Towards a general theory of ecological impacts of multiple, simultaneous stressors.

Predicting the impact that combined natural and anthropogenic stressors have on ecological communities ranks as one of the most important research agendas in ecology. Climate change and the fragmentation of habitat are considered the two largest threats to the global environment. They are expected to impact on the diversity, composition and dynamics of the communities that underpin ecosystem services. Pollution and (over)harvesting of natural resources considerably complicate these impacts. It is safe to assume that communities are experiencing multiple, simultaneous challenges.

It also seems easy to assume that combined threats might simply add up to generate impact. The more stressors, the more and worse the impact. However, it may be that, because of the way biology works, some stressors cancel each other out, or combine to be less impactful than expected. And, of course, the opposite is possible (and scary): stressors may exacerbate each other, leading to effects that are worse than expected compared to just adding their effects together.

Unfortunately, we really have no idea about whether stress combines in an additive or non-additive fashion. And we have very rudimentary understanding of how feedbacks among population dynamics, community structure and ecosystem function operate under multiple stressors. We suggest, in fact, that the distribution of these additive or interactive effects can tell us something about how predictable and how generalizable are the effects of stressors.

We propose to explore the distribution of additive and interactive effects caused by multiple stressors by building a model that allows biology to determine if stress adds up or not, and then comparing this to patterns in real data. Our unique contribution comes from recognising that some kinds of stress, like temperature, act on physiology and change the rates at which things like metabolism growth and reproduction happen. In contrast, some stressors simply kill things, either by harvesting or by direct impacts from things like pollution. We will build the first model that allows these distinctions to be accommodated, giving us the best chance of understanding how stressors combine to affect populations, the structure of communities and the ecosystem functions we rely upon.

The research proposed here is fundamental. It is, however, about establishing a modelling platform that informs on the distribution of additive or interactive effects associated with multiple forms of stressors experienced by ecological communities. It is this analysis of the distribution of these effects that can help scientists and natural resource managers understand how and when effects will be predictable, and whether effects are generalisable. In this context, we see three major groups of beneficiaries:

1. Policymakers and managers concerned with the conservation of biological diversity (marine, freshwater and terrestrial) in the face of environmental change. Our research will provide an understanding of the mechanisms that mediate response to environmental change, and how they facilitate the emergence of predictable and or generalizable responses at multiple scales.
2. The public, for whom food web networks provide an accessible route to understanding of complex ecological principles. The structure of our model, and its reliance on network principles, lends itself to illustrating how well-known forms of stress interaction with biodiversity. Our project provides an important opportunity for education and outreach, increasing public understanding of key evolutionary and ecological ideas.
3. 1st Year Minority/Women Students. In the past few years, there has been a decrease in the number of summer research bursaries available to young people interested in learning about science. Furthermore, the issues of supporting women and minorities in science (STEM) and computer programming has increased. Our research focused on STEM topics and computer modelling provides an ideal opportunity to experience a combination of ecology and conservation via computer based activities, to learn first -hand how research works and whether a career in research may be of interest.