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USGS2025

Latitudinal gradients of snow contamination in the Rocky Mountains associated with anthropogenic sources

Seasonal snow is an important source of drinking water and recreation, and for agriculture in the Rocky Mountain region. Monitoring snow-water quality can inform on the effects to the albedo and energy balance of the snowpack, and the sources of natural and anthropogenic aerosol and gases. This study analyzed metals in the seasonal snowpack from water year (WY) 2018 for 49 sites. Calcium, lanthanum, and cerium concentrations support the importance of mineral dust to the southern Rocky Mountains. Mercury (Hg), zinc (Zn), and cadmium (Cd) concentrations showed a similar spatial pattern to mineral dust, whereas antimony (Sb) concentrations were highest in the northern Rocky Mountains. To assess the relative contributions from dust versus anthropogenic contaminant sources, enrichment factors (EF) were calculated, with values above 10 indicating anthropogenic contamination. For Cd, Hg, Sb, and Zn, EF values exceeded 10 at northern sites. These observations were compared to spatial trends of EF values of Hg from WY2009 to WY2018, regional monitoring networks, and back trajectory analyses. The agreement between these datasets revealed temporally consistent contaminant sources and/or transport processes to the northern Rocky Mountains snowpack. Sources include current and historical mining and smelting in the region. Strategies to limit the emissions of these metals to the Northern Rockies could benefit from focusing on remediation of contaminated sites, and continued monitoring and mitigation of active mining and smelting.

Colorado , Idaho, Montana, New Mexico, Utah, Wyomi↗

USGS2012

A benthic-macroinvertebrate index of biotic integrity and assessment of conditions in selected streams in Chester County, Pennsylvania, 1998-2009

The Stream Conditions of Chester County Biological Monitoring Network (Network) was established by the U.S. Geological Survey and the Chester County Water Resources Authority in 1969. Chester County encompasses 760 square miles in southeastern Pennsylvania and has a rapidly expanding population. Land-use change has occurred in response to this continual growth, as open space, agricultural lands, and wooded lands have been converted to residential and commercial lands. In 1998, the Network was modified to include 18 fixed-location sites and 9 flexible-location sites. Sites were sampled annually in the fall (October-November) during base-flow conditions for water chemistry, instream habitat, and benthic macroinvertebrates. A new set of 9 flexible-location sites was selected each year. From 1998 to 2009, 213 samples were collected from the 18 fixed-location sites and 107 samples were collected from the 84 flexible-location sites. Eighteen flexible-location sites were sampled more than once over the 12-year period; 66 sites were sampled only once. Benthic-macroinvertebrate data from samples collected during 1998-2009 were used to establish the Chester County Index of Biotic Integrity (CC-IBI). The CC-IBI was based on the methods and metrics outlined in the Pennsylvania Department of Environmental Protection's "A Benthic Index of Biotic Integrity for Wadeable Freestone Streams in Pennsylvania." The resulting CC-IBI consists of scores for benthic-macroinvertebrate samples collected from sites in the Network that related to reference conditions in Chester County. Mean CC-IBI scores for 18 fixed-location sites ranged from 37.21 to 88.92. Thirty-nine percent of the 213 samples collected at the 18 fixed-location sites had a CC-IBI score less than 50; 33 percent, 50 to 70; 28 percent, greater than 70. CC-IBI scores from the 107 flexible-location samples ranged from 23.48 to 99.96. Twenty-five percent of the 107 samples collected at the flexible-location sites had a CC-IBI score less than 50; 33 percent, 50 to 70; and 42 percent, greater than 70. Factors that were found to affect CC-IBI scores are nutrient concentrations, habitat conditions, and percent of wooded and urban land use. A positive relation was determined between mean CC-IBI scores and mean total habitat scores for the 18 fixed-location sites. CC-IBI scores were most strongly affected by stream bank vegetative protection, embeddedness, riparian zone width, and sediment deposition. The highest CC-IBI scores were associated with sites that had greater than 28 percent wooded-wetland-water land use, less than 5 percent urban land use, and no municipal wastewater discharges within 10 miles upstream from the sampling site. The lowest CC-IBI scores were associated with sites where urban land use was greater than 15 percent or a municipal wastewater discharge was within 10 miles upstream from the sampling reach. The Mann Kendall test for trends was used to determine trends in CC-IBI scores and concentrations of nitrate, orthophosphate, and chloride for the 18 fixed-location sites. A positive trend in CC-IBI was determined for six sites, and a negative trend was determined for one site. Positive trends in nitrate concentrations were determined for 4 of the 18 fixed-location sites, and a negative trend in orthophosphate concentrations was determined for 1 of the 18 fixed-location sites. Positive trends in chloride concentrations were determined for 16 of the 18 fixed-location sites.

