How diatom-, invertebrate- and fish-based diagnostic tools can support the ecological assessment of rivers in a multi-pressure context: Temporal trends over the past two decades in France

Synergistic effects of environmental factors on benthic diversity: Machine learning analysis

This study examines the water environmental factors of the Cangshan stream and benthic animal communities by using random forest, gradient boosting decision tree, and support vector machine models to analyze the complex response mechanisms of benthic animal diversity and community structure to environmental factors. Feature importance analysis, SHAP values, and 3D response surface analysis are applied to quantitatively assess the non-linear driving effects of environmental factors and their interactions. The findings suggest that total phosphorus and conductivity are central factors influencing benthic animal diversity, with moderate levels fostering community diversity, whereas high levels of total nitrogen and conductivity significantly reduce diversity. Benthic animals exhibit a non-linear response pattern to dissolved oxygen and temperature, with the interaction between dissolved oxygen and temperature highlighting the significant promotion of diversity under low-temperature, high-oxygen conditions, whereas high-temperature, low-oxygen conditions exert evident environmental stress on communities. The results of the multifactor synergistic effect analysis indicate that the moderate synergistic interaction between total phosphorus and conductivity significantly enhances diversity, whereas high total nitrogen levels weaken this positive effect. Model performance comparisons reveal that the RF outperforms the other models in terms of coefficient of determination, mean squared error, and mean absolute error, particularly in capturing complex non-linear relationships and factor interactions. Through machine learning, this study reveals the multidimensional driving mechanisms of environmental factors on benthic animal community characteristics, emphasizing the potential to capture non-linear relationships and multifactor interactions, thereby providing scientific evidence and innovative approaches for stream ecosystem conservation and management.

The role of river connectivity in the distribution of fish in an anthropized watershed

The ongoing biodiversity crisis is especially severe in freshwater habitats. Anthropized watersheds, such as the Seine-Normandie basin in France, are particularly affected by human interference. The study of fish species distribution in watersheds often relies on environmental drivers such as land use or climate. Yet, fish are also exposed to river connectivity constraints, such as dams, that are understudied despite their potential impact on fish dispersal. For this study, we investigated the role of local and whole-basin longitudinal connectivity in fish distribution. We designed connectivity indices based on river network characteristics and specific mobility for 33 species and included these indices in species distribution models, taking into account habitat suitability, to quantify their role in species distribution. Keeping the best index for each species, an average of 29 % - and up to 57 % - of explained fish distribution, depending on species, was tied to connectivity. We found that high connectivity often had a significant and positive linear effect on species presence probability. Using a scoring system across multiple indices, we found connectivity indices that took local context into account (e.g. the ecological zonation of the river) performed consistently better than others. Indices that took only dispersal limitation into account scored higher for 12 species, while barriers, alone, were the most important constraint for 10 species, the remaining 11 being associated with both. This work points to fragmentation as a cause for lower likelihood of presence for many non-diadromous river fish species. It highlights the importance of considering both physical and functional connectivity constraints in fish distribution and provides additional insights for river management and restoration.

Macroinvertebrate communities respond strongly but non-specifically to a toxicity gradient derived by effect-based methods

Chemical pollution is one of the most important threats to freshwater ecosystems. The plethora of potentially occurring chemicals and their effects in complex mixtures challenge standard monitoring methods. Effect-based methods (EBMs) are proposed as complementary tools for the assessment of chemical pollution and toxic effects. To investigate the effects of chemical pollution, the ecological relevance of EBMs and the potential of macroinvertebrates as toxicity-specific bioindicators, ecological and ecotoxicological data were linked. Baseline toxicity, mutagenicity, dioxin-like and estrogenic activity of water and sediment samples from 30 river sites in central Germany were quantified with four in vitro bioassays. The responses of macroinvertebrate communities at these sites were assessed by calculating 16 taxonomic and functional metrics and by investigating changes in the taxonomic and trait composition. Principal component analysis revealed an increase in toxicity along a joint gradient of chemicals with different modes of action. This toxicity gradient was associated with a decrease in biodiversity and ecological quality, as well as significant changes in taxonomic and functional composition. The strength of the effects suggested a strong impact of chemical pollution and underlined the suitability of EBMs in detecting ecological relevant effects. However, the metrics, taxa, and traits associated with vulnerability or tolerance to toxicity were found to also respond to other stressors in previous studies and thus may have only a low potential as toxicity-specific bioindicators. Because macroinvertebrates respond integratively to all present stressors, linking both ecological and environmental monitoring is necessary to investigate the overall effects but also isolate individual stressors. EBMs have a high potential to separate the toxicity of chemical mixtures from other stressors in a multiple stressor scenario, as well as identifying the presence of chemical groups with specific modes of action.

