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At least 1,135 records · Page 63Linked to original sources
USGS2008

EAARL coastal topography–Northeast Barrier Islands 2007: First surface

These remotely sensed, geographically referenced elevation measurements of Lidar-derived first surface (FS) topography were produced collaboratively by the U.S. Geological Survey (USGS), Florida Integrated Science Center (FISC), St. Petersburg, FL, and the National Aeronautics and Space Administration (NASA), Wallops Flight Facility, VA. This project provides highly detailed and accurate datasets of the northeast coastal barrier islands in New York and New Jersey, acquired April 29-30 and May 15-16, 2007. The datasets are made available for use as a management tool to research scientists and natural resource managers. An innovative airborne Lidar instrument originally developed at the NASA Wallops Flight Facility, and known as the Experimental Advanced Airborne Research Lidar (EAARL), was used during data acquisition. The EAARL system is a raster-scanning, waveform-resolving, green-wavelength (532-nanometer) Lidar designed to map near-shore bathymetry, topography, and vegetation structure simultaneously. The EAARL sensor suite includes the raster-scanning, water-penetrating full-waveform adaptive Lidar, a down-looking red-green-blue (RGB) digital camera, a high-resolution multi-spectral color infrared (CIR) camera, two precision dual-frequency kinematic carrier-phase GPS receivers, and an integrated miniature digital inertial measurement unit, which provide for submeter georeferencing of each laser sample. The nominal EAARL platform is a twin-engine Cessna 310 aircraft, but the instrument may be deployed on a range of light aircraft. A single pilot, a Lidar operator, and a data analyst constitute the crew for most survey operations. This sensor has the potential to make significant contributions in measuring sub-aerial and submarine coastal topography within cross-environmental surveys. Elevation measurements were collected over the survey area using the EAARL system, and the resulting data were then processed using the Airborne Lidar Processing System (ALPS), a custom-built processing system developed in a NASA-USGS collaboration. ALPS supports the exploration and processing of Lidar data in an interactive or batch mode. Modules for presurvey flight line definition, flight path plotting, Lidar raster and waveform investigation, and digital camera image playback have been developed. Processing algorithms have been developed to extract the range to the first and last significant return within each waveform. ALPS is routinely used to create maps that represent submerged or first surface topography. Specialized filtering algorithms have been implemented to determine the 'bare earth' under vegetation from a point cloud of last return elevations.

New York↗
USGS2008

EAARL coastal topography– Northeast barrier islands 2007: Bare earth

These remotely sensed, geographically referenced elevation measurements of Lidar-derived bare earth (BE) topography were produced collaboratively by the U.S. Geological Survey (USGS), Florida Integrated Science Center (FISC), St. Petersburg, FL, and the National Aeronautics and Space Administration (NASA), Wallops Flight Facility, VA. This project provides highly detailed and accurate datasets of the northeast coastal barrier islands in New York and New Jersey, acquired April 29-30 and May 15-16, 2007. The datasets are made available for use as a management tool to research scientists and natural resource managers. An innovative airborne Lidar instrument originally developed at the NASA Wallops Flight Facility, and known as the Experimental Advanced Airborne Research Lidar (EAARL), was used during data acquisition. The EAARL system is a raster-scanning, waveform-resolving, green-wavelength (532-nanometer) Lidar designed to map near-shore bathymetry, topography, and vegetation structure simultaneously. The EAARL sensor suite includes the raster-scanning, water-penetrating full-waveform adaptive Lidar, a down-looking red-green-blue (RGB) digital camera, a high-resolution multi-spectral color infrared (CIR) camera, two precision dual-frequency kinematic carrier-phase GPS receivers and an integrated miniature digital inertial measurement unit, which provide for submeter georeferencing of each laser sample. The nominal EAARL platform is a twin-engine Cessna 310 aircraft, but the instrument may be deployed on a range of light aircraft. A single pilot, a Lidar operator, and a data analyst constitute the crew for most survey operations. This sensor has the potential to make significant contributions in measuring sub-aerial and submarine coastal topography within cross-environmental surveys. Elevation measurements were collected over the survey area using the EAARL system, and the resulting data were then processed using the Airborne Lidar Processing System (ALPS), a custom-built processing system developed in a NASA-USGS collaboration. ALPS supports the exploration and processing of Lidar data in an interactive or batch mode. Modules for presurvey flight line definition, flight path plotting, Lidar raster and waveform investigation, and digital camera image playback have been developed. Processing algorithms have been developed to extract the range to the first and last significant return within each waveform. ALPS is routinely used to create maps that represent submerged or first surface topography. Specialized filtering algorithms have been implemented to determine the 'bare earth' under vegetation from a point cloud of last return elevations.

