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At least 469 records · Page 26Linked to original sources
USGS2017

A comment on “temporal variation in survival and recovery rates of lesser scaup”

Concerns about declines in the abundance of lesser scaup ( Aythya affinis ) have promoted a number of analyses to understand reasons for this decline. Unfortunately, most of these analyses, including that of Arnold et al. (2016 Journal of Wildlife Management 80: 850–861), are based on observational studies leading to weak inference. Although we commend the efforts of Arnold et al. (2016 Journal of Wildlife Management 80: 850–861), we think their conclusions are over-stated given their retrospective analysis. Further, we note a number of inconsistencies in their reasoning and offer alternative conclusions that can be drawn from their analysis. Given the uncertainty still surrounding management of lesser scaup, we do not believe it is prudent to abandon or greatly modify adaptive management approaches designed specifically to make optimal decisions in the face of uncertainty. The current learning-based and recursive approach to management appears to be providing adequate guidance for harvest without punctuated changes to harvest levels, as Arnold et al. (2016 Journal of Wildlife Management 80: 850–861) recommend.

Journal of Wildlife Management↗
USGS2021

Drivers of extreme water levels in a large, urban, high-energy coastal estuary – A case study of the San Francisco Bay

Reliable and long-term hindcast data of water levels are essential in quantifying return period and values of extreme water levels. In order to inform design decisions on a local flood control district level, process-based numerical modeling has proven an essential tool to provide the needed temporal and spatial coverage for different extreme value analysis methods. To determine the importance of different physical processes to the extreme water levels we developed a process-based numerical model (Delft3D Flexible Mesh) and applied it to simulate a large, urban, high-energy coastal estuary (the San Francisco Bay). The unstructured grid with 1D/2DH model elements, allows for efficient model simulations and therefore it was possible to simulate over 70 years between 1950 and 2019. Results show significant skill in reproducing observations for the entire modeled time period with an average root-mean-square error of 8.0 cm. A process-based modeling approach allows for the explicit in- and exclusion of different physical processes to quantify their importance to the extremes. For the 100-year still water level (SWL), tide (70%) and non-tidal residual (NTR) (25%) explain the majority of the simulated high water levels in the Bay relative to Mean Higher High Water (MHHW). However, closer to the Delta, local fluvial inflow increases in importance. For longer return periods, the importance of tide decreases and the importance of remote NTRs and fluvial inflow increases.

California↗
USGS2009

Assessing rates of forest change and fragmentation in Alabama, USA, using the vegetation change tracker model

Forest change is of great concern for land use decision makers and conservation communities. Quantitative and spatial forest change information is critical for addressing many pressing issues, including global climate change, carbon budgets, and sustainability. In this study, our analysis focuses on the differences in geospatial patterns and their changes between federal forests and nonfederal forests in Alabama over the time period 1987–2005, by interpreting 163 Landsat Thematic Mapper (TM) scenes using a vegetation change tracker (VCT) model. Our analysis revealed that for the most part of 1990 s and between 2000 and 2005, Alabama lost about 2% of its forest on an annual basis due to disturbances, but much of the losses were balanced by forest regeneration from previous disturbances. The disturbance maps revealed that federal forests were reasonably well protected, with the fragmentation remaining relatively stable over time. In contrast, nonfederal forests, which are predominant in area share (about 95%), were heavily disturbed, clearly demonstrating decreasing levels of fragmentation during the time period 1987–1993 giving way to a subsequent accelerating fragmentation during the time period 1994–2005. Additionally, the identification of the statistical relationships between forest fragmentation status and forest loss rate and forest net change rate in relation to land ownership implied the distinct differences in forest cutting rate and cutting patterns between federal forests and nonfederal forests. The forest spatial change information derived from the model has provided valuable insights regarding regional forest management practices and disturbance regimes, which are closely associated with regional economics and environmental concerns.

