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At least 487 records · Page 27Linked to original sources
USGS1990

Geographic information system as country-level development and monitoring tool, Senegal example

Geographic information systems (GIS) allow an investigator the capability to merge and analyze numerous types of country-level resource data. Hypothetical resource analysis applications in Senegal were conducted to illustrate the utility of a GIS for development planning and resource monitoring. Map and attribute data for soils, vegetation, population, infrastructure, and administrative units were merged to form a database within a GIS. Several models were implemented using a GIS to: analyze development potential for sustainable dryland agriculture; prioritize where agricultural development should occur based upon a regional food budget; and monitor dynamic events with remote sensing. The steps for implementing a GIS analysis are described and illustrated, and the use of a GIS for conducting an economic analysis is outlined. Using a GIS for analysis and display of results opens new methods of communication between resource scientists and decision makers. Analyses yielding country-wide map output and detailed statistical data for each level of administration provide the advantage of a single system that can serve a variety of users.

Conference Paper↗
USGS2005

The New Hampshire watershed tool: a geographic information system tool to estimate streamflow statistics and ground-water-recharge rates

Estimates of low-flow statistics, flow durations, and ground-water-recharge rates are needed to assist water-resource managers in assessing surface-water resources and ground-water availability. Often these estimates are required at ungaged sites where no observed streamflow data are available for analysis. Regression equations for estimating low-flow statistics and flow durations, and for estimating ground-water-recharge rates at ungaged sites have been developed for New Hampshire. However, use of these equations requires numerous input parameters, such as basin and climatic characteristics. This report describes a customized geographic information system (GIS) application, the New Hampshire Watershed Tool, that automates the measurement of the characteristics used for input to the regression equations and calculates the corresponding flow statistics and ground-water-recharge rates.

Open-File Report↗
USGS2018

Leveraging geodetic data to reduce losses from earthquakes

Seismic hazard assessments that are based on a variety of data and the best available science, coupled with rapid synthesis of real-time information from continuous monitoring networks to guide post-earthquake response, form a solid foundation for effective earthquake loss reduction. With this in mind, the Earthquake Hazards Program (EHP) of the U.S. Geological Survey (USGS) Natural Hazards Mission Area (NHMA) engages in a variety of undertakings, both established and emergent, in order to provide high quality products that enable stakeholders to take action in advance of and in response to earthquakes. Examples include the National Seismic Hazard Model (NSHM), development of tools for improved situational awareness such as earthquake early warning (EEW) and operational earthquake forecasting (OEF), research about induced seismicity, and new efforts to advance comprehensive subduction zone science and monitoring. Geodetic observations provide unique and complementary information directly relevant to advancing many aspects of these efforts (fig. 1). EHP scientists have long leveraged geodetic data for a range of influential studies, and they continue to develop innovative observation and analysis methods that push the boundaries of the field of geodesy as applied to natural hazards research. Given the ongoing, rapid improvement in availability, variety, and precision of geodetic measurements, considering ways to fully utilize this observational resource for earthquake loss reduction is timely and essential. This report presents strategies, and the underlying scientific rationale, by which the EHP could achieve the following outcomes: The EHP is an authoritative source for the interpretation of geodetic data and its use for earthquake loss reduction throughout the United States and its territories. The USGS consistently provides timely, high quality geodetic data to stakeholders. Significant earthquakes are better characterized by incorporating geodetic data into USGS event response products and by expanded use of geodetic imaging data to assess fault rupture and source parameters. Uncertainties in the NSHM, and in regional earthquake models, are reduced by fully incorporating geodetic data into earthquake probability calculations. Geodetic networks and data are integrated into the operations and earthquake information products of the Advanced National Seismic System (ANSS). Earthquake early warnings are improved by more rapidly assessing ground displacement and the dynamic faulting process for the largest earthquakes using real-time geodetic data. Methodology for probabilistic earthquake forecasting is refined by including geodetic data when calculating evolving moment release during aftershock sequences and by better understanding the implications of transient deformation for earthquake likelihood. A geodesy program that encompasses a balanced mix of activities to sustain missioncritical capabilities, grows new competencies through the continuum of fundamental to applied research, and ensures sufficient resources for these endeavors provides a foundation by which the EHP can be a leader in the application of geodesy to earthquake science. With this in mind the following objectives provide a framework to guide EHP efforts: Fully utilize geodetic information to improve key products, such as the NSHM and EEW, and to address new ventures like the USGS Subduction Zone Science Plan. Expand the variety, accuracy, and timeliness of post-earthquake information products, such as PAGER (Prompt Assessment of Global Earthquakes for Response), through incorporation of geodetic observations. Determine if geodetic measurements of transient deformation can significantly improve estimates of earthquake probability. Maintain an observational strategy aligned with the target outcomes of this document that includes continuous monitoring, recording of ephemeral observations, focused data collection for use in research, and application-driven data processing and analysis systems. Collaborate on research, development, and operation of affordable, high-precision seafloor geodetic methods that improve earthquake forecasting and event response. Advance computational techniques and instrumentation to enable use of strategies like repeat-pass imagery and low-cost geodetic sensors for earthquake response, monitoring, and research. Engage stakeholders and collaborate with partner institutions to foster operational and research objectives and to safeguard the continued health of geodetic infrastructure upon which we mutually depend. Maintaining a vibrant internal research program provides the foundation by which the EHP can remain an effective and trusted source for earthquake science. Exploiting abundant new data sources, evaluating and assimilating the latest science, and pursuing novel avenues of investigation are means to fulfilling the EHP’s core responsibilities and realizing the important scientific advances envisioned by its scientists. Central to the success of such a research program is engaging personnel with a breadth of competencies and a willingness and ability to adapt these to the program’s evolving priorities, enabling current staff to expand their skills and responsibilities, and planning holistically to meet shared workforce needs. In parallel, collaboration with external partners to support scientific investigations that complement ongoing internal research enables the EHP to strengthen earthquake information products by incorporating alternative perspectives and approaches and to study topics and geographic regions that cannot be adequately covered internally. With commensurate support from technical staff who possess diverse skills, including engineering, information technology, and proficiency in quantitative analysis combined with basic geophysical knowledge, the EHP can achieve the geodetic outcomes identified in this document.

