SEARCH · Search USGS

Results for “Aggregates Manager”

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 415 records · Page 23Linked to original sources

USGS2019

Ligation and division of ductus deferens does not produce long term sterility in most bighead carp or grass carp

Invading species are most easily eradicated or controlled if detected early and rapid action can be taken, but locating and eradicating small numbers of aquatic invaders is extremely difficult. Bighead carp ( Hypophthalmichthys nobilis ) and grass carp ( Ctenopharyngodon idella ) are Asian cyprinids that have been widely introduced and are considered undesirable and detrimental invasive species in many parts of their introduced range. The relatively novel “Judas fish” technique is used to locate aggregations of fish in the wild by strategically releasing individuals equipped with surgically implanted transmitters. However, releasing Judas fish that are capable of reproducing is problematic because it could add to the invasion problem by contributing to recruitment if not recaptured. We thus tested whether surgical ligation and division of the ductus deferens could effectively sterilize adult diploid bighead and grass carp. If effective, surgical sterilization would result in a superior Judas fish by maintaining the reproductive motivation derived from intact gonads while blocking the reproductive potential. This technique was initially successful, but ultimately most individuals were able to recanalize the surgically-severed ducts and produce milt, and were thus potentially able to reproduce during the following spawning season. Thus, ligation and division of the ductus deferens does not seem to be a viable procedure to sterilize bighead carp or grass carp for deployment as Judas fish where long term sterility of the fish is paramount in importance.

Missouri↗

USGS2023

Status and trends of pelagic and benthic prey fish populations in Lake Michigan, 2022

Fall bottom trawl (fall BT) and lakewide acoustic (AC) surveys are conducted annually to generate indices of pelagic and benthic prey fish densities in Lake Michigan. The fall BT survey has been conducted each fall since 1973 using 12-m trawls at depths ranging from 9 to 110 m at fixed locations distributed across seven transects; this survey estimates densities of seven prey fish species [i.e., Alewife (Alosa pseudoharengus), Bloater ( Coregonus hoyi ), Rainbow Smelt ( Osmerus mordax ), Deepwater Sculpin ( Myoxocephalus thompsonii ), Slimy Sculpin ( Cottus cognatus ), Round Goby ( Neogobius melanostomus ), Ninespine Stickleback ( Pungitius pungitius )] as well as age-0 Yellow Perch ( Perca flavescens ) and large (> 350 mm) Burbot ( Lota lota ). The AC survey has been conducted each late summer/early fall since 2004, and the 2022 survey consisted of 26 transects [570 km total (354 miles)] covering bottom depths ranging from 5 to 255 m and 37 midwater trawl tows above bottom depths ranging 5 to 232 m; this survey estimates densities of three prey fish species (i.e., Alewife, Bloater, and Rainbow Smelt). The data generated from these surveys are used to estimate various population parameters that are, in turn, used by state and tribal agencies in managing Lake Michigan fish stocks. In spring of 2022, an additional spring bottom trawl survey (spring BT) was implemented across six of the transects sampled in the fall and sites ranged in depth from 9 to 236 m. The goal of the spring BT was to explore seasonal differences in biomass density and distributions of key prey species, mostly notably Alewife. Total prey fish biomass density from the spring BT was 2.1 kg/ha. For the AC survey, total biomass density of prey fish equaled 6.2 kg/ha, 37% higher than the long-term average (2004-2021) of 4.5 kg/ha and 0.43 kg/ha higher than the 2021 estimate. For the fall BT, total biomass density of prey fish equaled 8.7 kg/ha, the highest value since 2013 and 21% higher than average value from 20042021 (6.8 kg/ha). The 2022 fall BT biomass density was still well below the average over the entirety of the time series (1973-2021; 34.3 kg/ha). Over the period both surveys have been conducted (2004-2021), total biomass density has trended downward in the fall BT (despite a high 2022 estimate) and remained relatively stable in the AC survey. Bloater was the dominant species (by biomass) among prey fishes in both the spring and fall BT, while the AC survey reported co-dominance of Bloater and Alewife. Mean biomass of yearling and older (YAO) Alewife was 0.38 kg/ha in the spring BT, 3.0 kg/ha in the AC survey, and 0.10 in the fall BT. Alewife were aggregated in deepwater habitats in the spring of 2022 (> 110 m). Since 2014, catchability of YAO Alewives for the fall BT has been substantially lower than the AC survey. Results of the 2022 spring BT do not suggest that catchability is substantially higher in the spring than the fall. Comparing the acoustic estimate to previous years, YAO Alewife biomass was 40% higher than the average from 2004-2021. An age-7 fish was recorded for the first time since 2009. Despite the rare catches of older fish, the Alewife age distribution still appears truncated, with age-1 fish as the most represented age class in all three surveys. Numeric density of age-0 Alewife from the AC survey was 7 fish/ha in 2022, which is the third lowest in the time series and well below the longterm mean of 452 fish/ha. Biomass density of large (≥120 mm) Bloater was 2.7 kg/ha in the AC survey and 4.4 kg/ha in the fall BT - each at least an order of magnitude lower than what was estimated by the fall BT between 1981 and 1998. Following a record high year in 2021 (1,037 fish/ha), the numeric density of small (<120 mm) Bloater was only 15 fish/ha in the AC survey. Meanwhile, small Bloater density estimated in the fall BT was 261 fish/ha, the highest value since 1990 and likely partially reflective of a large 2021 year-class. Biomass density of large Rainbow Smelt (≥90 mm) was 0.29 kg/ha in the AC survey and 0.12 kg/ha in the fall BT survey, continuing the trend of low Rainbow Smelt biomass that has been observed since 2001. Numeric density of small (<90 mm) Rainbow Smelt was 21 fish/ha in the AC survey and 2.7 fish/ha in the fall BT, indicating a weak year-class. All four prey fish species sampled only by the fall BT indicated below average biomass densities. Deepwater Sculpin biomass density was estimated at 0.41 kg/ha, which makes 12 of the past 13 years when biomass was <1 kg/ha. Slimy Sculpin was estimated at 0.10 kg/ha, the highest estimate since 2016 but still only 25% of the long-term average. Round Goby was estimated at 1.3 kg/ha, above the average biomass of 0.82 kg/ha since 2008 but similar to intermittent high values observed throughout the dataset. Ninespine Stickleback density was 1.5 fish/ha. Burbot biomass remained near record low levels, and no age-0 Yellow Perch were caught, indicating a weak Yellow Perch year-class in 2022.

