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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↗

USGS2015

Effects of microhabitat and land use on stream salamander abundance in the southwest Virginia coalfields

Large-scale land uses such as residential wastewater discharge and coal mining practices, particularly surface coal extraction and associated valley fills, are of particular ecological concern in central Appalachia. Identification and quantification of both alterations across scales are a necessary first-step to mitigate negative consequences to biota. In central Appalachian headwater streams absent of fish, salamanders are the dominant, most abundant vertebrate predator providing a significant intermediate trophic role. Stream salamander species are considered to be sensitive to aquatic stressors and environmental alterations, and past research has shown linkages among microhabitat parameters, large-scale land use such as urbanization and logging with salamander abundances. However, little is known about these linkages in the coalfields of central Appalachia. In the summer of 2013, we visited 70 sites (sampled three times each) in the southwest Virginia coalfields to survey salamanders and quantify stream and riparian microhabitat parameters. Using an information-theoretic framework we compared the effects of microhabitat and large-scale land use on salamander abundances. Our findings indicate that dusky salamander (Desmognathus spp.) abundances are more correlated to microhabitat parameters such as canopy cover than to subwatershed land uses. Brook salamander (Eurycea spp.) abundances show strong negative associations to the suspended sediments and stream substrate embeddedness. Neither Desmognathus spp. nor Eurycea spp. abundances were influenced by water conductivity. These suggest protection or restoration of riparian habitats and erosion control is an important conservation component for maintaining stream salamanders in the mined landscapes of central Appalachia.

Virginia↗

USGS2018

Analysis of multi-decadal wetland changes, and cumulative impact of multiple storms 1984 to 2017

Land-cover classification analysis using Landsat satellite imagery acquired between 1984 and 2017 quantified short- (post-Hurricane Sandy) and long-term wetland-change trends along the Maryland and Virginia coasts between Metompkin Bay, VA and Ocean City, MD. Although there are limited options for upland migration of wetlands in the study area, regression analysis showed that wetland area increased slightly between 1984 and 2011, indicating that marsh aggradation rates were sufficient to maintain wetland elevation relative to mean sea level. Following Hurricane Irene (August 2011), the Halloween Nor’Easter (October 2011), and Hurricane Sandy (October 2012), wetland area decreased by more than 7 km 2 compared with average pre-storm extents. We assume that Hurricane Sandy had the greatest impact due to the size and intensity of the storm. However, the cumulative effects of multiple storms within a short time period likely contributed to the greater observed losses in coastal wetlands relative to earlier periods. Five years after Hurricane Sandy, wetland area had not significantly recovered, but more time may be necessary to assess if the observed wetland losses will persist or if new growth within flooded marsh areas will be sufficient for the wetlands to recover to pre-storm extents. Comparisons of long-term and storm-driven wetland changes can lead to improved accuracy of habitat vulnerability models and greater understanding of potential impacts of future storms and SLR to coastal wetlands.

Wetlands Ecology and Management↗

USGS2018

Multi-scale effects of land cover and urbanization on the habitat suitability of an endangered toad

Habitat degradation, entwined with land cover change, is a major driver of biodiversity loss. Effects of land cover change on species can be direct (when habitat is converted to alternative land cover types) or indirect (when land outside of the species habitat is altered). Hydrologic and ecological connections between terrestrial and aquatic systems are well understood, exemplifying how spatially disparate land cover conditions may influence aquatic habitats, but are rarely examined. We sought to quantify relative effects of land cover at two different but interacting scales on habitat suitability for the endangered arroyo toad ( Anaxyrus californicus ). Based on an existing distribution model for the arroyo toad and available land cover data, we estimated effects of land cover along streams and within entire watersheds on habitat suitability using structural equation modeling. Relationships between land cover and habitat suitability differed between scales, and broader, watershed-scale conditions influenced land cover along the embedded stream networks. We found anthropogenic development and forest cover at the watershed-scale negatively impacted habitat suitability, but development along stream networks was positively associated with suitability. The positive association between development along streams and habitat suitability may be attributable to increased spatial heterogeneity along urbanized streams, or related factors including policies designed to conserve riparian habitats amidst development. These findings show arroyo toad habitat is influenced by land cover across multiple scales, and can inform conservation of the species. Furthermore, our methodology can help elucidate similar dynamics with other taxa, particularly those reliant on both terrestrial and aquatic environments.

