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At least 1,117 records · Page 62Linked to original sources
USGS2007

Linking resources with demography to understand resource limitation for bears

1. Identifying the resources that limit growth of animal populations is essential for effective conservation; however, resource limitation is difficult to quantify. Recent advances in geographical information systems (GIS) and resource modelling can be combined with demographic modelling to yield insights into resource limitation. 2. Using long-term data on a population of black bears Ursus americanus, we evaluated competing hypotheses about whether availability of hard mast (acorns and nuts) or soft mast (fleshy fruits) limited bears in the southern Appalachians, USA, during 1981-2002. The effects of clearcutting on habitat quality were also evaluated. Annual survival, recruitment and population growth rate were estimated using capture-recapture data from 101 females. The availability of hard mast, soft mast and clearcuts was estimated with a GIS, as each changed through time as a result of harvest and succession, and then availabilities were incorporated as covariates for each demographic parameter. 3. The model with the additive availability of hard mast and soft mast across the landscape predicted survival and population growth rate. Availability of young clearcuts predicted recruitment, but not population growth or survival. 4. Availability of hard mast stands across the landscape and availability of soft mast across the landscape were more important than hard mast production and availability of soft mast in young clearcuts, respectively. 5. Synthesis and applications. Our results indicate that older stands, which support high levels of hard mast and moderate levels of soft mast, should be maintained to sustain population growth of bears in the southern Appalachians. Simultaneously, the acreage of intermediate aged stands (10-25 years), which support very low levels of both hard mast and soft mast, should be minimized. The approach used in this study has broad application for wildlife management and conservation. State and federal wildlife agencies often possess long-term data on both resource availability and capture-recapture for wild populations. Combined, these two data types can be used to estimate survival, recruitment, population growth, elasticities of vital rates and the effects of resource availability on demographic parameters. Hence data that are traditionally used to understand population trends can be used to evaluate how and why demography changes over time. ?? 2007 The Authors.

Journal of Applied Ecology↗
USGS2006

Understanding the genetic effects of recent habitat fragmentation in the context of evolutionary history: Phylogeography and landscape genetics of a southern California endemic Jerusalem cricket (Orthoptera: Stenopelmatidae: Stenopelmatus)

Habitat loss and fragmentation due to urbanization are the most pervasive threats to biodiversity in southern California. Loss of habitat and fragmentation can lower migration rates and genetic connectivity among remaining populations of native species, reducing genetic variability and increasing extinction risk. However, it may be difficult to separate the effects of recent anthropogenic fragmentation from the genetic signature of prehistoric fragmentation due to previous natural geological and climatic changes. To address these challenges, we examined the phylogenetic and population genetic structure of a flightless insect endemic to cismontane southern California, Stenopelmatus 'mahogani' (Orthoptera: Stenopelmatidae). Analyses of mitochondrial DNA sequence data suggest that diversification across southern California began during the Pleistocene, with most haplotypes currently restricted to a single population. Patterns of genetic divergence correlate with contemporary urbanization, even after correcting for (geographical information system) GIS-based reconstructions of fragmentation during the Pleistocene. Theoretical simulations confirm that contemporary patterns of genetic structure could be produced by recent urban fragmentation using biologically reasonable assumptions about model parameters. Diversity within populations was positively correlated with current fragment size, but not prehistoric fragment size, suggesting that the effects of increased drift following anthropogenic fragmentation are already being seen. Loss of genetic connectivity and diversity can hinder a population's ability to adapt to ecological perturbations commonly associated with urbanization, such as habitat degradation, climatic changes and introduced species. Consequently, our results underscore the importance of preserving and restoring landscape connectivity for long-term persistence of low vagility native species. Journal compilation ?? 2006 Blackwell Publishing Ltd.

Molecular Ecology↗
USGS2012

Advancing global marine biogeography research with open-source GIS software and cloud-computing

Across many scientific domains, the ability to aggregate disparate datasets enables more meaningful global analyses. Within marine biology, the Census of Marine Life served as the catalyst for such a global data aggregation effort. Under the Census framework, the Ocean Biogeographic Information System was established to coordinate an unprecedented aggregation of global marine biogeography data. The OBIS data system now contains 31.3 million observations, freely accessible through a geospatial portal. The challenges of storing, querying, disseminating, and mapping a global data collection of this complexity and magnitude are significant. In the face of declining performance and expanding feature requests, a redevelopment of the OBIS data system was undertaken. Following an Open Source philosophy, the OBIS technology stack was rebuilt using PostgreSQL, PostGIS, GeoServer and OpenLayers. This approach has markedly improved the performance and online user experience while maintaining a standards-compliant and interoperable framework. Due to the distributed nature of the project and increasing needs for storage, scalability and deployment flexibility, the entire hardware and software stack was built on a Cloud Computing environment. The flexibility of the platform, combined with the power of the application stack, enabled rapid re-development of the OBIS infrastructure, and ensured complete standards-compliance.