Forest Ecology and Management↗
USGS2018

The potential for citizen science to produce reliable and useful information in ecology

We examined features of citizen science that influence data quality, inferential power, and usefulness in ecology. As background context for our examination, we considered topics such as ecological sampling (probability based, purposive, opportunistic), linkage between sampling technique and statistical inference(designbased,modelbased),andscientificparadigms(confirmatory,exploratory).Wedistinguished several types of citizen science investigations, from intensive research with rigorous protocols targeting clearly articulated questions to mass-participation internet-based projects with opportunistic data collection lacking samplingdesign,andexaminedoverarchingobjectives,design,analysis,volunteertraining,andperformance. We identified key features that influence data quality: project objectives, design and analysis, and volunteer training and performance. Projects with good designs, trained volunteers, and professional oversight can meet statistical criteria to produce high-quality data with strong inferential power and therefore are well suited for ecological research objectives. Projects with opportunistic data collection, little or no sampling design, and minimal volunteer training are better suited for general objectives related to public education or data exploration because reliable statistical estimation can be difficult or impossible. In some cases, statistically robust analytical methods, external data, or both may increase the inferential power of certain opportunistically collected data. Ecological management, especially by government agencies, frequently requires data suitable for reliable inference. With standardized protocols, state-of-the-art analytical methods, and well-supervised programs, citizen science can make valuable contributions to conservation by increasing the scope of species monitoring efforts. Data quality can be improved by adhering to basic principles of data collection and analysis, designing studies to provide the data quality required, and including suitable statistical expertise, thereby strengthening the science aspect of citizen science and enhancing acceptance by the scientific community and decision makers.

Conservation Biology↗
USGS2024

Matching decision support modeling frameworks to disease emergence stages and associated management objectives

Wildlife disease management decisions often require rapid responses to situations that are fraught with uncertainty. By recognizing that management is implemented to achieve specific objectives, resource managers and science partners can identify an analysis technique and develop a monitoring plan to evaluate management effectiveness. For emerging infectious diseases, objectives may take several distinct forms, dependent on the perceived stage of disease emergence (i.e., pre-epidemic, early outbreak, mid-epidemic, and endemic), the expected rate of spread, and the anticipated effect of the disease on host populations. Identifying modeling techniques and metrics that are linked to management objectives will require early and consistent communication between managers and science partners. We link modeling approaches that can be used to forecast and evaluate the performance of intervention strategies with a range of disease management objectives. Our aim is to help scientists recognize alternative modeling approaches which may better align with different forms of disease management objectives, and to help managers evaluate the relevance of proposed modeling approaches to their specified objectives for disease management. Recognizing that disease management objectives can take different forms, and thus require different modeling approaches, can help wildlife disease response teams (i.e., natural resource managers, scientists, and stakeholders working collaboratively) better prepare and respond to disease threats.

Conservation Science and Practice↗
USGS2020

Changes in capture rates and body size among vertebrate species occupying an insular urban habitat reserve

Long‐term ecological monitoring provides valuable and objective scientific information to inform management and decision‐making. In this article, we analyze 22 years of herpetofauna monitoring data from the Point Loma Ecological Conservation Area (PLECA), an insular urban reserve near San Diego, CA. Our analysis showed that counts of individuals for one of the four most common terrestrial vertebrates declined, whereas counts for other common species increased or remained stable. Two species exhibited declines in adult body length, whereas biomass pooled over the five most common species increased over time and was associated with higher wet season precipitation. Although the habitat and vegetation at PLECA have remained protected and intact, we suspect that changes in arthropod communities may be driving changes in the abundance, growth, and development of insectivorous lizards. This study underscores the value of long‐term monitoring for establishing quantitative baselines to assess biological changes that would otherwise go undetected.

