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At least 1,045 records · Page 58Linked to original sources
USGS2022

Satellite remote sensing of crop water use across the Missouri River Basin for 1986–2018 period

Understanding historical crop water use (CWU) dynamics is important to improve land and water management. In this study, well-validated (coefficient of determination = 0.91, percent bias = 4%, and percent root mean square error = 11.8%) Landsat-based actual evapotranspiration (ETa) time-series estimations were used to (1) assess summer season CWU (CWU-Su) dynamics, (2) investigate CWU-Su trends over the study period (1986–2018; 33 years) at the regional- and pixel-scales, and (3) attribute CWU-Su driving factors across Missouri River Basin. Spatial variability of the ETa estimations along with the observed bimodal probability density distribution of ETa highlighted a strong relation between land cover and water uses across the basin. The bimodal distribution of ETa also indicated the presence of two major landcovers in the basin. The drier foothill regions in northwestern Missouri River Basin, dominated by grassland/shrubland, showed lower ETa (< 500 mm/year), whereas cropland dominated regions in lower semi-humid basin and forested subbasins exhibited higher ETa (> 600 mm/year). The CWU-Su anomalies revealed the vulnerability of the basin to year-to-year weather conditions. The CWU-Su trend analysis revealed a significant positive trend (p < 0.1) at the regional-scale affecting 30% of basin’s cropland pixels. The cropland pixels under positive CWU-Su trend were found to be clustered in the eastern and central Missouri River Basin as a result of the combined effect of increased crop production area, increased crop yields, crop practice shifts to higher biomass crops, and increased irrigated land. The effect of improved irrigation and water management practices on reducing CWU-Su was observed in western Missouri River Basin, which had a stable major crop throughout the study period. Overall, the study highlights the usefulness of Landsat imagery and remote sensing-based ETa modeling approaches in generating historical time-series ETa maps over a wide range of elevation, vegetation, and climate.

Missouri River Basin↗
USGS2010

Web-enabled Landsat Data (WELD): Landsat ETM+ composited mosaics of the conterminous United States

Since January 2008, the U.S. Department of Interior / U.S. Geological Survey have been providing free terrain-corrected (Level 1T) Landsat Enhanced Thematic Mapper Plus (ETM+) data via the Internet, currently for acquisitions with less than 40% cloud cover. With this rich dataset, temporally composited, mosaics of the conterminous United States (CONUS) were generated on a monthly, seasonal, and annual basis using 6521 ETM+ acquisitions from December 2007 to November 2008. The composited mosaics are designed to provide consistent Landsat data that can be used to derive land cover and geo-physical and bio-physical products for detailed regional assessments of land-cover dynamics and to study Earth system functioning. The data layers in the composited mosaics are defined at 30 m and include top of atmosphere (TOA) reflectance, TOA brightness temperature, TOA normalized difference vegetation index (NDVI), the date each composited pixel was acquired on, per-band radiometric saturation status, cloud mask values, and the number of acquisitions considered in the compositing period. Reduced spatial resolution browse imagery, and top of atmosphere 30 m reflectance time series extracted from the monthly composites, capture the expected land surface phenological change, and illustrate the potential of the composited mosaic data for terrestrial monitoring at high spatial resolution. The composited mosaics are available in 501 tiles of 5000 × 5000 30 m pixels in the Albers equal area projection and are downloadable at http://landsat.usgs.gov/WELD.php . The research described in this paper demonstrates the potential of Landsat data processing to provide a consistent, long-term, large-area, data record.

Remote Sensing of Environment↗
USGS2023

Land cover differentially affects abundance of common and rare birds

While rare species are vulnerable to global change, large declines in common species (i.e., those with large population sizes, large geographic distributions, and/or that are habitat generalists) also are of conservation concern. Understanding if and how commonness mediates species' responses to global change, including land cover change, can help guide conservation strategies. We explored avian population responses to land cover change along a gradient from common to rare species using avian data from the North American Breeding Bird Survey (BBS) and land cover data from the National Land Cover Database for the conterminous United States. Specifically, we used generalized linear mixed effects models to ask if species' commonness affected the relationship between land cover and counts, using the initial amount of and change in land cover surrounding each North American BBS route from 2001 to 2016. We quantified species' commonness as a continuous metric at the national scale using the logarithm (base 10) of each species' total count across all routes in the conterminous United States in 2001. For our focal 15-year period, we found that higher proportions of initial natural land cover favored (i.e., were correlated with higher) counts of rare but not common species. We also found that commonness mediated how change in human land cover, but not natural land cover, was associated with species' counts at the end of the study period. Increases in developed lands did not favor counts of any species. Increases in agriculture and declines in pasture favored counts of common but not rare species. Our findings show a signal of commonness in how species respond to a major dimension of global change. Evaluating how and why commonness mediates species' responses to land cover change can help managers design conservation portfolios that sustain the spectrum of common to rare species.

