Predicting Functional Responses in Agroecosystems from Animal Movement Data to Improve Management of Invasive Pests

Mark Q Wilber,James C Beasley,Nathan P Snow,Stephen S Ditchkoff,Samantha M Wisely,Justin W Fischer,John C Kilgo,Kim M Pepin,Ryan K Brook,Raoul K Boughton,Jesse S Lewis,Steve B Hartley,Sarah M Chinn,Ryan S Miller,Colleen T Webb,Kurt C Vercauteren,Lindsey K Holmstrom

doi:10.1002/bes2.1643

Abstract

Predicting Functional Responses in Agroecosystems from Animal Movement Data to Improve Management of Invasive Pests

Highlights

The manner in which invasive alien species (IAS) select resources affects the extent of ecological and economic damage they cause (Vitousek et al 1997, Pimental 2007, Shwiff et al 2012)
Using national-scale wild pig movement data, we found that variability in agricultural functional responses across habitats and individuals can be explained by ecological factors such as the availability of non-agricultural resources, pig attributes, and the stimulus of agricultural resources
The agricultural functional response in wild pigs was consistent with a Type III functional response, where crop use was an accelerating function of crop availability at low crop densities

Summary

Introduction

The manner in which invasive alien species (IAS) select resources affects the extent of ecological and economic damage they cause (Vitousek et al 1997, Pimental 2007, Shwiff et al 2012). There are three general families of functional responses: a linear functional response (Type I), a hyperbolically saturating functional response (Type II), and a sigmoidally saturating functional response (Type III; Fig. 1; Holling 1959). These functional responses can reflect different underlying foraging behaviors, have different effects on predicted stability of ecological systems at equilibrium, and determine the ability of a species to invade a system (Murdoch and Oaten 1975, Van Leeuwen et al 2007). Functional responses of IASs are typically measured in the lab and with a single resource (where resource density is manipulated and resource consumption is measured, e.g., Holling 1959), which can ignore realistic context dependencies present in nature (Dick et al 2014, Paterson et al 2015)

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Conclusion