Characterizing the spatial distribution and variation of species communities and validating these characteristics with data from the field are key elements for an ecosystem-based approach to management. However, models of species distributions that yield community structure are usually not linked to models of community dynamics, constraining understanding and management of the ecosystem, particularly in data-poor regions. Here we use a qualitative network model to predict changes in Antarctic benthic community structure between major marine habitats characterized largely by seafloor depth and slope, and use multivariate mixture models of species distributions to validate the community dynamics. We then assess how future increases in primary production associated with anticipated loss of sea-ice may affect the ecosystem. Our study shows how both spatial and structural features of ecosystems in data-poor regions can be analyzed and possible futures assessed, with direct relevance for ecosystem-based management.

中文翻译：

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对深层底栖海洋群落的空间分布和结构动力学的综合评估。

表征物种群落的空间分布和变化，并利用实地数据验证这些特征，是基于生态系统的管理方法的关键要素。但是，产生群落结构的物种分布模型通常不与群落动态模型联系在一起，从而限制了对生态系统的理解和管理，特别是在数据贫乏地区。在这里，我们使用定性网络模型来预测主要以海底深度和坡度为特征的主要海洋生境之间的南极底栖生物群落结构的变化，并使用物种分布的多元混合模型来验证群落动态。然后，我们评估与预期海冰流失相关的初级生产的未来增长可能如何影响生态系统。