California↗

USGS2014

Environmental impacts of utility-scale solar energy

Renewable energy is a promising alternative to fossil fuel-based energy, but its development can require a complex set of environmental tradeoffs. A recent increase in solar energy systems, especially large, centralized installations, underscores the urgency of understanding their environmental interactions. Synthesizing literature across numerous disciplines, we review direct and indirect environmental impacts – both beneficial and adverse – of utility-scale solar energy (USSE) development, including impacts on biodiversity, land-use and land-cover change, soils, water resources, and human health. Additionally, we review feedbacks between USSE infrastructure and land-atmosphere interactions and the potential for USSE systems to mitigate climate change. Several characteristics and development strategies of USSE systems have low environmental impacts relative to other energy systems, including other renewables. We show opportunities to increase USSE environmental co-benefits, the permitting and regulatory constraints and opportunities of USSE, and highlight future research directions to better understand the nexus between USSE and the environment. Increasing the environmental compatibility of USSE systems will maximize the efficacy of this key renewable energy source in mitigating climatic and global environmental change.

Renewable and Sustainable Energy Reviews↗

USGS2000

The role of landscape and habitat characteristics in limiting abundance of grassland nesting songbirds in an urban open space

We examine the relationships between abundance of grassland nesting songbirds observed in the Boulder Open Space, CO, USA and parameters that described landscape and habitat characteristics, in order to provide information for Boulder Open Space planners and managers. Data sets included bird abundance and plant species composition, collected during three breeding seasons (1994–1996), and landscape composition and configuration measures from a satellite image-derived land-cover map. We used regression quantiles to estimate the limitations imposed on bird abundance by urban encroachment and decreasing areas of grassland cover-types on the landscape, and habitat characteristics within 200 m diameter sample plots. After accounting for the effect of landscape grassland composition on four species (Western Meadowlark ( Sturnella neglecta ), Vesper Sparrow ( Pooecetes gramineus ), Horned Lark ( Eremophila alpestris ), and Grasshopper Sparrow ( Ammodramus savannarum )), change in abundance with proportion of urban area in the landscape was consistent with the pattern expected for limiting factors that were the active constraint at some times and places. Area of preferred grassland cover-types on the landscape was important for all species, and this remained the case when habitat variables were included in combined landscape–habitat models, with one exception (Western Meadowlark). Analysis of habitat variables enabled identification of important features at the local scale (e.g. shale plant communities in Lark Sparrow ( Chondestes grammacus ) habitat) that were indistinguishable using landscape data alone. Consideration of changes in the landscape due to urbanization and loss of grassland habitat are crucial for open space planning, and habitat features associated with localized and clumped bird species distributions provide important additional information. Widening the management focus to include areas that are not part of the open space system will facilitate a more complete understanding of potential limiting factor processes.

Landscape and Urban Planning↗

USGS2023

Vulnerability of estuarine systems in the contiguous United States to water quality change under future climate and land-use

