SEARCH · Search USGS

Results for “Four Seasons”

Search indexed USGS publications on groundwater, aquifers, geologic maps, mineral resources and earthquakes. Explore source records by subject and place.

SourceResearch connectionFrom yearThrough year

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 361 records · Page 20Linked to original sources

USGS2014

Concentrations, loads, and yields of total nitrogen and total phosphorus in the Barnegat Bay-Little Egg Harbor watershed, New Jersey, 1989-2011, at multiple spatial scales

Concentrations, loads, and yields of nutrients (total nitrogen and total phosphorus) were calculated for the Barnegat Bay-Little Egg Harbor (BB-LEH) watershed for 1989–2011 at annual and seasonal (growing and nongrowing) time scales. Concentrations, loads, and yields were calculated at three spatial scales: for each of the 81 subbasins specified by 14-digit hydrologic unit codes (HUC-14s); for each of the three BB-LEH watershed segments, which coincide with segmentation of the BB-LEH estuary; and for the entire BB-LEH watershed. Base-flow and runoff values were calculated separately and were combined to provide total values. Available surface-water-quality data for all streams in the BB-LEH watershed for 1980–2011 were compiled from existing datasets and quality assured. Precipitation and streamflow data were used to distinguish between water-quality samples that were collected during base-flow conditions and those that were collected during runoff conditions. Base-flow separation of hydrographs of six streams in the BB-LEH watershed indicated that base flow accounts for about 72 to 94 percent of total flow in streams in the watershed. Base-flow mean concentrations (BMCs) of total nitrogen (TN) and total phosphorus (TP) for each HUC-14 subbasin were calculated from relations between land use and measured base-flow concentrations. These relations were developed from multiple linear regression models determined from water-quality data collected at sampling stations in the BB-LEH watershed under base-flow conditions and land-use percentages in the contributing drainage basins. The total watershed base-flow volume was estimated for each year and season from continuous streamflow records for 1989–2011 and relations between precipitation and streamflow during base-flow conditions. For each year and season, the base-flow load and yield were then calculated for each HUC-14 subbasin from the BMCs, total base-flow volume, and drainage area. The watershed-loading application PLOAD was used to calculate runoff concentrations, loads, and yields of TN and TP at the HUC-14 scale. Flow-weighted event-mean concentrations (EMCs) for runoff were developed for each major land-use type in the watershed using storm sampling data from four streams in the BB-LEH watershed and three streams outside the watershed. The EMCs were developed separately for the growing and nongrowing seasons, and were typically greater during the growing season. The EMCs, along with annual and seasonal precipitation amounts and percent imperviousness associated with land-use types, were used as inputs to PLOAD to calculate annual and seasonal runoff concentrations, loads, and yields at the HUC-14 scale. Over the period of study (1989–2011), total surface-water loads (base flow plus runoff) for the entire BB-LEH watershed for TN ranged from about 455,000 kilograms (kg) as N (1995) to 857,000 kg as N (2010). For TP, total loads for the watershed ranged from about 17,000 (1995) to 32,000 kg as P (2010). On average, the north segment accounted for about 66 percent of the annual TN load and 63 percent of the annual TP load, and the central and south segments each accounted for less than 20 percent of the nutrient loads. Loads and yields were strongly associated with precipitation patterns, ensuing hydrologic conditions, and land use. HUC-14 subbasins with the highest yields of nutrients are concentrated in the northern part of the watershed, and have the highest percentages of urban or agricultural land use. Subbasins with the lowest TN and TP yields are dominated by forest cover. Percentages of turf (lawn) cover and nonturf cover were estimated for the watershed. Of the developed land in the watershed, nearly one quarter (24.9 percent) was mapped as turf cover. Because there is a strong relation between percent turf and percent developed land, percent turf in the watershed typically increases with percent development, and the amount of development can be considered a reasonable predictor of the amount of turf cover in the watershed. In the BB-LEH watershed, calculated concentrations of TN and TP were greater for developed–turf areas than for developed–nonturf areas, which, in turn, were greater than those for undeveloped areas.

