Scale of analysis drives the observed ratio of spatial to non-spatial variance in microbial water quality: insights from two decades of citizen science data.

AIMS: While fecal indicator bacteria (FIB) testing is used to monitor surface water for potential health hazards, observed variation in FIB levels may depend on the scale of analysis (SOA). Two decades of citizen science data, coupled with random effects models, were used to quantify the variance in FIB levels attributable to spatial versus temporal factors. METHODS AND RESULTS: Separately, Bayesian models were used to quantify the ratio of spatial to non-spatial variance in FIB levels and identify associations between environmental factors and FIB levels. Separate analyses were performed for three SOA: waterway, watershed, and statewide. As SOA increased (from waterway to watershed to statewide models), variance attributable to spatial sources generally increased and variance attributable to temporal sources generally decreased. While relationships between FIB levels and environmental factors, such as flow conditions (base versus stormflow), were constant across SOA, the effect of land cover was highly dependent on SOA and consistently smaller than the effect of stormwater infrastructure (e.g. outfalls). CONCLUSIONS: This study demonstrates the importance of SOA when developing water quality monitoring programs or designing future studies to inform water management.

Rise of Ruppia in Chesapeake Bay: Climate change-driven turnover of foundation species creates new threats and management opportunities.

Global change has converted many structurally complex and ecologically and economically valuable coastlines to bare substrate. In the structural habitats that remain, climate-tolerant and opportunistic species are increasing in response to environmental extremes and variability. The shifting of dominant foundation species identity with climate change poses a unique conservation challenge because species vary in their responses to environmental stressors and to management. Here, we combine 35 y of watershed modeling and biogeochemical water quality data with species comprehensive aerial surveys to describe causes and consequences of turnover in seagrass foundation species across 26,000 ha of habitat in the Chesapeake Bay. Repeated marine heatwaves have caused 54% retraction of the formerly dominant eelgrass (Zostera marina) since 1991, allowing 171% expansion of the temperature-tolerant widgeongrass (Ruppia maritima) that has likewise benefited from large-scale nutrient reductions. However, this phase shift in dominant seagrass identity now presents two significant shifts for management: Widgeongrass meadows are not only responsible for rapid, extensive recoveries but also for the largest crashes over the last four decades; and, while adapted to high temperatures, are much more susceptible than eelgrass to nutrient pulses driven by springtime runoff. Thus, by selecting for rapid post-disturbance recolonization but low resistance to punctuated freshwater flow disturbance, climate change could threaten the Chesapeake Bay seagrass' ability to provide consistent fishery habitat and sustain functioning over time. We demonstrate that understanding the dynamics of the next generation of foundation species is a critical management priority, because shifts from relatively stable habitat to high interannual variability can have far-reaching consequences across marine and terrestrial ecosystems.

Structural Equation Models Suggest That On-Farm Noncrop Vegetation Removal Is Not Associated with Improved Food Safety Outcomes but Is Linked to Impaired Water Quality.

While growers have reported pressures to minimize wildlife intrusion into produce fields through noncrop vegetation (NCV) removal, NCV provides key ecosystem services. To model food safety and environmental tradeoffs associated with NCV removal, published and publicly available food safety and water quality data from the Northeastern United States were obtained. Because data on NCV removal are not widely available, forest-wetland cover was used as a proxy, consistent with previous studies. Structural equation models (SEMs) were used to quantify the effect of forest-wetland cover on (i) food safety outcomes (e.g., detecting pathogens in soil) and (ii) water quality (e.g., nutrient levels). Based on the SEMs, NCV was not associated with or had a protective effect on food safety outcomes (more NCV was associated with a reduced likelihood of pathogen detection). The probabilities of detecting Listeria spp. in soil (effect estimate [EE] = -0.17; P = 0.005) and enterohemorrhagic Escherichia coli in stream samples (EE = -0.27; P < 0.001) were negatively associated with the amount of NCV surrounding the sampling site. Larger amounts of NCV were also associated with lower nutrient, salinity, and sediment levels, and higher dissolved oxygen levels. Total phosphorous levels were negatively associated with the amount of NCV in the upstream watershed (EE = -0.27; P < 0.001). Similar negative associations (P < 0.05) were observed for other physicochemical parameters, such as nitrate (EE = -0.38). Our findings suggest that NCV should not be considered an inherent produce safety risk or result in farm audit demerits. This study also provides a framework for evaluating environmental tradeoffs associated with using specific preharvest food safety strategies. IMPORTANCE Currently, on-farm food safety decisions are typically made independently of conservation considerations, often with detrimental impacts on agroecosystems. Comanaging agricultural environments to simultaneously meet conservation and food safety aims is complicated because farms are closely linked to surrounding environments, and management decisions can have unexpected environmental, economic, and food safety consequences. Thus, there is a need for research on the conservation and food safety tradeoffs associated with implementing specific preharvest food safety practices. Understanding these tradeoffs is critical for developing adaptive comanagement strategies and ensuring the short- and long-term safety, sustainability, and profitability of agricultural systems. This study quantifies tradeoffs and synergies between food safety and environmental aims, and outlines a framework for modeling tradeoffs and synergies between management aims that can be used to support future comanagement research.

