Search NASA⌕ Search

SEARCH · Search NASA

Results for “Wildlife”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 19 records
All sourcesNASA NTRSDOE OSTI
NASA NTRS2024

Jefferson County Ecological Conservation: Quantifying the Effects of Hydrologic Restoration in the Camas National Wildlife Refuge and Mud Lake Wildlife Management Area

Wetlands in the Camas National Wildlife Refuge and Mud Lake Wildlife Management Area, a rare landscape feature in the Intermountain West, are crucial for migratory birds along the Pacific Flyway, yet these wetlands have experienced a noticeable decline in extent and inundation over the last 40+ years. Partners at the U.S. Fish and Wildlife Service and Idaho Department of Fish and Game have ongoing restoration efforts that are yet to be quantified. To assist these partners, we used NASA Earth observations to quantify change in wetland extent and determine if the restoration projects met the intended impact. The QA_PIXEL band from Landsat 5 Thematic Mapper (TM) and Landsat 8 Operational Land Imager (OLI) was used to identify water. Landsat 8 OLI imagery was also used for classifying landcover in ArcGIS Pro for 2016 and 2020 and to forecast landcover in 2060 using TerrSet’s Land Change Modeler. We also compared lidar data from 2011 and 2019 to detect changes in vegetation height, ground elevation, and surface water levels, and Sentinel-2 Multispectral Instrument (MSI) imagery to detect changes in vegetation health. Classification results indicated overall accuracies over 84% and Kappa indices above 0.80, well surpassing random classification performance. From 2016 to 2020 our classifications showed an 825 acre increase in wetland extent, and our forecasted 2060 model showed a 2795 acre decrease. Combining our partners’ knowledge of the area with our analyses, we created a remote sensing workflow to enhance future monitoring and decision-making. This study demonstrated the feasibility of NASA Earth observations in quantifying wetlands, informing restoration projects, and supporting avian conservation.

Cassidy Bromka↗
NASA NTRS1989

Review of wildlife resources of Vandenberg Air Force Base, California

Wildlife resources are reviewed for purposes of developing a Base Biological Monitoring Program (BMP) for Vandenberg Air Force Base (VAFB) in Santa Barbara County, California. The review and recommendations were prepared by review of applicable scientific literature and environmental documents for VAFB, discussing information needs with natural resource management professionals at VAFB, and observations of base field conditions. This process found that there are 29 federally listed vertebrates (endangered, threatened, or Category 2) that occur or may occur in the vicinity of VAFB. There are also 63 other state listed or regionally declining species that may occur in the vicinity of VAFB. Habitats of VAFB represent a very valuable environmental resource for rare and declining wildlife in California. However, little information is available on VAFB wildlife resources other than lists of species that occur or are expected to occur. Recommendations are presented to initiate a long-term wildlife monitoring program at VAFB to provide information for environmental impact assessment and wise land use planning.

Breininger, David R.↗
NASA NTRSDate not supplied

Next-generation wildlife tracking devices and integrated sensors for measuring species-environment interactions and advancing conservation

Global land use and climate change have magnified the importance of collecting accurate animal movement and environmental data to improve our ability to model species interactions with the environment and promote effective conservation. Advanced animal tracking devices that couple cutting-edge technologies with our expanding need for ecological information is critical. In addition to further optimizing device size to monitor small, sensitive species, new paradigms for collecting, storing, and transmitting data about animals and their environments will propel wildlife tracking devices forward. Advanced telemetry capabilities will increase our ability to pair location and sensor data from tagged wildlife with remote sensing data. The USGS Western Ecological Research Center, NASA Ames Research Center, and collaborators have been developing new wildlife tracking devices and integrated environmental sensors to address these challenges. We describe a new, miniaturized solar GPS-enabled Globalstar satellite transmitter with accelerometer capability that is 20% lighter and 25% less expensive than existing commercially available tags. We also introduce a novel peer-to-peer, solar-powered network tag that uses long-range, low-power, wireless platform technology. Concurrently, we began adapting a carbon nanotube (CNT) sensor to detect dimethyl sulfide (DMS), a trace gas relevant to marine ecology and climate studies. CNT sensors offer a small, lightweight, and low-power technology that can detect changes in resistance across carbon nanotubes coated with adsorbent selected to specifically bind with a variety of reactive trace gasses. We flew a prototype sensor in a small UAS and sampled an apparent increase in DMS concentration consistent with a well-defined marine frontal boundary. Currently we are integrating project components to create a hybridized architecture of networked peer-to-peer and satellite tags with integrated CNT and additional on-board and remote sensors to advance animal tracking and to provide information for next generation wildlife conservation.

