Abstract

Global biodiversity is affected by human pressure and climate change, and the present rate of biodiversity loss is probably higher than ever before. Community composition is also changing, and interspecific interactions are under severe pressure. The extinction of one species within a food web can result in further secondary extinctions, due to bottom‐up effects that can be even more intense and less predictable than the direct effects of disturbance, undermining our capacity for ecosystem management and conservation. Here we investigated a metric for assessing the structural stability of food webs in the face of species loss, referred to as “Resistance”, based on two fundamental web properties: (1) the proportion of key species in the web, a “key” species being one whose deletion leads to at least one secondary extinction, and (2) the mean number of secondary extinctions observed per key species deletion. We compared web Resistance with web Robustness (Dunne et al. 2002) based on 12 detritus‐based riverine food webs under four species extinction scenarios on various temporal and spatial scales. We investigated the effect of multiple disturbances (extreme flood and river basin urbanization) on community vulnerability to biodiversity loss, assessing the behavior of Robustness and Resistance under the applied species extinction scenarios and testing their dependence on web topology. We estimated the contribution of the rarest and the most dominant species, and that of the most and least connected species, to web Resistance.Urbanization negatively affected community vulnerability to biodiversity loss. Only food web Resistance showed a significant flood effect and interaction between flood and urbanization. The most connected species contributed the most to food web resistance, whereas the rarest and the most abundant species had a similar, intermediate structural importance. Both food web Resistance and the role of selected key species varied across web description scales. Food web Resistance values were coherent across species extinction scenarios, demonstrating the suitability of the proposed approach for quantifying community vulnerability to species loss and the importance of considering food webs in monitoring and impact assessment programs. The approach is thus seen to be a promising research pathway supporting ecosystem management.

Highlights

  • Worldwide species extinction is occurring at a rate probably higher than ever before, driven by numerous interconnected factors (M.E.A. 2005)

  • Mean RC was significantly different at both sampling locations after the flood, and a combined effect of flood and river basin urbanization was detected (Table 1 and Fig. 2)

  • Metrics of food web structural stability such as Robustness and Resistance do not directly take account of dynamic changes in population abundance or potential diet shifts of consumers through space and time, the study of food web response to species extinction can make a meaningful contribution to more traditional monitoring and conservation approaches (Dunne et al 2002, May 2009)

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Summary

Introduction

Worldwide species extinction is occurring at a rate probably higher than ever before, driven by numerous interconnected factors (M.E.A. 2005). The local extinction of a species within an ecological network can result in further secondary extinctions, due to indirect effects along food webs that can be even more intense and less predictable than what is expected from the direct effects of disturbance (Dunne et al 2002, Tylianakis et al 2008, Beckerman et al 2010, Petchey et al 2010) Such unpredictability in ecological response, mediated by food web structure, could seriously undermine the ability of scientists and policy makers to cope with future environmental changes, weakening ecosystem management and conservation efforts. Information on the vulnerability of river communities to disturbance and to the possible consequent local extinction of species is urgently needed, in order to ensure informed management of lotic environments under global change scenarios

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