Search

As global phosphorus (P) stores rapidly decline, P fed algal blooms continue to threaten critical freshwater resources across the globe. In the Midwestern United States (US), particularly the Corn Belt, biorefineries could play a key role in addressing this issue. By recovering P from the byproducts of ethanol production these facilities could reduce the P content of distillers grain feed, thereby reducing P excreted in manures. This process could potentially divert P away from concentrated animal feeding operations (CAFOs) and toward renewable P (rP) fertilizer production utilizing the recovered P. To foster the inclusion of P recovery incentives in state nutrient reduction strategies, this study elucidates the cascading benefits of rP recovery from corn biorefineries in watersheds across six Upper Midwestern states. Incentivizing P recovery in watersheds that contain both biorefineries and CAFOs could foster the production of 107,500 metric tons (MT) rP fertilizer while diverting 26,800 MT P from CAFO wastes each year, nearly double the estimated P reduction potential for municipal wastewater in the analysis region. These estimates can inform nutrient reduction analysts and policymakers in determining P load reduction potential. To further guide incentive strategies, four priority watersheds are highlighted to illustrate P reduction and circularity typologies across the region., Competing Interests: Declaration of competing interest The authors declare the following financial interests/personal relationships which may be considered as potential competing interests:Roland Cusick reports financial support was provided by National Science Foundation. Rebecca L. Muenich reports financial support was provided by National Science Foundation. If there are other authors, they declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2025 The Authors. Published by Elsevier Ltd.. All rights reserved.)

The increasing global demand for meat and dairy products, fueled by rapid industrialization, has led to the expansion of Animal Feeding Operations (AFOs) in the United States (US). These operations, often found in clusters, generate large amounts of manure, posing a considerable risk to water quality due to the concentrated waste streams they produce. Accurately mapping AFOs is essential for effective environmental and disease management, yet many facilities remain undocumented due to variations in federal and state regulations. Current techniques for mapping AFOs in the US rely on a mix of manual digitization, aerial imaging, and image processing. By applying a machine learning-based random forest (RF) classification method to a socio-environmental dataset that excluded aerial images in this work, we overcame some of the limitations associated with aerial image-based approaches, enhancing mapping accuracy to 87 %. We used publicly available environmental, nutrient-focused, and socioeconomic data downscaled to the parcel level, which more accurately reflects farm boundaries and operations than previous methods. Our study incorporates 58 variables, with canopy cover, surrounding vegetation, day and nighttime land surface temperatures, and phosphorus from animals identified as key predictors of AFO presence. The relevance of these variables varies across states, influenced by whether the dominant land covers are human-induced, like croplands, or natural, such as savannas and grasslands. Thus, our public-data based approach, easily replicable, not only improves the precision of AFO detection, but also facilitates the monitoring of nutrient flows at the parcel level-critical for nutrient budgeting and recovery, water quality management, and disease risk assessment and tracing., Competing Interests: Declaration of competing interest The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: Rebecca Muenich reports financial support was provided by National Science Foundation. If there are other authors, they declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier B.V. All rights reserved.)

Biosolids can provide a nutrient rich soil amendment, particularly for poor soils and semi-arid or drought-prone areas. However, there are concerns that sludge and biosolids could be a source of propagation and exposure to AMR determinants such as antibiotic resistant bacteria (ARB), and antibiotic resistance genes (ARGs). To inform risk assessment efforts, a systematic literature review was performed to build a comprehensive spreadsheet database of ARB and ARG concentrations in biosolids (and some sludges specified as intended for land application), along with 69 other quantitative and qualitative meta-data fields from 68 published studies describing sampling information and processing methods that can be used for modeling purposes. Mean ARG concentrations per gram in positive samples of biosolids ranged from -5.7 log 10 (gene copies [gc]/g) to 12.92 log 10 (gc/g) (with these range values reported per dry weight), and aqueous concentrations ranged from 0.9 log 10 (gc/L) to 14.6 log 10 (gc/L). Mean ARB concentrations per gram of biosolids ranged from 2.02 log 10 (colony forming units [CFU]/g) to 9.00 log 10 (CFU/g) (dry weight), and aqueous concentrations ranged from 3.23 log 10 (CFU/L) to 12.0 log 10 (CFU/L). ARG log removal values (LRVs) during sewage sludge stabilization were calculated from a meta-analysis of mean concentrations before and after stabilization from 31 studies, ranging from -2.05 to 5.52 logs. The classes of resistance most relevant for a risk assessment corresponded to sulfonamide (sul1 and sul2), tetracycline (tetZ, tetX, tetA and tetG), beta-lactam (bla TEM ), macrolide (ermB and ermF), aminoglycoside (strA and aac(6')-Ib-cr), and integron-associated (intI1). The resistance classes most relevant for ARB risk assessment included sulfonamides (sulfamethoxazole and sulfamethazine), cephalosporin (cephalothin and cefoxitin), penicillin (ampicillin), and ciprofloxin (ciprofloxacin). Considerations for exposure assessment are discussed to highlight risk assessment needs relating to antimicrobial resistance (AMR) associated with biosolids application. This study aids in prioritization of resources for reducing the spread of AMR within a One Health framework., Competing Interests: Declaration of competing interest The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: Kerry Hamilton reports financial support was provided by Water Research Foundation. Kerry Hamilton reports financial support was provided by U.S. Department of Agriculture. Nicholas Ashbolt reports administrative support was provided by The Cooperative Research Centre for Solving Antimicrobial Resistance in Agribusiness, Food and Environments (CRC SAAFE). If there are other authors, they declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier B.V. All rights reserved.)

