Lamy Thomas, Reed Daniel C, Rassweiler Andrew, Siegel David A, Kui Li, Bell Tom W, Simons Rachel D, Miller Robert J
Marine Science Institute, University of California, Santa Barbara, CA, 93106, USA.
Department of Biological Science, Florida State University, Tallahassee, FL, 32304, USA.
Oecologia. 2018 Jan;186(1):217-233. doi: 10.1007/s00442-017-3994-1. Epub 2017 Nov 3.
Identifying spatial scales of variation in natural communities and the processes driving them is critical for obtaining a predictive understanding of biodiversity. In this study, we focused on diverse communities inhabiting productive kelp forests on shallow subtidal rocky reefs in southern California, USA. We combined long-term community surveys from 86 sites with detailed environmental data to determine what structures assemblages of fishes, invertebrates and algae at multiple spatial scales. We identified the spatial scales of variation in species composition using a hierarchical analysis based on eigenfunctions, and assessed how sea surface temperature (SST), water column chlorophyll, giant kelp biomass, wave exposure and potential propagule delivery strength contributed to community variation at each scale. Spatial effects occurring at multiple scales explained 60% of the variation in fish assemblages and 52% of the variation in the assemblages of invertebrates and algae. Most variation occurred over broad spatial scales (> 200 km) consistent with spatial heterogeneity in SST and potential propagule delivery strength, while the latter also explained community variation at medium scales (65-200 km). Small scale (1-65 km) community variation was substantial but not linked to any of the measured drivers. Conclusions were consistent for both reef fishes and benthic invertebrates and algae, despite sharp differences in their adult mobility. Our results demonstrate the scale dependence of environmental drivers on kelp forest communities, showing that most species were strongly sorted along oceanographic conditions over various spatial scales. Such spatial effects must be integrated into models assessing the response of marine ecosystems to climate change.
识别自然群落中变异的空间尺度及其驱动过程，对于实现对生物多样性的预测性理解至关重要。在本研究中，我们聚焦于美国加利福尼亚州南部浅海潮汐带岩石礁上高产海带森林中的多样群落。我们将来自86个地点的长期群落调查与详细的环境数据相结合，以确定在多个空间尺度上鱼类、无脊椎动物和藻类群落的构成要素。我们使用基于特征函数的层次分析来识别物种组成的空间尺度变异，并评估海面温度（SST）、水柱叶绿素、巨型海带生物量、海浪暴露程度和潜在繁殖体输送强度如何在每个尺度上对群落变异产生影响。多个尺度上出现的空间效应解释了鱼类群落变异的60%以及无脊椎动物和藻类群落变异的52%。大多数变异发生在与SST和潜在繁殖体输送强度的空间异质性一致的广泛空间尺度（>200公里）上，而后者也解释了中等尺度（65 - 200公里）上的群落变异。小尺度（1 - 65公里）的群落变异很大，但与任何测量的驱动因素均无关联。尽管礁鱼与底栖无脊椎动物和藻类在成体移动性上存在显著差异，但研究结论对二者均一致。我们的结果表明环境驱动因素对海带森林群落具有尺度依赖性，显示出大多数物种在不同空间尺度上沿着海洋学条件被强烈分选。这种空间效应必须纳入评估海洋生态系统对气候变化响应的模型中。
