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At least 613 records · Page 34Linked to original sources

USGS2015

Development of an assessment tool for agricultural best management practice implementation in the Great Lakes Restoration Initiative priority watersheds—Upper East River, tributary to Green Bay, Wisconsin

Introduction The Great Lakes face a number of serious challenges that cause damage to water quality, habitat, ecology, and coastal health. Excess nutrients from point and nonpoint sources have a history of causing harmful algal blooms (HABs); since the late 1990s, a resurgence of HABs have forced beach closures and resulted in water quality impairments across the Great Lakes. Studies increasingly point to phosphorus (P) runoff from agricultural lands as the cause of these HABs. In 2010, the Great Lakes Restoration Initiative (GLRI) was launched to revitalize the Great Lakes. The GLRI aims to address the challenges facing the Great Lakes and provide a framework for restoration and protection. As part of this effort, the Priority Watersheds Work Group (PWWG), cochaired by the U.S. Environmental Protection Agency (EPA) and the U.S. Department of Agriculture-Natural Resources Conservation Service (USDA–NRCS), is targeting Priority Watersheds (PWs) to reduce the amount of P reaching the Great Lakes. Within the PWs, USDA–NRCS identifies small-scale subbasins with high concentrations of agriculture for coordinated nutrient reduction efforts and enhanced monitoring and modeling. The USDA–NRCS supplies financial and/or technical assistance to producers to install or implement best management practices (BMPs) to lessen the negative effects of agriculture to water quality; additional funding is provided by the GLRI through USDA–NRCS to saturate the small-scale subbasins with BMPs. The watershed modeling component, introduced in this fact sheet, assesses the effectiveness of USDA–NRCS funded BMPs, and nutrient reductions because of GLRI or other funding programs are differentiated. Modeling scenarios consider BMPs that have already been applied and those planned to be implemented across the small-scale subbasins.

Wisconsin↗

USGS2015

Development of an assessment tool for agricultural best management practice implementation in the Great Lakes restoration initiative priority watersheds—Eagle Creek, tributary to Maumee River, Ohio

Ohio↗

USGS2015

Development of an assessment tool for agricultural best management practice Implementation in the Great Lakes Restoration Initiative priority watersheds—Alger Creek, tributary to Saginaw River, Michigan

The Great Lakes face a number of serious challenges that cause damage to water quality, habitat, ecology, and coastal health. Excess nutrients from point and nonpoint sources have a history of causing harmful algal blooms (HABs); since the late 1990s, a resurgence of HABs have forced beach closures and resulted in water quality impairments across the Great Lakes. Studies increasingly point to phosphorus (P) runoff from agricultural lands as the cause of these HABs. In 2010, the Great Lakes Restoration Initiative (GLRI) was launched to revitalize the Great Lakes. The GLRI aims to address the challenges facing the Great Lakes and provide a framework for restoration and protection. As part of this effort, the Priority Watersheds Work Group (PWWG), cochaired by the U.S. Environmental Protection Agency (EPA) and the U.S. Department of Agriculture-Natural Resources Conservation Service (USDA–NRCS), is targeting Priority Watersheds (PWs) to reduce the amount of P reaching the Great Lakes. Within the PWs, USDA–NRCS identifies small-scale subbasins with high concentrations of agriculture for coordinated nutrient reduction efforts and enhanced monitoring and modeling. The USDA–NRCS supplies financial and/or technical assistance to producers to install or implement best management practices (BMPs) to lessen the negative effects of agriculture to water quality; additional funding is provided by the GLRI through USDA–NRCS to saturate the small-scale subbasins with BMPs. The watershed modeling component, introduced in this fact sheet, assesses the effectiveness of USDA–NRCS funded BMPs, and nutrient reductions because of GLRI or other funding programs are differentiated. Modeling scenarios consider BMPs that have already been applied and those planned to be implemented across the small-scale subbasins.

Michigan↗

USGS2021

Tradeoffs in habitat value to maximize natural resource benefits from coastal restoration in a rapidly eroding wetland: Is monitoring land area sufficient?