Pennsylvania↗

USGS2024

Co-mast: Harmonized seed production data for woody plants across US long-term research sites

Plants display a range of temporal patterns of inter-annual reproduction, from relatively constant seed production to “mast seeding,” the synchronized and highly variable interannual seed production of plants within a population. Previous efforts have compiled global records of seed production in long-lived plants to gain insight into seed production, forest and animal population dynamics, and the effects of global change on masting. Existing datasets focus on seed production dynamics at the population scale but are limited in their ability to examine community-level mast seeding dynamics across different plant species at the continental scale. We harmonized decades of plant reproduction data for 141 woody plant species across nine Long-Term Ecological Research (LTER) or long-term ecological monitoring sites from a wide range of habitats across the United States. Plant reproduction data are reported annually between 1957 and 2021 and based on either seed traps or seed and/or cone counts on individual trees. A wide range of woody plant species including trees, shrubs, and lianas are represented within sites allowing for direct community-level comparisons among species. We share code for filtering of data that enables the comparison of plot and individual tree data across sites. For each species, we compiled relevant life history attributes (e.g., seed mass, dispersal syndrome, seed longevity, sexual system) that may serve as important predictors of mast seeding in future analyses. To aid in phylogenetically informed analyses, we also share a phylogeny and phylogenetic distance matrix for all species in the dataset. These data can be used to investigate continent-scale ecological properties of seed production, including individual and population variability, synchrony within and across species, and how these properties of seed production vary in relation to plant species traits and environmental conditions. In addition, these data can be used to assess how annual variability in seed production is associated with climate conditions and how that varies across populations, species, and regions. The dataset is released under a CC0 1.0 Universal public domain license.

Ecology↗

USGS2019

Measurement of cyanobacteria bloom magnitude using satellite remote sensing

Cyanobacterial harmful algal blooms (cyanoHABs) are a serious environmental, water quality and public health issue worldwide because of their ability to form dense biomass and produce toxins. Models and algorithms have been developed to detect and quantify cyanoHABs biomass using remotely sensed data but not for quantifying bloom magnitude, information that would guide water quality management decisions. We propose a method to quantify seasonal and annual cyanoHAB magnitude in lakes and reservoirs. The magnitude is the spatio-temporal mean of weekly or biweekly maximum cyanobacteria biomass for the season or year. CyanoHAB biomass is quantified using a standard reflectance spectral shape-based algorithm that uses data from Medium Resolution Imaging Spectrometer (MERIS). We demonstrate the method to quantify annual and seasonal cyanoHAB magnitude in Florida and Ohio respectively during 2003-2011 and rank the lakes based on median magnitude over the study period. The new method can be applied to Ocean Land Color Imager (OLCI) on Sentinel-3 data for assessment of cyanoHABs and the change over time, even with issues such as variable data acquisition frequency or sensor calibration uncertainties between satellites. CyanoHAB magnitude can support monitoring and management decision-making for recreational and drinking water sources.

Florida, Ohio↗

USGS2025

Simulated soundscapes and transfer learning boost the performance of acoustic classifiers under data scarcity

1. The biodiversity crisis necessitates spatially extensive methods to monitor multiple taxonomic groups for evidence of change in response to evolving environmental conditions. Programs that combine passive acoustic monitoring and machine learning are increasingly used to meet this need. These methods require large, annotated datasets, which are time-consuming and expensive to produce, creating potential barriers to adoption in data- and funding-poor regions. Recently released pre-trained avian acoustic classification models provide opportunities to reduce the need for manual labelling and accelerate the development of new acoustic classification algorithms through transfer learning. Transfer learning is a strategy for developing algorithms under data scarcity that uses pre-trained models from related tasks to adapt to new tasks. 2. Our primary objective was to develop a transfer learning strategy using the feature embeddings of a pre-trained avian classification model to train custom acoustic classification models in data-scarce contexts. We used three annotated avian acoustic datasets to test whether transfer learning and soundscape simulation-based data augmentation could substantially reduce the annotated training data necessary to develop performant custom acoustic classifiers. We also conducted a sensitivity analysis for hyperparameter choice and model architecture. We then assessed the generalizability of our strategy to increasingly novel non-avian classification tasks. 3. With as few as two training examples per class, our soundscape simulation data augmentation approach consistently yielded new classifiers with improved performance relative to the pre-trained classification model and transfer learning classifiers trained with other augmentation approaches. Performance increases were evident for three avian test datasets, including single-class and multi-label contexts. We observed that the relative performance among our data augmentation approaches varied for the avian datasets and nearly converged for one dataset when we included more training examples. 4. We demonstrate an efficient approach to developing new acoustic classifiers leveraging open-source sound repositories and pre-trained networks to reduce manual labelling. With very few examples, our soundscape simulation approach to data augmentation yielded classifiers with performance equivalent to those trained with many more examples, showing it is possible to reduce manual label-ling while still achieving high-performance classifiers and, in turn, expanding the potential for passive acoustic monitoring to address rising biodiversity monitoring needs.

