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Background: The urgent need for conservation efforts in response to the global biodiversity crisis is exemplified by initiatives, such as the EU LIFE BEETLES project. This project aims to preserve endangered arthropod species that are crucial for ecosystem functionality, with a focus on endemic beetle species in Flores, Pico and Terceira Islands (Azores, Portugal): Tarphiusfloresensis Borges & Serrano, 2017, Pseudanchomenusaptinoides (Tarnier, 1860) and Trechusterrabravensis Borges, Serrano & Amorim, 2004. These species are single island endemics respectively from Flores, Pico and Terceira. They are threatened by environmental degradation, facing the dual challenge of restricted distribution and habitat degradation due to the spread of invasive plants.The project aims to enhance habitat quality and biodiversity conservation through habitat restoration and plant invasive species control measures. These measures are funded by the European Commission and coordinated by the Azorean Environment Directorate-General. The current Data Paper evaluates the effectiveness of the LIFE BEETLES project in improving habitat quality and offers insights into the balance between habitat restoration efforts and endangered species conservation in island ecosystems, utilising as ecological indicator the Index of Biotic Integrity (IBI) framework. New information: This study establishes a comprehensive database derived from a long-term arthropod monitoring survey that used SLAM (Sea, Land and Air Malaise) traps and pitfall traps. Our findings present a proxy for assessing the overall habitat quality for endemic invertebrates, using arthropods as main indicators.From September 2020 to June 2023, a total of 31 SLAM traps were monitored. The traps were set up as follows: seven in Flores (three in mixed forest and four in native forest), 10 in Pico (four in mixed forest and six in native forest) and 14 in Terceira (three in mixed forest and 11 in native forest). Traps were monitored every three months.In addition, we surveyed the epigean fauna in 19 transects with 15 non-attractive pitfall traps per transect. The transects were set up during two weeks at the end of August every year between 2020 and 2023. Eight transects were established in Flores, consisting of one in pasture, four in mixed forest and three in native forest. Six transects were established in Pico, consisting of two in pastures and four in native forest. Five transects were established in Terceira, consisting of two in mixed forest and three in native forest.A total of 243 arthropod taxa were recorded, with 207 identified at the species or subspecies level. These taxa belonged to four classes, 24 orders and 101 families. Out of the 207 identified taxa, 46 were endemic, 60 were native non-endemic, 80 were introduced and 21 were of indeterminate status. Habitat information is also provided, including general habitat and dominant species composition. This publication contributes to the conservation of highly threatened endemic beetles by assessing habitat quality, based on arthropod communities and habitat description (e.g. native or exotic vegetation).Using the Index of Biotic Integrity (IBI) to comparing pre- and post-intervention data, we found no significant change within the epigean community. In contrast, the understorey community sampled with SLAM traps experienced a slight global decrease in biotic integrity over the study period. These findings suggest that the short duration of the study may not be sufficient to detect significant changes, as ecosystem recovery often requires long-term monitoring. The observed changes in the understorey community may be attributed to disturbances from intervention activities, highlighting the need for ongoing monitoring to assess long-term ecological resilience and recovery.

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Background: The database we introduce is a pivotal component of the LIFE SNAILS project (Support and Naturalisation in Areas of Importance for Land Snails). This initiative is dedicated to safeguarding three endangered species of terrestrial molluscs, specifically, two snails (Oxychilusagostinhoi Martins 1981 and Leptaxisminor Backhuys, 1975) and a semi-slug (Plutoniaangulosa (Morelet, 1860)), all of which are single island endemics from Santa Maria Island and face significant threats towards their populations.In this study, we established a comprehensive database derived from a long-term arthropod monitoring campaign utilising SLAM (Sea, Land, Air, Malaise) traps. Although molluscs were not the primary focus, our findings serve as a credible proxy for evaluating the overall habitat quality for endemic invertebrates, with arthropods serving as principal indicators. From September to December of 2022, a total of 11 SLAM traps were installed and monitored monthly in eleven sites of mixed forests of Santa Maria Island. New information: Based on the 33 available samples (11 sites x 3 sampling periods), we recorded a total of 118 taxa of arthropods (of which 94 were identified at species or subspecies level), belonging to three classes, 14 orders and 62 families. From the 94 identified taxa, a total of 21 species were endemic, 31 native non-endemic, 32 introduced and 10 indeterminate. We also provide additional information of the habitat quality (Index of Biotic Integrity), including general habitat and dominant species composition.We registered three new records to the Island, the native bug Piezodoruslituratus (Fabricius, 1794) (Hemiptera, Pentatomidae), the Azorean endemic beetle Phloeosinusgillerforsi Bright, 1987 (Coleoptera, Curculionidae) and the exotic ant Hypoponerapunctatissima (Roger, 1859) (Hymenoptera, Formicidae) and one new record for the Azores Archipelago, the native beetle Cephenniumvalidum Assing & Meybohm, 2021 (Coleoptera, Staphylinidae, Scydmaeninae).This publication not only contributes to the conservation of highly threatened endemic molluscs, through an assessment of habitat quality, based on arthropod communities and habitat description (e.g. native or exotic vegetation), but also provides an updated inventory of arthropods from Santa Maria Island.