Louisiana contains nearly 40% of estuarine herbaceous wetlands in the contiguous United States, supporting valuable ecosystem services and providing significant economic benefits to the state and the entire United States. However, coastal Louisiana is a hotspot for rapid land loss from factors including hurricanes, land use change, and high subsidence rates contributing to high relative sea-level rise. The Coastal Protection and Restoration Authority (CPRA) was established after major hurricanes in 2005 to coordinate coastal restoration in Louisiana and develop the Louisiana Coastal Master Plan. The LA Coastal Master Plan uses numerical modeling of multiple scenarios to select a suite of restoration projects based on maximum land area created and flood reduction (as proxies for ecosystem value). Using potential value to aquatic, terrestrial, and social resources, our work compared habitat value of shallow open water areas to emergent wetland. While potential resource benefits varied by emergent wetland salinity type and emergent wetland versus water, they were similar, suggesting that restoration planning based primarily on wetland land area may not achieve the maximum possible ecosystem benefits. After nearly 20 years of integrated restoration planning in coastal Louisiana, a reassessment of restoration planning decision drivers may be beneficial to ensure maximum benefits from coastal restoration. As a result of the Deepwater Horizon oil spill, settlement funds will be a major support to coastal restoration in Louisiana for many years. Assessing potential habitat value to multiple natural and social resources in Louisiana has potential to maximize synergy with large northern Gulf of Mexico restoration programs.

Louisiana↗

USGS1997

Digital shaded-relief image of Alaska

One of the most spectacular physiographic images of the conterminous United States, and the first to have been produced digitally, is that by Thelin and Pike ( USGS I-2206, 1991 ). The image is remarkable for its crispness of detail and for the natural appearance of the artificial land surface. Our goal has been to produce a shaded-relief image of Alaska that has the same look and feel as the Thelin and Pike image. The Alaskan image could have been produced at the same scale as its lower 48 counterpart (1:3,500,000). But by insetting the Aleutian Islands into the Gulf of Alaska, we were able to print the Alaska map at a larger scale (1:2,500,000) and about the same physical size as the Thelin and Pike image. Benefits of the 1:2,500,000 scale are (1) greater resolution of topographic features and (2) ease of reference to the U.S. Geological Survey (USGS) (1987) Alaska Map E and the statewide geologic map (Beikman, 1980), which are both 1:2,500,000 scale. Manually drawn, shaded-relief images of Alaska's land surface have long been available (for example, Department of the Interior, 1909; Raisz, 1948). The topography depicted on these early maps is mainly schematic. Maps showing topographic contours were first available for the entire State in 1953 (USGS, 1:250,000) (J.H. Wittmann, USGS, written commun., 1996). The Alaska Map E was initially released in 1954 in both planimetric (revised in 1973 and 1987) and shaded-relief versions (revised in 1973, 1987, and 1996); topography depicted on the shaded-relief version is based on the 1:250,000-scale USGS topographic maps. Alaska Map E was later modified to include hypsometric tinting by Raven Maps and Images (1989, revised 1993) as copyrighted versions. Other shaded-relief images were produced for The National Geographic Magazine (LaGorce, 1956; 1:3,000,000) or drawn by Harrison (1970; 1:7,500,000) for The National Atlas of the United States. Recently, the State of Alaska digitally produced a shaded-relief image of Alaska at 1:2,500,000 scale (Alaska Department of Natural Resources, 1994), using the 1,000-m digital elevation data set referred to below. An important difference between our image and these previous ones is the method of reproduction: like the Thelin and Pike (1991) image, our image is a composite of halftone images that yields sharp resolution and preserves contrast. Indeed, the first impression of many viewers is that the Alaskan image and the Thelin and Pike image are composites of satellite-generated photographs rather than an artificial rendering of a digital elevation model. A shaded-relief image represents landforms in a natural fashion; that is, a viewer perceives the image as a rendering of reality. Thus a shaded-relief image is intrinsically appealing, especially in areas of spectacular relief. In addition, even subtle physiographic features that reflect geologic structures or the type of bedrock are visible. To our knowledge, some of these Alaskan features have not been depicted before and so the image should provide earth scientists with a new "look" at fundamental geologic features of Alaska.