Global Change Biology↗
USGS2013

The added complications of climate change: Understanding and managing biodiversity and ecosystems

Ecosystems around the world are already threatened by land-use and land-cover change, extraction of natural resources, biological disturbances, and pollution. These environmental stressors have been the primary source of ecosystem degradation to date, and climate change is now exacerbating some of their effects. Ecosystems already under stress are likely to have more rapid and acute reactions to climate change; it is therefore useful to understand how multiple stresses will interact, especially as the magnitude of climate change increases. Understanding these interactions could be critically important in the design of climate adaptation strategies, especially because actions taken by other sectors (eg energy, agriculture, transportation) to address climate change may create new ecosystem stresses.

Frontiers in Ecology and the Environment↗
USGS2025

Estimated hydrogeologic, spatial, and temporal distribution of self-supplied domestic groundwater withdrawals for aquifers of the Virginia Coastal Plain

Water use from private-domestic wells accounts for nearly 40 percent of total groundwater withdrawals in the Virginia Coastal Plain Physiographic Province (henceforth called the Virginia Coastal Plain). However, because self-supplied domestic water use generally falls below the Virginia Department of Environmental Quality (VDEQ) reporting and management threshold of 300,000 gallons per month, quantifying these withdrawals is challenging. This report builds upon the foundation of previous U.S. Geological Survey investigations by providing revised techniques to improve estimates of the aquifer source, spatial distribution, and monthly magnitude of these groundwater withdrawals. The aquifer sources of private-domestic wells in the Virginia Coastal Plain were estimated by cross-referencing 8,264 well records from the VDEQ and the Virginia Department of Health to a digital model of the Virginia Coastal Plain hydrogeologic framework. This analysis highlights the regional importance of the Yorktown-Eastover, Potomac, and surficial aquifers. Collectively, these three aquifers account for 80 percent of self-supplied domestic groundwater withdrawals. The population using self-supplied domestic water was estimated using census blocks, well-use ratios, building footprints, and land-use and land-cover data to produce a high-resolution, disaggregated, raster-based dataset. This approach improves upon previous models at the census-block or road-network scale by reducing the low-density spread of the self-supplied domestic population across undeveloped areas and concentrating the population and its corresponding water use in the areas where it is most likely to occur. Results show that an estimated 475,332 people comprise the 2020 self-supplied domestic population of the Virginia Coastal Plain, an increase of 5.7 percent since 2010, and the greatest concentrations of self-supplied domestic population surround large cities. Estimates could be further refined with the addition of current and complete spatial data on public water-system service areas. The quantity of water used by the self-supplied domestic population was estimated by modifying published state per-capita water-use coefficients with the corresponding monthly variability assessed from Virginia Coastal Plain public water-system withdrawal data. This analysis estimates an average increase of 12 percent from June through August and an average decrease of 8 percent from December through March from the baseline annual average of 80 gallons per day per capita, which generally matches similar studies in the eastern United States. The application of these revised methodologies for the estimation of private-domestic wells and the self-supplied domestic population improves understanding of domestic groundwater use in the Virginia Coastal Plain across hydrogeologic, spatial, and temporal scales. These revisions help better inform water-resource managers and decision makers and support higher resolution groundwater modeling. Furthermore, these methods are transferrable to other areas where self-supplied domestic water withdrawals are important to the overall water budget.

Virginia↗
USGS1956

Land use and sediment yield

When the vegetal cover is removed from a land surface, the rate of removal of the soil material, at least initially, increases rapidly. So well known is this principle that it hardly needs restatement. If attention is focused on any individual drainage basin in its natural state, large or small, and inquiry is made as to the rate of denudation, a quantitative answer is not easily obtained. The possible error in any computation of rate of sediment production from any given drainage basin is considerable. Significant variations are found in sediment yields from closely adjacent watersheds which appear to be generally similar. To make a quantitative evaluation of the change in the rate of denudation when the natural vegetation is disturbed is, therefore, even more difficult. Considering the fact that "soil conservation" has been promoted to the status of a science, our lack of ability to answer what is apparently so simple a question may seem surprising. Let us look at some of the reasons.