Transactions in GIS↗
USGS2005

Integrating habitat status, human population pressure, and protection status into biodiversity conservation priority setting

Priority setting is an essential component of biodiversity conservation. Existing methods to identify priority areas for conservation have focused almost entirely on biological factors. We suggest a new relative ranking method for identifying priority conservation areas that integrates both biological and social aspects. It is based on the following criteria: the habitat's status, human population pressure, human efforts to protect habitat, and number of endemic plant and vertebrate species. We used this method to rank 25 hotspots, 17 megadiverse countries, and the hotspots within each megadiverse country. We used consistent, comprehensive, georeferenced, and multiband data sets and analytical remote sensing and geographic information system tools to quantify habitat status, human population pressure, and protection status. The ranking suggests that the Philippines, Atlantic Forest, Mediterranean Basin, Caribbean Islands, Caucasus, and Indo-Burma are the hottest hotspots and that China, the Philippines, and India are the hottest megadiverse countries. The great variation in terms of habitat, protected areas, and population pressure among the hotspots, the megadiverse countries, and the hotspots within the same country suggests the need for hotspot- and country-specific conservation policies.

Conservation Biology↗
USGS2009

A spatial model to prioritize sagebrush landscapes in the intermountain west (U.S.A.) for restoration

The ecological integrity of Sagebrush (Artemisia spp.) ecosystems in the Intermountain West (U.S.A.) has been diminished by synergistic relationships among human activities, spread of invasive plants, and altered disturbance regimes. An aggressive effort to restore Sagebrush habitats is necessary if we are to stabilize or improve current habitat trajectories and reverse declining population trends of dependent wildlife. Existing economic resources, technical impediments, and logistic difficulties limit our efforts to a fraction of the extensive area undergoing fragmentation, degradation, and loss. We prioritized landscapes for restoring Sagebrush habitats within the intermountain western region of the United States using geographic information system (GIS) modeling techniques to identify areas meeting a set of conditions based on (1) optimum abiotic and biotic conditions favorable for revegetation of Sagebrush; (2) potential to increase connectivity of Sagebrush habitats in the landscape to benefit wildlife; (3) location of population strongholds for Greater Sage-Grouse (Centrocercus urophasianus, a species of conservation concern); and (4) potential impediments to successful restoration created by Cheatgrass (Bromus tectorum, an invasive exotic annual grass). Approximately 5.8 million ha in southwestern Idaho, northern Nevada, and eastern Oregon met our criteria for restoring Wyoming big sagebrush (Artemisia tridentata ssp. wyomingensis) and 5.1 million ha had high priority for restoring Mountain big sagebrush (A. tridentata ssp. vaseyana). Our results represent an integral component in a hierarchical framework after which site-specific locations for treatments can be focused within high-priority areas. Using this approach, long-term restoration strategies can be implemented that combine local-scale treatments and objectives with large-scale ecological processes and priorities. ?? 2008 Society for Ecological Restoration International.

Restoration Ecology↗
USGS2005

A map overlay error model based on boundary geometry

An error model for quantifying the magnitudes and variability of errors generated in the areas of polygons during spatial overlay of vector geographic information system layers is presented. Numerical simulation of polygon boundary displacements was used to propagate coordinate errors to spatial overlays. The model departs from most previous error models in that it incorporates spatial dependence of coordinate errors at the scale of the boundary segment. It can be readily adapted to match the scale of error-boundary interactions responsible for error generation on a given overlay. The area of error generated by overlay depends on the sinuosity of polygon boundaries, as well as the magnitude of the coordinate errors on the input layers. Asymmetry in boundary shape has relatively little effect on error generation. Overlay errors are affected by real differences in boundary positions on the input layers, as well as errors in the boundary positions. Real differences between input layers tend to compensate for much of the error generated by coordinate errors. Thus, the area of change measured on an overlay layer produced by the XOR overlay operation will be more accurate if the area of real change depicted on the overlay is large. The model presented here considers these interactions, making it especially useful for estimating errors studies of landscape change over time. ?? 2005 The Ohio State University.