Alaska↗

USGS2022

Linear regression model documentation for computing water-quality constituent concentrations using continuous real-time water-quality data for the Republican River, Clay Center, Kansas, July 2018 through March 2021

The Republican River is the primary inflow to Milford Lake and drains areas of Kansas, Nebraska, and Colorado. Milford Lake has been listed as impaired and designated hypereutrophic by the Kansas Department of Health and Environment because of excessive nutrient loading. Milford Lake had confirmed harmful algal blooms every summer from 2011 through 2017 and in 2020 and 2021. In the lower Republican River drainage basin, the Regional Conservation Partnership Program, administered by the Natural Resources Conservation Service, provides reimbursement to agricultural producers that implement best management practices intended to decrease sediment and nutrient runoff and loading into Milford Lake. Sediment and nutrient loads could potentially be driving factors in the development of harmful algal blooms in the reservoir. Since July 2018, the U.S. Geological Survey, in cooperation with the Kansas Water Office, has collected continuous and discrete water-quality data at the Republican River at Clay Center, Kansas, streamgage (U.S. Geological Survey station 06856600), which is about 15 river miles upstream from Milford Lake. This report documents site-specific regression models for the computation of continuous concentrations of suspended sediment, total nitrogen, total phosphorus, and total carbon developed using continuous and discrete data collected from July 24, 2018, the date of continuous water-quality monitor installation, through March 31, 2021. The objective of this study is to characterize sediment and nutrient transport in the Milford Lake drainage basin before, during, and after best management practice implementation using the models described in this report. The explanatory variable turbidity explained a high amount (72–96 percent) of the variance in suspended-sediment, total nitrogen, total phosphorus, and total carbon concentrations. Statistical plots for the four selected models showed the desired normality and homoscedasticity in residuals, and model standard error ratios indicated that recomputing each selected model after removing a randomly selected 10 percent of the data did not substantially change model coefficients.

Kansas↗

USGS2011

Swallows as a sentinel species for contaminant exposure and effect studies

Tree swallows are an important model species to study the effects of contaminants in wild bird populations and have been used extensively in studies across North America. The advantages of swallows compared to other avian species are detailed. Three case histories are provided where swallows have been successfully used in Natural Resource Damage and Ecological Risk Assessments. The final two sections of this chapter are for individuals who want more in-depth information and include a summary of the chemical classes for which there are swallow data, including effect levels when known. Information provided in this section can be used to put exposure to most classes of contaminants into context with other sites across North America. Finally, commonly used endpoints, ranging from population-level down to cellular and genetic endpoints, are discussed including considerations and pitfalls, and when further work is needed to more fully understand the role of environmental and biological variation in interpreting these endpoints.

Book chapter↗

USGS2007

Characterizing the spatial structure of endangered species habitat using geostatistical analysis of IKONOS imagery

Our study used geostatistics to extract measures that characterize the spatial structure of vegetated landscapes from satellite imagery for mapping endangered Sonoran pronghorn habitat. Fine spatial resolution IKONOS data provided information at the scale of individual trees or shrubs that permitted analysis of vegetation structure and pattern. We derived images of landscape structure by calculating local estimates of the nugget, sill, and range variogram parameters within 25 ?? 25-m image windows. These variogram parameters, which describe the spatial autocorrelation of the 1-m image pixels, are shown in previous studies to discriminate between different species-specific vegetation associations. We constructed two independent models of pronghorn landscape preference by coupling the derived measures with Sonoran pronghorn sighting data: a distribution-based model and a cluster-based model. The distribution-based model used the descriptive statistics for variogram measures at pronghorn sightings, whereas the cluster-based model used the distribution of pronghorn sightings within clusters of an unsupervised classification of derived images. Both models define similar landscapes, and validation results confirm they effectively predict the locations of an independent set of pronghorn sightings. Such information, although not a substitute for field-based knowledge of the landscape and associated ecological processes, can provide valuable reconnaissance information to guide natural resource management efforts.