New York↗
USGS2004

Fort Collins Science Center

The U.S. Geological Survey's Fort Collins Science Center (FORT) is one of 17 USGS biological science centers nationwide. FORT conducts research and develops technical applications to assist land managers in understanding and managing biological resources, habitats, and ecosystems. Although the majority of FORT's activities are conducted within the 15-state Central Region of the USGS, many FORT projects are national or international in scope. FORT serves all Department of the Interior land management bureaus and other natural resource agencies. In addition, FORT scientists partner with DOI and other federal entities such as CDC, DOE, EPA, NASA, NIH, and USDA to share expertise and resources. FORT also partners with several universities and works cooperatively with states and nongovernmental organizations. Products and services include reports and publications, predictive models and software, maps and GIS products, and other technical assistance in the form of meetings, workshops, training, field visits, and needs assessments.

Fact Sheet↗
USGS2018

Quantifying uncertainty and tradeoffs in resilience assessments

Several frameworks have been developed to assess the resilience of social-ecological systems, but most require substantial data inputs, time, and technical expertise. Stakeholders and practitioners often lack the resources for such intensive efforts. Furthermore, most end with problem framing and fail to explicitly address trade-offs and uncertainty. To remedy this gap, we developed a rapid survey assessment that compares the relative resilience of social-ecological systems with respect to a number of resilience properties. This approach generates large amounts of information relative to stakeholder inputs. We targeted four stakeholder categories: government (policy, regulation, management), end users (farmers, ranchers, landowners, industry), agency/public science (research, university, extension), and NGOs (environmental, citizen, social justice) in four North American watersheds, to assess social-ecological resilience through surveys. Conceptually, social-ecological systems are comprised of components ranging from strictly human to strictly ecological, but that relate directly or indirectly to one another. They have soft boundaries and several important dimensions or axes that together describe the nature of social-ecological interactions, e.g., variability, diversity, modularity, slow variables, feedbacks, capital, innovation, redundancy, and ecosystem services. There is no absolute measure of resilience, so our design takes advantage of cross-watershed comparisons and therefore focuses on relative resilience. Our approach quantifies and compares the relative resilience across watershed systems and potential trade-offs among different aspects of the social-ecological system, e.g., between social, economic, and ecological contributions. This approach permits explicit assessment of several types of uncertainty (e.g., self-assigned uncertainty for stakeholders; uncertainty across respondents, watersheds, and subsystems), and subjectivity in perceptions of resilience among key actors and decision makers and provides an efficient way to develop the mental models that inform our stakeholders and stakeholder categories.

