Linking the Agricultural Landscape of the Midwest to Stream Health with Structural Equation Modeling

An innovative method for identifying aquatic environmental characteristics: construction of water quality fingerprint spectrum and combination with two-dimensional correlation spectroscopy analysis

With the deterioration of water quality and explosion of data scale, the diversification and complication of water quality analysis tasks are increasing, which require advanced analysis and visualization methods. Current multivariate statistical methods face challenges in processing multi-dimensional data and conducting causal analysis of fluctuations in water quality over temporal or spatial variations. In this study, a water quality fingerprint spectrum was constructed to perform multiscale and large-volume dataset. Based on the water quality fingerprint spectrum, a workflow of water quality was proposed for exploring the priority control regions, periods, and parameters were identified, and the key factors and effect pathways of response mechanisms, which consisted of three modules: data preparation, data interpretation, and causal analysis. In this study, we constructed a water quality fingerprint spectrum based on 792 water quality data from Lake Shahu as an example to present the methodology. The results showed that CODCr, TN, and TP were identified as priority control parameters of Lake Shahu, which were mainly affected by tourism activities and water replenishment. According to the results to conduct causal analysis, we found that the water replenishment could directly improve water quality (total effect: -0.464) by inhibition of algal growth and dilution of CODCr and TP concentrations, while tourism activities do the opposite (total effect: 0.562). The innovative analysis method conducted a thorough examination of fluctuations in water quality over spatio-temporal variations and paved the way between data and practical requirements in future works of water quality analysis and management.

Did green infrastructure improve water purification ecosystem services in Shandong Peninsula urban agglomeration? Evidence from total phosphorus

Non-point source pollution significantly impacts the sustainable development of river ecosystems. Water purification ecosystem services (WPES) play a crucial role in mitigating non-point source pollution. Green infrastructure (GI) maintains ecosystem services; however, how GI affects WPES remains poorly explored. Using total phosphorus (TP), we investigated the mechanisms by which GI and its structure and functions influence WPES in the Shandong Peninsula urban agglomeration. Results show that GI significantly improved WPES, with the lower TP loads (49-fold) and TP export capacity (3-fold) in GI areas compared to non-GI areas. These effects are associated with specific GI attributes, including structural connectivity, vegetation coverage, and soil conservation capability, which exhibit cascading effects (|r| > 0.8). Optimizing GI structural connectivity can indirectly regulate WPES by enhancing GI ecological functions (vegetation coverage and soil conservation), making it a crucial land management strategy. Specifically, the enhancement of vegetation coverage, which is critical for improving WPES (|r| > 0.6), should focus on both the 'scale' and 'health' of the vegetation. Cultivating GI (|r| > 0.6) offers greater benefits for WPES than forests and grasslands alone (|r| < 0.6). Effectively leveraging the relationships between GI attributes and WPES can significantly reduce TP risks.

Utilizing machine learning to optimize agricultural inputs for improved rice production benefits

Lower efficiency of agricultural inputs in the four conventional rice planting methods limits productivity and environmental benefits in Southwest China. Thus, we developed a machine-learning-based decision-making system for achieving optimal comprehensive benefits during rice production. Based on conventional benefits for achieving optimal benefits, implemented strategies in these planting methods: reducing N fertilizer by 16% while increasing seed inputs by 9% in mechanical transplanting (MT) method improved yield and environmental benefits; reducing N fertilizer and seed inputs by 10-12% in mechanical direct seeding (MD) method decreased environmental impacts; increasing N-K fertilizers and seed inputs by 15-33% in manual transplanting (MAT) method improved its comprehensive benefits by 7-14%; applying N-P-K fertilizer ratio of 2:1:2 in manual direct seeding (MAD) method enhanced yield. Our study provides strategies for improving benefits in these planting methods, with MT method being more beneficial for optimizing comprehensive benefits, especially in yield and environmental impacts, in Southwest China.

Unraveling the complex interactions between ozone pollution and agricultural productivity in China's main winter wheat region using an interpretable machine learning framework

Surface ozone has become a significant atmospheric pollutant in China, exerting a profound impact on crop production and posing a serious threat to food security. Previous studies have extensively explored the physiological mechanisms of ozone damage to plants. However, the effects of ozone interactions with other environmental factors, such as climate change, on agricultural productivity at the regional scale, particularly under natural conditions, remain insufficiently understood. In this study, we employed an interpretable machine learning framework, specifically the eXtreme Gradient Boosting (XGBoost) algorithm enhanced by SHapley Additive exPlanations (SHAP), to investigate the influence of ozone and its interactions with environmental factors on crop production in China's primary winter wheat region. Additionally, a structural equation model was developed to elucidate the mechanisms driving these interactions. Our findings demonstrate that ozone pollution exerts a significant negative effect on winter wheat productivity (r = -0.47, P < 0.001), with productivity losses escalating from -12.28 % to -22.09 % as ozone levels increase. Notably, the impact of ozone is spatially heterogeneous, with western Shandong province identified as a hotspot for ozone-induced damage. Furthermore, our results confirm the complexity of the relationship between ozone pollution and agricultural productivity, which is influenced by multiple interacting environmental factors. Specifically, we found that severe ozone pollution, when combined with high aerosol concentrations or elevated temperatures, significantly exacerbates crop productivity losses, although drought conditions can partially mitigate these adverse effects. Our study highlights the importance of incorporating the interactive effects of air pollution and climate change into future crop models. The comprehensive framework developed in this study, which integrates statistical modeling with explainable machine learning, provides a valuable methodological reference for quantitatively assessing the impact of air pollution on crop productivity at a regional scale.

Pesticide presence in stream water, suspended sediment and biofilm is strongly linked to upstream catchment land use and crop type

Pesticide pollution can present high ecological risks to aquatic ecosystems. Small streams are particularly susceptible. There is a need for reproducible and readily available methods to identify aquatic regions at risk of pesticide contamination. There is currently a limited understanding of the relationship between upstream catchment land use and the presence of pesticides in multiple aquatic matrices. The aim of this study was to develop empirical relationships between different land uses and the levels of pesticides detected in multiple aquatic matrices. The inclusion of biofilm and suspended sediment as monitoring matrices has recently been proven effective for the characterization of pesticide exposure in stream ecosystems. Ten streams in Ontario, Canada with a variety of upstream catchment land uses were sampled in 2021 and 2022. Water, suspended sediment and biofilm were collected and analyzed from each site for the presence of approximately 500 different pesticides. Each of the three matrices exhibited distinctive pesticide exposure profiles. We found a significant relationship between the percentage of agriculture and urban land use and the detection of multiple pesticides in water, sediment and biofilm (logistic regressions, P<0.05). Statistically significant probabilistic models capable of predicting pesticide detections based on upstream catchment land use were developed. High-resolution cover crop maps identified soybeans, corn and other agriculture (e.g., vegetables, berries, canola) as the key variables associated with individual pesticide detection frequencies in each of the three matrices (linear regressions, P<0.05). Soybean land use was also the strongest predictor of site-wide pesticide pollution. This modelling approach using upstream catchment land use variables has the potential to be a powerful tool to identify streams at risk of pesticide pollution.

Application of Synchronous Evaluation-Diagnosis Model with Quantitative Stressor-Response Analysis (SED-QSR) to Urban Lake Ecological Status: A Proposed Multiple-Level System

Ecological integrity assessment and degradation diagnosis are used globally to evaluate the health of water bodies and pinpoint critical stressors. However, current studies mainly focus on separate evaluation or diagnosis, leading to an inadequate exploration of the relationship between stressors and responses. Here, based on multiple data sets in an urban lake system, a synchronous evaluation-diagnosis model with quantitative stressor-response analysis was advanced, aiming to improve the accuracy of evaluation and diagnosis. The weights for key physicochemical stressors were quantitatively determined in the sequence of NDAVIadj > CODMn > TP > NH4+-N by the combination of generalized additive model and structural equation modeling, clarifying the most significant effects of aquatic vegetation on the degradation of fish assemblages. Then, sensitive biological metrics were screened by considering the distinct contributions of four key stressors to alleviate the possible deviation caused by common methods. Finally, ecological integrity was evaluated by summing the key physicochemical stressors and sensitive biological metrics according to the model-deduced weights instead of empirical weights. Our system's diagnosis and evaluation results achieved an accuracy of over 80% when predicting anthropogenic stress and biological status, which highlights the great potential of our multiple-level system for ecosystem management.