Methods in Ecology and Evolution↗

USGS2017

Status and understanding of groundwater quality in the North San Francisco Bay Shallow Aquifer study unit, 2012; California GAMA Priority Basin Project (ver. 1.1, February 2018)

Groundwater quality in the North San Francisco Bay Shallow Aquifer study unit (NSF-SA) was investigated as part of the Priority Basin Project of the California Groundwater Ambient Monitoring and Assessment (GAMA) Program. The study unit is in Marin, Mendocino, Napa, Solano, and Sonoma Counties and included two physiographic study areas: the Valleys and Plains area and the surrounding Highlands area. The NSF-SA focused on groundwater resources used for domestic drinking water supply, which generally correspond to shallower parts of aquifer systems than that of groundwater resources used for public drinking water supply in the same area. The assessments characterized the quality of untreated groundwater, not the quality of drinking water. This study included three components: (1) a status assessment , which characterized the status of the quality of the groundwater resources used for domestic supply for 2012; (2) an understanding assessment , which evaluated the natural and human factors potentially affecting water quality in those resources; and (3) a comparison between the groundwater resources used for domestic supply and those used for public supply. The status assessment was based on data collected from 71 sites sampled by the U.S. Geological Survey for the GAMA Priority Basin Project in 2012. To provide context, concentrations of constituents measured in groundwater were compared to U.S. Environmental Protection Agency (EPA) and California State Water Resources Control Board Division of Drinking Water regulatory and non-regulatory benchmarks for drinking-water quality. The status assessment used a grid-based method to estimate the proportion of the groundwater resources that has concentrations of water-quality constituents approaching or above benchmark concentrations. This method provides statistically unbiased results at the study-area scale and permits comparisons to other GAMA Priority Basin Project study areas. In the NSF-SA study unit as a whole, inorganic constituents with human-health benchmarks were detected at high relative concentrations (RCs) in 27 percent of the shallow aquifer system, and inorganic constituents with secondary maximum contaminant levels (SMCL) were detected at high RCs in 24 percent of the system. The inorganic constituents detected at high RCs were arsenic, boron, fluoride, manganese, nitrate, iron, sulfate, and total dissolved solids (TDS). Organic constituents with human-health benchmarks were detected at high RCs in 1 percent of the shallow aquifer system. Of the 148 organic constituents analyzed, 30 constituents were detected, although only 1, chloroform, had a detection frequency greater than 10 percent. Natural and anthropogenic factors that could affect the groundwater quality were evaluated by using results from statistical testing of associations between constituent concentrations and values of potential explanatory factors. Groundwater age class (modern, mixed, or pre-modern), redox class (oxic or anoxic), aquifer lithology class (metamorphic, sedimentary, or volcanic), and dissolved oxygen concentrations were the explanatory factors that explained distribution patterns of most of the inorganic constituents best. Groundwater classified primarily as pre-modern or mixed in age was associated with higher concentrations of arsenic and fluoride than waters classified as modern. Anoxic or mixed redox conditions were associated with higher concentrations of boron, fluoride, and manganese. Similar patterns of association with explanatory variables were seen for inorganic constituents with aesthetic-based benchmarks detected at high concentrations. Nitrate and perchlorate had higher concentrations in oxic than in the anoxic redox class and were positively correlated with urban land use. The NSF-SA water-quality results were compared to those of the GAMA North San Francisco Bay Public-Supply Aquifer study unit (NSF-PA). The NSF-PA was sampled in 2004 and covers much of the same area as the NSF-SA, but focused on the deeper public-supply aquifer system. The comparison of the NSF-PA to the NSF-SA showed that there were more differences between the Valleys and Plains study areas of the two study units than between the Highlands study areas of the two study units. As expected from the shallower depth of wells, the NSF-SA Valleys and Plains study area had a lesser proportion of pre-modern age groundwater and greater proportion of modern age groundwater than the NSF-PA Valleys and Plains study area. In contrast, well depths and groundwater ages were not significantly different between the two Highlands study areas. Arsenic, manganese, and nitrate were present at high RCs, and perchlorate was detected in greater proportions of the NSF-SA Valleys and Plains study area than the NSF-PA Valleys and Plains study area.