Ecology and Society↗
USGS1993

Managing biological diversity

Biological diversity is the variety of life and accompanying ecological processes (Off. Technol. Assess. 1987, Wilcove and Samson 1987, Keystone 1991). Conservation of biological diversity is a major environmental issue (Wilson 1988, Counc. Environ. Quality 1991). The health and future of the earth's ecological systems (Lubchenco et al. 1991), global climate change (Botkin 1990), and an ever-increasing rate in loss of species, communities, and ecological systems (Myers 1990) are among issues drawing biological diversity to the mainstream of conservation worldwide (Int. Union Conserv. Nat. and Nat. Resour. [IUCN] et al. 1991). The legal mandate for conserving biological diversity is now in place (Carlson 1988, Doremus 1991). More than 19 federal laws govern the use of biological resources in the United States (Rein 1991). The proposed National Biological Diversity Conservation and Environmental Research Act (H.R. 585 and S.58) notes the need for a national biological diversity policy, would create a national center for biological diversity research, and recommends a federal interagency strategy for ecosystem conservation. There are, however, hard choices ahead for the conservation of biological diversity, and biologists are grappling with how to set priorities in research and management (Roberts 1988). We sense disillusion among field biologists and managers relative to how to operationally approach the seemingly overwhelming charge of conserving biological diversity. Biologists also need to respond to critics like Hunt (1991) who suggest a tree farm has more biological diversity than an equal area of old-growth forest. At present, science has played only a minor role in the conservation of biological diversity (Weston 1992) with no unified approach available to evaluate strategies and programs that address the quality and quantity of biological diversity (Murphy 1990, Erwin 1992). Although actions to conserve biological diversity need to be clearly defined by viewing issues across biological, spatial, and temporal scales (Knopf and Smith 1992), natural resource managers find much conflicting information in the literature on strategies and programs for the conservation of biological diversity (Ehrlich 1992). Moreover, recommendations provided in much of the published information available for planning or decisions not only can be debated but may prove counterproductive if implemented. Current operational efforts beg for clearer focus on fundamental concepts central to daily decisions that impact native biological diversity. Recognizing that many biologists would provide different council and at the risk of oversimplification, we offer the following 4 topical issues as fundamental guidance to wise conservation action. These recommendations are based on our collective experiences working within conservation agencies since our original, collaborative essay (Samson and Knopf 1982). They are offered as initial, rather than authoritative, steps to better align research and management decisions with what we perceive as the critical issues in conserving biological diversity at the landscape and ecosystem levels of resolution.

Wildlife Society Bulletin↗
USGS2026

Colocating artificial intelligence data centers with energy infrastructure on Federal public lands—A science synthesis and spatial analysis to inform decision making

