Evaluating predictive models of species’ distributions: criteria for selecting optimal models

By R. P. Anderson, D. Lew, A. Townsend Peterson. 2003

1,245 citations recorded by the source corpus.

Subfields: Ecological Modeling, Ecology, Genetics

View Paper: https://www.semanticscholar.org/paper/ced6e27494bd6227213a4f0b05f50043193e59b9

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Citations in the corpus

Impact of the quality of climate models for modelling species occurrences in countries with poor climatic documentation: a case study from Bolivia (2010, background): “However, presence–absence models are of limited applicability especially in the tropics, where low densities of study sites prevent their use (Anderson et al., 2003).”
Estimating optimal complexity for ecological niche models: A jackknife approach for species with small sample sizes (2013, background): “, 2005) are not valid for resence–pseudoabsence or presence–background situations (due o apparent commission error; Anderson et al., 2003; Peterson t al., 2011).”
Modeled climate change effects on distributions of Canadian butterfly species (2004, methodology): “…predictive ability of this modeling technique for diverse biodiversity phenomena in various regions have been published elsewhere (Peterson and Cohoon 1999; Peterson 2001; Peterson and Vieglais 2001; Peterson et al. 2002a, 2002c, 2002d; Stockwell and Peterson 2002a, 2002b; Anderson et al. 2003).”
Ecological niche modeling as a predictive tool: silver and bighead carps in North America (2006, methodology): “GARP modeling has been discussed in detail in e.g., Anderson et al. (2003), Feria and Peterson (2002), Levine et al. (2004) and Wiley et al. (2003).”
Reconstructing the Pleistocene geography of the Aphelocoma jays (Corvidae) (2004, methodology): “…using the methods that we utilize here — has been explored in a series of sensitivity analyses (Peterson & Cohoon, 1999; Stockwell & Peterson, 2002a,b; Anderson et al ., 2003; Stockwell & Peterson, 2003) and tests of model predictivity (Peterson, 2001; Anderson et al ., 2002; Peterson et al .,…”
Model‐based uncertainty in species range prediction (2006, background): “It may, in fact, be argued that the best techniques are those that make the fewest false-negative predictions (Anderson et al., 2003).”
Real vs. artefactual absences in species distributions: tests for Oryzomys albigularis (Rodentia: Muridae) in Venezuela (2003, methodology): “…& Cohoon, 1999; Peterson et al., 1999, 2001, 2002a,b,c,d; Stockwell & Peters, 1999; Chen & Peterson, 2000; Elith, 2000; Godown & Peterson, 2000; Sánchez-Cordero & Martı́nez-Meyer, 2000; Peterson, 2001; Peterson & Vieglais, 2001; Anderson et al., 2002a, 2003; Elith & Burgman, 2002; Feria-A.”
Niches and distributional areas: Concepts, methods, and assumptions (2009, positive): “When multiple GARP models are generated and combined via consensus approaches (71) an estimate of the concordance between different stochastic solutions to an optimization problem is obtained.”
Ecological niche modelling of montane mammals in the Great Basin, North America: examining past and present connectivity of species across basins and ranges (2009, methodology): “To select the best ENMs from among the replicate model runs, we followed Anderson et al. (2003) in prioritizing low-omission models for further consideration (the 20% of replicate models showing the lowest extrinsic omission error), and then retaining the central 50% of the distribution of areas p”
Sampling bias and the use of ecological niche modeling in conservation planning: a field evaluation in a biodiversity hotspot (2010, methodology): “We used the default parameters of the OpenModeller version of GARP with the best subset selection option (optimum models considering omission/commission relationships; see Anderson et al. 2003 ).”
A maximum entropy approach to species distribution modeling (2004, methodology): “To reduce the variability inherent in GARP’s random search procedure, we made composite GARP predictions using the “best-subsets” procedure (Anderson et al., 2003), as was done in recent applications (Peterson et al.”
Is Cassava the Answer to African Climate Change Adaptation? (2012, background): “2006), GARP (Genetic Algorithm for Rule-set Production) (Anderson et al. 2003), support vector machines (Drake et al.”