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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“…toxic species) and their evolution through abiotic and sometimes biotic factors is an important and useful goal to forecast the evolution of communities (Wiens et al., 2009; Elith et al., 2010; Kearney et al., 2010) but it requires a detailed understanding of the mechanisms driving their fitness.”
Background
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“If a change results in the highest probability of occurrence, the variable changed is then viewed as a limiting factor (see Elith et al., 2010 and Hill et al., 2012, as well as supporting information for more © 2017 The Royal Entomological Society, Medical and Veterinary Entomology, 32,…”
Background
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Uncertainty in consensus predictions of plant species' vulnerability to climate change
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Current evidence of climate‐driven colour change in insects and its impact on sexual signals
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“The expression of insect colours in terms of quantity and quality can be impacted by environmental factors including temperature, rainfall, and solar radiation (Cott, 1940; Elith et al., 2010).”
Background
Predicted effects of climate change on potential sources of non‐indigenous marine species
Floerl, O., Rickard, G. J., Inglis, G. J., & Roulston, H. (2013) · Diversity and Distributions · doi:10.1111/ddi.12048 · Cited by 25
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“Instead, we ask whether the ability of ENMs to detect this barrier using readily available and typically useful environmental variables (i.e., WorldClim bioclimatic layers) is affected by the presence of PSM localities.”
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“…species to two (from a default setting of 1), as doing so alleviates overfitting when sample sizes are small and greatly increases model performance and model transferability to future climates (Dudík et al., 2007; Elith et al., 2010; Anderson and Gonzalez, 2011; Radosavljevic and Anderson, 2014).”
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“…(the variable that is furthest outside its training range; Elith et al. 2010) maps, the MaxEnt’s explain tool (exploring what drives a high or low prediction at any given site in geographic space; Elith et al. 2010), and response curves suggested that extrapolation might not be a critical issue.”
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“For details, see Elith et al. (2010).”
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“To minimize errors of temporal extrapolation from current to past niche models, we ran Multivariate Environmental Similarity Surface analyses (MESS) in dismo (Figure S2; Elith et al., 2010).”
Method
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Evaluating range‐expansion models for calculating nonnative species' expansion rate
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“There are a number of methods available for accounting for sample bias (see Fourcade et al. 2014), including the utilisation of target background points (Phillips et al. 2009) or bias grids (Elith et al. 2010).”
BackgroundMethodInfluential
Quantifying the stability of planktic foraminiferal physical niches between the Holocene and Last Glacial Maximum
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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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