Executive Summary Artificial intelligence (AI) is rapidly transforming industries and economies, creating an urgent need to strategically plan for the energy and infrastructure required to support increasing AI use. U.S. Federal agencies and bureaus have been directed to explore ways to accelerate permitting, development, and deployment of energy resources and AI technologies, including encouraging the colocation of energy infrastructure and data centers. To inform these initiatives, this report synthesizes relevant scientific information and presents a spatial analysis of existing energy infrastructure and data centers on or near U.S. Federal public lands managed by the Bureau of Land Management (BLM). The purpose of this science synthesis and spatial analysis is to provide the BLM with foundational information for considering potential colocation of data centers with energy infrastructure on Federal public lands to support evidence-based decisions. Additionally, this report provides insight into current (2025) and potential future energy demands by providing projections of a range of potential future environmental conditions relevant to maintaining industry-recommended cooling temperature standards necessary for efficient data center operations. As a part of this effort, a rapid response literature review was conducted of the best available science on the topic of data center development and energy infrastructure in July–August 2025, supplemented by additional resources recommended by U.S. Federal agency and bureau subject matter experts (hereafter experts; including the U.S. Department of Energy National Laboratory of the Rockies) and peer reviewers. To better understand current conditions relevant to AI data center development, a spatial analysis was conducted across Alaska and 11 States in the Western United States, Arizona, California, Colorado, Idaho, Montana, Nevada, New Mexico, Oregon, Utah, Washington, and Wyoming, all of which contain extensive BLM-managed surface lands (hereafter referred to as “BLM lands”) that could be considered for the colocation of energy infrastructure and AI data centers. This effort identified BLM lands within 10 miles of existing transmission lines, consistent with methods used in previous BLM programmatic environmental impact statements. This report describes the types of data centers operating within the United States, which vary in ownership, size, technology, and proximity to end users. This report then outlines the primary considerations of data center development, including reliable energy supply, natural resources (such as water availability to support cooling requirements), and relevant policy and regulatory considerations. Energy supply considerations are pivotal for data center operation. Between 2014 and 2018, data centers in the United States accounted for nearly 2 percent of the Nation’s total electricity consumption, and data center energy consumption is projected to increase from 2 to 6.7–12 percent of total U.S. electricity use by 2028. These energy requirements necessitate careful consideration of energy supply when considering potentially suitable locations for data center development. Experts anticipate that an increase in renewable energy generation will likely support most potential future power demand needs, including for data centers, followed by increases in natural gas, nuclear, and geothermal energy production. Additional capacity in the form of battery storage will likely not generate electricity, but may improve the reliability and flexibility of supply, helping to ensure that growing data center loads can be met. However, the U.S. Department of Energy estimates that the United States will need, on average, 57 percent more energy transmission infrastructure by 2035 to account for the growing power demand introduced by development such as data centers. Cooling server equipment in data centers requires large amounts of electricity and water, and this demand can be exacerbated by hot and humid conditions. Energy efficient water-based cooling technologies may reduce electricity consumption onsite but require more water consumption. This additional water demand has the potential to increase water stress and competition with other users. As such, developing data centers will likely need a thorough assessment of current and potential future water availability, as well as consideration of how water demand may change across other sectors. Data center development involves policy and regulatory considerations, as projects must undergo environmental review and authorization processes that can take 18–24 months. Coordinating these environmental reviews and authorizations with other energy development projects, such as building new transmission lines, may cause additional delays. Recent efforts by the U.S. Department of Energy and U.S. Department of the Interior aim to expedite environmental reviews and authorizations and improve coordination across agencies. The spatial analysis identified 771 existing AI data centers and more than 3,300 power plants. The spatial analysis found that 6 percent of AI data centers and 22 percent of power plants in the Western United States were on or within 1 mile of BLM lands, and California had the largest number of facilities. Most existing AI data centers were near high-voltage transmission lines and close to power plants, supporting efficient energy delivery. More than 90,000,000 acres of BLM lands were within 10 miles of existing high-voltage transmission lines, representing 38 percent of BLM lands in the study area. Available transmission infrastructure and the overlap with BLM lands varied by State, and Alaska had limited overlap compared to the rest of the Western United States. To operate most efficiently, data center temperatures must be at or below 80.6 degrees Fahrenheit. This analysis of future temperature and precipitation projections indicated increasing cooling demands for data centers, particularly in Arizona, California, and Nevada, where rising temperatures are expected to increase energy and operational costs while potentially stressing current regional electrical grid infrastructure. This report highlights relevant energy supply, natural resources, and regulatory considerations for data center development on BLM lands. This report does not provide a comprehensive ecological, regulatory, land suitability, or permitting analysis. The factors described here are contextual considerations only and are not intended to identify, rank, quantify, or recommend optimal areas for data center colocation. This spatial analysis focused solely on energy considerations relevant to data centers and did not consider water availability, critical habitats, BLM National Conservation Lands, areas of cultural or historical significance, and other sensitive resources. These topics are recognized as critical but were not within the scope of this science synthesis and spatial analysis.

Scientific Investigations Report↗
USGS2023

Summary of the history and research of the U.S. Geological Survey gas hydrate properties laboratory in Menlo Park, California, active from 1993 to 2022

