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At least 343 records · Page 19Linked to original sources
USGS2024

Remote sensing for monitoring mine lands and recovery efforts

Under the Bipartisan Infrastructure Law Ecosystem Restoration Program, the U.S. Department of the Interior has invested in assessing and recovering degraded ecosystems to promote healthy human communities and wildlife habitats. One priority established by the program is the need to address degraded ecosystems associated with mine lands, including active, inactive, and abandoned mines. Mine lands occur in every State of the United States and present a range of environmental hazards and safety risks to human communities and wildlife habitats. However, limited information compiled across the United States exists on the whereabouts of mining activities and their potential environmental effects on landscapes. Remote sensing is the process of acquiring information about the landscape from ground platforms, aircraft, or satellites to assess surface characteristics such as topography, vegetation, and soil properties and can therefore provide important cost-effective methods for identifying mining sites and assessing their environmental effects. Based on a literature review of remote sensing applications that assessed land health conditions and monitoring of mine lands, this report highlights important approaches, capabilities, considerations, and case studies using a breadth of techniques. The report identifies considerations for setting appropriate vegetation recovery targets and demonstrates how remote sensing can inform the prioritization, recovery design, and long-term assessments of recovery to help support decision makers and land managers. Applications of remote sensing to mine recovery will be most effective when recovery targets are clearly defined and quantifiable from data collected before mining activity, per the Surface Mining Control and Reclamation Act of 1977 and similar laws. Additionally, the collected data would need to be accessible and maintained in databases for baseline references used to establish these recovery targets.

continental United States↗
USGS2004

Predicting water quality by relating secchi-disk transparency and chlorophyll a measurements to satellite imagery for Michigan inland lakes, August 2002

Inland lakes are an important economic and environmental resource for Michigan. The U.S. Geological Survey and the Michigan Department of Environmental Quality have been cooperatively monitoring the quality of selected lakes in Michigan through the Lake Water Quality Assessment program. Through this program, approximately 730 of Michigan's 11,000 inland lakes will be monitored once during this 15-year study. Targeted lakes will be sampled during spring turnover and again in late summer to characterize water quality. Because more extensive and more frequent sampling is not economically feasible in the Lake Water Quality Assessment program, the U.S. Geological Survey and Michigan Department of Environmental Quality investigate the use of satellite imagery as a means of estimating water quality in unsampled lakes. Satellite imagery has been successfully used in Minnesota, Wisconsin, and elsewhere to compute the trophic state of inland lakes from predicted secchi-disk measurements. Previous attempts of this kind in Michigan resulted in a poorer fit between observed and predicted data than was found for Minnesota or Wisconsin. This study tested whether estimates could be improved by using atmospherically corrected satellite imagery, whether a more appropriate regression model could be obtained for Michigan, and whether chlorophyll a concentrations could be reliably predicted from satellite imagery in order to compute trophic state of inland lakes. Although the atmospheric-correction did not significantly improve estimates of lake-water quality, a new regression equation was identified that consistently yielded better results than an equation obtained from the literature. A stepwise regression was used to determine an equation that accurately predicts chlorophyll a concentrations in northern Lower Michigan.

Michigan↗
USGS2016

Response and resilience of Spartina alterniflora to sudden dieback

We measured an array of biophysical and spectral variables to evaluate the response and recovery of Spartina alterniflora to a sudden dieback event in spring and summer 2004 within a low marsh in coastal Virginia, USA. S. alterniflora is a foundation species, whose loss decreases ecosystem services and potentiates ecosystem state change. Long-term records of the potential environmental drivers of dieback such as precipitation and tidal inundation did not evidence any particular anomalies, although Hurricane Isabel in fall 2003 may have been related to dieback. Transects were established across the interface between the dieback area and apparently healthy areas of marsh. Plant condition was classified based on ground cover within transects as dieback, intermediate and healthy. Numerous characteristics of S. alterniflora culms within each condition class were assessed including biomass, morphology and spectral attributes associated with photosynthetic pigments. Plants demonstrated evidence of stress in 2004 and 2005 beyond areas of obvious dieback and resilience at a multi-year scale. Resilience of the plants was evident in recovery of ground cover and biomass largely within 3 y, although a small remnant of dieback persisted for 8 y. Culms surviving within the dieback and areas of intermediate impact had modified morphological traits and spectral response that reflected stress. These morphometric and spectral differences among plant cover condition classes serve as guidelines for monitoring of dieback initiation, effects and subsequent recovery. Although a number of environmental and biotic parameters were assessed relative to causation, the reason for this particular dieback remains largely unknown, however.

