Microbial source tracking (MST) in Chattahoochee River National Recreation Area: Seasonal and precipitation trends in MST marker concentrations, and associations with E. coli levels, pathogenic marker presence, and land use.
Ontology highlight
ABSTRACT:
SUBMITTER: McKee BA
PROVIDER: S-EPMC8188702 | biostudies-literature | 2020 Mar
REPOSITORIES: biostudies-literature
Publications
Microbial source tracking (MST) in Chattahoochee River National Recreation Area: Seasonal and precipitation trends in MST marker concentrations, and associations with E. coli levels, pathogenic marker presence, and land use.
McKee By Anna BA Molina Marirosa M Cyterski Mike M Couch Ann A
Water research 20191226
Escherichia coli levels in recreational waters are often used to predict when fecal-associated pathogen levels are a human health risk. The reach of the Chattahoochee River that flows through the Chattahoochee River National Recreation Area (CRNRA), located in the Atlanta-metropolitan area, is a popular recreation area that frequently exceeds the U.S. Environmental Protection Agency beach action value (BAV) for E. coli. A BacteriALERT program has been implemented to provide real-time E. coli est ...[more]
Similar Datasets
Project description:This study provides extended seasonal predictions for the Upper Colorado River Basin (UCRB) precipitation in boreal spring using an artificial neural network (ANN) model and a stepwise linear regression model, respectively. Sea surface temperature (SST) predictors are developed taking advantage of the correlation between the precipitation and SST over three ocean basins. The extratropical North Pacific has a higher correlation with the UCRB spring precipitation than the tropical Pacific and North Atlantic. For the ANN model, the Pearson correlation coefficient between the observed and predicted precipitation exceeds 0.45 (p-value < 0.01) for a lead time of 12 months. The mean absolute percentage error (MAPE) is below 20% and the Heidke skill score (HSS) is above 50%. Such long-lead prediction skill is probably due to the UCRB soil moisture bridging the SST and precipitation. The stepwise linear regression model shows similar prediction skills to those of ANN. Both models show prediction skills superior to those of an autoregression model (correlation < 0.10) that represents the baseline prediction skill and those of three of the North American Multi-Model Ensemble (NMME) forecast models. The three NMME models exhibit different skills in predicting the precipitation, with the best skills of the correlation ~ 0.40, MAPE < 25%, and HSS > 40% for lead times less than 8 months. This study highlights the advantage of oceanic climate signals in extended seasonal predictions for the UCRB spring precipitation and supports the improvement of the UCRB streamflow prediction and related water resource decisions.Supplementary informationThe online version contains supplementary material available at 10.1007/s00382-022-06422-x.
| S-EPMC10011310 | biostudies-literature
Project description:BackgroundThe river Göta Älv is a source of freshwater for 0.7 million swedes. The river is subject to contamination from sewer systems discharge and runoff from agricultural lands. Climate models projects an increase in precipitation and heavy rainfall in this region. This study aimed to determine how daily rainfall causes variation in indicators of pathogen loads, to increase knowledge of variations in river water quality and discuss implications for risk management.MethodsData covering 7 years of daily monitoring of river water turbidity and concentrations of E. coli, Clostridium and coliforms were obtained, and their short-term variations in relation with precipitation were analyzed with time series regression and non-linear distributed lag models. We studied how precipitation effects varied with season and compared different weather stations for predictive ability.ResultsGenerally, the lowest raw water quality occurs 2 days after rainfall, with poor raw water quality continuing for several more days. A rainfall event of >15 mm/24-h (local 95 percentile) was associated with a three-fold higher concentration of E. coli and 30% higher turbidity levels (lag 2). Rainfall was associated with exponential increases in concentrations of indicator bacteria while the effect on turbidity attenuated with very heavy rainfall. Clear associations were also observed between consecutive days of wet weather and decreased water quality. The precipitation effect on increased levels of indicator bacteria was significant in all seasons.ConclusionsRainfall elevates microbial risks year-round in this river and freshwater source and acts as the main driver of varying water quality. Heavy rainfall appears to be a better predictor of fecal pollution than water turbidity. An increase of wet weather and extreme events with climate change will lower river water quality even more, indicating greater challenges for drinking water producers, and suggesting better control of sources of pollution.