New Jersey↗

USGS2018

A case study and a meta-analysis of seasonal variation in fish mercury concentrations

Mercury contamination in aquatic ecosystems is a concern due to health risks of consuming fish. Fish mercury concentrations are highly variable and influenced by a range of environmental factors. However, seasonal variation in mercury levels are typically overlooked when monitoring fish mercury concentrations, establishing consumption advisories, or creating accumulation models. Temporal variation in sampling could bias mercury concentration estimates of accumulation potential. Thus, the objectives of this study were to first evaluate seasonal variation of largemouth bass ( Micropterus salmoides ) axial muscle mercury concentration from two Iowa, USA impoundments. Second, we conducted a meta-analysis to evaluate if seasonal variation in mercury concentration is dependent upon mean mercury concentration, waterbody type, or fish trophic level or mean length. Largemouth bass were collected four times between May and October (24–36 fish per month) from Twelve Mile (2013) and Red Haw (2014) lakes. Largemouth bass axial muscle mercury concentrations were variable within and between lakes, ranging from undetectable ( < 0.05 mg/kg) to 0.54 mg/kg. Largemouth bass mercury concentrations were similar across months in Twelve Mile but varied temporally in Red Haw and were highest in July, intermediate in May and September, and lowest during October. Results of the meta-analysis suggest that seasonal variation in mercury concentrations is more likely to occur as mean mercury concentration of the population increases but is unrelated to waterbody type, trophic status, and fish size. Understanding seasonal variation in fish mercury concentrations will aid in the development of standardized sampling programs for long-term monitoring programs and fish consumption advisories.

Iowa↗

USGS2019

The dependence of hydroclimate projections in snow‐dominated regions of the western United States on the choice of statistically downscaled climate data

We assess monthly temperature and precipitation data produced by four statistically based techniques that were used to downscale general circulation models (GCMs) in the Climate Model Intercomparison Program Phase 5 (CMIP5) (Taylor et al., 2012). We drive a simple water-balance model with the downscaled data to demonstrate the effect of the methods on the cold season hydrology of three, snow dominated regions in the western U.S. Independent of substantial variation among the GCM simulations over the regions (maximum range of ~3.5 °C and 50% change in precipitation), the four methods produce disparate high resolution representations of the magnitude and spatial patterns of future temperature and precipitation simulated by the models that range for up to ~3 °C and 30% change in precipitation that propagate into the hydrologic simulations. Temperature-dependent snowfall, accumulation, and melt in the model are sensitive to how atmospheric lapse rates are applied in the gridded observations that are used to remove the bias in raw GCM temperatures. By the end of the century the same downscaling method (Bias Corrected Spatial Disaggregation) yields a loss of cold-season snowpack of 34% over the Greater Yellowstone Area under a constant lapse rate ( 6.5°C km-1), whereas spatially variable lapse rates nearly double the loss to 66%, highlighting the roll of both lapse rates and high elevation stations in the bias correction dataset. The two newest downscaling methods (Multivariate Adaptive Constructed Analogs and Localized Constructed Analogs) preserve the magnitude of change simulated GCMs better than the other methods and the produce comparable hydrologic projections. Because the downscaled data from the methods vary spatially and by GCM, the downscaled data should be evaluated carefully as part of the process of using downscaled climate products to drive hydrological models over the area of interest.

Arizona, California, Colorado, Idaho, Montana,Neva↗

USGS2016

Changes in seasonal climate outpace compensatory density-dependence in eastern brook trout

Understanding how multiple extrinsic (density-independent) factors and intrinsic (density-dependent) mechanisms influence population dynamics has become increasingly urgent in the face of rapidly changing climates. It is particularly unclear how multiple extrinsic factors with contrasting effects among seasons are related to declines in population numbers and changes in mean body size and whether there is a strong role for density-dependence. The primary goal of this study was to identify the roles of seasonal variation in climate driven environmental direct effects (mean stream flow and temperature) versus density-dependence on population size and mean body size in eastern brook trout (Salvelinus fontinalis). We use data from a 10-year capture-mark-recapture study of eastern brook trout in four streams in Western Massachusetts, USA to parameterize a discrete-time population projection model. The model integrates matrix modeling techniques used to characterize discrete population structures (age, habitat type and season) with integral projection models (IPMs) that characterize demographic rates as continuous functions of organismal traits (in this case body size). Using both stochastic and deterministic analyses we show that decreases in population size are due to changes in stream flow and temperature and that these changes are larger than what can be compensated for through density-dependent responses. We also show that the declines are due mostly to increasing mean stream temperatures decreasing the survival of the youngest age class. In contrast, increases in mean body size over the same period are the result of indirect changes in density with a lesser direct role of climate-driven environmental change.

