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USGS2015

Selection of vegetation types and density of bison in an arid ecosystem

Understanding species habitat selection and factors that drive selection are key components for conservation. We report the first resource selection functions (RSFs) for bison inhabiting an arid ecosystem and use them with density estimates of bison to estimate the number of bison that could be supported if the bison range were expanded to federal lands in the San Luis Valley of Colorado. We derived RSFs for vegetation types using locations of plains bison collected weekly over 3 years from 2005 to 2007. Bison selected for wet or mesic grassland habitats in all seasons. Wetland selection by bison was predicted to be 18 times greater than that of rabbitbrush vegetation, the reference category, and selection of meadows was predicted to be 11 times greater than that of the rabbitbrush type. Willow-dominated plant communities were strongly avoided. Cottonwood communities were also avoided, with the exception of some moderate levels of selection in fall. The willow and cottonwood communities have an understory with low biomass of herbaceous species and low productivity in this arid system. Based on the RSFs we predicted that in the San Luis Valley of Colorado up to 2,379 bison could be supported in similar habitats under Fish and Wildlife Service (FWS) jurisdiction, and up to 759 bison could be supported on adjacent National Park Service (NPS) land. This modeling framework provides a conservation tool for the restoration of bison to their historical habitats, and has utility for application to other terrestrial species where assumptions are met.

Colorado↗

USGS2021

Golden eagle population surveys in the vicinity of the Altamont Pass Wind Resource Area, California, 2014–21

Golden Eagles ( Aquila chrysaetos ) are among the highest profile species killed by collisions with wind turbines at the Altamont Pass Wind Resource Area (APWRA) in the northern Diablo Range of west-central California. Understanding the distribution, site occupancy, and nesting status of eagles near the APWRA is needed to identify and minimize possible population-level impacts. We established a broad-scale survey design across a 5,185-km square-kilometer region of the Diablo Range, including the APWRA, to monitor site occupancy, abundance, and reproduction of Golden Eagles. During the study period we identified as many as 230 territorial pairs of Golden Eagles in the study area, up to 21 of which overlapped with the APWRA in any given year. On average, we detected a similar density of pairs at sites surveyed in the APWRA (1 pair per 17.8 km 2 surveyed) relative to sites surveyed in the surrounding region (1 pair per 20.3 km 2 surveyed). In 2020 and 2021, estimates of the proportion of pairs that successfully fledged at least one young (nesting success) were 0.27 and 0.26, respectively, which were above the seven-year average (0.22). On average, eagle pairs monitored in the APWRA had similar reproductive output (0.37 young fledged per pair) relative to pairs monitored outside of the APWRA (0.30 young fledged per pair). We observed a substantially higher proportion of territorial subadult pair members at the APWRA (mean = 29 percent of 16 pairs aged) relative to pairs monitored and aged in the surrounding region (mean = 3 percent of 122 pairs), indicating potentially higher rates of adult mortality or displacement at territories overlapping with the APWRA. Emergent threats to eagles in the study region, including a severe wildfire that impacted over 60 historical breeding territories in 2020, may interact with existing threats to affect population status and thus warrants further investigation. Our study provides wind energy developers, land managers, and regulatory agencies with key information on the spatial distribution, habitat quality, and population status of Golden Eagles needed to promote compatible wind energy production and long-term conservation of this federally protected wildlife species.

California↗

USGS2016

Spatial and temporal variation of stream chemistry associated with contrasting geology and land-use patterns in the Chesapeake Bay watershed—Summary of results from Smith Creek, Virginia; Upper Chester River, Maryland; Conewago Creek, Pennsylvania; and Difficult Run, Virginia, 2010–2013