Changes in climate and land-use and land-cover (LULC) are expected to influence surface water runoff and nutrient characteristics of estuarine watersheds, but the extent to which estuaries are vulnerable to altered nutrient loading under future conditions is poorly understood. The present work aims to address this gap through the development of a new vulnerability assessment framework that accounts for (a) estuarine exposure to projected changes in total nitrogen (TN) and total phosphorus (TP) loads as a function of LULC and climate change under several scenarios, (b) sensitivity, and (c) adaptive capacity. The framework was applied to 112 estuaries and their contributing watersheds across the contiguous U.S., specifically to look at regional variability in estuarine vulnerability to nutrient loading. Study findings revealed that the largest increases in estuarine nutrient loads are expected in the North and South Atlantic regions and eastern Gulf of Mexico, while the lowest increases are expected in the North and South Pacific regions and the western Gulf of Mexico. However, the North Atlantic and the South Pacific had the highest adaptive capacity, which could potentially counteract the effects of LULC and climate change on nutrient loads. Strong variation in predicted estuarine nutrient loads was observed as a function of climate model projections, while projected LULC changes were more consistently associated with elevated loads. Our findings illustrate the benefits of integrating natural and socio-ecological factors to identify opportunities to develop adaptation plans and policies to mitigate ecological degradation in vitally important estuaries.

Earth's Future↗

USGS2025

Practitioners’ perceived risks to biodiversity from renewable energy expansion through 2050

Large-scale (e.g., > 1 megawatt capacity) wind and solar energy (hereafter, LSWS) developments are increasing to aid decarbonization. However, LSWS can also negatively affect biodiversity. Planners and other interested parties’ perceptions about the impact of LSWS on biodiversity will thus affect how trade-offs are managed during planning and buildout. We present a survey of professionals (n=116) working at the intersection of LSWS and biodiversity protection across the United States concerning: (1) perceived environmental impacts from LSWS expansion; and (2) how these impacts compare to other land-use and land-cover change drivers. We find that practitioners perceive LSWS to impact biodiversity negatively but less so than other land-cover change drivers, including fossil fuels and agriculture. This highlights the need for increased attention to the role of practitioners in advancing renewable energy and biodiversity conservation.

Humanities and Social Sciences Communications↗

USGS2022

Wind turbine wakes can impact down-wind vegetation greenness

Global wind energy has expanded 5-fold since 2010 and is predicted to expand another 8–10-fold over the next 30 years. Wakes generated by wind turbines can alter downwind microclimates and potentially downwind vegetation. However, the design of past studies has made it difficult to isolate the impact of wake effects on vegetation from land cover change. We used hourly wind data to model wake and non-wake zones around 17 wind facilities across the U.S. and compared remotely-sensed vegetation greenness in wake and non-wake zones before and after construction. We located sampling sites only in the dominant vegetation type and in areas that were not disturbed before or after construction. We found evidence for wake effects on vegetation greenness at 10 of 17 facilities for portions of, or the entire growing season. Evidence included statistical significance in Before After Control Impact statistical models, differences >3% between expected and observed values of vegetation greenness, and consistent spatial patterns of anomalies in vegetation greenness relative to turbine locations and wind direction. Wakes induced both increases and decreases in vegetation greenness, which may be difficult to predict prior to construction. The magnitude of wake effects depended primarily on precipitation and to a lesser degree aridity. Wake effects did not show trends over time following construction, suggesting the changes impact vegetation greenness within a growing season, but do not accrue over years. Even small changes in vegetation greenness, similar to those found in this study, have been seen to affect higher trophic levels. Given the rapid global growth of wind energy, and the importance of vegetation condition for agriculture, grazing, wildlife, and carbon storage, understanding how wakes from wind turbines impact vegetation is essential to exploit or ameliorate these effects.