Conference Paper↗
USGS2003

Studies of Alaskan volcanoes using synthetic aperature radar and Landsat imagery

Approximately 10 percent of the world’s active volcanoes are located in the Alaskan Aleutian arc and produce about 3-4 explosive eruptions per year. Even with this high amount of volcanic activity, the remote locations and harsh environments of the Aleutian volcanoes conspire to keep them among some of the most poorly studied volcanoes in the world. Space-borne remote sensed imagery can play a significant role in improving our understanding of activity at these volcanoes. Synthetic aperture radar (SAR), Landsat imagery, and Digital Elevation Models (DEMs) derived from SRTM and the National Elevation Database (NED) are used to study several Alaskan volcanoes. Interferometric SAR (InSAR) techniques with ERS-1 and ERS-2 SAR imagery are used to measure ground-surface deformation, which enables the construction of detailed mechanical models that enhance the study of magmatic and tectonic processes. The 30-year historical archive of Landsat data is used to study land cover change, visualize the ash plumes of Aleutian volcanic eruptions, and to map the extent of lava flows. Differencing two DEMs that represent volcano topography before and after an eruption makes it possible to calculate the volume of extruded materials. This paper provides a progress report on how InSAR, Landsat imagery and digital elevation data can be used to better understand the volcanic processes at three Aleutian volcanoes.

Alaska↗
USGS2018

Federal lands greenhouse emissions and sequestration in the United States—Estimates for 2005–14

In January 2016, the Secretary of the U.S. Department of the Interior tasked the U.S. Geological Survey (USGS) with producing a publicly available and annually updated database of estimated greenhouse gas emissions associated with the extraction and use (predominantly some form of combustion) of fossil fuels from Federal lands. In response, the USGS has produced estimates of the greenhouse gas emissions resulting from the extraction and end-use combustion of fossil fuels produced on Federal lands in the United States, as well as estimates of ecosystem carbon emissions and sequestration on those lands. American Indian and Tribal lands were not included in this analysis. The emissions estimates span a 10-year period (2005–14) and are reported for 28 States and two offshore areas. Nationwide emissions from fossil fuels produced on Federal lands in 2014 were 1,279.0 million metric tons of carbon dioxide equivalent (MMT CO 2 Eq.) for carbon dioxide (CO 2 ), 47.6 MMT CO 2 Eq. for methane (CH 4 ), and 5.5 MMT CO 2 Eq. for nitrous oxide (N 2 O). Compared to 2005, the 2014 totals represent decreases in emissions for all three greenhouse gases (decreases of 6.1 percent for CO 2 , 10.5 percent for CH 4 , and 20.3 percent for N 2 O). Emissions from fossil fuels produced on Federal lands represent, on average, 23.7 percent of national emissions for CO 2 , 7.3 percent for CH 4 , and 1.5 percent for N 2 O over the 10 years included in this estimate. In 2005, Federal lands of the conterminous United States stored 82,289 MMT CO 2 Eq. in terrestrial ecosystems. By 2014, carbon storage, or sequestration, was estimated at 83,600 MMT CO 2 Eq., representing an increase of 1.6 percent, or 1,311 MMT CO 2 Eq. Soils stored most of the ecosystem carbon (63 percent), followed by live vegetation (26 percent) and dead organic matter (11 percent). The rate of net carbon uptake in ecosystems ranged from a sink (sequestration) of 475 million metric tons of carbon dioxide per year (MMT CO 2 Eq./yr) to a source (emission) of 51 MMT CO 2 Eq./yr because of annual variability in climate and weather, rates of land-use and land-cover change, and wildfire frequency, among other factors. At the national level, the USGS estimates that terrestrial ecosystems (forests, grasslands, and shrublands) on Federal lands sequestered an average of 195 MMT CO 2 Eq./yr between 2005 and 2014, offsetting approximately 15 percent of the CO 2 emissions resulting from the extraction of fossil fuels on Federal lands and their end-use combustion. The USGS estimates presented in this report represent a first-of-its-kind accounting for the emissions resulting from fossil fuel extraction on Federal lands and the end-use combustion of those fuels, as well as for the sequestration of carbon in terrestrial ecosystems on Federal lands. The net CO 2 emissions estimate, which is the difference between the emitted and sequestered CO 2 , provides an informative combined result describing the emissions (fossil fuel extraction and end-use combustion) associated with a State’s Federal lands and sequestration on those same lands. The estimates included in this report can provide context for future energy decisions, as well as a basis to track change in the future.