| S-EPMC4038599 | biostudies-literature
Project description:Faecal pollution in stormwater, wastewater and direct run-off can carry zoonotic pathogens to streams, rivers and the ocean, reduce water quality, and affect both recreational and commercial fishing areas of the coastal ocean. Typically, the closure of beaches and commercial fishing areas is governed by the testing for the presence of faecal bacteria, which requires an 18-24 h period for sample incubation. As water quality can change during this testing period, the need for accurate and timely predictions of coastal water quality has become acute. In this study, we: (i) examine the relationship between water quality, precipitation and river discharge at several locations within the Gulf of Maine, and (ii) use multiple linear regression models based on readily obtainable hydrometeorological measurements to predict water quality events at five coastal locations. Analysis of a 12 year dataset revealed that high river discharge and/or precipitation events can lead to reduced water quality; however, the use of only these two parameters to predict water quality can result in a number of errors. Analysis of a higher frequency, 2 year study using multiple linear regression models revealed that precipitation, salinity, river discharge, winds, seasonality and coastal circulation correlate with variations in water quality. Although there has been extensive development of regression models for freshwater, this is one of the first attempts to create a mechanistic model to predict water quality in coastal marine waters. Model performance is similar to that of efforts in other regions, which have incorporated models into water resource managers' decisions, indicating that the use of a mechanistic model in coastal Maine is feasible.
| S-EPMC4632571 | biostudies-literature
Project description:The long-term viability of Pacific salmon stocks and the fisheries they support are threatened if large numbers die prematurely en-route to spawning grounds. Physiological profiles that were correlated with the fate of wild sockeye salmon during river migration were discovered using functional genomics studies on biopsied tissues. Three independent biotelemetry studies tracked the biopsied fish after tagging in the marine environment over 200 km from the Fraser River, in the lower river 69 km from the river mouth and at the spawning grounds. Salmon carrying the poor performance (unhealthy) profile in the ocean exhibited a 4-times lower probability of arriving to spawning grounds than those with a healthy genomic signature, although generally migrated into the river and to the spawning grounds faster. A related unhealthy signature observed in the river was associated with a 30% reduction in survival to spawning grounds in one of the three stocks tested. At spawning grounds, the same poor performance signature was associated with twice the pre-spawning mortality compared with healthy fish. Functional analysis revealed that the unhealthy signature, which intensified during migration to spawning grounds, was consistent with an intracellular pathogenic infection, likely a virus. These results are the first to suggest a pathogen present in salmon in the marine environment could be a major source of mortality during migration and spawning in the river. This series are gill expression profiles from the study of fish sampled and tagged in the lower river and tracked as they swam towards the spawning grounds.
2010-12-31 | GSE22177 | GEO
Project description:Impoundment is among the most common hydrologic alterations with impacts on aquatic ecosystems that can include effects on mercury (Hg) cycling. However, landscape-scale differences in Hg bioaccumulation between reservoirs and other habitats are not well characterized nor are the processes driving these differences. We examined total Hg (THg) concentrations of Smallmouth Bass (Micropterus dolomieu) collected from reservoir, tailrace, and free-flowing reaches along an 863 km segment of the Snake River, USA, a semiarid river with 22 impoundments along its course. Across three size-classes (putative 1-year-old, first reproductive, and harvestable sized fish), THg concentrations in reservoirs and tailraces averaged 76% higher than those in free-flowing segments. Among reservoirs, THg concentrations were highest in reservoirs with inconsistent stratification patterns, 47% higher than annually stratified, and 144% higher than unstratified reservoirs. Fish THg concentrations in tailraces immediately downstream of stratified reservoirs were higher than those below unstratified (38-130%) or inconsistently stratified (32-79%) reservoirs. Stratification regimes influenced the exceedance of fish and human health benchmarks, with 52-80% of fish from stratifying reservoirs and downstream tailraces exceeding a human consumption benchmark, compared to 6-17% where stratification did not occur. These findings suggest that impoundment and stratification play important roles in determining the patterns of Hg exposure risk across the landscape.