Virginia↗
USGS2008

Integrated monitoring and information systems for managing aquatic invasive species in a changing climate

Changes in temperature, precipitation, and other climatic drivers and sea-level rise will affect populations of existing native and non-native aquatic species and the vulnerability of aquatic environments to new invasions. Monitoring surveys provide the foundation for assessing the combined effects of climate change and invasions by providing baseline biotic and environmental conditions, although the utility of a survey depends on whether the results are quantitative or qualitative, and other design considerations. The results from a variety of monitoring programs in the United States are available in integrated biological information systems, although many include only non-native species, not native species. Besides including natives, we suggest these systems could be improved through the development of standardized methods that capture habitat and physiological requirements and link regional and national biological databases into distributed Web portals that allow drawing information from multiple sources. Combining the outputs from these biological information systems with environmental data would allow the development of ecological-niche models that predict the potential distribution or abundance of native and non-native species on the basis of current environmental conditions. Environmental projections from climate models can be used in these niche models to project changes in species distributions or abundances under altered climatic conditions and to identify potential high-risk invaders. There are, however, a number of challenges, such as uncertainties associated with projections from climate and niche models and difficulty in integrating data with different temporal and spatial granularity. Even with these uncertainties, integration of biological and environmental information systems, niche models, and climate projections would improve management of aquatic ecosystems under the dual threats of biotic invasions and climate change

Conservation Biology↗
USGS2018

Laboratory evaluation of the Sea-Bird Scientific HydroCycle-PO4 phosphate sensor

Sea-Bird Scientific’s HydroCycle-PO 4 phosphate sensor is a single-analyte wet-chemistry sensor designed for in situ environmental monitoring. The unit was evaluated at the U.S. Geological Survey Hydrologic Instrumentation Facility to assess the accuracy of the sensor in solutions with known phosphorous concentration and to test the effects of chromophoric (colored) dissolved organic matter (CDOM) and natural water matrixes on sensor accuracy. Accuracy was tested with three standards: 0.110, 0.174, and 0.260 milligram per liter, as phosphorous (mg/L as P). The 0.110- and 0.260-mg/L standards were made from a dilution of a National Institute of Standards and Technology-traceable phosphate-phosphorous standard with Type I deionized water (DIW). Average measured phosphate concentrations of the tested standards (0.110, 0.174, and 0.260 mg/L as P) in DIW were 0.132, 0.181, and 0.310 mg/L as P, for differences of 20, 4, and 19 percent, respectively. Measured phosphate concentration of a tested standard was biased by the addition of tea water filtered through a 0.45-micrometer pore size filter (filtered tea water [FTW]) simulating the effect of CDOM. An aliquot of the filtered tea solution was sent to a certified environmental laboratory, which reported a less than reporting level (<0.004 mg/L as P) phosphate concentration. True color of the FTW was measured at 380 platinum-cobalt units by using Standard Methods 8025. For this FTW test, the measured phosphate concentration for the clear 0.260 mg/L as P standard averaged 0.366 mg/L as P. This concentration increased to an average of 0.653 mg/L as P with the addition of 10 percent FTW, and to an average of 0.859 mg/L as P with the addition of 20 percent FTW. These test results indicate a positive bias of up to 40 percent of the concentrations of the measured phosphate concentrations when CDOM is present and indicate a proportional increase in an apparent concentration of phosphorus instrument response as CDOM concentration increases.

Open-File Report↗
USGS2003

A strategy for mapping mid-scale existing vegetation in support of national fire fuel assessment

Geospatial distribution of natural vegetation is among the very important environmental parameters required for applications ranging from global climate change to monitoring of natural hazards, monitoring of ecosystem vitality, and fire management practices. Increasingly sophisticated applications require vegetation datasets to cover large areas at a suitable scale and provide sufficiently detailed information. In this paper, we describe a research effort to develop a remote sensing methodology capable of producing 30-meter resolution, wall-to-wall coverage of existing vegetation types and structure variables in support of a multi-agency fire fuels and fire risks assessment project. Success of this remote sensing research effort is dependent on improved sensor and data qualities, a thorough understanding of regional and local vegetation ecology, successful integration of remote sensing with a large amount of field plot data, and flexible mapping algorithms. Preliminary results produced in the Wasatch Range and Uinta Mountains of central Utah include 28 vegetation types with an overall accuracy of 60% (average by life forms), percent canopy density (sub-pixel density) of forest, shrub, and herbaceous cover (correlation coefficient of 89, 60, and 55% respectively), and average top canopy height of forest, shrub, and herbaceous cover (correlation coefficient of 73, 50, 20% respectively). Techniques to improve the first-round results are discussed, including refinements of mapping models and use of relevant environmental gradients and potential vegetation classification associated with actual vegetation types.