Arizona↗

USGS2017

Cooperative Fish and Wildlife Research Units - A model partnership program

The U.S. Geological Survey (USGS) Cooperative Fish and Wildlife Research Units (CRU) program is a unique model of cooperative partnership among the USGS, other U.S. Department of the Interior and Federal agencies, universities, State fish and wildlife agencies, and the Wildlife Management Institute. These partnerships are maintained as one of the USGS’s strongest links to Federal and State land and natural resource management agencies. Established in 1935 to meet the need for trained professionals in the growing field of wildlife management, the program currently consists of 40 Cooperative Fish and Wildlife Research Units located on university campuses in 38 States and supports 119 research scientist positions when fully funded. The threefold mission of the CRU program is to (1) conduct scientific research for the management of fish, wildlife, and other natural resources; (2) provide technical assistance to natural resource managers in the application of scientific information to natural resource policy and management; and (3) train future natural resource professionals.

Fact Sheet↗

USGS2023

The 3D Elevation Program—Supporting Montana’s economy

Introduction Montana, America’s fourth largest State with an area of 147,040 square miles, is defined by its diverse terrain. The western two-fifths of the State falls within the Rocky Mountains and the eastern three-fifths is in the Great Plains. Because of its location along the Continental Divide, the rivers in Montana drain into either the Pacific Ocean or the Gulf of Mexico. Montana is often called the Treasure State due to its mineral wealth, which includes oil, gas, and coal, but the State’s primary economic activity is agriculture. Other economic activities include natural resources conservation, water supply and quality, infrastructure and construction management, flood risk management, and geologic resource assessment and hazard mitigation. Critical applications that meet the State’s management needs depend on light detection and ranging (lidar) data that provide a highly detailed three-dimensional (3D) model of the Earth’s surface and aboveground features.

Montana↗

USGS2016

Evaluation of dynamic coastal response to sea-level rise modifies inundation likelihood

Sea-level rise (SLR) poses a range of threats to natural and built environments1, 2, making assessments of SLR-induced hazards essential for informed decision making3. We develop a probabilistic model that evaluates the likelihood that an area will inundate (flood) or dynamically respond (adapt) to SLR. The broad-area applicability of the approach is demonstrated by producing 30 × 30 m resolution predictions for more than 38,000 km2 of diverse coastal landscape in the northeastern United States. Probabilistic SLR projections, coastal elevation and vertical land movement are used to estimate likely future inundation levels. Then, conditioned on future inundation levels and the current land-cover type, we evaluate the likelihood of dynamic response versus inundation. We find that nearly 70% of this coastal landscape has some capacity to respond dynamically to SLR, and we show that inundation models over-predict land likely to submerge. This approach is well suited to guiding coastal resource management decisions that weigh future SLR impacts and uncertainty against ecological targets and economic constraints.

Nature Climate Change↗

USGS1994

The space-time structure of oil and gas field growth in a complex depositional system

Shortly after the discovery of an oil and gas field, an initial estimate is usually made of the ultimate recovery of the field. With the passage of time, this initial estimate is almost always revised upward. The phenomenon of the growth of the expected ultimate recovery of a field, which is known as "field growth," is important to resource assessment analysts for several reasons. First, field growth is the source of a large part of future additions to the inventory of proved reserves of crude oil and natural gas in most petroliferous areas of the world. Second, field growth introduces a large negative bias in the forecast of the future rates of discovery of oil and gas fields made by discovery process models. In this study, the growth in estimated ultimate recovery of oil and gas in fields made up of sandstone reservoirs formed in a complex depositional environment (Frio strand plain exploration play) is examined. The results presented here show how the growth of oil and gas fields is tied directly to the architectural element of the shoreline processes and tectonics that caused the deposition of the individual sand bodies hosting the producible hydrocarbon. ?? 1994 Oxford University Press.