Scientific Investigations Report↗
USGS2014

The effects of changing land cover on streamflow simulation in Puerto Rico

This study quantitatively explores whether land cover changes have a substantive impact on simulated streamflow within the tropical island setting of Puerto Rico. The Precipitation Runoff Modeling System (PRMS) was used to compare streamflow simulations based on five static parameterizations of land cover with those based on dynamically varying parameters derived from four land cover scenes for the period 1953-2012. The PRMS simulations based on static land cover illustrated consistent differences in simulated streamflow across the island. It was determined that the scale of the analysis makes a difference: large regions with localized areas that have undergone dramatic land cover change may show negligible difference in total streamflow, but streamflow simulations using dynamic land cover parameters for a highly altered subwatershed clearly demonstrate the effects of changing land cover on simulated streamflow. Incorporating dynamic parameterization in these highly altered watersheds can reduce the predictive uncertainty in simulations of streamflow using PRMS. Hydrologic models that do not consider the projected changes in land cover may be inadequate for water resource management planning for future conditions.

Journal of the American Water Resources Associatio↗
USGS1996

Exploratory analysis of environmental interactions in central California

As part of its global change research program, the United States Geological Survey (USGS) has produced raster data that describe the land cover of the United States using a consistent format. The data consist of elevations, satellite measurements, computed vegetation indices, land cover classes, and ancillary political, topographic and hydrographic information. This open-file report uses some of these data to explore the environment of a (256-km)? region of central California. We present various visualizations of the data, multiscale correlations between topography and vegetation, a path analysis of more complex statistical interactions, and a map that portrays the influence of agriculture on the region's vegetation. An appendix contains C and Mathematica code used to generate the graphics and some of the analysis.

Open-File Report↗
USGS2013

Wetland fire scar monitoring and analysis using archival Landsat data for the Everglades

The ability to document the frequency, extent, and severity of fires in wetlands, as well as the dynamics of post-fire wetland land cover, informs fire and wetland science, resource management, and ecosystem protection. Available information on Everglades burn history has been based on field data collection methods that evolved through time and differ by land management unit. Our objectives were to (1) design and test broadly applicable and repeatable metrics of not only fire scar delineation but also post-fire land cover dynamics through exhaustive use of the Landsat satellite data archives, and then (2) explore how those metrics relate to various hydrologic and anthropogenic factors that may influence post-fire land cover dynamics. Visual interpretation of every Landsat scene collected over the study region during the study time frame produced a new, detailed database of burn scars greater than 1.6 ha in size in the Water Conservation Areas and post-fire land cover dynamics for Everglades National Park fires greater than 1.6 ha in area. Median burn areas were compared across several landscape units of the Greater Everglades and found to differ as a function of administrative unit and fire history. Some burned areas transitioned to open water, exhibiting water depths and dynamics that support transition mechanisms proposed in the literature. Classification tree techniques showed that time to green-up and return to pre-burn character were largely explained by fire management practices and hydrology. Broadly applicable as they use data from the global, nearly 30-year-old Landsat archive, these methods for documenting wetland burn extent and post-fire land cover change enable cost-effective collection of new data on wetland fire ecology and independent assessment of fire management practice effectiveness.

Florida↗
USGS2022

Drivers of habitat quality for a reintroduced elk herd

Understanding spatiotemporal variation in habitat quality is essential for guiding wildlife reintroduction and restoration programs. The habitat productivity hypothesis posits that home range size is inversely related to habitat quality. Thus, home range size may be used as a proxy for habitat quality and can identify important land cover features for a recovering species. We sought to quantify variation in home range size across the biological cycle (seasons) for a reintroduced elk ( Cervus canadensis ) population in southwestern Virginia, USA and quantify habitat quality by linking home range sizes to the land cover types they contain using linear mixed-effects models. We found mean home range size was largest during late gestation for female elk. Additionally, throughout the year, smaller home ranges were associated with larger proportions of non-forested habitats whereas forested habitats were generally the opposite. However, both presumed poor- and high-quality habitats influenced female elk space use. Our approach revealed spatial variation in habitat quality for a recovering elk herd, demonstrated the importance of non-forested habitats to elk, can guide decisions regarding the location of future elk reintroduction programs, and serve as a model for evaluating habitat quality associated with wildlife reintroductions.