California↗
USGS2010

Importance of coastal change variables in determining vulnerability to sea- and lake-level change

In 2001, the U.S. Geological Survey began conducting scientific assessments of coastal vulnerability to potential future sea- and lake-level changes in 22 National Park Service sea- and lakeshore units. Coastal park units chosen for the assessment included a variety of geological and physical settings along the U.S. Atlantic, Pacific, Gulf of Mexico, Gulf of Alaska, Caribbean, and Great Lakes shorelines. This research is motivated by the need to understand and anticipate coastal changes caused by accelerating sea-level rise, as well as lake-level changes caused by climate change, over the next century. The goal of these assessments is to provide information that can be used to make long-term (decade to century) management decisions. Here we analyze the results of coastal vulnerability assessments for several coastal national park units. Index-based assessments quantify the likelihood that physical changes may occur based on analysis of the following variables: tidal range, ice cover, wave height, coastal slope, historical shoreline change rate, geomorphology, and historical rate of relative sea- or lake-level change. This approach seeks to combine a coastal system's susceptibility to change with its natural ability to adapt to changing environmental conditions, and it provides a measure of the system's potential vulnerability to the effects of sea- or lake-level change. Assessments for 22 park units are combined to evaluate relationships among the variables used to derive the index. Results indicate that Atlantic and Gulf of Mexico parks have the highest vulnerability rankings relative to other park regions. A principal component analysis reveals that 99% of the index variability can be explained by four variables: geomorphology, regional coastal slope, water-level change rate, and mean significant wave height. Tidal range, ice cover, and historical shoreline change are not as important when the index is evaluated at large spatial scales (thousands of kilometers). ?? 2010 Coastal Education and Research Foundation.

Journal of Coastal Research↗
USGS2009

Gap Analysis -A geographic approach to planning for biological diversity

The Mission of the Gap Analysis Project (GAP) is to promote conservation by providing broad geographic information on biological diversity to resource managers, planners, and policy makers who can use the information to make informed decisions. As part of the National Biological Information Infrastructure (NBII) —a collaborative program to provide increased access to data and information on the nation’s biological resources--GAP data and analytical tools have been used in hundreds of applications: from basic research to comprehensive state wildlife plans; from educational projects in schools to ecoregional assessments of biodiversity. The challenge: keeping common species common means protecting them BEFORE they become threatened. To do this on a state or regional basis requires key information such as land cover descriptions, predicted distribution maps for native animals, and an assessment of the level of protection currently given to those plants and animals. GAP works cooperatively with Federal, state, and local natural resource professionals and academics to provide this kind of information. GAP activities focus on the creation of state and regional databases and maps that depict patterns of land management, land cover, and biodiversity. These data can be used to identify “gaps” in conservation--instances where an animal or plant community is not adequately represented on the existing network of conservation lands. GAP is administered through the U.S. Geological Survey. Through building partnerships among disparate groups, GAP hopes to foster the kind of collaboration that is needed to address conservation issues on a broad scale.

GAP Bulletin↗
USGS2011

Coordinating standards and applications for optical water quality sensor networks

Joint USGS-CUAHSI Workshop: In Situ Optical Water Quality Sensor Networks; Shepherdstown, West Virginia, 8-10 June 2011; Advanced in situ optical water quality sensors and new techniques for data analysis hold enormous promise for advancing scientific understanding of aquatic systems through measurements of important biogeochemical parameters at the time scales over which they vary. High-frequency and real-time water quality data also provide the opportunity for early warning of water quality deterioration, trend detection, and science-based decision support. However, developing networks of optical sensors in freshwater systems that report reliable and comparable data across and between sites remains a challenge to the research and monitoring community. To address this, the U.S. Geological Survey (USGS) and the Consortium of Universities for the Advancement of Hydrologic Science, Inc. (CUAHSI), convened a 3-day workshop to explore ways to coordinate development of standards and applications for optical sensors, as well as handling, storage, and analysis of the continuous data they produce.

