Temporal and spatial variability of instream indicator bacteria (Escherichia coli) and implications for water quality monitoring

Many water quality monitoring programs quantify Escherichia coli, an indicator of fecal contamination and potential sewage pollution. However, interpretation of E. coli data can be complex due to abiotic factors that influence its growth and mortality. The goal of this study was to quantify the variability of E. coli in a river and assess the impact of that variability on water quality monitoring study design and sewage pollution source identification. Over 1900 samples were collected and analyzed from 2007 to 2017 in the Norwalk River in Connecticut. Sixty-six percent of the samples collected during weekly to monthly monitoring had E. coli concentrations below 200 CFU/100 mL, indicating that elevated bacteria concentrations were captured infrequently. Patterns observed during daily sampling indicated that the randomization of sampling days within a week may support the identification of pollution sources driven by human behavioral patterns. Spatial autocorrelation in bacteria concentrations was not observed between sites, indicating that the sample locations were not spaced sufficiently close together to be redundant for monitoring. On finer spatial scales however, detection of a known pollution source was found to be challenging at even short distances downstream, with less than 25% of the original source concentration detected at 10 m downstream and less than 10% by 1000 m downstream, suggesting that a high density of study sites may be needed to detect potential sources. These findings can be used to better understand the natural variability of this important indicator organism in freshwater systems, and inform more efficient and effective monitoring.

Thorium content in soil, water and sediment samples and fluvial sediment-associated transport in a catchment system with a semiarid-coastal interface, Brazil

Thorium (Th) is one of the main sources of natural radiation to ecosystems. However, data regarding Th concentrations in rocks, soil, water and sediments are currently scarce. Accordingly, this study aimed to establish background concentrations and quality reference values (QRVs) for Th in the environmentally impacted Ipojuca River catchment in Brazil, where the weathering of granites releases Th into the environment. Additionally, the study aimed to calculate Th fluxes in water, and both bed and suspended sediment. The mean Th concentration in the study catchment soils was 28.6 mg kg^-1. The QRV for Th was estimated to be 21 mg kg^-1 and 86.3 Bq kg^-1. Bed and suspended sediment-associated concentrations ranged from 2.8 to 32.9 mg kg^-1. Suspended sediment-associated discharge (3.42 t year^-1) accounted for more than 99% of the total Th flux, while the dissolved phase transport was negligible in comparison. At the downstream cross section in the study catchment, suspended sediment samples exhibited Th concentrations similar to those observed in rivers impacted by mining activities. The discharge of sediment to the ocean from the study area is mainly triggered by soil erosion processes in the hotspot region (middle-inferior course). It is essential to identify Th hotspots before establishing environmental policies regarding human health and environmental protection.

Magnesium isotopes reveal bedrock impacts on stream organisms

Magnesium is an essential element to aquatic organisms and understanding the origin of Mg is important for understanding their growth. Ultimately, Mg in streams is derived from the chemical weathering of bedrock in the catchment. In this study, we used Mg stable isotope ratios (δ²⁶Mg) to test whether stream organisms reflect lithological sources in stream catchments. In November 2017 and May 2018, we sampled aquatic insects and small gobies from six temperate streams in the Lake Biwa area (central Japan). Three of these streams had up to 38% limestone in their catchment (limestone streams), and three streams lacked limestone (non-limestone streams). We hypothesised that stream organisms from limestone streams had significantly lower δ²⁶Mg values compared to those of the same organisms from non-limestone streams. Aquatic insects from limestone streams had an average of 0.78‰ lower δ²⁶Mg values than those of the same organisms from non-limestone streams, thereby indicating a lithological control on the δ²⁶Mg of aquatic insects. Aquatic insects often showed an offset to higher δ²⁶Mg values compared to those of stream water, thereby pointing to a ²⁶Mg-enriched diet as an additional Mg source to water and/or Mg isotope fractionation during Mg accumulation. Instead, stream water was the main Mg source for small gobies, as their bones reflected the δ²⁶Mg of water. We concluded that δ²⁶Mg could trace Mg sources of aquatic organisms, and the same methodology can be applied to other metals.

