1 Introduction
The spatial distribution of direct contact among animals (co-location of
animals at the same time) greatly influences the dynamics of various
ecological processes, such as disease transmission, social organization,
and human-wildlife conflict (Meijaard et al. 2011, Kurvers et al. 2014,
Craft 2015). The spatial distributions of contacts across landscapes are
often heterogeneous due to various factors, including animal movement
patterns (e.g., migration, speed), social behaviors (e.g., mating,
territoriality, fission-fusion dynamics), densities of animals, and
external factors such as food availability and predators (Kareiva and
Odell 1987, Spiegel et al. 2017). Assessing drivers of such
heterogeneity is key for mechanistic understanding of contact-driven
ecological processes.
While social factors like group membership can influence contact
structure and heterogeneity (i.e., animals within the same social groups
tend to stay together, resulting in a higher contact rate) (Silk et al.
2019), landscape features like the distribution of resources also impact
contact patterns (McClure et al. 2022). Areas with abundant resources or
preferred habitats may attract more animals, including from different
social groups, structuring contacts. Exploring the role of the landscape
in structuring contacts can facilitate understanding of the spatial
distributions and extents of contact based ecological processes and
enable the prediction of contacts or contact-driven ecological processes
on the landscape.
Frameworks to investigate environmental drivers of contacts and
probabilistically predict their distributions are limited. Koen et al.
(2017) adopted social network analysis to estimate the effects of
landscape connectivity on contact rates by comparing contact rates based
on broad-scale environmental conditions. In addition, some spatial
models (e.g., conditional autoregressive model) have also been applied
to quantify the effects of different factors on the spatial distribution
of contact rates (Yang et al. 2021a). However, these approaches have not
explicitly compared the spatial conditions where contacts occurred to
those where contacts could have occurred. As such, these approaches did
not estimate and disentangle how different landscape features drive
probability of contact occurrence across the landscape. Building off the
assumption that contacts differentially occur at the places with
abundant resources or preferred habitat, previous studies have used the
spatial overlap of individual or population-level habitat selection as a
proxy for contact probability (Habib et al. 2011). However, it remains
unclear whether patterns of resource selection can accurately predict
hotspots of contact.
In this study, we developed a method to quantify landscape factors
influential to contact locations. We applied the method to movement data
from two wild pig (Sus scrofa ) populations in dissimilar
landscapes, exemplifying how our approach can identify geographical
attributes associated with contact events. We use our framework to test
the hypothesis that the landscape variables that drive contacts are the
same as those that drive individual-level space use, as has been assumed
in previous applications of resource selection analysis to contact
behavior. Consequently, we assess the utility of aggregating individual
resource selection functions to predict the spatial properties of
contact behavior. We discuss the implications of this work for
understanding contact dynamics in wild pig systems.