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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.

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River ecological health assessments are the premise for protecting river biodiversity and curbing river water environment deterioration. To explore the river ecosystem health status and its response mechanism to water environmental factors in the middle reaches of the Yarlung Zangbo River, phytoplankton samples were collected during July and October 2021, and water environmental factors were measured. The phytoplankton species were identified, and their cell abundance and biomass were calculated. The phytoplankton integrity index was constructed to evaluate the ecological health status of the river. The temporal and spatial distribution characteristics of water environmental factors and phytoplankton community, as well as the correlation between P-IBI value and community parameters and water environmental factors were analyzed. The results showed that the difference in water environmental factors was not evident in time but was significant in space. The average cell abundance and biomass of phytoplankton were in the order of wet season>dry season and main stream>tributaries. Diatoms dominated the community, and pH and WT were the major water environmental factors driving the spatial and temporal distributions of phytoplankton. The ecological health status of the middle reaches of the Yarlung Zangbo River was "healthy to sub-healthy." The river health status was better than that of the dry season, and that of the tributaries was better than that of the main stream. EC, TUR, WT, NO3--N, and NH4+-N were the major water environmental factors affecting the ecological health status of the river reach, which could be affected by the direction and rate of phytoplankton community succession. It is involved in and affects the process of material circulation and energy flow of the river ecosystem, thereby driving the ecological health of the middle reaches of the Yarlung Zangbo River.

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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.

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Given tidal flat special environmental conditions and the degree of pollution caused by human activities, there is an urgent need to quantitatively assess their ecological status. Bioindication has become an indispensable part of environmental quality monitoring on account of its sensitivity to environmental disturbance. Thus, this study used bio-indicators to establish a multi-metrics-based index of biotic integrity (Mt-IBI) to evaluate the ecological status of the tidal flats with/without aquaculture through metagenomic sequencing. Four core indexes that were significantly correlated to other indexes with redundancy (p < 0.05), including Escherichia, beta-lactam antibiotic resistance genes, cellulase and xyloglucanases and the keystone species with 21° in the network, were selected after the screening processes. By implementing Mt-IBI in the tidal flats, the ecological health of the sampling sites was categorized into three levels, with Mt-IBI values of 2.01-2.63 (severe level), 2.81-2.93 (moderate level) and 3.23-4.18 (mild level), respectively. Through SEM analysis, water chemical oxygen demand and antibiotics were determined to be the primary controlling factors of the ecological status of tidal flat regions influenced by aquaculture, followed by salinity and total nitrogen. It is worth noting that the alteration of microbial communities impacted ecological status through the mediation of antibiotics. It is hoped that the results of our study will provide a theoretical basis for coastal environment restoration and that the use of Mt-IBI to assess ecosystem status in different aquatic environments will be further popularized in the future.

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The development of multimetric indices (MMIs) to measure the biotic condition of aquatic habitats is based on metrics derived from biological assemblages. Considering fish assemblages, the inconsistencies in metrics responses outside of the places where they were developed limit MMI transferability and applicability to other locations, requiring local calibration. The factors behind the low transferability of these MMIs are still poorly understood. We investigated how environmental dissimilarity and spatial distance influence the transferability of metrics generated from local stream fish assemblages to other regions. We also tested whether functional and taxonomic metrics respond differently to the spatial distance. We used data from 239 fish assemblages from streams distributed across a Brazilian, the upper Parana basin and characterized each site according to the level of anthropogenic disturbance at the landscape scale using an Anthropogenic Pressure Index (API). We divided the upper Parana basin into sub-basins and used two of them to create template response models of the metrics in relation to the API. We used these response models to predict the responses outside the template sub-basins. Our response variable representing a metric of transferability was the absolute difference between metric's predicted and observed value for each site (prediction error). We thus modeled the prediction error in relation to the predictor variables that were i) the environmental dissimilarity between each site with the average of the sites from template sub-basins (climatic, topographic and soil type variables) and ii) the spatial distance (overland and watercourse distance) between each site and the center of the template sub-basin. We found that errors in metric predictions were associated with both environmental dissimilarity and spatial distance. Furthermore, functional and taxonomic metrics responded equally to spatial distance. These results indicate the need for local calibration of metrics when developing MMIs, especially if the protocols already available come from distant and environmentally dissimilar places.

