Species distribution models that do not incorporate global data misrepresent potential distributions: a case study using Iberian diving beetles

By D. Sánchez‐Fernández, Jorge M. Lobo, Olga L. Hernández-Manrique. 2011

109 citations recorded by the source corpus.

Subfields: Ecological Modeling, Ecology, Nature and Landscape Conservation

View Paper: https://www.semanticscholar.org/paper/a06cf4cce3166074cb6ea9ae0eba7d8aff159110

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Ecological Modeling

In Ecology

In Nature and Landscape Conservation

Citations in the corpus

Using species distribution models in paleobiogeography: A matter of data, predictors and concepts (2011, background): “…of PSDMs. Failing to include data from the entire geographic distribution of a species can result in sampling a spuriously narrow range of environmental tolerance, which ultimately results in an underestimation of its potential distribution (Thuiller et al., 2004; Sánchez-Fernández et al., 2011).”
Partial versus Full Species Distribution Models (2012, background): “Instead of simply estimating the bioclimatic envelope, ENMs “link the envelope to elements of ecological niche theory rooted in the early work of Grinnell (1917) and Hutchinson (1957)”, and also in the later work of Tilman (1982).”
Modelling horses for novel climate courses: insights from projecting potential distributions of native and alien Australian acacias with correlative and mechanistic models (2011, background): “…been suggested that models of invasive species fitted with pooled data from alien and native ranges may improve the descriptive performance of the models relative to models fitted with native-range data only (Mau-Crimmins et al., 2006; Broennimann & Guisan, 2008; Sanchez-Fernandez et al., 2011).”
Uncertainty associated with survey design in Species Distribution Models (2014, methodology): “The data used to calibrate models are known to lead to differences in SDM predictions thus being expected to affect their performance (e.g. Kadmon et al., 2003; Barry & Elith, 2006; S anchez-Fern andez et al., 2011).”