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Updated: Nov 8, 2025

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Linking Predation Risk, Herbivore Physiological Stress and Microbial Decomposition of Plant Litter
Published on: March 12, 2013
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Altered precipitation dynamics lead to a shift in herbivore dynamical regime
Adam Pepi1,2, Marcel Holyoak3, Richard Karban2
1Graduate Group in Ecology, University of California Davis, Davis, CA, USA.
Ecology Letters
|April 24, 2021
Summary
Changing precipitation patterns can alter moth population cycles, shifting them from short to long oscillations. This interaction highlights the need for climate shift data to predict future population dynamics accurately.
Area of Science:
- Ecology
- Population Dynamics
- Climate Science
Background:
- Population dynamics are influenced by interactions between internal biological factors and external environmental changes.
- While changes in average climate are well-studied, alterations in environmental variability also impact population dynamics significantly.
- This study examines a 34-year moth census in California, analyzing shifts in population oscillations and regional precipitation patterns.
Discussion:
- Wavelet and time series analyses revealed a regime shift in moth population dynamics, transitioning from shorter to longer period oscillations.
- These changes coincided with alterations in regional precipitation dynamics, suggesting a causal link.
- Simulations indicated that shifting precipitation patterns likely drove the observed changes in moth population dynamics, potentially through stochastic resonance with delayed density-dependence.
Key Insights:
- A significant regime shift was identified in California moth population dynamics over 34 years.
- The study links this shift to contemporaneous changes in regional precipitation dynamics.
- Climate variability, not just mean climate, plays a critical role in population dynamics.
Outlook:
- Predicting future population dynamics requires understanding both climatic shifts and their interplay with endogenous density-dependence.
- Current models based solely on historical data may fail to predict future population trends due to these complex interactions.
- Further research is needed to integrate climate variability into ecological forecasting models.
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