Burgess, Benjamin Joshua; (2021) Null model detection of multiple stressor interactions in aquatic ecosystems. Doctoral thesis (Ph.D), UCL (University College London).

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Abstract

Ecosystems are subjected to a wide range of stressors, many of which are anthropogenic in origin. However, far from being impacted by isolated threats, these ecosystems are affected by multiple co-occurring stressors. Currently, there is little understanding of how, or whether, these stressors interact to affect individuals, populations, or communities. Indeed, studies vary in whether they find co-occurring stressors to interact in an additive, antagonistic, or synergistic manner. However, attempts to determine general ecological covariables which may explain these disparate findings have so far failed to do so. Here, I use meta-analytical and theoretical approaches to better understand how stressors can be expected to interact, with a particular emphasis on freshwater ecosystems. Firstly, I simulate food chains which are subjected to co-occurring stressors and compare these results to the findings of the largest multiple stressor meta-analysis, here focusing on freshwater densities. Both approaches illustrate that null (i.e., additive) classifications dominate for individual interactions; although, overall stressors interact to affect density in an antagonistic manner. Secondly, I analyse the statistical tools frequently used to classify multiple stressor interactions. I illustrate that many results which are ascribed ecological importance instead arise due to statistical artefacts of these tools. In turn, I highlight that many experimental designs, commonplace to multiple stressor ecology, lack the statistical power necessary to detect the interactions of co-occurring stressors. Thirdly, I collate and analyse the datasets of seven aquatic multiple stressor meta-analyses under a single consistent framework. I illustrate that the current absence of generalities from multiple stressor meta-analyses primarily arises due to methodological, not ecological, variation. In turn, removing methodological differences results in generalities becoming apparent. Finally, I collate the findings of the above chapters and outline the potential implications for multiple stressor ecology. In doing so, I explore current challenges facing the field alongside future directions.

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