How invasive oysters can affect parasite infection patterns in native mussels on a large spatial scale.

There are surprisingly few field studies on the role of invasive species on parasite infection patterns in native hosts. We investigated the role of invasive Pacific oysters (Magallana gigas) in determining parasite infection levels in native blue mussels (Mytilus edulis) in relation to other environmental and biotic factors. Using hierarchical field sampling covering three spatial scales along a large intertidal ecosystem (European Wadden Sea), we found strong spatial differences in infection levels of five parasite species associated with mussels and oysters. We applied mixed models to analyse the associations between parasite prevalence and abundance in mussels and oysters, and 12 biological and environmental factors. For each parasite-host relationship, an optimal model (either a null, one-factor or two-factor model) was selected based on AIC scores. We found that the density of invasive oysters contributed to three of the 12 models. Other biological factors such as host size (six models), and the density of target or alternative host species (five models) contributed more frequently to the best models. Furthermore, for parasite species infecting both mussels and oysters, parasite population densities were higher in native mussels, attributed to the higher densities of mussels. Our results indicate that invasive species can affect parasite infection patterns in native species in the field, but that their relative contribution may be further mediated by other biological and environmental parameters. These results stress the usefulness of large-scale field studies for detailed assessments of the mechanisms underlying the impacts of invasive species on native host communities.

Moving on with foraging theory: incorporating movement decisions into the functional response of a gregarious shorebird.

Models relating intake rate to food abundance and competitor density (generalized functional response models) can predict forager distributions and movements between patches, but we lack understanding of how distributions and small-scale movements by the foragers themselves affect intake rates. Using a state-of-the-art approach based on continuous-time Markov chain dynamics, we add realism to classic functional response models by acknowledging that the chances to encounter food and competitors are influenced by movement decisions, and, vice versa, that movement decisions are influenced by these encounters. We used a multi-state modelling framework to construct a stochastic functional response model in which foragers alternate between three behavioural states: searching, handling and moving. Using behavioural observations on a molluscivore migrant shorebird (red knot, Calidris canutus canutus), at its main wintering area (Banc d'Arguin, Mauritania), we estimated transition rates between foraging states as a function of conspecific densities and densities of the two main bivalve prey. Intake rate decreased with conspecific density. This interference effect was not due to decreased searching efficiency, but resulted from time lost to avoidance movements. Red knots showed a strong functional response to one prey (Dosinia isocardia), but a weak response to the other prey (Loripes lucinalis). This corroborates predictions from a recently developed optimal diet model that accounts for the mildly toxic effects due to consuming Loripes. Using model averaging across the most plausible multi-state models, the fully parameterized functional response model was then used to predict intake rate for an independent data set on habitat choice by red knot. Comparison of the sites selected by red knots with random sampling sites showed that the birds fed at sites with higher than average Loripes and Dosinia densities, that is sites for which we predicted higher than average intake rates. We discuss the limitations of Holling's classic functional response model which ignores movement and the limitations of contemporary movement ecological theory that ignores consumer-resource interactions. With the rapid advancement of technologies to track movements of individual foragers at fine spatial scales, the time is ripe to integrate descriptive tracking studies with stochastic movement-based functional response models.

How well do food distributions predict spatial distributions of shorebirds with different degrees of self-organization?

1. Habitat selection models usually assume that the spatial distributions of animals depend positively on the distributions of resources and negatively on interference. However, the presence of conspecifics at a given location also signals safety and the availability of resources. This may induce followers to select contiguous patches and causes animals to cluster. Resource availability, interference and attraction therefore jointly lead to self-organized patterns in foraging animals. 2. We analyse the distribution of foraging shorebirds at landscape level on the basis of a resource-based model to establish, albeit indirectly, the importance of conspecific attraction and interference. 3. At 23 intertidal sites with a mean area of 170 ha spread out over the Dutch Wadden Sea, the spatial distribution of six abundant shorebird species was determined. The location of individuals and groups was mapped using a simple method based on projective geometry, enabling fast mapping of low-tide foraging shorebird distributions. We analysed the suitability of these 23 sites in terms of food availability and travel distances to high tide roosts. 4. We introduce an interference sensitivity scale which maps interference as a function of inter-individual distance. We thus obtain interference-insensitive species, which are only sensitive to interference at short inter-individual distances (and may thus pack densely) and interference-sensitive species which interfere over greater inter-individual distances (and thus form sparse flocks). 5. We found that interference-insensitive species like red knot (Calidris canutus) and dunlins (Calidris alpina) are more clustered than predicted by the spatial distribution of their food resources. This suggests that these species follow each other when selecting foraging patches. In contrast, curlew (Numenius arquata) and grey plover (Pluvialis squatarola), known to be sensitive to interference, form sparse flocks. Hence, resource-based models have better predictive power for interference-sensitive species than for interference-insensitive species. 6. It follows from our analysis that monitoring programmes, habitat selection models and statistical analyses should also consider the mechanisms of self-organization.