The U.S. Clean Water Act is believed to have driven widespread decreases in pollutants from point sources and developed areas, but has not substantially affected nutrient pollution from agriculture. Today, the highest nutrient concentrations in surface waters are often associated with agricultural production. In this Perspective, we explore whether challenges stemming from the Clean Water Act's inability to mitigate agricultural nutrient pollution are also exacerbated by coarse nutrient monitoring. We evaluate the current state of nutrient monitoring in surface waters of the contiguous U.S. relative to agricultural nutrient inputs to assess how monitoring effort varies across agriculturally intensive areas. The locations of nutrient monitoring stations with approximately seasonal sampling frequency (4 samples per year, on average) from 2012 to 2021 were compiled from the U.S. Water Quality Portal. Monitoring station locations were then compared to watershed-scale (HUC-8) nutrient inventory estimates for agricultural fertilizer and livestock manure inputs. From this assessment, we found that many, but not all, of the nation's most agriculturally intensive areas are under-monitored, and often unmonitored. While it is well-known that the Midwest is the epicenter of agricultural production in the U.S., our results reveal it is poorly monitored relative to its agricultural nutrient inputs. Other regions, like the California Central Valley and parts of the southeastern Coastal Plain were also coarsely monitored relative to nutrient inputs. Conversely, some agriculturally intensive watersheds were moderately-to-well monitored (e.g., western Lake Erie basin, eastern North Carolina, and the Delmarva Peninsula), with these basins largely having established Total Maximum Daily Loads and discharging to prominent waterways. In closing, we argue that sparse monitoring across many of the nation's most agriculturally intensive areas motivate a need to re-envision nutrient monitoring networks, and that increased resources and advanced technologies are likely required to enable effective nutrient source identification throughout the nation., Competing Interests: The authors declare no competing financial interest., (© 2024 The Authors. Published by American Chemical Society.)

Phosphorus (P) deficiency is one of the major constraints for sustainable crop production in calcareous soils. This study aimed to elucidate the key soil characteristics modulating the variability of soil Olsen P in these typical soils. A comprehensive soil sampling initiative (1.5 samples per hectare) was conducted on a 100-ha farm, considering 31 attributes that included soil physical and chemical properties, and geographic attributes. Three machine learning algorithms-partial least squares regression (PLSR), random forest (RF), and cubist regression (CR)-were employed to understand key variables controlling soil Olsen P. Furthermore, the same data set was used to spatially map the variations in Olsen P levels using ordinary kriging. The results revealed that soil chemical factors, specifically exchangeable manganese and zinc, cation exchange capacity, and carbonate, played a crucial role in controlling P levels. Among the machine learning models, the best performing model was RF (R 2  = 0.95, RMSE = 1.30 mg kg -1 ) followed by CR (R 2  = 0.92 and RMSE = 1.43 mg kg -1 ). Additionally, the analysis using a Gaussian semi-variogram model showed a good performance (R 2  = 0.78, RMSE = 2.05 m) in visualizing the spatial distribution of Olsen P, revealing its heterogeneity. The resulting pattern of Olsen P distribution may be attributed not only to soil properties but also to external factors, such as sediment transport through watercourses across the study area and atmospheric deposition from a nearby P mining site. Overall, the combination of geostatistical methods and machine learning approach demonstrates a significant potential in understanding the complexity of soil available P (Olsen-P) that could help to develop sustainable and precise P management., Competing Interests: The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (© 2024 The Authors.)

