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Temporal Autocorrelation Increases Temperature-Driven Extinction Risk by Clustering Stressful Conditions
Alison J Robey1, Misha T Kummel1, David A Vasseur1
1Department of Ecology & Evolutionary Biology, Yale University, New Haven, Connecticut, USA.
Ecology Letters
|July 18, 2026
Summary
Increasing temperature autocorrelation, a climate change effect, heightens extinction risks for populations by clustering stressful conditions. This finding is crucial for predicting species vulnerability to climate change.
Area of Science:
- Ecology
- Climate Change Biology
- Evolutionary Biology
Background:
- Climate change alters thermal environments, affecting temporal autocorrelation and heatwaves.
- Existing models often overlook autocorrelation's impact on extinction risk.
Purpose of the Study:
- To investigate how increasing temporal autocorrelation in thermal environments influences population extinction risks.
- To integrate autocorrelation into thermal performance-based forecasting.
Main Methods:
- Paired stochastic population dynamics simulations with generated temperature time series.
- Validated predictions using factorial experiments with protist microcosms.
Main Results:
- Higher temporal autocorrelation increases extinction risk by clustering stressful conditions.
- Reduced survival extent of warming and variability for populations with unimodal thermal tolerance.
- Significant elevation of extinction risk in microcosms with stressful temperatures and higher autocorrelation.
Conclusions:
- Temporal autocorrelation is a critical factor in thermal risk assessment for species.
- Provides a foundation for predicting species and environmental vulnerability to climate change-induced thermal stress.
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