Lake Michigan↗

USGS2002

Aerial survey methodology for bison population estimation in Yellowstone National Park

I developed aerial survey methods for statistically rigorous bison population estimation in Yellowstone National Park to support sound resource management decisions and to understand bison ecology. Survey protocols, data recording procedures, a geographic framework, and seasonal stratifications were based on field observations from February 1998-September 2000. The reliability of this framework and strata were tested with long-term data from 1970-1997. I simulated different sample survey designs and compared them to high-effort censuses of well-defined large areas to evaluate effort, precision, and bias. Sample survey designs require much effort and extensive information on the current spatial distribution of bison and therefore do not offer any substantial reduction in time and effort over censuses. I conducted concurrent ground surveys, or 'double sampling' to estimate detection probability during aerial surveys. Group size distribution and habitat strongly affected detection probability. In winter, 75% of the groups and 92% of individual bison were detected on average from aircraft, while in summer, 79% of groups and 97% of individual bison were detected. I also used photography to quantify the bias due to counting large groups of bison accurately and found that undercounting increased with group size and could reach 15%. I compared survey conditions between seasons and identified optimal time windows for conducting surveys in both winter and summer. These windows account for the habitats and total area bison occupy, and group size distribution. Bison became increasingly scattered over the Yellowstone region in smaller groups and more occupied unfavorable habitats as winter progressed. Therefore, the best conditions for winter surveys occur early in the season (Dec-Jan). In summer, bison were most spatially aggregated and occurred in the largest groups by early August. Low variability between surveys and high detection probability provide population estimates with an overall coefficient of variation of approximately 8% and have high power for detecting trends in population change. I demonstrated how population estimates from winter and summer can be integrated into a comprehensive monitoring program to estimate annual growth rates, overall winter mortality, and an index of calf production, requiring about 30 hours of flight per year.

Wyoming↗

USGS2012

Florida Bay salinity and Everglades wetlands hydrology circa 1900 CE: A compilation of paleoecology-based statistical modeling analyses

Throughout the 20th century, the Greater Everglades Ecosystem of south Florida was greatly altered by human activities. Construction of water-control structures and facilities altered the natural hydrologic patterns of the south Florida region and consequently impacted the coastal ecosystem. Restoration of the Greater Everglades Ecosystem is guided by the Comprehensive Everglades Restoration Plan (CERP), which is attempting to reverse some of the impacts of water management. In order to achieve this goal, it is essential to understand the predevelopment conditions (circa 1900 Common Era, CE) of the natural system, including the estuaries. The purpose of this report is to use empirical data derived from analyses of estuarine sediment cores and observations of modern hydrologic and salinity conditions to provide information on the natural system circa 1900 CE. A three-phase approach, developed in 2009, couples paleosalinity estimates derived from sediment cores to upstream hydrology using statistical models prepared from existing monitoring data. Results presented here update and improve previous analyses. A statistical method of estimating the paleosalinity from the core information improves the previous assemblage analyses, and the system of linear regression models was significantly upgraded and expanded. The upgraded method of coupled paleosalinity and hydrologic models was applied to the analysis of the circa-1900 CE segments of five estuarine sediment cores collected in Florida Bay. Comparisons of the observed mean stage (water level) data to the paleoecology-based model's averaged output show that the estimated stage in the Everglades wetlands was 0.3 to 1.6 feet higher at different locations. Observed mean flow data compared to the paleoecology-based model output show an estimated flow into Shark River Slough at Tamiami Trail of 401 to 2,539 cubic feet per second (cfs) higher than existing flows, and at Taylor Slough Bridge an estimated flow of 48 to 218 cfs above existing flows. For salinity in Florida Bay, the difference between paleoecology-based and observed mean salinity varies across the bay, from an aggregated average salinity of 14.7 less than existing in the northeastern basin to 1.0 less than existing in the western basin near the transition into the Gulf of Mexico. When the salinity differences are compared by region, the difference between paleoecology-based conditions and existing conditions are spatially consistent.

Forida↗

USGS1997

Nesting season food habits of 4 species of herons and egrets at Lake Okeechobee, Florida

