PRJNA555584
Network-based biomonitoring: freshwater food webs, stable isotope analysis, DNA metabarcoding
Threatened freshwater ecosystems urgently require improved tools for effective management. Food web analysis is currently under-utilised, yet can be used to generate metrics to support biomonitoring assessments by measuring the stability and robustness of ecosystems. Using a previously developed analysis pipeline, we combined taxonomic outputs from DNA metabarcoding with a text-mining routine to extract trait information directly from the literature. This pipeline allowed us to generate heuristic food webs for sites within the Grand Lake Meadows (GLM), Atlantic Canada's largest wetland complex. While these food webs are derived from empirical traits and their structure has been shown to discriminate sites both spatially and temporally, the accuracy of their properties have not been assessed against other methods of trophic analysis. We explored two approaches to validate the utility of heuristic food webs. First, we qualitatively compared how well trophic position derived from heuristic food webs recovered spatial and temporal differences across the GLM complex in comparison to traditional stable isotope approaches. Second, we explored how the trophic position of invertebrates, derived from heuristic food webs, predicted trophic position measured from d15N values. In general, both heuristic food webs and stable isotopes were able to detect seasonal changes in maximum trophic position in the GLM complex. Samples from the entire GLM complex demonstrated that prey-averaged trophic position measured from heuristic food webs strongly predicted trophic position inferred from stable isotopes (R2 = 0.60), and even stronger relationships were possible for some individual models (R2 = 0.78 for best model). Beyond their areas of similarity, the heuristic food web pipeline and stable isotope analysis also appear to complement one another, suggesting a surprising degree of independence between community trophic niche width (assessed from stable isotopes) and food web size and complexity (assessed from heuristic food webs). Collectively, these analyses indicate that trait-based networks do generate properties that correspond to those of actual food webs, and support the routine adoption of food web metrics within ecosystem biomonitoring.