Factors driving nutrient trends in streams of the Chesapeake Bay watershed

Community coalescence under variable hydrochemical conditions of the Chesapeake Bay shaped bacterial diversity and functional traits

Community coalescence related to bacterial mixing events regulates community characteristics and affects the health of estuary ecosystems. At present, bacterial coalescence and its driving factors are still unclear. The present study used a dataset from the Chesapeake Bay (2017) to address how bacterial community coalescence in response to variable hydrochemistry in estuarine ecosystems. We determined that variable hydrochemistry promoted the deterioration of water quality. Temperature, orthophosphate, dissolved oxygen, chlorophyll a, Secchi disk depth, and dissolved organic phosphorus were the key environmental factors driving community coalescence. Bacteria with high tolerance to environmental change were the primary taxa accumulated in community coalescence, and the significance of deterministic processes to communities was revealed. Community coalescence was significantly correlated with the pathways of metabolism and organismal systems, and promoted the co-occurrence of antibiotic resistance and virulence factor genes. Briefly, community coalescence under variable hydrochemical conditions shaped bacterial diversity and functional traits, to optimise strategies for energy acquisition and lay the foundation for alleviating environmental pressures. However, potential pathogenic bacteria in community coalescence may be harmful to human health and environmental safety. The present study provides a scientific reference for ecological management of estuaries.

Improving the Identification of Pollution Source Areas with Catchment-Resolution Sensitivity Analysis

The significant impacts of total nitrogen (TN) and total phosphorus (TP) on riverine ecosystems underscores the critical need to identify the primary nutrient source areas in watersheds. This study aims to unravel the influences of terrain and land use types on mean monthly TN (TNM) and mean monthly TP (TPM) export across varying catchment resolutions in the Qiantang River Watershed of China. The findings of this study illuminated the critical role of topography in understanding nutrient dynamics, wielding a profound influence over water flow patterns and nutrient dispersion. Both land slope and Stream Power Index (SPI) displayed substantial negative correlations (r < -0.6) with TNM and TPM concentrations, whereas the Topographic Wetness Index (TWI) showed positive correlations with the nutrient indexes. In addition to terrain characteristics, impervious land surfaces had a positive correlation with nutrient concentrations, while grassland and forest areas exhibited negative correlations. Results further underscored the substantial influence of catchment resolution on correlations between watershed properties and riverine nutrient concentrations. It was imperative to choose an effective catchment resolution in watershed delineation - not too coarse, nor too fine - to accurately capture the topographic and land use impacts on nutrient dynamics. With the most appropriate catchment size (Catchment 700 km2), the critical pollution source areas for TN and TP pollution were identified, and thus could be used to guide future pollution reduction efforts. The study not only highlights the importance of identifying an appropriate catchment size for water pollution, but also emphasizes the necessity of effectively extracting critical pollution source areas to mitigate water nutrient pollution and increase the ecological integrity of the Qiantang River Watershed.

Complex hydrology and variability of nitrogen sources in a karst watershed

Streams draining karst areas with rapid groundwater transit times may respond relatively quickly to nitrogen reduction strategies, but the complex hydrologic network of interconnected sinkholes and springs is challenging for determining the placement and effectiveness of management practices. This study aims to inform nitrogen reduction strategies in a representative agricultural karst setting of the Chesapeake Bay watershed (Fishing Creek watershed, Pennsylvania) with known elevated nitrate contamination and a previous documented groundwater residence time of less than a decade. During baseflow conditions, streamflow did not increase with drainage area. Headwaters and the main stem lost substantial flow to sinkholes until eventually discharging along large springs downstream. Seasonal hydrologic conditions shift the flow and nitrogen load spatially among losing and gaining stream sections. A compilation of nitrogen source inputs with the geochemistry and the pattern of enrichment of δ15N and δ18O suggest that the nitrogen in streams and springs during baseflow represents a mixture of manure, fertilizer, and wastewater sources with low potential for denitrification. The pH and calcite saturation index increased along generalized flow paths from headwaters to springs and indicate shorter groundwater residence times in baseflow during the spring versus summer. Given the substantial investment in management practices, fixed monitoring sites could incorporate synoptic water sampling to properly monitor long-term progress and help inform management actions in karst watersheds. Although karst watersheds have the potential to respond to nitrogen reduction strategies due to shorter groundwater residence times, high nitrogen inputs, effectiveness of conservation practices, and release of legacy nutrients within the karst cavities could confound progress of water quality goals.

Blue and red tides in the Chesapeake Bay watershed: Examining political and environmental framings of collective action during the 2016 and 2020 elections

Watersheds require collective care and management at local and regional levels to maintain their ecological health. The Chesapeake Bay's last several decades of stagnantly poor ecological health presents a distinctive case study for explicating the challenges of motivating collective action across a diverse regional natural resource. Our study uses county- and individual-level descriptive analysis to examine interrelated framings of environmental quality, environmental sentiment, and political action at two critical moments in time-the 2016 and 2020 presidential elections. We find that demographic, environmental, and political characteristics vary with distance to the Chesapeake Bay and that linked environmental and political characteristics appeared to become more polarized between 2016 and 2020. We found no evidence that local environmental quality influenced new political actions such as voting; however, people already likely to vote were influenced by their pro-environmental values such as priorities around climate change.

