Lead
Aim - The purpose of this proposal is to combine individual-based data with a novel stochastic food web theory to improve our understanding of the mechanisms that drive variability among individuals within the same species in prey selection and their effect on biodiversity in multi-trophic ecosystems.

Lay summary
Background – Most empirical data show evidence of a large variability in resource use among individuals in natural populations. These data has recently shown coexistence driven by higher intraspecific than interspecific variation in resource use, thus confirming previous theoretical results. However, theoretical results taking into account intraspecific variance were developed in the context of a single ecological community and its usefulness to understand diversity in multi-trophic ecosystems has yet to be confirmed. For example, a higher intraspecific than interspecific variation in resource use can enable coexistence within
an ecological community, but this pattern can me misleading for two or more interacting communities because individual variation in prey selection across prey with different abundance can lead to species extinctions in food webs. Thus predators consuming many or just a few prey can increase or decrease diversity by preferentially selecting common or rare prey. Connecting a mechanistic food web theory with individual-level variability in ecological interactions can help us to identify the strength in prey selection by individual predators and its effect
on biodiversity in multi-trophic ecosystems.

Research plan – I propose a general framework using stochastic individual-based food web models to connect the mechanisms that drive intraspecific variability with biodiversity patters in multi-trophic ecosystems. In the first stage we will test learning behavior and the the strength of prey selection mechanisms against a collection of individual based food webs. We aim to detect the main mechanisms that generate non-random intraspecific variation in prey selection and whether its effects are weak or strong on biodiversity in multi-trophic ecosystems. In the second stage we propose to generalize the theory by adding several traits in the context of multiple types of interactions. In the last stage we will test the theory using its predictions in intraspecific variation and the strength of resource selection using a variety of datasets ranging from antagonistic to mutualistic networks.

Impact and potential results – There are three features that make this proposal a candidate to produce high impact results. First, it will combine the analysis of high-resolution individual-based food web data and novel stochastic individual-
based models. Second it will help to detect the mechanisms that generate intraspecific variance in prey selection and its effects on diversity in natural and disturbed multi-trophic ecosystems across a broad range of taxa. Finally, it will help to connect basic research, sampling methods and experiments in a testable framework. The development of a stochastic context-dependent theory of individual-based food webs would trigger a feedback between experimentalists and theoreticians with the aim to understand the consequences of the variability observed in individual-based food webs and its implications for sampling effort and biodiversity in multi-trophic ecosystems.