Using niche-based GIS modeling to test geographic predictions of competitive exclusion and competitive release in South American pocket mice

By R. P. Anderson, A. Townsend Peterson, Marcela Gómez‐Laverde, Gó Mez-Laverde. 2002

377 citations recorded by the source corpus.

Subfields: Ecological Modeling, Ecology, Nature and Landscape Conservation

View Paper: https://www.semanticscholar.org/paper/f909eb450d4514d3db19daa9ff56f3cba6987690

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In Ecological Modeling

In Ecology

In Nature and Landscape Conservation

Citations in the corpus

Integrating GIS-based environmental data into evolutionary biology. (2008, background): “competitors [ 66 ], or by nonclimatic factors, such as lack of time for dispersal into climatically suitable areas [67], or rivers”
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.”
How biotic interactions may alter future predictions of species distributions: future threats to the persistence of the arctic fox in Fennoscandia (2012, background): “It has already been shown that introducing species interactions in SDMs can considerably alter the output of such models (Leathwick & Austin, 2001; Anderson et al., 2002; Araújo & Luoto, 2007; Meier et al., 2011).”
Pushing the limits in marine species distribution modelling: lessons from the land present challenges and opportunities (2011, background): “A few studies have demonstrated the importance of competitive exclusion on the distribution of terrestrial plants (Leathwick & Austin, 2001; Anderson et al., 2002) and animals (Russell & Clout, 2004; Ritchie et al., 2009).”
Novel methods improve prediction of species' distributions from occurrence data (2006, neutral): “This is particularly apparent in the CAN bird data set, in which the data display many of the biases possible in presence-only data (Anderson 2003).”
Spatially autocorrelated sampling falsely inflates measures of accuracy for presence‐only niche models (2009, methodology): “Ecological niche models are increasingly being employed to test predictions from ecological and evolutionary theory (Peterson et al., 1999; Anderson et al., 2002; Graham et al., 2004b), to test the invasion potential of species in novel areas (Peterson & Vieglais, 2001; Estrada-Peña et al.”
The effect of prevalence and its interaction with sample size on the reliability of species distribution models (2009, methodology): “Thus, these techniques can be useful tools in biogeography, paleoecology, evolution, and conservation (e.g., Peterson et al. 1999, Anderson et al. 2002a,b, Schadt et al. 2002, Barbosa et al. 2003, Peterson and Holt 2003, Chefaoui et al. 2005, Jiménez-Valverde and Lobo 2007a, Jiménez-Valverde et al.…”
Predicting the Distribution of the Amphibian Pathogen Batrachochytrium dendrobatidis in the New World 1 (2005, methodology): “These results parallel those of other investigations that have shown a high predictive power of distribution ranges from niche modeling (e.g., Anderson et al. 2002b, 2003; Peterson et al. 2002a, 2003, 2004; Peterson 2003; Ortega-Huerta & Peterson 2004).”
A comparative evaluation of presence‐only methods for modelling species distribution (2007, background): “Several studies have already taken this approach (Leathwick & Austin, 2001; Anderson et al ., 2002; Thomas et al ., 2004).”
Species Distribution Modeling in the Tropics: Problems, Potentialities, and the Role of Biological Data for Effective Species Conservation (2009, background): “Some examples can be found in Anderson et al. (2002), Ortega-Huerta and Peterson (2004), Peterson et al. (2004), and García (2006).”
Applications and limitations of museum data for conservation and ecology, with particular attention to species distribution models (2010, background): “Global sampling has been particularly poor in tropical areas and in arid environments (Stockwell and Peters, 1999; Anderson et al., 2002a; Soria-Auza and Kessler, 2008).”
Habitat suitability modelling and niche theory (2008, background): “This may be done either in geographical space by comparing the predicted distributions of species (Anderson et al .”
Uses and requirements of ecological niche models and related distributional models (2006, background): “That is, I argue that many species interactions take place in geographic space, and that they are far from universal: in this way, ecological potential of species is manifest in some portion of the range, and good (dense, representative) sampling will usually reveal that potential (Araújo and Guisan”