Uneven global distribution of phosphate rock deposits and the supply chains to transport phosphorus (P) make P fertilizers vulnerable to exogenous shocks, including commodity market shocks; extreme weather events or natural disasters; and geopolitical instability, such as trade disputes, disruption of shipping routes, and war. Understanding bidirectional risk transmission (global-to-local and local-to-global) in P supply and consumption chains is thus essential. Ignoring P system interdependencies and associated risks could have major impacts on critical infrastructure operations and increase the vulnerability of global food systems. We highlight recent unanticipated events and cascading effects that have impacted P markets globally. We discuss the need to account for exogenous shocks in local assessments of P flows, policies, and infrastructure design choices. We also provide examples of how accounting for undervalued global risks to the P industry can hasten the transition to a sustainable P future. For example, leveraging internal P recycling loops, improving plant P use efficiency, and utilizing legacy soil P all enhance system resiliency in the face of exogenous shocks and long-term anticipated threats. Strategies applied at the local level, which are embedded within national and global policy systems, can have global-scale impacts in derisking the P supply chain., Competing Interests: The authors declare no competing financial interest., (© 2024 The Authors. Published by American Chemical Society.)

Background: Limited information is available on the connectivity of Tribal communities to wastewater treatment facilities (WWTFs). This is important for understanding current sanitation infrastructure which drives public health and community construction, knowledge of potential routes of exposure through lack of infrastructure and/or discharging facilities, and opportunities to assess community health through wastewater-based surveillance (WBS)., Objectives: The objective of this work was to assess current wastewater infrastructure for 574 Federally Recognized Indian Tribes (FRITs) in the United States (US) to determine the number and location of facilities on or adjacent to Tribal reservations and Off-Reservation Trust Lands, with the goal of determining the feasibility of employing wastewater-based surveillance within these communities and to identify areas with inadequate sanitation infrastructure., Methods: Here, we identified available National Pollutant Discharge Elimination System (NPDES) wastewater discharge permits in the Environmental Protection Agency's Environmental Compliance History Online database to assess proximity to and within spatial boundaries of Tribal lands. These data were coupled to race data and tribal spatial boundary information from the US Census Bureau., Results: 94 FRITs have registered NPDES permits within Tribal boundaries including a total of 522 facilities. 210 of these are American Indian (AI)-serving (>50% AI) with the ability to reach 135,000 AI-people through the wastewater network to provide community health assessments via WBS. Of the remaining facilities, 153 predominantly serve non-Tribal populations raising concerns about infrastructure placement and indigenous sovereignty. 523 FRITs were identified as without permitted discharging WWTFs, which may suggest inadequate or alternative infrastructure., Impact Statement: Here, multiple data sources including permit information from the Environmental Protection Agency's National Pollution Discharge Elimination System and US Census Bureau data were used to determine the number of wastewater treatment facilities on or adjacent to Tribal lands and how many community members were connected to those municipal systems. This information was used to assess which Tribal communities may be a viable option for wastewater public health surveillance techniques and were used to answer supplemental questions related to basic sanitation and environmental justice concerns., (© 2024. The Author(s), under exclusive licence to Springer Nature America, Inc.)

Freshwater quality and ecosystem impairment associated with excess phosphorus (P) loadings have led to federally mandated P reduction for certain organic waste streams. Phosphorus reduction from livestock and poultry feeds such as corn ethanol distillers' grains (DGs) presents a centralized strategy for reducing P loss from animal manurein agriculturally intensive states, but little is known about the actual distribution and geospatial P contributions of DGs as animal feed. Here, a county-level flow network for corn ethanol DGs was simulated in the United States to elucidate opportunities for P reduction and the potential for nutrient trading between centralized sources. Overall, the estimated P in DGs that was transferred to US animal feeding operations was nearly twice that present in all human waste prior to treatment. Simulation results suggest that Midwestern states account for an estimated 63% of domestic DG usage, with 72% utilized within the state of production. County-level data were also used to highlight the potential of using nutrient trading markets to incentivize P recovery from DGs at biorefineries within an agriculturally intensive watershed region in Iowa. In summary, corn ethanol biorefineries represent a key leverage point for sustainable P management at the national and local scales.

In recent decades animal agriculture in the U.S. has moved from small, distributed operations to larger, concentrated animal feeding operations (CAFOs). CAFOs are defined by federal regulations based on animal numbers and confinement criteria. Because of the size of these operations, the excessive amount of manure generated is typically stored in lagoons, pits, or barns prior to field application or transport to other farms. Water and air quality near CAFOs can be impaired through the overflow of lagoons, stormwater runoff, lagoon seepage or emissions, motivating the following research question: what manure lagoon parameters impact pollutant fate and transport across multiple mechanisms? To address this question, a CAFO lagoon module was developed to assess lagoon overflow risk, groundwater quality, and ammonia emissions of a dairy lagoon. The results from 10,000 Monte Carlo simulations indicated that lagoon overflow is a rare occurrence for simulated environmental conditions in Washington (3.17%). Second, we developed a groundwater module to complete a groundwater quality assessment of a Dairy Lagoon in Washington using analytical and semi-analytical solutions for groundwater solute transport. The long-term effects of this lagoon on water quality were explored as well as the effectiveness of improving the lagoon lining to reduce seepage. Doubling the lagoon liner thickness attenuated peak groundwater ammonia-N concentrations by 2.8. Lastly, we constructed an air quality module and found that ammonia emissions were not sensitive to changes in lagoon liner construction, but small reductions in lagoon pH significantly reduced yearly average ammonia emissions. The combined model can be used to improve understanding of the impacts of CAFO lagoon overflow and seepage and develop sustainable management practices at the field scale for these key components of the agricultural landscape., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2022 Elsevier Ltd. All rights reserved.)