Open-File Report↗
USGS2010

Applications of factor analysis in study of chemistry of groundwater quality, Mojave River Valley, California

Factor analysis is applied to results of chemical analyses of 103 water samples from wells in the Upper and Middle Mojave River valley, San Bernardino County, California. Chemical analyses showed that there are three principal chemical types of water, calcium bicarbonate, sodium sulfate, and sodium chloride, as well as many mixtures of the three. Data were studied by factor analysis to learn the relative importance of each principal ion in determining the variations among the samples, and to examine the possibility of chemical equilibrium between aqueous and solid phases in the aquifers. Most of the covariance in the system may be accounted for by variances of Ca +2 , Mg +2 , Na +1 , SO 4 −2 , and Cl −1 . There is almost identical loading on the constituents Na +1 and Cl −1 . The variance in chemical composition of the hydrochemical system is governed largely by sources of sodium chloride. None of the components is controlled by equilibrium between ions in the water and minerals in the aquifers. Concentrations of NO 3 −1 and F −1 vary independently of other constituents. Geographic distribution of statistical loadings of the principal constituents at individual wells does not reveal sources of the constituents, which must be deduced from geologic and hydrologic evidence. Factor analysis, however, furnished the critical information on chemical relationships basic to the deduction.

California↗
USGS2016

Methods for estimating peak-flow frequencies at ungaged sites in Montana based on data through water year 2011: Chapter F in Montana StreamStats