Conference Paper↗
USGS2025

Real-time oil spill concentration assessment through fluorescence imaging and deep learning

Oil spills may pose severe ecological and socioeconomic threats, necessitating rapid and accurate environmental assessment. Traditional assessment methods used to determine the extent of a spill including gas chromatography-mass spectrometry, satellite imaging, and visual surveys, are often time-consuming, expensive, and limited by weather conditions or sampling constraints. Furthermore, these methods frequently struggle to provide real-time data crucial for prompt decision-making during spill emergencies. This study addresses these limitations by combining fluorescence imaging, deep learning, a mobile application, and a data management system for automated and real-time oil spill assessment. Our approach leverages a convolutional neural network architecture for feature extraction coupled with a custom regression model, trained and evaluated on a self-curated comprehensive dataset of 1,530 fluorescence images from two distinct oil types, a napthalenic crude oil and an aromatic-napthalenic crude oil, at concentrations ranging from 0 to 500 mg/L. The proposed approach demonstrates superior performance compared to both traditional machine learning models and more complex deep learning architectures, achieving an R² score of 0.9958 and RMSE of 9.28. The application enables rapid, cost-effective field measurements with robust data tracking and analysis capabilities. This research advances oil spill monitoring technology with a scalable solution that balances accuracy, speed, and accessibility for real-time environmental assessment and emergency response.

Journal of Hazardous Materials↗
USGS2013

Hydrologic monitoring and selected hydrologic and environmental studies by the U.S. Geological Survey in Georgia, 2011–2013

This compendium of papers describes results of hydrologic monitoring and hydrologic and environmental studies completed by the U.S. Geological Survey (USGS) in Georgia during 2011–2013. The USGS addresses a wide variety of water issues in the State of Georgia working with local, State, and Federal partners. As the primary Federal science agency for water resource information, the USGS monitors the quantity and quality of water in the Nation’s rivers and aquifers, assesses the sources and fate of contaminants in aquatic systems, collects and analyzes data on aquatic ecosystems, develops tools to improve the application of hydrologic information, and ensures that its information and tools are available to all potential users. During 2011–2013, the USGS continued a long-term program of monitoring stream and groundwater resources, including flow, water quality, and water use. In addition, a variety of hydrologic and environmental studies were completed to assess water availability, hydrologic hazards, and the impact of development on water resources. Information on USGS activities in Georgia is available online at http://ga.water.usgs.gov/ .

Georgia↗
USGS2024

Water-quality monitoring strategy for Mount Hope Bay and the Taunton River Estuary, southeastern Massachusetts

The U.S. Geological Survey, in cooperation with the Massachusetts Department of Environmental Protection (MassDEP), began a study in 2018 to develop a water-quality monitoring strategy (WQMS) for Mount Hope Bay and the Taunton River Estuary in southeastern Massachusetts. MassDEP is interested in water-quality data in Mount Hope Bay and the Taunton River Estuary to characterize current water-quality conditions, assess nutrient-related effects, and capture conditions before and after planned upgrades to wastewater treatment facilities. The WQMS provides an overview of the environmental setting of Mount Hope Bay and the Taunton River Estuary and of dissolved oxygen and nutrient-related water-quality issues, reviews historical and existing monitoring data, and provides recommendations for future monitoring designed to meet five MassDEP management objectives: (1) support MassDEP’s review of coastal and marine dissolved oxygen criteria, (2) assess conditions within MassDEP waterbody assessment units in Mount Hope Bay and the Taunton River Estuary with respect to selected criteria in the Massachusetts Surface Water Quality Standards, (3) assess conditions along the freshwater/saltwater interface (salt wedge) of the Taunton River Estuary and delineate the boundary between the freshwater and saltwater waterbody assessment units, (4) estimate data requirements needed to determine nutrient loads flowing into Mount Hope Bay and the Taunton River Estuary, and (5) evaluate data requirements needed to support hydrodynamic and water-quality models for Mount Hope Bay and the Taunton River Estuary. This WQMS may be used by MassDEP to develop a statewide approach for monitoring estuaries in Massachusetts.

