eDNA-based diversity and multitrophic network reveal the effects of land use and pollutants on the subtropical Dongjiang River systems

Soil eDNA biomonitoring reveals changes in multitrophic biodiversity and ecological health of agroecosystems

Soil health is integral to sustainable agroecosystem management. Current monitoring and assessment practices primarily focus on soil physicochemical properties, yet the perspective of multitrophic biodiversity remains underexplored. Here we used environmental DNA (eDNA) technology to monitor multitrophic biodiversity in four typical agroecosystems, and analyzed the species composition and diversity changes in fungi, bacteria and metazoan, and combined with the traditional physicochemical variables to establish a soil health assessment framework centered on biodiversity data. First, eDNA technology detected rich multitrophic biodiversity in four agroecosystems, including 100 phyla, 273 classes, 611 orders, 1026 families, 1668 genera and 1146 species with annotated classification, and the relative sequence abundance of dominant taxa fluctuates tens of times across agroecosystems. Second, significant differences in soil physicochemical variables such as organic matter (OM), total nitrogen (TN) and available phosphorus (AP) were observed among different agroecosystems, nutrients were higher in cropland and rice paddies, while heavy metals were higher in fish ponds and lotus ponds. Third, biodiversity metrics, including α and β diversity, also showed significant changes across agroecosystems, the soil biota was generally more sensitive to nutrients (e.g., OM, TN or AP), while the fungal communities were mainly affected by heavy metals in October (e.g., Cu and Cr). Finally, we screened 48 sensitive organismal indicators and found significant positive consistency between the developed eDNA indices and the traditional soil quality index (SQI, reaching up to R2 = 0.58). In general, this study demonstrated the potential of eDNA technology in soil health assessment and underscored the importance of a multitrophic perspective for efficient monitoring and managing agroecosystems.

Assembly mechanism and stability of zooplankton communities affected by China's south-to-north water diversion project

Water diversion can effectively alleviate water resource shortages and improve water environmental conditions, while also causing unknown ecological consequences, in particular, the assembly mechanism of zooplankton communities in the affected areas will become more complex after long-term water transfer. Taking Nansi Lake, the second largest impounded lake along the eastern route of China's South to North Water Diversion Project (SNWDP), as an example, the composition and diversity of zooplankton communities in the lake area and estuaries during the water diversion period (WDP) and non-water diversion period (NWDP) were studied. The potential assembly process of zooplankton communities was further explored, and the stability of communities in different regions during different periods was compared. The related results indicated that the changes in water quality conditions induced by water diversion had a relatively weak impact on the zooplankton communities. In the assembly mechanism of zooplankton communities, stochastic process played a more important role during both WDP or NWDP, and the proportion of deterministic process was relatively higher during NWDP, which may be related to the greater role of total nitrogen (TN) in the assembly of the zooplankton communities. The network analysis and cohesion calculation results showed that the stability of the zooplankton communities in the lake area sites was higher than that in the estuary sites, and the stability during NWDP was higher than that during WDP. In sum, the stability of zooplankton communities displayed a degree of change affected by water diversion activities, but the community assembly was not significantly influenced by the water quality fluctuations after about relatively long-term water diversion. This study provides an in-depth understanding of the ecological effects of water diversion on the biological communities in the affected lake, which is beneficial to the management and regulation of long-term water diversion projects.

Water quality drives the reconfiguration of riverine planktonic microbial food webs

The food web is a cycle of matter and energy within river ecosystems. River environmental changes resulting from human activities are increasingly threatening the composition and diversity of global aquatic organisms and the multi-trophic networks. How multiple environmental factors influence food web patterns among multi-trophic microbial communities in rivers remains largely unknown. Using water quality evaluation and meta-omics techniques, we investigated the composition, structure and interaction characteristics, and drivers of food webs of microorganisms (archaea, bacteria, fungi, protists, metazoa, viridiplantae and viruses) at multiple trophic levels in different water quality environments (Classes II, III, and IV). First, water quality deterioration led to significant changes in the composition of the microbial community at multiple trophic levels, which were represented by the enrichment of Euryarchaeota in the archaeal community, the increase of r-strategists in the bacterial community, and the increase of the proportion of predators in the protist community. Second, deteriorating water quality resulted in a significant reduction in the dissimilarity of community structure (homogenization of community structure in Class III and IV waters). Of the symbiotic, parasitic, and predatory networks, the community networks in Class II water all showed the most stable symbiotic, parasitic, and predatory correlations (higher levels of modularity in the networks). In Class III and IV waters, nutrient inputs have led to increased reciprocal symbiosis and decreased competition between communities, which may have the risk of a positive feedback loop driving a system collapse. Finally, inputs of phosphorus and organic matter could be the main drivers of changes in the planktonic microbial food web in the Fen River. Overall, the results indicated the potential ecological risks of exogenous nutrient inputs, which were important for aquatic ecosystem conservation.

Environmental DNA and remote sensing datasets reveal the spatial distribution of aquatic insects in a disturbed subtropical river system

Biodiversity datasets with high spatial resolution are critical prerequisites for river protection and management decision-making. However, traditional morphological biomonitoring is inefficient and only provides several site estimates, and there is an urgent need for new approaches to predict biodiversity on fine spatial scales throughout the entire river systems. Here, we combined the environmental DNA (eDNA) and remote sensing (RS) technologies to develop a novel approach for predicting the spatial distribution of aquatic insects with high spatial resolution in a disturbed subtropical Dongjiang River system of southeast China. First, we screened thirteen RS-based vegetation indices that significantly correlated with the eDNA-inferred richness of aquatic insects. In particular, the green normalized difference vegetation index (GNDVI) and normalized difference red-edge2 (NDRE2) were closely related to eDNA-inferred richness. Second, using the gradient boosting decision tree, our data showed that the spatial pattern of eDNA-inferred richness could achieve a high spatial resolution to 500 m reach and accurate prediction of more than 80%, and the prediction efficiency of the headwater streams (Strahler stream order = 1) was slightly higher than the downstream (Strahler stream order >1). Third, using the random forest algorithm, the spatial distribution of aquatic insects could reach a prediction rate of over 70% for the presence or absence of specific genera. Overall, this study provides a new approach to achieving high spatial resolution prediction of the distribution of aquatic insects, which supports decision-making on river diversity protection under climate changes and human impacts.