California↗

USGS1994

Relation of stream quality to streamflow, and estimated loads of selected water-quality constituents in the James and Rappahannock rivers near the fall line of Virginia, July 1988 through June 1990

This report presents the results of a study by the U.S. Geological Survey, in cooperation with the Virginia Department of Environmental Quality-- Division of Intergovernmental Coordination to monitor and estimate loads of selected nutrients and suspended solids discharged to Chesapeake Bay from two major tributaries in Virginia. From July 1988 through June 1990, monitoring consisted of collecting depth-integrated, cross-sectional samples from the James and Rappahannock Rivers during storm- flow conditions and at scheduled intervals. Water- quality constituents that were monitored included total suspended solids (residue, total at 105 degrees Celsius), dissolved nitrite plus nitrate, dissolved ammonia, total Kjeldahl nitrogen (ammonia plus organic), total nitrogen, total phosphorus, dissolved orthopohosphorus, total organic carbon, and dissolved silica. Daily mean load estimates of each constituent were computed by month, using a seven-parameter log-linear-regression model that uses variables of time, discharge, and seasonality. Water-quality data and constituent- load estimates are included in the report in tabular and graphic form. The data and load estimates provided in this report will be used to calibrate the computer modeling efforts of the Chesapeake Bay region, evaluate the water quality of the Bay and the major effects on the water quality, and assess the results of best-management practices in Virginia.

Water-Resources Investigations Report↗

USGS2009

Options for national parks and reserves for adapting to climate change

Past and present climate has shaped the valued ecosystems currently protected in parks and reserves, but future climate change will redefine these conditions. Continued conservation as climate changes will require thinking differently about resource management than we have in the past; we present some logical steps and tools for doing so. Three critical tenets underpin future management plans and activities: (1) climate patterns of the past will not be the climate patterns of the future; (2) climate defines the environment and influences future trajectories of the distributions of species and their habitats; (3) specific management actions may help increase the resilience of some natural resources, but fundamental changes in species and their environment may be inevitable. Science-based management will be necessary because past experience may not serve as a guide for novel future conditions. Identifying resources and processes at risk, defining thresholds and reference conditions, and establishing monitoring and assessment programs are among the types of scientific practices needed to support a broadened portfolio of management activities. In addition to the control and hedging management strategies commonly in use today, we recommend adaptive management wherever possible. Adaptive management increases our ability to address the multiple scales at which species and processes function, and increases the speed of knowledge transfer among scientists and managers. Scenario planning provides a broad forward-thinking framework from which the most appropriate management tools can be chosen. The scope of climate change effects will require a shared vision among regional partners. Preparing for and adapting to climate change is as much a cultural and intellectual challenge as an ecological challenge.

Environmental Management↗

USGS1998

Water-quality assessment of part of the upper Mississippi River basin, Minnesota and Wisconsin— Ground-water quality in an urban part of the Twin Cities Metropolitan area, Minnesota, 1996