Ian G. Brosnan↗
NASA NTRSDate not supplied

Utilizing Earth Observations to Understand Landscape Patterns and Assist in Wildlife Management in Iona National Park, Angola

Following the end of the Angolan Civil War (1975-2002), human habitation in Iona National Park has grown exponentially, as has the livestock population. An ongoing drought beginning in 2017 has brought people, livestock, and wildlife into increasing competition for resources within the park. This study used Earth observation data, primarily Landsat and Sentinel imagery, to examine landscape trends to improve wildlife preservation approaches in Iona National Park, Angola. In collaboration with the NGO African Parks, we developed a robust land use and land cover (LULC) classification model using remote sensing data to augment sparse ground-based data in this arid land region. We used Google Earth Engine and a random forest classifier to map vegetation types, water bodies, and potential wildlife habitats. This analysis resulted in a high spatial resolution LULC time-series between 1984-2023, highlighting critical periods of socioecological change over the past 40 years. These results increased the partner’s ability to make scientifically grounded decisions about resource allocation and conservation priorities. This analysis supports the feasibility of applying remote sensing techniques coupled with machine learning models in dry regions, where standard survey methods are frequently limited by accessibility and resource availability. However, we identified limitations in ground-truth data and the difficulty of recognizing certain vegetation types in arid areas. Despite these limitations, the study demonstrated Earth observations' ability to transform wildlife management techniques in distant and data-scarce locations, providing a reproducible foundation for similar ecosystems around the world.

Emmanuel Aklie↗
NASA NTRS2016

Seasonal Variation of Total Mercury Burden in the American Alligator (Alligator Mississippiensis) at Merritt Island National Wildlife Refuge (MINWR), Florida

Seasonal variation of mercury (Hg) is not well studied in free-ranging wildlife. Atmospheric deposition patterns of Hg have been studied in detail and have been modeled for both global and specific locations with great accuracy and correlates to environment impact. However, monitoring these trends in wildlife is complicated due to local environmental parameters (e.g., rainfall, humidity, pH, bacterial composition) that can affect the transformation of atmospheric Hg to the biologically available forms. Here, we utilized an abundant and healthy population of American alligators (Alligator mississippiensis) at Merritt Island National Wildlife Refuge (MINWR), FL, and assessed Hg burden in whole blood samples over a span of 7 years (2007 2014; n 174) in an effort to assess seasonal variation of total [Hg]. While the majority of this population is assumed healthy, 18 individuals with low body mass indices (BMI, defined in this study) were captured throughout the 7 year sampling period. These individual alligators exhibited [Hg] that were not consistent with the observed overall seasonal [Hg] variation, and were statistically different from the healthy population of alligators. The alligators with low BMI had elevated concentrations of Hg compared to their age/sex/season matched counterparts with normal BMI. Statistically significant differences were found between the winter and spring seasons for animals with normal BMI. The data in this report supports the conclusion that organismal total [Hg] do fluctuate directly with seasonal deposition rates as well as other seasonal environmental parameters, such as average rainfall and prevailing wind direction. This study highlights the unique environment of MINWR to permit annual assessment of apex predators, such as the American alligator, to determine detailed environmental impact of contaminants of concern.