Despite widespread and ongoing implementation of conservation practices throughout the Chesapeake Bay watershed, water quality continues to be degraded by excess sediment and nutrient inputs. While the Chesapeake Bay Program has developed and maintains a large-scale and long-term monitoring network to detect improvements in water quality throughout the watershed, fewer resources have been allocated for monitoring smaller watersheds, even though water-quality improvements that may result from the implementation of conservation practices are likely to be first detected at smaller watershed scales. In 2010, the U.S. Geological Survey partnered with the U.S. Environmental Protection Agency and the U.S. Department of Agriculture to initiate water-quality monitoring in four selected small watersheds that were targeted for increased implementation of conservation practices. Smith Creek watershed is an agricultural watershed in the Shenandoah Valley of Virginia that is dominated by cattle and poultry production, and the Upper Chester River watershed is an agricultural watershed on the Eastern Shore of Maryland that is dominated by row-cropping activities. The Conewago Creek watershed is an agricultural watershed in southeastern Pennsylvania that is characterized by mixed agricultural activities. The fourth watershed, Difficult Run, is a suburban watershed in northern Virginia that is dominated by medium density residential development. The objective of this study was to investigate spatial and temporal variations in water chemistry and suspended sediment in these four relatively small watersheds that represent a range of land-use patterns and underlying geology to (1) characterize current water-quality conditions in these watersheds, and (2) identify the dominant sources, sinks, and transport processes in each watershed. The general study design involved two components. The first included intensive routine water-quality monitoring at an existing streamgage within each study area (including continuous water-quality monitoring as well as discrete water-quality sampling) to develop a detailed understanding of the temporal and hydrologic variability in stream chemistry and sediment transport in each watershed. The second component involved extensive water-quality monitoring at various sites throughout each watershed to develop a detailed understanding of spatial patterns. Both components were used to improve understanding of sources and transport processes affecting stream chemistry, including nutrients and suspended sediments, and their implications for detecting long-term trends related to best management practices. This report summarizes the results of monitoring that was performed from April 2010 through September 2013. Individual Small Watershed Summaries Summaries for each of the four small watersheds are presented below. Each watershed has a more descriptive and detailed section in the report, but these summaries may be particularly useful for some watershed managers and stakeholders desiring slightly less technical detail. Smith Creek Smith Creek is a 105.39-mi 2 watershed within the Shenandoah Valley that drains to the North Fork Shenandoah River. The long-term Smith Creek base-flow index is 72.3 percent, indicating that on average, approximately 72 percent of Smith Creek flow was base flow, which suggests that Smith Creek streamflow is dominated by groundwater discharge rather than stormwater runoff. A series of cluster and principal components analyses demonstrated that the majority of the variability in Smith Creek water quality could be attributed to hydrologic and seasonal variability. Statistically significant positive correlations with flow were observed for turbidity, suspended sediments, total nitrogen, ammonium, orthophosphate, iron, total phosphorus, and the ratio of calcium to magnesium. Statistically significant inverse correlations with flow were observed for specific conductance, magnesium, δ 15 N of nitrate, pH, bicarbonate, calcium, and δ 18 O of nitrate. Of particular note, flow and nitrate were not statistically significantly correlated, likely because of the relatively complex concentration-discharge relationship observed in continuous and discrete datasets. Statistically significant seasonal patterns were observed for numerous water-quality constituents: water temperature, turbidity, orthophosphate, total phosphorus, suspended-sediment concentration, and silica were higher during the warm season, but pH, dissolved oxygen, and sulfate were higher during the cool season. Surrogate regression models were developed to compute sediment and nutrient loads in Smith Creek using the continuous water-quality monitors. The mean Smith Creek in-stream sediment load was approximately 6,900 tons per year, with nearly 90 percent of the sediment load over the 3-year study period contributed during the eight largest storm events during that period. The Smith Creek total phosphorus load was approximately 21,000 pounds of phosphorus per year, with the majority of the load contributed during stormflow periods, although a substantial phosphorus load still occurs during base-flow conditions. The Smith Creek total nitrogen load was approximately 400,000 pounds per year, with total nitrogen accumulation less dominated by stormflow contributions (as was the case for sediment and total phosphorus) and strongly affected by base-flow export of nitrogen from the basin. Extensive water-quality monitoring throughout the Smith Creek watershed revealed how the complex geology and hydrology interacted to result in variable water chemistry. During relatively dry and low base-flow periods, much of the discharge in Smith Creek was contributed by a single dominant spring—Lacey Spring. During wetter base-flow periods, the flows in Smith Creek were largely generated by a mixture of headwater springs and forested mountain tributaries with very different geochemical composition. The headwater springs generally issued from limestone bedrock and were characterized as having relatively high nitrate, specific conductance, calcium, and magnesium, as well as relatively low concentrations of phosphorus, ammonium, iron, and manganese. The undeveloped, high-gradient, forested mountain sites were generally characterized by low ionic strength waters with low nutrient concentrations. Nitrate isotope data from the limestone springs generally were consistent with manure-derived nitrogen sources (such as cattle and poultry), although the possibility of other mixed sources cannot be excluded. Nitrate isotope data from the undeveloped, high-gradient forested mountain sites were more consistent with nitrogen from undisturbed soils, atmospheric deposition, or nitrogen fixation. Regardless of the nitrogen source, oxygen isotope data indicate that the nitrate was largely a result of nitrification. Land-use data indicate that manure sources of nitrogen dominated watershed nitrogen inputs. Phosphorus sources were less well studied. The presence of a single point-source discharge near the town of New Market contributed the majority of the phosphorus to Smith Creek under base-flow conditions, but nonpoint sources of phosphorus dominated the loading to Smith Creek during stormflow periods. Implementation of conservation practices increased in the Smith Creek watershed during the study period, and even though a broad range of practice types was implemented, the most common practices included stream fencing (for cattle exclusion), the development of nutrient management plans, conservation crop rotation, and the planting of cover crops. While the implementation of these conservation practices is encouraging, results indicate small increases in nitrate concentrations at the streamgage over the last 29 years, concurrent with small decreases in nitrate fluxes. It will likely be years before the cumulative effect of these practices can be detected in the Smith Creek water quality, and the magnitude of the effect of these conservation practices detected in Smith Creek will depend largely on whether nutrient loading (of manure and commercial fertilizer) is reduced over time. Upper Chester River The Upper Chester River watershed includes the 36-square-mile (mi 2 ) watershed area around several nontidal tributaries that drain into the tidal Chester River. The streamgage is on Chesterville Branch, the largest nontidal tributary (approximately 6.12 mi 2 ) and is the site for continuous water-quality monitoring for this project. The base-flow index at Chesterville Branch is about 72 percent and indicates that, as in most of the Coastal Plain, groundwater is the greatest contributor to streamflow. As such, more than 90 percent of the nitrogen in the stream is in the form of nitrate from groundwater. Continuous and discrete data collected at Chesterville Branch show the effects of streamflow and season on water quality. Significantly positive correlations with flow were observed for ammonium, dissolved and total phosphorus, sediment, and turbidity as runoff carried these constituents from the land surface into Chesterville Branch. Other constituents that increased significantly with flow include potassium, sulfate, iron, and manganese, which are likely contributed from near-stream areas and ponds with high organic-matter content. Total nitrogen, pH, and specific conductance, along with chemical constituents associated with groundwater inputs including nitrate, calcium, ratio of calcium to magnesium, silica, bicarbonate, and sodium, were negatively correlated with flow because concentrations of these constituents were diluted by runoff. Seasonal differences in water chemistry, which are most likely related to increased biologic effects on the uptake and release of chemicals in the stream and near-stream areas, also were observed. Water temperature, orthophosphate, δ 15 N of nitrate, bicarbonate, sodium, and the ratio of sodium to chloride were higher during the warm season, and dissolved oxygen, total nitrogen, nitrate, magnesium, sulfate, and manganese were higher during the cool season. Surrogate-regression models developed by using continuous water-quality data showed that the annual sediment load for the 2013 water year was about 2,600 tons, with more than 90 percent of this sediment contributed during two storms. The total phosphorus load in 2013 was about 13,000 pounds with more than 90 percent contributed during the same two storms as sediment. The load of total nitrogen, 140,000 pounds, accumulated steadily throughout the 2013 water year as nitrate in groundwater continuously discharged into the stream. The same two large storms that contributed 90 percent of the suspended-sediment and total phosphorus load only contributed about 20 percent of the annual total nitrogen load. Extensive water-quality monitoring of stream base flow throughout the Upper Chester River watershed identified how differences in land use and hydrogeology affected water chemistry. In parts of the watershed with well-drained soil and thick sandy aquifer sediments, concentrations of nitrate and other chemicals associated with fertilizer and lime application increased in streams as agricultural land use increased. More than 90 percent of the nitrogen in streams from these areas was in the form of nitrate, and concentrations ranged from about 5 milligrams per liter (mg/L) to 8 mg/L as nitrogen in the two largest tributaries. Stream nitrate concentrations were about 1 mg/L as nitrogen where soils were more poorly drained, the surficial aquifer sediments were thinner, and forests and wetlands were more widespread than agriculture. Nitrate isotope data were consistent with inorganic fertilizers ± atmospheric deposition and N 2 fixation as sources of nitrogen, and with nitrification as the dominant nitrate-forming process. Nitrate reduction was indicated by elevated δ 15 N and δ 18 O values in some samples from streams draining watersheds with poorly drained soils. An analysis of land-use data and SPARROW modeling input data attributed almost 90 percent of the nitrogen sources in the Upper Chester River watershed to inorganic fertilizer and fixation of atmospheric nitrogen by legumes, which is in agreement with the isotopic characteristics of nitrate in this watershed. Local sources of manure are limited in this area. Total phosphorus concentrations during base flow ranged from below detection to about 0.2 mg/L. Stream phosphorus concentrations during base flow were generally lower than those measured during storms because most phosphorus transport likely occurs as phosphorus attached to sediment particles during runoff. Because manure is not widely used in this area, the major source of phosphorus is likely fertilizer. The implementation of conservation practices in the Upper Chester River watershed increased substantially during the study period, with a total implementation of 1,194 U.S. Department of Agriculture-compliant practices. The most frequently used practices were oriented towards nutrient and sediment control, including cover crops, nutrient management planning, conservation crop rotation, conservation tillage, and irrigation management. The current Chesapeake Bay model for this area predicts that implementation of best management practices should result in a 13-percent decrease in overall delivery of nitrogen to the Upper Chester River. Because most nitrogen travels through the groundwater system for years to decades before being discharged to streams, the time period of monitoring was not sufficient to see the effects of these practices on water quality. The magnitude of the effect that may eventually be detected will depend on the degree to which nitrate leaching into the groundwater system is reduced over time. Loadings of phosphorus and sediment are primarily transported during large runoff events and are difficult to control and analyze for trends because of their timing and episodic nature. Conewago Creek Conewago Creek has two primary monitoring locations—one near the middle of the 47-mi 2 watershed and the other near the outlet just upstream of the Susquehanna River. The base-flow index was 47.3 percent for 2012–2013, indicating that on average, approximately 53 percent of the streamflow in Conewago Creek exited the watershed as surface flow, which suggests that the stormwater runoff was somewhat greater than groundwater discharge (base flow). A series of cluster and principal components analyses demonstrated that the majority of the variability in the Conewago Creek water quality could be attributed to hydrologic and seasonal variability. Statistically significant positive correlations with flow were observed at both monitoring sites for ammonium, total phosphorus, orthophosphate, iron, and manganese; additionally, at the upstream monitoring station, total nitrogen demonstrated a statistically significant positive correlation with flow. Statistically significant inverse correlations with flow were observed at both sites for water temperature, specific conductance (at the downstream site only), sulfate, chloride, calcium, and magnesium. Statistically significant seasonal patterns were observed for several water-quality constituents. Water temperature, phosphorus (upstream site only), and orthophosphate were higher during the warm season, and nitrate and total nitrogen (upstream site only) were higher during the cool season. Surrogate regression models were developed to compute sediment and nutrient load in Conewago Creek by using the continuous water-quality monitors and water-quality samples. Conewago Creek sediment load was approximately 9,900 tons in 2012 and approximately 18,900 tons in 2013, with nearly 80 percent of the sediment load in 2013 contributed by the three largest storm events. Annual total nitrogen loads could not be estimated due to poor model performance. The addition of continued monitoring or a continuously recording nitrate sensor could improve estimates of total nitrogen loads. During 2012 and 2013, phosphorus loads in Conewago Creek were approximately 50,000 pounds in each year. Combining data from one high-flow synoptic sampling with the data from routine sampling revealed how the geology and hydrology interact to result in variable water chemistry throughout the Conewago Creek watershed. The areas above the upstream gage in the headwaters are generally underlain by forested non-carbonate bedrock and are characterized by relatively low nitrate, specific conductance, calcium, and magnesium, as well as relatively low concentrations of phosphorus, ammonium, iron, and manganese. The more developed, agricultural areas below the upstream site were generally characterized by higher ionic strength waters with higher nutrient and metal concentrations. An analysis of land-use data and SPAtially Referenced Regressions On Watershed (SPARROW) modeling data indicates that manure sources of nitrogen dominate the input of nitrogen to the watershed. Implementation of conservation practices increased in the Conewago Creek watershed during the study period, and while a broad range of practice types were implemented, the most common practices included residue and tillage management, cover crops, nutrient management, terracing, and stream fencing (for animal exclusion or bank restoration). While the implementation of these conservation practices is encouraging, the cumulative effects of these practices probably will not be detected in Conewago Creek water quality for several years. The magnitude of the effects of these conservation practices on water quality in Conewago Creek will depend largely on the extent to which nutrient loading (septic, manure, and commercial fertilizer) and sediment-producing activities are reduced over time. Difficult Run The Difficult Run watershed is a 57.82-mi 2 watershed that drains to the Potomac River. The long-term Difficult Run base-flow index (from 1936 to 2010) was 57.9, indicating that approximately 58 percent of streamflow exited the watershed as base flow and 42 percent as stormflow; however, with continued development and urbanization of the watershed, the base-flow index has decreased to 50 percent during the last 20 years. This base-flow index was less than those of the other watersheds evaluated in this study, likely because the Difficult Run watershed largely is underlain by crystalline piedmont metamorphic rocks and has a greater proportion of impervious urban land cover. A series of cluster and principal components analyses indicated that most of the variability in Difficult Run water quality could be attributed to hydrologic variability and seasonality. Statistically significant positive correlations with flow were observed for turbidity, dissolved oxygen, suspended sediments, ammonium, orthophosphate, iron, and total phosphorus. Statistically significant inverse correlations with flow were observed for water temperature, pH, specific conductance, bicarbonate, calcium, magnesium, nitrate, δ 15 N of nitrate, and silica. Statistically significant seasonal patterns were observed for numerous water-quality constituents: water temperature, ammonium, orthophosphate, and δ 15 N of nitrate were higher during the warm season, and dissolved oxygen, nitrate, and manganese were higher during the cool season. Surrogate regression models were developed to compute sediment and nutrient loading rates. The Difficult Run sediment load was approximately 8,000 tons per year, with greater than 95 percent of the sediment load in the 2013 water year contributed by the seven largest storm events. The total phosphorus load in Difficult Run was approximately 14,000 pounds of phosphorus per year, with the majority of the load contributed during stormflow periods. The total nitrogen load in Difficult Run is estimated to have been approximately 140,000 pounds per year, with total nitrogen accumulation less dominated by stormflow contributions than that of phosphorus and strongly affected by base-flow export of nitrogen from the basin. Extensive water-quality monitoring throughout the Difficult Run watershed revealed relatively uniform generation of flow per unit of watershed area, as well as spatial variation in water quality that is strongly related to land-use activities. Elevated nitrate concentrations were observed in a subset of monitoring sites that are inversely correlated with population density and positively correlated to the septic system density within each subwatershed. The majority of the elevated nitrate concentrations for these sites are hypothesized to be caused by nitrate leaching from septic systems, more so than homeowner fertilizer usage among these subwatersheds that have lower population densities than other parts of the watershed. Nitrate isotope data, temporal patterns in the water-quality data, mass-balance computations, and a separate land-use analysis all generally indicate that leachate from septic systems was the likely source of the elevated nitrate. Another group of water-quality sites have relatively low nitrogen concentrations, are located in areas that are served by city sewer lines, and have experienced stream restoration activities. A final group of sites drained the areas with the highest imperviousness and had strongly elevated specific conductance, chloride, and sodium, which were likely caused by a combination of road salting and other anthropogenic sources draining these urbanized areas in the watershed. A fourth group of sites represents a mixture of water sources and had water quality similar to that at the Difficult Run streamgage. Analysis of the nitrate isotope data generally indicates a broad range of composition indicative of mixed natural and anthropogenic nitrogen sources. Implementation of conservation practices increased in the Difficult Run watershed during the study period, and while a broad range of practice types was implemented, the most common practices included stream restoration. While the implementation of these conservation practices is encouraging, the cumulative effect of these practices probably will not be detected in Difficult Run water quality for several years.