Development of environmental effects monitoring protocol in Brazil: a fish guide study of three river estuaries

In Brazil, there are no unified and effective environmental monitoring models for bodies of water. Thus, several methodologies are used that result in information that is often difficult to compare, especially for stakeholders involved in regional water management. Studies in some countries such as Australia, Chile, the USA, and Sweden use the monitoring model implemented in Canada that was developed in the early 1990s. This model was designed to evaluate whether the current environmental regulations are sufficiently protective for pulp and paper effluents and for metal mining effluents. In this study, the Canadian Environmental Effects Monitoring methodologies were applied to three different Brazilian river basins, with the goal of constructing a framework for monitoring environmental effects. Pilot studies were carried out in the estuarine regions of the Benevente, Jucu, and Santa Maria da Vitória river basins, which are important rivers in the state of Espírito Santo. Evaluations included fish health, bioaccumulation studies, benthic invertebrate survey, and physical-chemical analyses of water and sediment. The quality of the environments was evaluated by means of seasonal samplings and comparisons between discharge, upstream, and downstream areas. This study made it possible to identify appropriate fish species to be used in environmental effects monitoring and the environmental quality of the rivers themselves as well as knowledge and policy gaps to implement such monitoring programs in Brazil. The study raises questions about the adequacy of Brazilian environmental legislation concerning tidal rivers.

Comprehensive and quantitative assessment of nitrate dynamics in two contrasting forested basins along the Sea of Japan using dual isotopes of nitrate

The recent deposition rates of atmospheric nitrate derived from east Asia to the Japanese forested watershed facing the Sea of Japan are of serious concern. However, export ratios and the seasonality of atmospheric nitrate versus microbial nitrate from forest soils to upstreams have not yet been quantified. Furthermore, the influence of local nitrogen sources and internal biogeochemical processes are still unclear. To determine the influence of watershed properties and atmospheric nitrogen deposition on nitrate dynamics in two adjacent basins (the Kita and Minami Rivers) located in central Japan, we conducted seasonal synoptic surveys using the dual isotopes of nitrate. It was found that nitrate regenerated through nitrification in the forest soil was likely the dominant nitrogen source in both basins from the upstream to downstream waters. However, nitrate concentrations and the direct leaching ratio of atmospheric nitrate were considerably higher in the Kita River Basin than in the Minami River Basin, possibly due to the difference in forest environments. In the Kita River Basin, geographic trait such as altitude may be one factor regulating the sensitivity of forest ecosystem to nitrogen deposition. Quantitative assessments of nitrate outflows from the sub-basins revealed that nitrogen leached from the forest soil was a major source (61-81%) of nitrate loading to the coastal sea.

Assessing tree ring δ15N of four temperate deciduous species as an indicator of N availability using independent long-term records at the Fernow Experimental Forest, WV

Nitrogen deposition in the northeastern US changed N availability in the latter part of the twentieth century, with potential legacy effects. However, long-term N cycle measurements are scarce. N isotopes in tree rings have been used as an indicator of N availability through time, but there is little verification of whether species differ in the strength of this signal. Using long-term records at the Fernow Experimental Forest in West Virginia, we examined the relationship between soil conditions, including net nitrification rates, and wood δ¹⁵N in 2014, and tested the strength of correlation between tree ring δ¹⁵N of four species and stream water NO₃^- loss from 1971 to 2000. Higher soil NO₃^- was weakly associated with higher wood δ¹⁵N across species, and higher soil net nitrification rates were associated with higher δ¹⁵N for Quercus rubra only. The δ¹⁵N of Liriodendron tulipifera and Q. rubra, but neither Fagus grandifolia nor Prunus serotina, was correlated with stream water NO₃^-. L. tulipifera tree ring δ¹⁵N had a stronger association with stream water NO₃^- than Q. rubra. Overall, we found only limited evidence of a relationship between soil N cycling and tree ring δ¹⁵N, with a strong correlation between the wood δ¹⁵N and NO₃^- leaching loss through time for one of four species. Tree species differ in their ability to preserve legacies of N cycling in tree ring δ¹⁵N, and given the weak relationships between contemporary wood δ¹⁵N and soil N cycle measurements, caution is warranted when using wood δ¹⁵N to infer changes in the N cycle.

Forest filter effect for polybrominated diphenyl ethers in a tropical watershed

There is limited research characterizing the fates of persistent organic pollutants in tropical multi-use watersheds. This study aimed to evaluate the role of forests in the environmental fates of select polybrominated diphenyl ethers (PBDEs) for a case study tropical drainage basin, the Rio Cobre watershed. Field samples of deposition, soil, litterfall and the atmosphere of a forest and nearby clearing were analyzed for the presence of the PBDEs (PBDE-28, 47, 99, 100, 153, 154, 183 and 209), which are routinely detected in the environment. The mean air and litterfall concentrations of these PBDEs were generally lower in the forest than in the clearing, whereas the deposition flux rate and soil concentrations were higher in the forest. The results suggest that the forest filtered the PBDEs by transferring them from the atmosphere to the soil, despite the tropical nature of the study site.