Nutrient pollution from farm fertilizers and manure is a global concern. Excess nitrogen and phosphorous has been linked to algal blooms and a host of other water quality issues. In the U.S., most animal production occurs in concentrated animal feeding operations (CAFOs) housing a significant number of animals in a confined space. CAFOs tend to cluster in space and thus generate large quantities of manures within a small area. Liquid manure from CAFOs is often stored in open-air lagoons and then applied via irrigation to crops on nearby 'sprayfields'. The full scope and extent of CAFO impacts remain unclear because of the paucity of public information regarding animal numbers, barn and lagoon locations, and manure management practices. Where and when manure is applied on the landscape is key missing data that is needed to better understand and mitigate consequences of CAFO management practices. The aim of this study was to detect land applications of liquid manure using a remote sensing approach. We used random forest models incorporating C-Band synthetic-aperture radar, multispectral imagery, and other predictors to examine soil moisture conditions indicating probable liquid manure applications across known sprayfields in eastern North Carolina. Our models successfully distinguished saturated and unsaturated soils within corn, soybean, grassland, and 'other' crops, with 93-98% accuracy against validation for clear weather periods during the dormant, early, and late growing seasons. A Kruskal-Wallis test revealed that the mean soil saturation frequency was significantly higher on sprayfields than non-sprayfields of the same crop type (p < 2.2e-16). We also found that manure applications were concentrated within ∼1 km from the point of generation. This is the first application of satellite-based radar for identifying the location and timing of manure applications over broad areas. Future work can build on these methods to further understand manure management at CAFOs, as well as to improve pollution source tracking and modeling., (Copyright © 2022 Elsevier Ltd. All rights reserved.)

Concentrated Animal Feeding Operations (CAFOs) have arisen and expanded in the U.S. and globally to address efficiencies in livestock production. CAFOs tend to cluster in space for logistical purposes. Efficient distribution of concentrated manures produced by these operations is often not economically feasible, which may lead to accumulation on land near CAFOs, potentially resulting in local environmental changes. Moreover, as CAFOs are established or expand, they may need more lands to apply their manures, likely driving land use changes even after their establishment. Studies have yet to investigate these spatiotemporal impacts of CAFOs. We investigated whether the presence of regulated liquid waste CAFOs is associated with land use change over time and space as well as degraded environmental conditions surrounding those facilities. We used MODIS (Moderate Resolution Imaging Spectrometer) images from 2000 to 2018 to examine these questions in Michigan and North Carolina- states with varied CAFO establishment histories. We found that cropland extent increased while savanna and forest decreased near CAFOs. Similar observations did not occur outside of areas influenced by CAFOs. We also found evidence of environmental degradation, including decreased evapotranspiration and increased day and nighttime land surface temperatures in North Carolina. This study advances our understanding of environmental impacts surrounding CAFOs. Our findings can support policy changes and highlight the need to better understand these globally increasing entities., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2021 Elsevier B.V. All rights reserved.)

Air carries a diverse load of particulate microscopic biological matter in suspension, either aerosolized or aggregated with dust particles, the aerobiome, which is dispersed by winds from sources to sinks. The aerobiome is known to contain microbes, including pathogens, as well as debris or small-sized propagules from plants and animals, but its variability and composition has not been studied comprehensibly. To gain a dynamic insight into the aerobiome existing over a mixed-use dryland setting, we conducted a biologically comprehensive, year-long survey of its composition and dynamics for particles less than 10 μm in diameter based on quantitative analyses of DNA content coupled to genomic sequencing. Airborne biological loads were more dependent on seasonal events than on meteorological conditions and only weakly correlated with dust loads. Core aerobiome species could be understood as a mixture of high elevation (e.g. Microbacteriaceae, Micrococcaceae, Deinococci), and local plant and soil sources (e.g. Sphingomonas, Streptomyces, Acinetobacter). Despite the mixed used of the land surrounding the sampling site, taxa that contributed to high load events were largely traceable to proximal agricultural practices like cotton and livestock farming. This included not only the predominance of specific crop plant signals over those of native vegetation, but also that of their pathogens (bacterial, viral and eukaryotic). Faecal bacterial loads were also seasonally important, possibly sourced in intensive animal husbandry or manure fertilization activity, and this microbial load was enriched in tetracycline resistance genes. The presence of the native opportunistic pathogen, Coccidioides spp., by contrast, was detected only with highly sensitive techniques, and only rarely. We conclude that agricultural activity exerts a much stronger influence that the native vegetation as a mass loss factor to the land system and as an input to dryland aerobiomes, including in the dispersal of plant, animal and human pathogens and their genetic resistance characteristics., Competing Interests: Declaration of competing interest The authors declare no conflict of interest., (Copyright © 2021 Elsevier B.V. All rights reserved.)