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River and stream conservation programs have historically focused on a single spatial scale, for example, a watershed or stream site. Recently, the use of landscape information (e.g., land use and land cover) at multiple spatial scales and over large spatial extents has highlighted the importance of incorporating a landscape perspective into stream protection and restoration activities. Previously, we developed a novel framework that links information about watershed-, catchment-, and reach-scale integrity with stream biological condition using scatterplots and a landscape integrity map. Here we examined an application of this approach for streams in urban and other settings in King County, Washington State, United States, where we related stream macroinvertebrate condition to two indices of landscape integrity, the US Environmental Protection Agency's (USEPA) nationally available Index of Watershed Integrity (IWI) and Index of Catchment Integrity (ICI). We generated a scatterplot of IWI versus ICI for sample sites, where points represented site macroinvertebrate condition from poor to good. The same data were also visualized as a landscape integrity map that displayed catchments of King County according to the level of watershed and catchment integrity (high or low IWI/ICI). Almost three-quarters of poor-condition sites were associated with high-integrity watersheds and catchments (i.e., underperforming sites), which suggested that either one or both national indicators were insufficient for this area, and that sites underperformed because of local-scale factors. In response, we used a catchment-scale indicator related to forest condition (PctForestCat) after examining several GIS-based dispersal indicators from the National Hydrography Dataset and other candidates from the USEPA's StreamCat dataset. We then compared the results of the scatterplots and maps based on the current and original analyses and found that many of the sites previously classified as underperforming now performed as expected, that is, they were poor-condition sites in poor-condition catchments. This analysis demonstrates how results based on a national dataset can be improved by developing an alternative that represents regionally important stressors. The methods used to develop an effective landscape indicator based on StreamCat datasets, and the utility of the multiscale approach, could provide important tools for prioritizing, optimizing, and communicating stream conservation actions.

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The ecological heterogeneity created by river bends benefits the diversity of microorganisms, which is vital for the pollutant degradation and overall river health. However, quantitative tools capable of determining the interactions among different trophic levels and species are lacking, and research regarding ecological heterogeneity has been limited to a few species. By integrating the multi-species-based index of biotic integrity (Mt-IBI) and the structure equation model (SEM), an interactions-based prediction modeling framework was established. Based on DNA metabarcoding, a multi-species (i.e., bacteria, protozoans, and metazoans) based index of biotic integrity including 309 candidate metrics was developed. After a three-step screening process, eight core metrics were obtained to assess the ecological heterogeneity, quantitatively. The Mt-IBI value, which ranged from 2.08 to 7.17, was calculated as the sum of each single core metric value. The Mt-IBI revealed that the ecological heterogeneity of concave banks was higher than other sites. According to the result of the SEM, D90 was the controlling factor (r = -0.779) of the ecological heterogeneity under the influence of the river bends. The bend-induced redistribution of sediment particle further influenced the concentrations of carbon, nitrogen, and sulphur. The nitrogen group (r = 0.668) also played an essential role in determining the ecological heterogeneity, follow by carbon group (r = 0.455). Furthermore, the alteration of niches would make a difference on the ecological heterogeneity. This multi-species interactions-based prediction modeling framework proposed a novel method to quantify ecological heterogeneity and provided insight into the enhancement of ecological heterogeneity in river bends.

