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

海洋生物多样性面临的许多威胁，从气候变化到过度捕捞，都发生在非常大的地区，但我们对海洋生态的大部分知识都来自小规模的研究。因此，为了解决这种不匹配的问题，迫切需要找到扩大当地知识的方法，以便我们能够更好地了解生物多样性在与国际环境政策相关的规模上是如何分布的。已经朝着这个方向迈出了重要的第一步，努力将地方调查结果汇集到区域生物多样性数据库中。例如，已经收集了关于生活在欧洲各地海底沉积物中的各种生物（所谓的底栖物种）的分布情况的数据，从北部的北极到南部的地中海。欧洲的大部分生物多样性都存在于这些未被重视的群体中，我们的主要目标是利用这个庞大的数据库更好地了解这些非常多样化的物种是如何分布在这片非常广阔的区域中的。回到陆地上，生态学家已经开发了一系列方法来解决这些问题。我们计划使用一种方法，适用于到目前为止只在相当小的规模，它使用一个简单的几何过程来预测如何一个给定数量的个体生物可能分布在所有样本的调查植被调查的分析。这一过程可以应用于物种，并产生一系列关于生物多样性大规模分布的预测，例如预计在给定地区观察到的物种数量，以及常见和稀有物种的相对数量。这一方法在应用于欧洲底栖物种时将非常有用，原因有二。首先，与理论预测的一般一致性有助于确定我们观察到的生物多样性模式的一般原则。第二，也许更重要的是，我们的观察与理论预测的不同之处，可以大大有助于解释哪些存在于真实的生活中而非理论中的特征（例如，物种之间的生物差异）对生物多样性的空间分布实际上是重要的。我们可以再次利用生态学理论来预测在这方面可能很重要的生物学特征--例如，我们预计，产生浮游生物中漂流的幼虫的物种的种群结构将不同于后代直接在成年人附近发育的物种。但生物学并不是唯一可能影响多样性模式的因素。另一个例子是，我们预计受人类活动严重影响的地区的模式会有所不同-例如，我们知道底栖生物群落可能受到某些种类的商业捕鱼，特别是拖网捕鱼的严重影响-与相对较原始的地区相比。作为我们项目的一部分，我们计划从我们数据库中的物种生物学文献中收集数据，以及不同地区的环境特征（包括人类影响），以便我们验证这些假设。虽然总的来说，我们对陆地生物多样性的了解要比海洋生物多样性多得多，但事实证明，我们可以用新的海洋数据库解决的一些问题很难在陆地上进行测试。因此，我们的研究结果将对所有致力于大规模生物多样性模式的生态学家产生极大的兴趣。通过在以陆地生态学研究为主的大学部门和领先的海洋研究所之间建立合作，我们将处于一个令人羡慕的位置，将我们的工作成果传达给尽可能广泛的受众。除了扩大海洋生物多样性研究的规模，我们还希望扩大海洋和陆地生态学家的视野。

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.