Maryland, Pennsylvania, Virginia↗

USGS2024

Deep-ocean macrofaunal assemblages on ferromanganese and phosphorite-rich substrates in the Southern California Borderland

Mineral-rich hardgrounds, such as ferromanganese (FeMn) crusts and phosphorites, occur on seamounts and continental margins, gaining attention for their resource potential due to their enrichment in valuable metals in some regions. This study focuses on the Southern California Borderland (SCB), an area characterized by uneven and heterogeneous topography featuring FeMn crusts, phosphorites, basalt, and sedimentary rocks that occur at varying depths and are exposed to a range of oxygen concentrations. Due to its heterogeneity, this region serves as an optimal setting for investigating the relationship between mineral-rich hardgrounds and benthic fauna. This study characterizes the density, diversity, and community composition of macrofauna (>300 μm) on hardgrounds as a function of substrate type and environment (depth and oxygen ranges). Rocks and their macrofauna were sampled quantitatively using remotely operated vehicles (ROVs) during expeditions in 2020 and 2021 at depths above, within, and below the oxygen minimum zone (OMZ). A total of 3,555 macrofauna individuals were counted and 416 different morphospecies (excluding encrusting bryozoans and hydrozoans) were identified from 82 rocks at depths between 231 and 2,688 m. Average density for SCB macrofauna was 11.08 ± 0.87 ind. 200 cm −2 and mean Shannon-Wiener diversity per rock (H′ [loge] ) was 2.22 ± 0.07. A relationship was found between substrate type and macrofaunal communities. Phosphorite rocks had the highest H′ of the four substrates compared on a per-rock basis. However, when samples were pooled by substrate, FeMn crusts had the highest H′ and rarefaction diversity. Of all the environmental variables examined, water depth explained the largest variance in macrofaunal community composition. Macrofaunal density and diversity values were similar at sites within and outside the OMZ. This study is the first to analyze the macrofaunal communities of mineral-rich hardgrounds in the SCB, which support deep-ocean biodiversity by acting as specialized substrates for macrofaunal communities. Understanding the intricate relationships between macrofaunal assemblages and mineral-rich substrates may inform effects from environmental disruptions associated with deep-seabed mining or climate change. The findings contribute baseline information useful for effective conservation and management of the SCB and will support scientists in monitoring changes in these communities due to environmental disturbance or human impact in the future.