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Hydropower construction and climate change have aggravated river hydrological changes, which have reduced the water flow regime in the Ruhe River Basin. The reduced flow of the river seriously affected the water supply of nearby residents and the operation of the river ecosystem. Therefore, in order to alleviate the contradiction between water use for hydropower facilities and environmental water use, the urgent need is to explore the ecological flow-threshold of rivers. This study took the Fuhe River Basin as the research object, and summarized the monitoring data of eight hydrological stations from recent decades. Based on this, we explored the response law of P-IBI and flow, a tool to quickly measure the health of the ecosystem. Through the response relationship between alterations in environmental factors of the river and phytoplankton index of biotic integrity (P-IBI), it was determined that environmental flow was the dominant influencing factor of P-IBI. According to P-IBI, the threshold of environmental discharge in the Fuhe River was limited to 273~826.8 m3/s. This study established a regulatory framework for the river flow of large rivers by constructing P-IBI and determining the critical thresholds of environmental flow by constraining the constitution. These results provide a theoretical basis for better planning and improvement of river ecosystem restoration and river utilization.

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Prioritizing the relationship between heterogeneity of sediment habitats and river bends is critical when planning and reconstructing urban rivers. However, the exact relationship between ecological heterogeneity and river bends remains ambiguous. Therefore, this research proposed a new approach to quantify and predict bend-induced ecological heterogeneity, incorporating the bacteria-based index of biotic integrity (Ba-IBI), path model, and random forest regression model. The developed Ba-IBI quantified heterogeneity in sediment microbial communities, ranging from low (1.40) to high (3.97). A path model was developed and validated in order to further investigate the relative contributions of environmental factors to the Ba-IBI. The established path model, which was considered acceptable with a CMIN/df = 1.949 < 4, suggested that primary environmental factors affecting the sediment bacterial communities were flow velocity and ammonium concentration in sediment. To further characterize the relationship between environmental factors and the Ba-IBI, a function was constructed using the random forest regression model that predicts the responses of sediment bacterial communities to environmental factors with R2 = 0.6126. The proposed approach and prediction tools will provide knowledge to improve natural channel design and post-project evaluations in river restoration projects.

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The intertidal wetland ecosystem is vulnerable to environmental and anthropogenic stressors. Understanding how the ecological statuses of intertidal wetlands respond to influencing factors is crucial for the management and protection of intertidal wetland ecosystems. In this study, the community characteristics of bacteria, archaea and microeukaryote from Jiangsu coast areas (JCA), the longest muddy intertidal wetlands in the world, were detected to develop a composite microbial index of biotic integrity (CM-IBI) and to explore the influence mechanisms of stresses on the intertidal wetland ecological status. A total of 12 bacterial, archaea and microeukaryotic metrics were determined by range, responsiveness and redundancy tests for the development of ba-IBI, ar-IBI and eu-IBI. The CM-IBI was further developed via three sub-IBIs with weight coefficients 0.40, 0.33 and 0.27, respectively. The CM-IBI (R2 = 0.58) exhibited the highest goodness of fit with the CEI, followed by ba-IBI (R2 = 0.36), ar-IBI (R2 = 0.25) and eu-IBI (R2 = 0.21). Redundancy and random forest analyses revealed inorganic nitrogen (inorgN), total phosphorus (TP) and total organic carbon (TOC) to be key environmental variables influencing community compositions. A conditional reasoning tree model indicated the close associating between the ecological status and eutrophication conditions. The majority of sites with water inorgN<0.67 mg/L exhibited good statuses, while the poor ecological status was observed for inorgN>0.67 mg/L and TP > 0.11 mg/L. Microbial networks demonstrated the interactions of microbial taxonomic units among three kingdoms decreases with the ecological degradation, suggesting a reduced reliability and stability of microbial communities. Multi-level path analysis revealed fishery aquaculture and industrial development as the dominant anthropogenic activities effecting the eutrophication and ecological degradation of the JCA tidal wetlands. This study developed an efficient ecological assessment method of tidal wetlands based on microbial communities, and determined the influence of human activities and eutrophication on ecological status, providing guidance for management standards and coastal development.

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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.