Causal inference approaches reveal both positive and negative unintended effects of agricultural and urban management practices on instream biological condition

Agricultural and urban management practices (MPs) are primarily designed and implemented to reduce nutrient and sediment concentrations in streams. However, there is growing interest in determining if MPs produce any unintended positive effects, or co-benefits, to instream biological and habitat conditions. Identifying co-benefits is challenging though because of confounding variables (i.e., those that affect both where MPs are applied and stream biota), which can be accounted for in novel causal inference approaches. Here, we used two causal inference approaches, propensity score matching (PSM) and Bayesian network learning (BNL), to identify potential MP co-benefits in the Chesapeake Bay watershed portion of Maryland, USA. Specifically, we examined how MPs may modify instream conditions that impact fish and macroinvertebrate indices of biotic integrity (IBI) and functional and taxonomic endpoints. We found evidence of positive unintended effects of MPs for both benthic macroinvertebrates and fish indicated by higher IBI scores and specific endpoints like the number of scraper macroinvertebrate taxa and lithophilic spawning fish taxa in a subset of regions. However, our results also suggest MPs have negative unintended effects, especially on sensitive benthic macroinvertebrate taxa and key instream habitat and water quality metrics like specific conductivity. Overall, our results suggest MPs offer co-benefits in some regions and catchments with largely degraded conditions but can have negative unintended effects in some regions, especially in catchments with good biological conditions. We suggest the number and types of MPs drove these mixed results and highlight carefully designed MP implementation that incorporates instream biological data at the catchment scale could facilitate co-benefits to instream biological conditions. Our study underscores the need for more research on identifying effects of individual MP types on instream biological and habitat conditions.

Development of a basin-scale total nitrogen prediction model by integrating clustering and regression methods

Nutrient runoff into rivers caused by human activity has led to global eutrophication issues. The Nakdong River in South Korea is currently facing significant challenges related to eutrophication and harmful algal blooms, underscoring the critical importance of managing total nitrogen (T-N) levels. However, traditional methods of indoor analysis, which depend on sampling, are labor-intensive and face limitations in collecting high-frequency data. Despite advancements in sensor allowing for the measurement of various parameters, sensors still cannot directly measure T-N, necessitating surrogate regression methods. Therefore, we conducted T-N predictions using a water quality dataset collected from 2018 to 2022 at 157 observatories within the Nakdong River basin. To account for the water quality characteristics of each location, we employed a clustering technique to divide the basin and compared a Gaussian mixture model with K-means clustering. Moreover, optimal regressor for each cluster was selected by comparing multiple linear regression (MLR), random forest, and XGBoost. The results showed that forming four clusters via K-means clustering was the most suitable approach and MLR was reasonably accurate for all clusters. Subsequently, recursive feature elimination cross-validation was used to identify suitable parameters for T-N prediction, thus leading to the construction of high-accuracy T-N prediction models. Clustering was useful not only for improving the regressors but also for spatially analyzing the water quality characteristics of the Nakdong River. The MLR model can reveal causal relationships and thus is useful for decision-making. The results of this study revealed that the combination of a simple linear regression model and clustering method can be applied to a wide watershed. The clustering-based regression model showed potential for accurately predicting T-N at the basin level and is expected to contribute to nationwide water quality management through future applications in various fields.

Analyzing the impact of agricultural BMPs on stream nutrient load and biotic health in the Susquehanna-Chemung basin of New York

Despite the widespread use of agricultural best management practices (BMPs) to reduce watershed scale nutrient loads, there remain few studies that use directly observed data - instead of models - to evaluate BMP effectiveness at the watershed scale. In this study, we make use of extensive ambient water quality data, stream biotic health data, and BMP implementation data within the New York State portion of the Chesapeake Bay watershed to assess the role of BMPs on reducing nutrient loads and modifying biotic health in major rivers. The specific BMPs considered were riparian buffers and nutrient management planning. A simple mass balance approach was used to evaluate the role of wastewater treatment plant nutrient reductions, agricultural land use changes, and these two agricultural BMPs in matching observed downward trends in nutrient load. In the Eastern nontidal network (NTN) catchment - where BMPs have been more widely reported - the mass balance model suggested a small but discernible contribution of BMPs in matching the observed downward trend in total phosphorus. Contrastingly, BMP implementations did not show clear contributions towards total nitrogen reductions in the Eastern NTN catchment nor for the total nitrogen and phosphorus in the Western NTN catchment, where BMP implementation data are more limited. Assessment of the relationship between stream biotic health and BMP implementation using regression models found limited connection between extent of BMP implementation and biotic health. In this case, however, spatiotemporal mismatches between the datasets and the relatively stable biotic health, typically of moderate to good quality even before BMP implementation, may reflect the need for better monitoring design to assess BMP effects at the subwatershed scale. Additional studies, perhaps using citizen scientists, may be able to provide more suitable data within the existing frameworks of the long-term surveys. Given the preponderance of studies that rely only on modeling to understand nutrient loading reductions achieved by implementation of BMPs, it is essential to continue to collect empirical data to meaningfully evaluate whether there are actual measurable changes due to BMPs.