Factors affecting MeHg bioaccumulation in stream biota: the role of dissolved organic carbon and diet

The bioaccumulation of the neurotoxin methylmercury (MeHg) in freshwater ecosystems is thought to be mediated by both water chemistry (e.g., dissolved organic carbon [DOC] and dissolved mercury [Hg]) and diet (e.g., trophic position and diet composition). Hg in small streams is of particular interest given their role as a link between terrestrial and aquatic processes. Terrestrial processes determine the quantity and quality of streamwater DOC, which in turn influence the quantity and bioavailability of dissolved MeHg. To better understand the effects of water chemistry and diet on Hg bioaccumulation in stream biota, we measured DOC and dissolved Hg in stream water and mercury concentration in three benthic invertebrate taxa and three fish species across up to 12 tributary streams in a forested watershed in New Hampshire, USA. As expected, dissolved total mercury (THg) and MeHg concentrations increased linearly with DOC. However, mercury concentrations in fish and invertebrates varied non-linearly, with maximum bioaccumulation at intermediate DOC concentrations, which suggests that MeHg bioavailability may be reduced at high levels of DOC. Further, MeHg and THg concentrations in invertebrates and fish, respectively, increased with δ¹⁵N (suggesting trophic position) but were not associated with δ¹³C. These results show that even though MeHg in water is strongly determined by DOC concentrations, mercury bioaccumulation in stream food webs is the result of both MeHg availability in stream water and trophic position.

Metal impacts on the persistence and proliferation of β-lactam resistance genes in Xiangjiang River, China

Currently, the emergence of clinically relevant multi-resistant bacteria and the associated β-lactamases resistance genes which threaten the last frontier for antibiotics presents a major challenge for medical treatment. Xiangjiang River is typically contaminated with heavy metals due to the intensive metal mining activities within this watershed. The occurrence and distribution of several β-lactam antibiotics and ten β-lactam resistance genes (bla_TEM, bla_VIM, bla_SHV, bla_GES, bla_DHA, bla_OXA-1, bla_OXA-2, bla_OXA-10, bla_CMY-2, and bla_ampC) were investigated in the Xiangjiang River, China. The absolute abundance of bla genes was as high as (7.0 ± 0.6) × 10⁶ copies/mL for surface water and (2.3 ± 0.7) × 10⁸ copies/g for sediment. In contrast, all the detected β-lactam antibiotic compounds were below the detection limit. The distribution of individual bla gene subtypes was correlated with speciation of heavy metals which might affect the bacterial community structure. The principal coordinate analysis (PCoA) and Mantal test reconfirmed that the heavy metals had a correlation with the bla genes and the bla genes were correlated with bacterial community structure, suggesting that heavy metals impacted on the distribution of the bla genes by shifting bacterial community structure under the long-term selective pressure. The microcosm experiments indicated metal-induced persistence of bla genes in the resistant bacteria (Bacillus megaterium, Staphylococcus epidermidis). The persistence of β-lactam resistance under metal selective pressure is beneficial to the survival of resistant bacteria, thereby contributing to the shift of the bacterial community structure, consequently impacts on the distribution of bla genes.

Modeling the impacts of agricultural best management practices on runoff, sediment, and crop yield in an agriculture-pasture intensive watershed

Best management practices (BMPs) are commonly used to reduce sediment loadings. In this study, we modeled the Fort Cobb Reservoir watershed located in southwestern Oklahoma, USA using the Soil and Water Assessment Tool (SWAT) and evaluated the impacts of five agricultural BMP scenarios on surface runoff, sediment yield, and crop yield. The hydrological model, with 43 sub-basins and 15,217 hydrological response units, was calibrated (1991–2000) and validated (2001–2010) against the monthly observations of streamflow, sediment grab samples, and crop-yields. The coefficient of determination (R²), Nash-Sutcliffe efficiency (NS) and percentage bias (PB) were used to determine model performance with satisfactory values of R² (0.64 and 0.79) and NS (0.61 and 0.62) in the calibration and validation period respectively for streamflow. We found that contouring practice reduced surface runoff by more than 18% in both conservation tillage and no-till practices for all crops used in this modeling study. In addition, contour farming with either conservation tillage or no-till practice reduced sediment yield by almost half. Compared to the conservation tillage practice, no-till practice decreased sediment yield by 25.3% and 9.0% for cotton and grain sorghum, respectively. Using wheat as cover crop for grain sorghum generated the lowest runoff followed by its rotation with canola and cotton regardless of contouring. Converting all the crops in the watershed into Bermuda grass resulted in significant reduction in sediment yield (72.5–96.3%) and surface runoff (6.8–38.5%). The model can be used to provide useful information for stakeholders to prioritize ecologically sound and feasible BMPs at fields that are capable of reducing sediment yield while increasing crop yield.