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Methods for metric scoring and health status classification in development of index of biotic integrity (IBI) vary considerably across published studies. The difference between ecosystem health assessment results from these alternative methods for scoring and classification has rarely been studied systematically. Poyang Lake in China has experienced severe degradation over recent decades. Here, we aimed to develop a benthic macroinvertebrate-based index of biotic integrity (B-IBI) to assess the wetland health of Poyang Lake, and to evaluate the difference in assessment results using different methods of scoring and classification. Data on benthic macroinvertebrate assemblages, water quality and human-induced disturbances were collected at 30 sampling sites. Forty-nine attributes of macroinvertebrate assemblages were tested, and only the attributes that were significantly correlated with disturbance gradients or showed strong discriminatory power between reference and impaired sites were selected as the B-IBI metrics. Two scoring, two thresholding and three classification methods were applied for metric scoring and health status classification. Five assemblage attributes, i.e. the number of taxa, Shannon-Wiener diversity index, % Diptera, ASPT index and the number of predator taxa, were selected as the B-IBI metrics. Health status assessments varied considerably among the various metric scoring and classification methods, suggesting the importance of standardizing the methods for scoring and classification to be able to compare assessment results across different areas and time periods. The wetland health of Poyang Lake was rated as fair, which indicates that the wetland has experienced anthropogenic pressure and substantial changes in macroinvertebrate assemblage structure. Further, sample sites adjacent to tributary river mouths were in poor or very poor condition, suggesting that pollutant input by rivers has strong negative impacts on wetland health. Effective management of the entire lake basin and its watershed is therefore important for the wetland conservation.

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Incorporating information on landscape condition (or integrity) across multiple spatial scales and over large spatial extents in biological assessments may allow for a more integrated measure of stream biological condition and better management of streams. However, these systems are often assessed and managed at an individual scale (e.g., a single watershed) without a larger regional multiscale context. In this paper, our goals were: (1) To develop a conceptual framework that could combine stream biological condition to abiotic landscape integrity (or, conversely, stressor) data at three spatial scales: watershed, catchment and stream-reach scale, to enable more targeted management actions. Measures of landscape integrity and stressors are negatively related, i.e., integrity on a 0-1 scale is equal or equivalent to stressors on a 1-0 scale. (2) To develop the framework in such a way that allows operational flexibility, whereby different indicators can be used to represent biological condition, and landscape integrity (or stressors) at various scales. (3) To provide different examples of the framework's use to demonstrate the flexibility of its application and relevance to management. Examples include stream biological assessments from different regions and states across the U.S. for fish, macroinvertebrates and diatoms using a variety of assessment tools (e.g., the Biological Condition Gradient (BCG), and an Index of Biotic Integrity (IBI)). Landscape integrity indicators comprise U.S. EPA's nationally available Index of Watershed Integrity (IWI) and Index of Catchment Integrity (ICI), and state and regional derived watershed and stream-reach scale integrity indicators. Scatterplots and a landscape integrity map were used to relate samples of stream condition classes (e.g., good, fair, poor) to watershed, catchment and stream-reach scale integrity. This framework and approach could provide a powerful tool for prioritizing, targeting, and communicating management actions to protect and restore stream habitats, and for informing the spatial extent at which management is applied.

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Anthropogenic activity impacts stream ecosystems, resulting in a loss of diversity and ecosystem function; however, little is known about the response of aquatic microbial communities to changes in land use. Here, microbial communities were characterized in 82 headwater streams across a gradient of urban and agricultural land uses using 16S rRNA gene amplicon sequencing and compared to a rich data set of physicochemical variables and traditional benthic invertebrate indicators. Microbial diversity and community structures differed among watersheds with high agricultural, urban, and forested land uses, and community structure differed in streams classified as being in good, fair, poor, and very poor condition using benthic invertebrate indicators. Microbial community similarity decayed with geodesic distance across the study region but not with environmental distance. Stream community respiration rates ranged from 21.7 to 1,570 mg O2 m-2 day-1 and 31.9 to 3,670 mg O2 m-2 day-1 for water column and sediments, respectively, and correlated with nutrients associated with anthropogenic influence and microbial community structure. Nitrous oxide (N2O) concentrations ranged from 0.22 to 4.41 µg N2O liter-1; N2O concentration was negatively correlated with forested land use and was positively correlated with dissolved inorganic nitrogen concentrations. Our findings suggest that stream microbial communities are impacted by watershed land use and can potentially be used to assess ecosystem health.IMPORTANCE Stream ecosystems are frequently impacted by changes in watershed land use, resulting in altered hydrology, increased pollutant and nutrient loads, and habitat degradation. Macroinvertebrates and fish are strongly affected by changes in stream conditions and are commonly used in biotic indices to assess ecosystem health. Similarly, microbes respond to environmental stressors, and changes in community composition alter key ecosystem processes. The response of microbes to habitat degradation and their role in global biogeochemical cycles provide an opportunity to use microbes as a monitoring tool. Here, we identify stream microbes that respond to watershed urbanization and agricultural development and demonstrate that microbial diversity and community structure can be used to assess stream conditions and ecosystem functioning.

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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.