Identifying the critical areas and primary sources for agricultural non-point source pollution management of an emigrant town within the Three Gorges reservoir area

Agricultural non-point source pollution is threatening water environmental health of the Three Gorges reservoir. However, current studies for precision management of the agricultural non-point source pollution within this area are still limited. The objective of this study was identifying the critical areas and primary sources of agricultural non-point source pollution for precision management. Firstly, the inventory analysis approach was used to estimate the discharge amount of total nitrogen (TN), total phosphorus (TP), and chemical oxygen demand (COD) from farmland fertilizer, crop residues, livestock breeding, and daily activities. Afterwards, the deviation standardization method was applied to evaluate the emission intensity of TN, TP, and COD, as well as calculating the comprehensive pollution index (CPI) of each village, based on which the critical areas for agricultural non-point source pollution management could be distinguished. Moreover, the equivalence pollution load method was conducted to identify the primary pollution sources within each critical zone. The above methods were implemented to an emigrant town within the Three Gorges reservoir area named Gufu. Results showed that agricultural non-point source pollution in Gufu town has been alleviated to a certain extent since 2016. Nevertheless, in four areas of the town (i.e., Longzhu, Fuzi, Shendu, and Maicang), the agricultural non-point source pollution still deserved attention and improvement. For the mentioned critical areas, farmland fertilizer and livestock breeding were the primary sources causing agricultural non-point source pollution. The emission amount of TN and TP from farmland fertilizer accounted for 60% and 48% of the total, respectively. And those from livestock breeding were 29% and 46%. Our research could provide definite targets to relieve agricultural non-point source pollution, which had great significance to protect water environment while coordinating regional economic growth after emigrant resettlement.

Beneath the surface: spatial and temporal trends in water quality and its impacts on algal community composition in the Albemarle Sound, North Carolina

Urban and agricultural expansion and intensification pose a critical threat to water quality and aquatic ecosystems. Increased nutrient loading into waterways combined with warming temperatures due to climate change have increased eutrophication and algal blooms. The relationship between land use, nutrient availability, and algal growth can vary dramatically across space and time, but few studies have captured this variation. The goal of this research is to assess water quality across time and disparate land uses, and its influence on algal community composition in the Albemarle Sound, a brackish water estuary in North Carolina. We collected water quality data from 21 sites across the sound, visiting six sites in Chowan County biweekly and 15 other sites twice between June and August 2020. Water samples from each site were tested for nitrate, phosphate, ammonia, bicarbonate, and total phosphorus (TP). Preserved algal samples from the six Chowan County sites were enumerated under a microscope to estimate genus richness and biomass. In the Chowan County sites, phosphorus increased and nitrate decreased over the course of the summer. Across all sites, TP increased with development and agricultural land use. These results suggest that sources of nitrogen and phosphorus in the sound differ. Algal richness increased with nitrate concentration and decreased with precipitation while biomass increased with water temperature. Our results indicate that climate change impacts, particularly increasing temperatures and extreme precipitation, influence how land use, water quality, and algal community composition interact. These data demonstrate the co-benefits of mitigating climate change in developing management strategies to reduce algal blooms.

Supplementary Information

The online version contains supplementary material available at 10.1007/s10452-023-10008-y.

Ecosystem-level effects of re-oligotrophication and N:P imbalances in rivers and estuaries on a global scale

Trends and ecological consequences of phosphorus (P) decline and increasing nitrogen (N) to phosphorus (N:P) ratios in rivers and estuaries are reviewed and discussed. Results suggest that re-oligotrophication is a dominant trend in rivers and estuaries of high-income countries in the last two-three decades, while in low-income countries widespread eutrophication occurs. The decline in P is well documented in hundreds of rivers of United States and the European Union, but the biotic response of rivers and estuaries besides phytoplankton decline such as trends in phytoplankton composition, changes in primary production, ecosystem shifts, cascading effects, changes in ecosystem metabolism, etc., have not been sufficiently monitored and investigated, neither the effects of N:P imbalance. N:P imbalance has significant ecological effects that need to be further investigated. There is a growing number of cases in which phytoplankton biomass have been shown to decrease due to re-oligotrophication, but the potential regime shift from phytoplankton to macrophyte dominance described in shallow lakes has been documented only in a few rivers and estuaries yet. The main reasons why regime shifts are rarely described in rivers and estuaries are, from one hand the scarcity of data on macrophyte cover trends, and from the other hand physical factors such as peak flows or high turbidity that could prevent a general spread of submerged macrophytes as observed in shallow lakes. Moreover, re-oligotrophication effects on rivers may be different compared to lakes (e.g., lower dominance of macrophytes) or estuaries (e.g., limitation of primary production by N instead of P) or may be dependent on river/estuary type. We conclude that river and estuary re-oligotrophication effects are complex, diverse and still little known, and in some cases are equivalent to those described in shallow lakes, but the regime shift is more likely to occur in mid to high-order rivers and shallow estuaries.