Insights into the characteristics of changes in dissolved organic matter fluorescence components on the natural attenuation process of toluene

Natural attenuation (NA) is of great significance for the remediation of contaminated groundwater, and how to identify NA patterns of toluene in aquifers more quickly and effectively poses an urgent challenge. In this study, the NA of toluene in two typical soils was conducted by means of soil column experiment. Based on column experiments, dissolved organic matter (DOM) was rapidly identified using fluorescence spectroscopy, and the relationship between DOM and the NA of toluene was established through structural equation modeling analysis. The adsorption rates of toluene in clay and sandy soil were 39 % and 26 %, respectively. The adsorption capacity and total NA capacity of silty clay were large. The occurrence of fluorescence peaks of protein-like components and specific products indicated the occurrence of biodegradation. Arenimonas, Acidovorax and Brevundimonas were the main degrading bacteria identified in Column A, while Pseudomonas, Azotobacter and Mycobacterium were the main ones identified in Column B. The pH, ORP, and Fe(II) were the most important factors affecting the composition of microbial communities, which in turn affected the NA of toluene. These results provide a new way to quickly identify NA of toluene.

Elevation-associated pathways mediate aquatic biodiversity at multi-trophic levels along a plateau inland river

Aquatic biodiversity plays a significant role in maintaining the ecological balance and the overall health of riverine ecosystems. Elevation is an important factor influencing biodiversity patterns. However, it is still unclear through which pathway elevation influences riverine biodiversity at different trophic levels. In this study, the elevation-associated pathways affecting aquatic biodiversity at different trophic levels were explored using structural equation modeling (SEM) and taking the Bayin River, China as the case. The results showed that the elevational patterns were different among aquatic organisms at different trophic levels. For macroinvertebrates and bacteria, the pattern was hump-shaped; while for phytoplankton and zooplankton, it was U-shaped. Building upon these observed elevational patterns, our investigation delved into the direct and indirect pathways through which elevation influences aquatic biodiversity. We found that elevation exerts an impact on aquatic biodiversity via indirect pathways. For all aquatic organisms investigated, the major pathway through which elevation influences biodiversity is mediated by water temperature and water quality. For aquatic organisms at higher trophic levels, like macroinvertebrates and zooplankton, the crucial pathway is also mediated by the landscape. The results of this study contributed to understanding the effects of elevation on aquatic organisms at different trophic levels and provided an important basis for the assessment of riverine biodiversity at large scales.

Predicting macroinvertebrate average score per taxon (ASPT) at water quality monitoring sites in Japanese rivers

Biomonitoring with bioindicators such as river macroinvertebrates is fundamental for assessing the status of freshwater ecosystems. In Japan, water quality and biomonitoring surveys are conducted separately, leading to a lack of nationwide information on their relationships and the biological status of water quality monitoring (WQM) sites. To understand the biological status of WQM sites across Japan, we developed a multiple linear regression model to estimate the average score per taxon (ASPT) using river macroinvertebrate data surveyed at a total of 237 "aligned" sites based on the co-occurrence of biomonitoring and WQM sites. The resulting regression model with eight predictors, such as biological oxygen demand, the proportion of urban areas in the catchment, could predict ASPT with reasonable accuracy (e.g., an error of ±1 for 96% of the aligned data). Using this model, we estimated ASPT values at 2925 WQM sites in rivers nationwide, categorizing them into four levels of river environment quality: "very good" (29% of WQM sites), "good" (50%), "fairly good" (14%), and "not good" (8%). Furthermore, we observed statistically significant correlations (p < 0.05; 0.4 ≤ r ≤ 0.7) between ASPT and all eight macroinvertebrate metrics examined, such as mayfly and stonefly richness, providing ecological implications of changes in ASPT.

Depth-dependent variations of physicochemical properties of sedimentary dissolved organic matter and the influence on the elimination of typical pharmaceuticals

Sedimentary dissolved organic matter (DOM) could exert a significant influence on the transformation of trace organic contaminants. However, the variations of sedimentary DOM properties with depth and their impact on trace organic contaminants biodegradation remain unclear. In this study, the qualitative changes in DOM properties with depth were assessed using spectral techniques. Specifically, within the sediment range of 0-30 cm, humic acid and fulvic acid fractions exhibited higher degrees of humification and aromatization at 10-20 cm, while hydrophilic fractions showed higher degrees of humification and aromatization at 20-30 cm. Furthermore, electrochemical methods were employed to quantitatively assess the electron transfer capacity of sedimentary DOM at different depths, which displayed consistent variation trend with humification and aromatization degree. The high degree of humification and aromatization, along with strong electron-accepting capability of DOM, significantly enhanced the biodegradation rates of tetracycline and ritonavir. To gain deeper insights into the influence of molecular composition of DOM on its properties, two-dimensional gas chromatography-quadrupole mass spectrometry analysis revealed that quinones and phenolic hydroxyl compounds govern the redox reactivity of DOM. Simulated experiment of DOM-mediated biodegradation of typical pharmaceuticals confirmed the role of quinones and phenolic hydroxyl groups in the redox reactivity of DOM.

Multiple lines of evidence point to pesticides as stressors affecting invertebrate communities in small streams in five United States regions

Multistressor studies were performed in five regions of the United States to assess the role of pesticides as stressors affecting invertebrate communities in wadable streams. Pesticides and other chemical and physical stressors were measured in 75 to 99 streams per region for 4 weeks, after which invertebrate communities were surveyed (435 total sites). Pesticides were sampled weekly in filtered water, and once in bed sediment. The role of pesticides as a stressor to invertebrate communities was assessed by evaluating multiple lines of evidence: toxicity predictions based on measured pesticide concentrations, multivariate models and other statistical analyses, and previously published mesocosm experiments. Toxicity predictions using benchmarks and species sensitivity distributions and statistical correlations suggested that pesticides were present at high enough concentrations to adversely affect invertebrate communities at the regional scale. Two undirected techniques-boosted regression tree models and distance-based linear models-identified which pesticides were predictors of (respectively) invertebrate metrics and community composition. To put insecticides in context with known, influential covariates of invertebrate response, generalized additive models were used to identify which individual pesticide(s) were important predictors of invertebrate community condition in each region, after accounting for natural covariates. Four insecticides were identified as stressors to invertebrate communities at the regional scale: bifenthrin, chlordane, fipronil and its degradates, and imidacloprid. Fipronil was particularly important in the Southeast region, and imidacloprid, bifenthrin, and chlordane were important in multiple regions. For imidacloprid, bifenthrin, and fipronil, toxicity predictions were supported by mesocosm experiments that demonstrated adverse effects on naïve aquatic communities when dosed under controlled conditions. These multiple lines of evidence do not prove causality-which is challenging in the field under multistressor conditions-but they make a strong case for the role of insecticides as stressors adversely affecting invertebrate communities in streams within the five sampled regions.

Mechanism of nearshore sediment-facilitated oil transport: New insights from causal inference analysis

A quantitative understanding of spilled oil transport in a nearshore environment is challenging due to the complex physicochemical processes in aqueous conditions. The physicochemical processes involved in oil sinking mainly include oil dispersion, sediment settling, and oil-sediment interaction. For the first time, this work attempts to address the sinking mechanism in petroleum contaminant transport using structural causal models based on observed data. The effects of nearshore salinity distribution from the estuary to the ocean on those three processes are examined. The causal inference reveals sediment settling is the crucial process for oil sinking. Salinity indirectly affects oil sinking by promoting sediment settling rather than directly affecting oil-sediment interaction. The increase of salinity from 0‰ to 35‰ provides a natural enhancement for sediment settling. Notably, unbiased causal effect estimates demonstrate the strongest positive causal effect on the settling efficiency of sediments is posed by increasing oil dispersion effectiveness, with a normalized value of 1.023. The highest strength of the causal relationship between oil dispersion and sediment settling highlights the importance of the dispersing characteristics of spilled oil to sediment-facilitated oil transport. The employed logic, a data-driven method, will shed light on adopting advanced causal inference tools to unravel the complicated contaminants' transport.

Improving ecosystem health in highly altered river basins: a generalized framework and its application to the Mississippi-Atchafalaya River Basin

Continued large-scale public investment in declining ecosystems depends on demonstrations of "success". While the public conception of "success" often focuses on restoration to a pre-disturbance condition, the scientific community is more likely to measure success in terms of improved ecosystem health. Using a combination of literature review, workshops and expert solicitation we propose a generalized framework to improve ecosystem health in highly altered river basins by reducing ecosystem stressors, enhancing ecosystem processes and increasing ecosystem resilience. We illustrate the use of this framework in the Mississippi-Atchafalaya River Basin (MARB) of the central United States (U.S.), by (i) identifying key stressors related to human activities, and (ii) creating a conceptual ecosystem model relating those stressors to effects on ecosystem structure and processes. As a result of our analysis, we identify a set of landscape-level indicators of ecosystem health, emphasizing leading indicators of stressor removal (e.g., reduced anthropogenic nutrient inputs), increased ecosystem function (e.g., increased water storage in the landscape) and increased resilience (e.g., changes in the percentage of perennial vegetative cover). We suggest that by including these indicators, along with lagging indicators such as direct measurements of water quality, stakeholders will be better able to assess the effectiveness of management actions. For example, if both leading and lagging indicators show improvement over time, then management actions are on track to attain desired ecosystem condition. If, however, leading indicators are not improving or even declining, then fundamental challenges to ecosystem health remain to be addressed and failure to address these will ultimately lead to declines in lagging indicators such as water quality. Although our model and indicators are specific to the MARB, we believe that the generalized framework and the process of model and indicator development will be valuable in an array of altered river basins.