In the spring of 1996, the Upper Mississippi River Basin Study Unit of the National Water-Quality Assessment Program drilled 30 shallow monitoring wells in a study area characterized by urban residential and commercial land uses. The monitoring wells were installed in sandy river-terrace deposits adjacent to the Mississippi River in Anoka and Hennepin Counties, Minnesota, in areas where urban development primarily occurred during the past 30 years. Analyses of sediments collected during well drilling indicated that at most well sites the aquifer materials had relatively high hydraulic conductivities (ranging from 0.01 to 238 feet per day), and relatively low organic carbon contents (0.10 to 41 grams per kilogram), indicating a high susceptibility to leaching of fertilizers and organic substances used on the land surface. Sediment pH values, which can affect leaching of pesticides, were generally alkaline, ranging from 5.1 to 9.6. Ground-water levels ranged from 2.39 to 23.14 feet below land surface, and indicated that shallow ground water flows primarily toward the Mississippi River. Dissolved-oxygen concentrations in water samples from the wells were generally less than 3 milligrams per liter (mg/L) and specific conductances were generally greater than 600 microsiemens per centimeter. Calcium, magnesium, sodium, bicarbonate, chloride, and sulfate were the primary dissolved constituents in the water samples. Sodium and chloride concentrations were generally greater than commonly reported in the region, probably due to leaching of sodium chloride applied to roads during the winter. Most tracemetal concentrations in ground-water samples were less than 10 micrograms per liter (μg/L), but concentrations of iron and manganese commonly exceeded Secondary Maximum Contaminant Levels set by the U.S. Environmental Protection Agency of 300 and 50 μg/L, respectively. Mineral saturation indices indicated that calcite, dolomite, and gypsum were slightly undersaturated in most water samples, and that quartz, and many oxides and hydroxides of iron and manganese were oversaturated in all of the water samples. Concentrations of nitrate nitrogen, the primary nutrient of concern in ground water, ranged from less than 0.05 to 16 mg/L, with a median concentration of 1.4 mg/L. Dissolved phosphorus concentrations ranged from less than 0.01 to 1.5 mg/L in the water samples, with a median concentration of 0.02 mg/L. Water from one well was oversaturated with respect to hydroxyapatite, a phosphatic mineral used as a fertilizer. Pesticide compounds were detected in water samples from 16 wells, but concentrations of those compounds were less than 1.0 μg/L. Prometon, an herbicide commonly used for right-of-way weed control, was detected in water samples from 10 of the wells. Atrazine, and its metabolite deethylatrazine, were detectable in water samples from 6 and 8 wells, respectively. Atrazine is commonly applied to land planted with corn and is detectable in rainfall and air samples in concentrations of less than 1 ng/L in the urban land use study area. Other detected pesticide compounds, which are used in agriculture, right-of-way weed control, or lawn care included: tebuthiuron, EPTC, p , p '-DDE, metolachlor, simazine, bentazon, and bromacil. Volatile organic compounds were detected in water samples from 26 wells, but the concentrations of most of those compounds were less than 1 μg/L. Carbon disulfide, which may be produced by bacteria in soils, was the most commonly detected volatile organic compound in water samples from the wells. Other detected volatile organic compounds included: methyl chloride, acetone, dichlorofluoromethane, tetrahydrofuran, trichlorofluoromethane, methyl iodide, 1,1-dichloroethane, chloroform, toluene, trichloroethane, trichloroethene, cis -1,2-dichloroethene, methylene chloride, bromodichloromethane, benzene, methylisobutylketone, ethyl ether, and tetrachloroethene. Tritium concentrations, analyzed in water samples from 15 of the 30 wells, indicated that shallow ground water has been recharged since the mid-1950's, and that shallow ground water should be affected by urban development that has taken place over the past 40 years. Land uses in the urban land use study area affected the concentrations of some water-quality constituents. Concentrations of nitrate and chloride, and frequencies of detection of pesticides and of volatile organic compounds, were greater in water samples from the surficial sand and gravel aquifer underlying the urban land use study area than in water samples from similar aquifers from part of the Upper Mississippi River Basin National Water-Quality Assessment study unit. Land uses within 500-meter radii of each well were quantified by digitizing overlays of aerial photographs that were verified and updated in the field. Concentrations of magnesium and sulfate were greater in ground water beneath areas of denser residential development, which may be a natural artifact of better drainage and a deeper water table in those areas. Frequencies of detection of some pesticides and volatile organic compounds were greater in water from wells with greater proportions of industrial and transportation land uses. Ground water in areas with less dense residential development, mostly the more recently-developed areas, tended to have greater concentrations of agricultural herbicides and some nutrients probably a relict of previous agricultural land use.

Minnesota↗

USGS2016

Developing population models with data from marked individuals

Population viability analysis (PVA) is a powerful tool for biodiversity assessments, but its use has been limited because of the requirements for fully specified population models such as demographic structure, density-dependence, environmental stochasticity, and specification of uncertainties. Developing a fully specified population model from commonly available data sources – notably, mark–recapture studies – remains complicated due to lack of practical methods for estimating fecundity, true survival (as opposed to apparent survival), natural temporal variability in both survival and fecundity, density-dependence in the demographic parameters, and uncertainty in model parameters. We present a general method that estimates all the key parameters required to specify a stochastic, matrix-based population model, constructed using a long-term mark–recapture dataset. Unlike standard mark–recapture analyses, our approach provides estimates of true survival rates and fecundities, their respective natural temporal variabilities, and density-dependence functions, making it possible to construct a population model for long-term projection of population dynamics. Furthermore, our method includes a formal quantification of parameter uncertainty for global (multivariate) sensitivity analysis. We apply this approach to 9 bird species and demonstrate the feasibility of using data from the Monitoring Avian Productivity and Survivorship (MAPS) program. Bias-correction factors for raw estimates of survival and fecundity derived from mark–recapture data (apparent survival and juvenile:adult ratio, respectively) were non-negligible, and corrected parameters were generally more biologically reasonable than their uncorrected counterparts. Our method allows the development of fully specified stochastic population models using a single, widely available data source, substantially reducing the barriers that have until now limited the widespread application of PVA. This method is expected to greatly enhance our understanding of the processes underlying population dynamics and our ability to analyze viability and project trends for species of conservation concern.

Biological Conservation↗

USGS2019

A novel method to characterise levels of pharmaceutical pollution in large scale aquatic monitoring campaigns