Massachusetts↗

USGS2022

The thermal landscape of the Willamette River—Patterns and controls on stream temperature and implications for flow management and cold-water salmonids

Water temperature is a primary control on the health, diversity, abundance, and distribution of aquatic species, but thermal degradation resulting from anthropogenic influences on rivers is a challenge to threatened species worldwide. In the Willamette River Basin, northwestern Oregon, spring-run Chinook salmon ( Oncorhynchus tshawytscha ) and winter-run steelhead ( O. mykiss ) are formerly abundant cold-water-adapted species that are now protected under the Endangered Species Act. Among the challenges to the health of cold-water salmonids in the Willamette River Basin, disruptions in the seasonal patterns of stream temperature imposed by 13 large, multipurpose dams on tributaries to the Willamette River, as well as temperatures routinely in excess of regulatory limits in the Willamette River Basin, are contributing factors. To better understand controls on stream temperature, the sensitivity of stream temperature to flow augmentation as a management tool for suppressing high temperatures, and the implications for threatened salmonids, this study used a two-dimensional hydrodynamic and water-quality model (CE-QUAL-W2) to investigate spatial and temporal patterns of stream temperature in the Willamette River Basin. This study focused on the upper 160.4 river miles of the Willamette River from the confluence of the Middle Fork and Coast Fork Willamette Rivers (river mile 187.2) to Willamette Falls (river mile 26.8), three representative climate years (2011, a cool and wet year; 2015, an extremely hot and dry year; and 2016, a moderately hot and dry year), and a series of flow-augmentation scenarios. Model results show that the Willamette River upstream from Willamette Falls is divisible into four characteristic “thermal reaches” with similar thermal patterns, depending on tributary input, warming rate, and the timing of thermal response. In general, the Willamette River warms downstream during spring and summer, but patterns are complex, influenced by tributary inflows, and seasonally variable. Except in cool wet years (as illustrated by 2011), modeling suggests that adversely warm conditions for spring-run Chinook salmon are extensive from June or July through August. The thermal influence of flow augmentation from dam storage on four tributaries with U.S. Army Corps of Engineers dams varies spatially along the Willamette River, seasonally, and in magnitude, depending on a range of factors like distance from the Willamette River, the temperature of dam outflow, and the thermal template of tributary reaches controlling stream temperature adjustment to environmental heat fluxes. Modeling suggests that targeted flow management (via augmentation from dam storage) can reduce the extent and duration of thermally stressful conditions for Chinook salmon for short periods, but modeling suggests that flow augmentation is limited in its ability to fundamentally alter the “thermal landscape” (the entire range of temperature variation in a river system over space and time) of the Willamette River. While this research provides general insights into the thermal landscape of the Willamette River and its sensitivity to flow management, additional investigation into the thermal landscape of tributaries downstream from U.S. Army Corps of Engineers dams, as well as the thermal management of reservoirs, storage availability, and dam outflows, would be necessary to target specific management actions for supporting specified rearing or migration conditions for spring-run Chinook salmon and other cold-water-adapted species in the Willamette River Basin.

Oregon↗

USGS2025

Determining low-flow conditions at select streams to Barnegat Bay-Little Egg Harbor as the first step towards the development of ecological-flow targets

Maintaining streamflow to support human water needs and ecosystem services requires a fundamental understanding of the relations between changes in streamflow processes and ecosystem responses. Changes in the natural patterns in flow, geology, and topography alter the habitats that aquatic organisms rely on for food, shelter, and reproduction. The U.S. Geological Survey (USGS) implemented an ecological-flow framework that encapsulates the basic principles of the Ecological Limits of Hydrologic Alteration (ELOHA) to compare the relations between hydrologic metrics and stream conditions and estimate ecological flow needs in the Barnegat Bay-Little Egg Harbor watershed. As a first step in the ELOHA process, streamflow from two historical time periods (occurring between 1933 and 1988) was compared to streamflow for a recent time period (from 2004-2020) for four major streams in the Barnegat Bay-Little Egg Harbor watershed (North Branch Metedeconk River, Toms River, Cedar Creek, and Westecunk Creek), to evaluate if there were statistically significant differences in streamflow metrics. Analysis of monthly, seasonal, and annual low-flow metrics; patterns in the streamflow record; and general land-use changes were used to develop a better understanding of flow conditions in the watershed. The comparative streamflow analysis indicated that notable changes in flow processes for the study streams occurred between the three periods of record (PORs) evaluated in this study: period of record 1 (POR1, from water years 1933–1958), period of record 2 (POR2, from water years 1974–1988), and period of record 3 (POR3, from water years 2004–2020). For example, the mean of the daily streamflow decreased between the historical POR to the current POR in Cedar Creek but increased in North Branch Metedeconk and Toms Rivers. Larger and more significant changes (p-value <0.10) occurred during specific months or were related to the variability or seasonality of flow. North Branch Metedeconk River and Toms River, the two northern and most developed sites, exhibited changes in low-flow metrics and decreases in minimum n-day moving averages. Decreases in the normalized 75th-percentile exceedance flows were evident at three of the four study sub-basins during POR2 and POR3. In comparison, there was little to no evidence of negative changes to low-flow metrics at Westecunk Creek, the southernmost and least developed site, where all low-flow duration metrics increased as well as seasonal minimum consecutive 7-day average flows. Significant increases in monthly minimums (p-value <0.05) at Cedar Creek for spring months (April, May, and June) also were observed. Natural and anthropogenic processes can alter the landscape resulting in concomitant changes in the streamflow regime. There is a need to assess these changes and synthesize the results into a scientifically defensible set of goals and standards that help support the management of environmental flows. This study represents the initial steps in building the hydrologic foundation to inform management and develop future ecological flow targets that balance water availability for human and ecosystem needs in the Barnegat Bay-Little Egg Harbor watershed.

