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Annual Review of Marine Science

Volume 16, 2024

Designing More Informative Multiple-Driver Experiments

Abstract

For decades, multiple-driver/stressor research has examined interactions among drivers that will undergo large changes in the future: temperature, pH, nutrients, oxygen, pathogens, and more. However, the most commonly used experimental designs—present-versus-future and ANOVA—fail to contribute to general understanding or predictive power. Linking experimental design to process-based mathematical models would help us predict how ecosystems will behave in novel environmental conditions. We review a range of experimental designs and assess the best experimental path toward a predictive ecology. Full factorial response surface, fractional factorial, quadratic response surface, custom, space-filling, and especially optimal and sequential/adaptive designs can help us achieve more valuable scientific goals. Experiments using these designs are challenging to perform with long-lived organisms or at the community and ecosystem levels. But they remain our most promising path toward linking experiments and theory in multiple-driver research and making accurate, useful predictions.

Keyword(s): anthropogenic change, experimental design, interactions, multiple stressors, predictive ecology, theory–experiment integration
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2024-01-17
2025-02-18
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/content/journals/10.1146/annurev-marine-041823-095913
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Designing More Informative Multiple-Driver Experiments
Annual Review of Marine Science 16, 513 (2024); https://doi.org/10.1146/annurev-marine-041823-095913
/content/journals/10.1146/annurev-marine-041823-095913
/content/journals/10.1146/annurev-marine-041823-095913
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  • Article Type: Review Article

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