Data from: Vertebrate responses to human land use are influenced by their proximity to climatic tolerance limits
Williams, Jessica; Newbold, Tim (2021), Data from: Vertebrate responses to human land use are influenced by their proximity to climatic tolerance limits, Dryad, Dataset, https://doi.org/10.5061/dryad.sj3tx964n
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.
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.
'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.
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).