Freshwater lake ecosystem health assessment and its response to pollution stresses based on planktonic index of biotic integrity

Towards ecosystem-based techniques for tipping point detection

An ecosystem shifts to an alternative stable state when a threshold of accumulated pressure (i.e. direct impact of environmental change or human activities) is exceeded. Detecting this threshold in empirical data remains a challenge because ecosystems are governed by complex interlinkages and feedback loops between their components and pressures. In addition, multiple feedback mechanisms exist that can make an ecosystem resilient to state shifts. Therefore, unless a broad ecological perspective is used to detect state shifts, it remains questionable to what extent current detection methods really capture ecosystem state shifts and whether inferences made from smaller scale analyses can be implemented into ecosystem management. We reviewed the techniques currently used for retrospective detection of state shifts detection from empirical data. We show that most techniques are not suitable for taking a broad ecosystem perspective because approximately 85% do not combine intervariable non-linear relationships and high-dimensional data from multiple ecosystem variables, but rather tend to focus on one subsystem of the ecosystem. Thus, our perception of state shifts may be limited by methods that are often used on smaller data sets, unrepresentative of whole ecosystems. By reviewing the characteristics, advantages, and limitations of the current techniques, we identify methods that provide the potential to incorporate a broad ecosystem-based approach. We therefore provide perspectives into developing techniques better suited for detecting ecosystem state shifts that incorporate intervariable interactions and high-dimensionality data.

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.

Integrated machine learning reveals aquatic biological integrity patterns in semi-arid watersheds

Semi-arid regions present unique challenges for maintaining aquatic biological integrity due to their complex evolutionary mechanisms. Uncovering the spatial patterns of aquatic biological integrity in these areas is a challenging research task, especially under the compound environmental stress. Our goal is to address this issue with a scientifically rigorous approach. This study aims to explore the spatial analysis and diagnosis method of aquatic biological based on the combination of machine learning and statistical analysis, so as to reveal the spatial differentiation patterns and causes of changes of aquatic biological integrity in semi-arid regions. To this end, we have introduced an innovative approach that combines XGBoost-SHAP and Fuzzy C-means clustering (FCM), we successfully identified and diagnosed the spatial variations of aquatic biological integrity in the Wei River Basin (WRB). The study reveals significant spatial variations in species number, diversity, and aquatic biological integrity of phytoplankton, serving as a testament to the multifaceted responses of biological communities under the intricate tapestry of environmental gradients. Delving into the depths of the XGBoost-SHAP algorithm, we discerned that Annual average Temperature (AT) stands as the pivotal driver steering the spatial divergence of the Phytoplankton Integrity Index (P-IBI), casting a positive influence on P-IBI when AT is below 11.8 °C. The intricate interactions between hydrological variables (VF and RW) and AT, as well as between water quality parameters (WT, NO3-N, TP, COD) and AT, collectively sculpt the spatial distribution of P-IBI. The fusion of XGBoost-SHAP with FCM unveils pronounced north-south gradient disparities in aquatic biological integrity across the watershed, segmenting the region into four distinct zones. This establishes scientific boundary conditions for the conservation strategies and management practices of aquatic ecosystems in the region, and its flexibility is applicable to the analysis of spatial heterogeneity in other complex environmental contexts.

Ecosystem health evaluation of urban rivers based on multitrophic aquatic organisms

The ecosystem health evaluation method of urban rivers is significantly different from natural rivers, because of intensive human interferences and ecological restoration measures. Biotic integrity index (IBI) provides a method to quantify the response of aquatic organisms to environmental stress. Multi-trophic aquatic organisms may exhibit different responses and sensitivities to stress factors, which affects the reliability of the IBIs. This study proposed a hypothesis that the biota with the higher trophic level (whose habitat was not completely destroyed) or that of the biota with the shorter life cycle would be more sensitive in urban rivers. To prove the above hypothesis, the ecosystem health status of urban rivers was evaluated by the IBIs across multitrophic groups, including benthic invertebrates, zooplankton, phytoplankton, periphyton algae and microorganisms. The reliability of the IBIs was assessed by estimating their relationship with water quality index (WQI). The spatial distribution differences of the IBIs were distinguished by spatial autocorrelation analysis. The results showed that the IBI based on benthic invertebrates cannot mask the effects of dredging. Compared with the IBIs from other trophic groups, the correlation coefficients between the IBIs based on zooplankton and microorganisms and WQI were higher. Moreover, the evaluation results of Z (Zooplankton)-IBI and M (Microorganism)-IBI were able to discriminate the least, medium and highly impaired site groups divided by WQI. For the spatial response mode, Z-IBI and M-IBI could identify the high-value river sections under ecosystem restoration projects, and Z-IBI could also identify the low-value river sections under intensive human interferences. Therefore, Z-IBI and M-IBI could be recommended as the priority application in urban rivers. The constructed ecosystem health evaluation framework for urban rivers would play a guiding role in reducing impairments and restoring water ecosystem quality.

