100 years of anthropogenic impact causes changes in freshwater functional biodiversity

Abstract

Despite efforts from scientists and regulators, biodiversity is declining at an alarming rate. Unless we find transformative solutions to preserve biodiversity, future generations may not be able to enjoy nature's services. We have developed a conceptual framework that establishes the links between biodiversity dynamics and abiotic change through time and space using artificial intelligence. Here, we apply this framework to a freshwater ecosystem with a known history of human impact and study 100 years of community-level biodiversity, climate change and chemical pollution trends. We apply explainable network models with multimodal learning to community-level functional biodiversity measured with multilocus metabarcoding, to establish correlations with biocides and climate change records. We observed that the freshwater community assemblage and functionality changed over time without returning to its original state, even if the lake partially recovered in recent times. Insecticides and fungicides, combined with extreme temperature events and precipitations, explained up to 90% of the functional biodiversity changes. Community-level biodiversity reliably explained freshwater ecosystem shifts whereas traditional quality indices (e.g. Trophic Diatom Index) and physicochemical parameters proved to be poor metrics for these shifts. Our study advocates the advantage of high throughput systemic approaches on long-term trends over species-focused ecological surveys to identify the environmental factors that cause loss of biodiversity and disrupt ecosystem functions.

Single metabarcoding multiplex captures community‐level freshwater biodiversity and beyond

“…Because environmental change affects taxonomic groups differently, ignoring the biotic interactions of a species within its food web can lead to wrong estimation of effects (Fricke et al., 2022; Urban et al., 2016). Only by capturing the response of entire communities to environmental change, can we begin to understand the diagnostic links between environmental drivers and loss of biodiversity (Eastwood et al., 2022, 2023; Li et al., 2023; Urban et al., 2016).…”

“…We modified this protocol by multiplexing four loci in PCR1 (Figure 1). The multiplex protocol was optimized on randomly selected bulk environmental DNA (eDNA) samples extracted from a freshwater lake sediment core from a previous study (Eastwood et al., 2023) using DNeasy PowerSoil kit (Qiagen) ( seda DNA), following the manufacturer instructions, in a PCR free environment. Extraction and PCR blanks were used to monitor for contamination.…”

“…We optimized this protocol for lake freshwater communities because these communities support humans and wildlife (Darwall et al., 2018), and have high conservation value, delivering important ecosystem services (e.g., clean water, food provision, and recreation) (Dudgeon et al., 2006; Ruckelshaus et al., 2020). The samples used for this protocol optimization were a subset of samples isolated from a well‐characterized sedimentary archive (see (Eastwood, 2023) for details). In this previous study, a traditional single locus approach was applied to eDNA extracted from sediment samples, providing reassurance on the quality of the input DNA used in this study.…”

“…A multi‐locus approach is highly desirable to deliver community‐level assessments in a cost‐effective manner (Ficetola & Taberlet, 2023). However, thus far, community‐level assessments of biodiversity have only been achieved with the integration of results from individual loci (Eastwood et al., 2022, 2023; Li et al., 2023). A multi‐locus approach improves the robustness of taxonomic assignment alleviating false negatives caused by random missed amplifications of target genes caused for example by DNA degradation or mutation in primer sites (Zhan et al., 2014).…”