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Nonlinear Pharmacokinetics: Causes of Nonlinearity01:22

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Incorporating nonlinearity with generalized functional responses to simulate multiple predator effects.

Michael W McCoy1, Elizabeth Hamman2, Molly Albecker3

  • 1Florida Atlantic University (Harbor Branch Campus), Ft. Pierce, FL, United States.

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|August 24, 2022
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Summary
This summary is machine-generated.

Predicting multiple predator effects (MPE) on prey is challenging due to nonlinearities. Accounting for nonlinear prey risk, predator functional responses, and depletion is crucial for accurate ecological predictions.

Keywords:
Diversity function relationshipFunctional responseInteraction strengthJensens inequalityMPEMultiple predator effectsNonlinearPredatorPredictionPrey

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Area of Science:

  • Community ecology
  • Predator-prey dynamics
  • Ecological modeling

Background:

  • Quantitative predictions of multiple predator effects (MPE) often fail in community ecology.
  • Nonlinearities in prey predation risk and prey depletion are known sources of bias.

Purpose of the Study:

  • To explore additional sources of bias in MPE studies stemming from nonlinearities in prey predation risk.
  • To identify necessary factors for unbiased predictions of combined predator effects.

Main Methods:

  • Analysis of nonlinear size-dependent risk for prey.
  • Incorporation of nonlinear predator functional responses.
  • Consideration of prey depletion effects.

Main Results:

  • Failure to account for nonlinearities in prey risk, predator functional responses, and depletion leads to biased MPE predictions.
  • Accurate predictions require integrating nonlinear size-dependent risk and dynamic risk changes.

Conclusions:

  • Existing MPE frameworks may be biased due to overlooking nonlinear processes.
  • Reevaluation of the ubiquity of emergent MPEs over the past three decades is suggested.
  • Future research must incorporate nonlinearities for robust ecological predictions.