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Predicting natural enemy efficacy in biological control using ex-ante analyses.

Andrew Paul Gutierrez1,2, Luigi Ponti3,4, Peter Neuenschwander5

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This summary is machine-generated.

Predicting natural enemy efficacy for invasive species control is crucial. Mechanistic models can forecast pre-release success, improving biological control and global food security.

Keywords:
Bioeconomic analysisBiological controlPhysiologically based demographic modelTime-varying life tables

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Area of Science:

  • Ecology
  • Agricultural Science
  • Biological Control

Background:

  • Invasive species cause significant global losses in agriculture and natural systems.
  • The success rate of introducing natural enemies for biological control is low due to unpredictable efficacy.
  • Existing reviews of biological control efforts lack methods to predict pre-release effectiveness.

Purpose of the Study:

  • To develop and demonstrate a method for predicting the pre-release efficacy of natural enemies in biological control.
  • To analyze the contributions of introduced natural enemies and endemic pathogens to controlling invasive pests in Africa.
  • To assess the impact of biological control on cassava yield recovery across diverse African ecological zones.

Main Methods:

  • Utilized weather-driven metapopulation tri-trophic physiologically based demographic models (PBDMs).
  • Deconstructed the biological control of cassava mealybug (CM) and cassava green mite (CGM) in Africa.
  • Performed bioeconomic analysis of simulation results to parse control contributions and yield recovery.

Main Results:

  • Ex-ante pre-release analyses using PBDMs accurately predicted the biological control of CM and CGM.
  • PBDM analyses explained the success and/or failure of other historical biological control programs.
  • The study identified specific contributions of natural enemies and fungal pathogens to pest control.

Conclusions:

  • Well-parameterized mechanistic models, like PBDMs, can reliably predict pre-release natural enemy efficacy.
  • This predictive capability can significantly enhance the success rate of biological control programs.
  • Implementing such models is vital for improving global food security by managing invasive species effectively.