10. Is my species distribution model fit for purpose? Matching data and models to applications
    2015 713 citations Gurutzeta Guillera‐Arroita, José J. Lahoz‐Monfort et al. Global Ecology and Biogeography profile →
  11. What do we gain from simplicity versus complexity in species distribution models?
    2014 442 citations Sean M. McMahon, Jane Elith et al. Ecography profile →
  12. Predictive performance of presence‐only species distribution models: a benchmark study with reproducible code
    2021 427 citations Roozbeh Valavi, Gurutzeta Guillera‐Arroita et al. profile →
  13. A review of evidence about use and performance of species distribution modelling ensembles like BIOMOD
    2019 420 citations Tianxiao Hao, Jane Elith et al. Diversity and Distributions profile →
  14. block CV : An r package for generating spatially or environmentally separated folds for k ‐fold cross‐validation of species distribution models
    2018 412 citations Roozbeh Valavi, Jane Elith et al. Methods in Ecology and Evolution profile →
  15. Testing whether ensemble modelling is advantageous for maximising predictive performance of species distribution models
    2020 296 citations Tianxiao Hao, Jane Elith et al. Ecography profile →
  16. Point process models for presence‐only analysis
    2015 290 citations Jane Elith, William Fithian et al. Methods in Ecology and Evolution profile →

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Jane Elith Australia 58 22.3k 21.1k 15.1k 9.5k 6.8k 89 42.0k
Niklaus E. Zimmermann Switzerland 83 16.9k 0.8× 14.2k 0.7× 16.0k 1.1× 11.9k 1.3× 8.0k 1.2× 273 37.9k
Miguel B. Araújo Spain 90 29.9k 1.3× 22.4k 1.1× 22.3k 1.5× 10.8k 1.1× 11.8k 1.7× 238 46.7k
Antoine Guisan Switzerland 86 31.4k 1.4× 23.8k 1.1× 23.9k 1.6× 9.6k 1.0× 12.5k 1.8× 334 49.4k
Camille Parmesan United States 41 14.9k 0.7× 16.8k 0.8× 12.0k 0.8× 13.0k 1.4× 10.9k 1.6× 77 38.4k
Georgina M. Mace United Kingdom 85 9.4k 0.4× 16.7k 0.8× 12.4k 0.8× 13.2k 1.4× 7.6k 1.1× 186 42.3k
Walter Jetz United States 84 13.3k 0.6× 16.9k 0.8× 13.2k 0.9× 7.7k 0.8× 9.6k 1.4× 201 33.0k
Hugh P. Possingham Australia 123 13.3k 0.6× 30.5k 1.4× 17.1k 1.1× 23.1k 2.4× 4.9k 0.7× 749 54.8k
Jens‐Christian Svenning Denmark 92 10.6k 0.5× 11.6k 0.5× 15.1k 1.0× 7.7k 0.8× 9.6k 1.4× 574 32.5k
A. Townsend Peterson United States 101 33.6k 1.5× 24.1k 1.1× 19.6k 1.3× 8.8k 0.9× 13.5k 2.0× 611 58.0k
Robert J. Hijmans United States 51 15.6k 0.7× 13.1k 0.6× 11.2k 0.7× 8.0k 0.8× 10.1k 1.5× 136 39.3k

Countries citing papers authored by Jane Elith

Since Specialization
Citations

This map shows the geographic impact of Jane Elith's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Jane Elith with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jane Elith more than expected).

Fields of papers citing papers by Jane Elith

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Jane Elith. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Jane Elith. The network helps show where Jane Elith may publish in the future.

