The ability of climate envelope models to predict the effect of climate change on species distributions

By Robert J. Hijmans, Catherine H. Graham. 2006

694 citations recorded by the source corpus.

Subfields: Ecological Modeling, Ecology, Evolution, Behavior and Systematics, Nature and Landscape Conservation

View Paper: https://www.semanticscholar.org/paper/0b6ddb5eb148f09f9e26eba8a1bfff4a9e652894

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In Ecological Modeling

In Ecology, Evolution, Behavior and Systematics

In Nature and Landscape Conservation

Citations in the corpus

Paintings predict the distribution of species, or the challenge of selecting environmental predictors and evaluation statistics (2018, background): “When models are projected in space and time, they can predict range shifts under climate change (Hijmans & Graham, 2006) or estimate the potential expansion of invasive species (Jim enez-Valverde, Peterson et al., 2011).”
Adapting to climate change: a perspective from evolutionary physiology (2010, background): “…be modelled and how additional biological mechanisms might be incorporated to improve their utility (e.g. Pearson & Dawson 2003, Elith et al. 2006, Hijmans & Graham 2006, Brooker et al. 2007, Soberón 2007, Sutherst et al. 2007, Beale et al. 2008, Jeschke & Strayer 2008, Keith et al. 2008, Elith…”
How Useful Are Species Distribution Models for Managing Biodiversity under Future Climates (2010, methodology): “Performance is generally assessed using a test or validation data set (Elith et al. 2006, Hijmans and Graham 2006).”
Traits to stay, traits to move: a review of functional traits to assess sensitivity and adaptive capacity of temperate and boreal trees to climate change (2016, background): “However, there are concerns as to whether bioclimatic envelopemodels can adequately reflect actual changes in distributions (Pearson and Dawson 2003; Hampe 2004; Hijmans and Graham 2006).”
Extinction risk of North American seed plants elevated by climate and land‐use change (2017, background): “In other words, they may not give the exact answer for a specific time period (i.e. 2080 horizon), but the projected trends are likely to be realistic in the long term (Hijmans & Graham 2006; Kearney, Wintle & Por- ter 2010).”
Effects of Climate Change on Invasive Species (2021, methodology): “…based on species relationships to landscape characteristics (Elith and Leathwick 2009), and they have been used successfully to predict species invasions (Fernández and Hamilton 2015; Peterson 2003) and species range shifts under climate change (Hijmans and Graham 2006; Pearson and Dawson 2003).”
Modelling climate-change-induced shifts in the distribution of the koala (2011, background): “Maxent is a species distribution modelling approach that has been found to perform well under both current climates and future predictions (Hijmans and Graham 2006).”
Using species distribution models to predict new occurrences for rare plants (2009, neutral): “Second, SDMs model realized, not fundamental, niches (Malanson et al., 1992; Hijmans & Graham, 2006) incorporating whatever sampling bias is inherent in the data (Wisz et al., 2008).”
Climate change vulnerability assessment of species (2018, background): “Shortcomings of correlative CCVAs have been widely discussed (e.g., Pearson & Dawson, 2003; Hijmans & Graham, 2006; Hannah et al., 2007; Araújo & Peterson, 2012; Pacifici et al., 2015); their assumption that species' distributions are in equilibrium with the prevailing climate can prove problematic…”
Modeling Impacts of Climate Change on Giant Panda Habitat (2012, background): “Though climate envelope models are widely used in climate change research to predict future species distributions [26, 27], there are limitations.”