Estimating cumulative wastewater treatment plant discharge influences on acesulfame and Escherichia coli in a highly impacted watershed with a fully-integrated modelling approach

Wastewater treatment plant (WWTP) discharge is often considered a principal source of surface water contamination. In this study, a three-dimensional fully-integrated groundwater-surface water model was used to simulate the transport characteristics and cumulative loading of an artificial sweetener (acesulfame) and fecal indicator bacteria (Escherichia coli) from WWTPs within a 6800 km² mixed-use, highly impacted watershed in Ontario, Canada. The model, which employed 3.5 × 10⁶ computational nodes and 15 layers, facilitated a comprehensive assessment of groundwater-surface water interactions under high and low flow conditions; processes typically not accounted for in WWTP cumulative effects models. Simulations demonstrate that the model had significant capacity in reproducing the average and transient multi-year groundwater and surface water flow conditions in the watershed. As a proxy human-specific conservative tracer, acesulfame was useful for model validation and to help inform the representation of watershed-scale transport processes. Using a uniform WWTP acesulfame loading rate of 7.14 mg person^-1 day^-1, the general spatial trends and magnitudes of the acesulfame concentration profile along the main river reach within the watershed were reproduced; however, model performance was improved by tuning individual WWTP loading rates. Although instream dilution and groundwater-surface water interactions were strongly dependent on flow conditions, the main reach primarily consisted of groundwater discharge zones. For this reason, hydrodynamic dispersion in the hyporheic zone is shown as the predominant mechanism driving acesulfame into near-stream shallow groundwater, while under high flow conditions, the simulations demonstrate the potential for advective flushing of the shallow groundwater. Regarding the cumulative impact of the WWTPs on E. coli concentrations in the surface flow system, simulated transient E. coli levels downstream of WWTPs in the watershed were significantly lower than observed values, thus highlighting the potential importance of other sources of E. coli in the watershed.

Landscape patterns regulate non-point source nutrient pollution in an agricultural watershed

Landscape pattern critically affects hydrological cycling and the processes of non-point source nutrients pollution. However, little is known about the quantitative relationship between landscape characteristics and the river water quality, and very few studies have addressed the abrupt changes in river water quality with the gradient of landscape metrics. The present study was conducted in a typically intensive agriculture watershed of eastern China including 13 sub-watersheds with different landscape pattern metrics. We adopted redundancy analysis, nonparametric deviance reduction approach, bootstrap sampling and other statistical methods to reveal the quantitative relationship between landscape pattern metrics and water quality variables; then, the phenomenon of an abrupt change in river water quality was explored with different landscape pattern gradients. The results show that landscape pattern significantly affects river water quality, and this effect was quite different in dry and rainy seasons. In the studied watershed, landscape pattern metrics could respectively explain 71.1% and 55.3% of the total variance in the river water quality in dry and rainy seasons. The configuration metrics of landscape pattern had a stronger ability than their composition metrics to explain the variance in water quality. In the dry season, largest patch index of forestland (LPI_for), the most important landscape index, explained 37.9% of the total variance in water quality. While, in the rainy season, the most important landscape index was the largest patch index of farmland (LPI_far), and it could explain 32.4% of that variance. In the studied watershed, when the LPI_for was <35% or LPI_far was over than 50%, water quality would typically change abruptly, at which the probability of a change in river water would suddenly rise substantially.

Split and Merge Watershed: a two-step method for cell segmentation in fluorescence microscopy images