Nonrenewable Resources↗

USGS2005

CO2 dynamics in the Amargosa Desert: Fluxes and isotopic speciation in a deep unsaturated zone

Natural unsaturated-zone gas profiles at the U.S. Geological Survey's Amargosa Desert Research Site, near Beatty, Nevada, reveal the presence of two physically and isotopically distinct CO 2 sources, one shallow and one deep. The shallow source derives from seasonally variable autotrophic and heterotrophic respiration in the root zone. Scanning electron micrograph results indicate that at least part of the deep CO 2 source is associated with calcite precipitation at the 110-m-deep water table. We use a geochemical gas-diffusion model to explore processes of CO 2 production and behavior in the unsaturated zone. The individual isotopic species 12 CO 2 , 13 CO 2 , and 14 CO 2 are treated as separate chemical components that diffuse and react independently. Steady state model solutions, constrained by the measured δ 13 C (in CO 2 ), and δ 14 C (in CO 2 ) profiles, indicate that the shallow CO 2 source from root and microbial respiration composes ∼97% of the annual average total CO 2 production at this arid site. Despite the small contribution from deep CO 2 production amounting to ∼0.1 mol m −2 yr −1 , upward diffusion from depth strongly influences the distribution of CO 2 and carbon isotopes in the deep unsaturated zone. In addition to diffusion from deep CO 2 production, 14 C exchange with a sorbed CO 2 phase is indicated by the modeled δ 14 C profiles, confirming previous work. The new model of carbon-isotopic profiles provides a quantitative approach for evaluating fluxes of carbon under natural conditions in deep unsaturated zones.

Water Resources Research↗

USGS2019

Perspective: Developing flow policies to balance the water needs of humans and wetlands requires a landscape scale approach inclusive of future scenarios and multiple timescales

Maintenance of the natural flow regime is essential for continued wetland integrity; however, the flow regime is greatly influenced by both natural and anthropogenic forces. Wetlands may be particularly susceptible to altered flow regimes as they are directly impacted by water flows at a variety of time scales. In Puerto Rico, contemporary water management is decreasing freshwater recharge to wetlands and contributes to the salinization of important coastal wetlands as sea levels rise. Further, downscaled climate models predict an increase in drought frequency, intensity, and duration by mid-century. Conflicts over water allocation seem imminent between human and ecological needs. Current minimum flow policies are insufficient given the complexities of ecosystem processes and the changes in precipitation patterns and sea level rise that are expected in the future. Improved flow policies need to be established that reflect the functional relationships between specific representative ecological resources and components of the natural flow regime across all relevant time scales. Similarly, flow policies need to be developed within a landscape scale to implicitly address the socio-ecological trade-offs as well as the complexities of water management. Multi-disciplinary collaborations will be essential for increasing our resiliency to anticipated future changes.

Wetlands↗

USGS2020

Observations of an extreme atmospheric river storm with a diverse sensor network

Observational networks enhance real‐time situational awareness for emergency and water resource management during extreme weather events. We present examples of how a diverse, multitiered observational network in California provided insights into hydrometeorological processes and impacts during a 3‐day atmospheric river storm centered on 14 February 2019. This network, which has been developed over the past two decades, aims to improve understanding and mitigation of effects from extreme storms influencing water resources and natural hazards. We combine atmospheric reanalysis output and additional observations to show how the network allows: (1) the validation of record cool season precipitable water observations over southern California; (2) the identification of phenomena that produce natural hazards and present difficulties for short‐term weather forecast models, such as extreme precipitation amounts and snow level variability; (3) the use of soil moisture data to improve hydrologic model forecast skill in northern California's Russian River basin; and (4) the combination of meteorological data with seismic observations to identify when a large avalanche occurred on Mount Shasta. This case study highlights the value of investments in diverse observational assets and the importance of continued support and synthesis of these networks to characterize climatological context and advance understanding of processes modulating extreme weather.

California↗

USGS2024

Peak streamflow trends in South Dakota and their relation to changes in climate, water years 1921–2020

