Jane Elith
Impact in
- Ecological Modeling top 0.01%
- Species Distribution and Climate Change
- Nature and Landscape Conservation top 0.01%
- Ecology and Vegetation Dynamics Studies
- Fish Ecology and Management Studies
Papers in
-
- Species Distribution and Climate Change 78
-
- Ecology and Vegetation Dynamics Studies 60
- Fish Ecology and Management Studies 11
- Co-authors
- John R. Leathwick (15 shared papers)Trevor Hastie (10 shared papers)Steven J. Phillips (5 shared papers)Miroslav Dudı́k (2 shared papers)Catherine Helen Graham (6 shared papers)Colin J. Yates (4 shared papers)Yung En Chee (2 shared papers)Steven D. Phillips (4 shared papers)
- Journals
- Diversity and Distributions (13 papers)Ecography (10 papers)Methods in Ecology and Evolution (6 papers)Ecological Modelling (6 papers)Conservation Biology (4 papers)
- Partner nations
- AustraliaUnited StatesNew Zealand
In The Last Decade
Jane Elith
100 papers receiving 55.8k citations
Jane Elith's Hit Papers
Peers
Comparison fields: 5 of 224
- Ecological Modeling 31.9k
- Nature and Landscape Conservation 20.2k
- Ecology 28.3k
- Global and Planetary Change 12.2k
- Ecology, Evolution, Behavior and Systematics 9.3k
Countries citing papers authored by Jane Elith
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
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-authors
The 25 scholars most cited alongside Jane Elith, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 101 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | Collinearity: a review of methods to deal with it and a simulation study evaluating their performance Hit paper breakdown → | 2012 | 8156 |
| 2 | Novel methods improve prediction of species’ distributions from occurrence data Hit paper breakdown → | 2006 | 7584 |
| 3 | Species Distribution Models: Ecological Explanation and Prediction Across Space and Time Hit paper breakdown → | 2009 | 5636 |
| 4 | A statistical explanation of MaxEnt for ecologists Hit paper breakdown → | 2010 | 5409 |
| 5 | A working guide to boosted regression trees Hit paper breakdown → | 2008 | 5293 |
| 6 | Sample selection bias and presence‐only distribution models: implications for background and pseudo‐absence data Hit paper breakdown → | 2009 | 2403 |
| 7 | The art of modelling range-shifting species Hit paper breakdown → | 2010 | 2344 |
| 8 | Cross‐validation strategies for data with temporal, spatial, hierarchical, or phylogenetic structure Hit paper breakdown → | 2016 | 1629 |
| 9 | Predicting species distributions for conservation decisions Hit paper breakdown → | 2013 | 1608 |
| 10 | Do they? How do they? WHY do they differ? On finding reasons for differing performances of species distribution models Hit paper breakdown → | 2009 | 928 |
| 11 | Using generalized dissimilarity modelling to analyse and predict patterns of beta diversity in regional biodiversity assessment Hit paper breakdown → | 2007 | 853 |
| 12 | Is my species distribution model fit for purpose? Matching data and models to applications Hit paper breakdown → | 2015 | 772 |
| 13 | A standard protocol for reporting species distribution models Hit paper breakdown → | 2020 | 676 |
| 14 | Outstanding Challenges in the Transferability of Ecological Models Hit paper breakdown → | 2018 | 548 |
| 15 | Predictive performance of presence‐only species distribution models: a benchmark study with reproducible code Hit paper breakdown → | 2021 | 524 |
| 16 | What do we gain from simplicity versus complexity in species distribution models? Hit paper breakdown → | 2014 | 509 |
| 17 | 2006 | 507 | |
| 18 | 2006 | 501 | |
| 19 | block CV : An r package for generating spatially or environmentally separated folds for k ‐fold cross‐validation of species distribution models Hit paper breakdown → | 2018 | 493 |
| 20 | A review of evidence about use and performance of species distribution modelling ensembles like BIOMOD Hit paper breakdown → | 2019 | 482 |
About Jane Elith
Jane Elith is a scholar working on Ecological Modeling, Nature and Landscape Conservation, Ecology, Global and Planetary Change and Ecology, Evolution, Behavior and Systematics, having authored 101 papers that have together received 57.6k indexed citations. Recurring topics across this work include Species Distribution and Climate Change (78 papers), Ecology and Vegetation Dynamics Studies (60 papers), Wildlife Ecology and Conservation (45 papers), Fish Ecology and Management Studies (11 papers), Plant and animal studies (7 papers), Genetic diversity and population structure (7 papers), Data Analysis with R (6 papers) and Land Use and Ecosystem Services (6 papers). The work is most often cited by research in Ecological Modeling (31.9k citations), Nature and Landscape Conservation (20.2k citations), Ecology (28.3k citations), Global and Planetary Change (12.2k citations) and Ecology, Evolution, Behavior and Systematics (9.3k citations). Jane Elith has collaborated with scholars based in Australia, United States and New Zealand. Frequent co-authors include John R. Leathwick, Trevor Hastie, Steven J. Phillips, Miroslav Dudı́k, Catherine Helen Graham, Colin J. Yates, Yung En Chee, Steven D. Phillips, José Joaquín Lahoz‐Monfort and Michael Kearney. Their work appears in journals such as Diversity and Distributions, Ecography, Methods in Ecology and Evolution, Ecological Modelling and Conservation Biology.
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.