The development of advanced techniques in medical imaging has allowed scanning of the human body to microscopic levels, making research on cell behavior more complex and more in-depth. Recent studies have focused on cellular heterogeneity since cell-to-cell differences are always present in the cell population and this variability contains valuable information. However, identifying each cell is not an easy task because, in the images acquired from the microscope, there are clusters of cells that are touching one another. Therefore, the segmentation stage is a problem of considerable difficulty in cell image processing. Although several methods for cell segmentation are described in the literature, they have drawbacks in terms of over-segmentation, under-segmentation or misidentification. Consequently, our main motivation in studying cell segmentation was to develop a new method to achieve a good tradeoff between accurately identifying all relevant elements and not inserting segmentation artifacts. This article presents a new method for cell segmentation in fluorescence microscopy images. The proposed approach combines the well-known Marker-Controlled Watershed algorithm (MC-Watershed) with a new, two-step method based on Watershed, Split and Merge Watershed (SM-Watershed): in the first step, or split phase, the algorithm identifies the clusters using inherent characteristics of the cell, such as size and convexity, and separates them using watershed. In the second step, or the merge stage, it identifies the over-segmented regions using proper features of the cells and eliminates the divisions. Before applying our two-step method, the input image is first preprocessed, and the MC-Watershed algorithm is used to generate an initial segmented image. However, this initial result may not be suitable for subsequent tasks, such as cell count or feature extraction, because not all cells are separated, and some cells may be mistakenly confused with the background. Thus, our proposal corrects this issue with its two-step process, reaching a high performance, a suitable tradeoff between over-segmentation and under-segmentation and preserving the shape of the cell, without the need of any labeled data or relying on machine learning processes. The latter is advantageous over state-of-the-art techniques that in order to achieve similar results require labeled data, which may not be available for all of the domains. Two cell datasets were used to validate this approach, and the results were compared with other methods in the literature, using traditional metrics and quality visual assessment. We obtained 90% of average visual accuracy and an F-index higher than 80%. This proposal outperforms other techniques for cell separation, achieving an acceptable balance between over-segmentation and under-segmentation, which makes it suitable for several applications in cell identification, such as virus infection analysis, high-content cell screening, drug discovery, and morphometry.

Associating the spatial properties of a watershed with downstream Chl-a concentration using spatial analysis and generalized additive models

We examined the relationship between downstream algal growth potential and the spatial environmental factors of both upland areas and stream buffer zones using spatial analysis and generalized additive models (GAMs). The models employed site-representative concentrations of chlorophyll a (Chl-a) from a total of 688 national water quality monitoring stations and the spatial factors of the corresponding 688 watersheds. The spatial environmental factors included topography, climate, land use class, soil type, and proximity of the monitoring station to the weir downstream and wastewater treatment plants (WWTPs). The explanatory power (adjusted R² or R_adj²) of the models was used to compare different spatial influential scales defined by stream buffers and upstream circular buffers. The spatial environmental factors of the entire watershed area better explained the inter-station variation in Chl-a than did those of the stream buffer and/or upstream circular buffer areas. However, the spatial environmental factors of watershed areas more than 25 km upstream circular buffer zones had only minor influence on the explainability of the models with regards to the inter-station variation in Chl-a levels. Generally, land use patterns were more strongly related to the inter-station Chl-a variation than were point sources of pollutants such as WWTPs. The two most influencing land uses on the inter-station Chl-a variation were urban and agricultural land uses, with varying relative contributions depending on the spatial influential scale: In general relative contribution of urban land use was larger at a larger spatial influential scale while that of agricultural land use showed an opposite trend. In addition, the proximity to the weir downstream explained high Chl-a concentrations in the stream water. Relative importance and causal effects of the spatial environmental variables to instream Chl-a were established based on this national scale correlative analysis, leading to decision-making with the goal of controlling instream algal growth.

Learn to segment single cells with deep distance estimator and deep cell detector

Single cell segmentation is a critical and challenging step in cell imaging analysis. Traditional processing methods require time and labor to manually fine-tune parameters and lack parameter transferability between different situations. Recently, deep convolutional neural networks (CNN) treat segmentation as a pixel-wise classification problem and have become a general and efficient method for image segmentation. However, cell imaging data often possesses characteristics that adversely affect segmentation accuracy: absence of established training datasets, few pixels on cell boundaries, and ubiquitous blurry features. We developed a strategy that combines strengths of CNN and traditional watershed algorithm. First, we trained a CNN to learn Euclidean distance transform (EDT) of the mask corresponding to the input images (deep distance estimator). Next, we trained a faster R-CNN (Region with CNN) to detect individual cells in the EDT image (deep cell detector). Then, the watershed algorithm performed the final segmentation using the outputs of previous two steps. Tests on a library of fluorescence, phase contrast and differential interference contrast (DIC) images showed that both the combined method and various forms of the pixel-wise classification algorithm achieved similar pixel-wise accuracy. However, the combined method achieved significantly higher cell count accuracy than the pixel-wise classification algorithm did, with the latter performing poorly when separating connected cells, especially those connected by blurry boundaries. This difference is most obvious when applied to noisy images of densely packed cells. Furthermore, both deep distance estimator and deep cell detector converge fast and are easy to train.