Much of the current understanding of pharmaceutical pollution in the aquatic environment is based on research conducted in Europe, North America and other select high-income nations. One reason for this geographic disparity of data globally is the high cost and analytical intensity of the research, limiting accessibility to necessary equipment. To reduce the impact of such disparities, we present a novel method to support large-scale monitoring campaigns of pharmaceuticals at different geographical scales. The approach employs the use of a miniaturised sampling and shipping approach with a high throughput and fully validated direct-injection High-Performance Liquid Chromatography-Tandem Mass Spectrometry method for the quantification of 61 active pharmaceutical ingredients (APIs) and their metabolites in tap, surface, wastewater treatment plant (WWTP) influent and WWTP effluent water collected globally. A 7-day simulated shipping and sample stability assessment was undertaken demonstrating no significant degradation over the 1–3 days which is typical for global express shipping. Linearity (r 2 ) was consistently ≥0.93 (median = 0.99 ± 0.02), relative standard deviation of intra- and inter-day repeatability and precision was <20% for 75% and 68% of the determinations made at three concentrations, respectively, and recovery from Liquid Chromatography Mass Spectrometry grade water, tap water, surface water and WWTP effluent were within an acceptable range of 60–130% for 87%, 76%, 77% and 63% of determination made at three concentrations respectively. Limits of detection and quantification were determined in all validated matrices and were consistently in the ng/L level needed for environmentally relevant API research. Independent validation of method results was obtained via an interlaboratory comparison of three surface-water samples and one WWTP effluent sample collected in North Liberty, Iowa (USA). Samples used for the interlaboratory validation were analysed at the University of York Centre of Excellence in Mass Spectrometry (York, UK) and the U.S. Geological Survey National Water Quality Laboratory in Denver (Colorado, USA). These results document the robustness of using this method on a global scale. Such application of this method would essentially eliminate the interlaboratory analytical variability typical of such large-scale datasets where multiple methods were used.

Applied Sciences↗

USGS2016

National Park Service Vegetation Mapping Inventory Program: Natchez Trace Parkway vegetation mapping project report

The National Park Service (NPS) Vegetation Mapping Inventory (VMI) Program is an effort to classify, describe, and map existing vegetation of national park units for the NPS Natural Resource Inventory and Monitoring (I&M) Program. The NPS VMI Program is managed by the NPS I&M Division and provides baseline vegetation information to the NPS Natural Resource I&M Program. The U.S. Geological Survey Upper Midwest Environmental Sciences Center, NatureServe, NPS Gulf Coast Network, and NPS Natchez Trace Parkway (NATR; also referred to as Parkway) have completed vegetation classification and mapping of NATR for the NPS VMI Program. Mappers, ecologists, and botanists collaborated to affirm vegetation types within the U.S. National Vegetation Classification (USNVC) of NATR and to determine how best to map them by using aerial imagery. Analyses of data from 589 vegetation plots had been used to describe an initial 99 USNVC associations in the Parkway; this classification work was completed prior to beginning this NATR vegetation mapping project. Data were collected during this project from another eight quick plots to support new vegetation types not previously identified at the Parkway. Data from 120 verification sites were collected to test the field key to vegetation associations and the application of vegetation associations to a sample set of map polygons. Furthermore, data from 900 accuracy assessment (AA) sites were collected (of which 894 were used to test accuracy of the vegetation map layer). The collective of all these datasets resulted in affirming 122 USNVC associations at NATR. To map the vegetation and open water of NATR, 63 map classes were developed. including the following: 54 map classes represent natural (including ruderal) vegetation types in the USNVC, 5 map classes represent cultural (agricultural and developed) vegetation types in the USNVC, 3 map classes represent nonvegetation open-water bodies (non-USNVC), and 1 map class represents landscapes that had received tornado damage a few months prior to the time of aerial imagery collection. Features were interpreted from viewing 4-band digital aerial imagery by means of digital onscreen three-dimensional stereoscopic workflow systems in geographic information systems. (The aerial imagery was collected during mid-October 2011 for the northern reach of the Parkway and mid-November 2011 for the southern reach of the Parkway to capture peak leaf-phenology of trees.) The interpreted data were digitally and spatially referenced, thus making the spatial-database layers usable in geographic information systems. Polygon units were mapped to either a 0.5 hectare (ha) or 0.25 ha minimum mapping unit, depending on vegetation type or scenario. A geodatabase containing various feature-class layers and tables present the locations of USNVC vegetation types (vegetation map), vegetation plot samples, verification sites, AA sites, project boundary extent, and aerial image centers. The feature-class layer and related tables for the vegetation map provide 13,529 polygons of detailed attribute data covering 21,655.5 ha, with an average polygon size of 1.6 ha; the vegetation map coincides closely with the administrative boundary for NATR. Summary reports generated from the vegetation map layer of the map classes representing USNVC natural (including ruderal) vegetation types apply to 12,648 polygons (93.5% of polygons) and cover 18,542.7 ha (85.6%) of the map extent for NATR. The map layer indicates the Parkway to be 70.5% forest and woodland (15,258.7 ha), 0.3% shrubland (63.0 ha), and 14.9% herbaceous cover (3,221.0 ha). Map classes representing USNVC cultural types apply to 678 polygons (5.0% of polygons) and cover 2,413.9 ha (11.1%) of the map extent.