The U.S. Geological Survey (USGS), in cooperation with the Montana Department of Natural Resources and Conservation, completed a study to update methods for estimating peak-flow frequencies at ungaged sites in Montana based on peak-flow data at streamflow-gaging stations through water year 2011. The methods allow estimation of peak-flow frequencies (that is, peak-flow magnitudes, in cubic feet per second, associated with annual exceedance probabilities of 66.7, 50, 42.9, 20, 10, 4, 2, 1, 0.5, and 0.2 percent) at ungaged sites. The annual exceedance probabilities correspond to 1.5-, 2-, 2.33-, 5-, 10-, 25-, 50-, 100-, 200-, and 500-year recurrence intervals, respectively. Regional regression analysis is a primary focus of Chapter F of this Scientific Investigations Report, and regression equations for estimating peak-flow frequencies at ungaged sites in eight hydrologic regions in Montana are presented. The regression equations are based on analysis of peak-flow frequencies and basin characteristics at 537 streamflow-gaging stations in or near Montana and were developed using generalized least squares regression or weighted least squares regression. All of the data used in calculating basin characteristics that were included as explanatory variables in the regression equations were developed for and are available through the USGS StreamStats application (http://water.usgs.gov/osw/streamstats/) for Montana. StreamStats is a Web-based geographic information system application that was created by the USGS to provide users with access to an assortment of analytical tools that are useful for water-resource planning and management. The primary purpose of the Montana StreamStats application is to provide estimates of basin characteristics and streamflow characteristics for user-selected ungaged sites on Montana streams. The regional regression equations presented in this report chapter can be conveniently solved using the Montana StreamStats application. Selected results from this study were compared with results of previous studies. For most hydrologic regions, the regression equations reported for this study had lower mean standard errors of prediction (in percent) than the previously reported regression equations for Montana. The equations presented for this study are considered to be an improvement on the previously reported equations primarily because this study (1) included 13 more years of peak-flow data; (2) included 35 more streamflow-gaging stations than previous studies; (3) used a detailed geographic information system (GIS)-based definition of the regulation status of streamflow-gaging stations, which allowed better determination of the unregulated peak-flow records that are appropriate for use in the regional regression analysis; (4) included advancements in GIS and remote-sensing technologies, which allowed more convenient calculation of basin characteristics and investigation of many more candidate basin characteristics; and (5) included advancements in computational and analytical methods, which allowed more thorough and consistent data analysis. This report chapter also presents other methods for estimating peak-flow frequencies at ungaged sites. Two methods for estimating peak-flow frequencies at ungaged sites located on the same streams as streamflow-gaging stations are described. Additionally, envelope curves relating maximum recorded annual peak flows to contributing drainage area for each of the eight hydrologic regions in Montana are presented and compared to a national envelope curve. In addition to providing general information on characteristics of large peak flows, the regional envelope curves can be used to assess the reasonableness of peak-flow frequency estimates determined using the regression equations.

Montana↗
USGS2021

The spatial-temporal relationship of blue-winged teal to domestic poultry: Movement state modeling of a highly mobile avian influenza host

1. Migratory waterfowl facilitate long distance dispersal of zoonotic pathogens and are increasingly recognized as contributing to the geographic spread of avian influenza viruses (AIV). AIV are globally distributed and have the potential to produce highly contagious poultry disease, economically impact both large-scale and backyard poultry producers, and raise the specter of epidemics and pandemics in human populations. 2. Because migratory waterfowl behavior varies across multiple spatial and temporal scales, the timing and distribution of wild bird AIV introductions to poultry are also heterogeneous in time and space. To help reduce economic impacts to the poultry industry and enable poultry producers to better anticipate when and where poultry outbreaks may occur, it is critically important to consider the movement ecology of the waterfowl species transporting and transmitting AIV. 3. We used telemetry for a geographically widespread and common AIV host, blue-winged teal ( Spatula discors ; BWTE), to model reservoir host movement states with respect to backyard and commercial poultry facilities in the United States. Our modeling framework enabled us to estimate wild bird proximity to poultry facilities while concurrently assessing the influence of poultry facilities on BWTE movement state transition. Our primary objective was to estimate the likelihood of duck and poultry overlap by estimating when and where BWTE were geographically closest to poultry. 4. Synthesis and applications . Migratory waterfowl facilitate dispersal of the avian influenza viruses that cause highly contagious poultry disease. Movement analysis of blue-winged teal indicates that spatio-temporal overlap between wild birds and poultry facilities varies by season, the poultry type produced (e.g., turkey, chicken), and if the facility is a commercial or backyard operation. These findings are broadly applicable to disease ecology research and can be applied by poultry producers to improve bio-security, enhance poultry management, and prioritize disease surveillance efforts.