Peak-flow (flood) frequency analysis is essential to water-resources management applications, including the design of critical infrastructure such as bridges and culverts, and floodplain mapping. Federal guidelines for performing peak-flow flood frequency analyses are presented in a U.S. Geological Survey Techniques and Methods Report known as Bulletin 17C. A basic assumption within Bulletin 17C, which documents the guidelines for determining annual peak streamflow frequency, is that, for basins without major hydrologic alterations (for example, regulation, diversion, and urbanization), statistical properties of the distribution of annual peak streamflows are stationary; that is, the mean, variance, and skew are constant through time. Nonstationarity is a statistical property of a peak-flow series such that the long-term (on the order of decades) distributional properties change one or more times either gradually or abruptly through time. Individual nonstationarities may be attributed to one source such as flow regulation, land-use change, or climate but are often the result of a combination of sources, making detection and attribution of nonstationarities challenging. In response to a growing concern regarding nonstationarity in peak streamflows in the region, the U.S. Geological Survey, in cooperation with the Departments of Transportation of Illinois, Iowa, Michigan, Minnesota, Missouri, South Dakota, and Wisconsin; the Montana Department of Natural Resources and Conservation; and the North Dakota Department of Water Resources, assessed the potential nonstationarity in peak streamflows in the north-central United States. This chapter characterizes the effects of natural hydroclimatic shifts and potential climate change on annual peak streamflows in the State of South Dakota. Annual peak and daily streamflow as well as model-simulated gridded climatic data were examined for temporal monotonic trends, change points, and other statistical properties indicative of changing climatic and environmental conditions. Changes in annual peak and daily flows were evaluated among 13, 35, and 81 qualifying U.S. Geological Survey streamgages for the 75-, 50-, and 30-year trend periods through water year 2020 (the period from October 1, 2019, to September 30, 2020) in South Dakota, respectively. No qualifying streamgages were in the 100-year trend period in the State. Statistical tests for autocorrelation (independent and identically distributed assumption), monotonic trends, and change points in the median and scale are analyzed to evaluate potential stationarity violations (nonstationarity) for performing at-site peak-flow flood-frequency analysis. The trends are reported using a likelihood approach as an alternative to simply reporting significant trends with an arbitrary p -value cutoff point. A distinct east-west spatial pattern of likely upward and downward monotonic trends and change points, respectively, was detected in 75- and 50-year trend periods, but an inconsistent spatial pattern was detected in the 30-year trend period. Additionally, change points in the median annual peak streamflows were detected in the late 1970s and early 1980s in the western part of the State, but in the east, the change point was more commonly detected in 1992–93. A similar east-west spatial pattern of likely upward and downward trends was detected in the annual peak-flow timing, the day of the year of the annal peak streamflow. In the western part of the State, the annual peak streamflows are arriving earlier, but in the east, the annual peak streamflows are arriving later. A peaks-over-threshold (POT) analysis where, on average, there are two events per year (POT2) and four events per year (POT4) was also used to evaluate changes in the frequency (count) of daily streamflows exceeding the threshold. Similar to detected changes in the annual peak streamflow, an east-west likely upward or downward change corresponding to an increase or decrease, respectively, in the frequency of daily streamflow greater than a POT2 and POT4 threshold was detected. A monthly water-balance model was used to evaluate hydroclimatic variation in annual and seasonal precipitation, snowfall, potential evapotranspiration, and soil moisture storage for all qualifying streamgages in the 75-, 50-, and 30-year trend periods. Detected trends in the annual hydroclimatic metrics for the 75- and 50-year trend periods indicate a spatially consistent statewide increase in precipitation, decrease in snowfall, increase in potential evapotranspiration, and increase in soil moisture storage. Furthermore, detected trends in seasonal precipitation in the 75- and 50-year trend periods highlight a pronounced change in precipitation in winter and later into the summer season, especially in the 50-year trend period in the eastern part of the State. Statewide increases in seasonal soil moisture storage were also detected, highlighting year-round increasing flood magnitudes, particularly in the eastern part of the State. Based on the results of these stationarity tests for the qualifying streamgages in South Dakota among the 75-, 50-, and 30-year trend periods, consistent temporal and spatial patterns of nonstationarity were detected among the 75- and 50-year trend periods. Furthermore, when nonstationarity is detected in daily streamflow, increased streamflow and volume (increasing frequency in POT), as well as potentially bridge scour, may have implications on culvert and highway design in the eastern part of South Dakota. Thus, when performing at-site peak-flow flood-frequency analyses in South Dakota, potential nonstationarities and alternative approaches are important considerations.