Landscape structure and land use affect estuarine benthic invertebrates in the Virginian Biogeographic Province, USA

Estuaries are dynamic transition zones linking freshwater and oceanic habitats. These productive ecosystems are threatened by a variety of stressors including human modification of coastal watersheds. In this study, we examined potential linkages between estuarine condition and the watershed using multimodel inference. We examined attributes at the watershed scale as well as those associated with riparian areas but found that they were highly correlated. We also examined whether attributes closer to the estuary were more strongly related to benthic invertebrate condition and found that this was not generally true. In contrast, variability within the estuary strongly impacted model results and suggests that future modeling should incorporate estuarine variability or focus on the individual stations within the estuary. Modeling estuarine condition indicated that inherent landscape structure (e.g., estuarine area, watershed area, watershed:estuary ratio) is important to predicting benthic invertebrate condition and needs to be considered in the context of watershed/ estuary planning and restoration.

Do reductions in agricultural field drainage during the growing season impact bacterial densities and loads in small tile-fed watersheds?

Predicting bacterial levels in watersheds in response to agricultural beneficial management practices (BMPs) requires understanding the germane processes at both the watershed and field scale. Controlling subsurface tile drainage (CTD) is a highly effective BMP at reducing nutrient losses from fields, and watersheds when employed en masse, but little work has been conducted on CTD effects on bacterial loads and densities in a watershed context. This study compared fecal indicator bacteria (FIB) [E. coli, Enterococcus, Fecal coliform, Total coliform, Clostridium perfringens] densities and unit area loads (UAL) from a pair of flat tile-drained watersheds (∼250-467 ha catchment areas) during the growing season over a 10-year monitoring period, using a before-after-control-impact (BACI) design (i.e., test CTD watershed vs. reference uncontrolled tile drainage (UCTD) watershed during a pre CTD intervention period and a CTD-intervention period where the test CTD watershed had CTD deployed on over 80% of the fields). With no tile drainage management, upstream tile drainage to ditches comprised ∼90% of total ditch discharge. We also examined FIB loads from a subset of tile drained fields to determine field load contributions to the watershed drainage ditches. Statistical evidence of a CTD effect on FIB UAL in the surface water systems was not strong; however, there was statistical evidence of increased FIB densities [pronounced when E. coli >200 most probable number (MPN) 100 mL^-1] in the test CTD watershed during the CTD-intervention period. This was likely a result of reduced dilution/flushing in the test CTD watershed ditch due to CTD significantly decreasing the amount of tile drainage water entering the surface water system. Tile E. coli load contributions to the ditches were low; for example, during the 6-yr CTD-intervention period they amounted to on average only ∼3 and ∼9% of the ditch loads for the test CTD and reference UCTD watersheds, respectively. This suggests in-stream, or off-field FIB reservoirs and bacteria mobilization drivers, dominated ditch E. coli loads in the watersheds during the growing season. Overall, this study suggested that decision making regarding deployment of CTD en masse in tile-fed watersheds should consider drainage practice effects on bacterial densities and loads, as well as CTD's documented capacity to boost crop yields and reduce seasonal nutrient pollution.

Temporal fluctuations in young-of-the-year yellow perch mercury bioaccumulation in lakes of northeastern Minnesota

Identifying what determines fish mercury (Hg) bioaccumulation remains a key scientific challenge. While there has been substantial research on spatial variation in fish Hg bioaccumulation, the factors that influence temporal fluctuations in fish Hg have received less attention to date. In this study, we built upon a growing body of research investigating young-of-the-year (YOY) yellow perch Hg bioaccumulation and investigated annual fluctuations in YOY yellow perch Hg in six lakes in northeastern Minnesota over eight years. After accounting for spatial variation between the study lakes, we used model averaging to identify the lake physiochemical and climate factors that best explain temporal variation in fish biomass and fish Hg. Fish biomass of YOY yellow perch had a positive relationship with chlorophyll-α and total Kjeldahl nitrogen and a negative relationship with dissolved iron and dissolved oxygen. There was a positive relationship between annual variation in yellow perch Hg concentration and annual variation in lake total suspended solids, dissolved Fe and pH. Additionally, there was a negative relationship between fish Hg concentration and lake total Kjeldahl nitrogen and growing degree days. Together, our results suggest that annual variation in allochthonous inputs from the watershed, in-lake processes, and climate variables can explain temporal patterns in Hg bioaccumulation and growth biodilution is an important process controlling yellow perch Hg concentrations.