Fertilization intensities at the buffer zones of ponds regulate nitrogen and phosphorus pollution in an agricultural watershed

The sudden increase in water nutrients caused by environmental factors have always been a focus of attention for ecologists. Fertilizer inputs with spatio-temporal characteristics are the main contributors to water pollution in agricultural watersheds. However, there are few studies on the thresholds of nitrogen (N) and phosphorus (P) fertilization rates that affect the abrupt deterioration of water quality. This study aims to investigate 28 ponds in Central China in 2019 to reveal the relationships of basal and topdressing fertilization intensities in surrounding agricultural land with pond water N and P concentrations, including total N (TN), nitrate (NO3--N), ammonium (NH4+-N), total P (TP), and dissolved P (DP). Abrupt change analysis was used to determine the thresholds of fertilization intensities causing sharp increases in the pond water N and P concentrations. Generally, the observed pond water N and P concentrations during the high-runoff period were higher than those during the low-runoff period. The TN, NO3--N, TP, DP concentrations showed stronger positive correlations with topdressing intensities, while the NH4+-N concentrations exhibited a higher positive correlation with basal intensities. On the other hand, the NO3--N concentrations had a significant positive correlation with the topdressing N, basal N, and catchment slope interactions. Significant negative correlations were observed between all water quality parameters and pond area. Spatial scale analysis indicated that fertilization practices at the 50 m and 100 m buffer zone scales exhibited greater independent effects on the variations in the N and P concentrations than those at the catchment scale. The thresholds analysis results of fertilization intensities indicated that pond water N concentrations increased sharply when topdressing and basal N intensities exceeded 163 and 115 kg/ha at the 100 and 50 m buffer zone scales, respectively. Similarly, pond water P concentrations rose significantly when topdressing and basal P intensities exceeded 117 and 78 kg/ha at the 50 m buffer zone scale, respectively. These findings suggest that fertilization management should incorporate thresholds and spatio-temporal scales to effectively mitigate pond water pollution.

Exploring low-carbon mulching strategies for maize and wheat on-farm: Spatial responses, factors and mitigation potential

Mulching strategies - including plastic film mulching (FM) and straw mulching (SM) - can enhance crop yields while affecting multiple greenhouse gas (GHG) fluxes. However, most of currently published site-based studies only focus on a certain gas, resulting in an inability to spatially integrated understanding of changes in agricultural global warming potential (GWP) and greenhouse gas intensity (GHGI) caused by mulching across China. Thus, we developed an optimal model considering crop type, meteorology, soil and management variables by four machine learning methods, namely support vector machine, multilayer perceptron, random forest, and gradient boosting machine (GBM). Then we mapped the relative changes in yield and GHG fluxes caused by mulching strategies. The GBM model had the best simulation capability for yield and GHGs in China. Our result showed that FM increased yield in maize (25 %) and wheat (19 %), while SM respectively increased by 14 % and 11 %. Among the relative changes due to mulching strategies, yield and N2O emissions were mainly influenced by soil fertility and soil properties, CH4 uptakes and CO2 emissions were more affected by environmental factors. GWP in maize and wheat average increased by 40 % under FM, while SM decreased GWP by 14 % and 2 %, respectively. Besides, FM average increased GHGI in maize and wheat by 17 % and 9 %, and SM decreased GHGI by 22 % and 12 %, respectively. Spatially, FM reduced maize GWP on 19 % of cropland, while SM reduced maize and wheat GWP on 71 % and 64 % of cropland, respectively. Soil pH was significantly correlated with ΔGHGI in maize and wheat. Our analysis not only estimated for the first time the spatial effects of mulching strategies across China, but also systematically analyzes the agricultural carbon emission mitigation potential of mulching strategies, which promote the development of low-carbon agriculture based on locally appropriate mulching strategies.

Disentangling natural and anthropogenic effects on benthic macroinvertebrate assemblages in western US streams

Stream macroinvertebrate assemblages are shaped by natural and human-related factors that operate through complex hierarchical pathways. Quantifying these relationships can provide additional insights into stream ecological assessment. We applied a structural equation modeling framework to evaluate hypothesized pathways by which watershed, riparian, and in-stream factors affect benthic macroinvertebrate condition in the Western Mountains (WMT) and Xeric (XER) ecoregions in the United States. We developed a conceptual model grounded in theory, empirical evidence, and expert opinion to evaluate the following hypotheses: (1) macroinvertebrate assemblages are primarily driven by proximal, in-stream factors (e.g., water quality and physical habitat); (2) anthropogenic land uses affect macroinvertebrates indirectly by altering in-stream characteristics; and (3) riparian vegetation cover attenuates land use effects. We tested our model separately on three measures of benthic macroinvertebrate assemblage condition: ratio of observed-to-expected taxonomic richness (O/E); a multimetric index (MMI); and richness of Ephemeroptera, Plecoptera, and Trichoptera taxa (EPT). In the WMT, site-level riparian cover, in-stream physical habitat (relative bed stability), and water chemistry (total nitrogen) were the top three predictors of macroinvertebrate assemblages, each having over two times the magnitude of effect on macroinvertebrates compared with watershed-level predictors. In the arid XER, annual precipitation and stream flow characteristics were top predictors of macroinvertebrate assemblages and had similar magnitudes of effect as in-stream water chemistry. Path analyses revealed that land use activities in the watershed and at the stream site degraded macroinvertebrate assemblages indirectly by altering relative bed stability, water quality, and riparian cover/complexity. Increased riparian cover was associated with greater macroinvertebrate condition by reducing land use impacts on stream flow, streambed substrate, and water quality, but the pathways differed among ecoregions. In the WMT, site-level riparian cover affected macroinvertebrate assemblages partly through indirect pathways associated with greater streambed stability and reduced total nitrogen concentrations. In contrast, in the XER, watershed-level riparian cover affected macroinvertebrate assemblages through greater specific stream power. Identifying the relative effects of and pathways by which natural and anthropogenic factors affect macroinvertebrates can serve as a framework for prioritizing management and conservation efforts.

Insight into suppression of dibutyl phthalate on DOM removal during municipal sewage treatment using fluorescence spectroscopy with PARAFAC and moving-window 2D-COS

Dibutyl phthalate (DBP) has been widely detected in municipal and industrial wastewater, which could indirectly inhibit pollutant removals, especially degradation of dissolved organic matter (DOM). Here, the inhibition of DBP on DOM removal from wastewater in pilot-scale A2O-MBR system was investigated by fluorescence spectroscopy with two-dimensional correlation (2D-COS) and structural equation modeling (SEM). Seven components were extracted from DOM using parallel factor analysis, i.e., tryptophan-like (C1 and C2), fulvic-like (C4), tyrosine-like (C5), microbial humic-like (C6) and heme-like (C7). The tryptophan-like had a blue-shift at DBP occurrence, defined as blue-shift tryptophan-like (C3). DBP with 8 mg L^-1 exhibited a stronger inhibition on removals of DOM fractions, extraordinarily tyrosine-like and tryptophan-like in anoxic unit than DBP of 6 mg L^-1 by moving-window 2D-COS. The indirect removals of C1 and C2 through the C3 removal were more strongly inhibited by 8 mg L^-1 DBP than those by 6 mg L^-1 DBP, while the former exhibited a weaker inhibition on the direct degradation of C1 and C2 than the latter via SEM. Based on metabolic pathways, abundances of key enzymes secreted by microorganism in anoxic unit, degrading tyrosine-like and tryptophan-like, were higher in wastewater with 6 mg L^-1 DBP than those with 8 mg L^-1 DBP. These could provide a potential approach for online monitoring of DBP concentrations in wastewater treatment plants, which could rectify operating parameters, and then enhance the treatment efficiencies.

