Development of microbial community-based index of biotic integrity to evaluate the wetland ecosystem health in Suzhou, China

Evaluating a river's ecological health: A multidimensional approach

Evaluating the health of river surface water is essential, as rivers support significant biological resources and serve as vital drinking water sources. While the Water Quality Index (WQI) is commonly employed to evaluate surface water quality, it fails to consider biodiversity and does not fully capture the ecological health of rivers. Here we show a comprehensive assessment of the ecological health of surface water in the lower Yangtze River (LYR), integrating chemical and biological metrics. According to traditional WQI metrics, the LYR's surface water generally meets China's Class II standards. However, it also contains 43 high-risk emerging contaminants; nitrobenzenes are found at the highest concentrations, representing 25-90% of total detections, while polycyclic aromatic hydrocarbons present the most substantial environmental risks, accounting for 81-93% of the total risk quotient. Notably, the plankton-based index of biological integrity (P-IBI) rates the ecological health of the majority of LYR water samples (59.7%) as 'fair', with significantly better health observed in autumn compared to other seasons (p < 0.01). Our findings suggest that including emerging contaminants and P-IBI as additional metrics can enhance the traditional WQI analysis in evaluating surface water's ecological health. These results highlight the need for a multidimensional assessment approach and call for improvements to LYR's ecological health, focusing on emerging contaminants and biodiversity rather than solely on reducing conventional indicators.

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.

Multifunctional resilience of river health to human service demand in an alluvial quarried reach: a comparison amongst fuzzy logic, entropy, and AHP-based MCDM models

Riverine ecosystem services to human beings are dynamically evaluated by harmonic relationships; however, over growing human service demands (HSDs) are leading to deteriorate the river health resilience. In this study, an assessment index system of river health involving pressure-state-response (PSR) based on twenty indicators of riparian, channel geomorphic, hydroecological, and social attributes was developed to detect the multifunctional reliability and resilience of river system integrity for HSDs at upper (US), middle (MS), and lower segments (LS) of Kangsabati River using fuzzy logic, analytical hierarchical process (AHP), and entropy weight-based multi-criteria decision matrix (MCDM) methods. Borda integrating MCDM results revealed that overall indicator performance is high health score in US (77), medium score in MS (69), but mostly unhealthy score in LS (34); thus, entropy-MCDM models give highest rank to US, medium rank to MS, and least rank to LS, while AHP and fuzzy MCDM models assigned as high priority rank to MS, medium rank to US, and least rank to LS, respectively. According to model validation performances, entropy-MCDM models (RMSE < 2.48) are rationalized to the harmonic relationship of riverine system, whereas fuzzy and AHP-MCDM models (RMSE < 2.79) are signified to HSDs, and these results are closer to real problems. With the acceptability of AHP-MCDM models through the percentage change (73.89%) and intensity change (17.16) assessment, it points that over HSDs are crucial factors for river health degradation. Moreover, final outcome of the present research helps to find out the sick river health sites for ecological restoration.

Exploring a multisource-data framework for assessing ecological environment conditions in the Yellow River Basin, China

Ecological environment conditions (EEC) assessment plays an important role in watershed management. However, due to insufficient field data, EEC assessment in large-scale watersheds faces challenges. Our study was conducted to develop an effective EEC assessment method framework that was capable of reducing the use of field data. Three indicators were developed from multisource data, including landscape ecological risk index (LERI), road network density (RND), and industry density (ID). The knowledge-based raster mapping approach integrated the three indicators into an overall score of the EEC. Then model validation was conducted with principal components of water quality from field sampling data by Pearson correlation analysis methods. Finally, we applied and demonstrated the constructed method framework in the EEC assessment of the YRB.The results showed that bad EEC (0.5326 < Overall score ≤ 0.7679) areas were mainly distributed in the northern part of the YRB, showing a circular distribution pattern. The areas with bad EEC were 15.84 million km², accounting for 19.87 % of the YRB. The area of the highest LERI (0.157 < LERI≤0.246), the highest RND (4.4435 < RND ≤ 8.5574), and the highest ID (0.1403 < ID≤0.2597) finally converted to bad EEC was 7.22 million km², 0.78 million km², and 0.91 million km², respectively. The results indicated that the ecological risk factors were the primary challenges for improving EEC, followed by industrial agglomeration and road network factors. The primary factors affecting EEC varied between the provinces in the YRB, suggesting that provinces take the management strategies and measures should be adaptive. The correlation coefficients between EEC and the principal components of water quality characteristics were between 0.022 and 0.241, P < 0.05. These findings validated that our method framework could distinguish the spatial variation of EEC in detail and further provide effective support for watershed management.

Ecological health evaluation of rivers based on phytoplankton biological integrity index and water quality index on the impact of anthropogenic pollution: A case of Ashi River Basin

Based on the phytoplankton community matrices in the Ashi River Basin (ASRB), Harbin city, we developed an evaluation method using the phytoplankton index of biotic integrity (P-IBI) to evaluate ecological health while investigating the response of P-IBI to anthropogenic activities. We compared the effectiveness of P-IBI with that of the water quality index (WQI) in assessing ecological health. Between April and October 2019, phytoplankton and water samples were collected at 17 sampling sites in the ASRB on a seasonal basis. Our results showed that seven phyla were identified, comprising 137 phytoplankton species. From a pool of 35 candidate indices, five critical ecological indices (Shannon–Wiener index, total biomass, percentage of motile diatoms, percentage of stipitate diatom, and diatom quotient) were selected to evaluate the biological integrity of phytoplankton in the ASRB. The ecological status of the ASRB as measured by the P-IBI and WQI exhibited a similar spatial pattern. It showed a spatial decline in ecological status in accordance with the flow of the river. These results highlighted that P-IBI was a reliable tool to indicate the interaction between habitat conditions and environmental factors in the ASRB. Our findings contribute to the ecological monitoring and protection of rivers impacted by anthropogenic pollution.

Impact of Industrial Production, Dam Construction, and Agriculture on the Z-IBI in River Ecosystems: A Case Study of the Wanan River Basin in China

Industrial activity, dam construction, and agriculture—while important for socioeconomic progress—can severely damage the natural environment. To evaluate the effects of these human activities on the bio-integrity of riverine ecosystems, we examined the Wanan reach of the Ganjiang River (Wanan River basin), which contains the river’s largest reservoir. On the basis of 20 attributes of zooplankton, we constructed a zooplankton index of bio-integrity (Z-IBI) evaluation system using range analysis, discriminant analysis, and correlation analysis. Our research found that these anthropogenic activities can greatly change the composition and number of zooplankton community. The overall health status of this catchment was classified as “good”, and the eco-health situation of the reference, industrial, dam-controlled and agricultural sites were deemed “healthy”, “fair”, “good”, and “fair”, respectively. Our results suggested that the three activities adversely affected the integrity of local aquatic ecosystems. Agriculture was the activity most detrimental to the zooplankton community, followed by industrial production and dam construction. Therefore, we demonstrated that the Z-IBI evaluation system can be applied to reservoir–riverine ecosystems. We also provide guidance on the ecological protection, assessment, monitoring and of reservoir–riverine ecosystems and suggest that additional Z-IBI evaluation approaches be further developed in the future.