Based on the composition of nestling regurgitations collected during 3 breeding seasons, fish were the most important prey group for Great Egrets (Ardea alba: N = 200 nest-day samples; aggregate percent biomass [APB] = 73.4%), Snowy Egrets (Egretta thula: N = 115; APB = 91.4%), and Tricolored Herons (E. tricolor: N = 68; APB = 97.3%). For Little Blue Herons (E. caerulea: N = 57), grass shrimp (Palaemonetes paludosus; APB = 39.7%) ranked higher in overall importance than all fishes combined (APB = 36.5%). Dietary overlap, as measured by Schoener's Similarity Index, was greatest between Snowy Egrets and Tricolored Herons (77%) and lowest between Tricolored Herons and Little Blue Herons (30%). Diet diversity, as measured by Shannon's Index, was highest for Great Egrets (2.04), intermediate for Snowy Egrets (1.71) and Tricolored Herons (1.68), and lowest for Little Blue Herons (1.60). Great Egrets ate a wider variety of fish species and sizes, especially larger fishes, and more crayfish than the other species. Little Blue Herons ate fewer fish and more grass shrimp and insects, and ate smaller forage fishes than Tricolored Herons but similar-sized fish as Snowy Egrets. The coarse-scale trophic composition of Snowy Egret and Tricolored Heron diets did not differ significantly, but Tricolored Herons ate larger forage fishes than Snowy Egrets. Pronounced interannual and intercolony variation in diet composition suggested that Great Egrets and Little Blue Herons switched prey types as hydrologic conditions and habitat availability changed. Conversely, lack of such variation suggested that Snowy Egrets and Tricolored Herons adjusted their foraging tactics to ensure continued encounters with preferred prey despite changing habitat conditions. These results are generally consistent with other published data, help confirm some generalizations about foraging strategies and patterns of niche differentiation among these ecologically similar species, and have implications for managing the Lake Okeechobee ecosystem.

Florida↗

USGS1997

Nesting season food habits of 4 species of Herons and Egrets at Lake Okeechobee, Florida

Based on the composition of nestling regurgitations collected during 3 breeding seasons, fish were the most important prey group for Great Egrets (Ardea alba: N = 200 nest-day samples; aggregate percent biomass [APB] = 73.4%), Snowy Egrets (Egretta thula: N = 115; APB = 91.4%), and Tricolored Herons (E. tricolor. N = 68; APB = 97.3%). For Little Blue Herons (E. caerulerr. N = 57), grass shrimp (Palaemoneles paludosus; APB = 39.7%) ranked higher in overall importance than all fishes combined (APB = 36.5%). Dietary overlap, as measured by Schoener's Similarity Index, was greatest between Snowy Egrets and Tricolored Herons (77%) and lowest between Tricolored Herons and Little Blue Herons (30%). Diet diversity, as measured by Shannon's Index, was highest for Great Egrets (2.04), intermediate for Snowy Egrets (1.71) and Tricolored Herons (1.68), and lowest for Little Blue Herons (1.60). Great Egrets ate a wider variety of fish species and sizes, especially larger fishes, and more crayfish than the other species. Little Blue Herons ate fewer fish and more grass shrimp and insects, and ate smaller forage fishes than Tricolored Herons but similar-sized fish as Snowy Egrets. The coarse-scale trophic composition of Snowy Egret and Tricolored Heron diets did not differ significantly, but Tricolored Herons ate larger forage fishes than Snowy Egrets. Pronounced interannual and intercolony variation in diet composition suggested that Great Egrets and Little Blue Herons switched prey types as hydrologic conditions and habitat availability changed. Conversely, lack of such variation suggested that Snowy Egrets and Tricolored Herons adjusted their foraging tactics to ensure contin-ued encounters with preferred prey despite changing habitat conditions. These results are generally consistent with other published data, help confirm some generalizations about foraging strategies and patterns of niche differentiation among these ecologically similar species, and have implications for managing the Lake Okeechobce ecosystem.

Waterbirds↗

USGS2017

Quantifying site-specific physical heterogeneity within an estuarine seascape

Quantifying physical heterogeneity is essential for meaningful ecological research and effective resource management. Spatial patterns of multiple, co-occurring physical features are rarely quantified across a seascape because of methodological challenges. Here, we identified approaches that measured total site-specific heterogeneity, an often overlooked aspect of estuarine ecosystems. Specifically, we examined 23 metrics that quantified four types of common physical features: (1) river and creek confluences, (2) bathymetric variation including underwater drop-offs, (3) land features such as islands/sandbars, and (4) major underwater channel networks. Our research at 40 sites throughout Plum Island Estuary (PIE) provided solutions to two problems. The first problem was that individual metrics that measured heterogeneity of a single physical feature showed different regional patterns. We solved this first problem by combining multiple metrics for a single feature using a within-physical feature cluster analysis. With this approach, we identified sites with four different types of confluences and three different types of underwater drop-offs. The second problem was that when multiple physical features co-occurred, new patterns of total site-specific heterogeneity were created across the seascape. This pattern of total heterogeneity has potential ecological relevance to structure-oriented predators. To address this second problem, we identified sites with similar types of total physical heterogeneity using an across-physical feature cluster analysis. Then, we calculated an additive heterogeneity index, which integrated all physical features at a site. Finally, we tested if site-specific additive heterogeneity index values differed for across-physical feature clusters. In PIE, the sites with the highest additive heterogeneity index values were clustered together and corresponded to sites where a fish predator, adult striped bass ( Morone saxatilis ), aggregated in a related acoustic tracking study. In summary, we have shown general approaches to quantifying site-specific heterogeneity.