Journal of Applied Ecology↗
USGS2022

What common-garden experiments tell us about climate responses in plants

Common garden experiments are indoor or outdoor plantings of species or populations collected from multiple distinct geographic locations, grown together under shared conditions. These experiments examine a range of questions for theory and application using a variety of methods for analysis. The eight papers of this special feature comprise a cross section of contemporary approaches, summarized and synthesized here by what they tell us about the relationships between climate-related trait spectra and fitness optima. Four of the eight papers are based on field experiments in prairie, desert, Mediterranean and boreal biomes. Representative of many common garden experiments, these experiments reveal consistent evidence of traits varying with population climate provenance, but evidence of a tradeoff between growth and tolerance traits or of consistent fitness optimization at home is scant, in contrast to trait theory. Two synthesis papers highlight dominant patterns of trait divergence, including for an exotic invasive species. One theoretical paper warned that unknown kinship relationships between populations can result in the misidentification of adaptive trait divergence. A third synthesis paper formulated novel and ambitious goals for common-garden studies through including measurement of response variables at multiple levels of biological organization. The featured papers discuss multiple avenues for improving common garden studies. Genomic analysis, together with the quantification of kinship relationships, will continue to reveal the influence of environmental drivers on gene selection. Measuring a more complete set of fitness traits, especially for traits related to regeneration, will permit the development of projection models to explicitly link trait spectra, climate patterns and fitness consequences. More standardized data reporting will additionally improve abilities to synthesize findings across experiments. Testing population performance in competition with other species will produce more robust fitness comparisons between genotypes, especially for slower-growing genotypes in higher-resource environments. Adding gardens in and beyond climatic edge locations will furthermore strengthen the understanding of population failure and species exclusion. Finally, there is unrealized potential in adding ecosystem-level observations to common-garden studies that will enhance integrative analysis across scales of biological organization and scientific domains. Synthesis . With novel, creative designs, data integration and synthesis, common garden experiments will continue to advance the understanding of trait ensembles interacting with climate across scales of biological organization, provide pivotal data for global change models and guide ecological applications such as restoration of habitats for rare and climate sensitive species.

Journal of Ecology↗
USGS2023

Geospatial standard operating procedures of the Chesapeake Bay Program

Introduction The Chesapeake Bay Program (CBP) has operated a geographic information system (GIS) program since the early 1990s to address the established and growing need for and use of geospatial data, maps, and analysis within the CBP Partnership. This report is intended to detail the standard operating procedures of the CBP GIS program and address the quality assurance, quality control, and other technical activities that CBP will implement to ensure the commitment of the CBP GIS Team to performance standards (U.S. Environmental Protection Agency, 2003). The report is intended as an update to the 2011 Quality Assurance Project Plan (QAPP). For specialized tasks or analytical projects beyond the scope of this QAPP, a separate specialized QAPP with details on quality control, assurance procedures, and the geospatial methods associated with all aspects of the project may be required.

Open-File Report↗
USGS2009

Status Assessment of Laysan and Black-Footed Albatrosses, North Pacific Ocean, 1923-2005

Over the past century, Laysan (Phoebastria immutabilis) and black-footed (Phoebastria nigripes) albatrosses have been subjected to high rates of mortality and disturbance at the breeding colonies and at sea. Populations were greatly reduced and many colonies were extirpated around the turn of the 20th century as a result of feather hunting. Populations were recovering when military occupation of several breeding islands during World War II led to new population declines at these islands and additional colony extirpations. At sea, thousands of Laysan and black-footed albatrosses were killed each year in high-seas driftnet fisheries, especially from 1978 until the fisheries were banned in 1992. Through the 1990s, there was a growing awareness of the large numbers of albatrosses that were being killed in longline fisheries. During the 1990s, other anthropogenic factors, such as predation by non-native mammals and exposure to contaminants, also were documented to reduce productivity or increase mortality. In response to the growing concerns over the impacts of these threats on albatross populations, the U.S. Fish and Wildlife Service contracted with the U.S. Geological Survey to conduct an assessment of Laysan and black-footed albatross populations. This assessment includes a review of the taxonomy, legal status, geographic distribution, natural history, habitat requirements, threats, and monitoring and management activities for these two species. The second part of the assessment is an analysis of population status and trends from 1923 to 2005. Laysan and black-footed albatrosses forage throughout the North Pacific Ocean and nest on tropical and sub-tropical oceanic islands from Mexico to Japan. As of 2005, 21 islands support breeding colonies of one or both species. The core breeding range is the Hawaiian Islands, where greater than 99 percent of the World's Laysan albatrosses and greater than 95 percent of the black-footed albatrosses nest on the small islands and atolls of the Northwestern Hawaiian Islands. These islands are all protected as part of the Papahanaumokuakea Marine National Monument. Albatrosses are long-lived seabirds with deferred maturity, low fecundity, and high rates of adult survival. Their life history characteristics make populations especially vulnerable, to small increases in adult mortality. The primary threats to Laysan and black-footed albatrosses include interactions with commercial fisheries, predation by introduced mammals, reduced reproductive output due to contaminants, nesting habitat loss and degradation due to human development and invasive plant species, and potential loss and degradation of habitat due to climate change and sea-level rise. Incidental mortality (bycatch) in commercial fisheries is the greatest anthropogenic source of mortality (post-fledging) for both species. We found that longline fishing effort prior to the 1980s was greater than previously estimated and a very significant source of mortality. Regulations to minimize and monitor albatross mortality have been enacted in most U.S. and Canadian longline fisheries, but monitoring of bycatch rates and regulations to minimize seabird mortality are extremely limited in the much larger multinational longline fleets. Management to address threats at the breeding colonies is ongoing and includes eradication or control of non-native species, habitat management, and abatement programs to reduce impacts of contaminants. Effective long-term conservation and management of the Laysan and black-footed albatrosses require management and monitoring at the breeding colonies and at sea and continued assessment of population status and trends. We evaluated the status and trends of Laysan and black-footed albatross populations using linear regression, population viability analysis (PVA), and age-structured matrix models. Analyses were predominantly based on nest-count data gathered at French Frigate Shoals, Laysan Island, and Midw