Massachusetts↗
USGS2013

Louisiana Barrier Island Comprehensive Monitoring (BICM) Program Summary Report: Data and Analyses 2006 through 2010

The Barrier Island Comprehensive Monitoring (BICM) program was implemented under the Louisiana Coastal Area Science and Technology (LCA S&T) office as a component of the System Wide Assessment and Monitoring (SWAMP) program. The BICM project was developed by the State of Louisiana (Coastal Protection Restoration Authority [CPRA], formerly Department of Natural Resources [DNR]) to complement other Louisiana coastal monitoring programs such as the Coastwide Reference Monitoring System-Wetlands (CRMS-Wetlands) and was a collaborative research effort by CPRA, University of New Orleans (UNO), and the U.S. Geological Survey (USGS). The goal of the BICM program was to provide long-term data on the barrier islands of Louisiana that could be used to plan, design, evaluate, and maintain current and future barrier-island restoration projects. The BICM program used both historical and newly acquired (2006 to 2010) data to assess and monitor changes in the aerial and subaqueous extent of islands, habitat types, sediment texture and geotechnical properties, environmental processes, and vegetation composition. BICM datasets included aerial still and video photography (multiple time series) for shoreline positions, habitat mapping, and land loss; light detection and ranging (lidar) surveys for topographic elevations; single-beam and swath bathymetry; and sediment grab samples. Products produced using BICM data and analyses included (but were not limited to) storm-impact assessments, rate of shoreline and bathymetric change, shoreline-erosion and accretion maps, high-resolution elevation maps, coastal-shoreline and barrier-island habitat-classification maps, and coastal surficial-sediment characterization maps. Discussions in this report summarize the extensive data-collection efforts and present brief interpretive analyses for four coastal Louisiana geographic regions. In addition, several coastal-wide and topical themes were selected that integrate the data and analyses within a broader coastal context: (1) barrier-shoreline evolution driven by rapid relative sea-level rise (RSLR), (2) hurricane impacts to the Chandeleur Islands and likelihood of island recovery, (3) impact of tropical storms on barrier shorelines, (4) Barataria Bay tidal-inlet management, and (5) habitat changes related to RSLR. The final theme addresses potential future goals of the BICM program, including rotational annual to semi-decadal monitoring, proposed new-data collection, how to incorporate technological advances with previous data-collection and monitoring protocols, and standardizing methods and quality-control assessments for continued coastal monitoring and restoration.

Louisiana↗
USGS2021

An attention U-Net model for detection of fine-scale hydrologic streamlines

Surface water is an irreplaceable resource for human survival and environmental sustainability. Accurate, finely detailed cartographic representations of hydrologic streamlines are critically important in various scientific domains, such as assessing the quantity and quality of present and future water resources, modeling climate changes, evaluating agricultural suitability, mapping flood inundation, and monitoring environmental changes. Conventional approaches to detecting such streamlines cannot adequately incorporate information from the complex three-dimensional (3D) environment of streams and land surface features. Such information is vital to accurately delineate streamlines. In recent years, high accuracy lidar data has become increasingly available for deriving both 3D information and terrestrial surface reflectance. This study develops an attention U-net model to take advantage of high-accuracy lidar data for finely detailed streamline detection and evaluates model results against a baseline of multiple traditional machine learning methods. The evaluation shows that the attention U-net model outperforms the best baseline machine learning method by an average F1 score of 11.25% and achieves significantly better smoothness and connectivity between classified streamline channels. These findings suggest that our deep learning approach can harness high-accuracy lidar data for fine-scale hydrologic streamline detection, and in turn produce desirable benefits for many scientific domains.

North Carolina↗
USGS1982

Diagnosis of anticholinesterase poisoning in birds: Effects of environmental temperature and underfeeding on cholinesterase activity

Brain cholinesterase (ChE) activity has been used extensively to monitor exposure to organophosphorus (OP) and carbamate (CB) insecticides in wild birds. A series of factorial experiments was conducted to assess the extent to which noncontaminant-related environmental conditions might affect brain ChE activity and thereby confound the diagnosis of OP and CB intoxication. Underfeeding (restricting intake to 50% of control for 21 d or fasting for 1–3 d) or exposure to elevated temperature (36 ± 1°C for 1 d) caused only slightreductions (10–17%)in brain AChE activity in adult male Japanese quail ( Coturnix coturnix japonica ). This degree of “reduction” in brain AChE activity is considerably less than the 50% “inhibition” criterion employed in the diagnosis of insecticide-induced mortality, but nevertheless approaches the 20% “inhibition” level used as a conservative estimate of sublethal exposure to a known insecticide application.

