The effects of species’ range sizes on the accuracy of distribution models: ecological phenomenon or statistical artefact?

By J. McPherson, Walter Jetz, D. Rogers. 2004

585 citations recorded by the source corpus.

Subfields: Ecological Modeling, Ecology, Nature and Landscape Conservation

View Paper: https://www.semanticscholar.org/paper/d69c0ed95f2ed03ac7bb271e9074097df8465f4f

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In Ecological Modeling

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In Nature and Landscape Conservation

Citations in the corpus

Are niche‐based species distribution models transferable in space? (2006, background): “Hence differences in the size and upper limit of the altitudinal range between the two regions (McPherson et al., 2004) may have truncated the response curves of alpine and subalpine species to temperature-related predictors in AT, but not in CH: for example, true alpine species could have a linear…”
Additive threats from pathogens, climate and land-use change for global amphibian diversity (2011, background): “Because BEM projections can become unreliable for species with few occurrence record”
Habitat suitability modelling of an invasive plant with advanced remote sensing data (2009, background): “…(Pearce & Ferrier, 2000; Stockwell & Peterson, 2002; McPherson et al., 2004; Guisan et al., 2007), balance between presence and absence records (McPherson et al., 2004; Reese et al., 2005; Meynard & Quinn, 2007), and survey design (Nicholls, 1989; Reese et al., 2005; Edwards et al., 2006) of…”
Geographical patterns in prediction errors of species distribution models (2011, background): “Though such measures of predictive performance have been widely used, they suffer from serious shortcomings (McPherson et al., 2004; Lobo et al., 2008).”
Predicting the spatial distribution of an invasive plant species (Eupatorium adenophorum) in China (2007, methodology): “by some researchers (Cumming 2000; Mcpherson et al. 2004).”
Potential impacts of climate change on the distributions of several common and rare freshwater fishes in Canada (2005, background): “Although studies warn of Kappa’s sensitivity to prevalence, the effect of proportion of true positives and false negatives (e.g. McPherson et al ., 2004), other studies suggest the effect is negligible (Fielding & Bell, 1997; Manel et al ., 2001).”
Without quality presence–absence data, discrimination metrics such as TSS can be misleading measures of model performance (2018, background): “Cohen ' s Kappa has also been repeatedly criticized for the same reason (Allouche, Tsoar, & Kadmon, 2006; Lobo et al., 2010; McPherson, Jetz, & Rogers, 2004).”
Climatic stability in the Brazilian Cerrado: implications for biogeographical connections of South American savannas, species richness and conservation in a biodiversity hotspot (2012, background): “1), which may reflect a known bias in the AUC approach of a tendency to achieve higher values for more restricted-range models (McPherson et al., 2004).”
Species distribution modelling of marine benthos: a North Sea case study (2011, methodology): “In contrast to the AUC, κ is dependent on prevalence (McPherson et al. 2004).”
The effect of species response form on species distribution model prediction and inference (2009, methodology): “Improved prediction has been found in studies using Gibbs sampler in autologistic modelling (Hoeting et al., 2000; McPherson et al., 2004).”
A comparison of the performance of threshold criteria for binary classification in terms of predicted prevalence and Kappa (2008, background): “A particular value of kappa from one population is not necessarily comparable to the same kappa value from a different species or location, if the prevalence differs between the two populations (McPherson et al., 2004; Vaughan and Ormerod, 2005; Allouche et al., 2006).”
Soil nutritional factors improve models of plant species distribution: an illustration with Acer campestre (L.) in France (2006, background): “…Bakkenes et al., 2002; Dirnböck et al., 2003; Skov & Svenning, 2004; Araújo et al., 2006), to test biogeographical hypotheses (Huntley et al., 2004; McPherson et al., 2004) or to deal with conservation planning problems (Margules & Stein, 1989; Araújo & Williams, 2000; Polasky et al., 2000;…”