Food, energy, and water (FEW) sectors are inextricably linked, making one sector vulnerable to disruptions in another. Interactions between FEW systems, viral pandemics, and human health have not been widely studied. We mined scientific and news/media articles for causal relations among FEW and COVID-19 variables and qualitatively characterized system dynamics. Food systems promoted the emergence and spread of COVID-19, leading to illness and death. Major supply-side breakdowns were avoided (likely due to low morbidity/mortality among working-age people). However, COVID-19 and physical distancing disrupted labor and capital inputs and stressed supply chains, while creating economic insecurity among the already vulnerable poor. This led to demand-side FEW insecurities, in turn increasing susceptibility to COVID-19 among people with many comorbidities. COVID-19 revealed trade-offs such as allocation of water to hygiene versus to food production and disease burden avoided by physical distancing versus disease burden from increased FEW insecurities. News/media articles suggest great public interest in FEW insecurities triggered by COVID-19 interventions among individuals with low COVID-19 case-fatality rates. There is virtually no quantitative analysis of any of these trade-offs or feedbacks. Enhanced quantitative FEW and health models are urgently needed as future pandemics are likely and may have greater morbidity and mortality than COVID-19., Competing Interests: The authors declare no competing financial interest., (© 2021 American Chemical Society.)

Background: Several studies have reported environmental disparities regarding exposure to concentrated animal feeding operations (CAFOs). Public health implications of environmental justice from the intensive livestock industry are of great concern in North Carolina (NC), USA, a state with a large number and extensive history of CAFOs., Objectives: We examined disparities by exposure to CAFOs using several environmental justice metrics and considering potentially vulnerable subpopulations., Methods: We obtained data on permitted animal facilities from NC Department of Environmental Quality (DEQ). Using ZIP code level variables from the 2010 Census, we evaluated environmental disparities by eight environmental justice metrics (i.e., percentage of Non-Hispanic White, Non-Hispanic Black, or Hispanic; percentage living below the poverty level; median household income; percentage with education less than high school diploma; racial residential isolation (RI) for Non-Hispanic Black; and educational residential isolation (ERI) for population without college degree). We applied two approaches to assign CAFOs exposure for each ZIP code: (1) a count method based on the number of CAFOs within ZIP code; and (2) a buffer method based on the area-weighted number of CAFOs using a 15 km buffer., Results: Spatial distributions of CAFOs exposure generally showed similar patterns between the two exposure methods. However, some ZIP codes had different estimated CAFOs exposure for the different approaches, with higher exposure when using the buffer method. Our findings indicate that CAFOs are located disproportionately in communities with higher percentage of minorities and in low-income communities. Distributions of environmental justice metrics generally showed similar patterns for both exposure methods, however starker disparities were observed using a buffer method., Conclusions: Our findings of the disproportionate location of CAFOs provide evidence of environmental disparities with respect to race and socioeconomic status in NC and have implications for future studies of environmental and health impacts of CAFOs., (Copyright © 2021 Elsevier Inc. All rights reserved.)

The need for effective water quality models to help guide management and policy, and extend monitoring information, is at the forefront of recent discussions related to watershed management. These models are often calibrated and validated at the basin outlet, which ensures that models are capable of evaluating basin scale hydrology and water quality. However, there is a need to understand where these models succeed or fail with respect to internal process representation, as these watershed-scale models are used to inform management practices and mitigation strategies upstream. We evaluated an ensemble of models-each calibrated to in-stream observations at the basin outlet-against discharge and nutrient observations at the farm field scale to determine the extent to which these models capture field-scale dynamics. While all models performed well at the watershed outlet, upstream performance varied. Models tended to over-predict discharge through surface runoff and subsurface drainage, while under-predicting phosphorus loading through subsurface drainage and nitrogen loading through surface runoff. Our study suggests that while models may be applied to predict impacts of management at the basin scale, care should be taken in applying the models to evaluate field-scale management and processes in the absence of data that can be incorporated at that scale, even with the use of multiple models., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2020 Elsevier B.V. All rights reserved.)