Data synthesis for environmental management: A case study of Chesapeake Bay.

Synthesizing large, complex data sets to inform resource managers towards effective environmental stewardship is a universal challenge. In Chesapeake Bay, a well-studied and intensively monitored estuary in North America, the challenge of synthesizing data on water quality and land use as factors related to a key habitat, submerged aquatic vegetation, was tackled by a team of scientists and resource managers operating at multiple levels of governance (state, federal). The synthesis effort took place over a two-year period (2016-2018), and the results were communicated widely to a) scientists via peer review publications and conference presentations; b) resource managers via web materials and workshop presentations; and c) the public through newspaper articles, radio interviews, and podcasts. The synthesis effort was initiated by resource managers at the United States Environmental Protection Agencys' Chesapeake Bay Program and 16 scientist participants were recruited from a diversity of organizations. Multiple short, immersive workshops were conducted regularly to conceptualize the problem, followed by data analysis and interpretation that supported the preparation of the synthetic products that were communicated widely. Reflections on the process indicate that there are a variety of structural and functional requirements, as well as enabling conditions, that need to be considered to achieve successful outcomes from synthesis efforts.

Encountering Overdose: Examining the Contexts and Correlates of US College Students' Overdose Experiences.

BACKGROUND: As overdose rates increase, it is critical to better understand the causes and contexts of overdose, particularly for college students who exhibit high rates of alcohol and drug use. The purpose of this study was to examine the social contexts of U.S. college students' overdose experiences (their own, witnessed, and family'/friends'), and to assess the correlates of personal overdose. METHODS: A cross-sectional survey containing open- and closed-ended questions about overdose encounters was completed by undergraduate students at a southeastern American university (n = 1,236). Descriptive frequencies assessed prevalence, substance involvement, and fatalities associated with different encounter types. A content analysis of open-ended responses examined the social contexts of encounters. Multivariate logistic regression was used to assess the correlates of personal overdose. RESULTS: Forty-one percent of respondents reported at least one type of overdose encounter and witnessed overdose was most common. Substances involved varied across encounter type and 20-40% of respondents reported overdose-related fatalities. Students who encountered overdose often reported multiple experiences and many attributed overdoses to mixing substances. Respondents commonly encountered overdose as intervening bystanders and overdose events were often perceived to be intentional or the result of using substances to cope with stress/mental health concerns. Personal overdose was significantly associated with having ever mixed alcohol with prescription drugs, been diagnosed with a mental disorder, witnessed an overdose, and had a family member/friend overdose. CONCLUSION: Findings suggest a need for future research into the contexts and consequences of students' overdose encounters to more effectively tailor overdose prevention/response initiatives within college communities.

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.

Author Correction: Accuracy and Precision of Tidal Wetland Soil Carbon Mapping in the Conterminous United States.

A correction to this article has been published and is linked from the HTML and PDF versions of this paper. The error has not been fixed in the paper.

Accuracy and Precision of Tidal Wetland Soil Carbon Mapping in the Conterminous United States.

Tidal wetlands produce long-term soil organic carbon (C) stocks. Thus for carbon accounting purposes, we need accurate and precise information on the magnitude and spatial distribution of those stocks. We assembled and analyzed an unprecedented soil core dataset, and tested three strategies for mapping carbon stocks: applying the average value from the synthesis to mapped tidal wetlands, applying models fit using empirical data and applied using soil, vegetation and salinity maps, and relying on independently generated soil carbon maps. Soil carbon stocks were far lower on average and varied less spatially and with depth than stocks calculated from available soils maps. Further, variation in carbon density was not well-predicted based on climate, salinity, vegetation, or soil classes. Instead, the assembled dataset showed that carbon density across the conterminous united states (CONUS) was normally distributed, with a predictable range of observations. We identified the simplest strategy, applying mean carbon density (27.0 kg C m-3), as the best performing strategy, and conservatively estimated that the top meter of CONUS tidal wetland soil contains 0.72 petagrams C. This strategy could provide standardization in CONUS tidal carbon accounting until such a time as modeling and mapping advancements can quantitatively improve accuracy and precision.