New Jersey↗

USGS2022

Choosing an optimal duck season: Integrating hunter values and duck abundance

State wildlife agencies have long struggled to identify optimal hunting season dates for migratory game bird species that meet the diverse and often competing interests of stakeholders. Many approaches have been used to ensure the regulated community participates in the decision-making process, including public hearings, hunter season-date preference surveys, and hunter task forces or committees. Although hearings, surveys, and task force approaches include portions of the regulated community (typically the most avid) they may not necessarily reflect the opinions and values of all stakeholders. Additionally, these approaches rely heavily on limited anecdotal observations that may be unduly influenced by hunter avidity (e.g., days spent afield), hunter density, species preferences, and property access. To address the challenges caused by engaging only portions of the stakeholder community, we used a structured decision-making framework that included a 2017 duck hunter survey to elucidate values of a representative sample of the regulated community in each waterfowl hunting zone in the state of New York, USA. Rather than asking duck hunters about their specific duck hunting season date preferences, we asked them to rank 6 objectives describing what they value in their hunting experience (e.g., maximizing the opportunity to see mallards [ Anas platyrhynchos ] and black ducks [ Anas rubripes ], maximizing the number of weekend days). Four of the 6 objectives described duck species availability (i.e., abundance or immigration) and the remaining 2 described considerations that affect an individual hunter's opportunity or limitation to going duck hunting (i.e., holidays or conflicting hunting seasons). We used spatiotemporal abundance models derived from eBird citizen science data to estimate abundance and immigration rates of ducks in each waterfowl zone. We evaluated up to 9 unique season date alternatives developed by duck hunter task forces to determine which season date alternative best satisfied the competing objectives of duck hunters in each zone. The approach we developed allowed for selection of optimal duck hunting season dates and successfully involved avid duck hunters in the regulation development stages, while ensuring that the values of a representative sample of all stakeholders were directly considered through a clear and transparent decision-making process.

New York↗

USGS2008

Modeling variability and trends in pesticide concentrations in streams

A parametric regression model was developed for assessing the variability and long-term trends in pesticide concentrations in streams. The dependent variable is the logarithm of pesticide concentration and the explanatory variables are a seasonal wave, which represents the seasonal variability of concentration in response to seasonal application rates; a streamflow anomaly, which is the deviation of concurrent daily streamflow from average conditions for the previous 30 days; and a trend, which represents long-term (inter-annual) changes in concentration. Application of the model to selected herbicides and insecticides in four diverse streams indicated the model is robust with respect to pesticide type, stream location, and the degree of censoring (proportion of nondetections). An automatic model fitting and selection procedure for the seasonal wave and trend components was found to perform well for the datasets analyzed. Artificial censoring scenarios were used in a Monte Carlo simulation analysis to show that the fitted trends were unbiased and the approximate p-values were accurate for as few as 10 uncensored concentrations during a three-year period, assuming a sampling frequency of 15 samples per year. Trend estimates for the full model were compared with a model without the streamflow anomaly and a model in which the seasonality was modeled using standard trigonometric functions, rather than seasonal application rates. Exclusion of the streamflow anomaly resulted in substantial increases in the mean-squared error and decreases in power for detecting trends. Incorrectly modeling the seasonal structure of the concentration data resulted in substantial estimation bias and moderate increases in mean-squared error and decreases in power. ?? 2008 American Water Resources Association.

Journal of the American Water Resources Associatio↗

USGS1988

Food availability controls seasonal cycle of growth in Macoma balthica (L.) in San Francisco Bay, California

A 2-yr field study of growth in the bivalve Macoma balthica (L.) at four locations in San Francisco Bay, California, U.S., showed that the timing and rate of growth (increase in shell length) were related to food supply. This clam feeds on both planktonic and benthic microalgae, depending on availability. Growth was apparently food-limited during some months, during one year more than the other, and at some locations more than others. Tissue-weight changes were also related to food availability. The heaviest animals were found in that year and at those locations with the highest chl a concentrations. Tissue-weight gains usually coincided with increased shell-growth rate or with reproductive development, although some large animals showed weight gain independent of both of these factors during periods with mid-range chl a levels. Weight losses coincided with spawning or periods of low growth rate, except at one station where, during a period when most animals were reproductively ripe, food concentrations were high, and shell growth was rapid, animals lost weight. This study failed to show a relation between salinity and the timing or rate of change of either shell length or tissue weight. The mild temperatures (10-23 ??C water temperature) of the area studied resulted in no growth inhibition due to low temperature, but there was some indication that the high air temperatures found in these intertidal areas limited growth rates. ?? 1988.