Environmental Toxicology and Chemistry↗
USGS2016

Physical condition and stress levels during early development reflect feeding rates and predict pre- and post-fledging survival in a nearshore seabird

The effects of acute environmental stressors on reproduction in wildlife are often difficult to measure because of the labour and disturbance involved in collecting accurate reproductive data. Stress hormones represent a promising option for assessing the effects of environmental perturbations on altricial young; however, it is necessary first to establish how stress levels are affected by environmental conditions during development and whether elevated stress results in reduced survival and recruitment rates. In birds, the stress hormone corticosterone is deposited in feathers during the entire period of feather growth, making it an integrated measure of background stress levels during development. We tested the utility of feather corticosterone levels in 3- to 4-week-old nestling brown pelicans ( Pelecanus occidentalis ) for predicting survival rates at both the individual and colony levels. We also assessed the relationship of feather corticosterone to nestling body condition and rates of energy delivery to nestlings. Chicks with higher body condition and lower corticosterone levels were more likely to fledge and to be resighted after fledging, whereas those with lower body condition and higher corticosterone levels were less likely to fledge or be resighted after fledging. Feather corticosterone was also associated with intracolony differences in survival between ground and elevated nest sites. Colony-wide, mean feather corticosterone predicted nest productivity, chick survival and post-fledging dispersal more effectively than did body condition, although these relationships were strongest before fledglings dispersed away from the colony. Both reproductive success and nestling corticosterone were strongly related to nutritional conditions, particularly meal delivery rates. We conclude that feather corticosterone is a powerful predictor of reproductive success and could provide a useful metric for rapidly assessing the effects of changes in environmental conditions, provided pre-existing baseline variation is monitored and understood.

Gulf of Mexico↗
USGS2025

The continued decline of the Palila (Loxioides bailleui) on Mauna Kea, Island of Hawaiʻi

Palila ( Loxioides bailleui ) are critically endangered Hawaiian honeycreepers specializing on māmane ( Sophora chrysophylla ) seeds and restricted to Mauna Kea volcano on the Island of Hawaiʻi. Recently, the population was estimated to decline by 89% between 1998 and 2021, despite decades of ungulate removal, fence construction, māmane regeneration, fire suppression, and predator control. To inform managers with the most recent update on the status and trends of the Palila population, we analyzed annual bird survey data collected using point-transect distance sampling since 1998, including new annual survey data from 2022, 2023, and 2024. Prior to analysis, we predicted the population trajectory would change between 2021 and 2024 because of continued management actions promoting habitat recovery. We used distance sampling, log-linear regression, and state-space modeling to produce the new estimates and analyze trends across the time series. The 2022 population estimate was 367 to 742 birds (95% confidence interval; point estimate: 545), the lowest in recorded history. The 2023 and 2024 estimates of 374 to 842 birds (point estimate: 596) and 412 to 970 birds (point estimate: 666) were the second and third lowest in our time series, respectively. Our estimates for years before 2022 show population fluctuations between 4000 to 6800 birds from 1998 to 2005, then a steep decline through 2010. For the next decade, abundance fluctuated around 1000 birds, before declining again in 2021 to less than 700 birds. From 1998 to 2024, the population declined by more than 90%, or 205 birds per year, with 100% statistical support for an overall downward trend, despite significant management efforts and research. The greatest threats facing the Palila, if familiar, are not being eliminated swiftly enough to promote their recovery. The currently small and range-limited population is vulnerable to future climate-related events such as drought and fire. Continued monitoring can help to assess the response of Palila to adaptive management actions and changing environmental conditions.

Hawaii↗
USGS2011

Effects of acid deposition on ecosystems: Advances in the state of the science

Chapter 2 focused on the environmental results of the ARP, presenting data from national monitoring networks on SO2 and NOx emissions, air quality, atmospheric deposition, surface water chemistry, and visibility. This chapter expands on this information by examining the most recent research into how ecosystems respond to acid deposition, especially the processes that control the recovery of ecosystems as acid deposition decreases. In Chapter 2, two general trends were discussed regarding the current recovery status of affected ecosystems: (1) these ecosystems are trending generally towards recovery, but improvements in ecosystem condition shown by surface water chemistry monitoring data thus far have been less than the improvements in deposition; and (2) ecosystem impacts and trends vary widely by geographic region, but the evidence of improvement is strongest and most evident in the Northeast. These trends are not uniform across the United States, however, and in some regions (e.g., central Appalachian Mountain region), trends in improved water quality are generally not evident. Despite the strong link in many areas between reduced emissions and reduced acidity of atmospheric deposition, the link is less clear between reduced acidity and recovery of the biological communities that live in aquatic and terrestrial ecosystems that have experienced deleterious effects from acid deposition. The recovery of these communities is proceeding at a slower pace than, for example, the improvements in stream and lake ANC would indicate. The goal of this chapter is to synthesize the science in a weightof-evidence manner to provide policy makers with tangible evidence and likely causative factors regarding ecosystem status and recovery patterns to date. This chapter serves as an update to the 2005 NAPAP RTC (NSTC, 2005), with an emphasis on scientific studies and monitoring since 2003, which was the last year for consideration of research results in the 2005 report. Several issues pertinent to ecosystem response to emission controls and acid deposition are receiving increasing attention in the scientific literature and will be discussed in this chapter, including the (1) observed delay in ecosystem recovery in the eastern United States, even with decreases in emissions and deposition over the past 30 years; (2) emerging ecosystem impacts of nitrogen deposition in the western United States; (3) the application of critical deposition loads as a tool for scientists to better inform air quality policies; (4) the role of changes in climate and the carbon cycle as factors that affect the response of ecosystems to acid deposition; and (5) the interaction of multiple pollutants in ecosystems. Throughout this chapter, the value of long-term environmental monitoring data in informing air quality policy will be highlighted, including the limitations of assessing the current status of some ecosystem indicators for which continuous, long-term data are lacking.

