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Macroecological context predicts species' responses to climate warming.
Joshua S Lynn1,2, Kari Klanderud3, Richard J Telford1
1Department of Biological Sciences, University of Bergen, Bergen, Norway.
Global Change Biology
|January 29, 2021
Summary
Predicting species' responses to climate change is challenging. Incorporating macroecological context into climate change experiments enhances predictability, using climate differences to forecast species colonization and extinction probabilities.
Area of Science:
- Ecology
- Climate Change Biology
- Macroecology
Background:
- Species responses to climate change vary, hindering generalized predictions in biodiversity science.
- Macroecological context is crucial for understanding and predicting species' reactions to climate manipulations.
Purpose of the Study:
- To enhance the predictability of species' responses to climate change by integrating macroecological context into experimental data.
- To assess the utility of "climate differences"—the disparity between a species' climatic niche and experimental site conditions—in predicting ecological outcomes.
Main Methods:
- Combined data from an 8-year turf transplant climate change experiment in Norway with macroecological climate niche data for 151 vascular plant species.
- Utilized "climate differences" to predict colonization probability, extinction probability, and changes in species abundance.
- Analyzed species-specific and across-site variations in responses to climate manipulations.
Main Results:
- Colonization probability increased with warmer species distribution optima relative to the target site; extinction probability increased with colder optima.
- Climate differences proved more effective predictors of species' responses than range size.
- Observed weak species responses to increased precipitation in oceanic climates.
Conclusions:
- Integrating macroecological context into climate change experiments improves the predictability of species' responses.
- Findings support the validity of space-for-time substitutions for predicting climate warming impacts, provided other factors are controlled.
- The proposed method offers a framework for generalizing and predicting species' responses to climate change globally.
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