Waterbodies around the world experience problems associated with elevated phosphorus (P) and nitrogen (N) loads. While vital for ecosystem functioning, when present in excess amounts these nutrients can impair water quality and create symptoms of eutrophication, including harmful algal blooms. Under a changing climate, nutrient loads are likely to change. While climate models can serve as inputs to watershed models, the climate models often do not adequately represent the distribution of observed data, generating uncertainties that can be addressed to some degree with bias correction. However, the impacts of bias correction on nutrient models are not well understood. This study compares 4 univariate and 3 multivariate bias correction methods, which correct precipitation and temperature variables from 4 climate models in the historical (1980-1999) and mid-century future (2046-2065) time periods. These variables served as inputs to a calibrated Soil and Water Assessment Tool (SWAT) model of Lake Erie's Maumee River watershed. We compared the performance of SWAT outputs driven with climate model outputs that were bias-corrected (BC) and not bias-corrected (no-BC) for dissolved reactive P, total P, and total N. Results based on graphical comparisons and goodness of fit metrics showed that the choice of BC method impacts both the direction of change and magnitude of nutrient loads and hydrological processes. While the Delta method performed best, it should be used with caution since it considers historical variable relationships as the basis for predictions, which may not hold true under future climate. Quantile Delta Mapping (QDM) and Multivariate Bias Correction N-dimensional probability density function transform (MBCn) BC methods also performed well and work well for non-stationary climate scenarios. Furthermore, results suggest that February-July cumulative load in the Maumee basin is likely to decrease in the mid-century as runoff and snowfall decrease, and evapotranspiration increases with warming temperatures., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2020 Elsevier B.V. All rights reserved.)

In response to increased harmful algal blooms (HABs), hypoxia, and nearshore algae growth in Lake Erie, the United States and Canada agreed to phosphorus load reduction targets. While the load targets were guided by an ensemble of models, none of them considered the effects of climate change. Some watershed models developed to guide load reduction strategies have simulated climate effects, but without extending the resulting loads or their uncertainties to HAB projections. In this study, we integrated an ensemble of four climate models, three watershed models, and four HAB models. Nutrient loads and HAB predictions were generated for historical (1985-1999), current (2002-2017), and mid-21st-century (2051-2065) periods. For the current and historical periods, modeled loads and HABs are comparable to observations but exhibit less interannual variability. Our results show that climate impacts on watershed processes are likely to lead to reductions in future loading, assuming land use and watershed management practices are unchanged. This reduction in load should help reduce the magnitude of future HABs, although increases in lake temperature could mitigate that decrease. Using Monte-Carlo analysis to attribute sources of uncertainty from this cascade of models, we show that the uncertainty associated with each model is significant, and that improvements in all three are needed to build confidence in future projections., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2020 Elsevier B.V. All rights reserved.)

Reducing harmful algal blooms in Lake Erie, situated between the United States and Canada, requires implementing best management practices to decrease nutrient loading from upstream sources. Bi-national water quality targets have been set for total and dissolved phosphorus loads, with the ultimate goal of reaching these targets in 9-out-of-10 years. Row crop agriculture dominates the land use in the Western Lake Erie Basin thus requiring efforts to mitigate nutrient loads from agricultural systems. To determine the types and extent of agricultural management practices needed to reach the water quality goals, we used five independently developed Soil and Water Assessment Tool models to evaluate the effects of 18 management scenarios over a 10-year period on nutrient export. Guidance from a stakeholder group was provided throughout the project, and resulted in improved data, development of realistic scenarios, and expanded outreach. Subsurface placement of phosphorus fertilizers, cover crops, riparian buffers, and wetlands were among the most effective management options. But, only in one realistic scenario did a majority (3/5) of the models predict that the total phosphorus loading target would be met in 9-out-of-10 years. Further, the dissolved phosphorus loading target was predicted to meet the 9-out-of-10-year goal by only one model and only in three scenarios. In all scenarios evaluated, the 9-out-of-10-year goal was not met based on the average of model predictions. Ensemble modeling revealed general agreement about the effects of several practices although some scenarios resulted in a wide range of uncertainty. Overall, our results demonstrate that there are multiple pathways to approach the established water quality goals, but greater adoption rates of practices than those tested here will likely be needed to attain the management targets., (Copyright © 2020 Elsevier Ltd. All rights reserved.)