Hg↗
NASA NTRS2019

Changes in Vegetation Cover of the Arctic National Wildlife Refuge Estimated from MODIS Greenness Trends, 2000 to 2018

The Arctic National Wildlife Refuge (ANWR) was established in 1980 and covers 19 million acres (77,000 km2) in northeast Alaska. Wildlife habitats in the ANWR are vulnerable to long-lasting effects from any disturbance, in part because short growing seasons in the arctic provide limited time for species to recover. Trends and transitions in the growing season MODerate resolution Imaging Spectroradiometer (MODIS) Normalized Difference Vegetation Index (NDVI) time-series at 250-m resolution were analyzed for the period from 2000 to 2018 to understand recent patterns of vegetation change in all ecoregions of the ANWR. Statistical analysis of changes in each MODIS pixel NDVI time series was conducted using the "Breaks for Additive Seasonal and Trend" method (BFAST) to map regional change rates. Results suggested that most negative NDVI anomalies in the tundra-covered river drainages of the Brooks Range Mountains and coastal plain have been associated with early spring thawing and elevated levels of surface moisture in low elevation drainages of the northern ANWR ecoregions.

Arctic National Wildlife Refuge↗
NASA NTRS1974

The economic value of remote sensing of earth resources from space: An ERTS overview and the value of continuity of service. Volume 4: Forestry, wildlife and rangeland

The economic value of ERS information in the resource management area of extensive use of living resources, forestry, wildlife, and rangeland, is determined. Timber and forage resources are quantitatively evaluated. It is shown that these resources have economic value in the tens of billions of dollars, but the economic benefits of improved management of the forests and rangelands are not limited to efficiency in the production of these commercial resources. Multiple-use values including watershed, wildlife, and recreation are also involved.

Andrews, J.↗
NASA NTRS1979

Wildlife monitoring program plan

A plan for integrating the various requirements for wildlife monitoring with modern aerospace technology is presented. This plan is responsive to user needs, recognizes legal requirements, and is based on an evolutionary growth from domestic animals and larger animals to smaller, more scarce and remote species. The basis for animal study selection was made from the 1973 Santa Cruz Summer Study on Wildlife Monitoring. As techniques are developed the monitoring and management tasks will be interfaced with and eventually operated by the user agencies. Field efforts, aircraft and satellites, will be supplemented by laboratory investigations. Sixty percent of the effort will be in hardware research and development (satellite technology, microminiaturization) and the rest for gathering and interpreting data.

Sebesta, P.↗
NASA NTRS1982

Mapping of wildlife habitat in Farmington Bay, Utah

Mapping was accomplished through the interpretation of high-altitude color infrared photography. The feasibility of utilizing LANDSAT digital data to augment the analysis was explored; complex patterns of wildlife habitat and confusion of spectral classes resulted in the decision to make limited use of LANDSAT data in the analysis. The final product is a map which delineates wildlife habitat at a scale of 1:24,000. The map is registered to and printed on a screened U.S.G.S. quadrangle base map. Screened delineations of shoreline contours, mapped from a previous study, are also shown on the map. Intensive field checking of the map was accomplished for the Farmington Bay Waterfowl Management Area in August 1981; other areas on the map received only spot field checking.

Jaynes, R. A.↗
NASA NTRS1982

Integration of Fish and Wildlife Data with Geobased and Remotely Sensed Land Use/land Cover Data: a Demonstration Using Sites in Pennsylvania

The U.S. Fish and Wildlife Service developed a statewide fish and wildlife data base for the Pennsylvania Game Commission that includes 125 categories of information on each of the 844 species. This species data base is integrated with geobased and remotely-sensed land use/land cover data from two sites in Pennsylvania. One site is an energy development project; the other is a high-energy use area. Analyses using the combined animal and land use data bases can be demonstrated for a variety of land use/land cover types at both sites. The ability to make "what if" analysis prior to project implementation is presented.