Geographical Analysis↗
USGS2005

Calibration of the DRASTIC ground water vulnerability mapping method

Ground water vulnerability maps developed using the DRASTIC method have been produced in many parts of the world. Comparisons of those maps with actual ground water quality data have shown that the DRASTIC method is typically a poor predictor of ground water contamination. This study significantly improved the effectiveness of a modified DRASTIC ground water vulnerability map by calibrating the point rating schemes to actual ground water quality data by using nonparametric statistical techniques and a geographic information system. Calibration was performed by comparing data on nitrite plus nitrate as nitrogen (NO 2 + NO 3 -N) concentrations in ground water to land-use, soils, and depth to first-encountered ground water data. These comparisons showed clear statistical differences between NO 2 + NO 3 -N concentrations and the various categories. Ground water probability point ratings for NO 2 + NO 3 -N contamination were developed from the results of these comparisons, and a probability map was produced. This ground water probability map was then correlated with an independent set of NO 2 + NO 3 -N data to demonstrate its effectiveness in predicting elevated NO 2 + NO 3 -N concentrations in ground water. This correlation demonstrated that the probability map was effective, but a vulnerability map produced with the uncalibrated DRASTIC method in the same area and using the same data layers was not effective. Considerable time and expense have been outlaid to develop ground water vulnerability maps with the DRASTIC method. This study demonstrates a cost-effective method to improve and verify the effectiveness of ground water vulnerability maps.

Idaho, Wyoming↗
USGS2007

Latin hypercube approach to estimate uncertainty in ground water vulnerability

A methodology is proposed to quantify prediction uncertainty associated with ground water vulnerability models that were developed through an approach that coupled multivariate logistic regression with a geographic information system (GIS). This method uses Latin hypercube sampling (LHS) to illustrate the propagation of input error and estimate uncertainty associated with the logistic regression predictions of ground water vulnerability. Central to the proposed method is the assumption that prediction uncertainty in ground water vulnerability models is a function of input error propagation from uncertainty in the estimated logistic regression model coefficients (model error) and the values of explanatory variables represented in the GIS (data error). Input probability distributions that represent both model and data error sources of uncertainty were simultaneously sampled using a Latin hypercube approach with logistic regression calculations of probability of elevated nonpoint source contaminants in ground water. The resulting probability distribution represents the prediction intervals and associated uncertainty of the ground water vulnerability predictions. The method is illustrated through a ground water vulnerability assessment of the High Plains regional aquifer. Results of the LHS simulations reveal significant prediction uncertainties that vary spatially across the regional aquifer. Additionally, the proposed method enables a spatial deconstruction of the prediction uncertainty that can lead to improved prediction of ground water vulnerability. ?? 2007 National Ground Water Association.

Ground Water↗
USGS2007

Fast algorithm for automatically computing Strahler stream order

An efficient algorithm was developed to determine Strahler stream order for segments of stream networks represented in a Geographic Information System (GIS). The algorithm correctly assigns Strahler stream order in topologically complex situations such as braided streams and multiple drainage outlets. Execution time varies nearly linearly with the number of stream segments in the network. This technique is expected to be particularly useful for studying the topology of dense stream networks derived from digital elevation model data.

Water Resources Bulletin↗
USGS2007

Multivariate classification of small order watersheds in the Quabbin Reservoir Basin, Massachusetts

ABSTRACT: A multivariate approach was used to analyze hydrologic, geologic, geographic, and water-chemistry data from small order watersheds in the Quabbin Reservoir Basin in central Massachusetts. Eighty three small order watersheds were delineated and landscape attributes defining hydrologic, geologic, and geographic features of the watersheds were compiled from geographic information system data layers. Principal components analysis was used to evaluate 11 chemical constituents collected bi-weekly for 1 year at 15 surface-water stations in order to subdivide the basin into subbasins comprised of watersheds with similar water quality characteristics. Three principal components accounted for about 90 percent of the variance in water chemistry data. The principal components were defined as a biogeochemical variable related to wet. land density, an acid-neutralization variable, and a road-salt variable related to density of primary roads. Three subbasins were identified. Analysis of variance and multiple comparisons of means were used to identify significant differences in stream water chemistry and landscape attributes among subbasins. All stream water constituents were significantly different among subbasins. Multiple regression techniques were used to relate stream water chemistry to landscape attributes. Important differences in landscape attributes were related to wetlands, slope, and soil type.