Coastal eutrophication is a leading cause of degraded water quality around the world. Identifying the sources and their relative contributions to impaired downstream water quality is an important step in developing management plans to address water quality concerns. Recent mass-balance studies of Total Phosphorus (TP) loads of the Maumee River watershed highlight the considerable phosphorus contributions of non-point sources, including agricultural sources, degrading regional downstream water quality. This analysis builds upon these mass-balance studies by using the Soil and Water Assessment Tool to simulate the movement of phosphorus from manure, inorganic fertilizer, point sources, and soil sources, and respective loads of TP and Dissolved Reactive Phosphorus (DRP). This yields a more explicit estimation of source contribution from the watershed. Model simulations indicate that inorganic fertilizers contribute a greater proportion of TP (45% compared to 8%) and DRP (58% compared to 12%) discharged from the watershed than manure sources in the March-July period, the season driving harmful algal blooms. Although inorganic fertilizers contributed a greater mass of TP and DRP than manure sources, the two sources had similar average delivery fractions of TP (2.7% for inorganic fertilizers vs. 3.0% for manure sources) as well as DRP (0.7% for inorganic fertilizers vs. 1.2% for manure sources). Point sources contributed similar proportions of TP (5%) and DRP (12%) discharged in March-July as manure sources. Soil sources of phosphorus contributed over 40% of the March-July TP load and 20% of the March-July DRP load from the watershed to Lake Erie. Reductions of manures and inorganic fertilizers corresponded to a greater proportion of phosphorus delivered from soil sources of phosphorus, indicating that legacy phosphorus in soils may need to be a focus of management efforts to reach nutrient load reduction goals. In agricultural watersheds aground the world, including the Maumee River watershed, upstream nutrient management should not focus solely on an individual nutrient source; rather a comprehensive approach involving numerous sources should be undertaken., (Copyright © 2020 Elsevier Ltd. All rights reserved.)

Watershed-scale hydrologic models are frequently used to inform conservation and restoration efforts by identifying critical source areas (CSAs; alternatively 'hotspots'), defined as areas that export relatively greater quantities of nutrients and sediment. The CSAs can then be prioritized or 'targeted' for conservation and restoration to ensure efficient use of limited resources. However, CSA simulations from watershed-scale hydrologic models may be uncertain and it is critical that the extent and implications of this uncertainty be conveyed to stakeholders and decision makers. We used an ensemble of four independently developed Soil and Water Assessment Tool (SWAT) models and a SPAtially Referenced Regression On Watershed attributes (SPARROW) model to simulate CSA locations for flow, phosphorus, nitrogen, and sediment within the ~17,000-km 2 Maumee River watershed at the HUC-12 scale. We then assessed uncertainty in CSA simulations determined as the variation in CSA locations across the models. Our application of an ensemble of models - differing with respect to inputs, structure, and parameterization - facilitated an improved accounting of CSA prediction uncertainty. We found that the models agreed on the location of a subset of CSAs, and that these locations may be targeted with relative confidence. However, models more often disagreed on CSA locations. On average, only 16%-46% of HUC-12 subwatersheds simulated as a CSA by one model were also simulated as a CSA by a different model. Our work shows that simulated CSA locations are highly uncertain and may vary substantially across models. Hence, while models may be useful in informing conservation and restoration planning, their application to identify CSA locations would benefit from comprehensive uncertainty analyses to avoid inefficient use of limited resources., (Copyright © 2020 Elsevier Ltd. All rights reserved.)

Hurricanes that damage lives and property can also impact pollutant sources and trigger poor water quality. Yet, these water quality impacts that affect both human and natural communities are difficult to quantify. We developed an operational remote sensing-based hurricane flood extent mapping method, examined potential water quality implications of two "500-year" hurricanes in 2016 and 2018, and identified options to increase social-ecological resilience in North Carolina. Flooding detected with synthetic aperture radar (>91% accuracy) extended beyond state-mapped hazard zones. Furthermore, the legal floodplain underestimated impacts for communities with higher proportions of older adults, disabilities, unemployment, and mobile homes, as well as for headwater streams with restricted elevation gradients. Pollution sources were repeatedly affected, including ∼55% of wastewater treatment plant capacity and swine operations that generate ∼500 M tons/y manure. We identified ∼4.8 million km 2 for possible forest and wetland conservation and ∼1.7 million km 2 for restoration or altered management opportunities. The results suggest that current hazard mapping is inadequate for resilience planning; increased storm frequency and intensity necessitate modification of design standards, land-use policies, and infrastructure operation. Implementation of interventions can be guided by a greater understanding of social-ecological vulnerabilities within hazard and exposure areas.

In the past 20 years, Lake Erie has experienced a resurgence of harmful algal blooms and hypoxia driven by increased nutrient loading from its agriculturally dominated watersheds. The increase in phosphorus loading, specifically the dissolved reactive portion, has been attributed to a combination of changing climate and agricultural management. While many management practices and strategies have been identified to reduce phosphorus loads, the impacts of future climate remain uncertain. This is particularly the case for the Great Lakes region because many global climate models do not accurately represent the land-lake interactions that govern regional climate. For this study, we used midcentury (2046-2065) climate projections from one global model and four regional dynamically downscaled models as drivers for the Soil and Water Assessment Tool configured for the Maumee River watershed, the source of almost 50% of Lake Erie's Western Basin phosphorus load. Our findings suggest that future warming may lead to less nutrient runoff due to increased evapotranspiration and decreased snowfall, despite projected moderate increases in intensity and overall amount of precipitation. Results highlight the benefits of considering multiple environmental drivers in determining the fate of nutrients in the environment and demonstrate a need to improve approaches for climate change assessment using watershed models.