Measuring the immeasurable: A structural equation modeling approach to assessing soil health

Soil health is recognized as an important ecosystem property sensitive to human impact. As a concept, soil health cannot be directly measured, and so assessment and modeling efforts largely rely upon key biological, chemical, and physical indicators. Efforts to develop an overall soil health index are largely lacking due to significant statistical challenges and the necessity for regional calibration. Taken from the field of educational research, structural equation modeling (SEM) is an attractive approach to enhance the reliability and validity of soil health scoring. Therefore, SEM may be utilized to advance research efforts to understand management practices impacts on soil health. Our objectives were to develop a robust scoring function that (i) captures the concept of soil health and latent variables, (ii) adjusts scores by inherent soil properties and legacy of intensive land use to adequately reflect our regional conditions and contemporary land management, and (iii) meets the diverse practitioner needs. Through this process, we refined our minimum dataset of soil health indicators and reconceptualized soil health indicators into functional properties. Our results support the development of a robust single level or a multilevel SEM model-depending on the practitioner's goals-that accounts for repeated sampling or pseudoreplication. While the SEM scoring functions were highly related to the conventional scoring approach, SEM outperformed the conventional methods in terms of its wider distribution of scores-and thus enhanced discriminatory power on the lower and higher range of scores. We also confirmed that the SEM scoring function that includes adjustments for mineralogy and legacy of intensive land use successfully differentiates among contemporary management practices and land use. Therefore, we have confidence that the tool is reliable and appropriate to further examine more nuanced impacts of land use change and management practices within a given land use across time and space covering a diversity of soils. (300 words).

Analysis of the Relative Importance of Stand Structure and Site Conditions for the Productivity, Species Diversity, and Carbon Sequestration of Cunninghamia lanceolata and Phoebe bournei Mixed Forest

Forest stand structure (the characteristics and interrelationships of live trees) and site conditions (the physical and environmental characteristics of a specific location) have been linked to forest regeneration, nutrient cycling, wildlife habitat, and climate regulation. While the effects of stand structure (i.e., spatial and non-spatial) and site conditions on the single function of Cunninghamia lanceolata and Phoebe bournei (CLPB) mixed forest have been studied in previous studies, the relative importance of stand structure and site conditions in terms of productivity, species diversity, and carbon sequestration remains unresolved. In this study, a structural equation model (SEM) was adopted to analyze the relative importance of stand structure and site conditions for the forest productivity, species diversity, and carbon sequestration of CLPB mixed forest in Jindong Forestry in Hunan Province. Our research demonstrates that site conditions have a greater influence on forest functions than stand structure, and that non-spatial structures have a greater overall impact on forest functions than spatial structures. Specifically, the intensity of the influence of site conditions and non-spatial structure on functions is greatest for productivity, followed by carbon sequestration and species diversity. In contrast, the intensity of the influence of spatial structure on functions is greatest for carbon sequestration, followed by species diversity and productivity. These findings provide valuable insights for the management of CLPB mixed forest in Jindong Forestry and have significant reference value for the close-to-natural forest management (CTNFM) of pure Cunninghamia lanceolata forests.

Identifying the impact of toxicity on stream macroinvertebrate communities in a multi-stressor context based on national ecological and ecotoxicological monitoring databases

In situ bioassays are used to measure the harmful effects induced by mixtures of toxic chemicals in watercourses. In France, national-scale biomonitoring data are available including invertebrate surveys and in-field chemical toxicity measures with caged gammarids to assess environmental toxicity of mixtures of chemicals. The main objective of our study is to present a proof-of-concept approach identifying possible links between in-field chemical toxicity, stressors and the ecological status. We used two active biomonitoring databases comprising lethal toxicity (222 in situ measures of gammarid mortality) and sublethal toxicity (101 in situ measures of feeding inhibition). We measured the ecological status of each active biomonitoring site using the I₂M₂ metric (macroinvertebrate-based multimetric index), accounted for known stressors of nutrients and organic matter, hydromorphology and chemical toxicity. We observed a negative relationship between stressors (hydromorphology, nutrients and organic matter, and chemical toxicity) and the good ecological status. This relationship was aggravated in watercourses where toxicity indicators were degraded. We validated this hypothesis for instance with nutrients and organic matter like nitrates or hydromorphological conditions like percentage of vegetation on banks. Future international assesments concerning the role of in-field toxic pollution on the ecological status in a multi-stressor context are now possible via the current methodology.

Identifying Key Stressors Driving Biological Impairment in Freshwater Streams in the Chesapeake Bay Watershed, USA

Biological communities in freshwater streams are often impaired by multiple stressors (e.g., flow or water quality) originating from anthropogenic activities such as urbanization, agriculture, or energy extraction. Restoration efforts in the Chesapeake Bay watershed, USA seek to improve biological conditions in 10% of freshwater tributaries and to protect the biological integrity of existing healthy watersheds. To achieve these goals, resource managers need to better understand which stressors are most likely driving biological impairment. Our study addressed this knowledge gap through two approaches: 1) reviewing and synthesizing published multi-stressor studies, and 2) examining 303(d) listed impairments linked to biological impairment as identified by jurisdiction regulatory agencies (the states within the watershed and the District of Columbia). Results identified geomorphology (i.e., physical habitat), salinity, and toxic contaminants as important for explaining variability in benthic community metrics in the literature review. Geomorphology (i.e., physical habitat and sediment), salinity, and nutrients were the most reported stressors in the jurisdictional impairment analysis. Salinity is likely a major stressor in urban and mining settings, whereas geomorphology was commonly reported in agricultural settings. Toxic contaminants, such as pesticides, were rarely measured; more research is needed to quantify the extent of their effects in the region. Flow alteration was also highlighted as an important urban stressor in the literature review but was rarely measured in the literature or reported by jurisdictions as a cause of impairment. These results can be used to prioritize stressor monitoring by managers, and to improve stressor identification methods for identifying causes of biological impairment.

Applying EEM-PARAFAC combined with moving-window 2DCOS and structural equation modeling to characterize binding properties of Cu (II) with DOM from different sources in an urbanized river

Dissolved organic matter (DOM) in aquatic environment distinctly affects the behavior and fate of heavy metals via complexation, while the interfacial mechanisms and processes are still lacking in detail. Here, Cu (II) binding characteristics of DOM originated from hilly (NDOM), rural (RDOM) and urban (UDOM) regions in an urbanized river was explored by fluorescence excitation-emission matrix spectroscopy (EEM) combined with principal component coefficients, parallel factor analyses (PARAFAC), moving-window two-dimensional correlation spectroscopy (MW2DCOS) and structural equation modeling (SEM). Eight components were extracted from the titrants through EEM-PARAFAC, i.e., phenol-like substance (C1), tyrosine-like substance (C2), visible tryptophan-like substance (C3), ultraviolet tryptophan-like substance (C4), recent biological production (C5), wastewater-derived organic matter (C6), microbial humic-like substance (C7) and fulvic-like substance (C8). Interestingly, NDOM only contained C1, C3, C5 and C8, while nearly all components were found in RDOM (except for C2) and UDOM (except for C4). The f value of C1 (1.239) in NDOM was much higher than those in RDOM (0.134) and UDOM (0.115), so was of C8. It indicated that phenol-like and fulvic-like derived from autochthonous sources exhibited great binding ratios in the complexation with Cu (II). Moreover, C3 and C5 from UDOM exhibited higher f values (0.591 and 1.983) than those from NDOM and RDOM, suggesting that Cu (II) has a great binding capacity on protein-like from domestic and industrial wastewater. The MW2DCOS revealed that phenol-like and protein-like in NDOM and RDOM were essential for the binding of 160 μmol L^-1 Cu (II), whereas fulvic-like in NDOM and UDOM could react significantly with 10 μmol L^-1 Cu (II). Based on SEM, Cu (II) concentration had a negative direct effect on the fluorescence intensity of C7 or C8, whereas it showed an indirect positive effect on C7 or C8 through influencing C5, so was C6. It suggested that Cu (II) showed an indirect positive effect on the C8. This study might present a further comprehend of the environmental behaviors of Cu (II) in rivers.

Insight into structural composition of dissolved organic matter in saline-alkali soil by fluorescence spectroscopy coupled with self-organizing map and structural equation modeling

Soil salinization has been occurring all over the world, which severely affected crop production and threatened the life of mankind. It is necessary to take serious steps to improve soil fertility for the sustainability and productive capacity of agriculture. Soil samples of different depths were collected from native vegetation communities (Comm. Phragmites communis (CPC) and Comm. Populus alba (CPA)) and irrigated crops (corn fields (CFD) and seed melon fields (SMF)) in Hetao irrigation area of China. Three dimensional excitation-emission matrix (EEM) fluorescence technology combined with self-organizing map were used to analyze the dissolved organic matter (DOM) composition and structural characteristics in saline-alkali soils and its spatial distribution under different vegetation covers. Critical factors were recognized by classification and regression tree (CART) for distinguishing soil samples, and latent factors were revealed with structural equation modeling (SEM) for improving the humification degree of DOM from saline soils in Hetao irrigation area. Five components were obtained in the DOM substances, i.e., tyrosine-like (C1), tryptophan-like (C2), UV fulvic-like (C3), visible fulvic-like (C4) and humic-like (C5). The protein-like peaks were all obvious, and the fulvic-like peaks (600-735 a.u.) were conspicuous in the CPC soil than in others, except CFD1 and SMF1. C1 was the critical factor to distinguish native vegetation from irrigated crops, and C1 and C2 were the critical factors to distinguish CFD from SMF. Contrary to the HA/FA (0.20) and A/C (0.25), the path coefficient (-0.15) of sources with T/H was negative, indicating that the incremental contents of fluorenscense substances were in the sequences of protein-like > visible fulvic-like > UV fulvic-like > humic-like, affecting by the allochthonous. C1 (1.00) and C4 (1.00) were the primary components for improving the humification degree of DOM, which were principally originated from plant debris. EEM combined with self-organizing map, CART and SEM is an efficient way to distinguish different salinized soils and reveal the latent factors for improving the soil fertility.