The U.S. Geological Survey (USGS) Clathrate Hydrate Properties Project, active from 1993 to 2022 in Menlo Park, California, stemmed from an earlier project on the properties of planetary ices supported by the National Aeronautics and Space Administration’s (NASA’s) Planetary Geology and Geophysics Program. We took a material science approach in both projects, emphasizing chemical purity of samples, having controlled grain size and grain texture, and having verified crystal structures and phase relations. A foundational contribution from our USGS Gas Hydrate Properties Laboratory (GHPL) was in demonstrating the ability to reproducibly create such pure clathrate hydrate samples for study. Clathrate sample synthesis was achieved by heating sieved and weighed pure granular water ice in the presence of cold clathrate-forming gas or liquid. During heating, the ice melts at the grain scale and reacts with the gas to form clathrate. The resulting material has the desired uniformity and purity, with known intergranular porosity; our subsequent measurements showed that these clathrates exhibited the established clathrate structures and phase relations. This novel synthesis method was successful in creating clathrates of pure methane, ethane, propane, carbon dioxide, and multi-component gases. By mixing sand or silt with granular ice, we were also able to make clathrate-sediment aggregates with controlled grain textures. This simple method, adopted by many others in the community, permitted us to measure the physical and chemical properties of well-characterized and well-crystallized clathrates and clathrate/sediment aggregates. At about the same time, we adapted conventional scanning electron microscopy to cryogenic conditions for analysis of grain-scale characteristics of clathrates made in the GHPL as well as those collected from nature by drill core. The uniformity and reproducibility of our samples also allowed us to investigate how clathrates respond to environmental changes in chemistry, temperature, and pressure: we measured chemical exchange rates with dissolved gas species—such as noble gases and chlorofluorocarbons—as well as rates of clathrate dissolution and decomposition. These advances include the first accurate mapping of the conditions that promote the remarkable process of “anomalous preservation” at room pressure, a metastability that offers potential application for low-cost and safe transportation of natural gas from gas fields far from pipelines. Another advancement stemming from the GHPL was the compaction of as-synthesized porous clathrates to nearly full density by applying external pressure using three different techniques. Compaction allows for high-accuracy measurements of many fundamental physical and chemical properties of these materials, such as elastic wavespeeds and moduli, complete thermal properties, decomposition rates, thermal expansion, and clathrate equations of state. These properties and others, in turn, have helped USGS scientists to interpret geophysical well logs and active geophysical surveys, as well as model the rates of gas production from hydrate deposits in nature. Studying this class of icy minerals that occur in abundance on Earth and in the outer solar system has been a fascinating laboratory journey. Here, we summarize the history and major findings of the USGS GHPL in Menlo Park, including both in-house research as well as findings from the synergistic collaborations with other agencies and institutes that were key to the success of our laboratory. The Menlo Park GHPL was more formally incorporated within the USGS Gas Hydrates Project, a collaboration among multiple USGS Science Centers, in the early 2000s under the leadership of Deborah Hutchinson, and now under the leadership of Carolyn Ruppel and Timothy Collett.

Open-File Report↗
USGS2006

Stable isotope compositions of serpentinite seamounts in the Mariana forearc: Serpentinization processes, fluid sources and sulfur metasomatism

The Mariana and Izu-Bonin arcs in the western Pacific are characterized by serpentinite seamounts in the forearc that provide unique windows into the mantle wedge. We present stable isotope (O, H, S, and C) data for serpentinites from Conical seamount in the Mariana forearc and S isotope data for Torishima seamount in the Izu-Bonin forearc in order to understand the compositions of fluids and temperatures of serpentinization in the mantle wedge, and to investigate the transport of sulfur from the slab to the mantle wedge. Six serpentine mineral separates have a restricted range of ??18O (6.5-8.5???). Antigorite separates have ??D values of -29.5??? to -45.5??? that reflect serpentinization within the mantle wedge whereas chrysotile has low ??D values (-51.8??? to -84.0???) as the result of re-equilibration with fluids at low temperatures. Fractionation of oxygen isotopes between serpentine and magnetite indicate serpentinization temperatures of 300-375 ??C. Two late cross-fiber chrysotile veins have higher ??18O values of 8.9??? to 10.8??? and formed at lower temperatures (as low as ???100 ??C). Aqueous fluids in equilibrium with serpentine at 300-375 ??C had ??18O = 6.5-9??? and ??D = -4??? to -26???, consistent with sediment dehydration reactions at temperatures <200 ??C in the subducting slab rather than a basaltic slab source. Three aragonite veins in metabasalt and siltstone clasts within the serpentinite flows have ??18O = 16.7-24.5???, consistent with the serpentinizing fluids at temperatures <250 ??C. ??13C values of 0.1-2.5??? suggest a source in subducting carbonate sediments. The ??34S values of sulfide in serpentinites on Conical Seamount (-6.7??? to 9.8???) result from metasomatism through variable reduction of aqueous sulfate (??34S = 14???) derived from slab sediments. Despite sulfur metasomatism, serpentinites have low sulfur contents (generally < 164 ppm) that reflect the highly depleted nature of the mantle wedge. The serpentinites are mostly enriched in 34S (median ??34Ssulfide = 4.5???), consistent with a 34S-enriched mantle wedge as inferred from arc lavas. ?? 2006 Elsevier B.V. All rights reserved.

