Freshwater fish community structured more by dispersal limitation than by environmental heterogeneity

Abstract –  We examined the relative contribution of environmental heterogeneity and dispersal limitation on freshwater fish community composition in 18 Greek protected lakes and reservoirs. Environmental heterogeneity was measured by spatial pattern metrics (calculated by digital map processing, e.g., patch richness density, area-weighted mean patch area), altitude, maximum lake depth and trophic status. Dispersal limitation was measured by straight-line distances among lake centres. Ecosystems were clustered according to species composition. We examined the correlation of similarity in species composition among ecosystems with that of environmental heterogeneity and with straight-line distances, for the entire dataset, as well as for the occurring clusters. Fish species richness increased with ecosystem area and decreased with altitude. The clusters identified (aquatic ecosystems of Northern vs. ecosystems of Western Greece), implied an underlying biogeographical pattern as defined, with Pindus range acting as a natural barrier. Between ecosystems similarity, based on fish species composition, showed a weak to insignificant correlation with environmental heterogeneity, but was significantly correlated to dispersal limitation for the entire dataset as well as within each occurring cluster. Thus, natural barriers, species biogeography and dispersal limitation played a more significant role in shaping freshwater fish communities than environmental heterogeneity.     

Accuracy of fractal dimension estimates for small samples of ecological distributions

We carry out a simulation study of the estimation of fractal dimension in a grid-based setting typical of ecological species distributions, using null landscape models. We calculate the box-counting dimension for samples taken in various types of sampling geometry. Sampler geometries include simple blocks,Cantor grids and line transects. This method may be used to measure fractal dimension of a species distribution, but the accuracy depends on a number of criteria. The most important is sampling effort: any estimate will be inaccurate if the sampling effort is low. We also find the geometry of the sampler to be important. For a given sampling effort, schemes based on the Cantor grids performed better than either line transects or simple blocks. Sampling effort can be improved either by using a bigger sampler over a larger area or by repeated sampling of a smaller area: optimum performance is often a trade-off between these two mechanisms. However, performance is also highly sensitive to the type of fractal object being sampled, with certain types of object requiring a much greater effort for an accurate estimate of fractal dimension. These results raise the possibilities of using novel sampling techniques to estimate fractal dimension, when confronted with limited resources and time, but underline also the need for an understanding of the “type” of fractality expected in ecological situations. This revised version was published online in July 2006 with corrections to the Cover Date.