What do we want to estimate from observational datasets? Choosing appropriate statistical analysis methods based on the chemical management phase

The goals of observational dataset analysis vary with the management phase of environments threatened by anthropogenic chemicals. For example, identifying severely compromised sites is necessary to determine candidate sites in which to implement measures during early management phases. Among the most effective approaches is developing regression models with high predictive power for dependent variable values using the Akaike information criterion. However, this analytical approach may be theoretically inappropriate to obtain the necessary information in various chemical management phases, such as the intervention effect size of a chemical required in the late chemical management phase to evaluate the necessity of an effluent standard and its specific value. However, choosing appropriate statistical methods based on the data analysis objective in each chemical management phase has rarely been performed. This study provides an overview of the primary data analysis objectives in the early and late chemical management phases. For each objective, several suitable statistical analysis methods for observational datasets are detailed. In addition, the study presents examples of linear regression analysis procedures using an available dataset derived from field surveys conducted in Japanese rivers. Integr Environ Assess Manag 2022;18:1414-1422. © 2021 The Authors. Integrated Environmental Assessment and Management published by Wiley Periodicals LLC on behalf of Society of Environmental Toxicology & Chemistry (SETAC).

Natural and anthropogenic factors and their interactions drive stream community integrity in a North American river basin at a large spatial scale

Urbanization, agriculture, and other human activities can exert considerable influence on the health and integrity of stream ecosystems. These influences vary greatly over space, time, and scale. We investigated trends in stream biotic integrity over 19 years (1997-2016) in relation to natural and anthropogenic factors in their spatial context using data from a stream biomonitoring program in a region dominated by agricultural land use. Macroinvertebrate and fish diversity and abundance data were used to calculate four multimetric indices (MMIs) that described biotic integrity of streams from 1997 to 2016. Boosted regression trees (BRT), a machine learning technique, were used to model how stream integrity responded to catchment-level natural and anthropogenic drivers including land use, human population density, road density, runoff potential, and natural factors such as latitude and elevation. Neither natural nor anthropogenic factors were consistently more influential on the MMIs. Macroinvertebrate indices were most responsive to time, latitude, elevation, and road density. Fish indices were driven mostly by latitude and longitude, with agricultural land cover among the most influential anthropogenic factors. We concluded that 1) stream biotic integrity was mostly stable in the study region from 1997 to 2016, although macroinvertebrate MMIs had decreased approximately 10% since 2010; 2) stream biotic integrity was driven by a mix of factors including geography, human activity, and variability over yearly time intervals; 3) MMI responses to environmental drivers were nonlinear and often nonmonotonic; 4) MMI composition could influence causal inferences; and 5) although our findings were mostly consistent with the literature on drivers of stream integrity, some commonly seen patterns were not evident. Our findings highlight the utility of large-scale, publicly available spatial data for understanding drivers of stream biodiversity and illustrate some potential pitfalls of large scale, integrative analyses.

Physical habitat in conterminous US streams and Rivers, part 2: A quantitative assessment of habitat condition

Rigorous assessments of the ecological condition of water resources and the effect of human activities on those waters require quantitative physical, chemical, and biological data. The U.S. Environmental Protection Agency's river and stream surveys quantify river and stream bed particle size and stability, instream habitat complexity and cover, riparian vegetation cover and structure, and anthropogenic disturbance activities. Physical habitat is strongly controlled by natural geoclimatic factors that co-vary with human activities. We expressed the anthropogenic alteration of physical habitat as O/E ratios of observed habitat metric values divided by values expected under least-disturbed reference conditions, where site-specific expected values vary given their geoclimatic and geomorphic context. We set criteria for good, fair, and poor condition based on the distribution of O/E values in regional least-disturbed reference sites. Poor conditions existed in 22-24% of the 1.2 million km of streams and rivers in the conterminous U.S. for riparian human disturbance, streambed sediment and riparian vegetation cover, versus 14% for instream habitat complexity. Based on the same four indicators, the percentage of stream length in poor condition within 9 separate U.S. ecoregions ranged from 4% to 42%. Associations of our physical habitat indices with anthropogenic pressures demonstrate the scope of anthropogenic habitat alteration; habitat condition was negatively related to the level of anthropogenic disturbance nationally and in nearly all ecoregions. Relative risk estimates showed that streams and rivers with poor sediment, riparian cover complexity, or instream habitat cover conditions were 1.4 to 2.6 times as likely to also have fish or macroinvertebrate assemblages in poor condition. Our physical habitat condition indicators help explain deviations in biological conditions from those observed among least-disturbed sites and inform management actions for rehabilitating impaired waters and mitigating further ecological degradation.

Physical habitat in conterminous US streams and rivers, Part 1: Geoclimatic controls and anthropogenic alteration

Anthropogenic alteration of physical habitat structure in streams and rivers is increasingly recognized as a major cause of impairment worldwide. As part of their assessment of the status and trends in the condition of rivers and streams in the U.S., the U.S. Environmental Protection Agency's (USEPA) National Aquatic Resource Surveys (NARS) quantify and monitor channel size and slope, substrate size and stability, instream habitat complexity and cover, riparian vegetation cover and structure, anthropogenic disturbance activities, and channel-riparian interaction. Like biological assemblages and water chemistry, physical habitat is strongly controlled by natural geoclimatic factors that can obscure or amplify the influence of human activities. We developed a systematic approach to estimate the deviation of observed river and stream physical habitat from that expected in least-disturbed reference conditions. We applied this approach to calculate indices of anthropogenic alteration of three aspects of physical habitat condition in the conterminous U.S. (CONUS): streambed sediment size and stability, riparian vegetation cover, and instream habitat complexity. The precision and responsiveness of these indices led the USEPA to use them to evaluate physical habitat condition in CONUS rivers and streams. The scores of these indices systematically decreased with greater anthropogenic disturbance at river and stream sites in the CONUS and within ecoregions, which we interpret as a response of these physical habitat indices to anthropogenic influences. Although anthropogenic activities negatively influenced all three physical habitat indices in the least-disturbed sites within most ecoregions, natural geoclimatic and geomorphic factors were the dominant influences. For sites over the full range of anthropogenic disturbance, analyses of observed/expected sediment characteristics showed augmented flood flows and basin and riparian agriculture to be the leading predictors of streambed instability and excess fine sediments. Similarly, basin and riparian agriculture and non-agricultural riparian land uses were the leading predictors of reduced riparian vegetation cover complexity in the CONUS and within ecoregions. In turn, these reductions in riparian vegetation cover and complexity, combined with reduced summer low flows, were the leading predictors of instream habitat simplification. We conclude that quantitative measures of physical habitat structure are useful and important indicators of the impacts of human activities on stream and river condition.

Characterizing the exposure of streams in southern Ontario to agricultural pesticides

Aquatic communities can be exposed to pesticides transported from land. Characterizing this exposure is key to predicting potential toxic effects. In this study, samples of streamwater from 21 sites were used to characterize pesticide exposure to aquatic communities. Sites were in agricultural areas of southwestern Ontario, Canada and were sampled monthly from 2012 to 2019 from April to November. Samples were analyzed for a suite of hundreds of pesticides and pesticide degradation products and other water quality indicators (e.g., nutrients). Frequently detected pesticides included herbicides (2,4-D; bentazon; MCPP; metolachlor) and neonicotinoid insecticides (NNIs) (clothianidin; thiamethoxam) which were detected in >50% of samples collected between 2015 and 2019. Non-metric multidimensional scaling (NMDS) was used to explore connections between pesticide concentrations and upstream land use and crop type. Detectable concentrations of the NNI clothianidin and many herbicides were related to corn, soybean, and grain/cereal crops while concentrations of the NNI imidacloprid, insecticide flonicamid, and fungicide boscalid were related to greenhouse/nursery land use. Potential toxicity to aquatic communities was assessed by comparing pesticide concentrations to Pesticide Toxicity Index (PTI) values. Few samples exceeded levels where acute (1% of samples) or chronic toxicity (10.5%) would be expected. The diamide insecticide chlorantraniliprole was detected in several streamwater samples at levels that may cause toxicity to aquatic invertebrates, highlighting the need for continued toxicity research into this pesticide class. The number of pesticides detected was positively correlated with nutrient and total suspended solids levels, underscoring the multiple stressors aquatic communities are exposed to in these habitats.

