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At least 469 records · Page 26Linked to original sources

USGS2017

How well do route survey areas represent landscapes at larger spatial extents? An analysis of land cover composition along Breeding Bird Survey routes

The occurrence of birds in a survey unit is partly determined by the habitat present. Moreover, some bird species preferentially avoid some land cover types and are attracted to others. As such, land cover composition within the 400 m survey areas along a Breeding Bird Survey (BBS) route clearly influences the species available to be detected. Ideally, to extend survey results to the larger landscape, land cover composition within the survey area should be similar to that at larger spatial extents defining the landscape. Such representativeness helps minimize possible roadside effects (bias), here defined as differences in bird species composition and abundance along a roadside as compared to a larger surrounding landscape. We used land cover data from the 2011 National Land Cover Database to examine representativeness of land cover composition along routes. Using ArcGIS, the percentages of each of 15 land cover types within 400 m buffers along 2,696 U.S. BBS routes were calculated and compared to percentages in 2 km, 5 km, and 10 km buffers surrounding each route. This assessment revealed that aquatic cover types and highly urbanized land tend to be slightly underrepresented in the survey areas. Two anthropogenic cover types (pasture/hay and cropland) may be slightly overrepresented in the survey areas. Over all cover types, 92% of the 2,696 routes exhibited “good” representativeness, with <5 percentage points per cover type difference in proportional cover between the 400 m and 10 km buffers. This assessment further supports previous research indicating that any land-cover-based roadside bias in the bird data of the BBS is likely minimal.

Condor↗

USGS2005

Correlates of vernal pool occurrence in the Massachusetts USA, landscape

Vernal pool wetlands are at risk of destruction across the northeast United States, due in part to their diminutive size and short hydroperiolds. These characteristics make it difficult to locate vernal pool habitats in the landscape during much of the year, and no efficient method exists for predicting their occurrence. A logistic regression procedure was used to identify large-scale variables that influence the presence of a potential vernal pool, including surficial geology, land use and land cover, soil classification, topography, precipitation, and surficial hydrologic features. The model was validated with locations of field-verified vernal pools. The model demonstrated that the probability of potential vernal pool occurrence is positively related to slope, negatively related to till/bedrock surficial geology, and negatively related to the proportion of cropland, urban/commercial, and high density residential development in the landscape. The relationship between vernal pool occurrence and large-scale variables suggests that these habitats do not occur at random in the landscape, and thus, protection in situ should be considered.

Massachusetts↗

USGS2015

Daily nest survival rates of Gunnison Sage-Grouse ( Centrocercus minimus ): assessing local- and landscape-scale drivers

The Gunnison Sage-Grouse ( Centrocercus minimus ) is a species of conservation concern and is a candidate for listing under the U.S. Endangered Species Act because of substantial declines in populations from historic levels. It is thought that loss, fragmentation, and deterioration of sagebrush ( Artemisia spp.) habitat have contributed to the decline and isolation of this species into seven geographically distinct subpopulations. Nest survival is known to be a primary driver of demography of Greater Sage-Grouse ( C. urophasianus ), but no unbiased estimates of daily nest survival rates (hereafter nest survival) exist for Gunnison Sage-Grouse or published studies identifying factors that influence nest survival. We estimated nest survival of Gunnison Sage-Grouse for the western portion of Colorado's Gunnison Basin subpopulation, and assessed the effects and relative importance of local- and landscape-scale habitat characteristics on nest survival. Our top performing model was one that allowed variation in nest survival among areas, suggesting a larger landscape-area effect. Overall nest success during a 38-day nesting period (egg-laying plus incubation) was 50% (daily survival rate; SE = 0.982 [0.003]), which is higher than previous estimates for Gunnison Sage-Grouse and generally higher than published for the closely related Greater Sage-Grouse. We did not find strong evidence that local-scale habitat variables were better predictors of nest survival than landscape-scale predictors, nor did we find strong evidence that any of the habitat variables we measured were good predictors of nest survival. Nest success of Gunnison Sage-Grouse in the western portion of the Gunnison Basin was higher than previously believed.