Conference Paper↗
USGS2022

Valuing angling on reservoirs using benefit transfer

Economic assessments are rarely applied to inland recreational fisheries for management purposes, especially when compared to fish, habitat, and creel assessments, yet economic assessments can provide critical information for management decisions. We provide a brief overview of economic value, key terminology, and existing economic techniques to address these issues. Benefit transfer, a technique used to measure economic value when an original analysis is not practicable, is conducted by drawing on existing estimates of economic value in similar contexts. We describe an application of benefit transfer to measure the economic value of several recreational fisheries in Nebraska, USA. We examine two approaches to benefit transfer—value transfer and function transfer—which we demonstrate estimate similar economic values for fishing site access but substantially different economic values for catch rate improvements at some reservoirs. We encourage agencies that are responsible for inland recreational fisheries management to consider economic assessment, especially benefit transfer, as a critical tool in the management toolbox.

North American Journal of Fisheries Management↗
USGS2017

Microsatellite marker development from next-generation sequencing in the New England cottontail (Sylvilagus transitionalis) and cross-amplification in the eastern cottontail (S. floridanus)

Objective The New England cottontail ( Sylvilagus transitionalis ) is a species of high conservation priority in the Northeastern United States, and was a candidate for federal listing under the Endangered Species Act until a recent decision determined that conservation actions were sufficient to preclude listing. The aim of this study was to develop a suite of microsatellite loci to guide future research efforts such as the analysis of population genetic structure, genetic variation, dispersal, and genetic mark-recapture population estimation. Results Thirty-five microsatellite markers containing tri- and tetranucleotide sequences were developed from shotgun genomic sequencing of tissue from S. transitionalis , S. obscurus , and S. floridanus . These loci were screened in n = 33 wild S. transitionalis sampled from a population in eastern Massachusetts, USA. Thirty-two of the 35 loci were polymorphic with 2–6 alleles, and observed heterozygosities of 0.06–0.82. All loci conformed to Hardy–Weinberg Equilibrium proportions and there was no evidence of linkage disequilibrium or null alleles. Primers for 33 of the 35 loci amplified DNA extracted from n = 6 eastern cottontail ( S. floridanus ) samples, of which nine revealed putative species-diagnostic alleles. These loci will provide a useful tool for conservation genetics investigations of S. transitionalis and a potential diagnostic species assay for differentiating sympatric eastern and New England cottontails.

Massachusetts↗
USGS2009

The National Map - geographic names

The Geographic Names Information System (GNIS), developed by the U.S. Geological Survey (USGS) in cooperation with the U.S. Board on Geographic Names (BGN), contains information about the official names for places, features, and areas in the 50 States, the District of Columbia, the territories and outlying areas of the United States, including Antarctica. It is the geographic names component of The National Map. The BGN maintains working relationships with State names authorities to cooperate in achieving the standardization of geographic names. The GNIS contains records on more than 2 million geographic names in the United States - from populated places, schools, reservoirs, and parks to streams, valleys, springs, ridges, and every feature type except roads and highways. Entries include information such as the federally-recognized name and variant names and spellings for the feature; former names; the status of the name as determined by the BGN; county or counties in which each named feature is located; geographic coordinates that locate the approximate center of an aerial feature or the mouth and source of a linear feature, such as a stream; name of the cell of the USGS topographic map or maps on which the feature may appear; elevation figures derived from the National Elevation Dataset; bibliographic code for the source of the name; BGN decision dates and historical information are available for some features. Data from the GNIS are used for emergency preparedness, mapmaking, local and regional planning, service delivery routing, marketing, site selection, environmental analysis, genealogical research, and other applications.

