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At least 955 records · Page 53Linked to original sources
USGS2019

Where’s the rock: Using convolutional neural networks to improve land cover classification

While machine learning techniques have been increasingly applied to land cover classification problems, these techniques have not focused on separating exposed bare rock from soil covered areas. Therefore, we built a convolutional neural network (CNN) to differentiate exposed bare rock ( rock ) from soil cover ( other ). We made a training dataset by mapping exposed rock at eight test sites across the Sierra Nevada Mountains (California, USA) using USDA’s 0.6 m National Aerial Inventory Program (NAIP) orthoimagery. These areas were then used to train and test the CNN. The resulting machine learning approach classifies bare rock in NAIP orthoimagery with a 0.95 F 1 "> F 1 score. Comparatively, the classical OBIA approach gives only a 0.84 F 1 "> F 1 score. This is an improvement over existing land cover maps, which underestimate rock by almost 90%. The resulting CNN approach is likely scalable but dependent on high-quality imagery and high-performance algorithms using representative training sets informed by expert mapping. As image quality and quantity continue to increase globally, machine learning models that incorporate high-quality training data informed by geologic, topographic, or other topical maps may be applied to more effectively identify exposed rock in large image collections.

California↗
USGS2020

Causes of land change in the U.S. Interior Highlands, 2001–2011

The causes of land change from 2001 through 2011 for the Interior Highlands region of the south-central United States were assessed using satellite imagery, historical land-use and land-cover data, and digital orthophotos. The study was designed to develop improved regional land-use and land-cover change information, including identification of the proximate causes of change. The four leading causes of land change involved various stages of forest change: harvest (376,497 hectares), reforestation (105,150 hectares), stand loss to fire (98,875 hectares), and thinning (54,029 hectares). The study provides baseline spatial data for understanding human and ecological dynamics in the region. The spatial data, including metadata, are available in the data release associated with this report at https://doi.org/10.5066/P9W4SF05.

Missouri, Arkansas, Oklahoma, Kansas↗
USGS2021

Modeling moose habitat use by age, sex, and season in Vermont, USA using high-resolution lidar and national land cover data

Moose ( Alces alces ) populations have experienced unprecedented declines along the southern periphery of their range, including Vermont, USA. Habitat management may be used to improve the status of the population and health of individuals. To date, however, Vermont wildlife managers have been challenged to effectively use this important tool due to the lack of fine-scale information on moose space use and habitat characteristics. To assess habitat use, we combined more than 40,000 moose locations collected from radio-collared individuals (n = 74), recent land cover data, and high resolution, 3-dimensional lidar ( light detection and ranging ) data to develop Resource Utilization Functions (RUF) by age (mature and young adult), season (dormant and growth), and sex. Each RUF linked home range use to average habitat conditions within 400 m or 1 km of each 30 m 2 pixel within the home range. Across analyses, the top RUF models included both composition (as measured through the National Land Cover Database) and structure (as measured through lidar) variables, and significantly outperformed models that excluded lidar variables. These findings support the notion that lidar is an effective tool for improving the ability of models to estimate patterns of habitat use, especially for larger bodied mammals. Generally speaking, female moose actively used areas with proportionally more regenerating forest (i.e., forage < 3.0 m) and more mature forest (i.e., canopy structure > 6.0 m), while males actively used more high elevation, mixed forest types. Further, moose exhibited important seasonal differences in habitat use that likely reflect temporal changes in energetic and nutritional requirements and behavior across the year. Moose used areas with proportionally more regenerating forest (i.e., forage < 3.0 m) during the growth period and female moose had strong positive associations with lidar-derived canopy structure during the growth (but not the dormant) period. Ultimately, the resultant maps of habitat use provide a means of informing management activities (e.g., the restoration or alteration of habitats to benefit moose) and policies around land use that may contribute to population recovery.