Massachusetts↗

USGS1998

Great Lakes

The Great Lakes region, as defined here, includes the Great Lakes and their drainage basins in Minnesota, Wisconsin, Illinois, Indiana, Ohio, Pennsylvania, and New York. The region also includes the portions of Minnesota, Wisconsin, and the 21 northernmost counties of Illinois that lie in the Mississippi River drainage basin, outside the floodplain of the river. The region spans about 9º of latitude and 20º of longitude and lies roughly halfway between the equator and the North Pole in a lowland corridor that extends from the Gulf of Mexico to the Arctic Ocean. The Great Lakes are the most prominent natural feature of the region (Fig. 1). They have a combined surface area of about 245,000 square kilometers and are among the largest, deepest lakes in the world. They are the largest single aggregation of fresh water on the planet (excluding the polar ice caps) and are the only glacial feature on Earth visible from the surface of the moon (The Nature Conservancy 1994a). The Great Lakes moderate the region’s climate, which presently ranges from subarctic in the north to humid continental warm in the south (Fig. 2), reflecting the movement of major weather masses from the north and south (U.S. Department of the Interior 1970; Eichenlaub 1979). The lakes act as heat sinks in summer and heat sources in winter and are major reservoirs that help humidify much of the region. They also create local precipitation belts in areas where air masses are pushed across the lakes by prevailing winds, pick up moisture from the lake surface, and then drop that moisture over land on the other side of the lake. The mean annual frost-free period—a general measure of the growing-season length for plants and some cold-blooded animals—varies from 60 days at higher elevations in the north to 160 days in lakeshore areas in the south. The climate influences the general distribution of wild plants and animals in the region and also influences the activities and distribution of the human population. The wild plants and animals and the natural systems that support them in the Great Lakes region are valuable resources of considerable local, regional, and national interest. They are also, in part, transboundary resources that we share with our Canadian neighbors to the north. The way these resources are changing over time is inadequately known and is a cause for concern for resource users and for those charged with managing and protecting these unique and valuable resources. This chapter describes the wild plants and animals and the systems that support them in the Great Lakes region; addresses their condition; and points out the gaps in our knowledge about them that, if filled, would aid in their conservation and appropriate use.

Illinois, Indiana, Minnesota, New York, Ohio, Penn↗

USGS2025

Status and trends of pelagic and benthic prey fish populations in Lake Michigan, 2024

Fall bottom trawl (fall BT) and lakewide acoustic (AC) surveys are conducted annually to generate indices of pelagic and benthic prey fish densities in Lake Michigan. The fall BT survey has been conducted each fall since 1973 using 12-m trawls at depths ranging from 9 to 110 m at fixed locations distributed across seven transects; this survey estimates densities of seven prey fish species [i.e., Alewife ( Alosa pseudoharengus ), Bloater ( Coregonus hoyi ), Rainbow Smelt ( Osmerus mordax ), Deepwater Sculpin ( Myoxocephalus thompsonii ), Slimy Sculpin ( Cottus cognatus ), Round Goby ( Neogobius melanostomus ), Ninespine Stickleback ( Pungitius pungitius )] as well as age-0 Yellow Perch ( Perca flavescens ) and large (> 350 mm) Burbot ( Lota lota ). In recent years, wild juvenile (<400 mm) Lake Trout ( Salvelinus namaycush ) have also become more common in the fall bottom trawl. The AC survey has been conducted each late summer/early fall since 2004 (except 2020). The 2024 AC survey consisted of 24 transects [468 km total (291 miles)] covering bottom depths ranging from 16 to 173 m and 38 midwater trawl tows at 4 to 72 m; this survey estimates densities of three prey fish species (i.e., Alewife, Bloater, and Rainbow Smelt). The data generated from these surveys are used to estimate various population parameters that are, in turn, used by state and tribal agencies in managing Lake Michigan fish stocks. In spring of 2024, an additional spring bottom trawl survey (spring BT) was implemented across six of the transects sampled in the fall and sites ranged in depth from 9 to 237 m. The goal of the spring BT, conducted annually since 2021 with differing levels of effort, was to explore seasonal differences in biomass density and distributions of key prey species, most notably Alewife. Total prey fish biomass density from the spring BT was 5.7 kg/ha. For the AC survey, total biomass density of prey fish equaled 10.8 kg/ha, more than double the long-term average (20042023) of 5.1 kg/ha but 4.0 kg/ha lower than the 2023 estimate. For the fall BT, total biomass density of prey fish equaled 2.1 kg/ha, the lowest value since 2020 and 69% lower than the average from 2004-2023 (6.8 kg/ha). The 2024 fall BT biomass density was only 6.3% of the average over the entirety of the time series (1973-2023; 33.1 kg/ha). Over the period both surveys have been conducted (2004-2024), total biomass density has trended downward in the fall BT (despite a high 2022 estimate) and remained relatively stable in the AC survey. Deepwater Sculpin and Bloater were the most common species (by biomass) among prey fishes in the spring BT while the AC survey and fall BT reported co-dominance of Bloater and Alewife. Mean biomass of yearling and older (YAO) Alewife was 1.30 kg/ha in the spring BT, 4.7 kg/ha in the AC survey, and 0.68 kg/ha in the fall BT. Since 2014, annual survey results suggest that the catchability of YAO Alewives for the fall BT is substantially lower than the AC survey. Like previous spring surveys, Alewives were aggregated in deeper habitats, with 93% of biomass collected between 110 and 201 m. Results of the 2024 spring BT align with past spring surveys and do not suggest that spring bottom trawling provides a better index of age-2 and older Alewives than fall bottom trawling, even with adjustments for differences in habitat use. However, the spring BT does appear to index age-1 Alewives more effectively than the fall BT. The 2024 AC survey YAO Alewife biomass density estimate was 77% higher than the average from 2004-2023. The Alewife population of Lake Michigan appears to be composed mostly of young fish and the proportion of age-4 and older Alewives was <1.8% in each of the three surveys. Age-0 Alewife numeric density from the AC survey was 510 fish/ha in 2024, slightly higher than the long-term mean (486 fish/ha). Biomass density of large (≥120 mm) Bloater was 5.2 kg/ha in the AC survey and 0.76 kg/ha in the fall BT, while total Bloater biomass in the spring BT was 1.8 kg/ha - all three estimates were much lower than what was estimated by the fall BT between 1981 and 1998. The density of small (<120 mm) Bloater was 456 fish/ha in the AC survey, the second highest value in the time series and potentially reflective of an above average 2024 year-class. Meanwhile, small Bloater density estimated in the fall BT was only 16 fish/ha. Biomass density of large Rainbow Smelt (≥90 mm) was 0.21 kg/ha in the AC survey and 0.03 kg/ha in the fall BT survey, continuing the trend of low large Rainbow Smelt biomass observed since 2001. Numeric density of small (<90 mm) Rainbow Smelt was 31 fish/ha in the AC survey and 143 fish/ha in the fall BT. All four prey fish species indexed only by the fall BT had below-average biomass densities regardless of trawling season. Deepwater Sculpin biomass density was 0.26 kg/ha, which makes 14 of the past 15 years with biomass <1 kg/ha. Spring BT Deepwater Sculpin biomass density (2.0 kg/ha) was higher than any fall BT estimate since 2006, likely reflective of including bottom trawls at greater depths in the spring than the fall. Slimy Sculpin was estimated to be < 0.04 kg/ha in the spring and fall BT, an order of magnitude lower than the long-term average from the fall BT. Round Goby biomass density estimates were low and similar across seasons (0.43 kg/ha in the spring and 0.10 kg/ha in the fall). Ninespine Stickleback density was 3.9 fish/ha in the fall BT and no fish were collected in the spring BT.