Ecological consequences of neonicotinoid mixtures in streams

Neonicotinoid mixtures are common in streams worldwide, but corresponding ecological responses are poorly understood. We combined experimental and observational studies to narrow this knowledge gap. The mesocosm experiment determined that concentrations of the neonicotinoids imidacloprid and clothianidin (range of exposures, 0 to 11.9 μg/liter) above the hazard concentration for 5% of species (0.017 and 0.010 μg/liter, respectively) caused a loss in taxa abundance and richness, disrupted adult emergence, and altered trophodynamics, while mixtures of the two neonicotinoids caused dose-dependent synergistic effects. In 85 Coastal California streams, neonicotinoids were commonly detected [59% of samples (n = 340), 72% of streams], frequently occurred as mixtures (56% of streams), and potential toxicity was dominated by imidacloprid (maximum = 1.92 μg/liter) and clothianidin (maximum = 2.51 μg/liter). Ecological responses in the field were consistent with the synergistic effects observed in the mesocosm experiment, indicating that neonicotinoid mixtures pose greater than expected risks to stream health.

Machine learning-aided causal inference for unraveling chemical dispersant and salinity effects on crude oil biodegradation

Chemical dispersants have been widely applied to tackle oil spills, but their effects on oil biodegradation in global aquatic systems with different salinities are not well understood. Here, both experiments and advanced machine learning-aided causal inference analysis were applied to evaluate related processes. A halotolerant oil-degrading and biosurfactant-producing species was selected and characterized within the salinity of 0-70 g/L NaCl. Notably, dispersant addition can relieve the biodegradation barriers caused by high salinities. To navigate the causal relationships behind the experimental data, a structural causal model to quantitatively estimate the strength of causal links among salinity, dispersant addition, cell abundance, biosurfactant productivity and oil biodegradation was built. The estimated causal effects were integrated into a weighted directed acyclic graph, which showed that overall positive effects of dispersant addition on oil biodegradation was mainly through the enrichment of cell abundance. These findings can benefit decision-making prior dispersant application under different saline environments.

Multiple in-stream stressors degrade biological assemblages in five U.S. regions

Biological assemblages in streams are affected by a wide variety of physical and chemical stressors associated with land-use development, yet the importance of combinations of different types of stressors is not well known. From 2013 to 2017, the U.S. Geological Survey completed multi-stressor/multi-assemblage stream ecological assessments in five regions of the United States (434 streams total). Diatom, invertebrate, and fish communities were enumerated, and five types of potential stressors were quantified: habitat disturbance, excess nutrients, high flows, basic water quality, and contaminants in water and sediment. Boosted regression tree (BRT) models for each biological assemblage and region generally included variables from all five stressor types and multiple stressors types in each model was the norm. Classification and regression tree (CART) models then were used to determine thresholds for each BRT model variable above which there appeared to be adverse effects (multi-metric index (MMI) models only). In every region and assemblage there was a significant inverse relation between the MMI and the number of stressors exerting potentially adverse effects. The number of elevated instream stressors often varied substantially for a given level of land-use development and the number of elevated stressors was a better predictor of biological condition than was development. Using the adverse effects-levels that were developed based on the BRT model results, 68% of the streams had two or more stressors with potentially adverse effects and 35% had four or more. Our results indicate that relatively small increases in the number of stressors of different types can have a large effect on a stream ecosystem.

Revealing heavy metal correlations with water quality and tracking its latent factors by canonical correlation analysis and structural equation modeling in Dongjianghu Lake

Decreasing levels of water quality and elevated concentrations of heavy metals in freshwaters can pose global challenges for drinking water sources. Multivariate statistical techniques have been applied on data matrices of water quality and heavy metals for keen characterization of their spatio-temporal variations, exploration of latent factors, and identification of pollution sources. Non-metric multidimensional scaling (nMDS), canonical correlation analysis (CCA), and structural equation modeling (SEM) were employed to process data matrices of the water quality and heavy metals with 14 parameters measured at 13 sampling sites in Dongjianghu Lake in March, June, August, and December 2016. The sampling sites were grouped into three clusters using the nMDS, suggesting that the increasing order of the water quality levels was approximately midstream < downstream < upstream and lake. The CCA of 14 parameters proved that the Escherichia coli, COD_Mn, TP, TN, TEMP, DO, and pH were the latent factors to distinguish the sampling sites, suggesting that the natural disturbances further influenced the lake and upstream, while the anthropogenic activities further influenced the midstream and downstream. The CCA of the heavy metals exhibited that the COD_Mn, F^-, and E. coli were the latent factors of the Cu, Zn, and As, while the DO and TEMP were the latent factors of the Cd. This indicated that the Cu, As, and Zn were mainly associated with the anthropogenic activities, while the Cd was predominantly relative to the natural conditions. The SEM of the water quality and heavy metals showed that the weights of COD_Mn (28.64%), NH₃-N (14.96%), BOD₅ (14.32%), TN (12.88%), and TP (10.18%) were higher than those of the pH (8.37%), DO (7.73%), TEMP (2.58%), and E. coli (0.34%). This indicated that the former exhibited strong influences on the heavy metals than the latter. Moreover, the COD_Mn and BOD₅ were the key factors of the heavy metals, which should be attributed to the no-point sources, especially the exploitation mining and mill tailings. The water quality assessment by the nMDS, CCA, and SEM can determine the status, trend corresponding to its standards, and trace latent factors and identify possible pollution sources. The study could provide a guide for water quality evaluation and pollution control.

Time marches on, but do the causal pathways driving instream habitat and biology remain consistent?

Stream ecosystems are complex networks of interacting terrestrial and aquatic drivers. To untangle these ecological networks, efforts evaluating the direct and indirect effects of landscape, climate, and instream predictors on biological condition through time are needed. We used structural equation modeling and leveraged a stream survey program to identify and compare important predictors driving condition of benthic macroinvertebrate and fish assemblages. We used data resampled 14 years apart at 252 locations across Maryland, USA. Sample locations covered a wide range of conditions that varied spatiotemporally. Overall, the relationship directions were consistent between sample periods, but their relative strength varied temporally. For benthic macroinvertebrates, we found that the total effect of natural landscape (e.g., elevation, longitude, latitude, geology) and land use (i.e., forest, development, agriculture) predictors was 1.4 and 1.5 times greater in the late 2010s compared to the 2000s. Moreover, the total effect of water quality (e.g., total nitrogen and conductivity) and habitat (e.g., embeddedness, riffle quality) was 1.2 and 4.8 times lower in the 2010s, respectively. For fish assemblage condition, the total effect of land use-land cover predictors was 2.3 times greater in the 2010s compared to the 2000s, while the total effect of local habitat was 1.4 times lower in the 2010s, respectively. As expected, we found biological assemblages in catchments with more agriculture and urban development were generally comprised of tolerant, generalist species, while assemblages in catchments with greater forest cover had more-specialized, less-tolerant species (e.g., Ephemeroptera, Plecoptera, and Trichoptera taxa, clingers, benthic and lithophilic spawning fishes). Changes in the relative importance of landscape and land-use predictors suggest other correlated, yet unmeasured, proximal factors became more important over time. By untangling these ecological networks, stakeholders can gain a better understanding of the spatiotemporal relationships driving biological condition to implement management practices aimed at improving stream condition.

Cross-Ecosystem Fluxes of Pesticides from Prairie Wetlands Mediated by Aquatic Insect Emergence: Implications for Terrestrial Insectivores

Contaminants alter the quantity and quality of insect prey available to terrestrial insectivores. In agricultural regions, the quantity of aquatic insects emerging from freshwaters can be impacted by insecticides originating from surrounding croplands. We hypothesized that, in such regions, adult aquatic insects could also act as vectors of pesticide transfer to terrestrial food webs. To estimate insect-mediated pesticide flux from wetlands embedded in an important agricultural landscape, semipermanetly and temporarily ponded wetlands were surveyed in cropland and grassland landscapes across a natural salinity gradient in the Prairie Pothole Region of North Dakota (USA) during the bird breeding season in 2015 and 2016 (n = 14 and 15 wetlands, respectively). Current-use pesticides, including the herbicide atrazine and the insecticides bifenthrin and imidacloprid, were detected in newly emerged insects. Pesticide detections were similar in insects emerging from agricultural and grassland wetlands. Biomass of emerging aquatic insects decreased 43%, and insect-mediated pesticide flux increased 50% along the observed gradient in concentrations of insecticides in emerging aquatic insects (from 3 to 577 ng total insecticide g^-1 insect). Overall, adult aquatic insects were estimated to transfer between 2 and 180 µg total pesticide wetland^-1  d^-1 to the terrestrial ecosystem. In one of the 2 study years, biomass of emerging adult aquatic insects was also 73% lower from agricultural than grassland wetlands and was dependent on salinity. Our results suggest that accumulated insecticides reduce the availability of adult aquatic insect prey for insectivores and potentially increase insectivore exposure to insect-borne pesticides. Adult aquatic insects retain pesticides across metamorphosis and may expose insectivores living near both agricultural and grassland wetlands to dietary sources of toxic chemicals. Environ Toxicol Chem 2021;40:2282-2296. Published 2021. This article is a U.S. Government work and is in the public domain in the USA.