Scientific Investigations Report↗
USGS2026

Peak-, mean-, and low-streamflow regional-regression equations for natural streamflow in central and western Colorado, 2019

The U.S. Geological Survey (USGS), in cooperation with the Colorado Department of Transportation, developed peak-, mean-, and low-streamflow regional-regression equations for estimating various statistics for natural streamflow in hydrologic regions of central and western Colorado. The peak-streamflow regression equations were developed using data from 418 streamgages, consisting of 15,202 years of record and a mean of approximately 36 years of record per streamgage. The mean- and low-streamflow regional-regression equations were developed using data from 323 streamgages where daily streamflow data were collected year-round. The annual exceedance-probability discharges for each streamgage were computed using the USGS software program PeakFQ. Mean monthly and 7-day minimum and maximum streamflows were computed using the USGS software program SWToolbox. Streamflow-duration values were computed using an R script. The regional-regression equations were determined using data for the period of record for a given streamgage through water year 2019. Geographic information systems datasets were used to develop 55 basin and 42 climatic characteristics, which were evaluated as candidate explanatory variables in the regression analysis. For the peak-streamflow regional-regression equations, the study area was divided into four hydrologic regions based on mean basin elevation, including the Plateau (less than 8,014 feet), Mid-Elevation (8,015 feet to 9,492 feet), Sub-Alpine (9,493 feet to 10,490 feet), and Alpine (greater than 10,490 feet) regions. For the peak-streamflow equations, the selection of basin and climatic characteristics was based on the 1-percent annual exceedance-probability discharge for each hydrologic region. For the mean streamflow, streamflow-duration values, and 7-day minimum and maximum streamflows, the study area was divided into four hydrologic regions based on river basin, including the (1) Colorado-East Slope Headwaters, (2) Green River, (3) Rio Grande, and (4) San Juan-Dolores. For mean streamflows, basin and climatic characteristics were evaluated separately for the annual period and each month for each hydrologic region. Regional regression equations published in this report are available for use in the USGS web-based program StreamStats.

Colorado↗
USGS2004

Regression equations for estimating flood flows for the 2-, 10-, 25-, 50-, 100-, and 500-Year recurrence intervals in Connecticut

Multiple linear-regression equations were developed to estimate the magnitudes of floods in Connecticut for recurrence intervals ranging from 2 to 500 years. The equations can be used for nonurban, unregulated stream sites in Connecticut with drainage areas ranging from about 2 to 715 square miles. Flood-frequency data and hydrologic characteristics from 70 streamflow-gaging stations and the upstream drainage basins were used to develop the equations. The hydrologic characteristics-drainage area, mean basin elevation, and 24-hour rainfall-are used in the equations to estimate the magnitude of floods. Average standard errors of prediction for the equations are 31.8, 32.7, 34.4, 35.9, 37.6 and 45.0 percent for the 2-, 10-, 25-, 50-, 100-, and 500-year recurrence intervals, respectively. Simplified equations using only one hydrologic characteristic-drainage area-also were developed. The regression analysis is based on generalized least-squares regression techniques. Observed flows (log-Pearson Type III analysis of the annual maximum flows) from five streamflow-gaging stations in urban basins in Connecticut were compared to flows estimated from national three-parameter and seven-parameter urban regression equations. The comparison shows that the three- and seven- parameter equations used in conjunction with the new statewide equations generally provide reasonable estimates of flood flows for urban sites in Connecticut, although a national urban flood-frequency study indicated that the three-parameter equations significantly underestimated flood flows in many regions of the country. Verification of the accuracy of the three-parameter or seven-parameter national regression equations using new data from Connecticut stations was beyond the scope of this study. A technique for calculating flood flows at streamflow-gaging stations using a weighted average also is described. Two estimates of flood flows - one estimate based on the log-Pearson Type III analyses of the annual maximum flows at the gaging station, and the other estimate from the regression equation - are weighted together based on the years of record at the gaging station and the equivalent years of record value determined from the regression. Weighted averages of flood flows for the 2-, 10-, 25-, 50-, 100-, and 500-year recurrence intervals are tabulated for the 70 streamflow-gaging stations used in the regression analysis. Generally, weighted averages give the most accurate estimate of flood flows at gaging stations. An evaluation of the Connecticut's streamflow-gaging network was performed to determine whether the spatial coverage and range of geographic and hydrologic conditions are adequately represented for transferring flood characteristics from gaged to ungaged sites. Fifty-one of 54 stations in the current (2004) network support one or more flood needs of federal, state, and local agencies. Twenty-five of 54 stations in the current network are considered high-priority stations by the U.S. Geological Survey because of their contribution to the longterm understanding of floods, and their application for regionalflood analysis. Enhancements to the network to improve overall effectiveness for regionalization can be made by increasing the spatial coverage of gaging stations, establishing stations in regions of the state that are not well-represented, and adding stations in basins with drainage area sizes not represented. Additionally, the usefulness of the network for characterizing floods can be maintained and improved by continuing operation at the current stations because flood flows can be more accurately estimated at stations with continuous, long-term record.

