Within‐taxon niche structure: niche conservatism, divergence and predicted effects of climate change

By P. Pearman, M. D’Amen, Catherine H. Graham, Wilfried Thuiller, N. E. Zimmermann. 2010

220 citations recorded by the source corpus.

Subfields: Ecological Modeling, Ecology, Nature and Landscape Conservation

View Paper: https://www.semanticscholar.org/paper/e4ef5bc60e2e49d4f89ab011e05e306ae3f67b0a

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In Ecological Modeling

In Ecology

In Nature and Landscape Conservation

Citations in the corpus

The effects of phenotypic plasticity and local adaptation on forecasts of species range shifts under climate change. (2014, background): “In our real species simulations we did find the pattern of less pessimistic forecasts when population differentiation is accounted for, which was an expected possibility (e.g., Pearman et al. 2010; Oney et al. 2013).”
Deep reefs are climatic refugia for genetic diversity of marine forests (2016, unknown): “…modelling considering the full range of S. polyschides and (2) sub-taxon modelling with phylogeographical structure (i.e. within-taxon niche structure; Pearman et al. , 2010), using distinct models for each geographical region identiﬁed as genetically differentiated (see genetic analyses below).”
Ecological genomics meets community-level modelling of biodiversity: mapping the genomic landscape of current and future environmental adaptation. (2015, background): “Studies have explored the use of SDMs in predicting the geographic distribution of subspecies (Pearman et al. 2010), lineages (Esp ındola et al. 2012; D’Amen et al. 2013; Yannic et al. 2014), genotypes or genetic clusters (Banta et al. 2012; Jay et al. 2012), climate zones (Sork et al. 2010) or…”
Climate change, genetic markers and species distribution modelling (2015, unknown): “Following the method of Pearman et al. (2010), this joint probability is: PðoccurrenceÞ j ¼ 1 À Y m k¼1 ð1 À P kj Þ which is the probability that at least one of the m clusters is present at site j.”
Cross-validation of species distribution models: removing spatial sorting bias and calibration with a null model. (2012, background): “For example, Pearman et al. (2010) found that models for groups below the species level (e.g., clades) are better than models for species.”
Species distribution models and mitochondrial DNA phylogeography suggest an extensive biogeographical shift in the high‐intertidal seaweed Pelvetia canaliculata (2014, background): “However, the distinct evolutionary histories and selective regimes experienced by lineages occupying different geographical/environmental spaces are likely to promote regional accumulation of unique and potentially adaptive genetic variability (Hampe & Petit, 2005; Pearman et al., 2010).”