Fact Sheet↗
USGS1993

Geohydrologic systems in Kansas, geohydrology of the Great Plains aquifer system

Sedimentary rocks of Late Cambrian through Early Cretaceous age in Kansas are part of a regional flow system of hydraulically connected aquifers and confining units. Future demands for water require that these deeply buried rocks be studied to describe hydrologic properties and ground-water-flow conditions and to provide information that will serve as the basis for decisions concerning the protection and the management of the water resources contained therein, Toward this end, the U.S. Geological Survey, as a part of its Central Midwest Regional Aquifer-System Analysis (CMRASA), began a 5-year hydrologic investigation of this regional flow system in Arkansas, Colorado, Kansas, Missouri, Nebraska, New Mexico, Oklahoma, South Dakota, and Texas (Jorgensen and Signor, 1981). This chapter is one of nine contained in Hydrologic Investigations Atlas HA-722, which present a description of the physical framework (Chapters B-F) and the geohydrology (Chapters G-I} of principal aquifers and confining systems in Upper Cambrian through Lower Cretaceous rocks in Kansas; the stratigraphic relations of these geohydrologic systems are discussed in detail in Chapter A (Wolf and others, 1990). This chapter (G) describes the geohydrology of the Great Plains aquifer system; the physical framework of the Great Plains aquifer system is presented in Chapter B (Spinazola and others, 1992). The maps in this chapter are based on existing data from selected geophysical and lithologic logs, drill-stem tests, water-level measurements, water-quality analyses, and published maps of stratigraphically equivalent units. An index to the geohydrologic data compiled for the CMRASA in Kansas is presented in Spinazola and others (1987). For the most part, data used to construct the maps were collected over many years and do not reflect aquifer conditions for any specific time period.

Kansas↗
USGS1998

A demonstration of the instream flow incremental methodology, Shenandoah River, Virginia

Current and projected demands on the water resources of the Shenandoah River have increased concerns for the potential effect of these demands on the natural integrity of the Shenandoah River system. The Instream Flow Incremental Method (IFIM) process attempts to integrate concepts of water-supply planning, analytical hydraulic engineering models, and empirically derived habitat versus flow functions to address water-use and instream-flow issues and questions concerning life-stage specific effects on selected species and the general well being of aquatic biological populations. The demonstration project also sets the stage for the identification and compilation of the major instream-flow issues in the Shenandoah River Basin, development of the required multidisciplinary technical team to conduct more detailed studies, and development of basin specific habitat and flow requirements for fish species, species assemblages, and various water uses in the Shenandoah River Basin. This report presents the results of an IFIM demonstration project, conducted on the main stem Shenandoah River in Virginia, during 1996 and 1997, using the Physical Habitat Simulation System (PHABSIM) model. Output from PHABSIM is used to address the general flow requirements for water supply and recreation and habitat for selected life stages of several fish species. The model output is only a small part of the information necessary for effective decision making and management of river resources. The information by itself is usually insufficient for formulation of recommendations regarding instream-flow requirements. Additional information, for example, can be obtained by analysis of habitat time-series data, habitat duration data, and habitat bottlenecks. Alternative-flow analysis and habitat-duration curves are presented.

Virginia↗
USGS1995

Accuracy of migrant landbird habitat maps produced from LANDSAT TM data: Two case studies in southern Belize

The study investigated the utility of Landsat TM data applied to produce geo-referenced habitat maps for two study areas (Toledo and Stann Creek). Locational and non-site-specific map accuracy was evaluated by stratified random sampling and statistical analysis of satellite classification (SCR) versus air photo interpretation results (PIR) for the overall classification and individual classes. The effect of classification scheme specificity on map accuracy was also assessed. A decision criteria was developed for the minimum acceptable level of map performance (i.e., classification accuracy and scheme specificity). A satellite map was deemed acceptable if it has a useful degree of classification specificity, plus either an adequate overall locational agreement (< 70%) and/or non-site specific agreement (Chi Square goodness of fit test results indicating insufficient evidence to reject the null hypothesis that the overall classification distribution for the SCR and PIR are equal). For the most detailed revised classification, overall locational accuracy ranges from 52% (5 classes) for the Toledo to 63% (9 classes) for the Stann Creek. For the least detailed revised classification, overall locational accuracy ranges from 91% (2 classes) for Toledo to 86% (5 classes) for Stann Creek. Considering both location and non-site-specific accuracy results, the most detailed yet insufficient accurate classification for both sites includes low/medium/tall broadleaf forest, broadleaf forest scrub and herb-dominated openings. For these classifications, the overall locational accuracy is 72% for Toledo (4 classes) and 75% for Stann Creek (7 classes). This level of classification detail is suitable for aiding many analyses of migrant landbird habitat use.