Natural Resource Report↗

USGS2023

Stream restoration milestones: Monitoring scales determine successes and failures

Urban stream restoration is growing globally, but there is much to learn from successes, failures, and evaluating tradeoffs in restoration practices. Significant time and resources have been invested towards restoring the structure and function of urban ecosystems and understanding and slowing the drivers of degradation. However, the rapid pace of urbanization and its effects on urban waters present an ever-growing challenge to environmental managers and restoration practitioners when identifying and prioritizing effective strategies for restoration and monitoring outcomes. Here, we synthesize major findings and papers originating from the 5th Symposium on Urbanization and Stream Ecology (SUSE5) and propose a new concept for monitoring restoration based on lessons learned. Efforts from SUSE5 showed that urban disturbances and restoration activities have strong localized impacts that can be challenging to detect and disentangle across broader watershed scales and longitudinal flowpaths. Most urban stream restoration projects are monitored at only one or a few locations that do not capture significant variability across stream reaches and longer flowpaths. Based on knowledge from SUSE5, we present a new concept called ‘restoration milestones.’ The restoration milestones concept proposes that the scale of stream monitoring over space and time can influence whether a stream restoration project is considered a success or failure. Therefore, answers to questions regarding restoration effectiveness and durability can be affected by spatial and temporal monitoring scales. Setting realistic restoration milestones involves establishing monitoring strategies that account for spatial and temporal variability. Tracking restoration performance through time across stream reaches along longitudinal flowpaths could aid in more accurately assessing project performance. We explore applications for evaluating restoration milestones along longitudinal stream flowpaths including: (1) identifying target areas of improvement along drainage networks, (2) accurately accounting for tradeoffs in habitat, protection of infrastructure, and water quality along flowpaths, and (3) detecting how far downstream the effects of stream restoration and stormwater management can be propagated. Monitoring across different spatial and temporal scales is an overlooked but critical factor in determining restoration success. Additionally, the scale of the restoration project itself can determine the type and magnitude of improvements. Expectations for what a restoration project can accomplish in terms of water quality improvements should be calibrated to the project’s spatial scale and evolution over time. Longitudinal studies of stream restoration help identify successes and failures along flowpaths.

Urban Ecosystems↗

USGS2012

Modeling of land use and reservoir effects on nonpoint source pollution in a highly agricultural basin

Nonpoint source (NPS) pollution is tightly linked to land use activities that determine the sources and magnitudes of pollutant loadings to stream water. The pollutant loads may also be alleviated within reservoirs because of the physical interception resulting from changed hydrological regimes and other biochemical processes. It is important but challenging to assess the NPS pollution processes with human effects due to the measurement limitations. The objective of this study is to evaluate the effects of human activities such as land uses and reservoir operation on the hydrological and NPS pollution processes in a highly agricultural area-the Iowa River Basin-using the Soil and Water Assessment Tool (SWAT). The evaluation of model performance at multiple sites reveals that SWAT can consistently simulate the daily streamflow, and monthly/annual sediment and nutrient loads (nitrate nitrogen and mineral phosphorus) in the basin. We also used the calibrated model to estimate the trap efficiencies of sediment (~78%) and nutrients (~30%) in the Coralville Reservoir within the basin. These non-negligible effects emphasize the significance of incorporating the sediment and nutrient removal mechanisms into watershed system studies. The spatial quantification of the critical NPS pollution loads can help identify hot-spot areas that are likely locations for the best management practices.

Iowa↗

USGS2019

Explaining harvests of wild-harvested herbaceous plants: American ginseng as a case study

Wild-harvested plants face increasing demand globally. As in many fisheries, monitoring the effect of harvesting on the size and trajectory of resource stocks presents many challenges given often limited data from disparate sources. Here we analyze American ginseng ( Panax quinquefolius L.) harvests from 18 states in the eastern U.S. 1978–2014 to infer temporal patterns and evidence of population declines, and we test the effects of local environmental and socioeconomic factors on ginseng harvesting at the county level 2000–2014. Despite rising prices, annual wild ginseng harvests decreased from a high point in the late 1980s to early 1990s, then, in most, increased after 2005 or 2010 - suggesting range-wide overexploitation notwithstanding federal regulations that, since 1999, restrict minimum harvest age. County-level harvest rates increased with available habitat, road density, poverty and unemployment, but decreased when public land formed a large proportion of county area. Harvests were largest in the Southern Appalachian region. Poverty and accessibility were strongly related to high levels of harvesting. A key implication is that to conserve valuable wild native plant products while also improving local livelihoods, wild cultivation and good stewardship practices must be strongly promoted. Our approach to assessing the condition of wild populations offers a broad template that could be adapted to other wild-harvested plants.

Biological Conservation↗

USGS2007

Can modeling improve estimation of desert tortoise population densities?

