spatially explicit approach to trophic interactions and landscape formation: patchiness in small-scale variability of grazing effects along an intertidal stress gradient

1. It is well known that grazing contributes to spatial and temporal patterns of algal cover on rocky shores, but this effect has traditionally been studied through grazer exclusion experiments using randomly positioned treatments at particular levels on the shore. Additionally, the effects of grazing on algal composition and biomass are expected to vary across gradients of physical stress and according to grazer size classes. 2. We examine two possible sources of spatial variability on rocky shores: (i) across-shore variability and (ii) size class of grazers. We combined this approach with an across-shore experiment, with experimental blocks running continuously from low to high shore, to examine the spatial structure of the effect strength of grazing for different size classes of grazers. 3. The results indicate that grazing effects vary among zones, habitats and grazer size classes. Micrograzers played a weak role in structuring the algal community and composition. Both macrograzers and mesograzers were important structuring agents on the upper low shore to the mid shore, but only mesograzers were important in tidal pools. Patterns across the shore of grazing effects were dynamic and patchy, acting simultaneously at different scales. The spatial pattern of grazing effects across the shore was also variable in time and was explained by the interactions among physical and biotic factors, often at the longer (10-m scale) spatial intervals (or lags); mesograzers influenced almost the whole range of lags. 4. We conclude, based on cross-semivariograms, that abiotic factors set variability at large scales, while the effects of biotic factors (in this case grazing) operate simultaneously at scales ranging from small to large. 5. Synthesis. Combining zonation and across-shore experiments indicates that grazing effects do not follow a continuous gradient, but instead have a patchy distribution. This approach provides information about spatial variability that is not available using only the traditional approach, contributing to our understanding of zonation models.