Wilson Journal of Ornithology↗

USGS2005

Multivariate analysis of scale-dependent associations between bats and landscape structure

The assessment of biotic responses to habitat disturbance and fragmentation generally has been limited to analyses at a single spatial scale. Furthermore, methods to compare responses between scales have lacked the ability to discriminate among patterns related to the identity, strength, or direction of associations of biotic variables with landscape attributes. We present an examination of the relationship of population- and community-level characteristics of phyllostomid bats with habitat features that were measured at multiple spatial scales in Atlantic rain forest of eastern Paraguay. We used a matrix of partial correlations between each biotic response variable (i.e., species abundance, species richness, and evenness) and a suite of landscape characteristics to represent the multifaceted associations of bats with spatial structure. Correlation matrices can correspond based on either the strength (i.e., magnitude) or direction (i.e., sign) of association. Therefore, a simulation model independently evaluated correspondence in the magnitude and sign of correlations among scales, and results were combined via a meta-analysis to provide an overall test of significance. Our approach detected both species-specific differences in response to landscape structure and scale dependence in those responses. This matrix–simulation approach has broad applicability to ecological situations in which multiple intercorrelated factors contribute to patterns in space or time.

Ecological Applications↗

USGS2007

Forest dynamics in Oregon landscapes: Evaluation and application of an individual-based model

The FORCLIM model of forest dynamics was tested against field survey data for its ability to simulate basal area and composition of old forests across broad climatic gradients in western Oregon, USA. The model was also tested for its ability to capture successional trends in ecoregions of the west Cascade Range. It was then applied to simulate present and future (1990-2050) forest landscape dynamics of a watershed in the west Cascades. Various regimes of climate change and harvesting in the watershed were considered in the landscape application. The model was able to capture much of the variation in forest basal area and composition in western Oregon even though temperature and precipitation were the only inputs that were varied among simulated sites. The measured decline in total basal area from tall coastal forests eastward to interior steppe was matched by simulations. Changes in simulated forest dominants also approximated those in the actual data. Simulated abundances of a few minor species did not match actual abundances, however. Subsequent projections of climate change and harvest effects in a west Cascades landscape indicated no change in forest dominance as of 2050. Yet, climate-driven shifts in the distributions of some species were projected. The simulation of both stand-replacing and partial-stand disturbances across western Oregon improved agreement between simulated and actual data. Simulations with fire as an agent of partial disturbance suggested that frequent fires of low severity can alter forest composition and structure as much or more than severe fires at historic frequencies. ?? 2007 by the Ecological Society of America.

Ecological Applications↗

USGS2009

Scaling the effects of moose browsing on forage distribution, from the geometry of plant canopies to landscapes

Landscape heterogeneity influences large herbivores by altering their feeding rates, but as herbivores attempt to maximize feeding rates they also create spatial heterogeneity by altering plant growth. Herbivore feeding rates thus provide a quantitative link between the causes and consequences of spatial heterogeneity in herbivore-dominated ecosystems. The fractal geometry of plant canopies determines both the density and mass of twigs available to foraging herbivores. These properties determine a threshold distance between plants (d * ) that distinguishes the mechanisms regulating herbivore intake rates. When d * is greater than the actual distance between plants (d), intake is regulated by the rate of food processing in the mouth. But when d * < d, intake is regulated by the rate at which the herbivore encounters new plants. Alterations to plant geometry due to past browsing could change the rate at which herbivores encounter and process bites of plant tissue, modify d * relative to d, and thus change intake rates and the distribution of mechanisms regulating it across landscapes. We measured changes in the geometry of aspen (Populus tremuloides) and balsam fir (Abies balsamea) saplings along gradients of moose browsing from 2001 to 2005 at Isle Royale National Park, Michigan, USA. For aspen saplings, fractal dimension of bite density, bite mass, and forage biomass responded quadratically to increasing moose browsing and were greatest at -3-4 g-g.m-2.yr" 1 consumption. For balsam fir, in contrast, these same measures declined steadily with increasing moose browsing. The different responses of plant canopies to increased browsing altered d * around plants. In summer, d * > d for aspen saplings at all prior consumption levels. Food processing therefore regulated summer moose feeding rates across our landscapes. In winter, changes in bite mass due to past browsing were sufficient to cause d * < d for aspen and balsam fir. Therefore, travel velocity and food processing jointly regulated intake rate during winter. Browsing-induced changes in the small-scale geometry of plant canopies can determine intake rate at larger spatial scales by changing d * relative to d and, hence, which mechanisms determine intake rate, essentially altering how herbivores sense the distribution of their food resources. ?? 2009 by the Ecological Society of America.