Probability maps of anthropogenic impacts affecting ecological status in European rivers

Understanding how anthropogenic pressures affect river ecological status is pivotal to designing effective management strategies. Knowledge on river aquatic habitats status in Europe has increased tremendously since the introduction of the European Union Water Framework Directive, yet heterogeneities in mandatory monitoring and reporting still limit identification of patterns at continental scale. Concurrently, several model and data-based indicators of anthropogenic pressures to freshwater that cover the continent consistently have been developed. The objective of this work was to create European maps of the probability of occurrence of river conditions, namely failure to achieve good ecological status, or to be affected by specific pervasive impacts. To this end, we applied logistic regression methods to model the river conditions as functions of continental-scale water pressure indicators. The prediction capacity of the models varied with river condition: the probability to fail achieving good ecological status, and occurrence of nutrient and organic pollution were rather well predicted; conversely, chemical (other than nutrient and organic) pollution and alteration of habitats due to hydrological or morphological changes were poorly predicted. The most important indicators explaining river conditions were the shares of agricultural and artificial land, mean annual net abstractions, share of pollution loads from point sources, and the share of upstream river length uninterrupted by barriers. The probability of failing to achieve good ecological status was estimated to be high (>60%) for 36% of the considered river network of about 1.6 M km. Occurrence of impact of nutrient pollution was estimated high (>60%) in 26% of river length and that of organic pollution 20%. The maps are built upon information reported at country level pursuant EU legal obligations, as well as indicators generated from European scale models and data: both sources are affected by epistemic uncertainty. In particular, reported information depend on data collection scoping and schemes, as well as national knowledge and interpretation of river system pressures. In turn, water pressure indicators are affected by heterogeneous biases due to incomplete or incorrect inputs and uncertainty of models adopted. Lack of effective reach- and site-scale indicators may hamper detection of locally relevant impacts, for example in explaining alteration of habitats due to morphological changes. The probability maps provide a continental snapshot of current river conditions, and offer an alternative source of information on river aquatic habitats, which may help filling in knowledge gaps. Foremost, the analysis demonstrates the need for developing more effective continental-scale indicators for hydromorphological alterations and chemical pollution.

Environmental and anthropogenic drivers of contaminants in agricultural watersheds with implications for land management

If not managed properly, modern agricultural practices can alter surface and groundwater quality and drinking water resources resulting in potential negative effects on aquatic and terrestrial ecosystems. Exposure to agriculturally derived contaminant mixtures has the potential to alter habitat quality and negatively affect fish and other aquatic organisms. Implementation of conservation practices focused on improving water quality continues to increase particularly in agricultural landscapes throughout the United States. The goal of this study was to determine the consequences of land management actions on the primary drivers of contaminant mixtures in five agricultural watersheds in the Chesapeake Bay, the largest watershed of the Atlantic Seaboard in North America where fish health issues have been documented for two decades. Surface water was collected and analyzed for 301 organic contaminants to determine the benefits of implemented best management practices (BMPs) designed to reduce nutrients and sediment to streams in also reducing contaminants in surface waters. Of the contaminants measured, herbicides (atrazine, metolachlor), phytoestrogens (formononetin, genistein, equol), cholesterol and total estrogenicity (indicator of estrogenic response) were detected frequently enough to statistically compare to seasonal flow effects, landscape variables and BMP intensity. Contaminant concentrations were often positively correlated with seasonal stream flow, although the magnitude of this effect varied by contaminant across seasons and sites. Land-use and other less utilized landscape variables including biosolids, manure and pesticide application and percent phytoestrogen producing crops were inversely related with site-average contaminant concentrations. Increased BMP intensity was negatively related to contaminant concentrations indicating potential co-benefits of BMPs for contaminant reduction in the studied watersheds. The information gained from this study will help prioritize ecologically relevant contaminant mixtures for monitoring and contributes to understanding the benefits of BMPs on improving surface water quality to better manage living resources in agricultural landscapes inside and outside the Chesapeake Bay watershed.

Linking Altered Flow Regimes to Biological Condition: an Example Using Benthic Macroinvertebrates in Small Streams of the Chesapeake Bay Watershed

Regionally scaled assessments of hydrologic alteration for small streams and its effects on freshwater taxa are often inhibited by a low number of stream gages. To overcome this limitation, we paired modeled estimates of hydrologic alteration to a benthic macroinvertebrate index of biotic integrity data for 4522 stream reaches across the Chesapeake Bay watershed. Using separate random-forest models, we predicted flow status (inflated, diminished, or indeterminant) for 12 published hydrologic metrics (HMs) that characterize the main components of flow regimes. We used these models to predict each HM status for each stream reach in the watershed, and linked predictions to macroinvertebrate condition samples collected from streams with drainage areas less than 200 km2. Flow alteration was calculated as the number of HMs with inflated or diminished status and ranged from 0 (no HM inflated or diminished) to 12 (all 12 HMs inflated or diminished). When focused solely on the stream condition and flow-alteration relationship, degraded macroinvertebrate condition was, depending on the number of HMs used, 3.8-4.7 times more likely in a flow-altered site; this likelihood was over twofold higher in the urban-focused dataset (8.7-10.8), and was never significant in the agriculture-focused dataset. Logistic regression analysis using the entire dataset showed for every unit increase in flow-alteration intensity, the odds of a degraded condition increased 3.7%. Our results provide an indication of whether altered streamflow is a possible driver of degraded biological conditions, information that could help managers prioritize management actions and lead to more effective restoration efforts.

A Review of Biological Monitoring of Aquatic Ecosystems Approaches: with Special Reference to Macroinvertebrates and Pesticide Pollution

Biological monitoring is the evaluating changes in the environment using the biological responses with the intent of using such information in quality control of the ecosystem. Biomarkers and bioindicators are two main components of the hierarchy of biomonitoring process. Bioindicators can be used to monitor changes of ecosystems and to distinguish alteration of human impact from natural variability. There is a wide range of aquatic taxa such as macroinvertebrates, fish and periphyton, planktons which are successfully used in the biomonitoring process. Among them, macroinvertebrates are an important group of aquatic organisms that involves transferring energy and material through the trophic levels of the aquatic food chain and their sensitivity to environmental changes differs among the species. The main approaches of assessing freshwater ecosystems health using macroinvertebrates include measurement of diversity indices, biotic indices, multimetric approaches, multivariate approaches, Indices of Biological Integrity (IBI), and trait-based approaches. Among these, biotic indices and multimetric approaches are commonly used to evaluate the pesticide impacts on aquatic systems. Recently developed trait-based approaches such as SPEcies At Risk of pesticides (SPEAR) index was successfully applied in temperate regions to monitor the events of pesticide pollution of aquatic ecosystems but with limited use in tropics. This paper reviews the literature on different approaches of biomonitoring of the aquatic environment giving special reference to macroinvertebrates. It also reviews the literature on how biomonitoring could be used to monitor pesticide pollution of the aquatic environment. Thus the review aims to instil the importance of current approaches of biomonitoring for the conservation and management of aquatic ecosystems especially in the regions of the world where such knowledge has not been integrated in ecosystem conservation approaches.

Risk Assessment of Pesticide Mixtures in Australian Rivers Discharging to the Great Barrier Reef

Rivers discharging to the Great Barrier Reef carry complex pesticide mixtures. Here we present a first comprehensive ecotoxicological risk assessment using species sensitivity distributions (SSDs), explore how risk changes with time and land use, and identify the drivers of mixture risks. The analyzed data set comprises 50 different pesticides and pesticide metabolites that were analyzed in 3741 samples from 18 river and creek catchments between 2011 and 2016. Pesticide mixtures were present in 82% of the samples, with a maximum of 23 pesticides and a median of five compounds per sample. Chemical-analytical techniques were insufficiently sensitive for at least seven pesticides (metsulfuron-methyl, terbutryn, imidacloprid, clothianidin, ametryn, prometryn, and thiamethoxam). The classical mixture concepts of concentration addition and independent action were applied to the pesticide SSDs, focusing on environmental threshold values protective for 95% of the species. Both concepts produced almost identical risk estimates. Mixture risk was therefore finally assessed using concentration addition, as the sum of the individual risk quotients. The sum of risk quotients ranges between 0.05 and 122 with a median of 0.66. An ecotoxicological risk (i.e., a sum of individual risk quotients exceeding 1) was indicated in 38.5% of the samples. Sixteen compounds accounted for 99% of the risk, with diuron, imidacloprid, atrazine, metolachlor, and hexazinone being the most important risk drivers. Analysis of land-use patterns in catchment areas showed an association between sugar cane farming and elevated risk levels, driven by the presence of diuron.