Journal of Experimental Marine Biology and Ecology↗

USGS1999

The effect of frozen soil on snowmelt runoff at Sleepers River, Vermont

Soil frost depth has been monitored at the Sleepers River Research Watershed in northeastern Vermont since 1984. Soil frost develops every winter, particularly in open fields, but its depth varies greatly from year to year in inverse relation to snow depth. During the 15 years of record at a benchmark mid-elevation open site, the annual maximum frost depth varied from 70 to 390 mm. We empirically tested the hypothesis that frozen soil prevents infiltration and recharge, thereby causing an increased runoff ratio (streamflow/(rain+snowmelt)) during the snowmelt hydrograph rise and a decreased runoff ratio during snowmelt recession. The hypothesis was not supported at the 111 km 2 W-5 catchment; there was no significant correlation of the runoff ratio with the seasonal maximum frost depth for either the pre-peak or post-peak period. In an analysis of four events, however, the presence of frost promoted a large and somewhat quicker response to rainfall relative to the no-frost condition, although snow cover caused a much greater time-to-peak regardless of frost status. For six years of flow and frost depth measured at the 59 ha agricultural basin W-2, the hypothesis appeared to be supported. The enhancement of runoff due to soil frost is evident on small plots and in extreme events, such as rain on frozen snow-free soil. In the northeastern USA and eastern Canada, the effect is often masked in larger catchments by several confounding factors, including storage of meltwater in the snowpack, variability in snowmelt timing due to elevational and aspect differences, interspersed forested land where frost may be absent, and the timing of soil thawing relative to the runoff peak.

Hydrological Processes↗

USGS2010

A model to forecast short-term snowmelt runoff using synoptic observations of streamflow, temperature, and precipitation

Snowmelt runoff is forecast with a statistical model that utilizes daily values of stream discharge, gaged precipitation, and maximum and minimum observations of air temperature. Synoptic observations of these variables are made at existing low- and medium-altitude weather stations, thus eliminating the difficulties and expense of new, high-altitude installations. Four model development steps are used to demonstrate the influence on prediction accuracy of basin storage, a preforecast test season, air temperature (to estimate ablation), and a prediction based on storage. Daily ablation is determined by a technique that employs both mean temperature and a radiative index. Radiation (both long- and short-wave components) is approximated by using the range in daily temperature, which is shown to be closely related to mean cloud cover. A technique based on the relationship between prediction error and prediction season weather utilizes short-term forecasts of precipitation and temperature to improve the final prediction. Verification of the model is accomplished by a split sampling technique for the 1960–1977 period. Short- term (5–15 days) predictions of runoff throughout the main snowmelt season are demonstrated for mountain drainages in western Washington, south-central Arizona, western Montana, and central California. The coefficient of prediction ( C p ) based on actual, short-term predictions for 18 years is for Thunder Creek (Washington), 0.69; for South Fork Flathead River (Montana), 0.45; for the Black River (Arizona), 0.80; and for the Kings River (California), 0.80.

Water Resources Research↗

USGS2006

Physical habitat classification and instream flow modeling to determine habitat availability during low-flow periods, North Fork Shenandoah River, Virginia