Long-term nutrient reductions lead to the unprecedented recovery of a temperate coastal region.

Humans strongly impact the dynamics of coastal systems, yet surprisingly few studies mechanistically link management of anthropogenic stressors and successful restoration of nearshore habitats over large spatial and temporal scales. Such examples are sorely needed to ensure the success of ecosystem restoration efforts worldwide. Here, we unite 30 consecutive years of watershed modeling, biogeochemical data, and comprehensive aerial surveys of Chesapeake Bay, United States to quantify the cascading effects of anthropogenic impacts on submersed aquatic vegetation (SAV), an ecologically and economically valuable habitat. We employ structural equation models to link land use change to higher nutrient loads, which in turn reduce SAV cover through multiple, independent pathways. We also show through our models that high biodiversity of SAV consistently promotes cover, an unexpected finding that corroborates emerging evidence from other terrestrial and marine systems. Due to sustained management actions that have reduced nitrogen concentrations in Chesapeake Bay by 23% since 1984, SAV has regained 17,000 ha to achieve its highest cover in almost half a century. Our study empirically demonstrates that nutrient reductions and biodiversity conservation are effective strategies to aid the successful recovery of degraded systems at regional scales, a finding which is highly relevant to the utility of environmental management programs worldwide.

Urbanization reduces and homogenizes trait diversity in stream macroinvertebrate communities.

More than one-half of the world's population lives in urban areas, so quantifying the effects of urbanization on ecological communities is important for understanding whether anthropogenic stressors homogenize communities across environmental and climatic gradients. We examined the relationship of impervious surface coverage (a marker of urbanization) and the structure of stream macroinvertebrate communities across the state of Maryland and within each of Maryland's three ecoregions: Coastal Plain, Piedmont, and Appalachian, which differ in stream geomorphology and community composition. We considered three levels of trait organization: individual traits, unique combinations of traits, and community metrics (functional richness, functional evenness, and functional divergence) and three levels of impervious surface coverage (low [<2.5%], medium [2.5% to 10%], and high [>10%]). The prevalence of an individual trait differed very little between low impervious surface and high impervious surface sites. The arrangement of trait combinations in community trait space for each ecoregion differed when impervious surface coverage was low, but the arrangement became more similar among ecoregions as impervious surface coverage increased. Furthermore, trait combinations that occurred only at low or medium impervious surface coverage were clustered in a subset of the community trait space, indicating that impervious surface affected the presence of only a subset of trait combinations. Functional richness declined with increasing impervious surface, providing evidence for environmental filtering. Community metrics that include abundance were also sensitive to increasing impervious surface coverage: functional divergence decreased while functional evenness increased. These changes demonstrate that increasing impervious surface coverage homogenizes the trait diversity of macroinvertebrate communities in streams, despite differences in initial community composition and stream geomorphology among ecoregions. Community metrics were also more sensitive to changes in the abundance rather than the gain or loss of trait combinations, showing the potential for trait-based approaches to serve as early warning indicators of environmental stress for monitoring and biological assessment programs.

Using Bayesian hierarchical models to better understand nitrate sources and sinks in agricultural watersheds.

Export coefficient models (ECMs) are often used to predict nutrient sources and sinks in watersheds because ECMs can flexibly incorporate processes and have minimal data requirements. However, ECMs do not quantify uncertainties in model structure, parameters, or predictions; nor do they account for spatial and temporal variability in land characteristics, weather, and management practices. We applied Bayesian hierarchical methods to address these problems in ECMs used to predict nitrate concentration in streams. We compared four model formulations, a basic ECM and three models with additional terms to represent competing hypotheses about the sources of error in ECMs and about spatial and temporal variability of coefficients: an ADditive Error Model (ADEM), a SpatioTemporal Parameter Model (STPM), and a Dynamic Parameter Model (DPM). The DPM incorporates a first-order random walk to represent spatial correlation among parameters and a dynamic linear model to accommodate temporal correlation. We tested the modeling approach in a proof of concept using watershed characteristics and nitrate export measurements from watersheds in the Coastal Plain physiographic province of the Chesapeake Bay drainage. Among the four models, the DPM was the best--it had the lowest mean error, explained the most variability (R2 = 0.99), had the narrowest prediction intervals, and provided the most effective tradeoff between fit complexity (its deviance information criterion, DIC, was 45.6 units lower than any other model, indicating overwhelming support for the DPM). The superiority of the DPM supports its underlying hypothesis that the main source of error in ECMs is their failure to account for parameter variability rather than structural error. Analysis of the fitted DPM coefficients for cropland export and instream retention revealed some of the factors controlling nitrate concentration: cropland nitrate exports were positively related to stream flow and watershed average slope, while instream nitrate retention was positively correlated with nitrate concentration. By quantifying spatial and temporal variability in sources and sinks, the DPM provides new information to better target management actions to the most effective times and places. Given the wide use of ECMs as research and management tools, our approach can be broadly applied in other watersheds and to other materials.

