Department Fish Ecology and Evolution

In recent years, there has been a renewed interest in the ecological consequences of individual trait variation within populations. Given that individual variability arises from evolutionary dynamics, to fully understand eco-evolutionary feedback loops, we need to pay special attention to how standing trait variability affects ecological dynamics. There is mounting empirical evidence that intra-specific phenotypic variation can exceed species-level means, but theoretical models of multi-trophic species coexistence typically neglect individual-level trait variability. What is needed are multispecies datasets that are resolved at the individual level that can be used to discriminate among alternative models of resource selection and species coexistence in food webs. Here, using one the largest individual-based datasets of a food web compiled to date, along with an individual trait-based stochastic model that incorporates Approximate Bayesian computation methods, we document intra-population variation in the strength of prey selection by different classes or predator phenotypes which could potentially alter the diversity and coexistence patterns of food webs. In particular, we found that strongly connected individual predators preferentially consumed common prey, whereas weakly connected predators preferentially selected rare prey. Such patterns suggest that food web diversity may be governed by the distribution of predator connectivity and individual trait variation in prey selection. We discuss the consequences of intra- specific variation in prey selection to assess fitness differences among predator classes (or phenotypes) and track longer term food web patterns of coexistence accounting for several phenotypes within each prey and predator species.

Populations of species typically considered trophic generalists may include specialized individuals consistently feeding on certain resources. Optimal foraging theory states that individuals should feed on those resources most valuable to them. This, however, may vary according to individual differences in detecting or processing resources, different optimization criteria, and competitive abilities. White Storks (Ciconia ciconia) are trophic generalists at the population level. Their European population recovery has been attributed to increased wintering in southern Europe (rather than Africa) where they feed upon new anthropogenic food subsidies: predictable dumps and less predictable and more difficult to detect, but abundant, invasive Procambarus clarkii crayfishes in ricefields. We studied the foraging strategies of resident and wintering storks in southwestern Spain in ricefields and dumps, predicting that more experience in the study area (residents vs. immigrants, old vs. young) would increase ricefield specialization. We developed the first multi-event capture–recapture model to evaluate behavioral consistency, analyzing 3042 observations of 1684 banded storks. There were more specialists among residents (72%) than immigrants (40%). All resident specialists foraged in ricefields, and ricefield use increased with individual age. In contrast, some immigrants specialized on either dumps (24%) or ricefields (16%), but the majority were generalists (60%). Our results provide empirical evidence of high individual foraging consistency within a generalist species and a differential resource selection by individuals of different ages and origins, probably related to their previous experience in the foraging area. Thus, future changes in food resource availability at either of the two anthropogenic subsidies (ricefields or dumps) may differentially impact individuals of different ages and origins making up the wintering population. The use of multi-event capture–recapture modeling has proven useful for studying interindividual variability in behavior.

Studies of food webs suggest that limited nonrandom dispersal can play an important role in structuring food webs. It is not clear, however, whether density-dependent dispersal fits empirical patterns of food webs better than density-independent dispersal. Here, we study a spatially distributed food web, using a series of population-dispersal models that contrast density-independent and density-dependent dispersal in landscapes where sampled sites are either homogeneously or heterogeneously distributed. These models are fitted to empirical data, allowing us to infer mechanisms that are consistent with the data. Our results show that models with density-dependent dispersal fit the α, β, and γ tritrophic richness observed in empirical data best. Our results also show that density-dependent dispersal leads to a critical distance threshold beyond which site similarity (i.e., β tritrophic richness) starts to decrease much faster. Such a threshold can also be detected in the empirical data. In contrast, models with density-independent dispersal do not predict such a threshold. Moreover, preferential dispersal from more centrally located sites to peripheral sites does not provide a better fit to empirical data when compared with symmetric dispersal between sites. Our results suggest that nonrandom dispersal in heterogeneous landscapes is an important driver that shapes local and regional richness (i.e., α and γ tritrophic richness, respectively) as well as the distance-decay relationship (i.e., β tritrophic richness) in food webs.

Dispersal and the underlying movement behaviour are processes of pivotal importance for understanding and predicting metapopulation and metacommunity dynamics. Generally, dispersal decisions are condition-dependent and rely on information in the broad sense, like the presence of conspecifics. However, studies on metacommunities that include interspecific interactions generally disregard condition-dependence. Therefore, it remains unclear whether and how dispersal in metacommunities is condition-dependent and whether rules derived from single-species contexts can be scaled up to (meta)communities. Using experimental protist metacommunities, we show how dispersal and movement depend on and are adjusted by the strength of interspecific interactions. We found that the predicting movement and dispersal in metacommunities requires knowledge on behavioural responses to intra- and interspecific interaction strengths. Consequently, metacommunity dynamics inferred directly from single-species metapopulations without taking interspecific interactions into account are likely flawed. Our work identifies the significance of condition-dependence for understanding metacommunity dynamics, stability and the coexistence and distribution of species.