COMPLEX SYSTEMS SEMINAR<br>Whither Goest Thou, Gaia? Bioenergetic Approaches to Predicting the Ecological Impacts of Environmental Change
Climate change, land use change and other anthropogenic influences are affecting ecosystems worldwide. Predictive models for future impacts are urgently needed but generally remain elusive due to ecosystem complexity and a lack of data to parameterize models. Here, I argue that most impacts can be understood using bioenergetic approaches. Two major frameworks – the Metabolic Theory of Ecology (MTE) and Dynamic Energy Budget Theory (DEB) – have emerged in recent years, and I will discuss how these can be used to develop process-based and predictive models for the ecological impacts of environmental change. I will primarily focus on climate change impacts on arctic ecosystems, which – due to their relatively low complexity – are particularly suitable for developing and testing predictive models. First, I will link MTE with host-macroparasite models, an approach that allows addressing some of the central questions concerning climatic impacts on host-parasite systems, such as which systems are the most sensitive to change, or at which locations climate change will have the greatest impact. The framework allows integrating multiple nonlinear environmental effects to predict parasite fitness under novel conditions, and can, for example, be used to determine whether climate change will lead to range contractions, shifts, or expansions. Applying the models to seasonal environments, I further show that climate warming can split previously continuous spring-to-fall transmission seasons into two separate transmission seasons with altered timings. Moreover, I will show that parasites with an indirect life cycle may adapt more easily to warmer climates than parasites with a direct life cycle, in contrast to commonly prevailing assumptions. Model predictions conform closely with empirical data for several helminth parasites, indicating broad model applicability. Second, I will use polar bears as an example to discuss how DEB-models can predict survival, reproduction and population abundances for arctic mammals under future conditions. Severe nonlinear declines in each of these parameters are predicted for polar bears, with expectations again matching empirical observations. Finally, I will highlight potential alleys for linking the MTE- and DEB-approaches to develop a unifying mechanistic framework for the ecological impacts of environmental change across a wide variety of taxa. Throughout, I will place particular emphasis on the usefulness of process-based approaches for estimating model parameters a priori, even in data-poor systems. This ability could help resolve prevailing problems of data scarcity and thus provide approaches for predicting the future state of ecosystems worldwide.