Predicting functional responses in agro-ecosystems from animal movement data to improve management of invasive pests

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

Research output: Contribution to journalArticle

Abstract

Functional responses describe how changing resource availability affects consumer resource use, thus providing a mechanistic approach to prediction of the invasibility and potential damage of invasive alien species (IAS). However, functional responses can be context dependent, varying with resource characteristics and availability, consumer attributes, and environmental variables. Identifying context dependencies can allow invasion and damage risk to be predicted across different ecoregions. Understanding how ecological factors shape the functional response in agro-ecosystems can improve predictions of hotspots of highest impact and inform strategies to mitigate damage across locations with varying crop types and availability. We linked heterogeneous movement data across different agro-ecosystems to predict ecologically driven variability in the functional responses. We applied our approach to wild pigs (Sus scrofa), one of the most successful and detrimental IAS worldwide where agricultural resource depredation is an important driver of spread and establishment. We used continental-scale movement data within agro-ecosystems to quantify the functional response of agricultural resources relative to availability of crops and natural forage. We hypothesized that wild pigs would selectively use crops more often when natural forage resources were low. We also examined how individual attributes such as sex, crop type, and resource stimulus such as distance to crops altered the magnitude of the functional response. There was a strong agricultural functional response where crop use was an accelerating function of crop availability at low density (Type III) and was highly context dependent. As hypothesized, there was a reduced response of crop use with increasing crop availability when non-agricultural resources were more available, emphasizing that crop damage levels are likely to be highly heterogeneous depending on surrounding natural resources and temporal availability of crops. We found significant effects of crop type and sex, with males spending 20% more time and visiting crops 58% more often than females, and both sexes showing different functional responses depending on crop type. Our application demonstrates how commonly collected animal movement data can be used to understand context dependencies in resource use to improve our understanding of pest foraging behavior, with implications for prioritizing spatiotemporal hotspots of potential economic loss in agro-ecosystems.

Original languageEnglish (US)
Article numbere02015
JournalEcological Applications
DOIs
StateAccepted/In press - Jan 1 2019

Fingerprint

functional response
crop
ecosystem
animal
resource
introduced species
resource use
pig
pest
damage
forage
crop damage
invasibility
ecoregion
resource availability
foraging behavior
prediction
natural resource

Keywords

  • agro-ecosystems
  • continuous-time functional movement models
  • crop damage
  • functional response
  • habitat
  • invasive alien species
  • movement ecology
  • resource selection
  • wild pigs (Sus scrofa)

ASJC Scopus subject areas

  • Ecology

Cite this

Wilber, M. Q., Chinn, S. M., Beasley, J. C., Boughton, R. K., Brook, R. K., Ditchkoff, S. S., ... Pepin, K. M. (Accepted/In press). Predicting functional responses in agro-ecosystems from animal movement data to improve management of invasive pests. Ecological Applications, [e02015]. https://doi.org/10.1002/eap.2015

Predicting functional responses in agro-ecosystems from animal movement data to improve management of invasive pests. / Wilber, Mark Q.; Chinn, Sarah M.; Beasley, James C.; Boughton, Raoul K.; Brook, Ryan K.; Ditchkoff, Stephen S.; Fischer, Justin W.; Hartley, Steve B.; Holmstrom, Lindsey K.; Kilgo, John C.; Lewis, Jesse S.; Miller, Ryan S.; Snow, Nathan P.; VerCauteren, Kurt C.; Wisely, Samantha M.; Webb, Colleen T.; Pepin, Kim M.

In: Ecological Applications, 01.01.2019.

Research output: Contribution to journalArticle

Wilber, MQ, Chinn, SM, Beasley, JC, Boughton, RK, Brook, RK, Ditchkoff, SS, Fischer, JW, Hartley, SB, Holmstrom, LK, Kilgo, JC, Lewis, JS, Miller, RS, Snow, NP, VerCauteren, KC, Wisely, SM, Webb, CT & Pepin, KM 2019, 'Predicting functional responses in agro-ecosystems from animal movement data to improve management of invasive pests', Ecological Applications. https://doi.org/10.1002/eap.2015
Wilber, Mark Q. ; Chinn, Sarah M. ; Beasley, James C. ; Boughton, Raoul K. ; Brook, Ryan K. ; Ditchkoff, Stephen S. ; Fischer, Justin W. ; Hartley, Steve B. ; Holmstrom, Lindsey K. ; Kilgo, John C. ; Lewis, Jesse S. ; Miller, Ryan S. ; Snow, Nathan P. ; VerCauteren, Kurt C. ; Wisely, Samantha M. ; Webb, Colleen T. ; Pepin, Kim M. / Predicting functional responses in agro-ecosystems from animal movement data to improve management of invasive pests. In: Ecological Applications. 2019.
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