The Influence of Climate and Livestock Reservoirs on Human Cases of Giardiasis

Giardia duodenalis is an intestinal parasite which causes diarrhoeal illness in people. Zoonotic subtypes found in livestock may contribute to human disease occurrence through runoff of manure into multi-use surface water. This study investigated temporal associations among selected environmental variables and G. duodenalis occurrence in livestock reservoirs on human giardiasis incidence using data collected in the Waterloo Health Region, Ontario, Canada. The study objectives were to: (1) evaluate associations between human cases and environmental variables between 1 June 2006 and 31 December 2013, and (2) evaluate associations between human cases, environmental variables and livestock reservoirs using a subset of this time series, with both analyses controlling for seasonal and long-term trends. Human disease incidence exhibited a seasonal trend but no annual trend. A Poisson multivariable regression model identified an inverse association with water level lagged by 1 month (IRR = 0.10, 95% CI 0.01, 0.85, P < 0.05). Case crossover analysis found varying associations between lagged variables including livestock reservoirs (1 week), mean air temperature (3 weeks), river water level (1 week) and flow rate (1 week), and precipitation (4 weeks). This study contributes to our understanding of epidemiologic relationships influencing human giardiasis cases in Ontario, Canada.

Spinal cord watershed infarction: Novel findings on magnetic resonance imaging

Spinal cord watershed ischemia is a rare phenomenon often associated with cardiac arrest, prolonged hypotension, and atherosclerotic disease. It can manifest as central necrosis with peripheral sparing in the transverse axis, and central lesion with rostral and caudal sparing in the longitudinal axis. Few reports provide detailed imaging findings of spinal cord watershed ischemia lesions. We present a patient who experienced watershed infarcts of the brain and spinal cord following prolonged hypotension due to blood loss after an aortic aneurysm repair. The patient experienced loss of neurologic function of the lower extremities and left arm that did not recover following spinal cord ischemia protocol. MRI revealed spinal cord watershed ischemia in both the longitudinal and axial planes with the point of maximal T2 signal hyperintensity in the central cord at T10-T11. Unique findings included zones of central maximal T2 signal hyperintensity with peripheral sparing, and moderate T2 intensity representing partial ischemia between regions of maximal T2 intensity unaffected peripheral regions. Thoracoabdominal computed tomography angiogram revealed extensive intraluminal thrombus and bilateral spinal artery occlusion from T8 to L2 and bilateral severe renal artery stenosis. T7 and L3 spinal arteries were patent. We suspect preexisting atherosclerotic disease played a significant role in the development of widespread watershed lesions following prolonged hypotension and resulted in a clinical and imaging presentation distinct from that seen with isolated anterior spinal artery occlusion. Our unique MRI findings portray a rarely documented pattern of spinal cord watershed ischemia and prompt questions about the role of anatomic idiosyncrasies and preexisting vascular disease in the development of spinal cord watershed ischemia.

Using landscape scenarios to improve local nitrogen management and planning

Scenario-building is a widely used tool to initiate discussions on future land uses. In scenarios possible futures can be explored and peoples' ideas as well as societal trends can be visualized by the use of maps, pictures and figures. With focus on agricultural nitrogen management, and point of departure in the farmers' decisions-regarding fertilizer inputs, crop rotations, land use, and drainage, landscape scenarios are formulated based on local ideas for future nitrogen management and general prospects for local development. The key research question addressed in this paper is how landscape scenarios can guide farmers to improve nitrogen management in smaller catchments dominated by farming. Participatory modelling was used to develop landscape scenarios, depicting the change of nitrogen emission as a result of changes in landscape management and agricultural practices. In the development of the scenarios we used an ArcMap based tool combining statistical data, experimental knowledge, nitrate leaching modelling and input from local stakeholders on biophysical as well as land use and farm management issues. The scenarios presented are the result of a collaborative planning experiment within the frames of the dNmark research alliance on nitrogen. Three different types of scenarios are presented and discussed and their effects in terms of N reduction are estimated. The three scenarios were called: River valley set-aside, constructed wetlands, and land zonation. All the modelled scenarios are estimated to have a positive effect i.e. a reduction of the level of N leached to the root zone. Based on the experience gathered in the project, the feasibility of using scenarios for future environmental planning in the agricultural landscapes is discussed. Further, this is related to the current discussion in Denmark on geographically targeted nitrogen regulation. It is concluded that the co-creative approach to formulation of scenarios can be an effective way of increasing the knowledge and ownership of possible future solutions, however the cost associated with this planning approach is likely to substantially higher that more traditional planning approaches. Consequently, the estimated transactions costs should be weighed against the expected benefits in terms of more successful implementation.

