Abteilung Aquatische Ökologie

Biotic interactions and environmental changes due to increasing water temperatures, nutrient enrichment, and other factors can affect species diversity, abundance, and distribution. Lake Superior is the deepest and one of the most oligotrophic lakes in the Laurentian Great Lakes system. While considered the least affected by cultural eutrophication, Lake Superior is among the world's fastest-warming freshwater bodies, having already exhibited resulting physical and ecological changes over the past three decades. We used data from current and historical surveys to identify spatial patterns and provide an assessment of the status and temporal trends of the Lake Superior benthic community over the last 50 years. Our study indicated that the dominance structure of the community remained quite stable, with the highest proportion of community comprised by the deepwater amphipod Diporeia hoyi, followed by Oligochaeta, Sphaeriidae, and Chironomidae. Benthic community structure differed spatially, with higher species diversity found in the shallow zone (≤30 m), the highest Diporeia densities at intermediate depth zones (30–50 and 50–90 m), and the lowest densities of all taxa in the deepest zone (>90 m). Lakewide benthos densities increased in the 1990s–2000s, most likely due to reduced fish predation, but are now stabilized. Although current benthos densities are still higher than in the 1970s, nearshore surveys indicated declines in Diporeia and other major taxa in the last decade. These changes may indicate a return to levels observed in the 1970s or reflect a long-term trend of decline in populations, reinforcing the importance of frequent monitoring that could foretell lakewide changes.

Understanding the robustness of ecological networks against sustained species losses is paramount to devising effective biodiversity conservation strategies. To explore the impacts of species losses on network robustness (the capacity of food webs to withstand primary extinctions), we used a trophic metaweb of 7808 vertebrates, invertebrates and plants and 281,023 interactions across Switzerland. We inferred twelve regional multi-habitat food webs and simulated non-random species extinction scenarios on these webs, focusing on broad habitat types and regional species abundances. Here, we show that targeted removal of species associated with specific habitat types, particularly wetlands, resulted in greater network fragmentation and accelerated network collapse compared to random species removals. Networks were more vulnerable to the initial loss of common rather than rare species. These findings underscore the critical need for integrated conservation strategies maintaining a diverse mosaic of habitats in a landscape to mitigate the cascading effects of species loss. (Figure presented.)

Understanding how species interact within ecological networks is essential for predicting the consequences of environmental change, from trophic cascades to broader changes in species distributions and ecosystem functioning across large spatial scales. To facilitate such explorations, we constructed trophiCH: a country-level trophic meta-food web (henceforth “metaweb”) that includes vertebrates, invertebrates, and vascular plants within Switzerland, based on literature published between 1862 and 2023. Our comprehensive dataset catalogues 1,112,073 trophic interactions involving 23,151 species and 125 feeding guilds (e.g., fungivores). Thirty percent of species-level interactions were empirically documented. Additional species-level interactions were inferred by resolving coarser taxonomic records (e.g., inferring links from “species A feeds on genus B”) based on habitat co-occurrences. While explorations of large-scale food webs have often relied on modelling approaches due to data gaps, this empirically based metaweb paves the way for data-driven studies of real-world food webs across space and time. By integrating the metaweb with local species assemblages knowledge, future studies can gain insights into broad patterns of food web structure across spatial scales.