Ecological Monographs↗

USGS2009

Response of the everglades ridge and slough landscape to climate variability and 20th-century water management

The ridge and slough landscape of the Florida Everglades consists of a mosaic of linear sawgrass ridges separated by deeper-water sloughs with tree islands interspersed throughout the landscape. We used pollen assemblages from transects of sediment cores spanning sawgrass ridges, sloughs, and ridge-slough transition zones to determine the timing of ridge and slough formation and to evaluate the response of components of the ridge and slough landscape to climate variability and 20th-century water management. These pollen data indicate that sawgrass ridges and sloughs have been vegetationally distinct from one another since initiation of the Everglades wetland in mid-Holocene time. Although the position and community composition of sloughs have remained relatively stable throughout their history, modern sawgrass ridges formed on sites that originally were occupied by marshes. Ridge formation and maturation were initiated during intervals of drier climate (the Medieval Warm Period and the Little Ice Age) when the mean position of the Intertropical Convergence Zone shifted southward. During these drier intervals, marsh taxa were more common in sloughs, but they quickly receded when precipitation increased. Comparison with regional climate records suggests that slough vegetation is strongly influenced by North Atlantic Oscillation variability, even under 20th-century water management practices. ?? 2009 by the Ecological Society of America.

Ecological Applications↗

USGS2002

Preliminary comparison of landscape pattern-normalized difference vegetation index (NDVI) relationships to central plains stream conditions

We explored relationships of water quality parameters with landscape pattern metrics (LPMs), land use–land cover (LULC) proportions, and the advanced very high resolution radiometer (AVHRR) normalized difference vegetation index (NDVI) or NDVI-derived metrics. Stream sites (271) in Nebraska, Kansas, and Missouri were sampled for water quality parameters, the index of biotic integrity, and a habitat index in either 1994 or 1995. Although a combination of LPMs (interspersion and juxtaposition index, patch density, and percent forest) within Ozark Highlands watersheds explained >60% of the variation in levels of nitrite–nitrate nitrogen and conductivity, in most cases the LPMs were not significantly correlated with the stream data. Several problems using landscape pattern metrics were noted: small watersheds having only one or two patches, collinearity with LULC data, and counterintuitive or inconsistent results that resulted from basic differences in land use–land cover patterns among ecoregions or from other factors determining water quality. The amount of variation explained in water quality parameters using multiple regression models that combined LULC and LPMs was generally lower than that from NDVI or vegetation phenology metrics derived from time-series NDVI data. A comparison of LPMs and NDVI indicated that NDVI had greater promise for monitoring landscapes for stream conditions within the study area.

Kansas, Missouri, Nebraska↗

USGS1981

Evaluation of Landsat Multispectral Scanner data for mapping vegetated soil landscapes

Landsat multispectral scanner data for Brazos County, Texas, were evaluated in terms of effectiveness for classifying soils on vegetated landscapes at three times during the year: a time of normally adequate soil water, a time of expected soil water deficit, and a time when soil water is normally being replenished. Six test sites were used to evaluate LARSYS supervised and unsupervised classification of vegetated soil landscapes. Open grassland soils were best separated in the fall during a period when soil moisture was being replenished after the summer period of soil water deficit. Woodland soils were separated by Landsat data in late spring when adequate moisture was available. However, a high degree of accuracy was not achieved using Landsat for separating soil map units. Accurate separation of soil mapping units on vegetated landscapes was not possible during late summer when soil water was deficient. Selected soil properties important to plant growth were separable on the test sites using June and October Landsat data. Particle size and soil moisture regime were separated at both dates. Soils with argillic horizons were separated from soils without argillic horizons.