Assessing intervention effectiveness at promoting voluntary conservation practice adoption in agrienvironments

Although implementing conservation practices on private farms and forests can produce substantial environmental benefits, these practices are not being adopted widely enough to result in measurable improvements at regional scales. Researchers have investigated the production and program factors influencing producer choices to voluntarily adopt these practices. However, the findings of reviews are inconsistent, raising questions about review methods, including the omission of relevant variables. Further, applying lessons from past work to promote adoption is difficult because many reviews investigated dispositional or demographic variables that practitioners and policy makers cannot directly observe or influence. We conducted a new review of 146 empirical studies that tested the effects of different interventions (e.g., financial incentives, outreach events, and nudges) on increasing the likelihood of producers adopting conservation practices. We conducted a metaregression of quantitative studies from diverse disciplines that filtered studies by quality (i.e., use of randomization and clear analysis reporting). We synthesized these results with a thematic analysis of qualitative studies on producer perspectives about conservation practices. Financial incentives had the strongest evidence of increasing producers' likelihood of adopting conservation practices (odds ratio 1.86, p < 0.05). However, this effect was only apparent after filtering by study quality, which also improved model fit and identified significant regional differences (odds ratio -1.69, p < 0.01). The thematic review of qualitative studies revealed that peer groups may be successful in reinforcing adoption behaviors due to homophily effects and that financial incentives not only offset implementation costs but also mitigated perceived risks of adoption. Given the problems we encountered in testing hypotheses about the magnitude of variability explained by intervention types and practice characteristics, we recommend additional experimental and longitudinal work that accounts for financial incentives and pairs qualitative and quantitative data to clarify relationships between program design and practice adoption rates.

Nutrient limitation of phytoplankton in three tributaries of Chesapeake Bay: Detecting responses following nutrient reductions

Many coastal ecosystems suffer from eutrophication, algal blooms, and dead zones due to excessive anthropogenic inputs of nitrogen (N) and phosphorus (P). This has led to regional restoration efforts that focus on managing watershed loads of N and P. In Chesapeake Bay, the largest estuary in the United States, dual nutrient reductions of N and P have been pursued since the 1980s. However, it remains unclear whether nutrient limitation - an indicator of restriction of algal growth by supplies of N and P - has changed in the tributaries of Chesapeake Bay following decades of reduction efforts. Toward that end, we analyzed historical data from nutrient-addition bioassay experiments and data from the Chesapeake Bay long-term water-quality monitoring program for six stations in three tidal tributaries (i.e., Patuxent, Potomac, and Choptank Rivers). Classification and regression tree (CART) models were developed using concurrent collections of water-quality parameters for each bioassay monitoring location during 1990-2003, which satisfactorily predicted the bioassay-based measures of nutrient limitation (classification accuracy = 96%). Predictions from the CART models using water-quality monitoring data showed enhanced nutrient limitation over the period of 1985-2020 at four of the six stations, including the downstream station in each of these three tributaries. These results indicate detectable, long-term water-quality improvements in the tidal tributaries. Overall, this research provides a new analytical tool for detecting signs of ecosystem recovery following nutrient reductions. More broadly, the approach can be adapted to other waterbodies with long-term bioassays and water-quality data sets to detect ecosystem recovery.

Diversity and abundance of antibiotic resistance genes and their relationship with nutrients and land use of the inflow rivers of Taihu Lake

Taihu Lake is the third largest freshwater lake in China and an important source for drinking water, flood protection, aquaculture, agriculture, and other activities. This lake is connected to many principal and small rivers with inflow from west and outflow on the eastern side of the lake and these inflow rivers are believed to significantly contribute to the water pollution of the lake. This study was aimed at assessing the diversity and abundance of antibiotic resistance genes (ARGs) and mobile genetic elements (MGEs), and their relationship with water quality parameters and land use patterns. Water samples were collected from 10 major inflow rivers and the source water protection area of the Taihu Lake in spring and summer 2019. High-throughput profiling was used to detect and quantify 384 ARGs and MGEs and in addition, 11 water quality parameters were analyzed. The results showed that the number of ARGs/MGEs detected in each inflow river ranged from 105 to 185 in spring and 107 to 180 in summer. The aminoglycoside resistance genes were the most dominant types ARGs detected followed by beta-lactam resistance, multidrug resistance, macrolide-lincosamide-streptogramin B (MLSB) resistance genes, which contributed to 65% of the ARGs. The water quality parameters showed significant correlation with absolute abundance of ARGs. Furthermore, significant correlation between ARGs and MGEs were also observed which demonstrates potential gene transfer among organisms through horizontal gene transfer via MGEs. ARGs showed strong positive correlation with cultivated and industrial lands whereas, negative correlation was observed with river, lake, forest, land for green buffer, and land for port and harbor. The overall results indicate that the inflow rivers of Taihu Lake are polluted by various sources including multiple nutrients and high abundance of ARGs, which needs attention for better management of the inflow rivers of this lake.