Cushwa, C. T.↗
NASA NTRS1994

Endangered and potentially endangered wildlife on John F. Kennedy Space Center and faunal integrity as a goal for maintaining biological diversity

Buffer zones for space operations provide for a wildlife diversity unsurpassed among most federal facilities in the continental U.S. demonstrating the coexistence possible with one of man's greatest technological achievements. This document ranks 119 resident or migratory wildlife species that are endangered or declining. The ranking system herein was based on species' vulnerability to extinction and the relevance of Kennedy Space Center (KSC) for maintaining populations in the U.S. and Florida. One amphibian, 19 reptiles, 80 birds, and 19 mammals were considered endangered or declining. KSC is an integral area for regional species diversity being the focus of the Merritt Island/Cape Canaveral/Turnbull Ecosystem which is part of the Indian River Lagoon watershed, an estuary of national significance. Many species that use this system also use the nearby St. Johns River Basin ecosystem. These two ecosystems are biological corridors between temperate Carolinian and tropical/subtropical Caribbean biotic provinces. Threats to biological diversity on KSC were also reviewed. Traditional environmental assessments, resulting from environmental regulation guidelines, focus on environmental contaminants and habitat lost due to construction. However, this review suggested that small population sizes, isolation of populations, ecosystem and habitat fragmentation, road mortality, and other edge effects may represent more critical threats to biological diversity than the traditional topics.

Breininger, David R.↗
NASA NTRS1995

Geographic information analysis: An ecological approach for the management of wildlife on the forest landscape

This document is a summary of the project funded by NAGw-1460 as part of the Earth Observation Commericalization/Applications Program (EOCAP) directed by NASA's Earth Science and Applications Division. The goal was to work with several agencies to focus on forest structure and landscape characterizations for wildlife habitat applications. New analysis techniques were used in remote sensing and landscape ecology with geographic information systems (GIS). The development of GIS and the emergence of the discipline of landscape ecology provided us with an opportunity to study forest and wildlife habitat resources from a new perspective. New techniques were developed to measure forest structure across scales from the canopy to the regional level. This paper describes the project team, technical advances, and technology adoption process that was used. Reprints of related refereed journal articles are in the Appendix.

Ripple, William J.↗
NASA NTRS2017

The Don Edwards San Francisco Bay National Wildlife Refuge: A Natural Laboratory for Federal Agencies and Partners

The Don Edwards San Francisco Bay National Wildlife Refuge encompasses a rich mosaic of habitats and is a fecund and convenient field site for Earth science research, comprised of tidal salt marsh, open ponds, shallow water, mudflat habitat and encompassing a variety of tide, salinity, elevation, slope, and other conditions. Proximity to the NASA Ames Research Center and overlap with the center's UAS (unmanned aircraft systems) test area presents the opportunity to create a unique natural laboratory that can incubate and support a variety of research and benefit the Refuge in monitoring wildlife changes and habitat evolution over time.

Unmanned Airborne Vehicle↗
NASA NTRS2021

Louisiana Water Resources: Using NASA Earth Observations to Monitor Historical Changes in the Extension of Seagrass Meadows in the Breton National Wildlife Refuge in Louisiana

The barrier islands of Louisiana’s Breton National Wildlife Refuge (BNWR) are disappearing due to sea level rise, extreme hurricanes, sediment starvation, and the Deepwater Horizon oil spill. This decline in land area has damaged important bird habitat and reduced the islands’ ability to protect coastal Louisiana from storm surges. The persistence of the islands is synergetic to that of the surrounding seagrass beds; seagrass binds together land, protecting the islands from erosion, and the loss of land exposes the seagrass and accelerates its decline. Furthermore, seagrass is independently important, absorbing excess nutrients and providing habitat for marine ecosystems. Here we present the Tool for Coastal Remote Ecological Observations in Louisiana (Tool CREOL), a Google Earth Engine Tool built to easily access data from Landsat 5 TM, Landsat 7 ETM+, Landsat 8 OLI, and Aqua and Terra MODIS. We show, using time series and maps generated using the tool, how land area and seagrass have responded to destructive events from the past 36 years (1984-2021). In only 7 years, Hurricane Georges (1998), Ivan (2004), and Katrina (2005) reduced land area by approximately 85%, accompanied by a major decline in seagrass extent. Tool CREOL will have strategic utility in planning upcoming restoration and revegetation efforts planned by Louisiana’s Coastal Protection and Restoration Authority in the Breton National Wildlife Refuge and will provide up-to-date monitoring of the results of that project. The tool serves as a basic model which can be adapted to study similar coastal regions in the world.