How novel is too novel? Stream community thresholds at exceptionally low levels of catchment urbanization.

Novel physical and chemical conditions of many modern ecosystems increasingly diverge from the environments known to have existed at any time in the history of Earth. The loss of natural land to urbanization is one of the most prevalent drivers of novel environments in freshwaters. However, current understanding of aquatic community response to urbanization is based heavily upon aggregate indicators of community structure and linear or wedge-shaped community response models that challenge ecological community theory. We applied a new analytical method, threshold indicator taxa analysis (TITAN), to a stream biomonitoring data set from Maryland to explicitly evaluate linear community response models to urbanization that implicitly assume individual taxa decline or increase at incrementally different levels of urbanization. We used TITAN (1) to identify the location and magnitude of greatest change in the frequency and abundance of individual taxa and (2) to assess synchrony in the location of change points as evidence for stream community thresholds in response to percent impervious cover in catchments. We documented clear and synchronous threshold declines of 110 of 238 macroinvertebrate taxa in response to low levels of impervious cover. Approximately 80% of the declining taxa did so between 0.5% and 2% impervious cover, whereas the last 20% declined sporadically from 2% to 25% impervious cover. Synchrony of individual responses resulted in distinct community-level thresholds ranging from < or = 0.68% (mountains), 1.28% (piedmont), and 0.96% (coastal plain) impervious cover. Upper limits (95% confidence intervals) of community thresholds were < 2% cover in all regions. Within distinct physiographic classes, higher-gradient, smaller catchments required less impervious cover than lower gradient, larger catchments to elicit community thresholds. Relatively few taxa showed positive responses to increasing impervious cover, and those that did gradually increased in frequency and abundance, approximating a linear cumulative distribution. The sharp, synchronous declines of numerous taxa established a consistent threshold response at exceptionally low levels of catchment urbanization, and uncertainty regarding the estimation of impervious cover from satellite data was mitigated by several corroborating lines of evidence. We suggest that threshold responses of communities to urban and other novel environmental gradients may be more prevalent than currently recognized.

Effects of riparian buffers on nitrate concentrations in watershed discharges: new models and management implications.

Watershed analyses of nutrient removal in riparian buffers have been limited by the geographic methods used to map buffers and by the statistical models used to test and quantify buffer effects on stream nutrient levels. We combined geographic methods that account for buffer prevalence along flow paths connecting croplands to streams with improved statistical models to test for buffer effects on stream nitrate concentrations from 321 tributary watersheds to the Chesapeake Bay, USA. We developed statistical models that predict stream nitrate concentration from watershed land cover and physiographic province. We used information theoretic methods (AIC(c)) to compare models with and without buffer terms, and we demonstrate that models accounting for riparian buffers better explain stream nitrate concentrations than models using only land cover proportions. We analyzed the buffer model parameters to quantify differences within and among physiographic provinces in the potentials for nitrate loss from croplands and nitrate removal in buffers. On average, buffers in Coastal Plain study watersheds had a higher relative nitrate removal potential (95% of the inputs from cropland) than Piedmont buffers (35% of inputs). Buffers in Appalachian Mountain study watersheds were intermediate (retaining 39% of cropland inputs), but that percentage was uncertain. The absolute potential to reduce nitrate concentration was highest in the Piedmont study watersheds because of higher nitrate inputs from cropland. Model predictions for the study watersheds provided estimates of nitrate removals achieved with the existing cropland and buffer distributions. Compared to expected nitrate concentrations if buffers were removed, current buffers reduced average nitrate concentrations by 0.73 mg N/L (50% of their inputs from cropland) in the Coastal Plain study watersheds, 0.40 mg N/L (11%) in the Piedmont, and 0.08 mg N/L (5%) in the Appalachian Mountains. Restoration to close all buffer gaps downhill from croplands would further reduce nitrate concentrations by 0.66 mg N/L, 0.83 mg N/L, and 0.51 mg N/L, respectively, in the Coastal Plain, Piedmont, and Appalachian Mountain study watersheds. Aggregate nitrate removal by riparian buffers was less than suggested by many studies of field-to-stream transects, but buffer nitrate removal is significant, and restoration could achieve substantial additional removal.

The α7-nicotinic acetylcholine receptor and MMP-2/-9 pathway mediate the proangiogenic effect of nicotine in human retinal endothelial cells.