Increasing development and increasing water withdrawals for public, industrial, and agricultural water supply threaten to reduce streamflows in the Shenandoah River basin in Virginia. Water managers need more information to balance human water-supply needs with the daily streamflows necessary for maintaining the aquatic ecosystems. To meet the need for comprehensive information on hydrology, water supply, and instream-flow requirements of the Shenandoah River basin, the U.S. Geological Survey and the Northern Shenandoah Valley Regional Commission conducted a cooperative investigation of habitat availability during low-flow periods on the North Fork Shenandoah River. Historic streamflow data and empirical data on physical habitat, river hydraulics, fish community structure, and recreation were used to develop a physical habitat simulation model. Hydraulic measurements were made during low, medium, and high flows in six reaches at a total of 36 transects that included riffles, runs, and pools, and that had a variety of substrates and cover types. Habitat suitability criteria for fish were developed from detailed fish-community sampling and microhabitat observations. Fish were grouped into four guilds of species and life stages with similar habitat requirements. Simulated habitat was considered in the context of seasonal flow regimes to show the availability of flows that sustain suitable habitat during months when precipitation and streamflow are scarce. The North Fork Shenandoah River basin was divided into three management sections for analysis purposes: the upper section, middle section, and lower section. The months of July, August, and September were chosen to represent a low-flow period in the basin with low mean monthly flows, low precipitation, high temperatures, and high water withdrawals. Exceedance flows calculated from the combined data from these three months describe low-flow periods on the North Fork Shenandoah River. Long-term records from three streamflow-gaging stations were used to characterize the flow regime: North Fork Shenandoah River at Cootes Store, Va. (1925-2002), North Fork Shenandoah River at Mount Jackson, Va. (1943-2002), and North Fork Shenandoah River near Strasburg, Va. (1925-2002). The predominant mesohabitat types (14 percent riffle, 67.3 percent run, and 18.7 percent pool) were classified along the entire river (100 miles) to assist in the selection of reaches for hydraulic and fish community data collection. The upper section has predominantly particle substrate, ranging in size from sand to boulders, and the shortest habitat units. The middle section is a transitional section with increased bedrock substrate and habitat unit length. The lower section has predominantly bedrock substrate and the longest habitat units in the river. The model simulations show that weighted usable-habitat area in the upper management section is highest at flows higher than the 25-percent exceedance flow for July, August, and September. During these three months, total weighted usable-habitat area in this section is often less than the simulated maximum weighted usable-habitat area. Habitat area in the middle management section is highest at flows between the 25- and 75-percent exceedance flows for July, August, and September. In the middle section during these months, both the actual weighted usable-habitat area and the simulated maximum weighted usable-habitat area are associated with this flow range. Weighted usable-habitat area in the lower management section is highest at flows lower than the 75-percent exceedance flow for July, August, and September. In the lower section during these three months, some weighted usable-habitat area is available, but the normal range of flows does not include the simulated maximum weighted usable-habitat area. A time-series habitat analysis associated with the historic streamflow, zero water withdrawals, and doubled water withdrawals was completed. During s

Scientific Investigations Report↗

USGS1988

Experimental Mycoplasma gallisepticum infections in captive-reared wild turkeys

The effects of Mycoplasma gallisepticum (MG) infections on egg production, fertility, and hatchability were studied in captive-reared wild turkeys ( Meleagris gallopavo ). Three groups of adult birds, each consisting of four hens and two toms, were exposed to MG by the respiratory route at the beginning of their breeding season. Fourteen control birds received sterile growth medium. Although no mortality of infected or control birds occurred, egg production during the first breeding season after infection was reduced. The mean number of eggs/hen/day produced by infected groups the first breeding season postexposure (PE) was significantly lower than the control value. The mean number of eggs produced daily by the same hens 1 yr later was unaffected by MG infection. The pecentage of fertile eggs produced by infected groups was slightly reduced in both the first and second breeding seasons PE. Hatchability of fertile eggs from infected hens was significantly lower than eggs from control hens. Productivity may be impaired if MG infections occur in free-ranging wild turkey populations.

Journal of Wildlife Diseases↗

USGS2011

Comparison and analysis of empirical equations for soil heat flux for different cropping systems and irrigation methods

We evaluated the performance of four models for estimating soil heat flux density (G) in maize (Zea mays L.) and soybean (Glycine max L.) fields under different irrigation methods (center-pivot irrigated fields at Mead, Nebraska, and subsurface drip irrigated field at Clay Center, Nebraska) and rainfed conditions at Mead. The model estimates were compared against measurements made during growing seasons of 2003, 2004, and 2005 at Mead and during 2005, 2006, and 2007 at Clay Center. We observed a strong relationship between the G and net radiation (Rn) ratio (G/Rn) and the normalized difference vegetation index (NDVI). When a significant portion of the ground was bare soil, G/Rn ranged from 0.15 to 0.30 and decreased with increasing NDVI. In contrast to the NDVI progression, the G/Rn ratio decreased with crop growth and development. The G/Rn ratio for subsurface drip irrigated crops was smaller than for the center-pivot irrigated crops. The seasonal average G was 13.1%, 15.2%, 10.9%, and 12.8% of Rn for irrigated maize, rainfed maize, irrigated soybean, and rainfed soybean, respectively. Statistical analyses of the performance of the four models showed a wide range of variation in G estimation. The root mean square error (RMSE) of predictions ranged from 15 to 81.3 W m-2. Based on the wide range of RMSE, it is recommended that local calibration of the models should be carried out for remote estimation of soil heat flux.