Vermont↗
USGS2023

Livestock removal increases plant cover across a heterogeneous dryland landscape on the Colorado Plateau

Livestock removal is increasingly used as a management option to mitigate the negative impacts of grazing-related disturbances on rangelands. Removal generally increases plant cover, but it is unclear when, where, and by how much plant and soil cover changes can be expected. On the Colorado Plateau, complex geology, topography, soils, and climate all interact to mediate the relationship between land cover, climate, and disturbance. In this study we used new developments in land cover mapping and analysis to assess landscape plant and bare soil cover up to 30 years after livestock removal from two grazing allotments in Capitol Reef National Park, Utah, USA. Results indicate that livestock removal increases plant cover 0.17-0.32% per year and reduces bare soil cover 0.34-0.41% per year, although these rates may be suppressed by warming temperatures. Soils, assessed through Soil Geomorphic Units, played a strong but complex role in mediating land cover changes through time. These results suggest that livestock removal is an effective strategy for increasing plant cover and reducing bare soil on the Colorado Plateau, but including soil information in decision making will enhance efficiency by improving manager's ability to prioritize management actions effectively across space and through time.

Environmental Research Letters↗
USGS1987

Producing Alaska interim land cover maps from Landsat digital and ancillary data

In 1985, the U.S. Geological Survey initiated a research program to produce 1:250,000-scale land cover maps of Alaska using digital Landsat multispectral scanner data and ancillary data and to evaluate the potential of establishing a statewide land cover mapping program using this approach. The geometrically corrected and resampled Landsat pixel data are registered to a Universal Transverse Mercator (UTM) projection, along with arc-second digital elevation model data used as an aid in the final computer classification. Areas summaries of the land cover classes are extracted by merging the Landsat digital classification files with the U.S. Bureau of Land Management's Public Land Survey digital file. Registration of the digital land cover data is verified and control points are identified so that a laser plotter can products screened film separate for printing the classification data at map scale directly from the digital file. The final land cover classification is retained both as a color map at 1:250,000 scale registered to the U.S. Geological Survey base map, with area summaries by township and range on the reverse, and as a digital file where it may be used as a category in a geographic information system.

Alaska↗
USGS2010

Evaluation of aquatic biota in relation to environmental characteristics measured at multiple scales in agricultural streams of the Midwest: 1993-2004

This study evaluated the relations between algal, invertebrate, and fish assemblages and physical environmental characteristics of streams at the reach, segment, and watershed scale in agricultural settings in the Midwest. The 86 stream sites selected for study were in predominantly agricultural watersheds sampled as part of the U.S. Geological Survey's National Water-Quality Assessment Program. Species abundance and over 130 biological metrics were used to determine which aspects of the assemblages were most sensitive to change at the three spatial scales. Digital orthophotograph-based riparian land use/land cover was used for analyses of riparian conditions at the reach and segment scales. The percentage area of different land-use/land-cover types was also determined for each watershed. Out of over 230 environmental characteristics examined, those that best explained variation in the biotic assemblages at each spatial scale include the following: 1) reach: bank vegetative cover, fine silty substrate, and open canopy angle; 2) segment: woody vegetation and cropland in the 250-m riparian buffer, and average length of undisturbed buffer; and 3) watershed: land use/land cover (both total forested and row crop), low-permeability soils, slope, drainage area, and latitude. All three biological assemblages, especially fish, correlated more with land use/land cover and other physical characteristics at the watershed scale than at the reach or segment scales. This study identifies biotic measures that can be used to evaluate potential improvements resulting from agricultural best-management practices and other conservation efforts, as well as evaluate potential impairment from urban development or other disturbances.