Connecticut↗
USGS2023

Historical Structure from Motion (HSfM): Automated processing of historical aerial photographs for long-term topographic change analysis

Precisely measuring the Earth’s changing surface on decadal to centennial time scales is critical for many science and engineering applications, yet long-term records of quantitative landscape change are often temporally and geographically sparse. Archives of scanned historical aerial photographs provide an opportunity to augment these records with accurate elevation measurements that capture the historical state of the Earth surface. Structure from Motion (SfM) photogrammetry workflows produce high-quality digital elevation models (DEMs) and orthoimage mosaics from these historical images, but time-intensive tasks like manual image preprocessing (e.g., fiducial marker identification) and ground control point (GCP) selection impede processing at scale. We developed an automated method to process historical images and generate self-consistent time series of high-resolution (0.5–2 m) DEMs and orthomosaics, without manual GCP selection. The method relies on SfM to correct camera interior and exterior orientation and a robust multi-stage co-registration approach using modern reference terrain datasets for geolocation refinement. We demonstrate the method using scanned images from the North American Glacier Aerial Photography (NAGAP) archive collected between 1967 and 1997. We present results for two sites with variable photo acquisition geometry and overlap — Mount Baker and South Cascade Glacier in Washington State, USA. The automated method corrects initial camera position errors of several kilometers and produces accurately georeferenced, high-resolution DEMs and orthoimages, regardless of camera configuration, acquisition geometry, terrain characteristics, and reference DEM properties. The average RMS reprojection error following bundle adjustment optimization was 0.67 px (0.15 m) for the 261 images contributing to 10 final DEM mosaics between 1970 and 1992 at Mount Baker, and 0.65 px (0.13 m) for the 243 images contributing to 18 individual DEMs between 1967 and 1997 at South Cascade Glacier. The relative accuracy of elevation values in the historical time series stacks was 0.68 m at Mount Baker and 0.37 m at South Cascade Glacier. Our products have reduced systematic error and improved accuracy compared to DEM products generated using SfM with manual GCP selection. Final elevation change measurement precision was ∼ "> ∼ 0.7–1.0 m over a 30-year period, enabling the study of processes with rates as low as ∼ "> ∼ 1-3 cm/yr. Our results demonstrate the potential of this scalable method to rapidly process archives of historical imagery and deliver new quantitative insights on long-term geodetic change and Earth surface processes.

Washington↗
USGS2004

Fish-habitat modeling for gap analysis to conserve the endangered Topeka shiner (Notropis topeka)

Decision support tools that predict fish distribution over broad spatial scales are needed to assist in planning watershed management and endangered species recovery. We developed a geographical information system model with multivariate logistic regression to rank valley segments for probable occurrence of the endangered Topeka shiner (Notropis topeka) using stream condition variables (stream size, groundwater potential, channel slope, streamflow, network position) and land-cover variables (percent pasture, percent trees) in streams characteristic of the North American Great Plains. The stream condition and land-cover models correctly classified 89% and 68% of outcomes (i.e., presence or absence), respectively. Field tests of maps of predicted species distribution resulted in more species occurrences than expected in valley segments classified as high potential for presence and less than expected in low-potential valley segments. Gaps between high-priority segments and protected land parcels were found in all basins. In 37 basins with Topeka shiners, protected land coverage was <1% in 17 basins, 1-5% in 10 basins, and 5-21.8% in 10 basins. Conservation activities in gaps are long-term conservation measures, but maps of predicted species distribution have many immediate applications.