Texas↗

USGS2024

Examining inter-regional and intra-seasonal differences in wintering waterfowl landscape associations among Pacific and Atlantic flyways

The Central Valley of California (CVC) and Mid-Atlantic (MA) in the U.S. are both critical sites for nationwide food security (California Poultry Federation 2016, Prosser et al. 2017), and many waterfowl species annually, especially during the winter, providing feeding and roosting locations for a variety of species. Mapping waterfowl distributions, using NEXRAD, may aid in the adaptive management of important waterfowl habitat and allow various government agencies to better understand the interface between wild and domestic birds and commercial agricultural practices. We used 9 years (2014–2023) of data from the US NEXRAD network to model winter waterfowl relative abundance in the CVC and MA as a function of weather, temporal period, environmental conditions, and landcover characteristics using Boosted Regression Tree modelling. We were able to quantify the variability in effect size of 28 different covariates across space and time within two geographic regions which are critical to nationwide waterfowl management and host a high density of nationally important commercial agriculture. In general, weather, geographic (distance to features), and landcover condition (wetness index) predictors had the strongest relative effect on predicting wintering waterfowl relative abundance in both regions, while effects of land cover composition were more regionally and temporally specific. Increased daily mean temperature was a major predictor of increasing relative waterfowl abundance in both regions throughout the winter. Increasing precipitation had differing effects within regions, increasing relative waterfowl abundance in the MA, while decreasing in general within the CVC. Increasing relative waterfowl abundance in the CVC are strongly tied to the flooding of the landscape and rice availability, whereas waterfowl in the MA, where water is less limiting, are generally governed by waste grain availability and emergent wetland on the landscape. Waterfowl relative abundance in the MA was generally higher nearer to the Atlantic coast and lakes, while in the CVC they were higher nearer to lakes. Our findings promote a better understanding of spatial associations of waterfowl to landscape features and may aid in conservation and biosecurity management protocols.

Authorea↗

USGS2000

Factors limiting mallard brood survival in prairie pothole landscapes

In order to estimate mallard (Anas platyrhynchos) production from managed and unmanaged lands, waterfowl biologists need measurable predictors of brood survival. We evaluated effects of percent of seasonal basins holding water (WETSEAS), percent of upland landscape in perennial cover (PERNCOVER), rainfall (RAIN), daily minimum ambient temperature (TMIN), hatch date (HATCHDATE), brood age (BA; 0-7 or 8-30 days), age of brood females, and brood size on mallard brood survival in prairie pothole landscapes, and developed a predictive model using factors found to have significant effects. Sixteen of 56 radiomarked broods experienced total loss during 1,250 exposure days. Our final fitted model of brood survival contained only main effects of WETSEAS, HATCHDATE, and RAIN. Total brood loss during the first 30 days of exposure was 11.2 times more likely for broods hatched on areas with <17% WETSEAS than those on areas with >59% WETSEAS. Total brood loss was 5.2 times more likely during rainy conditions than during dry periods, and the hazard of total brood loss increased by 5% for each 1-day delay in hatching between 17 May and 12 August. High survival of mallard broods in landscapes where most seasonal basins contain water underscores the importance of maintaining seasonal wetlands as a major component of wetland complexes managed for mallard production. Because early hatched broods have higher survival, we also suggest that waterfowl managers focus their efforts on enhancing nest success of early laid clutches, especially in wet years.

Journal of Wildlife Management↗

USGS2016

Wyoming Landscape Conservation Initiative—A case study in partnership development

The Wyoming Landscape Conservation Initiative (WLCI) is a successful example of collaboration between science and natural resource management at the landscape scale. In southwestern Wyoming, expanding energy and mineral development, urban growth, and other changes in land use over recent decades, combined with landscape-scale drivers such as climate change and invasive species, have presented compelling challenges to resource managers and a diverse group of Federal, State, industry, and non-governmental organizations, as well as citizen stakeholders. To address these challenges, the WLCI was established as a collaborative forum and interagency partnership to develop and implement science-based conservation actions. About a decade after being established, this report documents the establishment and history of the WLCI, focusing on the path to success of the initiative and providing insights and details that may be useful in developing similar partnerships in other locations. Not merely retrospective, the elements of the WLCI that are presented herein are still in play, still evolving, and still contributing to the resolution of compelling conservation challenges in the Western United States. The U.S. Geological Survey has developed many successful longstanding partnerships, of which the WLCI is one example. “As the Nation’s largest water, earth, and biological science and civilian mapping agency, the U.S. Geological Survey collects, monitors, analyzes, and provides scientific understanding about natural resource conditions, issues, and problems. The diversity of our scientific expertise enables us to carry out large-scale, multi-disciplinary investigations and provide impartial scientific information to resource managers, planners, and other customers” (U.S. Geological Survey, 2016).