| S-EPMC10734268 | biostudies-literature
Project description:The long-term viability of Pacific salmon stocks and the fisheries they support are threatened if large numbers die prematurely en-route to spawning grounds. Physiological profiles that were correlated with the fate of wild sockeye salmon during river migration were discovered using functional genomics studies on biopsied tissues. Three independent biotelemetry studies tracked the biopsied fish after tagging in the marine environment over 200 km from the Fraser River, in the lower river 69 km from the river mouth and at the spawning grounds. Salmon carrying the poor performance (unhealthy) profile in the ocean exhibited a 4-times lower probability of arriving to spawning grounds than those with a healthy genomic signature, although generally migrated into the river and to the spawning grounds faster. A related unhealthy signature observed in the river was associated with a 30% reduction in survival to spawning grounds in one of the three stocks tested. At spawning grounds, the same poor performance signature was associated with twice the pre-spawning mortality compared with healthy fish. Functional analysis revealed that the unhealthy signature, which intensified during migration to spawning grounds, was consistent with an intracellular pathogenic infection, likely a virus. These results are the first to suggest a pathogen present in salmon in the marine environment could be a major source of mortality during migration and spawning in the river. This series are gill expression profiles from the study of fish sampled and tagged in the lower river and tracked as they swam towards the spawning grounds. Fish were caught in seine nets, gastrically implanted with radio transmitters, and biopsy sampled for blood, gill, muscle, and fin. Individual fish were tracked by receivers placed throughout the Fraser River watershed to identify and fate (i.e. the location of the receiver that last detected the fish). Targeted stocks of interest were genetically identified. Gene expression was profiled in gill tissue, a critical respiratory and ionoregulatory organ that is highly responsive to stress, chemical exposure and disease. Gene expression was assayed on the GRASP salmonid 16K cDNA microarray.
2010-12-31 | E-GEOD-22177 | biostudies-arrayexpress
Project description:The assessment and prediction of regional water quality are fundamental inputs to environmental planning and watershed ecological management. This paper explored spatiotemporal changes in the correlation of water quality parameters (WQPs) and land-use types (LUTs) in a reticular river network area. Water samples of 44 sampling sites were collected every quarter from 2016 to 2018 and evaluated for dissolved oxygen (DO), total phosphorus (TP), ammonia nitrogen (NH3-N), and permanganate index (CODMn). A redundancy analysis (RDA) and stepwise multiple linear regression (SMLR) were applied to analyze the land-use type impacts on seasonal WQPs at five buffer scales (100, 200, 500, 800, and 1000 m). The Kruskal-Wallis test results revealed significant seasonal differences in NH3-N, TP, CODMn, and DO. The area percentages of farmland, water area and built-up land in the study area were 38.96%, 22.75% and16.20%, respectively, for a combined total area percentage of nearly 80%. Our study showed that orchard land had an especially favorable influence on WQPs. Land-use type impacts on WQPs were more significant during the dry season than the wet season. The total variation explained by LUTs regarding WQPs at the 1 km buffer scale was slightly stronger than at smaller buffer scales. Built-up land had a negative effect on WQPs, but orchard and forest-grassland had a positive effect on WQPs. The effects of water area and farmland on WQPs were complex on different buffer scales. These findings are helpful for improving regional water resource management and environmental planning.
