Water diversion and pollution interactively shape freshwater food webs through bottom-up mechanisms

Abstract

[EN] Water diversion and pollution are two pervasive stressors in river ecosystems that often co-occur. Individual effects of both stressors on basal resources available to stream communities have been described, with diversion reducing detritus standing stocks and pollution increasing biomass of primary producers. However, interactive effects of both stressors on the structure and trophic basis of food webs remain unknown. We hypothesized that the interaction between both stressors increases the contribution of the green pathway in stream food webs. Given the key role of the high-quality, but less abundant, primary producers, we also hypothesized an increase in food web complexity with larger trophic diversity in the presence of water diversion and pollution. To test these hypotheses, we selected four rivers in a range of pollution subject to similar water diversion schemes, and we compared food webs upstream and downstream of the diversion. We characterized food webs by means of stable isotope analysis. Both stressors directly changed the availability of basal resources, with water diversion affecting the brown food web by decreasing detritus stocks, and pollution enhancing the green food web by promoting biofilm production. The propagation of the effects at the base of the food web to higher trophic levels differed between stressors. Water diversion had little effect on the structure of food webs, but pollution increased food chain length and trophic diversity, and reduced trophic redundancy. The effects at higher trophic levels were exacerbated when combining both stressors, as the relative contribution of biofilm to the stock of basal resources increased even further. Overall, we conclude that moderate pollution increases food web complexity and that the interaction with water abstraction seems to amplify this effect. Our study shows the importance of assessing the interaction between stressors to create predictive tools for a proper management of ecosystems.