Wyoming↗

USGS2012

Data resources for the Wyoming Landscape Conservation Initiative (WLCI) Integrated Assessment (IA)

The data contained in this report were compiled, modified, and analyzed for the Wyoming Landscape Conservation Initiative (WLCI) Integrated Assessment (IA). The WLCI is a long-term science based effort to assess and enhance aquatic and terrestrial habitats at a landscape scale in southwest Wyoming while facilitating responsible energy development through local collaboration and partnerships. The IA is an integrated synthesis and analysis of WLCI resource values based on best available data and information collected from multiple agencies and organizations. It is a support tool for landscape-scale conservation planning and evaluation, and a data and analysis resource that can be used for addressing specific management questions. The IA analysis was conducted using a Geographic Information System in a raster (that is, a grid) environment using a cell size of 30 meters. To facilitate the interpretation of the data in a regional context, mean values were summarized and displayed at the subwatershed unit (WLCI subwatersheds were subset from the National Hydrography Dataset, Hydrologic Unit Code 12/Level 6). A dynamic mapping platform, accessed via the WLCI webpage at http://www.wlci.gov is used to display the mapped information, and to access underlying resource values that were combined to produce the final mapped results. The raster data used in the IA are provided here for use by interested parties to conduct additional analyses and can be accessed via the WLCI webpage. This series contains 74 spatial data sets: WLCI subwatersheds (vector) and 73 geotiffs (raster) that are segregated into the major categories of Multicriteria Index (including Resource Index and Condition), Change Agents, and Future Change. The Total Multicriteria Index is composed of the Aquatic Multicriteria Index and the Terrestrial Multicriteria Index. The Aquatic Multicriteria Index is composed of the Aquatic Resource Index and the Aquatic Condition. The Aquatic Resource Index is composed of the following components: Groundwater, Special Management Areas, and Priority Areas. The Aquatic Condition is composed of the following components: Focal Species, Species of Concern, Focal Ecosystems, and Proper Functioning Condition. The Terrestrial Multicriteria Index is composed of the Terrestrial Resource Index and the Terrestrial Condition. The Terrestrial Resource Index is composed of the following components: Special Management Areas, Agriculture, and Priority Areas. The Terrestrial Condition is composed of the following components: Focal Species, Big Game, Species of Concern, Rare Plants, and Focal Ecosystems. The Change Agents are composed the following components: Roads, Energy, Mines, and Urban. The Future Change is composed of the following components: Oil-Gas-Coal, Wind, Minerals, Climate-Temperature, Invasive Species, and Urban.

Wyoming↗

USGS2007

Land Cover Applications, Landscape Dynamics, and Global Change

The Land Cover Applications, Landscape Dynamics, and Global Change project at U.S. Geological Survey (USGS) Center for Earth Resources Observation and Science (EROS) seeks to integrate remote sensing and simulation models to better understand and seek solutions to national and global issues. Modeling processes related to population impacts, natural resource management, climate change, invasive species, land use changes, energy development, and climate mitigation all pose significant scientific opportunities. The project activities use remotely sensed data to support spatial monitoring, provide sensitivity analyses across landscapes and large regions, and make the data and results available on the Internet with data access and distribution, decision support systems, and on-line modeling. Applications support sustainable natural resource use, carbon cycle science, biodiversity conservation, climate change mitigation, and robust simulation modeling approaches that evaluate ecosystem and landscape dynamics.