Transactions of the ASABE↗

USGS2023

Train, inform, borrow, or combine? Approaches to process-guided deep learning for groundwater-influenced stream temperature prediction

Although groundwater discharge is a critical stream temperature control process, it is not explicitly represented in many stream temperature models, an omission that may reduce predictive accuracy, hinder management of aquatic habitat, and decrease user confidence. We assessed the performance of a previously-described process-guided deep learning model of stream temperature in the Delaware River Basin (USA). We found lower accuracy (root mean square error [RMSE] of 1.71 versus 1.35°C) and stronger seasonal bias (absolute mean monthly bias of 1.06 vs. 0.68°C) for reaches primarily influenced by deep groundwater as compared to atmospheric conditions. We then tested four approaches for improving groundwater process representation: (a) a custom loss function leveraging the unique patterns of air and water temperature coupling characteristic of different temperature drivers, (b) inclusion of additional groundwater-relevant catchment attributes, (c) incorporation of additional process model outputs, and (d) a composite model. The custom loss function and the additional attributes significantly improved the predictive accuracy in groundwater-dominated reaches (RMSE of 1.37 and 1.26°C) and reduced the seasonal bias (absolute mean monthly bias of 0.44 and 0.48°C), but neither approach could identify holdout groundwater reaches. Variable importance analysis indicates the custom loss function nudges the model to use the existing inputs more efficiently, whereas with the added features the model relies on a broader suite of inputs. This analysis is a substantial step toward more accurately representing groundwater discharge processes in stream temperature models and will improve predictive accuracy and inform habitat management.

Delaware River Basin↗

USGS2016

Mixed stock analysis of Lake Michigan's Lake Whitefish Coregonus clupeaformis commercial fishery

Lake whitefish ( Coregonus clupeaformis ) support the primary commercial fishery in Lake Michigan. Discrete genetic stocks of lake whitefish have been identified and tagging data suggest stocks are mixed throughout much of the year. Our objectives were to determine if (1) differential stock harvest occurs in the commercial catch, (2) spatial differences in genetic composition of harvested fish were present, and (3) seasonal differences were present in the harvest by commercial fisheries that operate in management zones WI-2 and WFM-01 (Green Bay, Lake Michigan). Mixed stock analysis was conducted on 17 commercial harvest samples (n = 78–145/sample) collected from various ports lake-wide during 2009–2010. Results showed significant mixing with variability in stock composition across most samples. Samples consisted of two to four genetic stocks each accounting for ≥ 10% the catch. In 10 of 17 samples, the stock contributing the largest proportion made up < 60% of the harvest. In general, seasonal and annual differences existed in the proportional stock contribution at a single capture location. Samples from Wisconsin's primary commercial fishing management zone (WI-2) were composed predominately of fish from the Big Bay de Noc (Michigan) stock as opposed to the geographically proximate, North–Moonlight Bay (Wisconsin) stock. These findings have implications for management and allocation of fish to various quotas. Specifically, geographic location of harvest, the current means of allocating harvest quotas, is not the best predictor of genetic stock harvest.

Lake Michigan↗

USGS1964

Supergene iron ores of minas Gerais, Brazil

The iron ores of Minas Gerais , Brazil , fall into two categories: (1) hypogene hematite ore averaging 66 percent or more Fe, and (2) lower-grade supergene ores . Most ore now extracted is high-grade hypogene ore ; lower-grade supergene ores will be of much future value. All supergene ores formed by weathering of itabirite, a metamorphosed oxide-facies iron formation averaging about 38 percent Fe and 44 percent Si02. The Caue Itabirite crops out for about 540 linear kilometers in central Minas Gerais . Supergene ores fall into three intergradational categories: (1) enriched itabirite, averaging 49 percent Fe, easily con-centratable, with reserves about 25,000 million tons; (2) intermediate grade ores , averaging perhaps 63 percent Fe, with indicated and inferred reserves more than 600 million tons; and (3) canga, averaging between 57 and 62 percent Fe, with reserves in the hundreds of millions of tons. Disaggregation of hard and brittle itabirite by solution primarily of quartz and secondarily of other soluble constituents causes residual enrichment in iron with minor hydration of hematite. As weathering continues, most of the quartz is removed and more of the hematite is hydrated, producing intermediate grade ore . Secondary enrichment by limonite is important. The final weathering product is canga. In canga, almost all the iron is hydrated, and the rock is still further impoverished in Si02 and residually enriched in A1203 and P. Canga also forms by cementation of iron -rich detritus by limonite. Four factors control the supergene ore -forming process: (1) physiography, for ores occur on ridges and plateaus; (2) climate, for seasonal rainfall is apparently needed for the formation of extensive canga blankets; (3) grain size of the original itabirite, for quartz with a grain size much greater than 0.1 millimeter is not readily soluble; and (4) composition of the iron formation. The chemically inert and physically resistant canga blanket is essential to supergene ore formation because soft weathering products would otherwise be removed as fast as formed. Thus, canga gives time for the formation of other ore types. Iron fixed as cementing limonite in canga and as enriching limonite in intermediate grade ore was derived by leaching and hydration of hematite from itabirite. It probably moved in the ferrous state and was precipitated as insoluble hydrous ferric oxide primarily by oxygenation of the solutions, to a lesser extent by their evaporation at or near the surface, and to a still smaller degree by pH changes. The data show that the high-grade hematite ore , 66 percent Fe or higher, cannot have formed directly by supergene action. Geochemical processes resulting in supergene concentration of iron also concentrated alumina and phosphorus. The high-grade ore contains about the same low percentages of these materials as unweathered itabirite.