Virginia↗
USGS2005

Soil organic carbon dynamics as related to land use history in the northwestern Great Plains

Strategies for mitigating the global greenhouse effect must account for soil organic carbon (SOC) dynamics at both spatial and temporal scales, which is usually challenging owing to limitations in data and approach. This study was conducted to characterize the SOC dynamics associated with land use change history in the northwestern Great Plains ecoregion. A sampling framework (40 sample blocks of 10 × 10 km 2 randomly located in the ecoregion) and the General Ensemble Biogeochemical Modeling System (GEMS) were used to quantify the spatial and temporal variability in the SOC stock from 1972 to 2001. Results indicate that C source and sink areas coexisted within the ecoregion, and the SOC stock in the upper 20-cm depth increased by 3.93 Mg ha −1 over the 29 years. About 17.5% of the area was evaluated as a C source at 122 kg C ha −1 yr −1 . The spatial variability of SOC stock was attributed to the dynamics of both slow and passive fractions, while the temporal variation depended on the slow fraction only. The SOC change at the block scale was positively related to either grassland proportion or negatively related to cropland proportion. We concluded that the slow C pool determined whether soils behaved as sources or sinks of atmospheric CO 2 , but the strength depended on antecedent SOC contents, land cover type, and land use change history in the ecoregion.

Global Biogeochemical Cycles↗
USGS2003

Effects of landscape characteristics on land-cover class accuracy

The effects of patch size and land-cover heterogeneity on classification accuracy were evaluated using reference data collected for the National Land-Cover Data (NLCD) set accuracy assessment. Logistic regression models quantified the relationship between classification accuracy and these landscape variables for each land-cover class at both the Anderson Levels I and II classification schemes employed in the NLCD. The general relationships were consistent, with the odds of correctly classifying a pixel increasing as patch size increased and decreasing as heterogeneity increased. Specific characteristics of these relationships, however, showed considerable diversity among the various classes. Odds ratios are reported to document these relationships. Interaction between the two landscape variables was not a significant influence on classification accuracy, indicating that the effect of heterogeneity was not impacted by the sample being in a small or large patch. Landscape variables remained significant predictors of class-specific accuracy even when adjusted for regional differences in the mapping and assessment processes or landscape characteristics. The land-cover class-specific analyses provide insight into sources of classification error and a capacity for predicting error based on a pixel's mapped land-cover class, patch size and surrounding land-cover heterogeneity.

Remote Sensing of Environment↗
USGS1986

Vegetation and terrain mapping in Alaska using Landsat MSS and digital terrain data

During the past 5 years, the U.S. Geological Survey's (USGS) Earth Resources Observation Systems (EROS) Data Center Field Office in Anchorage, Alaska has worked cooperatively with Federal and State resource management agencies to produce land-cover and terrain maps for 245 million acres of Alaska. The need for current land-cover information in Alaska comes principally from the mandates of the Alaska National Interest Lands Conservation Act (ANILCA), December 1980, which requires major land management agencies to prepare comprehensive management plans. The land-cover mapping projects integrate digital Landsat data, terrain data, aerial photographs, and field data. The resultant land-cover and terrain maps and associated data bases are used for resource assessment, management, and planning by many Alaskan agencies including the U.S. Fish and Wildlife Service, U.S. Forest Service, Bureau of Land Management, and Alaska Department of Natural Resources. Applications addressed through use of the digital land-cover and terrain data bases range from comprehensive refuge planning to multiphased sampling procedures designed to inventory vegetation statewide. The land-cover mapping programs in Alaska demonstrate the operational utility of digital Landsat data and have resulted in a new land-cover mapping program by the USGS National Mapping Division to compile 1:250,000-scale land-cover maps in Alaska using a common statewide land-cover map legend.

Alaska↗
USGS2013

Recent land-use/land-cover change in the Central California Valley

Open access to Landsat satellite data has enabled annual analyses of modern land-use and land-cover change (LULCC) for the Central California Valley ecoregion between 2005 and 2010. Our annual LULCC estimates capture landscape-level responses to water policy changes, climate, and economic instability. From 2005 to 2010, agriculture in the region fluctuated along with regulatory-driven changes in water allocation as well as persistent drought conditions. Grasslands and shrublands declined, while developed lands increased in former agricultural and grassland/shrublands. Development rates stagnated in 2007, coinciding with the onset of the historic foreclosure crisis in California and the global economic downturn. We utilized annual LULCC estimates to generate interval-based LULCC estimates (2000–2005 and 2005–2010) and extend existing 27 year interval-based land change monitoring through 2010. Resulting change data provides insights into the drivers of landscape change in the Central California Valley ecoregion and represents the first, continuous, 37 year mapping effort of its kind.