Fact Sheet↗

USGS2008

A Landscape Indicator Approach to the Identification and Articulation of the Ecological Consequences of Land Cover Change in the Chesapeake Bay Watershed, 1970-2000

The advancement of geographic science in the area of land surface status and trends and land cover change is at the core of the current geographic scientific research of the U.S. Geological Survey (USGS) (McMahon and others, 2005). Perhaps the least developed or articulated aspects of USGS land change science have been the identification and analysis of the ecological consequences of land cover change. Changes in land use and land cover significantly affect the ability of ecosystems to provide essential ecological goods and services, which, in turn, affect the economic, public health, and social benefits that these ecosystems provide. One of the great scientific challenges for geographic science is to understand and calibrate the effects of land use and land cover change and the complex interaction between human and biotic systems at a variety of natural, geographic, and political scales. Understanding the dynamics of land surface change requires an increased understanding of the complex nature of human-environmental systems and will require a suite of scientific tools that include traditional geographic data and analysis methods, such as remote sensing and geographic information systems (GIS), as well as innovative approaches to understanding the dynamics of complex systems. One such approach that has gained much recent scientific attention is the landscape indicator, or landscape assessment, approach, which has been developed with the emergence of the science of landscape ecology.

Fact Sheet↗

USGS2018

Landscapes from the waves—Marine terraces of California

Many coastlines around the world have stair-step landforms, known as marine terraces. Marine terraces make up a large part of coastal California’s landscape—from San Diego to Crescent City. Find out how these landscapes form, why marine terraces are of interest to scientists, and where you can explore these landscapes.

California↗

USGS2011

Joint Ecosystem Modeling (JEM) ecological model documentation volume 2: roseate spoonbill ( Platalea ajaja ) landscape habitat suitability index v1.0.0

Ecological conditions in the Greater Everglades have changed due to human activities, including the construction of canals to divert water away from the core of the landscape. Current and planned restoration projects are designed to produce a natural sheetflow of water across the landscape. This restoration of water flow should provide an increase in freshwater needed to restore natural salinities to the fringing estuarine ecosystem. In this report, we describe a Landscape Habitat Suitability Index model designed to evaluate alternative restoration plans for the benefit of a key species, the roseate spoonbill (Platalea ajaja). Model output has shown to be a good indicator of areas capable of supporting spoonbills. Use of this model will allow examination of the potential response of this key species to water management proposed through the Greater Everglades restoration process.

Florida↗

USGS2012

Hydrologic and landscape database for the Cache and White River National Wildlife Refuges and contributing watersheds in Arkansas, Missouri, and Oklahoma

A hydrologic and landscape database was developed by the U.S. Geological Survey, in cooperation with the U.S. Fish and Wildlife Service, for the Cache River and White River National Wildlife Refuges and their contributing watersheds in Arkansas, Missouri, and Oklahoma. The database is composed of a set of ASCII files, Microsoft Access® files, Microsoft Excel® files, an Environmental Systems Research Institute (ESRI) ArcGIS® geodatabase, ESRI ArcGRID® raster datasets, and an ESRI ArcReader® published map. The database was developed as an assessment and evaluation tool to use in examining refuge-specific hydrologic patterns and trends as related to water availability for refuge ecosystems, habitats, and target species; and includes hydrologic time-series data, statistics, and hydroecological metrics that can be used to assess refuge hydrologic conditions and the availability of aquatic and riparian habitat. Landscape data that describe the refuge physiographic setting and the locations of hydrologic-data collection stations are also included in the database. Categories of landscape data include land cover, soil hydrologic characteristics, physiographic features, geographic and hydrographic boundaries, hydrographic features, regional runoff estimates, and gaging-station locations. The database geographic extent covers three hydrologic subregions—the Lower Mississippi–St Francis (0802), the Upper White (1101), and the Lower Arkansas (1111)—within which human activities, climatic variation, and hydrologic processes can potentially affect the hydrologic regime of the refuges and adjacent areas. Database construction has been automated to facilitate periodic updates with new data. The database report (1) serves as a user guide for the database, (2) describes the data-collection, data-reduction, and data-analysis methods used to construct the database, (3) provides a statistical and graphical description of the database, and (4) provides detailed information on the development of analytical techniques designed to assess water availability for ecological needs.

Arkansas;Missouri;Oklahoma↗