Modelling the species richness distribution of French dung beetles (Coleoptera, Scarabaeidae) and delimiting the predictive capacity of different groups of explanatory variables

By J. Lumaret, P. Jay‐Robert. 2002

139 citations recorded by the source corpus.

Subfields: Ecological Modeling, Nature and Landscape Conservation

View Paper: https://www.semanticscholar.org/paper/d979545e2fccb1c0cf92e9a8a6252031c7b3439f

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In Ecological Modeling

In Nature and Landscape Conservation

Citations in the corpus

Applications and limitations of museum data for conservation and ecology, with particular attention to species distribution models (2010, methodology): “An alternative method to account for spatial autocorrelation when modelling species’ distributions is to include the geographical coordinates (longitude and latitude), and interactions between them, as independent variables in the model; this is referred to as ‘trend surface analysis’ (Legendre, 199”
Ants, altitude and change in the northern Cape Floristic Region (2006, background): “…identifies the relative contribution of the environmental variables and spatial components to the explained variation in ant density and abundance, but it does not quantify the importance of individual variables (Legendre & Legendre, 1998; see also Lobo et al., 2002; van Rensburg et al., 2002).”
Defying the curse of ignorance: perspectives in insect macroecology and conservation biogeography (2010, background): “For 2010 The Authors Journal compilation 2010 The Royal Entomological Society, Insect Conservation and Diversity, 3, 172–179 instance, Lobo et al. (2002) pioneered the use of multiple partial regression in a macroecological context and showed that species richness of Scarabaeidae in France was…”
An ED-based Protocol for Optimal Sampling of Biodiversity (2005, background): “maximizing the representation of the assemblage variation in the region), it is possible to extrapolate maps of their estimated distribution over all the region (Margules et al. 1987; Bojorquez-Tapia et al. 1996; Iverson and Prasad 1998; Zimmermann and Kienast 1999; Hortal and Lobo 2001; Hortal et a”
Towards a biogeographic regionalization of the European biota (2010, methodology): “Finally, we used deviance partitioning (Lobo et al., 2002) to partition the deviance of each response variable into independent ‘effects’ of a particular predictor and covarying ‘effects’ of two or more predictors that cannot be disentangled.”