Cited by 2,813Species Distribution and Climate ChangeEcology and Vegetation Dynamics StudiesAnimal Ecology and Behavior Studies

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The art of modelling range-shifting species: The art of modelling range-shifting species

Elith, Jane, Kearney, Michael, Phillips, Steven·2010·Methods in Ecology and Evolution

DOI 10.1111/j.2041-210x.2010.00036.x

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Abstract

1. Species are shifting their ranges at an unprecedented rate through human transportation and environmental change. Correlative species distribution models (SDMs) are frequently applied for predicting potential future distributions of range-shifting species, despite these models’ assumptions that species are at equilibrium with the environments used to train (fit) the models, and that the training data are representative of conditions to which the models are predicted. Here we explore modelling approaches that aim to minimize extrapolation errors and assess predictions against prior biological knowledge. Our aim was to promote methods appropriate to range-shifting species. 2. We use an invasive species, the cane toad in Australia, as an example, predicting potential distributions under both current and climate change scenarios. We use four SDM methods, and trial weighting schemes and choice of background samples appropriate for species in a state of spread. We also test two methods for including information from a mechanistic model. Throughout, we explore graphical techniques for understanding model behaviour and reliability, including the extent of extrapolation. 3. Predictions varied with modelling method and data treatment, particularly with regard to the use and treatment of absence data. Models that performed similarly under current climatic conditions deviated widely when transferred to a novel climatic scenario. 4. The results highlight problems with using SDMs for extrapolation, and demonstrate the need for methods and tools to understand models and predictions. We have made progress in this direction and have implemented exploratory techniques as new options in the free modelling software, MaxEnt. Our results also show that deliberately controlling the fit of models and integrating information from mechanistic models can enhance the reliability of correlative predictions of species in non-equilibrium and novel settings. 5. Implications. The biodiversity of many regions in the world is experiencing novel threats created by species invasions and climate change. Predictions of future species distributions are required for management, but there are acknowledged problems with many current methods, and relatively few advances in techniques for understanding or overcoming these. The methods presented in this manuscript and made accessible in MaxEnt provide a forward step.

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Authors: Elith, J., Kearney, M., & Phillips, S.
Affiliations: The University of Melbourne (AU)
AT&T (United States) (US)
Corresponding author: Elith, Jane
ORCID: Elith, Jane
Kearney, Michael
Venue: Methods in Ecology and Evolution
Publisher: Wiley
Published: 2010-05-24
Volume: 1
Issue: 4
Pages: 330-342
ISSN: 2041-210X (ISSN-L)
DOI: 10.1111/j.2041-210x.2010.00036.x
OpenAlex: W2100533358
Semantic Scholar: 57fbdc5ff136d10620ea5204db024583249f9550
Cited by: 2,813
References: 79
Citations by year: 2026: 190 · 2025: 230 · 2024: 252 · 2023: 251 · 2022: 240 · 2021: 219 · 2020: 199 · 2019: 184 · 2018: 163 · 2017: 179 · 2016: 152 · 2015: 128 · 2014: 159 · 2013: 107 · 2012: 100
FWCI: 50.92
Type: journal article
Language: en
Open access: closed
Licence: doi.wiley.com/10.1002/tdm_license_1.1 (tdm)
onlinelibrary.wiley.com/termsAndConditions#vor (vor)
Locations: Methods in Ecology and Evolution (publishedVersion)
Topics: Physical Sciences › Environmental Science › Ecological Modeling › Species Distribution and Climate Change
Physical Sciences › Environmental Science › Nature and Landscape Conservation › Ecology and Vegetation Dynamics Studies
Physical Sciences › Environmental Science › Ecology › Animal Ecology and Behavior Studies
Keywords: species distribution modeling, extrapolation error, Rhinella marina, invasive species, climate change scenarios, absence data, MaxEnt, model reliability, species spread

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The art of modelling range-shifting species: The art of modelling range-shifting species

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