Environmental stressors can be thought of as any variable that exceeds its normal range in a given location, owing to human activities. While, the effect of environmental stressors on the life history of individuals is well studied (e.g., temperature), our ability to scale-up and predict population, community, and ecosystem response to multiple, co-occurring stressors is limited and lacks a mechanistic foundation. One reason is that stressors interact in potentially complex and non-linear ways and at multiple scales, including organismal, population, and community levels. Our predictive ability is further complicated by the fact that compensatory processes can occur at each scale, including physiological acclimation, adaptive evolution, and species sorting. Despite this complexity, studies on individuals are often used to set regulatory guidelines even though management targets are generally at the community or ecosystem level.
The biological response to co-occurring stressors might be additive, where the combined outcome is the sum of each stressor, or interactive, where the combined outcome shows synergistic or antagonistic effects. The latter is most problematic for management because interactive effects can cause ‘ecological surprises’. For example, when antagonistic interactions occur, reducing one stressor could worsen the problem. Predicting when interactive effects arise has been a significant research challenge. Meta-analyses reveal little consensus on the prevalence of multiple stressor interactions, with additive, synergistic, and antagonistic interactions detected at each hierarchical level of biological organization across a diversity of trophic levels and biomes. Along with the growing number and combinations of stressors, this poor predictive capacity means that multiple stressors are rarely incorporated in management, despite the recognized importance of considering such potentially interacting effects.
An additional challenge to predicting the effects of multiple stressors is that stressors often vary in time and space, which means the order that biological systems are exposed can influence their response. At the individual level, stressor timing can influence how strongly stressors interact because of cross-tolerance or cross-susceptibility, where exposure to one stressor triggers physiological responses that decrease (or increase) susceptibility to the second stressor. At the population level, exposure to an environmental stressor can result in evolutionary change, which could influence responses to a subsequent stressor. Communities may respond to environmental change through species sorting (increases or decreases in relative species abundance) which could influence susceptibility to additional stressors, depending on species co-tolerances.However, timing is rarely investigated, limitingour understanding of how compensatoryresponses to a single stressor (i.e., acclimation, evolution, or species sorting) influence biotic response to subsequent stressors. Recent studies have demonstrated that both order and duration of stressors influences physiological and population responses but this has not been adequately tested, especially for community structure and ecosystem function.
We are using a multi-scale approach that combines life history studies, field experiments,and modelling to address the following questions.
The biological response to co-occurring stressors might be additive, where the combined outcome is the sum of each stressor, or interactive, where the combined outcome shows synergistic or antagonistic effects. The latter is most problematic for management because interactive effects can cause ‘ecological surprises’. For example, when antagonistic interactions occur, reducing one stressor could worsen the problem. Predicting when interactive effects arise has been a significant research challenge. Meta-analyses reveal little consensus on the prevalence of multiple stressor interactions, with additive, synergistic, and antagonistic interactions detected at each hierarchical level of biological organization across a diversity of trophic levels and biomes. Along with the growing number and combinations of stressors, this poor predictive capacity means that multiple stressors are rarely incorporated in management, despite the recognized importance of considering such potentially interacting effects.
An additional challenge to predicting the effects of multiple stressors is that stressors often vary in time and space, which means the order that biological systems are exposed can influence their response. At the individual level, stressor timing can influence how strongly stressors interact because of cross-tolerance or cross-susceptibility, where exposure to one stressor triggers physiological responses that decrease (or increase) susceptibility to the second stressor. At the population level, exposure to an environmental stressor can result in evolutionary change, which could influence responses to a subsequent stressor. Communities may respond to environmental change through species sorting (increases or decreases in relative species abundance) which could influence susceptibility to additional stressors, depending on species co-tolerances.However, timing is rarely investigated, limitingour understanding of how compensatoryresponses to a single stressor (i.e., acclimation, evolution, or species sorting) influence biotic response to subsequent stressors. Recent studies have demonstrated that both order and duration of stressors influences physiological and population responses but this has not been adequately tested, especially for community structure and ecosystem function.
We are using a multi-scale approach that combines life history studies, field experiments,and modelling to address the following questions.
- Can individual life history responses of the dominant species in a community predict additive or interactive effects of co-occurring stressors on populations, communities, and ecosystem function (e.g., phytoplankton and zooplankton production, estimated as total biomass)?
- Can community structure (e.g., functional diversity, species diversity) predict additive or interactive effects of co-occurring stressors on ecosystem-level responses?
- Does the sequential application of stressors influence community/ecosystem response? That is, does adaptation to a single stressor result in larger (or smaller) community-level effects when exposed to a second stressor?
