General mechanisms for non-additivity between multiple stressors at higher temporal and biological scales

Abstract

Multiple anthropogenic stressors threaten the diversity, stability and functioning of ecosystems worldwide. The combined effects of these stressors can, however, be surprisingly difficult to predict due to complex interactions across different levels of organisation. Ecosystem managers are particularly concerned by synergistic stressor interactions, which cause the combined effects of stressors to be greater than expected based on their individual effects alone. Multiple-stressor researchers have primarily used phenomenological approaches to search for generalities in the frequencies of stressor interactions, but have so far encountered an overwhelming amount of context-dependence. Consequently, there is growing interest in a mechanistic understanding of the interactions between stressors (Chapter 2). In this thesis, I integrate evolutionary and ecological theory into the empirical field of multiple-stressor research to describe mechanisms of non-additivity between stressors, that are not specific to particular species, ecosystems or stressors. I focus on general sources of non-additivity at higher temporal scales (Chapter 3) and at higher levels of biological organisation (Chapters 4 and 5). An overarching theme of this thesis is that non-additivity between stressors can not only be caused by natural effects, but can also arise due to observational effects. Natural sources of non-additivity can be physico-chemical interactions between the stressors themselves, or biological effects occurring at multiple levels of organisation from individuals to ecosystems. Conversely, observational sources of non-additivity stem from statistical effects during the measurement and prediction of responses to stressors. These effects can obscure the natural sources of non-additivity that researchers are actually interested in. Recognising these contrasting sources of non-additivity is an important step towards the accurate prediction of the ecological impacts of multiple stressors. A mechanistic understanding of stressor interactions will enhance the management and conservation of ecosystems in the Anthropocene.