Midwest↗
USGS2009

Land Cover Change in the Boston Mountains, 1973-2000

The U.S. Geological Survey (USGS) Land Cover Trends project is focused on understanding the rates, trends, causes, and consequences of contemporary U.S. land-cover change. The objectives of the study are to: (1) to develop a comprehensive methodology for using sampling and change analysis techniques and Landsat Multispectral Scanner (MSS), Thematic Mapper (TM), and Enhanced Thematic Mapper Plus (ETM+) data to measure regional land-cover change across the United States; (2) to characterize the types, rates, and temporal variability of change for a 30-year period; (3) to document regional driving forces and consequences of change; and (4) to prepare a national synthesis of land-cover change (Loveland and others, 1999). The 1999 Environmental Protection Agency (EPA) Level III ecoregions derived from Omernik (1987) provide the geographic framework for the geospatial data collected between 1973 and 2000. The 27-year study period was divided into five temporal periods: 1973-1980, 1980-1986, 1986-1992, 1992-2000, and 1973-2000, and the data are evaluated using a modified Anderson Land Use Land Cover Classification System (Anderson and others, 1976) for image interpretation. The rates of land-cover change are estimated using a stratified, random sampling of 10-kilometer (km) by 10-km blocks allocated within each ecoregion. For each sample block, satellite images are used to interpret land-cover change for the five time periods previously mentioned. Additionally, historic aerial photographs from similar time frames and other ancillary data, such as census statistics and published literature, are used. The sample block data are then incorporated into statistical analyses to generate an overall change matrix for the ecoregion. Field data of the sample blocks include direct measurements of land cover, particularly ground-survey data collected for training and validation of image classifications (Loveland and others, 2002). The field experience allows for additional observations of the character and condition of the landscape, assistance in sample block interpretation, ground truthing of Landsat imagery, and determination of the driving forces of change identified in an ecoregion.

Open-File Report↗
USGS2014

Characterization of intra-annual reflectance properties of land cover classes in southeastern South Dakota using Landsat TM and ETM+ data

Landsat-7 and Landsat-5 have orbits that are offset from each other by 8 days. During the time that the sensors on both satellites are operational, there is an opportunity for conducting analyses that incorporate multiple intra-annual high spatial resolution data sets for characterizing the Earth's land surface. In the current study, nine Landsat thematic mapper (TM) and enhanced thematic mapper plus (ETM+) data sets, covering the same path and row on different dates, were acquired during a 1-year time interval for a region in southeastern South Dakota and analyzed. Scenes were normalized using pseudoinvariant objects, and digital data from a series of test sites were extracted from the imagery and converted to surface reflectance. Sunphotometer data acquired on site were used to atmospherically correct the data. Ground observations that were made throughout the growing season by a large group of volunteers were used to help interpret spectroradiometric patterns and trends. Normalized images were found to be very effective in portraying the seasonal patterns of reflectance change that occurred throughout the region. Many of the radiometric patterns related to plant growth and development, but some also related to different background properties. The different kinds of land cover in the region were spectrally and radiometrically characterized and were found to have different seasonal patterns of reflectance. The degree to which the land cover classes could be separated spectrally and radiometrically, however, depended on the time of year during which the data sets were acquired, and no single data set appeared to be adequate for separating all types of land cover. This has practical implications for classification studies because known patterns of seasonal reflectance properties for the different types of land cover within a region will facilitate selection of the most appropriate data sets for producing land cover classifications.

Canadian Journal of Remote Sensing↗
USGS2025

Factors influencing spatial and temporal patterns of Lanius ludovicianus (Loggerhead Shrike) occupancy at a grassland-sagebrush ecotone

Lanius ludovicianus (Loggerhead Shrike) is a predatory songbird that has experienced a severe population decline throughout its range since the 1940s, likely driven by a combination of factors, including habitat loss and fragmentation. Occupying larger territories compared to many other passerines, L. ludovicianus requires open habitat with interspersed trees and shrubs for nesting and perching and heterogeneous ground cover that provides hunting opportunities. Despite the general knowledge of L. ludovicianus habitat during breeding and nonbreeding seasons in many parts of its range, factors influencing long-term occupancy dynamics remain poorly understood. We addressed these knowledge gaps by analyzing 10 yr of L. ludovicianus detection data collected from breeding bird point-count surveys at a grassland-sagebrush ecotone in northeastern Wyoming, USA. We quantified L. ludovicianus detection and occupancy probabilities using a dynamic (multi-season) occupancy modeling framework and evaluated how initial occupancy and dynamic parameters (i.e., colonization and local extinction) were influenced by land-cover composition and change using remotely sensed land-cover data. Additionally, we used observer survey data to assess the influence of survey date and cloud cover on detection probability. We found that detection probability was influenced by survey date, while initial occupancy probability was positively associated with fences and presence of trees. Colonization probability increased with increased litter cover, whereas extinction probability was not influenced by land-cover and remained low throughout our study period. These findings highlight the importance of habitat features, such as fences and tree presence in shaping L. ludovicianus occupancy patterns. Further research is needed to understand the relationships between L. ludovicianus occupancy dynamics and demographic processes such as reproduction and survival. Identifying factors that influence occupancy dynamics and associated demographic processes can guide efforts to conserve and sustain L. ludovicianus populations.