Mariam Moeen↗
NASA NTRS2023

Southern Idaho Ecological Conservation: Investigating the Impact of Targeted Grazing to Improve Wetland Habitat in the Sterling Wildlife Management Area

Wetland ecosystems are vital for biodiversity conservation and ecosystem services. The Sterling Wildlife Management Area in Bingham County, Idaho, has management concerns about decadent and accumulated vegetation growth encroaching on wetland habitat, which presents challenges for wildlife, decreases biodiversity, and limits public access. Targeted grazing has been proposed as a sustainable alternative to chemical herbicides or burning. Land managers introduced targeted cattle grazing in January 2021 to reduce biomass. NASA DEVELOP partnered with the Idaho Department of Fish and Game to determine the impact of grazing using NASA Earth observations from Landsat 8 Operational Land Imager (OLI) in Google Earth Engine (GEE). Images were processed with TerrSet’s Land Change Modeler and ArcGIS Pro’s Change Detection Wizard to understand land changes following grazing. A Normalized Difference Vegetation Index (NDVI) analysis was performed to assess impacts on vegetation productivity and compare variance in biomass before and after grazing. A Normalized Difference Water Index (NDWI) was used to compare changes in the wetland and its vegetation content to evaluate the suitability of the area for migratory birds post-grazing. Results showed a decrease in the vegetation index and an increase in the water index postgrazing. The DEVELOP team’s analysis suggests that grazing helps break down thick, senesced vegetation and increase soil moisture. Providing a workflow model will aid partners in continuing to monitor this management area and other management areas across the state.

change detection↗
NASA NTRS2023

Evaluating MODIS Snow Products Using an Extensive Wildlife Camera Network

Snow covers a maximum of 47 million km 2 of Earth's northern hemisphere each winter and is an important component of the planet's energy balance, hydrology cycles, and ecosystems. Monitoring regional and global snow cover has increased in urgency in recent years due to warming temperatures and declines in snow cover extent. Optical satellite instruments provide large-scale observations of snow cover, but cloud cover and dense forest canopy can reduce accuracy in mapping snow cover. Remote camera networks deployed for wildlife monitoring operate below cloud cover and in forests, representing a virtually untapped source of snow cover observations to supplement satellite observations. Using images from 1,181 wildlife cameras deployed by the Norwegian Institute for Nature Research (NINA), we compared snow cover extracted from camera images to Moderate Resolution Imaging Spectroradiometer (MODIS) snow cover products during winter months of 2018–2020. Ordinal snow classifications (scale = 0–4) from cameras were closely related to normalized difference snow index (NDSI) values from the MODIS Terra Snow Cover Daily L3 Global 500m (MOD10A1) Collection 6 product (R 2 = 0.70). Tree canopy cover, the normalized difference vegetation index (NDVI), and image color mode influenced agreement between camera images and MOD10A1 NDSI values. For MOD10A1F, MOD10A1's corresponding cloud-gap filled product, agreement with cloud-gap filled values decreased from 78.5% to 56.4% in the first three days of cloudy periods and stabilized thereafter. Using our camera data as validation, we derived a threshold to create daily binary maps of snow cover from the MOD10A1 product. The threshold corresponding to snow presence was an NDSI value of 40.50, which closely matched a previously defined global binary threshold of 40 using the MOD10A2 8-day product. These analyses demonstrate the utility of camera trap networks for validation of snow cover products from satellite remote sensing, as well as their potential to identify sources of inaccuracy.

Validation↗