Environmental Research Letters↗

USGS2017

Grand challenges in understanding the interplay of climate and land changes

Half of Earth’s land surface has been altered by human activities, creating various consequences on the climate and weather systems at local to global scales, which in turn affect a myriad of land surface processes and the adaptation behaviors. This study reviews the status and major knowledge gaps in the interactions of land and atmospheric changes and present 11 grand challenge areas for the scientific research and adaptation community in the coming decade. These land-cover and land-use change (LCLUC)-related areas include 1) impacts on weather and climate, 2) carbon and other biogeochemical cycles, 3) biospheric emissions, 4) the water cycle, 5) agriculture, 6) urbanization, 7) acclimation of biogeochemical processes to climate change, 8) plant migration, 9) land-use projections, 10) model and data uncertainties, and, finally, 11) adaptation strategies. Numerous studies have demonstrated the effects of LCLUC on local to global climate and weather systems, but these putative effects vary greatly in magnitude and even sign across space, time, and scale and thus remain highly uncertain. At the same time, many challenges exist toward improved understanding of the consequences of atmospheric and climate change on land process dynamics and services. Future effort must improve the understanding of the scale-dependent, multifaceted perturbations and feedbacks between land and climate changes in both reality and models. To this end, one critical cross-disciplinary need is to systematically quantify and better understand measurement and model uncertainties. Finally, LCLUC mitigation and adaptation assessments must be strengthened to identify implementation barriers, evaluate and prioritize opportunities, and examine how decision-making processes work in specific contexts.

Earth Interactions↗

USGS2015

Wyoming greater sage-grouse habitat prioritization: A collection of multi-scale seasonal models and geographic information systems land management tools

With rapidly changing landscape conditions within Wyoming and the potential effects of landscape changes on sage-grouse habitat, land managers and conservation planners, among others, need procedures to assess the location and juxtaposition of important habitats, land-cover, and land-use patterns to balance wildlife requirements with multiple human land uses. Biologists frequently develop habitat-selection studies to identify prioritization efforts for species of conservation concern to increase understanding and help guide habitat-conservation efforts. Recently, the authors undertook a large-scale collaborative effort that developed habitat-selection models for Greater Sage-grouse ( Centrocercus urophasianus ) across large landscapes in Wyoming, USA and for multiple life-stages (nesting, late brood-rearing, and winter). We developed these habitat models using resource selection functions, based upon sage-grouse telemetry data collected for localized studies and within each life-stage. The models allowed us to characterize and spatially predict seasonal sage-grouse habitat use in Wyoming. Due to the quantity of models, the diversity of model predictors (in the form of geographic information system data) produced by analyses, and the variety of potential applications for these data, we present here a resource that complements our published modeling effort, which will further support land managers. We deliver all products described herein as online geographic information system data for visualization and downloading. We outline the data properties for each model and their data inputs, describe the process of selecting appropriate data products for multifarious applications, describe all data products and software, provide newly derived model composites, and discuss how land managers may use the models to inform future sage-grouse studies and potentially refine conservation efforts. The models, software tools, and associated opportunities for novel applications of these products should provide a suite of additional, but not exclusive, tools for assessing Wyoming Greater Sage-grouse habitats, which land managers, conservationists, and scientists can apply to myriad applications.

Wyoming↗

USGS2007

Landsat Data Continuity Mission

The Landsat Data Continuity Mission (LDCM) is a partnership between the National Aeronautics and Space Administration (NASA) and the U.S. Geological Survey (USGS) to place the next Landsat satellite in orbit by late 2012. The Landsat era that began in 1972 will become a nearly 45-year global land record with the successful launch and operation of the LDCM. The LDCM will continue the acquisition, archival, and distribution of multispectral imagery affording global, synoptic, and repetitive coverage of the Earth's land surfaces at a scale where natural and human-induced changes can be detected, differentiated, characterized, and monitored over time. The mission objectives of the LDCM are to (1) collect and archive medium resolution (circa 30-m spatial resolution) multispectral image data affording seasonal coverage of the global landmasses for a period of no less than 5 years; (2) ensure that LDCM data are sufficiently consistent with data from the earlier Landsat missions, in terms of acquisition geometry, calibration, coverage characteristics, spectral characteristics, output product quality, and data availability to permit studies of land-cover and land-use change over time; and (3) distribute LDCM data products to the general public on a nondiscriminatory basis and at a price no greater than the incremental cost of fulfilling a user request. Distribution of LDCM data over the Internet at no cost to the user is currently planned.

Fact Sheet↗