Earth and Planetary Science Letters↗
USGS2018

Wildland–urban interface residents’ relationships with wildfire: Variation within and across communities

Social science offers rich descriptions of relationships between wildland–urban interface residents and wildfire, but syntheses across different contexts might gloss over important differences. We investigate the potential extent of such differences using data collected consistently in sixty-eight Colorado communities and hierarchical modeling. We find substantial variation across responses for all considered measures, much of which occurs at the community-level. Our results show that many aspects of relationships with wildfire meaningfully differ both within and across communities. Our analysis suggests that some wildfire social science results will be relatively consistent across communities, whereas others will not, and this study contributes evidence to broader efforts for understanding which is which. As such, it provides important guidance for transferring the lessons of wildfire social science studies across contexts, and for practitioners who seek to understand the breadth of viewpoints within the communities with which they work.

Colorado↗
USGS2014

Retirement investment theory explains patterns in songbird nest-site choice

When opposing evolutionary selection pressures act on a behavioural trait, the result is often stabilizing selection for an intermediate optimal phenotype, with deviations from the predicted optimum attributed to tracking a moving target, development of behavioural syndromes or shifts in riskiness over an individual's lifetime. We investigated nest-site choice by female golden-winged warblers, and the selection pressures acting on that choice by two fitness components, nest success and fledgling survival. We observed strong and consistent opposing selection pressures on nest-site choice for maximizing these two fitness components, and an abrupt, within-season switch in the fitness component birds prioritize via nest-site choice, dependent on the time remaining for additional nesting attempts. We found that females consistently deviated from the predicted optimal behaviour when choosing nest sites because they can make multiple attempts at one fitness component, nest success, but only one attempt at the subsequent component, fledgling survival. Our results demonstrate a unique natural strategy for balancing opposing selection pressures to maximize total fitness. This time-dependent switch from high to low risk tolerance in nest-site choice maximizes songbird fitness in the same way a well-timed switch in human investor risk tolerance can maximize one's nest egg at retirement. Our results also provide strong evidence for the adaptive nature of songbird nest-site choice, which we suggest has been elusive primarily due to a lack of consideration for fledgling survival.

Manitoba, Minnesota↗
USGS2025

Hybrid coral reef restoration can be a cost-effective nature-based solution to provide protection to vulnerable coastal populations

Coral reefs can mitigate flood damages by providing protection to tropical coastal communities whose populations are dense, growing fast, and have predominantly lower-middle income. This study provides the first fine-scale, regionally modeled valuations of how flood risk reductions associated with hybrid coral reef restoration could benefit people, property, and economic activity along Florida and Puerto Rico’s 1005 kilometers of reef-lined coasts. Restoration of up to 20% of the regions’ coral reefs could provide flood reduction benefits greater than costs. Reef habitats with the greatest benefits are shallow, nearshore, and fronting low-lying, vulnerable communities, which are often where reef impacts and loss are the greatest. Minorities, children, the elderly, and those below the poverty line could receive more than double the hazard risk reduction benefits of the overall population, demonstrating that reef restoration as a nature-based solution can have positive returns on investment economically and socially by providing protection to the most vulnerable people.

Florida↗
USGS2024

A regional synthesis of climate data to inform the 2025 State Wildlife Action Plans in the Northeast U.S.

