Community- and ecosystem-level effects of multiple environmental change drivers: Beyond null model testing.

Area of Science:

• Ecology
• Environmental Science
• Global Change Biology

Background:

• Understanding the combined impacts of multiple environmental drivers is crucial for ecology.
• Current methods often rely on null models to assess synergistic or antagonistic effects, but these lack mechanistic insight.

Purpose of the Study:

• To critique the limitations of null model testing for understanding joint environmental change effects.
• To propose a novel framework for studying the impacts of multiple drivers on ecological communities and functions.

Main Methods:

• Ecological theory was used to demonstrate the inferential limits of null models.
• A new framework was developed, differentiating resource ratio shifts and multiple stressors.
• Stressor effects were integrated into resource uptake theory.

Main Results:

• Null models can obscure mechanistic understanding, as different mechanisms yield similar deviations, and the same mechanism can cause different deviations.
• The proposed framework necessitates formalizing 'multiple stressors' with specific factors (number, kind, selectivity, dynamics, trait diversity, tolerance).
• This framework generates testable predictions on how stressors and resource shifts impact biodiversity and ecosystem function.

Conclusions:

• The new framework advances ecological understanding by providing a mechanistic approach to multiple environmental drivers.
• It offers a more effective path for progressing research on global change effects compared to current null model practices.
• Informative failures of the framework can guide future experiments and theoretical advancements.