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The index of biotic integrity (IBI) has been widely used in river ecosystem health assessment. However, few studies have reported the application of microbial communities in ecosystem health assessment so far, especially for urban rivers. In this study, the Illumina high-throughput sequencing technique was applied to analyze the microbial community diversity and composition of five urban rivers selected in Zhejiang Province. Canonical correlation analyses (CCA) and Spearman correlation analysis were used to evaluate the relationship between each taxonomic group and the water quality properties to select the most sensitive taxonomic groups as candidate indexes. The functional metrics, including the relative abundance of pathogenic bacteria, pollutant-degrading bacteria, and nutrient cycling bacteria were also selected as candidate indexes. Based on the distribution range, discriminatory power, and Pearson's correlation analysis for candidate indexes, five metrics, including the Shannon-index, the number of microbial phyla, the relative abundance of Verrucomicrobia, Chlorobi, and Mycobacterium were selected to establish a biotic integrity index of microbes (M-IBI) evaluation system. A ratio score system was used to get metrics into a uniform score for all sampling points, and the results showed that among the urban river samples studied, most of them (40.9%) were at "Great" level, 45.5% were at "Good" level, 9.1% were at "Moderate" level, and 4.5% were at "Bad" level. The index of M-IBI effectively discriminated the least, medium, and highly impaired sampling points and provided a good match with the water quality (R=0.753, P<0.01), indicating that the M-IBI has potential as an index to evaluate the health of urban river ecosystems.

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Indices of biotic integrity (IBIs) are used to assess ecosystem health of streams and rivers. Streams and rivers with high IBI scores should support abundant and healthy populations of recreationally important sport fishes. However, the fundamental assumption that IBI scores and sport fish populations are associated needs to be examined. To verify this assumption, we tested associations between IBI scores and relative abundance of all sport fishes targeted by anglers, with emphasis on relative abundance of four size groups of smallmouth bass Micropterus dolomieu at 54 stream and river reaches in 2012 and 2013. We also tested for associations with smallmouth bass body condition and growth. A total of 13,708 fishes representing 85 species were captured including 11 sport fish species that included 571 smallmouth bass. We found that the maximum potential relative abundance of sport fishes and smallmouth bass size classes, as well as body condition of bass between 180 and 279 mm, could be predicted by IBI scores. We did not observe significant relationships with body condition of other bass size classes or with growth. Whereas abundance patterns were variable at reaches with higher IBI scores, abundance of larger, quality-sized sport fishes were more limited at reaches with IBI scores <30 that were classified as having poor biotic integrity. Maximum potential body condition was predicted to exceed 95, a condition value indicative of healthy fish, at IBI scores exceeding 50, reflective of reaches being classified as either fair, good, or excellent. These results confirm that management activities that enhance or maintain biotic integrity also support high-quality habitat for sport fish. While our findings support using IBIs as an indicator of the fishable goal specified in the United States Clean Water Act, managers should recognize that other factors not necessarily represented by the index can also limit sport fish populations.

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RESUMEN

Rivers are extensively regulated by damming, yet the effects of such interruption on bacterial communities have not been assessed quantitatively. To fill this gap, we proposed a bacteria-based index of biotic integrity (Ba-IBI) by using bacterial community dataset collected from the Three Gorges Reservoir and its upper reaches. Stability analysis based on bacterial resistance (RS) and resilience (RL) to external disturbance was conducted to improve the performance of the index. Four core metrics, i.e. the ratio of Bacilli, Bacteroidetes and Clostridia to Alphaproteobacteria (BBC/A), Oxalobacteraceae, Methanotrophs and Thermophiles were selected after range, responsive and redundancy tests. The improved Ba-IBI, ranging from 1.04 to 4.10, was better at distinguishing sites with or without direct dam effects compared with the unimproved one. The index values maintained high in the riverine sites while reducing in the reservoir, demonstrating the negative influence of dam construction on bacterial integrity. Based on the assessment results, 23.1%, 46.2% and 30.8% sampling sites were large, moderately and little affected by damming, respectively. A Random Forest (RF) regression model was trained and tested, offering a valid prediction of the input Ba-IBI and environmental parameters. Sensitivity analysis revealed the significant contributions of flow velocity towards the predicting process performance, indicating the importance of hydrodynamic conditions on determining the spatial variability of bacterial communities. This study provides not only a first quantitative insight for assessing bacterial response to damming, but also a guideline for applying the improved index in the dam regulation and ecological protection.

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