California↗

USGS2026

Stream sediment sources in Medicine Creek, northern Missouri and southern Iowa

This report presents the results of a cooperative study by the U.S. Geological Survey and Missouri Department of Natural Resources to quantify sediment transport source contributions in the Medicine Creek drainage basin. Understanding relative source contributions provides valuable information for selecting the conservation practices that may be most effective in reducing sediment and sediment-associated nutrient transport in the Medicine Creek drainage basin and similar areas of the Lower Grand River drainage basin. Sediment samples were collected from potential contributing areas (source samples) and from fluvial-transported samples (target samples). Source sample types included streambanks, row crop fields, and a combined pastures and forests category. Samples were analyzed for particle size and quantity of carbon, nitrogen, stable isotopes of carbon and nitrogen, and 49 mineral elements as potential tracers. Results for the carbon stable isotope ratio of carbon-13/carbon-12 (δ 13 C) and concentrations of total carbon, total nitrogen, calcium, potassium, and copper were selected by discriminant function analysis as the best combination of multiple tracers to differentiate each source type. The discriminant function analysis poorly differentiated pastures and forests, so these source types were combined. The sources defined by the discriminant function analysis were then used in an unmixing model to apportion sources for each target sample. In the study area, transported sediment was predominantly bank sediment, with an overall average of 86.9 percent of suspended-sediment samples and depositional streambed samples attributed to bank material. Suspended-sediment samples from the mainstem of Medicine Creek were dominated by bank sediments (average of 95.8 percent), and depositional streambed samples from throughout the drainage basin had more variable source contributions with an average of 71.1 percent attributed to bank material. The relative importance of upland sources (row crop fields and the combined pastures and forests category) varied seasonally and with streamflow but was not related to land use or drainage basin size. Relative contributions from upland sources were greater in the summer through winter rather than spring and during lower streamflow, though this may be driven by the seasonality of streamflow. These results indicate management practices that reduce bank erosion could be effective strategies for managing the dominant source of sediment and sediment-associated phosphorus.

Iowa, Missouri↗

USGS2012

Biodiversity of man-made open habitats in an underused country: a class of multispecies abundance models for count data

Since the 1960s, Japan has become highly dependent on foreign countries for natural resources, and the amount of managed lands (e.g. coppice, grassland, and agricultural field) has declined. Due to infrequent natural and human disturbance, early-successional species are now declining in Japan. Here we surveyed bees, birds, and plants in four human-disturbed open habitats (pasture, meadow, young planted forest, and abandoned clear-cut) and two forest habitats (mature planted forest and natural old-growth). We extended a recently developed multispecies abundance model to accommodate count data, and used the resulting models to estimate species-, functional group-, and community-level state variables (abundance and species richness) at each site, and compared them among the six habitats. Estimated individual-level detection probability was quite low for bee species (mean across species = 0.003; 0.16 for birds). Thirty-two (95% credible interval: 13-64) and one (0-4) bee and bird species, respectively, were suggested to be undetected by the field survey. Although habitats in which community-level abundance and species richness was highest differed among taxa, species richness and abundance of early-successional species were similar in the four disturbed open habitats across taxa except for plants in the pasture habitat which was a good habitat only for several exotic species. Our results suggest that human disturbance, especially the revival of plantation forestry, may contribute to the restoration of early-successional species in Japan

Biodiversity and Conservation↗

USGS2011

Development of a pan-Arctic monitoring plan for polar bears: Background paper

Polar bears (Ursus maritimus), by their very nature, and the extreme, remote environment in which they live, are inherently difficult to study and monitor. Monitoring polar bear populations is both arduous and costly and, to be effective, must be a long-term commitment. There are few jurisdictional governments and management boards with a mandate for polar bear research and management, and many have limited resources. Although population monitoring of polar bears has been a focus to some degree within most jurisdictions around the Arctic, of the 19 subpopulations recognised by the IUCN/Species Survival Commission Polar Bear Specialist Group (PBSG), adequate scientific trend data exist for only three of the subpopulations, fair trend data for five and poor or no trend data for the remaining 11 subpopulations (PBSG 2010a). There are especially critical knowledge gaps for the subpopulations in East Greenland, in the Russian Kara and Laptev seas, and in the Chukchi Sea, which is shared between Russia and the United States. The range covered by these subpopulations represents a third of the total area (approx. 23 million km2) of polar bears’ current range, and more than half if the Arctic Basin is included. If we use popular terms, we know close to nothing about polar bears in this portion of their range. As summer sea-ice extent, and to a lesser degree, spring-time extent, continues to retreat, outpacing model forecasts (Stroeve et al. 2007, Pedersen et al. 2009), polar bears face the challenge of adapting to rapidly changing habitats. There is a need to use current and synthesised information across the Arctic, and to develop new methods that will facilitate monitoring to generate new knowledge at a pan-Arctic scale. The circumpolar dimension can be lost when efforts are channelled into regional monitoring. Developing and implementing a plan that harmonises local, regional and global efforts will increase our power to detect and understand important trends for polar bears, with particular emphasis on how climate warming may differentially affect populations and habitats. Current knowledge is inadequate for a comprehensive understanding of the present and future impact of climate warming and its interaction with other stressors. The cumulative effects are unknown (Laidre et al. 2008). An integrated pan-Arctic research and monitoring plan will improve the ability to detect future trends, identify the most vulnerable subpopulations and guide effective conservation. There is a need to direct attention and resources where data are deficient to understand the mechanisms that drive trends, and to facilitate more effective and timely conservation response.

Report↗

USGS2016

Space and habitat use by breeding Golden-winged Warblers in the central Appalachian Mountains

Spot-mapping, or recording locations of observed use by territorial songbirds, is often used to delineate core breeding territories. However, a recent radiotelemetry study in Minnesota found that male Golden-winged Warblers ( Vermivora chrysoptera ) occurring in high-density populations used resources outside their spot-mapped territories. We compared differences in space use and quantified vegetation characteristics in territories and home ranges of individual male Golden-winged Warblers that we monitored using both spot-mapping and radiotelemetry. Our study sites in Pennsylvania and West Virginia had lower population density than in Minnesota. We recorded 524 telemetry locations among 12 male Golden-winged Warblers in Pennsylvania and 488 telemetry locations among seven males in West Virginia. Telemetry-delineated home ranges (100% and 50% minimum convex polygons [MCPs]) were two to four times larger than spot-mapped territories. Spot-mapped territories had minimal overlap among individual males, but home ranges had extensive space-use overlap in both the number and amount of MCP overlap among several males. Forty percent of telemetry locations were outside of spot-mapped territories. Sapling abundance was greater in home ranges (mean 22.5 saplings ± 2.1 SE) than spot-mapped territories in Pennsylvania (11.8 ± 1.9). In managed pastures of West Virginia, tree abundance was greater in home ranges (7.3 trees ± 0.8) than spot-mapped territories (1.9 ± 0.6). More telemetry locations than spot-mapped locations occurred in forest in both states, and telemetry locations were closer to intact forested edges of shrublands than spot-mapped locations in West Virginia. On several occasions, we observed radiomarked individuals >200 m (maximum of 1.5 km) from their MCP spot-mapped territory boundaries. Why Golden-winged Warblers leave their spot-mapped territories is unknown, but our observations suggest foraging, forays for extra-pair mating, and reconnaissance for postbreeding movements as possible motives. Our results from areas with low Golden-winged Warbler territory densities are similar to patterns reported for a high-density population in Minnesota. Ultimately, spot-mapping alone does not accurately reflect space use of Golden-winged Warblers during the breeding season, nor does it characterize all cover types used even in areas with relatively low territory densities. Current conservation plans for Golden-winged Warblers that are based on habitat characteristics measured within spot-mapped territories or at the landscape scale may not adequately incorporate space use at intermediate spatial scales of clusters of territories or home ranges.