Clean Water Act at 50: Celebrating the golden anniversary of the blue policy

Both the U.S. Clean Water Act (CWA) and the Journal of Environmental Quality (JEQ) trace back to 1972. The journal has a strong history of publishing science in support of the CWA, from basic science used to develop best management practices to address water quality problems to special sections on hot issues of the day and publishing long-term data that provide evidence of success. The objective of this article is to provide a brief overview of how JEQ has provided a publication outlet for researchers involved in efforts focused on key CWA issues and to introduce a special section celebrating the golden anniversary of this blue policy. The special section includes papers that look back historically on biosolids research that began with the advent of the CWA as well as a forward-looking paper encouraging readers to think about the implications of the ubiquitous use of lithium-ion batteries and a call to action before tangible problems are realized.

Regional patterns and drivers of total nitrogen trends in the Chesapeake Bay watershed: Insights from machine learning approaches and management implications

Anthropogenic nutrient inputs have led to nutrient enrichment in many waterbodies worldwide, including Chesapeake Bay (USA). River water quality integrates the spatial and temporal changes of watersheds and forms the foundation for disentangling the effects of anthropogenic inputs. We demonstrate with the Chesapeake Bay Non-Tidal Monitoring Network that machine learning approaches - i.e., hierarchical clustering and random forest (RF) classification - can be combined to better understand the regional patterns and drivers of total nitrogen (TN) trends in large monitoring networks, resulting in information useful for watershed management. Cluster analysis revealed regional patterns of short-term TN trends (2007-2018) and categorized the stations into three distinct trend clusters, namely, V-shape (n = 23), monotonic decline (n = 35), and monotonic increase (n = 26). RF models identified regional drivers of TN trend clusters by quantifying the effects of watershed characteristics (land use, geology, physiography) and major N sources on the trend clusters. Results provide encouraging evidence that improved agricultural nutrient management has resulted in declines in agricultural nonpoint sources, which in turn contributed to water-quality improvement in our period of analysis. Moreover, water-quality improvements are more likely in watersheds underlain by carbonate rocks, reflecting the relatively quick groundwater transport of this terrain. By contrast, water-quality improvements are less likely in Coastal Plain watersheds, reflecting the effect of legacy N in groundwater. Notably, results show degrading trends in forested watersheds, suggesting new and/or remobilized sources that may compromise management efforts. Finally, the developed RF models were used to predict TN trend clusters for the entire Chesapeake Bay watershed at the fine scale of river segments (n = 979), providing fine spatial information that can facilitate targeted watershed management, including unmonitored areas. More broadly, this combined use of clustering and classification approaches can be applied to other regional monitoring networks to address similar water-quality questions.

Major point and nonpoint sources of nutrient pollution to surface water have declined throughout the Chesapeake Bay watershed

Understanding drivers of water quality in local watersheds is the first step for implementing targeted restoration practices. Nutrient inventories can inform water quality management decisions by identifying shifts in nitrogen (N) and phosphorus (P) balances over space and time while also keeping track of the likely urban and agricultural point and nonpoint sources of pollution. The Chesapeake Bay Program's Chesapeake Assessment Scenario Tool (CAST) provides N and P balance data for counties throughout the Chesapeake Bay watershed, and these data were leveraged to create a detailed nutrient inventory for all the counties in the watershed from 1985-2019. This study focuses on three primary watershed nutrient balance components-agricultural surplus, atmospheric deposition, and point source loads-which are thought to be the leading anthropogenic drivers of nutrient loading trends across the watershed. All inputs, outputs, and derived metrics (n=53) like agricultural surplus and nutrient use efficiency, were subjected to short- and long-term trend analyses to discern how sources of pollution to surface water have changed over time. Across the watershed from 1985-2019, downward trends in atmospheric deposition were ubiquitous. Though there are varying effects, long-term declines in agricultural surplus were observed, likely because nutrients are being managed more efficiently. Multiple counties' point source loads declined, primarily associated with upgrades at major cities that discharge treated wastewater directly to tidal waters. Despite all of these positive developments, recent increases in agricultural surpluses from 2009-2019 highlight that water quality gains may soon be reversed in many agricultural areas of the basin. Besides tracking progress and jurisdictional influence on pollution sources, the nutrient inventory can be used for retrospective water quality analysis to highlight drivers of past improvement/degradation of water quality trends and for decision makers to develop and track their near- and long-term watershed restoration strategies.

Targeting for nonpoint source pollution reduction: A synthesis of lessons learned, remaining challenges, and emerging opportunities

The ability to identify, target, and treat critical pollution source areas on a landscape is an ongoing challenge for water quality programs that seek to address nonpoint source (NPS) pollution. In this article, we develop a conceptual framework for targeting program design, and review recent experience with the implementation of targeting programs that corresponds with a wide range of program characteristics. Through this review, we emphasize that the complex and locally dependent nature of NPS generation and transport makes it impossible to define a narrow set of rules to guide targeting programs everywhere. Instead, we evaluate key features of NPS targeting in several different contexts, highlighting lessons learned from recent experience. This synthesis of targeting program design and implementation points toward several areas of opportunity for improved NPS policy, however more research is needed to systematically document changes in behavior and pollutant loads. The lack of monitoring data at refined scales presents a major obstacle to targeting program success. This paper synthesizes new opportunities and ongoing challenges for the implementation of targeting in NPS water quality programs.