PURPOSE: Nicotine, the active component of cigarette smoke, has been found to stimulate angiogenesis in several experimental systems. In this study, the Matrigel duplex assay (Matrigel; BD Biosciences, Franklin Lakes, NJ) and the rat retinal explant assay were used to explore the molecular mechanisms underlying the proangiogenic effects of nicotine in endothelial cells. METHODS: Western blot analysis was performed to determine the nicotinic acetylcholine receptor (nAChR) subtypes expressed on primary human retinal microvascular endothelial cells (HRMECs). The angiogenic effect of nicotine in the retina was evaluated with the duplex assay. The results obtained from the assay were confirmed by the rat retinal explant angiogenesis assay. ELISAs were used to measure MMP-2, -9, and -13 levels in HRMEC culture supernatants. The role of α7-nAChRs in nicotine-induced angiogenesis was examined by siRNA techniques. RESULTS: Nicotine-induced angiogenesis required nAChR function and was associated with the upregulation of MMP-2 and -9 in HRMECs. Specifically, α7-nAChRs mediated the stimulatory effects of nicotine on retinal angiogenesis and MMP levels. Treatment of HRMECs with α7-nAChR antagonists ablated nicotine-induced angiogenesis. The inhibitory actions of α7-nAChR antagonists correlated with the suppression of MMP-2 and -9 levels in HRMECs. CONCLUSIONS: The α7-nAChR is vital for the proangiogenic activity of nicotine. The α7-nAChRs expressed on HRMECs upregulate levels of MMP-2 and -9, which stimulate retinal angiogenesis. The data also suggest that α7-nAChR antagonists could be useful agents for the therapy of angiogenesis-related retinal diseases.

Empirical models based on the universal soil loss equation fail to predict sediment discharges from Chesapeake Bay catchments.

The Universal Soil Loss Equation (USLE) and its derivatives are widely used for identifying watersheds with a high potential for degrading stream water quality. We compared sediment yields estimated from regional application of the USLE, the automated revised RUSLE2, and five sediment delivery ratio algorithms to measured annual average sediment delivery in 78 catchments of the Chesapeake Bay watershed. We did the same comparisons for another 23 catchments monitored by the USGS. Predictions exceeded observed sediment yields by more than 100% and were highly correlated with USLE erosion predictions (Pearson r range, 0.73-0.92; p < 0.001). RUSLE2-erosion estimates were highly correlated with USLE estimates (r = 0.87; p < 001), so the method of implementing the USLE model did not change the results. In ranked comparisons between observed and predicted sediment yields, the models failed to identify catchments with higher yields (r range, -0.28-0.00; p > 0.14). In a multiple regression analysis, soil erodibility, log (stream flow), basin shape (topographic relief ratio), the square-root transformed proportion of forest, and occurrence in the Appalachian Plateau province explained 55% of the observed variance in measured suspended sediment loads, but the model performed poorly (r(2) = 0.06) at predicting loads in the 23 USGS watersheds not used in fitting the model. The use of USLE or multiple regression models to predict sediment yields is not advisable despite their present widespread application. Integrated watershed models based on the USLE may also be unsuitable for making management decisions.

Watershed land use is strongly linked to PCBs in white perch in Chesapeake Bay subestuaries.

We related total PCBs (t-PCBs) in white perch (Morone americana), an abundant estuarine resident that supports a valuable recreational and commercial fishery in the mid-Atlantic region, to the amount and spatial arrangement of developed land in watersheds that discharge into 14 subestuaries of Chesapeake Bay. We considered the intensity of development in watersheds using four developed land-use measures (% impervious surface, % total developed land, % high-intensity residential + commercial [%high-res/comm], and % commercial) to represent potential source areas of PCBs to the subestuaries. We further evaluated the importance of source proximity by calculating three inverse-distance weighted (IDW) metrics of development, an approach that weighted developed land near the shoreline more heavily than developed land farther away. Unweighted percentages of each of the four measures of developed land explained 51-69% of the variance in t-PCBs. However, IDWs markedly improved the relationships between % developed land measures and t-PCBs. Percent commercial land, weighted by its simple inverse distance, explained 99% of the variance in t-PCBs, whereas the other three measures explained as much as 93-97%. PCBs historically produced or used in commercial and residential areas are apparently persisting in the environment atthe scale of the watersheds and subestuaries examined in this study, and developed land close to the subestuary has the greatest unit effect on t-PCBs in fish. These findings provide compelling evidence for a strikingly strong linkage between watershed land use and t-PCBs in white perch, and this relationship may prove useful for identifying unsampled subestuaries with a high risk of PCB contamination.