Studies in Avian Biology↗

USGS2022

Both real-time and long-term environmental data perform well in predicting shorebird distributions in managed habitat

Highly mobile species, such as migratory birds, respond to seasonal and inter-annual variability in resource availability by moving to better habitats. Despite the recognized importance of resource thresholds, species distribution models typically rely on long-term average habitat conditions, mostly because large-extent, temporally-resolved, environmental data are difficult to obtain. Recent advances in remote sensing make it possible to incorporate more frequent measurements of changing landscapes; however, there is often a cost in terms of model building and processing and the added value of such efforts is unknown. Our study tests whether incorporating real-time environmental data increases the predictive ability of distribution models, relative to using long-term average data. We developed and compared distribution models for shorebirds in California's Central Valley based on high temporal resolution (every 16-days), and 17-year long-term average, surface water data. Using abundance-weighted boosted regression trees, we modeled monthly shorebird occurrence as a function of surface water availability, crop type, wetland type, road density, temperature, and bird data source. While modeling with both real-time and long-term average data provided good fit to withheld validation data (0.79 < AUC < 0.89 across taxa), there were small differences in model performance. The best models incorporated long-term average conditions and spatial pattern information for real-time flooding (e.g. perimeter-area ratio of real-time water bodies). There was not a substantial difference in the performance of real-time and long-term average data models within time periods when real-time surface water differed substantially from the long-term average (specifically during drought years 2013-2016) and in intermittently flooded months or locations. Spatial predictions resulting from the models differed most in the southern region of the study area where there is lower water availability, fewer birds, and lower sampling density. Prediction uncertainty in the southern region of the study area highlights the need for increased sampling in this area. Because both sets of data performed similarly, the choice of which data to use may depend on the management context. Real-time data may ultimately be best for guiding dynamic, adaptive conservation actions whereas models based on long-term averages may be more helpful for guiding permanent wetland protection and restoration.

Ecological Applications↗

USGS2021

Divergence in salinity tolerance of northern Gulf of Mexico eastern oysters under field and laboratory exposure

The eastern oyster, Crassostrea virginica , is a foundation species within US Gulf of Mexico (GoM) estuaries that has experienced substantial population declines. As changes from management and climate are expected to continue to impact estuarine salinity, understanding how local oyster populations might respond and identifying populations with adaptations to more extreme changes in salinity could inform resource management, including restoration and aquaculture programs. Wild oysters were collected from four estuarine sites from Texas [Packery Channel (PC): 35.5, annual mean salinity, Aransas Bay (AB): 23.0] and Louisiana [Calcasieu Lake (CL): 16.2, Vermilion Bay (VB): 7.4] and spawned. The progeny were compared in field and laboratory studies under different salinity regimes. For the field study, F1 oysters were deployed at low (6.4) and intermediate (16.5) salinity sites in Alabama. Growth and mortality were measured monthly. Condition index and Perkinsus marinus infection intensity were measured quarterly. For the laboratory studies, mortality was recorded in F1 oysters that were exposed to salinities of 2.0, 4.0, 20.0/22.0, 38.0 and 44.0 with and without acclimation. The results of the field study and laboratory study with acclimation indicated that PC oysters are adapted to high-salinity conditions and do not tolerate very low salinities. The AB stock had the highest plasticity as it performed as well as the PC stock at high salinities and as well as Louisiana stocks at the lowest salinity. Louisiana stocks did not perform as well as the Texas stocks at high salinities. Results from the laboratory studies without salinity acclimation showed that all F1 stocks experiencing rapid mortality at low salinities when 3-month oysters collected at a salinity of 24 were used and at both low and high salinities when 7-month oysters collected at a salinity of 14.5 were used.

Alabama, Louisiana, Texas↗

USGS2025

Habitat selection by Rocky Mountain Population greater Sandhill Cranes (Antigone canadensis tabida) during spring and autumn migration at a key stopover area

The San Luis Valley (SLV), Colorado is a critical stopover area for Rocky Mountain Population greater Sandhill Cranes ( Antigone canadensis tabida ). During spring and autumn, cranes use crops for foraging and water resources adjacent to foraging areas for roosting and loafing. However, surface water is becoming increasingly limited in the SLV. Understanding the factors that affect use by roosting, loafing, and foraging cranes and where habitat is the most limiting will inform water and habitat management under changing conditions. We used mixed-effects models to determine the effects of habitat variables, ownership, and landcover type on the selection of roosting, loafing, and foraging areas by cranes marked with GPS transmitters (2015–2021). We found that Sandhill Cranes selected for areas with a high amount of water, relatively short vegetation (< 5 m in autumn, < 10 m in spring), close to grain fields (< 5 km), and areas identified as open water for roosting. Loafing Sandhill Cranes also selected for areas with short vegetation and close to grain fields but that had less water and more sandbar and were identified as pastures or wetlands. Although selection was higher for private land overall, we found evidence of avoidance of private lands and a stronger preference for public lands with increasing surface water for roosting in spring. For foraging areas, selection was highest for barley in both seasons, but triticale and other grains had relatively high selection in autumn. Our research confirms the importance of providing roosting and loafing areas on both private and public lands close to foraging areas and provides evidence that roosting and loafing opportunities may be most limited on public lands in the SLV.