Canadian Journal of Fisheries and Aquatic Sciences↗
USGS2018

Genetic population structure of Shoal Bass within their native range

Endemic to the Apalachicola River basin of the southeastern USA, the Shoal Bass Micropterus cataractae is a fluvial‐specialist sport fish that is imperiled because of anthropogenic habitat alteration. To counter population declines, restorative stocking efforts are becoming an increasingly relevant management strategy. However, population genetic structure within the species is currently unknown, but it could influence management decisions, such as brood source location. Leveraging a collaborative effort to collect and genotype specimens with 16 microsatellite loci, our objective was to characterize hierarchical population structure and genetic differentiation of the Shoal Bass across its native range, including an examination of structuring mechanisms, such as relatedness and inbreeding levels. Specimens identified as Shoal Bass were collected from 13 distinct sites ( N ranged from 17 to 209 per location) and were then taxonomically screened to remove nonnative congeners and hybrids (pure Shoal Bass N ranged from 13 to 183 per location). Our results revealed appreciable population structure, with five distinct Shoal Bass populations identifiable at the uppermost hierarchical level that generally corresponded with natural geographic features and anthropogenic barriers. Substructure was recovered within several of these populations, wherein differences appeared related to spatial isolation and local population dynamics. An analysis of molecular variance revealed that 3.6% of the variation in our data set was accounted for among three larger river drainages, but substructure within each river drainage also explained an additional 8.9% of genetic variation, demonstrating that management at a scale lower than the river drainage level would likely best conserve genetic diversity. Results provide a population genetic framework that can inform future management decisions, such as brood source location, so that genetic diversity within and among populations is conserved and overall adaptability of the species is maintained.

Apalachicola–Chattahoochee–Flint River Basin↗
USGS2005

A regional classification scheme for estimating reference water quality in streams using land-use-adjusted spatial regression-tree analysis

Various approaches are used to subdivide large areas into regions containing streams that have similar reference or background water quality and that respond similarly to different factors. For many applications, such as establishing reference conditions, it is preferable to use physical characteristics that are not affected by human activities to delineate these regions. However, most approaches, such as ecoregion classifications, rely on land use to delineate regions or have difficulties compensating for the effects of land use. Land use not only directly affects water quality, but it is often correlated with the factors used to define the regions. In this article, we describe modifications to SPARTA (spatial regression-tree analysis), a relatively new approach applied to water-quality and environmental characteristic data to delineate zones with similar factors affecting water quality. In this modified approach, land-use-adjusted (residualized) water quality and environmental characteristics are computed for each site. Regression-tree analysis is applied to the residualized data to determine the most statistically important environmental characteristics describing the distribution of a specific water-quality constituent. Geographic information for small basins throughout the study area is then used to subdivide the area into relatively homogeneous environmental water-quality zones. For each zone, commonly used approaches are subsequently used to define its reference water quality and how its water quality responds to changes in land use. SPARTA is used to delineate zones of similar reference concentrations of total phosphorus and suspended sediment throughout the upper Midwestern part of the United States. ?? 2006 Springer Science+Business Media, Inc.

Environmental Management↗
USGS2023

Genetic analysis of federally endangered Cape Sable seaside sparrow subpopulations in the Greater Everglades, USA

The federally endangered Cape Sable seaside sparrow ( Ammospiza maritima mirabilis ) is endemic to the Greater Everglades ecosystem in southern Florida, inhabiting fragmented marl prairies in six individual subpopulations. The subspecies is threatened by loss of breeding habitat from fire and water management. Genetic information is severely limited for the subspecies but could help inform decisions regarding subpopulation protections and potential translocations for genetic rescue. To provide genetic data and inform management efforts, feather samples were collected across five subpopulations (designated A–E) and protocols were tested to optimize DNA extraction yields. We assessed four mitochondrial DNA markers (N = 36–69) and 12 nuclear microsatellite loci (N = 55) in 108 sparrows. Mitochondrial DNA sequences revealed low haplotype diversity, with NADH dehydrogenase-2 haplotypes matching to most other extant subspecies and to the Atlantic coast subspecies. Nuclear diversity was low compared to other subspecies, but similar across subpopulations. Samples grouped as one population when analyzed by Principal Component Analysis, Bayesian modelling and genetic distance metrics. Limited genetic emigration was detected from one putative migrant. Relatedness was significantly different for sparrows in the most geographically distant subpopulation (A), likely reflecting high self-recruitment and natal site fidelity ( P = 0.003). The low to moderate effective population size (N E = 202.4; N E :N C = 0.06) and generation time estimates indicated that unique genetic variation could be lost quickly during stochastic events. The sample sizes were limited, which reduced the power to comprehensively address recent population size reductions and any subsequent loss of genetic diversity.

