Departamento de Biologia Animal, Instituto de Biologia, Universidade Estadual de Campinas, Campinas, 13.083-862, São Paulo, Brazil.
School of Marine and Environmental Affairs, University of Washington, Seattle, WA 98105, Washington, USA.
Ecology. 2020 Jul;101(7):e03080. doi: 10.1002/ecy.3080. Epub 2020 May 21.
Biodiversity loss is a hallmark of our times, but predicting its consequences is challenging. Ecological interactions form complex networks with multiple direct and indirect paths through which the impacts of an extinction may propagate. Here we show that accounting for these multiple paths connecting species is necessary to predict how extinctions affect the integrity of ecological networks. Using an approach initially developed for the study of information flow, we estimate indirect effects in plant-pollinator networks and find that even those species with several direct interactions may have much of their influence over others through long indirect paths. Next, we perform extinction simulations in those networks and show that although traditional connectivity metrics fail in the prediction of coextinction patterns, accounting for indirect interaction paths allows predicting species' vulnerability to the cascading effects of an extinction event. Embracing the structural complexity of ecological systems contributes towards a more predictive ecology, which is of paramount importance amid the current biodiversity crisis.
生物多样性的丧失是我们这个时代的一个标志，但预测其后果具有挑战性。生态相互作用形成了复杂的网络，其中有多种直接和间接的路径，灭绝的影响可以通过这些路径传播。在这里，我们表明，考虑到连接物种的这些多种路径，对于预测灭绝如何影响生态网络的完整性是必要的。我们使用最初为研究信息流而开发的方法来估计植物-传粉者网络中的间接效应，并发现即使是那些具有多种直接相互作用的物种，也可能通过长的间接路径对其他物种产生很大的影响。接下来，我们在这些网络中进行灭绝模拟，并表明尽管传统的连通性指标在预测共同灭绝模式方面存在缺陷，但考虑到间接相互作用路径可以预测物种对灭绝事件级联效应的脆弱性。接受生态系统结构复杂性有助于实现更具预测性的生态学，在当前的生物多样性危机中，这一点至关重要。