Report↗
USGS2020

Trends in oyster populations in the northeastern Gulf of Mexico: An assessment of river discharge and fishing effects over time and space

Within the Big Bend region of the northeastern Gulf of Mexico, one of the least developed coastlines in the continental USA, intertidal and subtidal populations of eastern oyster Crassostrea virginica (hereafter referred to as “oyster”) are a critical ecosystem and important economic constituent. We assessed trends in intertidal oyster populations, river discharge, and commercial fishing activity in the Suwannee River estuary within the Big Bend region using fisheries‐independent data from irregular monitoring efforts and publicly available environmental data. We used generalized linear models to evaluate counts of oysters from line‐transect surveys over time and space. We assessed model performance using simulation to understand potential bias and then evaluated whether these counts were related to freshwater inputs from the Suwannee River and commercial oyster fishing effort and landings at different time lags. We found that intertidal oyster counts have declined over time and that most of these declines are found in inshore intertidal oyster bars, which are becoming degraded. We also found a significant relationship between oyster counts and a 1‐year lag on mean daily Suwannee River discharge, but including commercial fishery trips or landings did not improve model fit. It is unclear whether declines in intertidal oyster bars are offset by formation of new oyster reefs elsewhere. These results quantify rapid declines in intertidal oyster reefs in a region of coastline with high conservation value that can be used to inform ongoing and proposed restoration projects in the region.

Florida↗
USGS2008

Davis Pond freshwater prediversion biomonitoring study: freshwater fisheries and eagles