Assessing the response of an urban stream ecosystem to salinization under different flow regimes

Urban streams are exposed to a variety of anthropogenic stressors. Freshwater salinization is a key stressor in these ecosystems that is predicted to be further exacerbated by climate change, which causes simultaneous changes in flow parameters, potentially resulting in non-additive effects on aquatic ecosystems. However, the effects of salinization and flow velocity on urban streams are still poorly understood as multiple-stressor experiments are often conducted at pristine rather than urban sites. Therefore, we conducted a mesocosm experiment at the Boye River, a recently restored stream located in a highly urbanized area in Western Germany, and applied recurrent pulses of salinity along a gradient (NaCl, 9 h daily of +0 to +2.5 mS/cm) in combination with normal and reduced current velocities (20 cm/s vs. 10 cm/s). Using a comprehensive assessment across multiple organism groups (macroinvertebrates, eukaryotic algae, fungi, parasites) and ecosystem functions (primary production, organic-matter decomposition), we show that flow velocity reduction has a pervasive impact, causing community shifts for almost all assessed organism groups (except fungi) and inhibiting organic-matter decomposition. Salinization affected only dynamic components of community assembly by enhancing invertebrate emigration via drift and reducing fungal reproduction. We caution that the comparatively small impact of salt in our study can be due to legacy effects from past salt pollution by coal mining activities >30 years ago. Nevertheless, our results suggest that urban stream management should prioritize the continuity of a minimum discharge to maintain ecosystem integrity. Our study exemplifies a holistic approach for the assessment of multiple-stressor impacts on streams, which is needed to inform the establishment of a salinity threshold above which mitigation actions must be taken.

Water quality deterioration remains a major stressor for macroinvertebrate, diatom and fish communities in German rivers

About 60 % of Europe's rivers fail to meet ecological quality standards derived from biological criteria. The causes are manifold, but recent reports suggest a dominant role of hydro-morphological and water quality-related stressors. Yet, in particular micropollutants and hydrological stressors often tend to be underrepresented in multiple-stressor studies. Using monitoring data from four Federal States in Germany, this study investigated the effects of 19 stressor variables from six stressor groups (nutrients, salt ions, dissolved oxygen/water temperature, mixture toxicity of 51 micropollutants, hydrological alteration and morphological habitat quality) on three biological assemblages (fishes, macroinvertebrates, benthic diatoms). Biological effects were analyzed for 35 community metrics and quantified using Random Forest (RF) analyses to put the stressor groups into a hierarchical context. To compare metric responses, metrics were grouped into categories reflecting important characteristics of biological communities, such as sensitivity, functional traits, diversity and community composition as well as composite indices that integrate several metrics into one single index (e.g., ecological quality class). Water quality-related stressors - but not micropollutants - turned out to dominate the responses of all assemblages. In contrast, the effects of hydro-morphological stressors were less pronounced and stronger for hydrological stressors than for morphological stressors. Explained variances of RF models ranged 23-64 % for macroinvertebrates, 16-40 % for benthic diatoms and 18-48 % for fishes. Despite a high variability of responses across assemblages and stressor groups, sensitivity metrics tended to reveal stronger responses to individual stressors and a higher explained variance in RF models than composite indices. The results of this study suggest that (physico-chemical) water quality deterioration continues to impact biological assemblages in many German rivers, despite the extensive progress in wastewater treatment during the past decades. To detect water quality deterioration, monitoring schemes need to target relevant physico-chemical stressors and micropollutants. Furthermore, monitoring needs to integrate measures of hydrological alteration (e.g., flow magnitude and dynamics). At present, hydro-morphological surveys rarely address the degree of hydrological alteration. In order to achieve a good ecological status, river restoration and management needs to address both water quality-related and hydro-morphological stressors. Restricting analyses to just one single organism group (e.g., macroinvertebrates) or only selected metrics (e.g., ecological quality class) may hamper stressor identification and its hierarchical classification and, thus may mislead river management.