Colorado↗

USGS2006

Vegetation classification for south Florida natural areas

Introduction A critical component of any ecological restoration program is documenting the temporal changes in the spatial extent, pattern, and proportion of plant communities within the landscape. The Comprehensive Everglades Restoration Plan (CERP - www.evergladesplan.org), authorized as part of the Water Resources and Development Act (WRDA) of 2000 (U.S. Congress, 2000), is an $8 billion hydrologic restoration project for all of south Florida. CERP includes 68 separate projects to be managed over the next 30 years by the South Florida Water Management District (SFWMD), the U. S. Army Corp of Engineers (USACE), and other State and Federal agencies. Restoration Coordination and Verification (RECOVER) is a system-wide program of the CERP, designed to organize, manage, and provide the highest quality scientific and technical support during implementation of the restoration program (RECOVER, in prep.). It is the role of RECOVER to develop and implement a system-wide Monitoring and Assessment Plan (MAP) (RECOVER, 2004) and to document how well the CERP is meeting its objectives for ecosystem restoration. One critical component of the MAP is vegetation mapping to document changes in the spatial extent, pattern, and proportion of plant communities within the Everglades landscape. A major aspect of the vegetation mapping project was determining a classification system for labeling vegetation categories utilizing a grid method. The grid method was created specifically for use in the CERP RECOVER vegetation monitoring and assessment project (Rutchey and others, in prep). The CERP RECOVER vegetation mapping project utilizes aerial photography and photointerpretation techniques (with ground truthing) to identify and label vegetation classes. A classification system that had sufficient flexibility and detail to enable the designation of vegetation classes using various remote sensing platforms and identification techniques needed to be developed. The classification system had to be hierarchical, represent distinct ecological communities, individual species, and physical characteristics such as density and height. In addition, it was desirable to have a classification system that allowed exotic species and cattail to be identified using density classes. The classification system was developed specifically for peninsular south Florida and the Florida Keys, from Lake Okeechobee in the north to Key West in the south (Figure 1). Specific areas of interest include Everglades National Park, Big Cypress National Preserve, Biscayne National Park, Florida Panther National Wildlife Refuge, Loxahatchee National Wildlife Refuge, the State of Florida Water Conservation Areas, Holeyland Wildlife Management Area, Rotenberger Wildlife Management Area, J.W. Corbett Wildlife Management Area, Pal-Mar Wildlife Management Area, the Lake Okeechobee Littoral Zones, and additional coastal wetlands of south eastern Miami-Dade County. In addition to being used for mapping of CERP affected areas, the National Park Service-South Florida/Caribbean Network is using the classification for mapping the remaining areas of Everglades National Park and Big Cypress National Preserve outside the CERP footprint, Florida Panther National Wildlife Refuge, Biscayne National Park, and Dry Tortugas National Park.

Florida↗

USGS2013

Mobile Bay

Mobile Bay is the largest bay found in Alabama’s coastal area (Handley et al., 2007). It was named an Estuary of National Significance in 1995 under the U.S. Environmental Protection Agency’s (EPA) National Estuary Program (NEP), and its Comprehensive Conservation Management Plan was completed in 2002. Mobile Bay is 1,070 km 2 (413 miles 2 ) in area and 51 km (32 miles) long, making it the sixth largest estuary in the continental United States (Mobile Bay NEP, 2008). Its ecosystem provides habitat for more than 300 species of birds, 310 species of fish, 68 species of reptiles, 57 species of mammals, 40 species of amphibians, and 15 species of shrimp (Mobile Bay NEP, 1997). Mobile Bay lies between the Mississippi and Atlantic Flyways (Mobile Bay NEP, 2003). Commercial and residential development and industrial use is heavy in the Mobile Bay area. Although local growth and industrial markets support the Mobile Bay area economy, the resulting environmental damage to the very ecosystem upon which they depend remains a threat to the environment, economy, and population. The Mobile Bay ecosystem boasts high biological diversity and productivity and supports many freshwater and saltwater species of recreational and commercial importance. The great diversity of Mobile Bay reflects the diversity of Alabama, which is home to the largest number of different plant and animal species of all states east of the Mississippi River (Stein, 2002), and is bolstered by the unique climate and geographic conditions surrounding the bay. Freshwater inflow from the Mobile-Tensaw River Delta, ranging from 60,000 to 3,700,000 gallons per second (Wallace, 1996), mixes with saltwater from the Gulf of Mexico, which enters Mobile Bay via wind and tides (Burgan and Engle, 2006). Because of the unique conditions surrounding Mobile Bay, including shallow waters, a dynamic climate, and artificial hydrologic modifications—such as the construction of the Mobile Bay Causeway in the 1920s, which serves as an unintentional barrier between Delta waters north of the Causeway and saline waters south of the Causeway, the salinity of Mobile Bay is highly variable. Mobile Bay receives an average of 165 cm (65 inches) of rain per year from tropical storms, summer thunderstorms, and winter cold fronts (Stout et al., 1998). The climate and geography that have made Mobile Bay so rich in resources have also contributed to the threats surrounding its ecosystem. The extensive amount of rain in Mobile Bay creates large amounts of runoff, polluting the waters with fertilizers, chemicals, sediment, oil, trash, and sewage (Mobile Bay NEP, 1997). Tourism, ecotourism, recreational and commercial fishing, recreational boating, shipping, and chemical, pulp, and paper production are significant industries in Mobile Bay and the surrounding areas. Despite the approximate \$3 billion and 55,000 jobs these industries bring into the community (Alabama Tourism Department, 2010), the growth, development, and environmental stress they create are major threats to the Mobile Bay ecosystem. Among the nation’s states, Alabama ranks fifth in number of different species (144 endemic species), second in number of extinctions that have already occurred (90 extinct species) and fourth in number of species at risk for extinction (14.8% at risk out of 4,533 total species; Stein, 2002). Twenty-one of these threatened and endangered species are found in Mobile Bay, whose brackish waters provide a nursery area for many species of vertebrates and invertebrates. Some of these species include the Alabama sturgeon, Gulf sturgeon, heavy pigtoe mussel, inflated heel-splitter mussel, West Indian manatee, Alabama beach mouse, Perdido beach mouse, Alabama red-bellied turtle, gopher tortoise, Kemp’s ridley sea turtle, green sea turtle, loggerhead sea turtle, eastern indigo snake, flatwoods salamander, piping plover, red-cockaded woodpecker, and wood stork. Habitat loss underlies the decline of some bird species in Mobile Bay, and large mammals such as the red wolf, Florida panther, and Florida black bear are no longer found in the area. However, some rare species, such as the swallow-tailed kite, sandhill crane, and gopher tortoise can still be found (Duke and Kruczynski, 1992). The value of wetlands in Mobile Bay and the rest of the Gulf of Mexico is still being investigated. Although various monetary valuations of wetlands exist, critics remark that undervaluation of wetlands is inevitable (Mobile Bay NEP, 2008) and that estimates often do not place appropriate value on ecological services (Mitsch and Gosselink, 2000). Additionally, many estimates account only for anthropogenic values. One estimate concludes that one acre of wetlands performs \$3,000 worth of water purification each year (Mobile Bay NEP, 1997). With more than 76,890 hectares (190,000 acres) of wetlands in the Mobile Bay area, that equates to a value exceeding one-half billion dollars every year. Tourism, fishing, boating, production, and shipping are significant industries in the Mobile Bay area. More than 90% of fish landed in recreational and commercial fishing in the bay depend on bay habitat, including wetlands, for life requirements (Mobile Bay NEP, 1997). The Port of Mobile is Alabama’s only ocean-ship port (Mobile Bay NEP, 2008). Baldwin County, on the eastern side of the bay, experienced a population increase of 75% from 1990 to 2007, with an 89% increase in housing units (Mobile Bay NEP, 2008). Development and industry support the Mobile Bay economy, but they depend on the continued health, sustainability, and production of the water and living resources of the Mobile Bay ecosystem. Wetland loss, along with other forms of environmental degradation, remains a threat to the Mobile Bay ecosystem and Mobile Bay’s socioeconomic foundation.

