Ecological status classification of the Taizi River Basin, China: a comparison of integrated risk assessment approaches

An innovative index to incorporate transcriptomic data into weight of evidence approaches for environmental risk assessment

The sharp decrease in the cost of RNA-sequencing and the rapid improvement in computational analysis of eco-toxicogenomic data have brought new insights into the adverse effects of chemicals on aquatic organisms. Yet, transcriptomics is generally applied qualitatively in environmental risk assessments, hampering more effective exploitation of this evidence through multidisciplinary studies. In view of this limitation, a methodology is here presented to quantitatively elaborate transcriptional data in support to environmental risk assessment. The proposed methodology makes use of results from the application of Gene Set Enrichment Analysis to recent studies investigating the response of Mytilus galloprovincialis and Ruditapes philippinarum exposed to contaminants of emerging concern. The degree of changes in gene sets and the relevance of physiological reactions are integrated in the calculation of a hazard index. The outcome is then classified according to five hazard classes (from absent to severe), providing an evaluation of whole-transcriptome effects of chemical exposure. The application to experimental and simulated datasets proved that the method can effectively discriminate different levels of altered transcriptomic responses when compared to expert judgement (Spearman correlation coefficient of 0.96). A further application to data collected in two independent studies of Salmo trutta and Xenopus tropicalis exposed to contaminants confirmed the potential extension of the methodology to other aquatic species. This methodology can serve as a proof of concept for the integration of "genomic tools" in environmental risk assessment based on multidisciplinary investigations. To this end, the proposed transcriptomic hazard index can now be incorporated into quantitative Weight of Evidence approaches and weighed, with results from other types of analysis, to elucidate the role of chemicals in adverse ecological effects.

Modeling the ecological status response of rivers to multiple stressors using machine learning: A comparison of environmental DNA metabarcoding and morphological data

Understanding the ecological status response of rivers to multiple stressors is a precondition for river restoration and management. However, this requires the collection of appropriate data, including environmental variables and the status of aquatic organisms, and analysis via a suitable model that captures the nonlinear relationships between ecological status and various stressors. The morphological approach has been the standard data collection method employed for establishing the status of aquatic organisms. However, this approach is very laborious and restricted to a specific set of organisms. Recently, an environmental DNA (eDNA) metabarcoding data approach has been developed that is far more efficient than the morphological approach and potentially applicable to an unlimited set of organisms. However, it remains unclear how well eDNA metabarcoding data reflects the impacts of environmental stressors on aquatic ecosystems compared with morphological data, which is essential for clarifying the potential applications of eDNA metabarcoding data in the ecological monitoring and management of rivers. The present work addresses this issue by modeling organism diversity based on three indices with respect to multiple environmental variables in both the catchment and reach scales. This is done by corresponding support vector machine (SVM) models constructed from eDNA metabarcoding and morphological data on 24 sampling locations in the Taizi River basin, China. According to the mean absolute percent error (MAPE) between the measured diversity index values and the index values predicted by the SVM models, the SVM models constructed from eDNA metabarcoding data (MAPE = 3.87) provide more accurate predictions than the SVM models constructed from morphological data (MAPE = 28.36), revealing that the eDNA metabarcoding data better reflects environmental conditions. In addition, the sensitivity of SVM model predictions of the ecological indices for both catchment-scale and reach-scale stressors is evaluated, and the stressors having the greatest impact on the ecological status of rivers are identified. The results demonstrate that the ecological status of rivers is more sensitive to environmental stressors at the reach scale than to stressors at the catchment scale. Therefore, our study is helpful in exploring the potential applications of eDNA metabarcoding data and SVM modeling in the ecological monitoring and management of rivers.