Book chapter↗
USGS2008

GAP Analysis Bulletin Number 15

The Mission of the Gap Analysis Project (GAP) <http://gapanalysis.nbii.gov> is to promote conservation by providing broad geographic information on biological diversity to resource managers, planners, and policy makers who can use the information to make informed decisions. As part of the National Biological Information Infrastructure (NBII) <http://www.nbii.gov>?a collaborative program to provide increased access to data and information on the nation?s biological resources--GAP data and analytical tools have been used in hundreds of applications: from basic research to comprehensive state wildlife plans; from educational projects in schools to ecoregional assessments of biodiversity. The challenge: keeping common species common means protecting them BEFORE they become threatened. To do this on a state or regional basis requires key information such as land cover descriptions, predicted distribution maps for native animals, and an assessment of the level of protection currently given to those plants and animals. GAP works cooperatively with Federal, state, and local natural resource professionals and academics to provide this kind of information. GAP activities focus on the creation of state and regional databases and maps that depict patterns of land management, land cover, and biodiversity. These data can be used to identify ?gaps? in conservation--instances where an animal or plant community is not adequately represented on the existing network of conservation lands. GAP is administered through the U.S. Geological Survey. Through building partnerships among disparate groups, GAP hopes to foster the kind of collaboration that is needed to address conservation issues on a broad scale. For more information, contact: John Mosesso National GAP Director 703-648-4079 Kevin Gergely National GAP Operations Manager 208-885-3565

GAP Bulletin↗
USGS2020

Bridging the research-management gap: Landscape ecology in practice on public lands in the western United States

The field of landscape ecology has grown and matured in recent decades, but incorporating landscape science into land management decisions remains challenging. Many lands in the western United States are federally owned and managed for multiple uses, including recreation, conservation, and energy development. We argue for stronger integration of landscape science into the management of these public lands. We open by outlining the relevance of landscape science for public land planning, management, and environmental effects analysis, including pertinent laws and policies. We identify challenges to integrating landscape science into public land management, including the multijurisdictional nature and complicated spatial pattern of public lands, the capacity of agencies to identify and fill landscape science needs, and public perceptions about the meaning of landscape approaches to management. We provide several recent examples related to landscape monitoring, restoration, reclamation, and conservation in which landscape science products were developed specifically to support decision-making. We close by highlighting three actions - elevating the importance of science-management partnerships dedicated to coproducing actionable landscape science products, identifying where landscape science could foster efficiencies in the land-use planning process, and developing scenario-based landscape models for shrublands - that could improve landscape science support for public land planners and managers.

Arizona, California, Colorado, Idaho, Montana, New↗
USGS2017

Designing a solution to enable agency-academic scientific collaboration for disasters

As large-scale environmental disasters become increasingly frequent and more severe globally, people and organizations that prepare for and respond to these crises need efficient and effective ways to integrate sound science into their decision making. Experience has shown that integrating nongovernmental scientific expertise into disaster decision making can improve the quality of the response, and is most effective if the integration occurs before, during, and after a crisis, not just during a crisis. However, collaboration between academic, government, and industry scientists, decision makers, and responders is frequently difficult because of cultural differences, misaligned incentives, time pressures, and legal constraints. Our study addressed this challenge by using the Deep Change Method, a design methodology developed by Stanford ChangeLabs, which combines human-centered design, systems analysis, and behavioral psychology. We investigated underlying needs and motivations of government agency staff and academic scientists, mapped the root causes underlying the relationship failures between these two communities based on their experiences, and identified leverage points for shifting deeply rooted perceptions that impede collaboration. We found that building trust and creating mutual value between multiple stakeholders before crises occur is likely to increase the effectiveness of problem solving. We propose a solution, the Science Action Network, which is designed to address barriers to scientific collaboration by providing new mechanisms to build and improve trust and communication between government administrators and scientists, industry representatives, and academic scientists. The Science Action Network has the potential to ensure cross-disaster preparedness and science-based decision making through novel partnerships and scientific coordination.

Ecology and Society↗