Florida↗
USGS2012

Population genetic structure of a widespread coniferous tree, Taxodium distichum [L.] Rich. (Cupressaceae), in the Mississippi River Alluvial Valley and Florida

Studies of genetic variation can elucidate the structure of present and past populations as well as the genetic basis of the phenotypic variability of species. Taxodium distichum is a coniferous tree dominant in lowland river flood plains and swamps of the southeastern USA which exhibits morphological variability and adaption to stressful habitats. This study provides a survey of the Mississippi River Alluvial Valley (MAV) and Florida to elucidate their population structure and the extent of genetic differentiation between the two regions and sympatric varieties, including bald cypress (var. distichum ) and pond cypress (var. imbricatum ). We determined the genotypes of 12 simple sequence repeat loci totaling 444 adult individuals from 18 natural populations. Bayesian clustering analysis revealed high levels of differentiation between the MAV and the Florida regions. Within the MAV region, there was a significant correlation between genetic and geographical distances. In addition, we found that there was almost no genetic differentiation between the varieties. Most genetic variation was found within individuals (76.73 %), 1.67 % among individuals within population, 15.36 % among populations within the regions, and 9.23 % between regions within the variety. Our results suggest that (1) the populations of the MAV and the Florida regions are divided into two major genetic groups, which might originate from different glacial refugia, and (2) the patterns of genetic differentiation and phenotypic differentiation were not parallel in this species.

Florida;Georgia;Louisiana;Mississippi;Alabama;Arka↗
USGS2014

Assessment of tsunami hazard to the U.S. Atlantic margin

Tsunami hazard is a very low-probability, but potentially high-risk natural hazard, posing unique challenges to scientists and policy makers trying to mitigate its impacts. These challenges are illustrated in this assessment of tsunami hazard to the U.S. Atlantic margin. Seismic activity along the U.S. Atlantic margin in general is low, and confirmed paleo-tsunami deposits have not yet been found, suggesting a very low rate of hazard. However, the devastating 1929 Grand Banks tsunami along the Atlantic margin of Canada shows that these events continue to occur. Densely populated areas, extensive industrial and port facilities, and the presence of ten nuclear power plants along the coast, make this region highly vulnerable to flooding by tsunamis and therefore even low-probability events need to be evaluated. We can presently draw several tentative conclusions regarding tsunami hazard to the U.S. Atlantic coast. Landslide tsunamis likely constitute the biggest tsunami hazard to the coast. Only a small number of landslides have so far been dated and they are generally older than 10,000 years. The geographical distribution of landslides along the margin is expected to be uneven and to depend on the distribution of seismic activity along the margin and on the geographical distribution of Pleistocene sediment. We do not see evidence that gas hydrate dissociation contributes to the generation of landslides along the U.S. Atlantic margin. Analysis of landslide statistics along the fluvial and glacial portions of the margin indicate that most of the landslides are translational, were probably initiated by seismic acceleration, and failed as aggregate slope failures. How tsunamis are generated from aggregate landslides remains however, unclear. Estimates of the recurrence interval of earthquakes along the continental slope may provide maximum estimates for the recurrence interval of landslide along the margin. Tsunamis caused by atmospheric disturbances and by coastal earthquakes may be more frequent than those generated by landslides, but their amplitudes are probably smaller. Among the possible far-field earthquake sources, only earthquakes located within the Gulf of Cadiz or west of the Tore-Madeira Rise are likely to affect the U.S. coast. It is questionable whether earthquakes on the Puerto Rico Trench are capable of producing a large enough tsunami that will affect the U.S. Atlantic coast. More information is needed to evaluate the seismic potential of the northern Cuba fold-and-thrust belt. The hazard from a volcano flank collapse in the Canary Islands is likely smaller than originally stated, and there is not enough information to evaluate the magnitude and frequency of flank collapse from the Azores Islands. Both deterministic and probabilistic methods to evaluate the tsunami hazard from the margin are available for application to the Atlantic margin, but their implementation requires more information than is currently available.

Marine Geology↗