California↗
USGS2018

Simulated hydrologic response to climate change during the 21st century in New Hampshire

The U.S. Geological Survey, in cooperation with the New Hampshire Department of Environmental Services and the Department of Health and Human Services, has developed a hydrologic model to assess the effects of short- and long-term climate change on hydrology in New Hampshire. This report documents the model and datasets developed by using the model to predict how climate change will affect the hydrologic cycle and provide data that can be used by State and local agencies to identify locations that are vulnerable to the effects of climate change in areas across New Hampshire. Future hydrologic projections were developed from the output of five general circulation models for two future climate scenarios. The scenarios are based on projected future greenhouse gas emissions and estimates of land-use and land-cover change within a projected global economic framework. An evaluation of the possible effect of projected future temperature on modeling of evapotranspiration is summarized to address concerns regarding the implications of the future climate on model parameters that are based on climate variables. The results of the model simulations are hydrologic projections indicating increasing streamflow across the State with large increases in streamflow during winter and early spring and general decreases during late spring and summer. Wide spatial variability in changes to groundwater recharge is projected, with general decreases in the Connecticut River Valley and at high elevations in the northern part of the State and general increases in coastal and lowland areas of the State. In general, total winter snowfall is projected to decrease across the State, but there is a possibility of increasing snow in some locations, particularly during November, February, and March. The simulated future changes in recharge and snowfall vary by watershed across the State. This means that each area of the State could experience very different changes, depending on topography or other factors. Therefore, planning for infrastructure and public safety needs to be flexible in order to address the range of possible outcomes indicated by the various model simulations. The absolute magnitude and timing of the daily streamflows, especially the larger floods, are not considered to be reliably simulated compared to changes in frequency and duration of daily streamflows and changes in accumulated monthly and seasonal streamflow volumes. Simulated current and future streamflow, groundwater recharge, and snowfall datasets include simulated data derived from the five general circulation models used in this study for a current reference time period and two future time periods. Average monthly streamflow time series datasets are provided for 27 streamgages in New Hampshire. Fourteen of the 27 streamgages associated with daily streamflow time series showed a good calibration. Average monthly groundwater recharge and snowfall time series for the same reference time period and two future time periods are also provided for each of the 467 hydrologic response units that compose the model.

New Hampshire↗
USGS2025

Greater white-fronted goose habitat use in Louisiana provides water depth management insights

Numerous waterfowl species have altered their geographic distribution in recent decades. The greater white-fronted goose ( Anser albifrons ) has shifted its wintering distribution from coastal marshes in Texas and Louisiana, USA, to interior landscapes, creating challenges for conservation managers. Although the range shift has been primarily attributed to landscape-scale changes in rice production, effects of fine-scale habitat conditions on greater white-fronted goose habitat use are unknown. Thus, information on fine-scale environmental conditions could provide information to managers working to mitigate effects of the shift. We used global positioning system neck collars to monitor 78 greater white-fronted geese in Louisiana each winter during 2016–2019 and visited all used locations to record vegetation height, water depth, and land cover. We modeled greater white-fronted goose habitat use in 4 regions across Louisiana (central, coastal, north, southwest), and evaluated effects of vegetation height, water depth, land cover, and interactions. In our candidate model set, we included a sampling null, which accounted for differences in sampling frequencies among hunt seasons and diel periods. The top model in the central, coastal, and north regions included water depth, whereas the top model in the southwest region included water depth, vegetation height, and land cover. Parameter estimates and confidence intervals indicated that goose habitat use was higher at sites with >5.1 cm of water compared to dry sites or sites with <5.1 cm of water. In the southwest region, goose habitat use was highest in areas identified as other land cover (e.g., corn, cotton, rye, sugarcane) and lowest in open water. Although Louisiana has substantial anthropogenic food resources in the form of rice agriculture and abundant grazing opportunities afforded by mild winters, our results indicate that wet areas provide better habitat to greater white-fronted geese than dry areas. New agricultural flooding regimes in Louisiana could improve habitat quality and potentially mitigate some effects of the winter distribution shift.

Louisiana↗