| S-EPMC7787537 | biostudies-literature
Project description:The seasonal and spatial eukaryotic phytoplankton composition in the Fenhe River was investigated based on the 18S rDNA V4 region. The relationship between phytoplankton functional groups and environmental factors was explored to effectively capture the responses of these taxa to environmental gradients and their effects on ecosystem function. Our results indicated that the Chlorophyta and Bacillariophyta had higher relative abundance than other taxa, and their diversity and richness indices in spring were higher than those in other seasons. The linear discriminant analysis effect size (LEfSe) analyses detected that the potential seasonal biomarkers included Desmodesmus, Cyclotella, Pseudoschroederia, Discostella, Scenedesmus, Monoraphidium, and Nannochloropsis; the spatial biomarkers included Amphora, Neochloris, Hindakia, Pseudomuriella, Coccomyxa, Chloroidium, Scherffelia, Chromochloris, and Scotinosphaera. The systemic evolution and distribution characteristics of the first 50 representative sequences showed that the dominant genus included Desmodesmus in spring, Pseudopediastrum in summer, Mychonastes in autumn, and Monoraphidium in winter. Main seasonal variation of phytoplankton functional groups was as follows: spring (J + F + C + X1) → summer (J + F + X1 + X2) → autumn (J + F + X1 + C) → winter (X1 + J + B + X2). Pearson correlation, redundancy analysis, and variance partitioning analysis showed temperature and phosphate were the determining factors causing the changes of phytoplankton functional groups and community composition in the Fenhe River.
| S-EPMC8633359 | biostudies-literature
Project description:The Chi and Mun River Basins, the primary tributary of the Mekong River Basin in Thailand, is undergoing significant land use changes that impact water quality. Understanding the relationship between land use and water quality is crucial for effective river basin management, providing insights applicable to global water systems. While past studies have examined water quality in the Mekong River Basin, research specifically focusing on the Chi-Mun River Basin remains limited. This study analyzes the spatial and temporal effects of land use changes on water quality from 2007 to 2021 using land use change estimation, 11 water quality parameters, and redundancy analysis (RDA). Water samples were collected in January, March, May, and August across multiple years. Seasonal variations were assessed, with dry season samples from January and March and wet season samples from May and August. Key findings include: (1) pH, Biochemical Oxygen Demand, Total Coliform Bacteria, Fecal Coliform Bacteria, Total Phosphorus, Nitrate Nitrogen, Ammonia-Nitrogen, and Suspended Solids increased during the wet season, while (2) Dissolved Oxygen, Electrical Conductivity, and Water Quality Index were higher in the dry season. (3) Land use changes had a greater impact on water quality during the wet season, driven by increased runoff from expanding urban and agricultural areas and declining paddy and forest cover. (4) Forests and aquatic areas improved water quality, while agricultural and urban expansion contributed to its deterioration. These findings underscore the need for sustainable land management strategies to balance regional development with ecological conservation in the Chi-Mun River Basin.
| S-EPMC11868589 | biostudies-literature
Project description:Anthropogenic land use and land cover change is primarily represented in climate model simulations through prescribed transitions from natural vegetation to cropland or pasture. However, recent studies have demonstrated that land management practices, especially irrigation, have distinct climate impacts. Here we disentangle the seasonal climate impacts of land cover change and irrigation across areas of high agricultural intensity using climate simulations with three different land surface scenarios: (1) natural vegetation cover/no irrigation, (2) year 2000 crop cover/no irrigation, and (3) year 2000 crop cover and irrigation rates. We find that irrigation substantially amplifies land cover-induced climate impacts but has opposing effects across certain regions. Irrigation mostly causes surface cooling, which substantially amplifies land cover change-induced cooling in most regions except over Central, West, and South Asia, where it reverses land cover change-induced warming. Despite increases in net surface radiation in some regions, this cooling is associated with enhancement of latent relative to sensible heat fluxes by irrigation. Similarly, irrigation substantially enhances the wetting influence of land cover change over several regions including West Asia and the Mediterranean. The most notable contrasting impacts of these forcings on precipitation occur over South Asia, where irrigation offsets the wetting influence of land cover during the monsoon season. Differential changes in regional circulations and moist static energy induced by these forcings contribute to their precipitation impacts and are associated with differential changes in surface and tropospheric temperature gradients and moisture availability. These results emphasize the importance of including irrigation forcing to evaluate the combined impacts of land surface changes for attributing historical climatic changes and managing future impacts.
| S-EPMC6360509 | biostudies-literature