DOI: 10.6084/m9.figshare.16895851.v1
title: Data and code from: Vertebrate population trends are influenced by interactions between land use, climatic position, habitat loss and climate change.

description: Abstract of paperRapid human-driven environmental changes are impacting animal populations around the world. Currently, land-use and climate change are two of the biggest pressures facing biodiversity. However, studies investigating the impacts of these pressures on population trends often do not consider potential interactions between climate and land-use change. Further, a population’s climatic position (how close the ambient temperature and precipitation conditions are to the species’ climatic tolerance limits) is known to influence responses to climate change but has yet to be investigated with regard to its influence on land-use change responses over time. Consequently, important variation across species’ ranges in responses to environmental changes may be being overlooked. Here, we combine data from the Living Planet and BioTIME databases to carry out a global analysis exploring the impacts of land use, habitat loss, climatic position, climate change, and the interactions between these variables, on vertebrate population trends. By bringing these datasets together, we analyse over 7,000 populations across 42 countries. We find that land-use change is interacting with climate change and a population’s climatic position to influence rates of population change. Moreover, features of a population’s local landscape (such as surrounding land cover) play important roles in these interactions. For example, populations in agricultural land uses where maximum temperatures were closer to their hot thermal limit, declined at faster rates when there had also been rapid losses in surrounding semi-natural habitat. The complex interactions between these variables on populations highlights the importance of taking intraspecific variation and interactions between local and global pressures into account. Understanding how drivers of change are interacting and impacting populations, and how this varies spatially, is critical if we are to identify populations at risk, predict species’ responses to future environmental changes and produce suitable conservation strategies.Information on data and code 'Code_to_run_models_JJW_GCB.R' contains the R script to run all the candidate models and then compare them.'Data_JJW_GCB.rds' contains the data used to run the candidate models that investigated how rate of population change was affected by land-use type and change, a population’s climatic position, and the rate of climate change experienced.<i>Metadata</i>Binomial = Species name (HIDDEN if classed as confidential within the Living Planet Index database)Class = The vertebrate Classloc_id = ID based on the population's location (latitude and longitude)data = The database the population’s time-series data was acquired from, either the Living Planet Index (LPI) or BioTIME databaseBaselineLU2 = Starting land-use typeTmax_rate, Tmin_rate, Ppmax_rate, Ppmin_rate = The average annual rate of change in maximum temperature of the warmest month, minimum temperature of the coldest month, precipitation of the wettest month and precipitation of the driest month, respectively, over the length of the population time-seriesPercentPVV2_rate = The average annual rate of change in the percentage of semi-natural habitat within a 1-km radius of the population, over the length of the population time-seriesstand_dist = The standardised distance of a population from their species’ geographic range edgeStart_Tmax_Pos, Start_Tmin_Pos, Start_Ppmax_Pos, Start_Ppmin_Pos = The maximum temperature of the warmest month (Tmax), minimum temperature of the coldest month (Tmin), precipitation of the wettest month (Ppmax), and precipitation of the driest month (Ppmin), a population experienced in the first year they were measured, relative to the species-level upper and lower realised thermal (for Tmax and Tmin) or precipitation (for Ppmax and Ppmin) tolerance limitslambda_mean = The average logged annual rate of population change