10.5061/DRYAD.SJ3TX964N
Williams, Jessica
0000-0002-8275-7597
University College London
Newbold, Tim
University College London
Data from: Vertebrate responses to human land use are influenced by their
proximity to climatic tolerance limits
Dryad
dataset
2021
Land-use change
Climatic position
2021-03-27T00:00:00Z
2021-03-27T00:00:00Z
en
1759695 bytes
3
CC0 1.0 Universal (CC0 1.0) Public Domain Dedication
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.
'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).