Assessing the effects of cascade dams on river ecological status using multi-species interaction-based index of biotic integrity (Mt-IBI)

Integrated evaluation of the impact of water diversion on water quality index and phytoplankton assemblages of eutrophic lake: A case study of Yilong Lake

Water diversion has been widely utilized to enhance lake water quality and mitigate cyanobacterial blooms. However, previous studies have mainly focused on investigating the effects of water diversion on water quality or aquatic ecological health. Consequently, there is limited research investigating the combined impact of water diversion on the water quality and the ecological health of eutrophic lakes, and whether the WQI and phytoplankton assemblages demonstrate similar patterns following water diversion. In this study, the effects of water diversion on the ecosystem health of eutrophic lakes were comprehensively evaluated based on the WQI indices and phytoplankton assemblages during the NWDP-21 and WDP-22. The results showed that the annual mean of WQI increased from 52.02 to 54.36 after water diversion, which improved the water quality of the lake, especially NH3-N and TN decreased by 58.6% and 15.2%, respectively. The phytoplankton assemblages changed significantly before and after water diversion, and we observed that the total biomass of phytoplankton decreased by 12.3% and phytoplankton diversity indices (Shannon-Wiener diversity, Pielou evenness, and Simpson index) increased by 8.6%-8.9% after water diversion, with an improvement in the connectivity and stability of the phytoplankton. Notably, enhanced adaptations of rare sub-communities for resource use in water diversion environments, and water diversion inhibited the dispersal ability of dominant functional groups, and the effects of hydrological disturbances on the structure of phytoplankton assemblage favored the ecological health of eutrophic lakes. VPA analysis further reveals that water diversion alters the drivers of phytoplankton functional group biomass and phytoplankton diversity. The results of the PLS-PM analysis clarify that water diversion indirectly impacts the total phytoplankton biomass and phytoplankton diversity primarily by modifying light availability. Significant correlations are observed between the dominant functional groups biomass and diversity indices of WQI. The trends in changes observed in water quality indices and phytoplankton following water diversion align with the evaluation of water ecological health. This study provides valuable guidance for the ecological management of the diversion project in Yilong Lake and serves as a reference for similar projects in other lakes.

Supervised machine learning improves general applicability of eDNA metabarcoding for reservoir health monitoring

Effective and standardized monitoring methodologies are vital for successful reservoir restoration and management. Environmental DNA (eDNA) metabarcoding sequencing offers a promising alternative for biomonitoring and can overcome many limitations of traditional morphological bioassessment. Recent attempts have even shown that supervised machine learning (SML) can directly infer biotic indices (BI) from eDNA metabarcoding data, bypassing the cumbersome calculation process of BI regardless of the taxonomic assignment of eDNA sequences. However, questions surrounding the general applicability of this taxonomy-free approach to monitoring reservoir health remain unclear, including model stability, feature selection, algorithm choice, and multi-season biomonitoring. Here, we firstly developed a novel biological integrity index (Me-IBI) that integrates multitrophic interactions and environmental information, based on taxonomy-assigned eDNA metabarcoding data. The Me-IBI can better distinguish the actual health status of the Three Gorges Reservoir (TGR) than physicochemical assessments and have a clear response to human activity. Then, taking this reliable Me-IBI as a supervised label, we compared the impact of selecting different numbers of features and SML algorithms on the stability and predictive performance of the model for predicting ecological conditions in multiple seasons using taxonomy-free eDNA metabarcoding data. We discovered that even with a small number of features, different SML algorithms can establish a stable model and obtain excellent predictive performance. Finally, we proposed a four-step strategy for standardized routine biomonitoring using SML tools. Our study firstly explores the general applicability problem of the taxonomy-free eDNA-SML approach and establishes a solid foundation for the large-scale and standardized biomonitoring application.

Exploring a multi-objective optimization operation model of water projects for boosting synergies and water quality improvement in big river systems

Due to excessive nutrient enrichment and rapidly increasing water demand, the occurrence of riverine environment deterioration events such as algal blooms in rivers of China has become more frequent and severe since the 1990s, which has imposed harmful consequences on riverine ecosystems. However, tackling river algal blooms as an important issue of restoring riverine environment is very challenging because the complex interaction mechanisms between the causes are impacted by multiple factors. The contributions of our study consist of: (1) optimizing joint operation of water projects for boosting synergies of water quality and quantity, and hydroelectricity; and (2) preventing algal bloom from perspectives of hydrological and water-quality conditions by regulating water releases of water projects. This study proposed a multi-objective optimization methodology grounded on the Non-dominated Sorting Genetic Algorithm to simultaneously minimize the excess values of algal bloom indicators (water quality, O1), minimize the used reservoir capacity for water supply (water quantity, O2), and maximize the hydropower generation (hydroelectricity, O3). The proposed methodology was applied to several catastrophic algal bloom events that took place between 2017 and 2021 and thirteen water projects in the Hanjiang River of China. The results indicated that the proposed methodology largely stimulated the synergistic benefits of the three objectives by reaching a 36.7% reduction in total nitrogen and phosphorus concentrations, a 33.1% improvement in the remaining reservoir capacity, and a 41.0% improvement in hydropower output, as compared with those of the standard operation policy (SOP). In addition, the optimal water release schemes of water projects would increase the minimum streamflow velocity of downstream algal bloom control stations by 8.6%-9.4%. This study provides a new perspective on water project operation in the environmental improvement in big river systems while boosting multi-objectives synergies to support environmentalists and decision-makers with scientific guidance on sustainable water resources management.

