Search

Barrier islands occur in north-western Europe between the North Sea and the Wadden Sea along the coast of Denmark, Germany and the Netherlands. Geomorphological units such as dunes and salt marshes are built by wind, water and sediment. The biota also feed back to the units by trapping sand and silt, transported by water and wind thus (de)stabilizing the local substrate and are able to modify their own abiotic environment. Hence, we refer to them as biogeomorphological units, thus including the role of engineering biota. We consider seven units: tidal basin, island head, intertidal flats, dune arc complex, wash-over complex, island tail with salt marsh, and green beach. We focus on the well-studied West-Frisian island of Schiermonnikoog, the Netherlands, from which we integrated published data. The biogeomorphological units are built with bioengineering species, and in turn provide habitats for plant- and animal species. These communities are subject to succession until climax stages with various timescales. These temporal aspects are derived from long-term measurements in the field, including the study of chronosequences. Biogeomorphological units also affect each other, including feed-backs from animals, plants and micro-organisms. Based on that we present a conceptual model of this particular barrier island. Knowledge gaps that can be identified include 1) interactions among geomorphological units, 2) interactions among these units and bio-engineers to come to biogeomorphological units, and 3) multiple spatial-temporal scales. Human interference such as A atmospheric deposition applies to all islands and is difficult to manage. Other human interferences may, however, differ among individual islands and their surroundings. They can be managed such as various intensities of fisheries, sand suppletion, extraction of groundwater, the attitude of local people towards artificial sand-drift dikes and livestock grazing. [ABSTRACT FROM AUTHOR]

The results of a restoration experiment carried out on a permanent grassland on peaty, heavy clay in the Netherlands are described. The experiment started in 1985, 7 years after fertilizer application had ceased, and was designed to provide insight into ecologically significant processes accompanying restoration. An analysis was made of the effect of management regime and of raising the water table on nutrient availability, dry matter production, tissue nutrient concentration, dynamics of species numbers and plant species replacement. Three management practices were compared: cutting and removal (RR), cutting and mulching (MM), sod removal in 1985, and thereafter cutting and removal of the hay (RS). Data are presented on changes during a 5-year period. No trend was discernible in soil pH, total C, N and P in the RR treatment; extractable P and K decreased sharply in the field with the raised groundwater level. Nine years after fertilizer application ceased, dry matter production had fallen from 10–11 to 6–7 t ha&sup-1; years&up-1;. In the subsequent 5 years of the experiment it declined to 5–5 t ha&sup-1; year&sup-1; when all cut biomass was removed, and to about 4 t ha&sup-1; year&sup-1; after sod removal. Mulching caused an increase to 11 t ha&sup-1; year&sup-1;. No effect was seen of the raised water level. The dry matter yield of the first June cut in the RR treatment decreased. The tissue K concentration also decreased, but no increase of the tissue P concentration was detected. It was concluded that the availability of K and to some extent of P was more important than N availability in explaining the decrease in dry matter production. The tissue nutrient concentrations were not influenced by the water table. Sod removal to a depth of 5 cm resulted in the lowest productivity and the lowest tissue concentrations of P, while tissue concentrations of N and K were not affected. Raising the water level resulted in a more rapid establishment of species indicative of wet conditions, some of which invaded from nearby ditches. The: trends of dominant species are described with a set of response models. The species were ranked from disappearing to colonizing species. The relationship between rank order of replacement and indicator values of species was investigated. Raising: the water table resulted in species indicative of wet conditions becoming dominant, independently of vegetation management. The removal of nutrients resulted in the appearance of species with a lower maximal height, indicative of lower P and K availability. [ABSTRACT FROM AUTHOR]

Theoretical models highlight that spatially self-organized patterns can have important emergent effects on the functioning of ecosystems, for instance by increasing productivity and affecting the vulnerability to catastrophic shifts. However, most theoretical studies presume idealized homogeneous conditions, which are rarely met in real ecosystems. Using self-organized mussel beds as a case study, we reveal that spatial heterogeneity, resulting from the large-scale effects of mussel beds on their environment, significantly alters the emergent properties predicted by idealized self-organization models that assume homogeneous conditions. The proposed model explicitly considers that the suspended algae, the prime food for the mussels, are supplied by water flow from the seaward boundary of the bed, which causes in combination with consumption a gradual depletion of algae over the simulated domain. Predictions of the model are consistent with properties of natural mussel patterns observed in the field, featuring a decline in mussel biomass and a change in patterning. Model analyses reveal a fundamental change in ecosystem functioning when this self-induced algal depletion gradient is included in the model. First, no enhancement of secondary productivity of the mussels comparing with non-patterns states is predicted, irrespective of parameter setting; the equilibrium amount of mussels is entirely set by the input of algae. Second, alternate stable states, potentially present in the original (no algal gradient) model, are absent when gradual depletion of algae in the overflowing water layer is allowed. Our findings stress the importance of including sufficiently realistic environmental conditions when assessing the emergent properties of self-organized ecosystems.

Increasing evidence shows that spatial interactions between sedentary organisms can structure communities and promote landscape complexity in many ecosystems. Here we tested the hypothesis that reef-forming mussels (Mytilus edulis L.), a dominant intertidal ecosystem engineer in the Wadden Sea, promote abundances of the burrowing bivalve Cerastoderma edule L. (cockle) in neighboring habitats at relatively long distances coastward from mussel beds. Field surveys within and around three mussel beds showed a peak in cockle densities at 50-100 m toward the coast from the mussel bed, while cockle abundances elsewhere in the study area were very low. Field transplantation of cockles showed higher survival of young cockles (2-3 years old) and increased spat fall coastward of the mussel bed compared to within the bed and to areas without mussels, whereas growth decreased within and coastward of the mussel bed. Our measurements suggest that the observed spatial patterns in cockle numbers resulted from (1) inhibition effects by the mussels close to the beds due to preemptive algal depletion and deteriorated sediment conditions and (2) facilitation effects by the mussels farther away from the beds due to reduction of wave energy. Our results imply that these spatial, scale-dependent interactions between reef-forming ecosystem engineers and surrounding communities of sedentary benthic organisms can be an important determinant of the large-scale community structure in intertidal ecosystems. Understanding this interplay between neighboring communities of sedentary species is therefore essential for effective conservation and restoration of soft-bottom intertidal communities.

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.