South Dakota↗

USGS2014

Brood surveys and hunter observations used to predict gobbling activity wild turkeys in Mississippi

The Mississippi Department of Wildlife, Fisheries, and Parks utilize data from turkey hunter observations and brood surveys from across the state to manage wild turkey Meleagris gallopavo populations. Since 1995, hunters have collected gobbling and jake observation data, while the Mississippi Department of Wildlife, Fisheries, and Parks' personnel and cooperating wildlife managers of several natural resource agencies throughout the state have collected brood survey data. Both sources of data serve to forecast poult recruitment and gobbling activity. The objective of this study was to evaluate if these data can serve as a viable predictor of gobbling activity. We used three mixed models to investigate the relationship between the number of jakes observed per hour of hunting 1 y prior and the total number of poults per hens 2 y prior (model 1), number of gobblers heard per hour of hunting and the number of jakes observed per hour of hunting 1 y prior (model 2), the number of gobblers heard per hour of hunting and the total number poults per total hens observed 2 y prior (model 3) using data from 1995 to 2008 among five wild turkey management regions encompassing the state. We incorporated region as a random effect to account for spatial variation. We found the number of jakes observed per hour of hunting 1 y prior correlated with the total number of poults per total hens observed 2 y prior. We also found the number of gobblers heard per hour of hunting correlated with the number of jakes observed per hour of hunting 1 y prior. Additionally, we found that the total poults per total hens observed 2 y prior was correlated to the number of gobblers heard per hour of hunting. Our results show promise for using indices of gobbling activity, jake observations, and brood surveys to estimate gobbling activity.

Journal of Fish and Wildlife Management↗

USGS2015

Hydrologic record extension of water-level data in the Everglades Depth Estimation Network (EDEN), 1991-99

The real-time Everglades Depth Estimation Network (EDEN) has been established to support a variety of scientific and water management purposes. The expansiveness of the Everglades, limited number of gaging stations, and extreme sensitivity of the ecosystem to small changes in water depth have created a need for accurate water-level and water-depth maps. The EDEN water-surface elevation model uses data from approximately 240 gages in the Everglades to create daily continuous interpolations of the water-surface elevation and water depth for the freshwater portion of the Everglades from 2000 to the present (2014). These maps provide hydrologic data previously unavailable for assessing biological and ecological studies. Ecologists working in the Everglades expressed a need to the EDEN project team for daily EDEN water-level surfaces from 1990 to 1999. The additional 10 years of surfaces will provide ecologists and resource managers with two decades (1991–2011) of surfaces to analyze hydrologic dynamics. Before 2000, many of the EDEN gages used to generate water surfaces were not in operation. These datasets were extended to provide estimations of hydrologic time-series histories. The general approach to the record extension (hindcasts) was to (1) create a database of available data from 1990 to the present; (2) use dynamic cluster analysis to group stations with similar hydrologic behaviors for subareas of the Everglades with a large number of stations; (3) use results from the cluster analysis to select candidate explanatory variables; (4) develop linear regression or artificial neural network models to extend water-level records; and (5) evaluate record extensions by using model performance statistics and comparison of water-surface maps for similar hydrologic conditions for the hindcasted period (1991–99) and measured period (2000–11). To hindcast and fill data records, 214 empirical models were developed—189 are linear regression models and 25 are artificial neural network models. The coefficient of determination (R 2 ) for 163 of the models is greater than 0.80 and the median percent model error (root mean square error divided by the range of the measured data) is 5 percent. To evaluate the performance of the hindcast models as a group, contour maps of modeled water-level surfaces at 2-centimeter (cm) intervals were generated using the hindcasted data. The 2-cm contour maps were examined for selected days to verify that water surfaces from the EDEN model are consistent with the input data. The biweekly 2-cm contour maps did show a higher number of issues during days in 1990 as compared to days after 1990. May 1990 had the lowest water levels in the Everglades of the 21-year dataset used for the hindcasting study. To hindcast these record low conditions in 1990, many of the hindcast models would require large extrapolations beyond the range of the predictive quality of the models. For these reasons, it was decided to limit the hindcasted data to the period January 1, 1991, to December 31, 1999. Overall, the hindcasted and gap-filled data are assumed to provide reasonable estimates of station-specific water-level data for an extended historical period to inform research and natural resource management in the Everglades.

Florida↗