Ornithological Applications↗
USGS2013

The development and application of a decision support system for land management in the Lake Tahoe Basin—The Land Use Simulation Model

This report describes and applies the Land Use Simulation Model (LUSM), the final modeling product for the long-term decision support project funded by the Southern Nevada Public Land Management Act and developed by the U.S. Geological Survey’s Western Geographic Science Center for the Lake Tahoe Basin. Within the context of the natural-resource management and anthropogenic issues of the basin and in an effort to advance land-use and land-cover change science, this report addresses the problem of developing the LUSM as a decision support system. It includes consideration of land-use modeling theory, fire modeling and disturbance in the wildland-urban interface, historical land-use change and its relation to active land management, hydrologic modeling and the impact of urbanization as related to the Lahontan Regional Water Quality Control Board’s recently developed Total Maximum Daily Load report for the basin, and biodiversity in urbanizing areas. The LUSM strives to inform land-management decisions in a complex regulatory environment by simulating parcel-based, land-use transitions with a stochastic, spatially constrained, agent-based model. The tool is intended to be useful for multiple purposes, including the multiagency Pathway 2007 regional planning effort, the Tahoe Regional Planning Agency (TRPA) Regional Plan Update, and complementary research endeavors and natural-resource-management efforts. The LUSM is an Internet-based, scenario-generation decision support tool for allocating retired and developed parcels over the next 20 years. Because USGS staff worked closely with TRPA staff and their “Code of Ordinances” and analyzed datasets of historical management and land-use practices, this report accomplishes the task of providing reasonable default values for a baseline scenario that can be used in the LUSM. One result from the baseline scenario for the model suggests that all vacant parcels could be allocated within 12 years. Results also include: assessment of model functionality, brief descriptions of the 7 basic output tables, assessment of the rate of change in land-use allocation pools over time, locations and amounts of the spatially explicit probabilities of land-use transitions by real estate commodity, and analysis of the state change from today’s existing land cover to potential land uses in the future. Assumptions and limitations of the model are presented. This report concludes with suggested next steps to support the continued utility of the LUSM and additional research avenues.

Nevada↗
USGS2004

Urban growth in American cities : glimpses of U.S. urbanization

The Earth's surface is changing rapidly. Changes are local, regional, national, and even global in scope. Some changes have natural causes, such as earthquakes or drought. Other changes, such as urban expansion, agricultural intensification, resource extraction, and water resources development, are examples of human-induced change that have significant impact upon people, the economy, and resources. The consequences that result from these changes are often dramatic and widespread (Buchanan, Acevedo, and Zirbes, 2002) It is the role of the U.S. Geological Survey (USGS) to provide useful and relevant scientific information both to the agencies within the Department of the Interior and to the Nation in general. In an effort to comply with this task, USGS scientists are assessing the status of, and the trends in, the Nation's land surface. This assessment provides useful information for regional and national land use decisionmaking. This knowledge can be used to deal with issues of significance to the Nation, such as quality-of-life, ecology of urban environments, ecosystem health, ecological integrity, water quality and quantity concerns, resource availability, vulnerability to natural hazards, safeguards to human health, air and land quality, and accessibility to scientific information. Results of these assessments can also be analyzed to reveal rates and trends in land use change. Results from urban growth studies provide a firm foundation for continuing research that explores the consequences of human modification of the landscape. The USGS seeks to illustrate and explain the spatial history of urban growth and corresponding land use change. Scientists are studying urban environments from a regional perspective and a time scale of decades to measure the changes that have occurred in order to help understand the impact of anticipated changes in the future. Within this booklet are pairs of images of selected urbanized regions from across the Nation. These image pairs illustrate the transformation that these areas have undergone over two decades. Specifically, they depict changes in the extent of urban land. Each change pair is composed of one image from the 1970s and one image from the 1990s. Accompanying each image pair is a brief historical geography of factors that helped facilitate major changes that have occurred since the founding of the main city and the consequences and challenges of regional urban growth. The goal of this publication is to provide an illustration of urban change that is easily understood by a broad audience. The images used throughout this booklet were generated from land cover data developed by the USGS. The data sources include the Geographic Information Retrieval and Analysis System (GIRAS) for the 1970s images and the National Land Cover Dataset (NLCD) for the 1990s images. GIRAS digital maps are based on photointerpretations completed in the mid-1970s. The NLCD is a land cover dataset for the conterminous United States based on 1992 Landsat thematic mapper (TM) satellite imagery and supplemental data (fig. 1a and fig. 1b). The USGS distributes both of these land use and land cover digital datasets. The images were developed by using a geographic information system (GIS). The GIRAS and NLCD datasets were used to identify urban land within each region. In the final images all urban areas are shown in red. A shaded-relief map of each region was used to display the topographic context of the red polygon coverage. For all of these images, urban land is defined as areas transformed into a built-up environment for human use. It includes residential areas, commercial and industrial developments, transportation features, and institutions.