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.

Linking Micropollutants to Trait Syndromes across Freshwater Diatom, Macroinvertebrate, and Fish Assemblages

The ecological quality of freshwater ecosystems is endangered by various micropollutants released into the environment by human activities. The cumulative effects of these micropollutants can affect the fitness of organisms and populations and the functional diversity of stream ecosystems. In this study, we investigated the relationships between the joint toxicity of micropollutants and trait syndromes. A trait syndrome corresponds to a combination of traits that could occur together in communities due to the trait selection driven by exposure to these micropollutants. Our objectives were to (i) identify trait syndromes specific to diatom, macroinvertebrate, and fish assemblages and their responses to exposure, taking into account four micropollutant types (mineral micropollutants, pesticides, PAHs, and other organic micropollutants) and nine modes of action (only for pesticides), (ii) explore how these syndromes vary within and among the three biological compartments, (iii) investigate the trait categories driving the responses of syndromes to micropollutant exposure, and (iv) identify specific taxa, so-called paragons, which are highly representative of these syndromes. To achieve these objectives, we analyzed a dataset including the biological and physico-chemical results of 2007 sampling events from a large-scale monitoring survey routinely performed in French wadeable streams. We have identified five (diatoms), eight (macroinvertebrates), and eight (fishes) trait syndromes, either positively or negatively related to an increasing toxicity gradient of different clusters of micropollutant types or modes of action. Our analyses identified several key trait categories and sets of paragons, exhibiting good potential for highlighting exposure by specific micropollutant types and modes of action. Overall, trait syndromes might represent a novel and integrative bioassessment tool, driven by the diversity of trait-based responses to increasing gradients of micropollutant toxic cocktails.

How good is good ecological status? A test across river typologies, diatom indices and biological elements

Good ecological status is the environmental objective of EU water legislation to be achieved by all European water bodies. However, good ecological status varies depending on national criteria, typology approach, and classification systems used. Since nutrient enrichment is the main cause of river degradation, it is important to establish nutrient criteria that consistently support good ecological status across these influential factors. This study analyzes good ecological status, depending on the typology, classification system and biological element used, and it discusses potential implications of the results for river management. We used a database of 425 sites from northern Spain, corresponding to 11 river types of the Spanish typology derived from physiographic data, or to the four river types resulting from NORTIdiat predictive model, derived from regional diatom reference assemblages. PERMANOVA analysis found significant differences among diatom assemblages across the four river types derived from the NORTIdiat system. Among the classification systems currently in use, or of potential use in the area, the upper P-PO₄^3- threshold, established as the P₉₅ of the class distribution for good ecological status, both NORTIdiat (50.7 μg l^-1) and the Multimetric Diatom index (MDIAT; 26.4 μg l^-1) were close to proposed thresholds for good status at the EU level. However, this value was much higher for the Specific Polluosensitivity Index (IPS; 118.1 μg l^-1). Nutrient thresholds for good status also varied among bioindicators, since the predictive invertebrate-based model NORTI classified 67% of samples with high P-PO₄^3- content in good ecological status, whereas the NORTIdiat classified only 33% of them in good status. Results suggest that current nutrient criteria used to establish good ecological status should be revised, accounting for biological specificity and response of biological elements, to provide a more ecologically coherent approach to preserving or restoring good ecological status.