Alabama↗

USGS2015

Bathymetry and capacity of Chambers Lake, Chester County, Pennsylvania

Introduction Chambers Lake is a manmade reservoir on Birch Run, a tributary to West Branch Brandywine Creek in Chester County, Pennsylvania. The lake was created in 1994 after the completion of Multi-Purpose Dam PA-436F (Hibernia Dam), which was built under the Watershed Protection & Flood Control Prevention Act (U.S. Soil Conservation Service, 1991). Hibernia dam is 1,700 feet upstream from the confluence of Birch Run with West Branch Brandywine Creek. The primary objectives for Hibernia Dam were to provide (1) flood control, (2) a supplemental source of water supply for the greater City of Coatesville public water system, and (3) recreational opportunities. The drainage basin of Chambers Lake encompasses approximately 4.5 square miles, and the lake covers a surface area of about 95 acres at normal pool, which is at an elevation of 579.2 feet above the North American Vertical Datum of 1988 (NAVD 88) [580.0 feet above the National Geodetic Vertical Datum of 1929 (NGVD 29)]. The crest of the auxiliary spillway of the dam is 586.6 feet above NAVD 88. The elevation of the auxiliary spillway is important to this investigation because this elevation defines the flood storage capacity of Chambers Lake. Water levels exceeding this elevation are routed through the auxiliary spillway and flow through adjoining woodland to Birch Run. The U.S. Geological Survey (USGS), in cooperation with Chester County Water Resources Authority (CCWRA) and the County of Chester, surveyed the bathymetry and selected above-water features of Chambers Lake in September 2014. The purpose of the survey was to develop an accurate representation of the surface of the bottom of Chambers Lake and to determine the stage area and reservoir-storage capacity relation as of September 2014. CCWRA is responsible for operation of the dam and water-supply reservoir. Since construction, CCWRA has used a stage–storage capacity relation developed from the original survey conducted in the 1990s to estimate the volume of water available for water supply and the available flood storage. The bathymetric mapping effort was initiated due to interest in potential changes in current (2014) storage capacity when compared to the stage–storage capacity relation developed during design. The generated bathymetric surface may serve as a baseline to which temporal changes in storage capacity, owing to sedimentation and other factors, can be compared. In addition, these data will improve the overall accuracy of the stage–storage capacity table that CCWRA uses for reservoir and flood management operations. This report describes the methods used to create a bathymetric map of Chambers Lake for the computation of reservoir storage capacity as of September 2014. The product is a bathymetric map and a table showing the storage capacity of the reservoir at 2-foot increments from minimum usable elevation up to full capacity at the crest of the auxiliary spillway.

Pennsylvania↗

USGS2018

Baseline water quality of an area undergoing shale-gas development in the Muskingum River watershed, Ohio, 2015–16

In 2015–16, the U.S. Geological Survey, in cooperation with the Muskingum Watershed Conservancy District, led a study to assess baseline (2015–16) surface-water quality in six lake drainage basins within the Muskingum River watershed that are in the early years of shale-gas development. In 2015, 9 of the 10 most active counties in Ohio for oil and gas development were wholly or partially within the Muskingum River watershed. In addition to shale gas development, the area has a history of conventional oil and gas development and coal mining. In all, 30 surface-water sites were sampled: 20 in tributaries flowing to the lakes, 4 in lakes themselves, and 6 downstream of the lakes. At each of the 30 sites, 6 samples were collected to characterize surface-water chemistry throughout a range of hydrologic conditions. The sampling generally occurred during low flows (periods of greater groundwater contribution) rather than during runoff events (periods of high stream stage). Trilinear diagrams of major ion chemistry revealed three main types of water in the study area―sulfate-dominated waters, bicarbonate-dominated waters, and waters with mixed bicarbonate and chloride anions. Most sites produced samples of bicarbonate-dominated water, and 11 sites produced samples with sulfate-type waters. Mixed bicarbonate and chloride waters were found in samples from two of the six lake drainage basins studied. The baseline (2015–16) assessment of surface-water quality in the study area indicated that few water-chemistry constituents and properties occurred at concentrations or levels that would adversely affect aquatic organisms. Chemical-specific, aquatic life use criteria were not met in only three instances: two were for total dissolved solids at sites likely impacted by coal mining in their drainage basins (hereafter referred to as “mine-impacted sites”), and one was for dissolved oxygen. Mine drainage from historical coal mining in the region likely affected the quality of about one-third of the streams sampled. To simplify interpretation of water-chemistry results, 11 sites with sulfate-type water were identified as mine-impacted sites based on water-quality criteria established by Ohio Department of Natural Resources, Division of Mineral Resources Management, and separated out for subsequent statistical analysis. Concentrations or levels of bicarbonate, boron, calcium, carbonate, total dissolved solids, fluoride, magnesium, lithium, pH, potassium, sodium, specific conductance, strontium, sulfate, and suspended sediment in water were higher (significance level of 0.05) at mine-impacted stream sites than at non-mine-impacted stream sites. An accidental release of oil- and gas-related brines could increase salinity (sodium and chloride), the concentration of total dissolved solids in shallow groundwater and streams, and specific conductance. For this study, chloride concentrations in the study area ranged from 2.12 to 76.1 milligrams per liter. Sources of chloride in water samples were evaluated using binary mixing curves and ratios of chloride to bromide. These ratios indicated that 13 samples from 3 sites in the drainage basin that contained the highest density of conventional oil and gas wells in the study, as well as 4 samples collected from other drainage basins, likely contained a component of brine. Concentrations or levels of barium, bromide, chloride, iron, lithium, manganese, and sodium were significantly higher (alpha = 0.05) in samples with a component of brine than in samples without a component of brine. Benzene, toluene, ethylbenzene and xylene (BTEX), compounds that occur naturally in crude oil, made up 24 of the 45 detections (53 percent) of volatile organic compounds in the study area. The BTEX detections were not associated with sites containing a component of brine. The only volatile organic compound detected in any of the 17 samples that contained a component of brine was acetone, detected in 3 (18 percent) of these samples and in 11 percent of samples not containing a component of brine. Considering that BTEX are gasoline hydrocarbons and that most of the detections occurred during warmer months in and around the lakes, the BTEX detections likely are associated with increases in outdoor activities such as automobile and boating traffic. Radium-226 and radium-228 were included in the list of analytes for this study because production water from shale-gas drilling can contain these naturally occurring radioactive materials. Concentrations of radium-226 exceeded background levels in only two surface-water samples. Concentrations of radium-228 exceeded background levels in one surface-water sample. A brine signature potentially indicative of oil and gas contamination was detected in samples collected at two sites that contained active or plugged waste injection wells, or both. Results from the study indicated significant differences in the median concentrations of bromide, chloride, lithium, manganese, sodium, and total dissolved nitrogen between sites with and without injection wells in their drainage areas. Median concentrations of bromide, chloride, lithium, and sodium, which are common oil- and gas-related contaminants, were higher at sites with injection wells in their drainage areas compared to sites without injection wells. Historical (1960s, 1970s, and 1980s) chloride concentrations and streamflow data at or near five of the six sampling sites downstream from each lake dam were compared to current (2015–16) values. An analysis of covariance was done to test the effects of streamflow, time (decade), and the combined effects (cross product) of streamflow and time on chloride concentrations. Those analyses indicated that streamflow was not significant in explaining the variation in chloride concentration, likely because streamflow in those locations is controlled by dam operations; therefore, association between runoff-generating events and streamflow is less direct than in unregulated streams. From the 1980s to the study period (2015–16), data for three of the five lakes indicated an increase in chloride concentrations. The comparison of historical and current (2015–16) study data from samples collected at another lake indicated that chloride concentrations increased from the 1960s to the 1970s, but concentrations in the 1970s and 2015–16 were similar even though 13 samples from this lake drainage basin were classified as having a component of brine. Median chloride concentrations for the fifth lake, however, seemed to decrease from the 1980s to 2015–16.