Nitrogen reductions have decreased hypoxia in the Chesapeake Bay: Evidence from empirical and numerical modeling

Seasonal hypoxia is a characteristic feature of the Chesapeake Bay due to anthropogenic nutrient input from agriculture and urbanization throughout the watershed. Although coordinated management efforts since 1985 have reduced nutrient inputs to the Bay, oxygen concentrations at depth in the summer still frequently fail to meet water quality standards that have been set to protect critical estuarine living resources. To quantify the impact of watershed nitrogen reductions on Bay hypoxia during a recent period including both average discharge and extremely wet years (2016-2019), this study employed both statistical and three-dimensional (3-D) numerical modeling analyses. Numerical model results suggest that if the nitrogen reductions since 1985 had not occurred, annual hypoxic volumes (O₂ < 3 mg L^-1) would have been ~50-120% greater during the average discharge years of 2016-2017 and ~20-50% greater during the wet years of 2018-2019. The effect was even greater for O₂ < 1 mg L^-1, where annual volumes would have been ~80-280% greater in 2016-2017 and ~30-100% greater in 2018-2019. These results were supported by statistical analysis of empirical data, though the magnitude of improvement due to nitrogen reductions was greater in the numerical modeling results than in the statistical analysis. This discrepancy is largely accounted for by warming in the Bay that has exacerbated hypoxia and offset roughly 6-34% of the improvement from nitrogen reductions. Although these results may reassure policymakers and stakeholders that their efforts to reduce hypoxia have improved ecosystem health in the Bay, they also indicate that greater reductions are needed to counteract the ever-increasing impacts of climate change.

An evaluation of the Chesapeake Bay management strategy to improve water quality in small agricultural watersheds

Chesapeake Bay water quality has been a concern since 1970. In rural areas, agriculture is the dominant N and P source, and the voluntary application of best management practices (BMPs) is the primary management tool. Here we test the hypothesis that the current management approach of primarily voluntary, untargeted BMP implementation is insufficient to create detectable, widespread reductions in N, P, and total suspended solid (TSS) concentrations in agricultural watersheds of the Choptank basin, a tributary of Chesapeake Bay. To test this hypothesis, we assessed BMP implementation and sampled water quality on participating farms, at intermediate streams within each watershed, and at watershed outlets of four watersheds from 2013 to 2014. We also present water quality data from 2003 to 2014 at the outlets of 12 additional agricultural and one forested watershed and survey-directed interviews of farmers. By the end of 2014, large numbers of BMPs, both structural and cultural, had been implemented. Of the 16 agricultural watersheds, 50% showed significant decreases in baseflow N, 37.5% showed no changes, and 12.5% showed increasing TN. Baseflow P significantly decreased at just one watershed, increased at one, and remained stable at 14. Stormflow N was similar to baseflow, but stormflow P was 5 times higher than baseflow. These data partially support our hypothesis. Surveys suggested farmers considered themselves responsible for the quality of water leaving their farms, but out-of-pocket cost was the major impediment to further BMP adoption. We suggest that greater outreach and more financial support for farmers to implement BMPs is required to increase the types and densities of BMPs needed to achieve regional water quality goals.

Fate and transport in environmental quality

Changes in pollutant concentrations in environmental media occur both from pollutant transport in water or air and from local processes, such as adsorption, degradation, precipitation, straining, and so on. The terms "fate and transport" and "transport and fate" reflect the coupling of moving with the carrier media and biogeochemical processes describing local transformations or interactions. The Journal of Environmental Quality (JEQ) was one of the first to publish papers on fate and transport (F&T). This paper is a minireview written to commemorate the 50th anniversary of JEQ and show how the research interests, methodology, and public attention have been reflected in fate and transport publications in JEQ during the last 40 years. We report the statistics showing how the representation of different pollutant groups in papers changed with time. Major focus areas have included the effect of solution composition on F&T and concurrent F&T, the role of organic matter, and the relative role of different F&T pathways. The role of temporal and spatial heterogeneity has been studied at different scales. The value of long-term F&T studies and developments in modeling as the F&T research approach was amply demonstrated. Fate and transport studies have been an essential part of conservation measure evaluation and comparison and ecological risk assessment. For 50 years, JEQ has delivered new insights, methods, and applications related to F&T science. The importance of its service to society is recognized, and we look forward to new generations of F&T researchers presenting their contributions in JEQ.

Treatment of Legacy Nitrogen as a Compliance Option to Meet Chesapeake Bay TMDL Requirements

In efforts to combat eutrophication, the U.S. Environmental Protection Agency has established aggressive nitrogen, phosphorus, and sediment reduction goals for states and regulated dischargers within the Chesapeake Bay watershed. Chesapeake Bay jurisdictions are struggling to meet the nutrient (N, P) reduction goals. This paper evaluates the efficacy of removing legacy N from groundwater as a compliance strategy for three potential classes of "buyers" of N reductions in the Chesapeake Bay watershed: permitted point sources, permitted municipal stormwater systems (called MS4s), and state nonpoint source (NPS) managers. We compare denitrifying spring bioreactors with conventional agricultural and urban NPS removal technologies using evaluative criteria important to each of these buyers. Results indicate that spring bioreactors compare favorably to other N removal technologies based on cost effectiveness, administrative costs, and certainty of N removal performance. Most conventional NPS technologies provide greater ancillary benefits. On balance, denitrifying spring bioreactors add a valuable compliance option to those tasked with achieving Bay N reduction goals.

