Abstract
AbstractContact rates vary widely among individuals in socially structured wildlife populations. Understanding the interplay of factors responsible for this variation is essential for planning effective disease management. Feral swine (Sus scrofa) are a socially structured species which pose an increasing threat to livestock and human health, and little is known about contact structure. We analyzed 11 GPS data sets from across the United States to understand the interplay of ecological and demographic factors on variation in co‐location rates, a proxy for contact rates. Between‐sounder contact rates strongly depended on the distance among home ranges (less contact among sounders separated by >2 km; negligible between sounders separated by >6 km), but other factors causing high clustering between groups of sounders also seemed apparent. Our results provide spatial parameters for targeted management actions, identify data gaps that could lead to improved management and provide insight on experimental design for quantitating contact rates and structure.
Highlights
Most wildlife populations exhibit contact heterogeneity, especially populations where territorial, dominance or other social grouping behaviors are common
This emphasizes that when using Global positioning system (GPS)-type data for quantitating contact rates, the interval between locations should approximate the minimum time between the start and end of a perceived disease- relevant contact
Additional studies, which include long-term monitoring should be undertaken to determine if contact rates change seasonally, which could obscure the potential importance of monitoring duration on quantitation of contact rates
Summary
Most wildlife populations exhibit contact heterogeneity, especially populations where territorial, dominance or other social grouping behaviors are common. Global positioning system (GPS) devices and ultra-high-frequency proximity loggers (PL) are two of the most commonly used technologies for quantitating contact in wildlife. Both devices are used to quantitate contact rates, social networks, factors driving contact heterogeneities and impacts of contact heterogeneities on disease transmission and management (e.g., Cross et al 2012, Hamede et al 2012, Drewe et al 2013, Lavelle et al 2014, Long et al 2014, Podgorski et al 2014, Williams et al 2014). Realistic representations of contact heterogeneities in wildlife populations can be used to optimize disease management in terms of when and where to increase surveillance and implement controls (Hamede et al 2012)
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