Karen Richardson

TL;DR: This work compared 16 modelling methods over 226 species from 6 regions of the world, creating the most comprehensive set of model comparisons to date and found that presence-only data were effective for modelling species' distributions for many species and regions.

TL;DR: Generalized dissimilarity modeling (GDM) as discussed by the authors is a statistical technique for analyzing and predicting spatial patterns of turnover in community composition (beta diversity) across large regions, which is an extension of matrix regression, designed specifically to accommodate two types of nonlinearity commonly encountered in large-scaled ecological data sets: (1) the curvilinear relationship between increasing ecological distance, and observed compositional dissimilarities, between sites; and (2) the variation in the rate of compositional turnover at different positions along environmental gradients.

TL;DR: New methods that model collections data in combination with abiotic data and predict potential total species distribution are examined, and potential high-priority biodiversity sites are selected based on the concept of irreplaceability, a measure of uniqueness.

TL;DR: A new approach to describing and mapping the global distribution of terrestrial biodiversity that focuses on estimating spatial pattern in emergent properties of biodiversity (richness and compositional turnover) rather than distributions of individual species, making it well suited to lesser-known, yet highly diverse, biological groups.

TL;DR: Analysis of populations within species or species within genera showed that undefended home ranges were larger than defended home ranges for carnivores and male ungulates, but not for primates.