Centre for Biodiversity Theory and Modelling, Theoretical and Experimental Ecology Station, CNRS-Paul Sabatier University, Moulis, 09200, France.
Department of Biosciences, Swansea University, Singleton Park, Swansea, SA2 8PP, United Kingdom.
Ecology. 2020 Nov;101(11):e03165. doi: 10.1002/ecy.3165. Epub 2020 Sep 16.
Understanding the drivers of geographical variation in species distributions, and the resulting community structure, constitutes one of the grandest challenges in ecology. Geographical patterns of species richness and composition have been relatively well studied. Less is known about how the entire set of trophic and non-trophic ecological interactions, and the complex networks that they create by gluing species together in complex communities, change across geographical extents. Here, we compiled data of species composition and three types of ecological interactions occurring between species in rocky intertidal communities across a large spatial extent (~970 km of shoreline) of central Chile, and analyzed the geographical variability in these multiplex networks (i.e., comprising several interaction types) of ecological interactions. We calculated nine network summary statistics common across interaction types, and additional network attributes specific to each of the different types of interactions. We then investigated potential environmental drivers of this multivariate network organization. These included variation in sea surface temperature and coastal upwelling, the main drivers of productivity in nearshore waters. Our results suggest that structural properties of multiplex ecological networks are affected by local species richness and modulated by factors influencing productivity and environmental predictability. Our results show that non-trophic negative interactions are more sensitive to spatially structured temporal environmental variation than feeding relationships, with non-trophic positive interactions being the least labile to it. We also show that environmental effects are partly mediated through changes in species richness and partly through direct influences on species interactions, probably associated to changes in environmental predictability and to bottom-up nutrient availability. Our findings highlight the need for a comprehensive picture of ecological interactions and their geographical variability if we are to predict potential effects of environmental changes on ecological communities.
了解物种分布的地理变化驱动因素以及由此产生的群落结构，是生态学中最具挑战性的问题之一。物种丰富度和组成的地理模式已经得到了相对较好的研究。然而，对于整个营养和非营养生态相互作用集合，以及它们通过将物种粘合成复杂群落而创建的复杂网络，如何在地理范围内发生变化，我们知之甚少。在这里，我们编译了智利中部一个大的空间范围内（约 970 公里的海岸线）的岩石潮间带群落中物种组成和三种物种间生态相互作用的数据，并分析了这些多重网络（即包含几种相互作用类型）的地理变异性。我们计算了九个常见于所有相互作用类型的网络汇总统计量，以及每个不同相互作用类型特有的附加网络属性。然后，我们研究了这种多元网络组织的潜在环境驱动因素。这些因素包括海面温度和沿海上升流的变化，这是近岸水域生产力的主要驱动因素。我们的研究结果表明，多重生态网络的结构属性受到局部物种丰富度的影响，并受到影响生产力和环境可预测性的因素的调节。我们的结果表明，非营养负相互作用比摄食关系对空间结构的时间环境变化更为敏感，而非营养正相互作用对其变化的稳定性最低。我们还表明，环境效应部分通过物种丰富度的变化来介导，部分通过对物种相互作用的直接影响来介导，这可能与环境可预测性的变化和底栖养分的可用性有关。我们的研究结果强调，如果我们要预测环境变化对生态群落的潜在影响，需要全面了解生态相互作用及其地理变异性。