Journal of the American Water Resources Associatio↗
USGS2007

Nutrients discharged to the Mississippi River from eastern Iowa watersheds, 1996-1997

The introduction of nutrients from chemical fertilizer, animal manure, wastewater, and atmospheric deposition to the eastern Iowa environment creates a large potential for nutrient transport in watersheds. Agriculture constitutes 93 percent of all land use in eastern Iowa. As part of the U.S. Geological Survey National Water Quality Assessment Program, water samples were collected (typically monthly) from six small and six large watersheds in eastern Iowa between March 1996 and September 1997. A Geographic Information System (GIS) was used to determine land use and quantify inputs of nitrogen and phosphorus within the study area. Streamliow from the watersheds is to the Mississippi River. Chemical fertilizer and animal manure account for 92 percent of the estimated total nitrogen and 99.9 percent of the estimated total phosphorus input in the study area. Total nitrogen and total phosphorus loads for 1996 were estimated for nine of the 12 rivers and creeks using a minimum variance unbiased estimator model. A seasonal pattern of concentrations and loads was observed. The greatest concentrations and loads occur in the late spring to early summer in conjunction with row-crop fertilizer applications and spring nmoff and again in the late fall to early winter as vegetation goes into dormancy and additional fertilizer is applied to row-crop fields. The three largest rivers in eastern Iowa transported an estimated total of 79,000 metric tons of total nitrogen and 6,800 metric tons of total phosphorus to the Mississippi River in 1996. The estimated mass of total nitrogen and total phosphorus transported to the Mississippi River represents about 19 percent of all estimated nitrogen and 9 percent of all estimated phosphorus input to the study area.

Iowa↗
USGS2008

A fully distributed implementation of mean annual streamflow regional regression equations

Estimates of mean annual streamflow are needed for a variety of hydrologic assessments. Away from gage locations, regional regression equations that are a function of upstream area, precipitation, and temperature are commonly used. Geographic information systems technology has facilitated their use for projects, but traditional approaches using the polygon overlay operator have been too inefficient for national scale applications. As an alternative, the Elevation Derivatives for National Applications (EDNA) database was used as a framework for a fully distributed implementation of mean annual streamflow regional regression equations. The raster “flow accumulation” operator was used to efficiently achieve spatially continuous parameterization of the equations for every 30 m grid cell of the conterminous United States (U.S.). Results were confirmed by comparing with measured flows at stations of the Hydro-Climatic Data Network, and their applications value demonstrated in the development of a national geospatial hydropower assessment. Interactive tools at the EDNA website make possible the fast and efficient query of mean annual streamflow for any location in the conterminous U.S., providing a valuable complement to other national initiatives (StreamStats and the National Hydrography Dataset Plus).

Journal of the American Water Resources Associatio↗
USGS2009

Mapping Hurricane Rita inland storm tide

Flood‐inundation data are most useful for decision makers when presented in the context of maps of affected communities and (or) areas. But because the data are scarce and rarely cover the full extent of the flooding, interpolation and extrapolation of the information are needed. Many geographic information systems provide various interpolation tools, but these tools often ignore the effects of the topographic and hydraulic features that influence flooding. A barrier mapping method was developed to improve maps of storm tide produced by Hurricane Rita. Maps were developed for the maximum storm tide and at 3‐h intervals from midnight (00:00 hours) through noon (12:00 hours) on 24 September 2005. The improved maps depict storm‐tide elevations and the extent of flooding. The extent of storm‐tide inundation from the improved maximum storm‐tide map was compared with the extent of flood inundation from a map prepared by the Federal Emergency Management Agency (FEMA). The boundaries from these two maps generally compared quite well especially along the Calcasieu River. Also a cross‐section profile that parallels the Louisiana coast was developed from the maximum storm‐tide map and included FEMA high‐water marks.

Louisiana↗
USGS2010

Flood hazard awareness and hydrologic modelling at Ambos Nogales, United States–Mexico border

Appropriate land‐use, watershed‐management, and flood‐attenuation plans are critical in the cross‐border urban environment known collectively as Ambos Nogales. This paper summarizes methodologies for predicting the watershed response associated with land‐use change within a spatial and temporal context through the use of a hydrological model in a cross‐border setting. The KINEROS2 model is implemented via the Automated Geospatial Watershed Assessment 2.0 geographic information system interface to evaluate the watershed of Nogales, Arizona, and Nogales, Sonora, Mexico, to assess flood vulnerability by quantifying volumes of runoff and peak flow, based on alternative land‐use scenarios. Cross‐border geospatial data acquisition and input to models are described. Discussions about the KINEROS2 model results identify flood‐prone areas, simulate the impact of land‐use change, and evaluate the impact of potential flood‐control interventions in the Ambos Nogales watershed. Products from this research are being used in a comprehensive plan for sustainable development in Ambos Nogales.

