Means and extremes: building variability into community-level climate change experiments.

Area of Science:

• Ecology
• Climate Change Science
• Environmental Science

Background:

• Ecological studies on climate change impacts often use static warming treatments, not reflecting real-world climate variability.
• Future climates are projected to include more extreme events, which significantly affect ecosystems more than gradual changes.
• Existing experimental approaches have limitations in simulating realistic climatic conditions.

Purpose of the Study:

• To review and classify existing experimental studies on temperature impacts on ecological communities based on their incorporation of variability.
• To highlight the shortcomings of current experimental designs in addressing climate variability and extreme events.
• To propose a new generation of experiments that integrate predicted climatic variability.

Main Methods:

• Systematic review of experimental studies assessing temperature effects on marine, freshwater, and terrestrial communities.
• Classification of studies into 'generations' based on their methodology for incorporating temperature variability.
• Analysis of how experimental designs align with or deviate from climate model predictions of variability.

Main Results:

• The majority of reviewed studies failed to incorporate extreme weather events into their experimental designs.
• Terrestrial ecosystem experiments often reduced variability, contrary to climate model predictions of increased variability.
• Marine and freshwater studies showed varying degrees of focus on variability, with freshwater experiments being less historically developed.

Conclusions:

• Current experimental approaches inadequately represent the climatic variability and extreme events crucial for understanding ecological responses.
• A new generation of experiments is needed, utilizing down-scaled climate models to incorporate predicted variability.
• Developing methods to generate realistic experimental climate change treatments is essential for advancing ecological research.