Do they? How do they? WHY do they differ? On finding reasons for differing performances of species distribution models

By Jane Elith, Catherine H. Graham. 2009

1,125 citations recorded by the source corpus.

Subfields: Ecological Modeling, Genetics, Nature and Landscape Conservation

View Paper: https://www.semanticscholar.org/paper/7ec883491c51a8e14d2a3d20173014faeb7b2441

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Citations in the corpus

Does the interpolation accuracy of species distribution models come at the expense of transferability (2012, background): “(2007), Elith and Graham (2009), and Wiens et al.”
Biotic interactions influence the projected distribution of a specialist mammal under climate change (2012, result): “…different modelling algorithms can yield differing results (Munoz & Felicisimo, 2004; Thuiller, 2004; Elith et al., 2006; Pearson et al., 2006; Elith & Graham, 2009), our approach was to test whether neglecting ecologically meaningful mechanisms, such as biotic interactions, can also yield…”
Cross-validation strategies for data with temporal, spatial, hierarchical, or phylogenetic structure (2017, background): “Models typically show larger error when extrapolating into these no-analogue conditions (Pearson 2006, Elith and Graham 2009).”
Establishing the link between habitat selection and animal population dynamics (2015, background): “Despite their bewildering variety (Guisan and Zimmermann 2000, Elith and Leathwick 2009), fundamentally different assumptions, and regularly conflicting outputs (Elith and Graham 2009), the basic thrust of these models is the same: organisms have a reason for being where we find them.”
A comparison between Ensemble and MaxEnt species distribution modelling approaches for conservation: A case study with Egyptian medicinal plants (2020, methodology): “There is always uncertainty about choosing the best methods to model species distributions (Elith and Graham, 2009).”
Benthos distribution modelling and its relevance for marine ecosystem management (2015, methodology): “…as, for example, species DM, habitat suitability modelling, ecological niche modelling, or bioclimatic envelopes, mainly refer to correlative approaches that use full spatial coverage data of environmental variables to explain and predict patterns of species distribution (Elith and Graham, 2009).”
Adapting to climate change: a perspective from evolutionary physiology (2010, background): “…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 & Graham 2009).”
Variation in niche and distribution model performance: The need for a priori assessment of key causal factors (2012, background): “At the other extreme, another Elith et al. (2006) dataset examined distributions of liana species across South America, where the likely BAM configuration was S ⊃ A ⊃ M, which is close to a WD situation, and again is difficult to model.”
Geographical patterns in prediction errors of species distribution models (2011, background): “Several recent studies have provided information about uncertainties for species distribution analysis concerning methodological issues, species and species traits (see, e.g., Elith & Graham, 2009).”
Spatial disaggregation of complex soil map units: A decision-tree based approach in Bavarian forest soils (2012, methodology): “The resulting “forest” is a “random” forest because at each split only a random subset of the candidate predictors is considered for the binary partition (Elith and Graham, 2009).”
The challenge of modeling niches and distributions for data‐poor species: a comprehensive approach to model complexity (2018, background): “Model complexity has key relevance both for geographic predictions and identification of realistic hypotheses regarding the driving environmental variables (Araújo and Guisan 2006, Elith and Graham 2009, Merow et al. 2014).”
Effects of the number of presences on reliability and stability of MARS species distribution models: the importance of regional niche variation and ecological heterogeneity (2010, result): “As in other published studies, the selection of this number of sites is somewhat arbitrary, but is more than enough to fit models (Elith & Graham 2009).”
No silver bullets in correlative ecological niche modelling: insights from testing among many potential algorithms for niche estimation (2015, methodology): “The efficacy of algorithms designed to estimate the ecological niche also responds to numerous factors, which has been the subject of large numbers of analyses (e.g. Stockwell & Peterson 2002; Graham et al. 2007; Guisan et al. 2007a,b; Elith & Graham 2009).”
How do species interactions affect species distribution models (2012, background): “When two taxa can disperse to dramatically diff erent environments, it is possible for models to confl ate diff erences in suitable environments with diff erences in available environments (Elith and Graham 2009, Godsoe 2010b).”