The State Wildlife Action Plans (SWAPs) are proactive planning documents, known as “comprehensive wildlife conservation strategies,” that assess the health of each state’s wildlife and habitats, identify current management and conservation challenges, and outline needed actions to conserve natural resources over the long term. SWAPs are revised every 10 years, with the last revision in 2015 and the next revision anticipated in 2025. State managers have a long history of managing for threats such as land-use change, pollution, and harvest. However, they have expressed a lack of expertise and capacity to keep pace with the rapid advances in climate science and noted that much of the information available is not scaled to meet their needs; thus making the prospect of integrating climate information into SWAPs a daunting task. (Johnson, 2018; Yocum et al., 2021; Blandford, 2022). This report, led by the Northeast Climate Adaptation Science Center (NE CASC), directly addresses SWAP climate science data needs through a Northeast regional synthesis across four key areas of climate science: 1) observed and projected climate changes, 2) species responses to climate change, 3) climate vulnerabilities and risks, and 4) scale-specific adaptation strategies and actions. In addition, case studies of climate adaptation efforts and climate threat to-action narratives provide illustrative examples of how climate change frameworks and tools are being operationalized in decision-making processes related to Regional Species of Greatest Conservation Need (RSGCN) and their habitats across the region. Lists of recent climate resources were also synthesized into extensive data tables to provide SWAP writing teams with a comprehensive platform of information to support content development (AFWA 2022).

Connecticut, Delaware, Maine, Maryland, Massachuse↗
USGS2004

Science for the changing Great Basin

The U.S. Geological Survey (USGS), with its multidisciplinary structure and role as a federal science organization, is well suited to provide integrated science in the Great Basin of the western United States. A research strategy developed by the USGS and collaborating partners addresses critical management issues in the basin, including invasive species, status and trends of wildlife populations and communities, wildfire, global climate change, and riparian and wetland habitats. Information obtained through implementation of this strategy will be important for decision-making by natural-resource managers.

The Great Basin↗
USGS2011

National Climate Change and Wildlife Science Center project accomplishments: highlights

The National Climate Change and Wildlife Science Center (NCCWSC) has invested more than $20M since 2008 to put cutting-edge climate science research in the hands of resource managers across the Nation. With NCCWSC support, more than 25 cooperative research initiatives led by U.S. Geological Survey (USGS) researchers and technical staff are advancing our understanding of habitats and species to provide guidance to managers in the face of a changing climate. Projects focus on quantifying and predicting interactions between climate, habitats, species, and other natural resources such as water. Spatial scales of the projects range from the continent of North America, to a regional scale such as the Pacific Northwest United States, to a landscape scale such as the Florida Everglades. Time scales range from the outset of the 20th century to the end of the 21st century. Projects often lead to workshops, presentations, publications and the creation of new websites, computer models, and data visualization tools. Partnership-building is also a key focus of the NCCWSC-supported projects. New and on-going cooperative partnerships have been forged and strengthened with resource managers and scientists at Federal, tribal, state, local, academic, and non-governmental organizations. USGS scientists work closely with resource managers to produce timely and relevant results that can assist managers and policy makers in current resource management decisions. This fact sheet highlights accomplishments of five NCCWSC projects.

Fact Sheet↗
USGS2024

Abundance and distribution of white-tailed deer on First State National Historical Park and surrounding lands