Planktonic ecological networks support quantification of changes in ecosystem health and functioning

Plankton communities are the foundation of marine food webs and have a large effect on the dynamics of entire ecosystems. Changes in physicochemical factors strongly influence planktonic organisms and their turnover rates, making their communities useful for monitoring ecosystem health. We studied and compared the planktonic food webs of Palude della Rosa (Venice Lagoon, Italy) in 2005 and 2007. The food webs were developed using a novel approach based on the Monte Carlo random sampling of parameters within specific and realistic ranges to derive 1000 food webs for July of each year. The consumption flows involving Strombididae, Evadne spp. and Podon spp. were identified as the most important in splitting food webs of the July of the two years. Although functional nodes (FNs) differed both in presence and abundance in July of the two years, the whole system indicators showed very similar results. Sediment resuspension acted as a source of stress for the Venice Lagoon, being the most used resource by consumers while inhibiting primary producers by increasing water turbidity. Primary production in the water column was mainly generated by benthic FNs. Although the system was near an equilibrium point, it tended to increase its resilience at the expense of efficiency due to stress. This study highlights the role of plankton communities, which can serve to assess ecosystem health.

Development and testing of a planktonic index of biotic integrity (P-IBI) for Lake Fuxian, China

Lake Fuxian has the largest reserves of high-quality water resources in China, and understanding its ecological health status is the basis of its environmental protection. Based on a seasonal field investigation of the plankton community, we established a planktonic index of biotic integrity (P-IBI) evaluation system to assess the lake's ecosystem health. The biological integrity of Lake Fuxian was relatively good during winter and spring, but gradually deteriorated from summer to autumn. Areas with poor biological integrity were mainly distributed near tourist attractions along the lake's west coast. Redundancy analysis (RDA) was performed to explore the relationships between the P-IBI, its selected indicators, and the environmental variables. Water temperature (WT), pH, ammonia nitrogen (NH3-N), and dissolved oxygen (DO) significantly influenced the P-IBI and its selected indicators. NH3-N and DO were significantly positively correlated with the P-IBI, indicating that it could be used as a water quality indicator to indirectly reflect lake biological integrity. We demonstrated that the P-IBI can effectively reflect temporal and spatial variations of biological integrity and could be used as a potential tool to evaluate Lake Fuxian ecosystem health.

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.

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.

Optimal Method for Biomass Estimation in a Cladoceran Species, Daphnia Magna (Straus, 1820): Evaluating Length–Weight Regression Equations and Deriving Estimation Equations Using Body Length, Width and Lateral Area

Assessing the biomass of zooplankton compensates for the difference between number of individuals and the accumulated body weight of the community, which helps assess aquatic ecosystem food web functions. Daphnia are crustaceans that play an intermediate role in biological interactions within food webs. The morphology and body specification of Daphnia differ during growth; hence, it is essential to apply species-specific equations to estimate biomass. We evaluated the length–weight regression equations used previously to estimate Daphnia magna biomass and conducted regression analyses using various body specifications and biomass measurements taken directly using devices such as a microbalance and microscopic camera. Biomass estimated using an equation from the Environmental Protection Agency was significantly different from the direct measurement: average biomass was lower, indicating that the equation possibly underestimated actual biomass. The biomass of D. magna had a higher multiple R2 value when length was compared with width and area, and a linear regression equation was the most suitable equation for biomass estimation. Because body specifications and biomass are affected by various environmental factors, the development of accurate species-specific biomass estimation equations will contribute to obtaining fundamental data with which the biological responses of zooplankton to aquatic ecosystem changes can be assessed.

