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Revealing hidden evolutionary capacity to cope with global change
Evatt Chirgwin1, Keyne Monro1, Carla M Sgro1
1School of Biological Sciences, Monash University, Melbourne, Vic., 3800, Australia.
Global Change Biology
|March 18, 2015
Summary
Global change threatens species persistence. A multivariate approach reveals adaptive genetic variation in marine worms, suggesting potential evolution even under warming, contrary to single-environment studies.
Area of Science:
- Evolutionary biology
- Marine ecology
- Climate change adaptation
Background:
- Species' long-term survival hinges on adaptive potential to global change.
- Most studies assess adaptive variation in single environments, potentially underestimating evolutionary capacity.
- Climate change is multivariate, necessitating a multivariate genetic approach for accurate assessment.
Purpose of the Study:
- To evaluate the evolutionary capacity of Galeolaria caespitosa larvae to adapt to warmer ocean temperatures.
- To determine if a multivariate genetic analysis alters conclusions about adaptive potential compared to univariate analyses.
- To highlight the importance of multivariate approaches in predicting species' responses to climate change.
Main Methods:
- Quantitative genetics design analyzing larval survival across three temperatures.
- Assessment of over 30,000 embryos from 204 unique families.
- Multivariate analysis of genetic variances and covariances in thermal tolerance.
Main Results:
- Adaptive genetic variation for survival was found at cooler temperatures but not the warmest.
- Univariate analysis suggested limited adaptive potential at the highest temperature.
- Multivariate analysis revealed potential for evolution at the warmest temperature through correlated selection responses.
Conclusions:
- A multivariate perspective is crucial for accurately estimating a species' adaptive potential to global change.
- Galeolaria caespitosa larvae may possess greater evolutionary capacity to cope with warming than previously indicated.
- Future research on climate change adaptation must adopt multivariate quantitative genetic methods.
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