DOI: 10.5061/dryad.sj3tx964n
title: Data from: Vertebrate responses to human land use are influenced by their proximity to climatic tolerance limits

description: Aim: Land-use change leads to local climatic changes, which can induce
 shifts in community composition. Indeed, human-altered land uses favour
 species able to tolerate greater temperature and precipitation extremes.
 However, environmental changes do not impact species uniformly across
 their distributions, and most research exploring the impacts of climatic
 changes driven by land use has not considered potential within-range
 variation. We explored whether a population’s climatic position (the
 difference between species’ thermal and precipitation tolerance limits and
 the environmental conditions a population experiences) influences their
 relative abundance across land-use types. Location: Global Methods: Using
 a global dataset of terrestrial vertebrate species and estimating their
 realised climatic tolerance limits, we analysed how the abundance of
 species within human-altered habitats relative to that in natural habitats
 varied across different climatic positions (controlling for proximity to
 geographic range edge). Results: A population’s thermal position strongly
 influenced abundance within human-altered land uses (e.g., agriculture).
 Where temperature extremes were closer to species’ thermal limits,
 population abundances were lower in human-altered land uses (relative to
 natural habitat) compared to areas further from these limits. These
 effects were generally stronger at tropical compared to temperate
 latitudes. In contrast, the influences of precipitation position were more
 complex, and often differed between land uses and geographic zones.
 Mapping the outcome of models revealed strong spatial variation in the
 potential severity of decline for vertebrate populations following
 conversion from natural habitat to cropland or pasture, due to their
 climatic position. Main conclusions: We highlight within-range variation
 in species’ responses to land use, driven (at least partly), by
 differences in climatic position. Accounting for spatial variation in
 responses to environmental changes is critical when predicting population
 vulnerability, producing successful conservation plans, and exploring how
 biodiversity may be impacted by future land-use and climate change
 interactions.
description: 'Occurrence_data_for_Williams_and_Newbold_Diversity_and_Distributions.rds' contains the data used within the probability of occurrence model. 'Abundance_data_for_Williams_and_Newbold_Diversity_and_Distributions.rds' contains the data used within the abundance (given presence) model.  Metadata Best_guess_binomial = Species binomial name, as found within the PREDICTS Project database (https://data.nhm.ac.uk/dataset/902f084d-ce3f-429f-a6a5-23162c73fdf7). SS and SSBS = Identity of the study (SS) and sampled site within study (SSBS), as found within the PREDICTS Project database. LandUse = Land-use type, derived from the PREDICTS Project database. stand_dist = Standardised distance to range edge. GZ = Geographic zone (i.e., whether the population is at a temperate or tropical latitude). StandMaxTemp = Climatic position with regard to maximum temperature of the warmest month. StandMinTemp = Climatic position with regard to minimum temperature of the coldest month. StandMaxPrecip = Climatic position with regard to precipitation of the wettest month. StandMinPrecip = Climatic position with regard to precipitation of the driest month. JW_Occ = Occurrence (0 = absent, 1 = present). LogAbund = Log-transformed abundance (given presence).