Lake Michigan↗

USGS2022

Automating sandhill crane counts from nocturnal thermal aerial imagery using deep learning

Population monitoring is essential to management and conservation efforts for migratory birds, but traditional low-altitude aerial surveys with human observers are plagued by individual observer bias and risk to flight crews. Aerial surveys that use remote sensing can reduce bias and risk, but manual counting of wildlife in imagery is laborious and may be cost-prohibitive. Therefore, automated methods for counting are critical to cost-efficient application of remote sensing for wildlife surveys covering large areas. We conducted nocturnal surveys of sandhill cranes ( Antigone canadensis ) during spring migration in the Central Platte River Valley of Nebraska, USA, using midwave thermal infrared sensors. We developed a framework for automated counting of sandhill cranes from thermal imagery using deep learning, assessed and compared the performance of two automated counting models, and quantified the effect of spatial resolution on counting accuracy. Aerial thermal imagery data were collected in March 2018 and 2021; 40 images were analyzed. We applied two deep learning models: an object detection approach, Faster R-CNN and a recently developed pixel-density estimation approach, ASPDNet. Model performance was determined using data independent of the training imagery. The effect of spatial resolution was quantified with a beta regression on relative error. Our results showed model accuracy of 9% mean percent error for ASPDNet and 18% for Faster R-CNN. Most error was related to the undercounting of sandhill cranes. ASPDNet had < 50% of the error of Faster R-CNN as measured by mean percent error, root-mean-squared error and mean absolute error. Spatial resolution affected accuracy of both models, with error rate increasing with coarser resolution, particularly with Faster R-CNN. Deep learning models, particularly pixel-density estimators, can accurately automate counting of migratory birds in a dense, aggregate setting such as nocturnal roosting sites.

Nebraska↗

USGS2022

Early treatment of white-nose syndrome is necessary to stop population decline

Since its introduction to North America, white-nose syndrome has been associated with declines greater than 90% in several bat species, prompting the development of treatments to reduce disease-related mortality. As treatment application is scaled up, predicting responses at the population level will help in the development of management plans. We develop a model allowing for the implementation of multiple treatment scenarios in bat populations at risk of severe mortality from white-nose syndrome. Our model allows for variation in over 10 parameters, including effectiveness of treatment, treatment-related disturbance, number of individuals treated, number of hibernacula treated, herd immunity and movement among hibernacula. Additionally, the model allows treatments to be applied to individuals, the hibernaculum or a combination of the two. We simulated treatments for populations of 1000, 10,000 and 100,000 individuals, with the distribution of individuals within hibernacula based on field surveys of Myotis lucifugus . When treatments are applied to individuals, we found that treatment success was most influenced by the number of bats effectively treated, the magnitude of disturbance and the year of first treatment relative to initial mortality. For treatments applied to hibernacula, we found year of first treatment relative to initial mortality, magnitude of disturbance and effectiveness of treatment to be the best predictors of success. Treatments have the potential to mitigate white-nose syndrome-related mortality, but application of treatments after initial mass mortality seems to be of limited benefit. Unknowns surrounding influential treatment parameters, such as disturbance to hibernating bats, created substantial variation across outcomes and highlight the importance of obtaining field estimates of parameters associated with treatments. Synthesis and applications : While treatment applications can increase survival from white-nose syndrome, their potential is strongly diminished when not applied before or during the early epidemic stages. Once the disease is established, increasing survival and reproduction through methods other than disease treatments could be a better option. In the United States, most areas yet to reach the late epidemic or established stage are in the west where bats do not aggregate in large colonies and treating a substantial number of individuals will be difficult.

Journal of Applied Ecology↗

USGS1988

Foods of juvenile ring-necked ducks: Relationship to wetland pH

Foods of 37 juvenile ring-necked ducks ( Aythya collaris ) from 16 different wetlands were examined in eastcentral Maine in 1983-85. Invertebrates made up 70% aggregate dry weight (100% occurrence) of the foods of Class Ia-IIa ( ≤ 24 days old) ducklings and 32% (86% occurrence) of Class IIb-III ( ≥ 25 days old) ducklings. These percentages may be as high as 85% for Ia-IIa ducklings and 47% for IIb-III ducklings after adjusting for insect sclerites. Ducklings ate invertebrates from 44 taxa and seeds or fibers from 23 plant taxa. Freshwater sponges (Porifera) were the most important invertebrate and constituted 23% of the foods of all ducklings. Seeds of pondweeds ( Potamogeton spp.) were the most important plant foods. Diets of ducklings from high-pH ( ≥ 6.1) wetlands were more diverse (t = 2.54, P = 0.021) than those from low-pH (<6.1) wetlands and consisted of 33 invertebrate taxa. Only 17 taxa occurred in ducklings from low-pH ponds. Class Ia-IIa ducklings from high-pH wetlands ate more invertebrates (77%) than ducklings from lower-pH wetlands (61%), although the difference was not significant (P = 0.21). Sponges made up the largest percentage of the diets and occurred in similar amounts in high- (34%) and low- (31.5%) pH wetlands.

