Eelke O. Folmer

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.

Seagrass–Sediment Feedback: An Exploration Using a Non-recursive Structural Equation Model

The reciprocal effects between sediment texture and seagrass density are assumed to play an important role in the dynamics and stability of intertidal–coastal ecosystems. However, this feedback relationship has been difficult to study empirically on an ecosystem scale, so that knowledge is mainly based on theoretical models and small-scale (experimental) studies. In this paper we apply a non-recursive structural equation model (SEM) to empirically investigate, at large spatial scale, the mutual dependence between seagrass (Zostera noltii) density and sediment texture, on the pristine, seagrass-dominated, intertidal mudflats of the Banc d’Arguin, Mauritania. The non-recursive SEM allows consistent estimation and testing of a direct feedback between sediment and seagrass whilst statistically controlling for the effects of nutrients and abiotic stress. The resulting model is consistent with the hypothesized negative feedback: grain size decreases with seagrass density, whereas fine grain size has a negative impact on seagrass density because it decreases pore water exchange which leads to hypoxic sediment conditions. Another finding is that seagrass density increases with sediment organic material content up to a threshold level beyond which it levels off. In combination with decreasing grain size, accumulation of organic matter creates hypoxic sediment conditions which lead to the production of toxic hydrogen sulfide which slows down seagrass growth. The negative feedback loop implies that intertidal Z. noltii modifies its own environment, thus controlling its growing conditions. To the best of our knowledge, this study is the first to demonstrate a direct negative feedback relationship in ecosystems by means of a non-recursive SEM.

Large-Scale Spatial Dynamics of Intertidal Mussel (Mytilus edulis L.) Bed Coverage in the German and Dutch Wadden Sea

Intertidal blue mussel beds are important for the functioning and community composition of coastal ecosystems. Modeling spatial dynamics of intertidal mussel beds is complicated because suitable habitat is spatially heterogeneously distributed and recruitment and loss are hard to predict. To get insight into the main determinants of dispersion, growth and loss of intertidal mussel beds, we analyzed spatial distributions and growth patterns in the German and Dutch Wadden Sea. We considered yearly distributions of adult intertidal mussel beds from 36 connected tidal basins between 1999 and 2010 and for the period 1968–1976. We found that in both periods the highest coverage of tidal flats by mussel beds occurs in the sheltered basins in the southern Wadden Sea. We used a stochastic growth model to investigate the effects of density dependence, winter temperature and storminess on changes in mussel bed coverage between 1999 and 2010. In contrast to expectation, we found no evidence that cold winters consistently induced events of synchronous population growth, nor did we find strong evidence for increased removal of adult mussel beds after stormy winter seasons. However, we did find synchronic growth within groups of proximate tidal basins and that synchrony between distant groups is mainly low or negative. Because the boundaries between synchronic groups are located near river mouths and in areas lacking suitable mussel bed habitat, we suggest that the metapopulation is under the control of larval dispersal conditions. Our study demonstrates the importance of moving from simple habitat suitability models to models that incorporate metapopulation processes to understand spatial dynamics of mussel beds. The spatio-dynamic structure revealed in this paper will be instrumental for that purpose.

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 dArguin, 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 Hollings 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.

The contributions of resource availability and social forces to foraging distributions: a spatial lag modelling approach

The spatial distribution of foraging animals at a given time simultaneously depends on (1) exogenous environmental variables such as resource availability and abiotic habitat characteristics, and (2) the endogenous variable social aggregation made up of the opposing mechanisms of conspecific attraction and repulsion. We developed an exogenous environment–social aggregation model to analyse the spatial distributions of six abundant shorebird species in the Dutch Wadden Sea at resolutions of 150xa0×xa0150, 200xa0×xa0200 and 250xa0×xa0250xa0m. We used these resolutions to check the robustness of the estimates to the modifiable areal unit problem. We estimated the model parameters by spatial autoregression. This approach enables, among others, estimation of the direct and indirect effects of an exogenous environmental variable on animal density. The former is given by the regression coefficient and the latter, which is due to the amplification of the direct effect by social aggregation, by the spatial multiplier. At all resolution levels and for all species, the explanatory power of social aggregation, measured by Nagelkerke R2, was larger than the combined contribution of the exogenous environmental variables food availability, silt content and mudflat elevation. Social aggregation was stronger for dunlin, Calidris alpina, red knot, Calidris canutus, and curlew, Numenius arquata, than for oystercatcher, Haematopus ostralegus, grey plover, Pluvialis squatarola, and bar-tailed godwit, Limosa lapponica. The total impacts (that is, direct effect plus all indirect impacts) of the exogenous environmental predictors tended to exceed substantially the direct effects (which tend to be the only ones examined in studies on foraging distributions).