Modelling species distributions in Britain: a hierarchical integration of climate and land-cover data

By Richard G. Pearson, Terence P. Dawson, Canran Liu. 2004

671 citations recorded by the source corpus.

Subfields: Ecological Modeling, Global and Planetary Change, Nature and Landscape Conservation

View Paper: https://www.semanticscholar.org/paper/36ae8908848fbae1ecb57d1b3aac826881b132b5

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Citations in the corpus

Promising the future? Global change projections of species distributions (2007, positive): “Identifying hierarchies of environmental drivers (Borcard & Legendre, 2002; Bjorholm, Svenning, Skov, & Balslev, 2005; Pearson et al., 2004).”
Assessing the accuracy of species distribution models: prevalence, kappa and the true skill statistic (TSS) (2006, methodology): “The most popular measure for the accuracy of presence‐absence predictions is Cohen’s kappa (Shao & Halpin 1995; Manel, Williams & Ormerod 2001; Loiselle et al . 2003; Petit et al . 2003; Berg, Gardenfors & von Proschwitz 2004; Parra, Graham & Freile 2004; Pearson, Dawson & Liu 2004; Rouget et al .”
The ecology of urban areas and their functions for species diversity (2011, neutral): “a main factor influencing the landscape (Pearson et al. 2004).”
Distribution patterns of boreal marshland birds: modelling the relationships to land cover and climate (2005, background): “Employing finer resolutions enables researchers to identify regions with suitable climate but unsuitable land cover for a given species (Pearson et al., 2004).”
Linking earth observation and taxonomic, structural and functional biodiversity: local to ecosystem perspectives (2016, background): “…addition, ven though the causal relationship between land cover and species istributions is indirect (Thuiller et al., 2004), several studies have lso made use of existing land cover or land use classifications that ad previously been derived from EO data (Pearson et al., 2004; ompe et al., 2008).”
Can we derive macroecological patterns from primary Global Biodiversity Information Facility data (2015, methodology): “In the case of MaxEnt, we also used the lowest predicted values associated with an observed presence as a threshold (Pearson et al., 2004).”
Biogeography and conservation of taxa from remote regions: An application of ecological-niche based models and GIS to North-African canids (2009, background): “Although the independent analyses of environmental factors is less frequently applied than modelling all factors together (but see Pearson et al., 2004; Anadón et al., 2007), in this study it stressed that certain regions can be suitable for the occurrence of a species according to topoclimatic…”
Environmental predictors of species richness in forest landscapes: abiotic factors versus vegetation structure (2016, positive): “Several studies highlighted the importance of complementing climatic variables with land cover and habitat information for improving predictions of species distributions and richness patterns at regional scales (Pearson et al., 2004; Thuiller et al., 2004; Ill an et al., 2010).”
The importance of biotic interactions for modelling species distributions under climate change (2007, background): “…degree of explanatory and predictive power than models including land-cover variables at continental (Europe, Thuiller et al ., 2004) and regional scales (Britain, Pearson et al ., 2004; Great Lakes Basin including parts of Canada and USA, Venier et al ., 2004; Finland, Luoto et al ., 2006).”
Predicting potential distributions of invasive species: where to go from here? (2010, methodology): “, 2006) but they have been refined afterwards with data representing other aspects of the environment, such as land use, soil or productivity (Pearson et al., 2004; Bradley & Mustard, 2006; Ficetola et al., 2007).”