Circular↗
USGS1995

Land-cover sampling designs, data-collection procedures, and land-cover data for the Central Nebraska Basins, 1993-94

Within the U.S. Geological Survey's National Water-Quality Assessment (NAWQA) Program, land-cover data are used in characterizing drainage areas upstream from surface-water sampling sites and areas selected for spatially distributed ground-water sampling. During the period of time when the initial 20 NAWQA study study-unit investigations were evaluating existing land-cover data, a Prototype 190 Conterminous U.S. land Cover Characteristics Data Set was produced by the Survey's EROS Data Center in Sioux Falls, South Dakota. As part of the Central Nebraska Basins (CNB) study-unit investigation, a method was developed to estimate the areal extent of the principal land-cover types within selected seasonally distinct land-cover (SDLC) regions defined in the 1990 prototype data set. This report describes the sampling designs and methods used to collect land-cover data in the CNB study unit. Data collected at 309 sampling sites during the summers of 1993 and 1994 are presented and statistically summarized. Eleven land-cover categories were quantified, including major field crops and broad noncropland cover types.

Open-File Report↗
USGS1979

Land use statistics for West Virginia, Part I

The West Virginia Geological and Economic Survey and the United States Geological Survey have completed a cooperative program to provide land-use and land-cover maps and data for the State. This program begins to satisfy a longstanding need for a consistent level of detail, standardization in categorization, and scale of compilation for land-use and land-cover maps and data. The statistical information contained in this Bulletin provides land-use acreage tabulations for the first 20 counties that have been completed. Statistics are being compiled for the remaining counties and will be published shortly. This information has been derived from the recently completed Land-Use Map of West Virginia (on open file at the West Virginia Geological and Economic Survey - Environmental Section). In addition to land-use acreage, we have also included land-use percent. All statistics throughout this Bulletin are in the same format for ease of comparison.

West Virginia↗
USGS2020

Substantially greater carbon emissions estimated based on annual land-use transition data

Quantifying land-use and land-cover change (LULCC) effects on carbon sources and sinks has been very challenging because of the availability and quality of LULCC data. As the largest estuary in the United States, Chesapeake Bay is a rapidly changing region and is affected by human activities. A new annual land-use and land-cover (LULC) data product developed by the U.S. Geological Survey Land Change Monitoring and Analysis Program (LCMAP) from 2001 to 2011 was analyzed for transitions between agricultural land, developed land, grassland, forest land and wetland. The Land Use and Carbon Scenario Simulator was used to simulate effects of LULCC and ecosystem disturbance in the south of the Chesapeake Bay Watershed (CBW) on carbon storage and fluxes, with carbon parameters derived from the Integrated Biosphere Simulator. We found that during the study period: (1) areas of forest land, disturbed land, agricultural land and wetland decreased by 90, 82, 57, and 65 km 2 , respectively, but developed lands gained 293 km 2 (29 km 2 annually); (2) total ecosystem carbon stock in the CBW increased by 13 Tg C from 2001 to 2011, mainly due to carbon sequestration of the forest ecosystem; (3) carbon loss was primarily attributed to urbanization (0.224 Tg C·yr −1 ) and agricultural expansion (0.046 Tg C·yr −1 ); and (4) estimated carbon emissions and harvest wood products were greater when estimated with the annual LULC input. We conclude that a dense time series of LULCC, such as that of the LCMAP program, may provide a more accurate accounting of the effects of land use change on ecosystem carbon, which is critical to understanding long-term ecosystem carbon dynamics.