Using flow cytometry for bacterioplankton community analysis as a complementary tool to Water Framework Directive to signal putatively impacted sites

Metal contamination, as well as pesticides, organic matter and nutrient input are main factors leading to freshwater ecosystems degradation. The Water Framework Directive (WFD) was implemented within the European Union with the ultimate goal of promoting a good ecological status in all European waterbodies. However, the broad implementation of the bioassessment behind WFD is costly and time-consuming and the search for complementary methodologies has been given significant attention. In this context, the main goal of this study was to evaluate whether flow cytometry (FCM) and denaturing gradient gel electrophoresis (DGGE) can be used as cellular/molecular tools to efficiently assess riverine bacterioplankton communities and relevantly inform on the ecological quality of these ecosystems. Caima river was chosen as case study using three sampling sites reflecting different levels and types of contamination (point-source organic and metal input). Both bacterioplankton community assessment approaches (DGGE and FCM), as well as macroinvertebrate and periphyton communities were consistent in signaling organic contamination. The putatively metal-loaded site bears some contradictory results depending on the community focused, possibly due to the overall low levels of metals actually found and seasonality. When comparing the two bacterioplankton community analysis tools, DGGE and FCM, the results obtained were essentially coherent, with FCM being simpler, faster and still accurate for screening bacteria communities via quantification of bacteria of high and low DNA content. This highlights the suitability of the FCM approach for prioritization of contaminated sampling sites and reinforces the suitability of using bacterioplankton communities as the focus of rapid tools to complement bioassessment sensu the WFD methodology, e.g. assisting the prioritization of potentially impacted areas.

Study on the accumulation characteristics and conduction trend of water environment risk from Taizihe River Basin, China

The accumulation and conduction of water environmental risks is of great significance to the ecological safety of river basins. To resist the outbreak of water environmental risk events, it is important to control the risk during its production and conduction phases and cut the chain of risk conduction. Currently, there are rarely reports on the research of water environment risk conduction in river basins. In order to reveal the risk accumulation characteristics and conduction trend of water environment from Taizihe River Basin, this study tried to calculate the risk level coefficient, the comprehensive risk index, the probability and intensity of the risk conduction based on the risk energy theory, and reveal the risk conduction trend in the region. The results showed that the risk sources in the study area mainly include mining, petrochemicals, metallurgical industries and equipment manufacturing industries, and habitats were waters, cultivated land, forest land, grasslands and urban land. There were one region (R4) in the slight risk area, one region (R6) in the low risk area, two regions (R3 and R5) in the medium risk area, one region (R7) in the high risk area, and two regions in the very high risk area (R1 and R2). The upper reaches of the Taizihe River was the main risk accumulation area, and the middle and lower reaches were the main risk conduction release areas. The most important contributors to the risk were TN and NH₃-N. The excess of nitrogen elements constituted the main risk source of node water quality. The highest risk during the wet and dry season occurred in the downstream section, and Tangmazhai, Xiaojiemiao, Sanchahe and Guchengzi all showed higher comprehensive risk values. This study breaks the previous idea of simple risk assessment, and observes the risk-shifting direction, which provides a theoretical and methodological support for watershed environmental risk research.

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

The development of microbial community-based biological indicators for assessing aquatic ecological status is urgently needed in heavily impaired regions, due to the local extinction of traditional indicator macro-organisms. The aim of this study was to develop and validate a microbial community-based index of biotic integrity (MC-IBI) to assess the health of wetlands in Suzhou, China. High-throughput sequencing was used to obtain information about microbial communities in wetlands and to investigate the health of the wetlands. When constructing the index, we selected what we considered were the most important environmental factors and biological parameters, and identified sensitive and tolerant species. We then used the index to evaluate the health of the inflows and outflows of 15 wetlands in Suzhou. The results showed that, of the 30 samples collected at the 10 impacted inflow sites, 2 were classified as "poor," 5 were "commonly," 18 were sub-healthy, and 5 were healthy; at the restored outflow sites, 24 were "healthy" and 6 were "sub-healthy." The health was worst at the inflows of wetlands that received agricultural effluent, followed by those that received industrial effluent, and was best at those that received urban effluent. The results from our study show that this newly developed MC-IBI gave reasonable evaluations of the health of wetland ecosystems. This application demonstrates that the evaluation system was feasible and we suggest that evaluations that further MC-IBI evaluation approaches should be developed further in the future.