The federally listed desert tortoise (Gopherus agassizii) is currently monitored using distance sampling to estimate population densities. Distance sampling, as with many other techniques for estimating population density, assumes that it is possible to quantify the proportion of animals available to be counted in any census. Because desert tortoises spend much of their life in burrows, and the proportion of tortoises in burrows at any time can be extremely variable, this assumption is difficult to meet. This proportion of animals available to be counted is used as a correction factor (g0) in distance sampling and has been estimated from daily censuses of small populations of tortoises (6-12 individuals). These censuses are costly and produce imprecise estimates of g0 due to small sample sizes. We used data on tortoise activity from a large (N = 150) experimental population to model activity as a function of the biophysical attributes of the environment, but these models did not improve the precision of estimates from the focal populations. Thus, to evaluate how much of the variance in tortoise activity is apparently not predictable, we assessed whether activity on any particular day can predict activity on subsequent days with essentially identical environmental conditions. Tortoise activity was only weakly correlated on consecutive days, indicating that behavior was not repeatable or consistent among days with similar physical environments. ?? 2007 by the Ecological Society of America.

Ecological Applications↗

USGS2019

Let’s agree to disagree: Comparing auto-acoustic identification programs for northeastern bats

With the declines in abundance and changing distribution of white-nose syndrome–affected bat species, increased reliance on acoustic monitoring is now the new “normal.” As such, the ability to accurately identify individual bat species with acoustic identification programs has become increasingly important. We assessed rates of disagreement between the three U.S. Fish and Wildlife Service–approved acoustic identification software programs (Kaleidoscope Pro 4.2.0, Echoclass 3.1, and Bat Call Identification 2.7d) and manual visual identification using acoustic data collected during summers from 2003 to 2017 at Fort Drum, New York. We assessed the percentage of agreement between programs through pairwise comparisons on a total nightly count level, individual file level (e.g., individual echolocation pass call file), and grouped maximum likelihood estimate level (e.g., probability values that a species is misclassified as present when in fact it is absent) using preplanned contrasts, Akaike Information Criterion, and annual confusion matrices. Interprogram agreement on an individual file level was low, as measured by Cohen's Kappa (0.2–0.6). However, site-night level pairwise comparative analysis indicated that program agreement was higher (40–90%) using single season occupancy metrics. In comparing analytical outcomes of our different datasets (i.e., how comparable programs and visual identification are regarding the relationship between environmental conditions and bat activity), we determined high levels of congruency in the relative rankings of the model as well as the relative level of support for each individual model. This indicated that among individual software packages, when analyzing bat calls, there was consistent ecological inference beyond the file-by-file level at the scales used by managers. Depending on objectives, we believe our results can help users choose automated software and maximum likelihood estimate thresholds more appropriate for their needs and allow for better cross-comparison of studies using different automated acoustic software.

Journal of Fish and Wildlife Management↗

USGS2001

Ecotoxicology of Wild Mammals

An international group of 32 scientists has critically reviewed the scientific literature on exposure and effects of environmental contaminants in wild mammals. The underlying theme of this text is encompassed by the following four questions: What exactly do we know about environmental contaminants in mammals? What are the commonalities and differences between mammal orders/species in the effects that contaminants have? How and to what degree of accuracy can we predict the adverse effects of environmental contaminants on mammalian wildlife? How significant are contaminant insults compared with other density-independent and -dependent factors such as habitat loss, climatic factors and disease? The book is organized three topical sections including introductory chapters that provide a background on environmental contaminants and the mammalian orders, eight taxonomic chapters discussing all aspects of the exposure to and effects of contaminants in mammalian orders, and four thematic chapters that review and discuss generic issues including biomarkers, prediction and extrapolation of exposure and effects, hazard and risk assessment, and the relative significance of contaminants on mammals compared with other commonly encountered stressors. A final a summary chapter identifies phylogenetic trends, critical data gaps, and overarching research needs. Although the absolute number of toxicological studies in domesticated and wild mammals eclipses that wildlife species, a detailed examination of our knowledge base reveals that information for 'wild' birds is actually greater than that for 'wild' mammals. Of the various mammalian taxa, ecotoxicological data is most noticeably lacking for marsupials and monotremes. In contrast, rodents (comprising 43% of all mammal species) have been studied extensively, despite evidence of their tolerance to some organochlorine compounds, rodenticides, and even radionuclides. Mammalian species at greatest risk of exposure include those that consume a high percentage of their body weight on a daily basis. Aquatic mammals tend to bioaccumulate tremendous burdens of lipophilic contaminants, although storage in their fat depots may actually limit toxicity. Carnivores appear to be more sensitive to adverse effects of environmental contaminants than herbivores. Remarkably few of the thousands of compounds manufactured worldwide have been toxicologically evaluated in wild mammals, and concentrations of even fewer have been monitored in tissues.

Ecological & Environmental Toxicology Series.↗