Ambos Nogales watershed↗
USGS2013

Mitigating the effects of landscape development on streams in urbanizing watersheds

This collaborative study examined urbanization and impacts on area streams while using the best available sediment and erosion control (S&EC) practices in developing watersheds in Maryland, United States. During conversion of the agricultural and forested watersheds to urban land use, land surface topography was graded and vegetation was removed creating a high potential for sediment generation and release during storm events. The currently best available S&EC facilities were used during the development process to mitigate storm runoff water quality, quantity, and timing before entering area streams. Detailed Geographic Information System (GIS) maps were created to visualize changing land use and S&EC practices, five temporal collections of LiDAR (light detection and ranging) imagery were used to map the changing landscape topography, and streamflow, physical geomorphology, and habitat data were used to assess the ability of the S&EC facilities to protect receiving streams during development. Despite the use of the best available S&EC facilities, receiving streams experienced altered flow, geomorphology, and decreased biotic community health. These impacts on small streams during watershed development affect sediment and nutrient loads to larger downstream aquatic ecosystems such as the Chesapeake Bay.

Maryl↗
USGS1987

Cumulative impacts of oil fields on northern Alaskan landscapes

Proposed further developments on Alaska's Arctic Coastal Plain raise questions about cumulative effects on arctic tundra ecosystems of development of multiple large oil fields. Maps of historical changes to the Prudhoe Bay Oil Field show indirect impacts can lag behind planned developments by many years and the total area eventually disturbed can greatly exceed the planned area of construction. For example, in the wettest parts of the oil field (flat thaw-lake plains), flooding and thermokarst covered more than twice the area directly affected by roads and other construction activities. Protecting critical wildlife habitat is the central issue for cumulative impact analysis in northern Alaska. Comprehensive landscape planning with the use of geographic information system technology and detailed geobotanical maps can help identify and protect areas of high wildlife use.

Alaska↗
USGS1998

Objective delineation of lahar-inundation hazard zones

A new method of delineating lahar hazard zones in valleys that head on volcano flanks provides a rapid, objective, reproducible alternative to traditional methods. The rationale for the method derives from scaling analyses of generic lahar paths and statistical analyses of 27 lahar paths documented at nine volcanoes. Together these analyses yield semiempirical equations that predict inundated valley cross-sectional areas (A) and planimetric areas (B) as functions of lahar volume (V) . The predictive equations ( A = 0.05 V 2/3 and B = 200 V 2/3 ) provide all information necessary to calculate and plot inundation limits on topographic maps. By using a range of prospective lahar volumes to evaluate A and B , a range of inundation limits can be plotted for lahars of increasing volume and decreasing probability. Resulting hazard maps show graphically that lahar-inundation potentials are highest near volcanoes and along valley thalwegs, and diminish gradually as distances from volcanoes and elevations above valley floors increase. We automate hazard-zone delineation by embedding the predictive equations in a geographic information system (GIS) computer program that uses digital elevation models of topography. Lahar hazard zones computed for Mount Rainier, Washington, mimic those constructed on the basis of intensive field investigations. The computed hazard zones illustrate the potentially widespread impact of large lahars, which on average inundate planimetric areas 20 times larger than those inundated by rock avalanches of comparable volume.

Washington↗
USGS2008

Shallow landslide hazard map of Seattle, Washington

Landslides, particularly debris flows, have long been a significant cause of damage and destruction to people and property in the Puget Sound region. Following the years of 1996 and 1997, the Federal Emergency Management Agency designated Seattle as a “Project Impact” city with the goal of encouraging the city to become more disaster resistant to landslides and other natural hazards. A major recommendation of the Project Impact council was that the city and the U.S. Geological Survey collaborate to produce a landslide hazard map. An exceptional data set archived by the city containing more than 100 yr of landslide data from severe storm events allowed comparison of actual landslide locations with those predicted by slope-stability modeling. We used an infinite-slope analysis, which models slope segments as rigid friction blocks, to estimate the susceptibility of slopes to debris flows, which are water-laden slurries that can form from shallow failures of soil and weathered bedrock and can travel at high velocities down steep slopes. Data used for the analysis consisted of a digital slope map derived from recent light detection and ranging (LiDAR) imagery of Seattle, recent digital geologic mapping of the city, and shear-strength test data for the geologic units found in the surrounding area. The combination of these data layers within a geographic information system (GIS) platform allowed us to create a shallow landslide hazard map for Seattle.

Washington↗