Improved method for benthic ecosystem health assessment by integrating chemical indexes into multiple biological indicator species-A case study of the Baiyangdian Lake, China

A comprehensive and scientific assessment of benthic ecosystem health is key to the rational selection of endogenous pollution reduction technologies for lakes. However, current assessments are mainly limited to biological indicators and ignore the actual benthic ecosystem situations, such as the impact of eutrophication and heavy metal pollution, which may lead to the one-sidedness of the evaluation results. In this study, taking Baiyangdian Lake, the largest shallow mesotrophic-eutrophic lake in the North China Plain, as an example, the chemical assessment index and biological integrity index were first combined to estimate the biological conditions, nutritional status and heavy metal pollution of lakes. The indicator system incorporated three biological assessments (benthic index of biotic integrity (B-IBI), submerged aquatic vegetation index of biological integrity (SAV-IBI) and microbial index of biological integrity (M-IBI)) and three chemical assessments (dissolved oxygen (DO), comprehensive trophic level index (TLI) and index of geoaccumulation (I_geo)). Twenty-three attributes of B-IBI, fourteen attributes of SAV-IBI and twelve attributes of M-IBI were screened by range, responsiveness, and redundancy tests to keep the core metrics that were significantly correlated with disturbance gradients or showed strong discriminatory power between reference and impaired sites. The assessment results of B-IBI, SAV-IBI, and M-IBI showed significant differences in the response to anthropogenic activities and seasonal change, among which the submerged plants showed more significant seasonal differences. It is difficult to reach a comprehensive conclusion regarding the benthic ecosystem health status based on a single biological community. In comparison with biological indicators, the score of chemical indicators is relatively low. DO, TLI and I_geo provide an essential supplement for the benthic ecosystem health assessment of lakes with eutrophication and heavy metal pollution problems. Using the new integrated assessment method, the benthic ecosystem health of Baiyangdian Lake was rated as fair, especially the northern parts of the lake adjacent to the inflow mouth of the Fu River, which were in poor condition, indicating that the lake has experienced anthropogenic disturbance, resulting in eutrophication, heavy metal pollution and biological community degradation. Whether it's spring or summer, the integrated assessment method provides a more plausible and comprehensive view of benthic ecosystem health under the pressure of increasing human activities and changing habitat and hydrological conditions, overcoming the narrow perspective and uncertainties of the single-index method. Thus, it can assist lake managers in providing technical support for ecological indication and restoration.

Evaluation and comparison of the benthic and microbial indices of biotic integrity for urban lakes based on environmental DNA and its management implications

With the intensification of human disturbance in urban lakes, the loss of eukaryotic biodiversity (macroinvertebrates, etc.) reduces the accuracy of the index of biotic integrity (IBI) assessment. Therefore, how to accurately evaluate the ecological status of urban lakes based on IBI has become an important issue. In this study, 17 sampling sites from four lakes in Wuhan City, China were selected to analyze the composition and diversity characteristics of benthic and microbial communities and their relationship with environmental factors based on eDNA high-throughput sequencing, and compare the application effects of the benthic index of biotic integrity (B-IBI) and the microbial index of biotic integrity (M-IBI). Canonical correspondence analysis showed that the key environmental factors affecting benthic family/genus composition were temperature, conductivity, total phosphorus (TP), and total nitrogen (TN). Redundancy analysis showed that pH, TP, conductivity, and ammonia nitrogen had the greatest impact on microbial phyla/genera. After screening, four and six core metrics were determined from candidate parameters to establish B-IBI and M-IBI. The B-IBI evaluation results showed that healthy, sub-heathy, and poor accounted for 58.8%, 35.3%, and 5.9%, respectively, in the sites. The results of the M-IBI evaluation showed that 29.4% of the sites were healthy, 47.1% were sub-healthy, and 23.5% were common. M-IBI was positively correlated with water quality (r = 0.74, P < 0.001), whereas B-IBI was not. Further results showed that M-IBI was negatively correlated with the relative abundance of bloom-forming cyanobacteria Planktothrix (r = -0.54, P < 0.05). Therefore, M-IBI is more sensitive than B-IBI and can better reflect the actual water pollution status. This study can provide a new perspective for ecological assessment and management of urban lakes strongly disturbed by human activities.

Phytoplankton community variation and ecological health assessment for impounded lakes along the eastern route of China's South-to-North Water Diversion Project

Interbasin water diversion projects have been proven to effectively alleviate water resource shortages in areas along water diversion lines, but few studies have focused on ecological health in impounded lakes compared with research on water quality and pollutants. Herein, monitoring data were collected during the nonwater diversion period (NWDP) and the water diversion period (WDP) from 2018 to 2019, and the index of biological integrity (IBI) method based on phytoplankton communities was used to evaluate the ecological health of the impounded lakes (Nansi Lake and Dongping Lake) along the eastern route of the South-to-North Water Diversion Project. The results demonstrated that water diversion improved the water quality of the impounded lakes during the WDP, especially total nitrogen and ammonia nitrogen. Meanwhile, the water diversion affected the phytoplankton community structure and diversity, and network analysis further revealed water diversion could be beneficial to the ecological health of impounded lakes. Furthermore, the P-IBI showed that the overall ecological health assessment was "good" during the WDP. Water diversion substantially improved the ecological health status and stability of the impounded lakes during the dry season. Finally, the direct correlations between the water quality parameters and the P-IBI were weak, and water quality parameters could indirectly affect the P-IBI by changing the phytoplankton community structure. These findings will enhance our understanding of the ecological health of the impounded lakes of the South-to-North Water Diversion Project. Furthermore, this study will provide a reference to support the ecosystem security of impounded lakes in other large water diversion projects.