Maine↗

USGS2024

Anthropogenic and environmental risk factors of salmonid predation in a tidal freshwater delta

Water diversions that support agricultural and municipal use result in fish mortality through entrainment and impingement. Additionally, this infrastructure may attract both predators and prey fishes, thereby increasing predation rates and prey mortality near these anthropogenic contact points. The Sacramento–San Joaquin Delta (the Delta) in California's Central Valley is a tidal freshwater ecosystem that exports large volumes of water for municipal and agricultural use while at the same time providing valuable migratory and rearing habitat for imperilled fishes. Emigrating juvenile salmonids experience high mortality in the Delta, with predation by non-native fishes contributing substantially. Therefore, this study had three main objectives. First, we determined if small water diversions aggregated piscivorous fishes like other similar structures in freshwater ecosystems. Second, we determined how small diversions may influence juvenile salmon predation risk in conjunction with other known predation risk factors (e.g. predator abundance, temperature and depth). Third, we assessed the predator assemblage, abundance and distribution to determine the likely predator composition in objectives one and two. Throughout the spring of 2021, we used ARIS (adaptive resolution imaging sonar; Sound Metrics) sonars to compare piscivore abundance at 30 water diversions in the north Delta to shorelines adjacent to diversions that did not contain these structures. We used predation event recorders (PERs) to assess the predation risk juvenile salmonids were exposed to, with linear distance (m) from diversions, and other predation risk factors in the north Delta. Finally, we used a boat electrofishing survey to determine the piscivore assemblage and compare spatial trends in black bass ( Micropterus spp.) CPUE and relative abundance throughout these waterways. Piscivore abundance was greater near small water diversions than at adjacent shorelines and the predation risk of juvenile salmonids increased with diversion proximity. Additionally, predation risk increased with increasing piscivore abundance and decreasing water depth. The north Delta predator assemblage was dominated by black basses ( Micropterus spp.), which likely drove the negative relationship of predation risk with water depth, given habitat requirements of these species. Furthermore, increasing smallmouth ( Micropterus dolomieu ) and spotted bass ( Micropterus punctulatus ) abundance in our northern study sites may have weakened temperature effects on predation, given metabolic requirements of these species. Our work demonstrated that small water diversions are likely to increase mortality of endangered salmonids, and that the north Delta predator assemblage was different than recorded by previous work in this system, changing predation risk factors. Although more work is needed to determine the population level impacts of diversions, the ubiquitous distribution of these structures warrants management solutions to reduce mortality from this source. These results indicate that in addition to entrainment and impingement, water diversions may increase mortality of small-bodied fishes by attracting predators and elevating predation risk. Given the continual human demand for freshwater, predator–prey interactions should be considered along with entrainment and impingement when assessing intake infrastructure mitigation, especially when diversions co-occur along migratory routes and essential habitat of imperilled fishes.

California↗

USGS2011

Spatially pooled depth-dependent reservoir storage, elevation, and water-quality data for selected reservoirs in Texas, January 1965-January 2010

The U.S. Geological Survey (USGS), in cooperation with Texas Tech University, constructed a dataset of selected reservoir storage (daily and instantaneous values), reservoir elevation (daily and instantaneous values), and water-quality data from 59 reservoirs throughout Texas. The period of record for the data is as large as January 1965-January 2010. Data were acquired from existing databases, spreadsheets, delimited text files, and hard-copy reports. The goal was to obtain as much data as possible; therefore, no data acquisition restrictions specifying a particular time window were used. Primary data sources include the USGS National Water Information System, the Texas Commission on Environmental Quality Surface Water-Quality Management Information System, and the Texas Water Development Board monthly Texas Water Condition Reports. Additional water-quality data for six reservoirs were obtained from USGS Texas Annual Water Data Reports. Data were combined from the multiple sources to create as complete a set of properties and constituents as the disparate databases allowed. By devising a unique per-reservoir short name to represent all sites on a reservoir regardless of their source, all sampling sites at a reservoir were spatially pooled by reservoir and temporally combined by date. Reservoir selection was based on various criteria including the availability of water-quality properties and constituents that might affect the trophic status of the reservoir and could also be important for understanding possible effects of climate change in the future. Other considerations in the selection of reservoirs included the general reservoir-specific period of record, the availability of concurrent reservoir storage or elevation data to match with water-quality data, and the availability of sample depth measurements. Additional separate selection criteria included historic information pertaining to blooms of golden algae. Physical properties and constituents were water temperature, reservoir storage, reservoir elevation, specific conductance, dissolved oxygen, pH, unfiltered salinity, unfiltered total nitrogen, filtered total nitrogen, unfiltered nitrate plus nitrite, unfiltered phosphorus, filtered phosphorus, unfiltered carbon, carbon in suspended sediment, total hardness, unfiltered noncarbonate hardness, filtered noncarbonate hardness, unfiltered calcium, filtered calcium, unfiltered magnesium, filtered magnesium, unfiltered sodium, filtered sodium, unfiltered potassium, filtered potassium, filtered chloride, filtered sulfate, unfiltered fluoride, and filtered fluoride. When possible, USGS and Texas Commission on Environmental Quality water-quality properties and constituents were matched using the database parameter codes for individual physical properties and constituents, descriptions of each physical property or constituent, and their reporting units. This report presents a collection of delimited text files of source-aggregated, spatially pooled, depth-dependent, instantaneous water-quality data as well as instantaneous, daily, and monthly storage and elevation reservoir data.

