The functional response of a generalist predator
Background: Predators can have profound impacts on the dynamics of their prey that depend on how predator consumption is affected by prey density (the predator's functional response). Consumption by a generalist predator is expected to depend on the densities of all its major prey species (its...
| Published in: | PLoS ONE |
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| Main Authors: | , , , , , , |
| Format: | Article in Journal/Newspaper |
| Language: | English |
| Published: |
2010
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| Subjects: | |
| Online Access: | https://risweb.st-andrews.ac.uk/portal/en/researchoutput/the-functional-response-of-a-generalist-predator(e6cf5d9f-9551-4032-ad59-50e11fa922e1).html https://doi.org/10.1371/journal.pone.0010761 https://research-repository.st-andrews.ac.uk/bitstream/10023/3269/1/SmoutPLOSone0010761Predator.pdf http://www.scopus.com/inward/record.url?scp=77956292866&partnerID=8YFLogxK |
| Summary: | Background: Predators can have profound impacts on the dynamics of their prey that depend on how predator consumption is affected by prey density (the predator's functional response). Consumption by a generalist predator is expected to depend on the densities of all its major prey species (its multispecies functional response, or MSFR), but most studies of generalists have focussed on their functional response to only one prey species. Methodology and principal findings: Using Bayesian methods, we fit an MSFR to field data from an avian predator (the hen harrier Circus cyaneus) feeding on three different prey species. We use a simple graphical approach to show that ignoring the effects of alternative prey can give a misleading impression of the predator's effect on the prey of interest. For example, in our system, a “predator pit” for one prey species only occurs when the availability of other prey species is low. Conclusions and significance: The Bayesian approach is effective in fitting the MSFR model to field data. It allows flexibility in modelling over-dispersion, incorporates additional biological information into the parameter priors, and generates estimates of uncertainty in the model's predictions. These features of robustness and data efficiency make our approach ideal for the study of long-lived predators, for which data may be sparse and management/conservation priorities pressing. |
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