Data from: Group density, disease, and season shape territory size and overlap of social carnivores

1. The spatial organization of a population can influence the spread of information, behaviour, and pathogens. Territory size and territory overlap, components of spatial organization, provide key information as these metrics may be indicators of habitat quality, resource dispersion, contact rates, and environmental risk (e.g., indirectly transmitted pathogens). Furthermore, sociality and behaviour can also shape space use, and subsequently, how space use and habitat quality together impact demography. 2. Our study aims to identify factors shaping the spatial organization of wildlife populations and assess the impact of epizootics on space use. We also use network analysis to describe spatial organization and connectivity of social groups. 3. Here, we assessed the seasonal spatial organization of Serengeti lions and Yellowstone wolves at the group level. We examine the factors predicting mean territory size and mean territory overlap for each population using generalized additive models. We further explore the mechanisms by which disease perturbations could cause changes in spatial organization. 4. We demonstrate that lions and wolves were similar in that group-level factors, such as number of groups, shaped spatial organization more than population-level factors, such as population density. Factors shaping territory size were slightly different than factors shaping territory overlap; for example, wolf pack size was an important predictor of territory overlap, but not territory size. Lion spatial networks were more highly connected, while wolf spatial networks varied seasonally. We found that resource dispersion may be more important for driving territory size and overlap for wolves than for lions. Additionally, canine distemper epizootics may alter lion spatial organization, highlighting the importance of including behavioural and movement ecology in studies of pathogen transmission dynamics. 5. We provide insight about when we might expect to observe the impacts of resource dispersion, disease perturbations, and other ecological factors on spatial organization. Our work highlights the importance of monitoring and managing social carnivore populations at the group level. Future research should elucidate the complex relationships between demographics, social and spatial structure, abiotic and biotic conditions, and pathogen infections.Here we provide the R code (as R Markdown documents) used to analyze variables predicting group-level territory size and overlap for Serengeti lions and Yellowstone wolves. We show the structure of the datasets, interpretation of the code, and summaries of the Serengeti lion and Yellowstone wolf metadata. We also provide the code for our generalized additive models (GAM) and model outputs. Specifically, 'Wolf_Datasets_Markdown.doc' demonstrates how we created the final dataset used in our GAMs from the raw locational data for Yellowstone wolves. This is where we parse down the data used, calculate certain network measures (e.g., degree), and estimate spatial measures (e.g., territory size). 'GAM_Markdown.doc' provides the code for our machine-learning imputations and exploration, GAMs and GAM outputs (e.g., model fit), and model selection