We estimated both abundance and distribution of white-tailed deer ( Odocoileus virginianus ) on the Brandywine Valley unit of First State National Historical Park (FRST) and the Brandywine Creek State Park (BCSP) during 2020 and 2021 with two widely used field methods — a road-based count and a network of camera traps. We conducted 24 road-based counts, covering 260 km of roadway, and deployed up to 16 camera traps, processing over 82,000 images representing over 5,000 independent observations. In both years, we identified bucks based on their body and antler characteristics, tracking their movements between baited camera trap locations. We tested seven estimators commonly reported in the literature, comparing the relative merits for managers of small, protected natural areas like FRST. Deer densities estimated from conventional road-based distance sampling were approximately 10 deer/km 2 lower than densities estimated from camera-trapping surveys. We attribute the bias in roadbased distance sampling to the difficulty of recording the precise effort expended to obtain the counts. Modifying the distance sampling method addressed many of the issues associated with the conventional approach. Despite little substantive differences in land cover types between the two methods, a clear spatial segregation of male and female deer at camera trap locations could bias roadbased counts if the sexes are not encountered in proportion to their abundances. There was a distinct gradient in deer distribution across the study area, with higher proportions of deer recorded in camera traps at FRST than BCSP, which harvests 20–60 deer annually during a regulated, hunting season. The most reliable (i.e., low bias, acceptable precision) methods, Spatial Capture Recapture (SCR) and Density Surface Modeling (DSM), produced deer densities of approximately 50 deer/km 2 in each year — a number which is consistent with previous estimates for New Castle County, Delaware, and our experience in similar, unhunted natural areas. Across both FRST and BCSP, these densities translated into area-wide (~1000 ha) population sizes between 650–1000 deer, with about one-half to two-thirds comprising the FRST population. Density surface modeling of mapped locations of deer detected during surveys, combined with camera-trapping and a time-to-event data analysis might be the only practical means of reliably assessing white-tailed deer abundance in small (<2000 ha), protected natural areas like FRST. Most other approaches are either too time-consuming, require identification and tracking of individual deer, the use of bait, or require intervention by a subject-area expert.

Delaware, Pennsylvania↗
USGS2011

Multi-scale clustering of functional data with application to hydraulic gradients in wetlands

A new set of methods are developed to perform cluster analysis of functions, motivated by a data set consisting of hydraulic gradients at several locations distributed across a wetland complex. The methods build on previous work on clustering of functions, such as Tarpey and Kinateder (2003) and Hitchcock et al. (2007), but explore functions generated from an additive model decomposition (Wood, 2006) of the original time se- ries. Our decomposition targets two aspects of the series, using an adaptive smoother for the trend and circular spline for the diurnal variation in the series. Different measures for comparing locations are discussed, including a method for efficiently clustering time series that are of different lengths using a functional data approach. The complicated nature of these wetlands are highlighted by the shifting group memberships depending on which scale of variation and year of the study are considered.

Journal of Data Science↗
USGS2026

Monitoring for the future of Central Alaska streams

Streams are good indicators of change and the health of watersheds. By monitoring stream chemical composition and the kinds of life they support, we can learn about how they are being stressed (by activities such as mining or climate change) or recovering from a stress (after restoration efforts). But Central Alaska watersheds and the natural stream conditions they produce are diverse. From long-term monitoring, and repeat measurements, we can start to understand the related baselines and fine-tune our understanding of changes.

Alaska↗
USGS2022

Southeast Utah Group climate and drought adaptation report: Exposure and perennial grass sensitivity

National Park Service (NPS) managers face growing challenges resulting from the effects of climate change. In particular, as temperatures rise in coming decades, natural resource management in the western United States must cope with expectations for elevated severity and frequency of droughts. These challenges are particularly pronounced for vegetation managers in dryland environments. Developing adaptive strategies requires specific information about the expected magnitude of change in climate and drought conditions as well as insights into how those changes will affect important vegetation resources. This report describes research focused on Southeast Utah Group (SEUG) park units designed to provide information about exposure and sensitivity of perennial grasses to aridification. Analyses at larger regional scales are also reported for context and comparison. This report is a product of an ongoing climate adaptation collaboration between the U.S. Geological Survey (USGS), NPS, and Northern Arizona University. The study it summarizes contributes quantitative ingredients for vulnerability assessments that are needed in the Climate-Smart Conservation framework. As such, the results informed a series of climate adaptation workshops conducted between 2018 and 2021 for Colorado Plateau scientists and managers. This is a giant step forward in science-informed management. The information in this report can be used to craft management strategies that can be implemented at the right place and time for individual species of concern.

Colorado, Utah↗