Ohio↗

USGS2014

Normative standards for land use in Vermont: Implications for biodiversity

The conversion of natural lands to developed uses poses a great threat to global terrestrial biodiversity. Natural resource managers, tasked with managing wildlife as a public trust, require techniques for predicting how much and where wildlife habitat is likely to be converted in the future. Here, we develop a methodology to estimate the “social carrying capacity for development” – SK d – for 251 towns across the state of Vermont, USA. SK d represents town residents’ minimum acceptable human population size and level of development within town boundaries. To estimate SK d across towns within the state of Vermont (USA), as well as the average state-wide SK d , we administered a visual preference survey ( n = 1505 responses) to Vermont residents, and asked respondents to rate alternative landuse scenarios in a fictional Vermont town on a scale of +4 (highly acceptable) to −4 (highly unacceptable). We additionally collected demographic data such as age and income, as well as ancillary information such as participation in town-planning meetings and location of residence. We used model selection and AIC to fit a cubic function to the response data, allowing us to estimate SK d at a town scale based on town demographic characteristics. On average, Vermonters had a SK d of 9.1% development on the landscape; this estimate is 68% higher than year 2000 levels for development (5.4%). Respondents indicated that management action to curb development was appropriate at 9.4% development (roughly the statewide SK d average). Management by local, regional, and state levels were considered acceptable for curbing development while federal level management of development was considered unacceptable. Given a scenario where development levels were at SK d , we predicted a 16,753 km 2 reduction in forested land (−11.16%) and a 1038 km 2 reduction in farmland (−60.45%). Such changes would dramatically alter biodiversity patterns state-wide. In a companion paper, we estimate how these changes would affect the distribution of wildlife species.

Vermont↗

USGS2006

Geologic map of the Valle 30' x 60' quadrangle, Coconino County, northern Arizona

The geologic map of the Valle 30' x 60' quadrangle is the result of a cooperative effort between the U.S. Geological Survey and the National Park Service to provide geologic information for regional resource management and visitor information services for Grand Canyon National Park, Arizona. The map area encompasses approximately 1,960 sq.mi. within Coconino County, northern Arizona and is bounded by long 112 deg to 113 deg W. and lat 35 deg 30 min to 36 deg N. and lies within the southern Colorado Plateaus geologic province (herein Colorado Plateau). The map area is locally subdivided into four physiographic parts; (1) the Grand Canyon (Cataract Canyon and extreme northeast corner of the map area), (2) the Coconino Plateau, (3) the Mount Floyd Volcanic Field, and (4) the San Francisco Volcanic Field as defined by Billingsley and others, 1997. Elevations range from 7,460 ft (2,274 m) on the Coconino Plateau along State Highway 64 northeast corner of the map area, to about 4,200 ft (1,280 m) at the bottom of Cataract Canyon. Settlements within the map area include Tusayan and Valle, Arizona. State Highway 64 and U.S. Highway 180 provide access to the Tusayan and Valle areas. Indian Route 18 is a paved highway in the northwest corner of the map area that is maintained by the Hualapai and Havasupai Indian Tribes and leads from State Route 66 about 7 mi (11 km) east of Peach Springs, Arizona to Hualapai Hilltop, a parking lot just north of the map area at the rim of Cataract Canyon where visitors begin an 8 mi (13 km) hike into Havasupai, Arizona. Other remote parts of the map are accessed by two dirt roads, which are maintained by Coconino County, and by several unmaintained local ranch roads. Weather conditions restrict travel within the area and visitors must obtain permission to access a few local ranch lands in the south-central edge of the map area. Extra water and food are highly recommended when traveling in this remote region. Access into Cataract Canyon is restricted to horse or foot travel and visitors must obtain permission from the Havasupai Tribe to hike within the Havasupai Indian Reservation. In the central part of the map area, most of the land is privately owned and managed by the Babbitt Ranches Inc. in conjunction with the Nature Conservancy and the Navajo Tribe. In the southern half of the map, land alternates between privately owned land and State land forming a checkerboard pattern. The National Park Service manages land in Grand Canyon National Park (extreme northeast edge of map area), the U.S. Forest Service manages lands in the Kaibab National Forest, the Hualapai Tribe manages lands in the northwest quarter of the map area, and the Havasupai Tribe manages lands within Cataract Canyon and adjacent parts of the Coconino Plateau.

Scientific Investigations Map↗

USGS2024

Estimated reductions in phosphorus loads from removal of leaf litter in the Lake Champlain drainage area, Vermont

Excess nutrient loading and other factors are driving eutrophication and other negative effects on water-quality conditions in Lake Champlain and other receiving waters in Vermont. Two common best management practices were evaluated to determine how these practices can be optimized by targeting maintenance and operation to align better with seasonally driven needs, specifically to help municipalities remove a greater proportion of seasonal leaves and organic debris, reduce nutrient loading, and achieve water-quality goals. To characterize solid materials typically removed by the municipal BMPs of catch-basin (CB) cleaning and street cleaning (SC), subsamples of CB and SC materials were collected each month from nine participating municipalities in central and northwestern Vermont between September 2017 and November 2018. Monthly and seasonal composites of CB and SC samples were created from the subsamples of available materials from all municipalities. Samples were analyzed for concentrations of total organic carbon, total Kjeldahl nitrogen, and total phosphorus (P), and separated into three particle-size fractions. Distribution of particle-size fractions was similar between CB and SC as both practices generally collect the coarser fraction of solid materials (greater than 125 micrometers in diameter). In the fall, however, the range of the coarser fraction of materials increased. This is attributed to the ability of SC to collect leaves and other light organic materials that commonly pass through a CB system designed to trap heavier materials. Total organic carbon, total Kjeldahl nitrogen, and total P concentrations were highest in the catch-basin samples in the fall of 2017, and concentrations in the SC samples were highest in the fall of 2018. The collection of fewer samples in 2017 may account for some of the variability between fall 2017 and fall 2018 results. A subset of SC samples collected from piles representing specific street-cleaning routes in September and November 2018 were also analyzed. Materials collected in November were dominated by leaves, and the concentrations of the analyzed species of carbon, nitrogen, and phosphorus in some samples were more than double those in samples collected on the same street-cleaning routes in September. The Vermont Department of Environmental Conservation and the University of Vermont developed estimates of load-reduction credits for CB and SC practices based on a policy developed by the Wisconsin Department of Natural Resources that determined the potential for credits associated with leaf-removal activities. This process also considered BMPs that were initiated during the U.S. Environmental Protection Agency’s Lake Champlain Basin Total Maximum Daily Load monitoring period (2000 to 2009) and adapted the Wisconsin Department of Natural Resources policies to apply to existing SC routes in the cooperating Vermont municipalities that possessed at least 17 percent tree cover. This exercise demonstrated that applying the Wisconsin Department of Natural Resources policy to existing street-cleaning routes possessing 17 percent or more tree cover would result in reductions in total P loads up to 65 percent of mandated target reductions, and about a 25 percent reduction on average. Continuous simulations of stormwater runoff volume, and of loads of suspended sediments and total P, also were created for Englesby Brook Basin, an urbanized basin in Burlington and South Burlington that drains to Lake Champlain. Although the basin is more developed than the average of the nine cooperating municipalities, streamflow and P loading data collected by the U.S. Geological Survey were available to evaluate model performance. Simulations based on a year of average climatic conditions projected potential small reductions in total P of 0.08 to 0.10 percent as a result of CB cleaning and SC practices. Simulated weekly SC practices, however, reduced street-solid loads by as much as 7 percent. When the proportion of total P seen in fall SC materials collected in Vermont was applied to these simulated street-solid loads, estimated reductions of total P were about 29 percent. The combination of analytical results, estimated load-reduction credits, and simulated reductions indicate that targeted increases of SC activities to reduce leaf loading in the fall have the potential to reduce loading to receiving waters and could help regulated communities meet their water-quality goals.

Vermont↗