Occurrence, distribution and ecological risk assessment of the herbicide simazine: A case study

The occurrence and distributions of simazine, and its environmental behaviors were studied in Taizi River, China. Results showed that concentration of simazine in surface water and suspended solids (SS) were in the range of 35-1150 ng L^-1and 0.00-1075 ng g^-1 with mean value of 240.26 ng L^-1 and 311.68 ng g^-1, respectively. A significant correlation between the concentrations of simazine and organic carbon was observed in both surface water and SS (r₁ = 0.82, n₁ = 15, r₂ = 0.68, n₂ = 10). and organic carbon in SS was more adsorptive to simazine. Moreover, the concentrations of simazine in groundwater were negatively correlated to the well depths and the distances to the corn fields, and higher concentration of simazine corresponds to younger groundwater. The criterion continuous concentration (CCC) of simazine to Chinese native aquatic species was derived based on the species sensitivity distribution (SSD) to assess the ecological risk. The CCC for simazine was derived to be 4.8 μg L^-1. Furthermore, Ecological risk assessment through risk quotient (RQ) showed that simazine presented low risk (RQ < 0.1) in some of sampling sites, while simazine posed medium risk (0.1 < RQ < 1) only on a few sampling sites nearby corn fields. The study contributed a better sight on the presence of simazine in river and its ecological risk to native aquatic species, and provided information for further studies of simazine potential hazards to the aquatic ecosystem.

Ecological risk analysis of pesticides used on irrigated rice crops in southern Brazil

Based on studies conducted in the past decade in the southern region of Brazil to determine residue levels of the pesticides normally used on irrigated rice crops, changes can be observed in relation to the presence of pesticides in the waters of the main river basins in Santa Catarina State. In previous harvests, the presence of residues of 7 pesticides was determined, with the herbicide bentazon and the insecticide carbofuran being the products showing highest frequency. Following toxicological tests conducted with 8 different test organisms, deterministic and probabilistic risk analysis was performed to assess the situation of the river basins in areas used for the production of irrigated rice. Of the species tested, the herbicide bentazon showed greatest toxicity toward plants, but did not present an ecological risk because in the worst-case scenario the highest concentration of this pesticide in the environment is 37 times lower than the lowest EC50/LC50 value obtained in the tests. The insecticide carbofuran, which had the highest toxicity toward the organisms used in the tests, presented an ecological risk in the deterministic analysis, but without any associated probability. The results highlight the need for increased efforts in training farmers in crop management practices and for the continual monitor of water bodies for the presence of pesticide residues.

Screening of pollution control and clean-up materials for river chemical spills using the multiple case-based reasoning method with a difference-driven revision strategy

In-depth filtering of emergency disposal technology (EDT) and materials has been required in the process of environmental pollution emergency disposal. However, an urgent problem that must be solved is how to quickly and accurately select the most appropriate materials for treating a pollution event from the existing spill control and clean-up materials (SCCM). To meet this need, the following objectives were addressed in this study. First, the material base and a case base for environment pollution emergency disposal were established to build a foundation and provide material for SCCM screening. Second, the multiple case-based reasoning model method with a difference-driven revision strategy (DDRS-MCBR) was applied to improve the original dual case-based reasoning model method system, and screening and decision-making was performed for SCCM using this model. Third, an actual environmental pollution accident from 2012 was used as a case study to verify the material base, case base, and screening model. The results demonstrated that the DDRS-MCBR method was fast, efficient, and practical. The DDRS-MCBR method changes the passive situation in which the choice of SCCM screening depends only on the subjective experience of the decision maker and offers a new approach to screening SCCM.