Texas↗

USGS2019

Black-tailed prairie dog, Cynomys ludovicianus (Sciuridae), metapopulation response to novel sourced conspecific signals

Aggregation of territorial individuals within a species can be facilitated via conspecific signals, wherein settlement implies habitat suitability, ease of resource acquisition and/or increased predator detection. The black-tailed prairie dog is a colonial small mammal with alarm vocalizations that confer benefits via group vigilance against predators and increased foraging time. Although prairie dog alarm calls are relatively well understood, the information embedded in their jump-yip call, which includes both a distinct cry and a bodily gesture, remains less clear. We evaluated prairie dog behaviour in response to conspecific acoustic signals using playbacks of alarm and jump-yip calls at 26 sites in northeastern Wyoming, U.S.A. Recorded calls from an isolated colony were broadcast to a mean of five individuals per site, and behavioural responses were compared against uninfluenced behaviour and a control playback of ambient sounds. The alarm playback caused prairie dogs to increase vigilance 122% and decrease foraging time 23%, demonstrating prairie dogs will shift behaviour based on signals from individuals of an unfamiliar colony. However, the alarm call playback reduced frequency of the jump-yip behaviour only at colonies nearest the recording source. The jump-yip playback caused unfamiliar prairie dogs to display 339% more jump-yips than uninfluenced behaviour. The jump-yip playback did not alter recipients' foraging or vigilance behaviours relative to control treatments, suggesting that although prairie dogs can understand and reciprocate an unfamiliar, single modality signal, they may not shift other behaviours based on this stimulus. As such, the purpose and benefits of the jump-yip call remain unclear. Playback efficacy also had a nonlinear relationship with distance from recording source. Our work improves understanding of communication at the metapopulation level, examines the potential role of the jump-yip and provides insights for how conspecific signals might be used as a management tool.

Wyoming↗

USGS2014

American white pelican predation on Cui-ui in Pyramid Lake, Nevada

Anthropogenic changes to the Pyramid Lake–Truckee River ecosystem in Nevada are suspected to have altered the predator–prey balance between American white pelican Pelecanus erythrorhynchos and Cui-ui Chasmistes cujus . We estimated the loss of the adult Cui-ui population to pelican predation over a 13-year period by netting and tagging Cui-uis as they aggregated at the mouth of the Truckee River prior to their spawning migration into the Truckee River. Cui-ui access to the Truckee River typically required traversing a shallow delta (a foraging advantage for these American white pelicans). Dams and greater frequency of low stream flows also contributed to American white pelican foraging success. We used tag recoveries from Pyramid Lake's nesting colony of American white pelicans along with an experiment to estimate the chance of tag recovery within the colony to calculate the number of tagged fish taken by American white pelicans. We also used numbered tags to test whether there was a size preference for Cui-uis taken. Our results showed that the primary source of adult Cui-ui mortality was from American white pelican predation in the Truckee River. Within a 13-year period American white pelicans had taken 90% of the tags deployed during the first 7 years of the interval. There was no preference for the size of Cui-uis taken. A better understanding of the effects of heavy cropping by American white pelicans on Cui-ui population dynamics is still needed.

Nevada↗

USGS2004

Documentation of the Santa Clara Valley regional ground-water/surface-water flow model, Santa Clara Valley, California

The Santa Clara Valley is a long, narrow trough extending about 35 miles southeast from the southern end of San Francisco Bay where the regional alluvial-aquifer system has been a major source of water. Intensive agricultural and urban development throughout the 20th century and related ground-water development resulted in ground-water-level declines of more than 200 feet and land subsidence of as much as 12.7 feet between the early 1900s and the mid-1960s. Since the 1960s, Santa Clara Valley Water District has imported surface water to meet growing demands and reduce dependence on ground-water supplies. This importation of water has resulted in a sustained recovery of the ground-water flow system. To help support effective management of the ground-water resources, a regional ground-water/surface-water flow model was developed. This model simulates the flow of ground water and surface water, changes in ground-water storage, and related effects such as land subsidence. A numerical ground-water/surface-water flow model of the Santa Clara Valley subbasin of the Santa Clara Valley was developed as part of a cooperative investigation with the Santa Clara Valley Water District. The model better defines the geohydrologic framework of the regional flow system and better delineates the supply and demand components that affect the inflows to and outflows from the regional ground-water flow system. Development of the model includes revisions to the previous ground-water flow model that upgraded the temporal and spatial discretization, added source-specific inflows and outflows, simulated additional flow features such as land subsidence and multi-aquifer wellbore flow, and extended the period of simulation through September 1999. The transient-state model was calibrated to historical surface-water and ground-water data for the period 1970–99 and to historical subsidence for the period 1983–99. The regional ground-water flow system consists of multiple aquifers that are grouped into upper- and lower-aquifer systems. Ground-water inflow occurs as natural recharge in the form of streamflow infiltration and areal infiltration of precipitation along stream channels, artificial recharge from infiltration of imported water at recharge ponds and along selected stream channels, and leakage along selected transmission pipelines. Ground-water outflow occurs as evapotranspiration, stream base flow, discharge through pumpage from wells, and subsurface flow to the San Francisco Bay. The geohydrologic framework of the regional ground-water flow system was represented as six model layers. The hydraulic properties were redefined on the basis of cell-based lithologic properties that were delineated in terms of aggregate thicknesses of coarse-grained, fine-grained, and mixed textural categories. The regional aquifer systems also are dissected by several laterally extensive faults that may form at least partial barriers to the lateral flow of ground water. The spatial extent of the ground-water flow model was extended and refined to cover the entire Santa Clara Valley, including the Evergreen subregion. The temporal discretization was refined and the period of simulation was extended to 1970–99. The model was upgraded to MODFLOW-2000 (MF2K) and was calibrated to fit historical ground-water levels, streamflow, and land subsidence for the period 1970–99. The revised model slightly overestimates measured water levels with an root-mean-square error of -7.34 feet. The streamflow generally shows a good match on gaged creeks and rivers for flows greater than 1.2 cubic feet per second. The revised model also fits the measured deformation at the borehole extensometer site located near San Jose within 16 to 27 percent and the extensometer site near Sunnyvale within 3 percent of the maximum measured seasonal deformation for the deepest extensometers. The total ground-water inflow and outflow of about 225,500 acre-feet per year (acre-ft/yr) for the period 1970–89 and of about 205,300 acre-feet per year for the period for the period 1970–99 is comparable with that of the previous model, 207,200 acre-ft/yr for the period 1970–89. Overall the simulated net change in storage increased by about 189,500 acre-ft/yr for the entire period of simulation, which represents about one and a half years of the 1970–99 average pumping. The changes in ground-water flow and storage generally reflect the major climate cycles and the additional importation of water by Santa Clara Valley Water District, with the basin in recovery since the drought of the late 1980s and early 1990s. The average total recharge rate, from natural and artificial recharge and from streamflow infiltration for the revised model for the entire simulation period 1970–99, was about 157,100 acre-ft/yr, which represents about 59 percent of the inflow to the ground-water flow system. The average rate of artificial recharge of about 77,600 acre-ft/yr represents about 30 percent of the inflow to the ground-water flow system. The average pumpage for the entire 29.75-year simulation period is about 133,400 acre-ft/yr and represents about 69 percent of the outflow from the ground-water flow system. Most of the simulated recharge infiltrates and flows through the uppermost layers (i.e. model layers 1 and 3) of the aquifer system. Most of the water that flows to the deeper model layers is occurring through wellbores, with wellbore flow representing 19 percent of the total ground-water inflow between model layers.