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.

The Chesapeake Bay Program Modeling System: Overview and Recommendations for Future Development

The Chesapeake Bay is the largest, most productive, and most biologically diverse estuary in the continental United States providing crucial habitat and natural resources for culturally and economically important species. Pressures from human population growth and associated development and agricultural intensification have led to excessive nutrient and sediment inputs entering the Bay, negatively affecting the health of the Bay ecosystem and the economic services it provides. The Chesapeake Bay Program (CBP) is a unique program formally created in 1983 as a multi-stakeholder partnership to guide and foster restoration of the Chesapeake Bay and its watershed. Since its inception, the CBP Partnership has been developing, updating, and applying a complex linked modeling system of watershed, airshed, and estuary models as a planning tool to inform strategic management decisions and Bay restoration efforts. This paper provides a description of the 2017 CBP Modeling System and the higher trophic level models developed by the NOAA Chesapeake Bay Office, along with specific recommendations that emerged from a 2018 workshop designed to inform future model development. Recommendations highlight the need for simulation of watershed inputs, conditions, processes, and practices at higher resolution to provide improved information to guide local nutrient and sediment management plans. More explicit and extensive modeling of connectivity between watershed landforms and estuary sub-areas, estuarine hydrodynamics, watershed and estuarine water quality, the estuarine-watershed socioecological system, and living resources will be important to broaden and improve characterization of responses to targeted nutrient and sediment load reductions. Finally, the value and importance of maintaining effective collaborations among jurisdictional managers, scientists, modelers, support staff, and stakeholder communities is emphasized. An open collaborative and transparent process has been a key element of successes to date and is vitally important as the CBP Partnership moves forward with modeling system improvements that help stakeholders evolve new knowledge, improve management strategies, and better communicate outcomes.

Advancing estuarine ecological forecasts: seasonal hypoxia in Chesapeake Bay

Ecological forecasts are quantitative tools that can guide ecosystem management. The coemergence of extensive environmental monitoring and quantitative frameworks allows for widespread development and continued improvement of ecological forecasting systems. We use a relatively simple estuarine hypoxia model to demonstrate advances in addressing some of the most critical challenges and opportunities of contemporary ecological forecasting, including predictive accuracy, uncertainty characterization, and management relevance. We explore the impacts of different combinations of forecast metrics, drivers, and driver time windows on predictive performance. We also incorporate multiple sets of state-variable observations from different sources and separately quantify model prediction error and measurement uncertainty through a flexible Bayesian hierarchical framework. Results illustrate the benefits of (1) adopting forecast metrics and drivers that strike an optimal balance between predictability and relevance to management, (2) incorporating multiple data sources in the calibration data set to separate and propagate different sources of uncertainty, and (3) using the model in scenario mode to probabilistically evaluate the effects of alternative management decisions on future ecosystem state. In the Chesapeake Bay, the subject of this case study, we find that average summer or total annual hypoxia metrics are more predictable than monthly metrics and that measurement error represents an important source of uncertainty. Application of the model in scenario mode suggests that absent watershed management actions over the past decades, long-term average hypoxia would have increased by 7% compared to 1985. Conversely, the model projects that if management goals currently in place to restore the Bay are met, long-term average hypoxia would eventually decrease by 32% with respect to the mid-1980s.

Exploring private land conservation non-adopters' attendance at outreach events in the Chesapeake Bay watershed, USA

BACKGROUND

Outreach events such as trainings, demonstrations, and workshops are important opportunities for encouraging private land operators to adopt voluntary conservation practices. However, the ability to understand the effectiveness of such events at influencing conservation behavior is confounded by the likelihood that attendees are already interested in conservation and may already be adopters. Understanding characteristics of events that draw non-adopters can aid in designing events and messaging that are better able to reach beyond those already interested in conservation.

METHODS

For this study, we interviewed 101 operators of private agricultural lands in Maryland, USA, and used descriptive statistics and qualitative comparative analysis to investigate differences between the kinds of outreach events that adopters and non-adopters attended.

RESULTS

Our results suggested that non-adopters, as compared to adopters, attended events that provided production-relevant information and were logistically easy to attend. Further, non-adopters were more selective when reading advertisements, generally preferring simplicity. Future research and outreach can build on these findings by experimentally testing the effectiveness of messages that are simple and relevant to farmers' production priorities.