Common insecticide disrupts aquatic communities: A mesocosm-to-field ecological risk assessment of fipronil and its degradates in U.S. streams

Insecticides in streams are increasingly a global concern, yet information on safe concentrations for aquatic ecosystems is sparse. In a 30-day mesocosm experiment exposing native benthic aquatic invertebrates to the common insecticide fipronil and four degradates, fipronil compounds caused altered emergence and trophic cascades. Effect concentrations eliciting a 50% response (EC50) were developed for fipronil and its sulfide, sulfone, and desulfinyl degradates; taxa were insensitive to fipronil amide. Hazard concentrations for 5% of affected species derived from up to 15 mesocosm EC50 values were used to convert fipronil compound concentrations in field samples to the sum of toxic units (∑TUFipronils). Mean ∑TUFipronils exceeded 1 (indicating toxicity) in 16% of streams sampled from five regional studies. The Species at Risk invertebrate metric was negatively associated with ∑TUFipronils in four of five regions sampled. This ecological risk assessment indicates that low concentrations of fipronil compounds degrade stream communities in multiple regions of the United States.

The effect of intervention in nickel concentrations on benthic macroinvertebrates: A case study of statistical causal inference in ecotoxicology

Field survey-based ecological risk assessments for trace metals are conducted to examine the necessity and/or effectiveness of management intervention, such as setting of environmental quality standards. Observational datasets often involve confounders that may bias estimation of the effects of intervention (e.g., reduction of trace-metal concentrations through regulation). The field of ecotoxicology lags behind some other research fields in understanding proper analytical procedures for causal inference from observational datasets; there are only a few field survey-based ecotoxicological studies that have explicitly controlled for confounders in their statistical analyses. In the present study, we estimated the effect of intervention in nickel concentrations on Ephemeroptera, Plecoptera, and Trichoptera richness in rivers in Japan. We also provide detailed explanations for the backgrounds of spurious associations derived from confounders and on proper analytical procedures for obtaining an unbiased estimate of the targeted intervention effect by using regression analysis. We constructed a multiple regression model based on a causal diagram for aquatic insects and environmental factors, and on "the backdoor criterion," that enabled us to determine the set of covariates required to obtain an unbiased estimate of the targeted intervention effect from regression coefficients. We found that management intervention in nickel concentrations may be ineffective compared to intervention in organic pollution, and that analysis ignoring the confounders overestimated the effect of intervention in nickel concentrations. Our results highlight the fact that confounders can lead to misjudging the necessity for management of anthropogenic chemical substances. Confounders should be explicitly specified and statistically controlled to achieve a comprehensive assessment of ecological risks for various substances.

How to quantify the links between bioavailable contamination in watercourses and pressures of anthropogenic land cover, contamination sources and hydromorphology at multiple scales?

Active biomonitoring permits the quantification of biological exposure to chemicals through measurements of bioavailable concentrations in biota and biological markers of toxicity in organisms. It enables respective comparison of the levels of contamination between sites and sampling campaigns. Caged gammarids are recently proposed as relevant probes for measuring bioavailable contamination in freshwater systems. The purpose of the present study was to develop a multi-pressure and multiscale approach, considering metallic contamination levels (from data based on active biomonitoring) as a response to pressures (combination of individual stressors). These pressures were anthropogenic land cover, industry density, wastewater treatment plant density, pressures on stream hydromorphological functioning, riverside vegetation and bioavailability factors. A dataset combining active biomonitoring and potentially related pressures was established at the French national scale, with 196 samplings from 2009 to 2016. The links between pressures and metallic contamination were defined and modelled via structural equation modeling (more specifically partial least squares - path modeling). The model enabled the understanding of the respective influences of pressures on metallic bioconcentration in caged sentinel organisms. Beyond validating the local influence of industries and wastewater treatment plants on metallic contamination, this model showed a complementary effect of driving forces of anthropogenic land cover (leading to human activities). It also quantified a significant influence of pressures on stream hydromorphological functioning, presence of vegetation and physico-chemical parameters on metal bioconcentration. This hierarchical multi-pressure approach could serve as a concept on how pressures and contamination (assessed by active biomonitoring) can be connected. Its future application will enable better understanding of environmental pressures leading to contamination in freshwater ecosystems.

Prioritizing river basins for intensive monitoring and assessment by the US Geological Survey

The US Geological Survey (USGS) is currently (2020) integrating its water science programs to better address the nation's greatest water resource challenges now and into the future. This integration will rely, in part, on data from 10 or more intensively monitored river basins from across the USA. A team of USGS scientists was convened to develop a systematic, quantitative approach to prioritize candidate basins for this monitoring investment to ensure that, as a group, the 10 basins will support the assessment and forecasting objectives of the major USGS water science programs. Candidate basins were the level-4 hydrologic units (HUC04) with some of the smaller HUC04s being combined; median candidate-basin area is 46,600 km². Candidate basins for the contiguous United States (CONUS) were grouped into 18 hydrologic regions. Ten geospatial variables representing land use, climate change, water use, water-balance components, streamflow alteration, fire risk, and ecosystem sensitivity were selected to rank candidate basins within each of the 18 hydrologic regions. The two highest ranking candidate basins in each of the 18 regions were identified as finalists for selection as "Integrated Water Science Basins"; final selection will consider input from a variety of stakeholders. The regional framework, with only one basin selected per region, ensures that as a group, the basins represent the range in major drivers of the hydrologic cycle. Ranking within each region, primarily based on anthropogenic stressors of water resources, ensures that settings representing important water-resource challenges for the nation will be studied.

The importance of natural versus human factors for ecological conditions of streams and rivers

Streams are influenced by watershed-scale factors, such as climate, geology, topography, hydrology, and soils, which mostly vary naturally among sites, as well as human factors, agriculture and urban development. Thus, natural factors could complicate assessment of human disturbance. In the present study, we use structural equation modeling and data from the 2008-2009 United States National Rivers and Streams Assessment to quantify the relative importance of watershed-scale natural and human factors for in-stream conditions. We hypothesized that biological condition, represented using a diatom multimetric index (MMI), is directly affected by in-stream physicochemical environment, which in turn is regulated by natural and human factors. We evaluated this hypothesis at both national and ecoregion scales to understand how influences vary among regions. We found that direct influences of in-stream environment on diatom MMIs were greater than natural and human factors at the national scale and in all but one ecoregion. Meanwhile, in-stream environments were jointly explained by natural variations in precipitation, base flow index, hydrological stability, % volcanic rock, soil water table depth, and soil depth and by human factors measured as % crops, % other agriculture, and % urban land use. The explained variance of in-stream environment by natural and human factors ranged from 0.30 to 0.75, for which natural factors independently accounted for the largest proportion of explained variance at the national scale and in seven ecoregions. Covariation between natural and human factors accounted for a higher proportion of explained variance of in-stream environment than unique effects of human factors in most ecoregions. Ecoregions with relatively weak effects by human factors had relatively high levels of covariance, high levels of human disturbance, or small ranges in human disturbance. We conclude that accounting for effects of natural factors and their covariation with human factors will be important for accurate ecological assessments.

Projected urban growth in the southeastern USA puts small streams at risk

Future land-use development has the potential to profoundly affect the health of aquatic ecosystems in the coming decades. We developed regression models predicting the loss of sensitive fish (R² = 0.39) and macroinvertebrate (R² = 0.64) taxa as a function of urban and agricultural land uses and applied them to projected urbanization of the rapidly urbanizing Piedmont ecoregion of the southeastern USA for 2030 and 2060. The regression models are based on a 2014 investigation of water quality and ecology of 75 wadeable streams across the region. Based on these projections, stream kilometers experiencing >50% loss of sensitive fish and invertebrate taxa will nearly quadruple to 19,500 and 38,950 km by 2060 (16 and 32% of small stream kilometers in the region), respectively. Uncertainty was assessed using the 20 and 80% probability of urbanization for the land-use projection model and using the 95% confidence intervals for the regression models. Adverse effects on stream health were linked to elevated concentrations of contaminants and nutrients, low dissolved oxygen, and streamflow alteration, all associated with urbanization. The results of this analysis provide a warning of potential risks from future urbanization and perhaps some guidance on how those risks might be mitigated.