Delaware, Maryland, Virginia↗
USGS2011

Chapter 11: Management considerations

We conducted an ecoregional assessment of sagebrush ( Artemisia spp. ) ecosystems in the Wyoming Basins and surrounding regions (WBEA) to determine broad-scale species-environmental relationships. Our goal was to assess the potential influence from threats to the sagebrush ecosystem on associated wildlife through the use of spatially explicit occurrence and abundance models. These models were developed using information from field surveys conducted along gradients of vegetation productivity and human disturbance integrated with spatial datasets delineating land cover, topography, and human land use in the WBEA area. Our evaluation included all sagebrush-associated wildlife species across multiple taxa whose habitat requirements and distributions were appropriate for modeling and interpretation at the broad scales of this assessment. Dominant land uses were included in delineating the human footprint. Although overall levels of the cumulative human footprint were generally low across the WBEA area, oil and gas activities have decreased the amount of shrubland habitats and increased fragmentation within development regions over the last century. At the scale of this assessment, the influence of humans was primarily expressed as an indirect function through actions that altered or reduced available habitat. We identified 65 plant species of conservation concern; 28 of 40 vertebrate species associated with sagebrush were species of concern in at least one state. We modeled environmental relationships for 15 wildlife species from data collected from surveys conducted in 2005 and 2006 designed to sample multiple species and taxa along land cover and land use gradients across the WBEA area. Occurrence of 3 species was negatively influenced by human features; anthropogenic features were a positive influence for 3 species, 8 had a mixed response, and 1 had no measurable relationship. Sagebrush land cover, considered in all wildlife models, was important to most species but differed among species in the proportion of sagebrush required and at what spatial extent. For most species examined, the spatial extent at which sagebrush cover influenced the probability of occupancy was much larger than an individual’s home range size. Exotic plants were strongly associated with human features, particularly roads, which may function as linear vectors to facilitate spread of exotic plants across the WBEA area. We used coarse-grained spatial and thematic data because of the large spatial extent (350,000 km 2 ) of the WBEA area and the need for a consistent land cover map for the region. Distributions of species occurrence or abundance mapped in this assessment need to be corroborated with information on population demographics. In addition, our results should be interpreted relative to assumptions inherent in broad-scale ecoregional assessments. Our assessment provides managers with extensive and detailed maps of occurrence and abundance, allowing for status assessments of native species, diversity and richness, natural communities, and ecological systems present within the Wyoming Basins.