A comprehensive inventory of ecosystem services across the entire Great Lakes basin is currently lacking and is needed to make informed management decisions. A greater appreciation and understanding of ecosystem services, including both use and non-use services, may have avoided misguided resource management decisions in the past that have resulted in legacies inherited by future generations. Given the interest in ecosystem services and lack of a coherent approach to addressing this topic in the Great Lakes, a summit was convened involving 28 experts working on various aspects of ecosystem services in the Great Lakes. The invited attendees spanned a variety of social and natural sciences. Given the unique status of the Great Lakes as the world's largest collective repository of surface freshwater, and the numerous stressors threatening this valuable resource, timing was propitious to examine ecosystem services. Several themes and recommendations emerged from the summit. There was general consensus that 1) a comprehensive inventory of ecosystem services throughout the Great Lakes is a desirable goal but would require considerable resources; 2) more spatially and temporally intensive data are needed to overcome our data gaps, but the arrangement of data networks and observatories must be well-coordinated; 3) trade-offs must be considered as part of ecosystem services analyses; and 4) formation of a Great Lakes Institute for Ecosystem Services, to provide a hub for research, meetings, and training is desirable. Several challenges also emerged during the summit, which are discussed in the paper.

Widespread adoption of agricultural conservation measures in Lake Erie's Maumee River watershed may be required to reduce phosphorus loading that drives harmful algal blooms and hypoxia. We engaged agricultural and conservation stakeholders through a survey and workshops to determine which conservation practices to evaluate. We investigated feasible and desirable conservation practices using the Soil and Water Assessment Tool calibrated for streamflow, sediment, and nutrient loading near the Maumee River outlet. We found subsurface placement of phosphorus applications to be the individual practice most influential on March-July dissolved reactive phosphorus (DRP) loading from row croplands. Perennial cover crops and vegetated filter strips were most effective for reducing seasonal total phosphorus (TP) loading. We found that practices effective for reducing TP and DRP load were not always mutually beneficial, culminating in trade-offs among multiple Lake Erie phosphorus management goals. Adoption of practices at levels considered feasible to stakeholders led to nearly reaching TP targets for western Lake Erie on average years; however, adoption of practices at a rate that goes beyond what is currently considered feasible will likely be required to reach the DRP target.

The recent resurgence of hypoxia and harmful algal blooms in Lake Erie, driven substantially by phosphorus loads from agriculture, have led the United States and Canada to begin developing plans to meet new phosphorus load targets. To provide insight into which agricultural management options could help reach these targets, we tested alternative agricultural-land-use and land-management scenarios on phosphorus loads to Lake Erie. These scenarios highlight certain constraints on phosphorus load reductions from changes in the Maumee River Watershed (MRW), which contributes roughly half of the phosphorus load to the lake's western basin. We evaluate the effects on phosphorus loads under nutrient management strategies, reduction of fertilizer applications, employing vegetative buffers, and implementing widespread cover crops and alternative cropping changes. Results indicate that even if fertilizer application ceased, it may take years to see desired decreases in phosphorus loads, especially if we experience greater spring precipitation or snowmelt. Scenarios also indicate that widespread conversions to perennial crops that may be used for biofuel production are capable of substantially reducing phosphorus loads. This work demonstrates that a combination of legacy phosphorus, land management, land use, and climate should all be considered when seeking phosphorus-loading solutions.

We present a comparison of two ecohydrologic models commonly used for planning land management to assess the production of hydrologic ecosystem services: the Soil and Water Assessment Tool (SWAT) and the Integrated Valuation of Ecosystem Services and Tradeoffs (InVEST) annual water yield model. We compare these two models at two distinct sites in the US: the Wildcat Creek Watershed in Indiana and the Upper Upatoi Creek Watershed in Georgia. The InVEST and SWAT models provide similar estimates of the spatial distribution of water yield in Wildcat Creek, but very different estimates of the spatial distribution of water yield in Upper Upatoi Creek. The InVEST model may do a poor job estimating the spatial distribution of water yield in the Upper Upatoi Creek Watershed because baseflow provides a significant portion of the site's total water yield, which means that storage dynamics which are not modeled by InVEST may be important. We also compare the ability of these two models, as well as one newly developed set of ecosystem service indices, to deliver useful guidance for land management decisions focused on providing hydrologic ecosystem services in three particular decision contexts: environmental flow ecosystem services, ecosystem services for potable water supply, and ecosystem services for rainfed irrigation. We present a simple framework for selecting models or indices to evaluate hydrologic ecosystem services as a way to formalize where models deliver useful guidance., (Copyright © 2016 Elsevier Ltd. All rights reserved.)