The need to integrate legacy nitrogen storage dynamics and time lags into policy and practice

Increased fluxes of reactive nitrogen (N_r), often associated with N fertilizer use in agriculture, have resulted in negative environmental consequences, including eutrophication, which cost billions of dollars per year globally. To address this, best management practices (BMPs) to reduce N_r loading to the environment have been introduced in many locations. However, improvements in water quality associated with BMP implementation have not always been realised over expected timescales. There is a now a significant body of scientific evidence showing that the dynamics of legacy N_r storage and associated time lags invalidate the assumptions of many models used by policymakers for decision making regarding N_r BMPs. Building on this evidence, we believe that the concepts of legacy N_r storage dynamics and time lags need to be included in these models. We believe the biogeochemical research community could play a more proactive role in advocating for this change through both awareness raising and direct collaboration with policymakers to develop improved datasets and models. We anticipate that this will result in more realistic expectations of timescales for water quality improvements associated with BMPs. Given the need for multi-nutrient policy responses to tackle challenges such as eutrophication, integration of N stores will have the further benefit of aligning both researchers and policymakers in the N community with the phosphorus and carbon communities, where estimation of stores is more widespread. Ultimately, we anticipate that integrating legacy N_r storage dynamics and time lags into policy frameworks will better meet the needs of human and environmental health.

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.

Factors Affecting Nitrate Concentrations in Stream Base Flow

Elevated nitrogen concentrations in streams and rivers in the Chesapeake Bay watershed have adversely affected the ecosystem health of the bay. Much of this nitrogen is derived as nitrate from groundwater that discharges to streams as base flow. In this study, boosted regression trees (BRTs) were used to relate nitrate concentrations in base flow (n = 156) to explanatory variables describing nitrogen sources, geology, and soil and catchment characteristics. From these relations, a BRT model was developed to predict base flow nitrate concentrations in streams throughout the Chesapeake Bay watershed. The highest base flow nitrate concentrations were associated with intensive agricultural land use, carbonate geology, and sparse riparian canopy, which suggested that reduced nitrogen inputs, particularly over carbonate terrane, are critical for limiting nitrate concentrations. The lowest nitrate concentrations in the BRT model were associated with extensive riparian canopy, high levels of organic carbon in soils, and suboxic conditions at shallow depths, which suggested that denitrification in the subsurface, particularly in the riparian zone, is limiting base flow nitrate concentrations. Nitrate transport from aquifers to streams can take decades to occur, resulting in decades-long lag times between the time when a land-use activity is implemented and when its effects are fully observed in streams. Predictive models of base flow nitrate concentrations in streams will help identify which portions of a watershed are likely to have large fractions of total stream nitrogen load derived from pathways with significant lag times.

Nutrient limitation of phytoplankton in Chesapeake Bay: Development of an empirical approach for water-quality management

Understanding the temporal and spatial roles of nutrient limitation on phytoplankton growth is necessary for developing successful management strategies. Chesapeake Bay has well-documented seasonal and spatial variations in nutrient limitation, but it remains unknown whether these patterns of nutrient limitation have changed in response to nutrient management efforts. We analyzed historical data from nutrient bioassay experiments (1992-2002) and data from long-term, fixed-site water-quality monitoring program (1990-2017) to develop empirical approaches for predicting nutrient limitation in the surface waters of the mainstem Bay. Results from classification and regression trees (CART) matched the seasonal and spatial patterns of bioassay-based nutrient limitation in the 1992-2002 period much better than two simpler, non-statistical approaches. An ensemble approach of three selected CART models satisfactorily reproduced the bioassay-based results (classification rate = 99%). This empirical approach can be used to characterize nutrient limitation from long-term water-quality monitoring data on much broader geographic and temporal scales than would be feasible using bioassays, providing a new tool for informing water-quality management. Results from our application of the approach to 21 tidal monitoring stations for the period of 2007-2017 showed modest changes in nutrient limitation patterns, with expanded areas of nitrogen-limitation and contracted areas of nutrient saturation (i.e., not limited by nitrogen or phosphorus). These changes imply that long-term reductions in nitrogen load have led to expanded areas with nutrient-limited phytoplankton growth in the Bay, reflecting long-term water-quality improvements in the context of nutrient enrichment. However, nutrient limitation patterns remain unchanged in the majority of the mainstem, suggesting that nutrient loads should be further reduced to achieve a less nutrient-saturated ecosystem.

Best Management Practices for Diffuse Nutrient Pollution: Wicked Problems Across Urban and Agricultural Watersheds

Extensive time and financial resources have been dedicated to address nonpoint sources of nitrogen and phosphorus in watersheds. Despite these efforts, many watersheds have not seen substantial improvement in water quality. The objective of this study is to review the literature and investigate key factors affecting the lack of improvement in nutrient levels in waterways in urban and agricultural regions. From 94 studies identified in the academic literature, we found that, although 60% of studies found improvements in water quality after implementation of Best Management Practices (BMPs) within the watershed, these studies were mostly modeling studies rather than field monitoring studies. For studies that were unable to find improvements in water quality after the implementation of BMPs, the lack of improvement was attributed to lack of knowledge about BMP functioning, lag times, nonoptimal placement and distribution of BMPs in the watershed, postimplementation BMP failure, and socio-political and economic challenges. We refer to these limiting factors as known unknowns. We also acknowledge the existence of unknown unknowns that hinder further improvement in BMP effectiveness and suggest that machine learning, approaches from the field of business and operations management, and long-term convergent studies could be used to resolve these unknown unknowns.