Extending the scale of marine biodiversity research: spatial models of the European macrobenthos

Many of the threats facing marine biodiversity, from climate change to overfishing, occur over very large areas, yet most of our knowledge of marine ecology is derived from rather small-scale studies. To address this mismatch, there is therefore a pressing need to find ways to scale up local knowledge so that we can gain a better understanding of how biodiversity is distributed at scales relevant to international environmental policy. An important first step in this direction has already been taken, through efforts to pool the results of local surveys into regional biodiversity databases. For instance, data on the distribution of all kinds of organisms living in the sediment at the bottom of the sea (so-called benthic species) throughout Europe have been gathered together, from the Arctic in the north to the Mediterranean in the south. Much of Europe's biodiversity is to be found among such underappreciated groups, and our principle aim is to use this huge database to gain a better understanding of how these very diverse species are distributed over this very large area. Back on dry land, ecologists have developed a range of methods to address such questions. We plan to use a method applied so far only to the analysis of vegetation surveys at rather small scales, which uses a simple a geometric process to predict how a given number of individual organisms are likely to be distributed between all samples in the survey. This process can be applied across species, and produces a series of predictions regarding the large-scale distribution of biodiversity, such as the number of species expected to be observed in a given area, and the relative numbers of common and rare species. This approach will be really useful when applied to the European benthic species for two reasons. First, a general agreement with the predictions of the theory is useful in determining the general principles responsible for the patterns of biodiversity that we observe. Second, perhaps more importantly, the way in which our observations differ from the theoretical predictions can go a long way towards explaining which kinds of features present in real life but not in the theory (for example, biological differences between species) are actually important in terms of the spatial distribution of biodiversity. We can again draw on ecological theory to make predictions about the biological characteristics likely to be important in this respect - for instance, we expect that the population structure of species which produce larvae that drift in the plankton will differ from species in which offspring develop in direct proximity to the adults. But biology is not the only thing likely to influence patterns of diversity. As another example, we expect patterns to differ in areas which are heavily impacted by human activities - for instance, we know that benthic communities can be significantly affected by certain kinds of commercial fishing, particularly trawling - compared with areas which are relatively more pristine. As part of our project, we plan to collect data from the literature on both the biology of the species in our database, and on features of the environment (including human impacts) in different areas, to allow us to test such hypotheses. Although in general we know much more about terrestrial than marine biodiversity, some of the questions we can address with new marine databases have actually proved very difficult to test on land. Our results will therefore be of great interest to all ecologists working on large scale patterns of biodiversity. By establishing a collaboration between a university department dominated by the study of terrestrial ecology and a leading marine institute, we will be in an enviable position to communicate the results of our work to as wide an audience as possible. As well as extending the scale of marine biodiversity research, then, we hope also to expand the horizons of marine and terrestrial ecologists.