Minas Gerais↗

USGS2014

Effects of land use, stream habitat, and water quality on biological communities of wadeable streams in the Illinois River Basin of Arkansas, 2011 and 2012

The Illinois River Basin includes an area of diverse land use in northwestern Arkansas. Land-use data collected in 2006 indicate that most of the land in the basin is agricultural. The agricultural land is used primarily for production of poultry and cattle. Eighteen sites were selected from the list of candidate sites based on drainage area, land use, presence or absence of an upstream wastewater-treatment plant, water quality, and other information gathered during the reconnaissance. An important consideration in the process was to select sites along gradients of forest to urban land use and forest to agricultural land use. Water-quality samples were collected for analysis of nutrients, and a multiparameter field meter was used to measure water temperature, specific conductance, pH, and dissolved oxygen. Streamflow was measured immediately following the water-quality sampling. Macroalgae coverage was estimated and periphyton, macroinvertebrate, and fish communities were sampled at each site. Stream habitat also was assessed. Many types of land-use, water-quality, and habitat factors affected one or more aspects of the biological communities. Several macroinvertebrate and fish metrics changed in response to changes in percent forest; sites that would be considered most disturbed, based on these metrics, are sites with the highest percentages of urban land use in their associated basins. The presence of large mats of macroalgae was one of the most noticeable biological characteristics in several streams within the Illinois River Basin. The highest macroalgae percent cover values were recorded at four sites downstream from wastewater-treatment plants. Macroalgae percent cover was strongly correlated only with bed substrate size, canopy closure, and specific conductance. Periphyton metrics were most often and most strongly correlated with riparian shading, specific conductance, substrate turbidity, percent agriculture, poultry house density, and unpaved road density; some of these factors were strongly correlated with percent forest, percent urban, or percent agriculture. Total biovolume of periphyton was not strongly correlated with any of the land use, habitat, or water-quality factors assessed in the present study. Although algal growth typically increases with higher nutrient concentrations and less shading, the standing crop of periphyton on rocks can be reduced by herbivorous macroinvertebrates and fish, which may explain why total biovolume in Ozark streams was not strongly affected by water-quality (or other habitat) factors. A macroinvertebrate index and several macroinvertebrate metrics were adversely affected by increasing urban and agricultural land use and associated environmental factors. Factors most commonly affecting the index and metrics included factors associated with water quality, stream geometry, sediment, land-use percentages, and road density. In general, the macroinvertebrate index was higher (indicative of least disturbance) at sites with greater percentages of forest in their basins, lower percentages of urban land in their basins, and lower paved road density. Upstream wastewater-treatment plants affected several metrics. For example, three of the five lowest macroinvertebrate index scores, two of the five lowest percent predator values, and two of the five highest percent gatherer-collector values were at sites downstream from wastewater-treatment plants. The Ozark Highlands fish index of biotic integrity and several fish metrics were adversely affected by increasing urban and agricultural land use and associated factors. Factors affecting these metrics included factors associated with nutrients, sediment, and shading. In general, the fish index of biotic integrity was higher at sites with higher percentages of forest in their basins, lower percentages of urban land in their basins, higher unpaved road density, and lower paved and total road density. Upstream wastewater-treatment plants seemed to affect some fish community metrics substantially but had little effect on other metrics. For example, three of the five lowest relative abundances of lithophilic spawner minus stonerollers and four of the five highest stoneroller abundances were at sites downstream from wastewater-treatment plants. Interpretations of the results of the study described in this report are limited by a number of factors. These factors individually and collectively add to uncertainty and variability in the responses to various environmental stresses. Notwithstanding the limiting factors, the biological responses of macroalgae cover and periphyton, macroinvertebrate, and fish metrics to environmental variables provide multiple lines of evidence that biological communities of these streams are affected by recent and ongoing land-use practices. For several biological metrics there appears to be a threshold of about 40 to 50 percent forest where values of these metrics change in magnitude. However, the four sites with more than 50 percent forest in their basins were the four sites sampled in late May–early June of 2012 (rather than July–August of 2011). The relative influence of season and forest percentage on the biological communities at these sites is unknown.

Arkansas↗