Food webs as proxies for ecological interaction networks

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Historically, food webs have been the common model for ecosystem connectivity and the iconic image of a complex system. By definition, however, food webs depict only direct trophic interactions (who eats whom), one of many ways in which species may interact. This project will develop and use the emerging approach of empirical dynamic modeling (EDM) to construct networks showing the realized causal influences between species (interaction webs) for several ecosystems. These interaction webs are network diagrams that quantify the measurable impact of one species on another as they interact in time. The approach is transformative in that it measures impacts that may be propagated indirectly along causal chains. It is unlike current analytical frameworks, because it accommodates the fact that ecological interactions are not constant but change through time, and depend on the broader ecological context (e.g., where the intensity of competition among consumers changes with prey availability). Moreover, this approach can be used to generate dynamic mathematical models of complex ecosystems from real-time field data. This research has immediate value for producing actionable advice for ecological management by identifying the important species in ecosystems, exposing hidden causal chains of indirect effects (e.g. exposing unintended consequences of management decisions), and by providing scientifically sound early warning signs for critical transitions. The results of this work should be critically useful to resource managers and environmental stewards alike. This project will use the EDM method of Convergent Cross Mapping to identify causal interactions and construct realized influence webs, using data taken from 6 ecosystems spanning 4 biomes: Port Erin Bay, the North Atlantic Ocean, Canada's Experimental Lake Area, and the Chihuahua Desert. These interaction networks will be compared to classical food webs constructed from literature review to test the extent to which food webs depict the most important ecosystem interactions. A cross-system analysis will be done to quantify the type and frequency of non-trophic interactions (e.g. competition versus indirect mutualism), with validation against experimental evidence where possible (e.g. known non-trophic interactions from long-term experiments at two study sites). In addition, the interaction webs will be tested for the ability to identify important nodes and pathways, such as keystone predators and indirect effects resulting from transitive causal chains. Finally, this project will go beyond the classical image of a static ecological network, by acknowledging the reality that interactions are dynamic (i.e. change over time).