Characterizing interactions of socioeconomic development and environmental impact at a watershed scale

Worldwide socioeconomic development has resulted in huge irretrievable environmental problems in various ecosystems. This study employed seven coastal watersheds in two provinces, Zhejiang and Fujian, China forming a gradient to testify the environmental Kuznets curve (EKC) interactions between socioeconomic development and environmental impact at a watershed scale. Annual socioeconomic indicators, including gross domestic product (GDP) and its components, registered population (agricultural and non-agricultural population), and electricity consumption, and annual discharges of chemical oxygen demand (COD) and ammonium were collected at a county level, and land use pattern to generate watershed level dataset in the period of 2011-2016. Results indicated that non-agricultural GDP per capita of the non-agricultural population and discharge of COD or ammonium per unit of total GDP were top-ranked pair-indicators significantly fitting the EKC model instead of the classic GDP per capita and pollutants. The development of seven selected watersheds have passed the turning point of the EKC and entered impact-reducing development stages along the EKC, i.e., the three Zhejiang watersheds are at the low-impact development stage, the Huotong Stream watershed from Fujian province was at impact-declining development stage right, and other three Fujian watersheds were at medium-impact development stage. In term of the environmental impact indicator, pollutant discharge per unit of total GDP serves as a development impact indictor per se. These findings might provide an EKC-based approach to support and strategize the watershed management for sustainable development in the world.

Linking watershed modeling and bacterial source tracking to better assess E. coli sources

Terrestrial fate and transport processes of E. coli can be complicated by human activities like urbanization or livestock grazing. There is a critical need to address contributing sources of bacterial contamination, properly assess the management of critical sources, and ultimately reduce E. coli concentrations in impaired water bodies. In particular, characterization of wildlife animal contributions and other "background" input sources of microbial pollution are highly uncertain and data are scarce. This study attempts to identify critical sources of E. coli and the efficacy of conservation practices for mitigating E. coli concentrations in the Arroyo Colorado watershed, Texas, using a process-based hydrologic and water quality model. We propose to incorporate a bacterial source tracking assessment into the modeling framework to fill the gap in data on wildlife and human contribution. In addition, other sources identified through a GIS survey, national census, and local expert knowledge were incorporated into the model as E. coli sources. Results suggest that simulated distribution of E. coli sources significantly improved after incorporating this enhanced data on E. coli sources into the model (R² = 0.90) compared to the SWAT result without BST (R² = 0.59). Scenario assessments indicate that wildlife contributions may remain significant despite land use change and urbanization, expected to mostly occur in agricultural and range lands. A combination of nonpoint source management measures, voluntary implementation of advanced treatment by wastewater plants where possible, and installation of aerators in the zone of impairment were demonstrated to be effective measures for restoring the recreation and aquatic life uses of the Arroyo Colorado.

Effect of watershed land use on tributaries' water quality in the east African Highland

A study was carried out on four tributaries of Gilgel Gibe Reservoir to identify water physicochemical characteristics in different land use categories (farmland, naturally vegetated land, and settlement). Water samples were collected from 12 sampling sites along four permanent streams flowing into Gilgel Gibe Reservoir. Data sets were evaluated using nonparametric statistical techniques. Dissolved oxygen (DO), temperature, biochemical oxygen demand (BOD₅), total phosphorus (TP), soluble reactive phosphorus (SRP), total nitrogen (TN), turbidity, total dissolved solids (TDS), and total suspended solids (TSS) spatially showed significant differences in the wet season and DO, temperature, and BOD₅ varied significantly during the dry season. When excluding DO, electrical conductivity (EC), and TP during the wet and dry seasons, the remaining variables showed significant differences. During the wet season, concentrations of most water quality parameters were greatest in influents from agricultural land. Pollution and eutrophication risk is closely associated with drainage from agricultural land, requiring that emphasis and priorities be given to land use management and conservation.

A watershed-scale, citizen science approach to quantifying microplastic concentration in a mixed land-use river

Microplastic (particles < 5 mm) pollution dynamics are well documented in oceans and increasingly studied in freshwater. We used a watershed-scale approach to examine spatial and temporal patterns in microplastic concentrations in the Gallatin River watershed (Montana, USA). At 72 sites, trained volunteers collected ∼1-L grab samples at 4 seasons per year over 2 years (n = 714 samples). Microplastics were found in 57% of the samples (mean = 1.2 particles L^-1). The majority of particles were fibers (80%), 0.1-1.5 mm long. Chemical identification determined 93% of particles measured by μFT-IR were synthetic or semi-synthetic materials. Microplastic concentration differed significantly among dates, but showed no longitudinal pattern or relationship to land-use among subwatersheds. At two sites with gaging stations, microplastic was negatively related to discharge when compared across dates. This suggests stormwater is not a source of microplastic in this watershed, but instead dilutes microplastic inputs from other sources. We conclude that microplastic sources are diverse, and measurements of microplastic deposition, resuspension, and transport may be needed to clarify the role of land-use patterns on microplastic pollution. This large scale, citizen science based approach provides a model for future analysis which can further expand microplastic collection at the watershed scale.