California↗

USGS2011

The water-quality monitoring program for the Baltimore reservoir system, 1981-2007—Description, review and evaluation, and framework integration for enhanced monitoring

The City of Baltimore, Maryland, and parts of five surrounding counties obtain their water from Loch Raven and Liberty Reservoirs. A third reservoir, Prettyboy, is used to resupply Loch Raven Reservoir. Management of the watershed conditions for each reservoir is a shared responsibility by agreement among City, County, and State jurisdictions. The most recent (2005) Baltimore Reservoir Watershed Management Agreement (RWMA) called for continued and improved water-quality monitoring in the reservoirs and selected watershed tributaries. The U.S. Geological Survey (USGS) conducted a retrospective review of the effectiveness of monitoring data obtained and analyzed by the RWMA jurisdictions from 1981 through 2007 to help identify possible improvements in the monitoring program to address RWMA water-quality concerns. Long-term water-quality concerns include eutrophication and sedimentation in the reservoirs, and elevated concentrations of (a) nutrients (nitrogen and phosphorus) being transported from the major tributaries to the reservoirs, (b) iron and manganese released from reservoir bed sediments during periods of deep-water anoxia, (c) mercury in higher trophic order game fish in the reservoirs, and (d) bacteria in selected reservoir watershed tributaries. Emerging concerns include elevated concentrations of sodium, chloride, and disinfection by-products (DBPs) in the drinking water from both supply reservoirs. Climate change and variability also could be emerging concerns, affecting seasonal patterns, annual trends, and drought occurrence, which historically have led to declines in reservoir water quality. Monitoring data increasingly have been used to support the development of water-quality models. The most recent (2006) modeling helped establish an annual sediment Total Maximum Daily Load to Loch Raven Reservoir, and instantaneous and 30-day moving average water-quality endpoints for chlorophyll-a (chl-a) and dissolved oxygen (DO) in Loch Raven and Prettyboy Reservoirs. Modelers cited limitations in data, including too few years with sufficient stormflow data, and (or) a lack of (readily available) data, for selected tributary and reservoir hydrodynamic, water-quality, and biotic conditions. Reservoir monitoring also is too infrequent to adequately address the above water-quality endpoints. Monitoring data also have been effectively used to generally describe trophic states, changes in trophic state or conditions related to trophic state, and in selected cases, trends in water-quality or biotic parameters that reflect RWMA water-quality concerns. Limitations occur in the collection, aggregation, analyses, and (or) archival of monitoring data in relation to most RWMA water-quality concerns. Trophic, including eutrophic, conditions have been broadly described for each reservoir in terms of phytoplankton production, and variations in production related to typical seasonal patterns in the concentration of DO, and hypoxic to anoxic conditions, where the latter have led to elevated concentrations of iron and manganese in reservoir and supply waters. Trend analyses for the period 1981-2004 have shown apparent declines in production (algal counts and possibly chl-a). The low frequency of phytoplankton data collection (monthly or bimonthly, depending on the reservoir), however, limits the development of a model to quantitatively describe and relate temporal variations in phytoplankton production including seasonal succession to changes in trophic states or other reservoir water-quality or biotic conditions. Extensive monitoring for nutrients, which, in excessive amounts, cause eutrophic conditions, has been conducted in the watershed tributaries and reservoirs. Data analyses (1980-90s) have (a) identified seasonal patterns in concentrations, (b) characterized loads from (non)point sources, and (c) shown that different seasonal patterns and trends in nutrient concentrations occur between watershed tributaries and downstream reservoir.

Maryl;Pennsylvania↗