In January 2001, the construction of the Davis Pond freshwater diversion structure was completed by the U.S. Army Corps of Engineers. The diversion of freshwater from the Mississippi River is intended to mitigate saltwater intrusion from the Gulf of Mexico and to lessen the concomitant loss of wetland areas. In addition to the freshwater inflow, Barataria Bay basin would receive nutrients, increased flows of sediments, and water-borne and sediment-bound compounds. The purpose of this biomonitoring study was, therefore, to serve as a baseline for prediversion concentrations of selected contaminants in bald eagle ( Haliaeetus leucocephalus ) nestlings (hereafter referred to as eaglets), representative freshwater fish, and bivalves. Samples were collected from January through June 2001. Two similarly designed postdiversion studies, as described in the biological monitoring program, are planned. Active bald eagle nests targeted for sampling eaglet blood (n = 6) were generally located southwest and south of the diversion structure. The designated sites for aquatic animal sampling were at Lake Salvador, at Lake Cataouatche, at Bayou Couba, and along the Mississippi River. Aquatic animals representative of eagle prey were collected. Fish were from three different trophic levels and have varying feeding strategies and life histories. These included herbivorous striped mullet ( Mugil cephalus ), omnivorous blue catfish ( Ictalurus furcatus ), and carnivorous largemouth bass ( Micropterus salmoides ). Three individuals per species were collected at each of the four sampling sites. Freshwater Atlantic rangia clams ( Rangia cuneata ) were collected at the downstream marsh sites, and zebra mussels ( Dreissena spp.) were collected on the Mississippi River. The U.S. Geological Survey (USGS) Biomonitoring of Environmental Status and Trends (BEST) protocols served as guides for fish sampling and health assessments. Fish are useful for monitoring aquatic ecosystems because they accumulate pesticides and other contaminants. Biomarker data on individual fish, generated at the USGS National Wetlands Research Center (Lafayette, La.), included percent white blood cells in whole blood, spleen weight to body weight ratio, liver weight to body weight ratio, condition factor, splenic macrophage aggregates, and liver microsomal 7-ethoxyresorufin-o-deethylase (EROD) activity. Fish age was estimated by comparing total lengths with values from the same species in the Southeast United States as determined from the literature. Contaminant analyses were coordinated by the U.S. Fish and Wildlife Service (USFWS) Analytical Control Facility (Laurel, Md.), where residues of organochlorine (OC) pesticides, total polychlorinated biphenyls (PCBs), polycyclic aromatic hydrocarbons (PAHs), aliphatic hydrocarbons (AHs), and trace elements were determined. The organic contaminant data were generated at the Mississippi State University Chemical Lab (Mississippi State, Miss.), and the inorganic contaminant data were generated by the Texas A&M University Geochemical and Environmental Research Group (College Station, Tex.). Statistical tests were performed to assess relationships among contaminants, fish age, fish species, and collection sites. Trends in interspecific differences among fish in concentrations of contaminants were noted. Striped mullet (hereafter mullet) frequently displayed the highest chemical concentrations. Levels of contaminants were generally higher in samples obtained from the Mississippi River than in those collected from the diversion area and were higher in mussels and clams (hereafter bivalves) than in fish. Because the Mississippi River sampling site for mullet and largemouth bass was downriver of the structure and south of New Orleans and the catfish site was upriver, the downriver data may not be directly reflective of the results from the receiving waters at the Davis Pond structure. Compared to the Caernarvon freshwater prediversion study in 1990 that assessed possible influx of contaminants with the freshwater diversion, contaminant levels in fishes and bivalves in this study were generally lower, yet three nontoxic inorganic elements in Davis Pond fish samples exhibited ranges of concentrations that were more than two times higher than did those from Caernarvon. Levels in bivalves were different between diversions but about equal in the numbers of trace elements showing high levels per location. Contaminant values were compared to those listed in various literature and agency sources, both regional and national, including the National Contaminant Biomonitoring Program (NCBP), in which the 85th percentile and above represents what is considered to be an elevated contaminant concentration and cause for concern. Generally, bivalves were at the high end of their ranges for both organic and inorganic contaminants. In this study, OCs were detectable in 67 percent of fish from the Mississippi River site, ranging from 0.15 to 1.09 μg/g wet weight (ww) or fresh weight (fw), and in 11 percent of the fish from the marsh sites, ranging from 0.06 to 0.612 μg/g ww. Bivalves from the Mississippi River had OC levels of 0.096 μg/g ww, whereas none were detectable in bivalves at the marsh sites. In this study, p,p ’-dichlorodiphenyldichloroethylene ( p,p’ -DDE) (a biodegradation product of DDT [dichlorodiphenyl trichloroethane]) and total PCBs were the most frequently detected OCs and were primarily from the Mississippi River. For total OC content, using adjusted least squares means, some significant interactions were noted between fish species and sites. PAHs were detected in aquatic animals at all sites (range of 0.017–17.534 μg/g ww), as were AHs (range of 0.423–4.549 μg/g ww); the highest levels of PAHs and AHs were found in bivalves from the Mississippi River. When analysis of variance (α = 0.05) was performed with data from aquatic animals, there were only two significant relationships between PAHs, AHs, and OCs between species, site, and age or the interaction among these variables. There was an interaction between fish species and n-decane (an AH) in that mullet and largemouth bass had significantly higher levels than did catfish ( P = 0.0175). When general linear means were used to investigate associations of inorganic contaminants among fish species, site, and age or any interactions among these variables, no significant results were noted for arsenic, cadmium, lead, beryllium, boron, molybdenum, or nickel. The range of mercury in fish in this study was 0.04–0.14 μg/g ww (0.14– 0.48 μg/g dry weight [dw]), with the most elevated levels detected in predatory largemouth bass at the sampling point farthest downstream from the structure and within the marsh area. Mercury was positively correlated with fish age ( P = 0.0152), where levels were estimated to increase 0.0253 parts per million (ppm) dw per year. In the Mississippi River, catfish showed significantly higher levels of mercury than did mullet or largemouth bass ( P = 0.00167). Among fish species, mullet displayed the highest levels in fish of aluminum, barium, manganese, and iron, all considered to have low toxicity in hydrologic systems. An interaction between fish and site was seen with aluminum ( P = 0.0031), where concentrations in mullet were significantly higher in the Mississippi River than at the other sites, as was also seen with barium ( P = 0.0009), chromium ( P = <0.0001), manganese ( P = 0.0004), strontium ( P = 0.0074), vanadium ( P = 0.0156), and zinc ( P = 0.0059). For iron ( P = 0.0.0001), mullet and largemouth bass at both the Mississippi River and Lake Salvador showed higher levels than did catfish, and these two species showed higher levels at two of the four sites. An interaction between fish and site was also seen with chromium ( P = <0.0001) in that concentrations in mullet were significantly higher in the Mississippi River than at the other sites, as was also seen with strontium ( P = 0.0074), vanadium ( P = 0.0156), and zinc ( P = 0.0059), metals for which deleterious effects have been demonstrated in other ecosystems. The NCBP program lists the 85th percentile for zinc at 34.2 μg/g fw (117.9 μg/g dw). In the Davis Pond prediversion biomonitoring study (hereafter the current study), one fish (MUL31RIVER, fish ID 8) showed values higher than that (125.4 μg/g dw or 37.54 μg/g ww), and the Mississippi River bivalve sample (MUSSRIVER) had a value of 140 μg/g dw (41.2 μg/g ww). In the current study, approximately 86 percent of the fish had measurable selenium levels, yet none reached the 85th percentile. The 85th percentile for selenium from the NCBP was 0.73 μg/g ww. Significantly higher levels of selenium were seen in mullet than in largemouth bass and catfish ( P = 0.0023). The NCBP 85th percentile for lead is 0.22 μg/g ww (0.76 μg/g dw). In the current study, the range of concentrations of lead was as much as 18.3 ppm dw (MUL31RIVER, fish ID 8), with the three most elevated values (range of 3.46–5.31 μg/g ww) coming from mullet from the Mississippi River. Biomarker data are measurable and directly reflect the condition of the animal, and measuring more than one biomarker in an individual increases confidence in health assessments. In the current study, biomarkers included macrophage aggregates (MAs), liver (hepatosomatic index [HSI]) and spleen (splenosomatic index [SSI]) weight to body weight ratios, percent white blood cells (WBCs) in whole blood, and condition factor. Few significant differences were noted with any of the biomarkers between sites, and there were no relationships between species and sites. For improved use of biomarker assessments, an increase in fish sample size would be useful for postdiversion sampling, as would comparisons of fish of the same sex and reproductive condition. During the current study, success for eagle nests in the diversion area and reference sites was similar as determined by numbers of nestlings fledged. When temperatures were below average during winter 2000, nests in both regions similarly failed. At each nest, the primary evidence of food items was small mammals. Eaglets (n = 6) generally appeared healthy, and whole blood concentrations of organic contaminants exceeded detection limits with three incidences of p,p’ -DDE (0.002–0.006 μg/L ww) and one incidence of oxychlordane (0.002 μg/L ww). The levels of p,p’ -DDE were well below those that have been inversely correlated with productivity and success rates of nesting bald eagles on a regional scale. The low values found in the whole blood samples for OC pesticides and PCBs were even lower when corrected for plasma volume. Aluminum values were 3.66 and 5.75 μg/L in two samples, zinc ranged from 5.21 to 6.77 μg/L ww in six samples, and silicon ranged from 1.7 to 4.6 μg/L in four samples. Selenium was detectable in each bird with the range at 0.332–0.566 μg/L ww, and strontium ranged from 0.0581 to 0.0975 μg/L ww. Mercury was detectable in blood samples from each bird and ranged from 0.0254 to 0.0845 μg/L ww, whereas lead was detectable in four samples and ranged from 0.0042 to 0.0136 μg/L ww. Although no detectable levels of total PCBs were found (also correlated with decreased reproductive productivity), 70 percent of the aquatic animals from the Mississippi River contained total PCBs (range 0.13–0.79 μg/L), whereas only about 7 percent of the aquatic animals sampled from the marsh area contained PCBs. Suggestions for postdiversion sampling include lowering the analytical detection limit for some metals, sampling aquatic animals over the course of a single season, obtaining a higher sample number of mature fish of one species (for example, blue catfish) within a range of total lengths for biomarker analyses, obtaining otoliths for estimating fish ages, assessing dioxins in eaglet blood, examining triazines in water, and obtaining all Mississippi River fish samples as close to the Davis Pond structure intake as possible. Because contaminants found in blood of eaglets reflect their prey species and because of the contaminant levels found in fish in the current study, eaglets may not be consuming primarily these species; therefore, obtaining juvenile nutria ( Myocastor coypus ) or turtle species for contaminant analyses might be considered, as well as collecting greater blood volume and using plasma to measure OCs and PCBs. Data obtained postdiversion will be compared with prediversion data to monitor changes.

Louisiana↗
USGS2014

Assessing and managing freshwater ecosystems vulnerable to global change

Freshwater ecosystems are important for global biodiversity and provide essential ecosystem services. There is consensus in the scientific literature that freshwater ecosystems are vulnerable to the impacts of environmental change, which may trigger irreversible regime shifts upon which biodiversity and ecosystem services may be lost. There are profound uncertainties regarding the management and assessment of the vulnerability of freshwater ecosystems to environmental change. Quantitative approaches are needed to reduce this uncertainty. We describe available statistical and modeling approaches along with case studies that demonstrate how resilience theory can be applied to aid decision-making in natural resources management. We highlight especially how long-term monitoring efforts combined with ecological theory can provide a novel nexus between ecological impact assessment and management, and the quantification of systemic vulnerability and thus the resilience of ecosystems to environmental change.

Florida Everglades↗