Wyoming↗
USGS2012

A water-budget model and estimates of groundwater recharge for Guam

On Guam, demand for groundwater tripled from the early 1970s to 2010. The demand for groundwater is anticipated to further increase in the near future because of population growth and a proposed military relocation to Guam. Uncertainty regarding the availability of groundwater resources to support the increased demand has prompted an investigation of groundwater recharge on Guam using the most current data and accepted methods. For this investigation, a daily water-budget model was developed and used to estimate mean recharge for various land-cover and rainfall conditions. Recharge was also estimated for part of the island using the chloride mass-balance method. Using the daily water-budget model, estimated mean annual recharge on Guam is 394.1 million gallons per day, which is 39 percent of mean annual rainfall (999.0 million gallons per day). Although minor in comparison to rainfall on the island, water inflows from water-main leakage, septic-system leachate, and stormwater runoff may be several times greater than rainfall at areas that receive these inflows. Recharge is highest in areas that are underlain by limestone, where recharge is typically between 40 and 60 percent of total water inflow. Recharge is relatively high in areas that receive stormwater runoff from storm-drain systems, but is relatively low in urbanized areas where stormwater runoff is routed to the ocean or to other areas. In most of the volcanic uplands in southern Guam where runoff is substantial, recharge is less than 30 percent of total water inflow. The water-budget model in this study differs from all previous water-budget investigations on Guam by directly accounting for canopy evaporation in forested areas, quantifying the evapotranspiration rate of each land-cover type, and accounting for evaporation from impervious areas. For the northern groundwater subbasins defined in Camp, Dresser & McKee Inc. (1982), mean annual baseline recharge computed in this study is 159.1 million gallons per day, which is 50 percent of mean annual rainfall, and is 42 percent greater than the recharge estimate of Camp, Dresser & McKee Inc. (1982). For the northern aquifer sectors defined in Mink (1991), which encompass most of the northern half of the island, mean annual baseline recharge computed in this study is 238.0 million gallons per day, which is 51 percent of mean annual rainfall, and is about 6 percent lower than the recharge estimate of Mink (1991). For the drought simulation performed in this study, recharge for the entire island is 259.3 million gallons per day, which is 34 percent lower than recharge computed for baseline conditions. For all aquifer sectors defined by Mink (1991), total recharge during drought conditions is 32 percent lower than mean baseline recharge. For the future land-cover water-budget simulation, which represents potential land-cover changes owing to the military relocation and population growth, estimated recharge for the entire island is nearly equal to the baseline recharge estimate that was based on 2004 land cover. Using the water-budget model, estimated recharge in the northern half of the island is most sensitive to crop coefficients and net precipitation rates&mdash;two of the water-budget parameters used in the estimation of total evapotranspiration. Estimated recharge in the southern half of the island is most sensitive to crop coefficients, net precipitation rate, and runoff-to-rainfall ratios. During March 2010 to May 2011, bulk-deposition samples from five rainfall stations on Guam were collected and analyzed for chloride. Additionally, samples from five groundwater sites were collected and analyzed for chloride. Results were used to estimate groundwater recharge using the chloride mass-balance method. Recharge estimates using this method at three bulk-deposition stations on the northern limestone plateau range from about 25 to 48 percent of rainfall. These recharge estimates are similar to the estimate of Ayers (1981) who also used this method. Recharge estimates at each bulk-deposition station, however, are lower than the baseline recharge estimate from the water-budget model used in this study. This may be because no large storms, such as tropical cyclones, passed near Guam during March 2010 to May 2011.

Scientific Investigations Report↗
USGS2007

Estimating soil erosion using the USPED model and consecutive remotely sensed land cover observations

Intensified soil erosion contributes to the degradation of ecosystems. Better estimation of soil erosion across landscapes is a necessary part of understanding ecosystem biogeochemical cycles and ecosystem sustainability. In this study, we used the Unit Stream Power-based Erosion Deposition (USPED) model to estimate the lateral movement of soils across Fort Benning, a military training installation in western Georgia, USA. A land cover weight factor was used in the calculation of surface flow accumulation. The simulation results were compared with observations of the total suspended sediments in stream water for ten watersheds, and showed a significant linear relationship (R 2 = 0.72). Erosion estimates of the ten watersheds are also related to the land disturbance index that is a measure of the intensity of military training disturbances. Results suggest that the USPED model is an effective tool to quantify erosion and deposition at military installations.

Georgia↗
USGS2020

Human-associated species dominate passerine communities across the United States

Aim Human development and agriculture can have transformative and homogenizing effects on natural systems, shifting the composition of ecological communities towards non-native and native species that tolerate or thrive under human-dominated conditions. These impacts cannot be fully captured by summarizing species presence, as they include dramatic changes to patterns of species abundance. However, how human land use patterns and species invasions intersect to shape patterns of abundance and dominance within ecological communities is poorly understood even in well-known taxa. Location Conterminous United States. Time period 2010–2012. Major taxa studied Passeriformes. Methods We analyse continental-scale monitoring data to study the proportional abundance of non-native and native synanthropic species within passerine bird communities. Synanthropic species are those that benefit from an association with humans. We estimate how the amount and configuration of human development and agriculture relate to the degree to which human-associated species dominate passerine communities across the continent. Results Human-associated species comprised the majority of detected passerine individuals across two-thirds of bird surveys. Non-native and synanthropic species responded differently to land cover and reached highest relative abundance in different portions of the continent. The proportional abundance of synanthropic birds increased rapidly with development, but was not related to the configuration of land cover. The proportion of non-native individuals was higher when intensively-used land cover was more aggregated. Main conclusions Even low amounts of intensively-used lands were associated with a dramatic reshaping of passerine communities, with consequences for patterns of relative abundance across the continent.

Global Ecology and Biogeography↗