Co-authorship network of co-authors of Jane Elith

This figure shows the co-authorship network connecting the top 25 collaborators of Jane Elith. A scholar is included among the top collaborators of Jane Elith based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Jane Elith. Jane Elith is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Davies, Hugh F., Margaret Ayre, Brett A. Bryan, et al.. (2025). Applying the IUCN Global Ecosystem Typology to classify, describe, and map ecosystems based on regional data and Indigenous knowledge. Conservation Biology. 39(6). e70099–e70099.
2.
Valavi, Roozbeh, Jane Elith, José J. Lahoz‐Monfort, & Gurutzeta Guillera‐Arroita. (2023). Flexible species distribution modelling methods perform well on spatially separated testing data. Global Ecology and Biogeography. 32(3). 369–383. 38 indexed citations
3.
Hao, Tianxiao, Jane Elith, José J. Lahoz‐Monfort, & Gurutzeta Guillera‐Arroita. (2020). Testing whether ensemble modelling is advantageous for maximising predictive performance of species distribution models. Ecography. 43(4). 549–558. 296 indexed citations breakdown →
4.
Briscoe, Natalie J., Jane Elith, Roberto Salguero‐Gómez, et al.. (2019). Forecasting species range dynamics with process‐explicit models: matching methods to applications. Ecology Letters. 22(11). 1940–1956. 160 indexed citations
5.
Valavi, Roozbeh, Jane Elith, José J. Lahoz‐Monfort, & Gurutzeta Guillera‐Arroita. (2018). block CV : An r package for generating spatially or environmentally separated folds for k ‐fold cross‐validation of species distribution models. Methods in Ecology and Evolution. 10(2). 225–232. 412 indexed citations breakdown →
6.
Snäll, Tord, Joona Lehtomäki, Anni Arponen, Jane Elith, & Atte Moilanen. (2015). Green Infrastructure Design Based on Spatial Conservation Prioritization and Modeling of Biodiversity Features and Ecosystem Services. Environmental Management. 57(2). 251–256. 83 indexed citations
7.
Fithian, William, Jane Elith, Trevor Hastie, & David A. Keith. (2014). A Proportional Observer Bias Model for Multispecies Distribution Modeling. arXiv (Cornell University). 2 indexed citations
8.
Burgman, Mark A., Michael A. McCarthy, Andrew P. Robinson, et al.. (2013). Improving decisions for invasive species management: reformulation and extensions of the Panetta–Lawes eradication graph. Diversity and Distributions. 19(5-6). 603–607. 13 indexed citations
9.
Phillips, Steven J. & Jane Elith. (2013). On estimating probability of presence from use–availability or presence–background data. Ecology. 94(6). 1409–1419. 128 indexed citations
10.
Zurell, Damaris, Jane Elith, & Boris Schröder. (2012). Predicting to new environments: tools for visualizing model behaviour and impacts on mapped distributions. Diversity and Distributions. 18(6). 628–634. 120 indexed citations
11.
Morán‐Ordóñez, Alejandra, Susana Suárez‐Seoane, Jane Elith, Leonor Calvo, & Estanislao de Luis. (2011). Satellite surface reflectance improves habitat distribution mapping: a case study on heath and shrub formations in the Cantabrian Mountains (NW Spain). Diversity and Distributions. 18(6). 588–602. 43 indexed citations
12.
Elith, Jane, Steven J. Phillips, Trevor Hastie, et al.. (2010). A statistical explanation of MaxEnt for ecologists. Diversity and Distributions. 17(1). 43–57. 5041 indexed citations breakdown →
13.
Leathwick, John R., et al.. (2009). Robust planning for restoring diadromous fish species in New Zealand's lowland rivers and streams. New Zealand Journal of Marine and Freshwater Research. 43(3). 659–671. 11 indexed citations
14.
Yates, Colin J., et al.. (2009). Assessing the impacts of climate change and land transformation on Banksia in the South West Australian Floristic Region. Diversity and Distributions. 16(1). 187–201. 103 indexed citations
15.
Leathwick, John R., Atte Moilanen, Malcolm P. Francis, et al.. (2008). Novel methods for the design and evaluation of marine protected areas in offshore waters. Conservation Letters. 1(2). 91–102. 157 indexed citations
16.
Ward, Gillian, Trevor Hastie, Simon C. Barry, Jane Elith, & John R. Leathwick. (2008). Presence‐Only Data and the EM Algorithm. Biometrics. 65(2). 554–563. 207 indexed citations
17.
Elith, Jane, John R. Leathwick, & Trevor Hastie. (2008). A working guide to boosted regression trees. Journal of Animal Ecology. 77(4). 802–813. 4964 indexed citations breakdown →
18.
Ferrier, Simon, Glenn Manion, Jane Elith, & Karen Richardson. (2007). Using generalized dissimilarity modelling to analyse and predict patterns of beta diversity in regional biodiversity assessment. Diversity and Distributions. 13(3). 252–264. 774 indexed citations breakdown →
19.
Elith, Jane & John R. Leathwick. (2007). Predicting species distributions from museum and herbarium records using multiresponse models fitted with multivariate adaptive regression splines. Diversity and Distributions. 13(3). 265–275. 265 indexed citations
20.
Potts, Joanne & Jane Elith. (2006). Comparing species abundance models. Ecological Modelling. 199(2). 153–163. 291 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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