Lake ecosystem health assessment using a novel hybrid decision-making framework in the Nam Co, Qinghai-Tibet Plateau

Lake health assessment (LHA), a powerful tool for lake ecological protection, provides the foundation for sustainable water environment management. However, existing methods have not yet considered the effects of fuzziness and randomness on LHA. In addition, most of the current studies on LHA focus on the plain areas, lack of quantitative studies in mountain areas, such as the Qinghai-Tibet Plateau. The Pythagorean fuzzy cloud (PFC) integration algorithm drawing on the advantages of Pythagorean fuzzy sets (PFS) and cloud model was proposed. A novel hybrid decision-making framework combining PFC integration algorithm and TOPSIS model was developed to determine the lake health levels with fuzziness and randomness. An indicator system incorporating ecosystem integrity (physical habitat, water quantity and quality, aquatic life) and non-ecological performance (social services) was established. To comprehensively investigate the lake health level in the Qinghai-Tibet Plateau, the Nam Co was selected as study area. Our results confirm that the developed framework in this study can overcome the shortcomings of existing methods and provide a more effective approach for LHA with fuzziness and randomness. In Nam Co, the non-ecological performance was significantly better than the ecosystem integrity. Health levels exhibited a remarkable spatial variation influenced by tourism and grazing, with decreasing health status from the northwestern to southeastern Nam Co. Approximately 85% of the sampling sites were at excellent or healthy levels, 15% were subhealthy, and no sampling sites were unhealthy and sick. Our results highlight that tourism has affected health levels at Nam Co, and effective measures are needed to minimize the impact in ecological fragile areas.

Assessment of Aquatic Ecosystem Health with Indices of Biotic Integrity (IBIs) in the Ganjiang River System, China

Indices of biotic integrity (IBIs) are widely used to assess aquatic ecosystem health. However, there are few studies on their relationships. Based on fish, macroinvertebrate and plankton survey data collected in the Ganjiang River system from 2016 to 2017, redundancy analysis (RDA) and canonical correspondence analysis (CCA) were used to analyze how the community structures of these organisms respond to environmental variables. The fish IBI (F-IBI), benthic macroinvertebrate IBI (B-IBI), and phytoplankton IBI (P-IBI) were applied to evaluate the health status of the aquatic ecosystem. A Kruskal–Wallis test (p < 0.05) and Spearman’s correlation coefficient analysis were performed to evaluate the spatiotemporal heterogeneity of the results. Our results suggested that the F-IBI-, B-IBI-, and P-IBI-based assessments indicated good, fair, and healthy Ganjiang River system ecosystem health statuses, respectively, and significant differences existed among these indices (p < 0.05). The main environmental factors affecting F-IBI, B-IBI, and P-IBI were different. At the temporal scale, the F-IBI and B-IBI were stable, while the P-IBI fluctuated obviously. The consistency between the F-IBI and B-IBI results was better than that between each of these indices and the P-IBI results, and the consistency was better on a larger scale. These research results show that comprehensive assessments based on multiple groups rather than a single group can better characterize the impacts of environmental pressures on water ecosystems.

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

Cascade dams have exerted significant effects on river ecosystems. To quantitatively assess dam-induced effects on river ecological status, a novel multi-species interaction-based index of biotic integrity (Mt-IBI) was developed. Benthic microbiota was selected as a bio-indicator for its sensitivity to the environmental disturbance. An environmental DNA metabarcoding tool was used to identify microbiota (bacteria, protozoan, and metazoan). The Mt-IBI was applied to assess the ecological status of the Hanjiang River, a representative dam-affected river in China. Fifteen sampling sites along the Hanjiang River were sampled in June 2018. Seven core metrics were screened from a total of 364 candidate metrics to calculate the value of the Mt-IBI. The Mt-IBI of the Hanjiang River ranged from 1.90 to 6.39, with a mean value of 4.02. The mean values of Mt-IBI at the reservoir and riverine side of dams were 2.11 and 3.81, respectively. The downstream reach without dam constructions had the highest mean Mt-IBI (5.79). Thus, the continuity of the river was strongly related to the Mt-IBI. Structural equation models (SEMs) were further established to identify the dominant environmental variables in the dam-affected river. The SEMs indicated that flow velocity (coefficient 0.749) was the most important determinant of ecological status in the Hanjiang River. Water organic matter also played a vital role in determining the ecological status of the Hanjiang River, and exerted the strongest direct effect (P < 0.001, r = 0.712). The reliability of SEMs was verified by building a support vector regression model (R² = 0.8141). This study can provide new tools for ecological assessment and diagnosis, and provide a new perspective for the management of cascade dams.