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At least 19 recordsLinked to original sources
USGS2017

Translating statistical species-habitat models to interactive decision support tools

Understanding species-habitat relationships is vital to successful conservation, but the tools used to communicate species-habitat relationships are often poorly suited to the information needs of conservation practitioners. Here we present a novel method for translating a statistical species-habitat model, a regression analysis relating ring-necked pheasant abundance to landcover, into an interactive online tool. The Pheasant Habitat Simulator combines the analytical power of the R programming environment with the user-friendly Shiny web interface to create an online platform in which wildlife professionals can explore the effects of variation in local landcover on relative pheasant habitat suitability within spatial scales relevant to individual wildlife managers. Our tool allows users to virtually manipulate the landcover composition of a simulated space to explore how changes in landcover may affect pheasant relative habitat suitability, and guides users through the economic tradeoffs of landscape changes. We offer suggestions for development of similar interactive applications and demonstrate their potential as innovative science delivery tools for diverse professional and public audiences.

PLoS ONE↗
USGS1990

Geographic information system as country-level development and monitoring tool, Senegal example

Geographic information systems (GIS) allow an investigator the capability to merge and analyze numerous types of country-level resource data. Hypothetical resource analysis applications in Senegal were conducted to illustrate the utility of a GIS for development planning and resource monitoring. Map and attribute data for soils, vegetation, population, infrastructure, and administrative units were merged to form a database within a GIS. Several models were implemented using a GIS to: analyze development potential for sustainable dryland agriculture; prioritize where agricultural development should occur based upon a regional food budget; and monitor dynamic events with remote sensing. The steps for implementing a GIS analysis are described and illustrated, and the use of a GIS for conducting an economic analysis is outlined. Using a GIS for analysis and display of results opens new methods of communication between resource scientists and decision makers. Analyses yielding country-wide map output and detailed statistical data for each level of administration provide the advantage of a single system that can serve a variety of users.

Conference Paper↗
USGS2007

Strategic Plan for the North American Breeding Bird Survey: 2006-2010

Executive Summary The mission of the North American Breeding Bird Survey (BBS) is to provide scientifically credible measures of the status and trends of North American bird populations at continental and regional scales to inform biologically sound conservation and management actions. Determining population trends, relative abundance, and distributions of North American avifauna is critical for identifying conservation priorities, determining appropriate conservation actions, and evaluating those actions. The BBS program, jointly coordinated by the U.S. Geological Survey and Environment Canada’s Canadian Wildlife Service, provides the U.S. and Canadian Federal governments, state and provincial agencies, other conservation practitioners, and the general public with science-based avian population trend estimates and other information for regional and national species’ population assessments. Despite the demonstrated value of the BBS for furthering avian conservation across North America, its importance is often underappreciated, and it is underfunded compared with many other government-supported programs that report on status of the environment. Today, BBS resources, adjusted for inflation, are below the amount allocated in the 1970s and are still only sufficient to support two biologists. Yet the number of routes, participants, data, and data requests has quadrupled. Data and information management and delivery requirements and security concerns, non-existent in 1966, impose further demands on BBS resources. In addition, the Mexican expansion of the BBS offers new hope for a truly continental approach to avian conservation, but also brings additional challenges. Meeting the goals of this plan will take cooperation among myriad stakeholders; yet, even with collaboration, most objectives of this plan will be unattainable if BBS program support is not increased. The BBS developed this strategic plan to help set priorities and identify resources required for the program to continue to meet the evolving needs of the conservation community for information on bird population change. By setting clear goals, strategies, and measures of success, this plan provides a cohesive framework and vision for maintenance and development of the BBS. The plan identifies two major goals for the BBS, with a number of strategies and objectives to achieve these goals. Over the next 5 years, progress made in addressing each long-term goal and its associated 5-year strategies and objectives will gage the plan’s success. Specific actions, projected outcomes, and measures of success related to accomplishing these are outlined in Table 1, with a timeline in Table 2. The two main goals for the program, with a summary of the strategies to achieve them, are: Goal 1: Collect scientifically credible measures of the status and trends of North American bird populations at continental and regional scales. The North American Breeding Bird Survey will continue to support North American natural resource conservation through the collection of scientifically credible measures of the status and trends of continental bird populations. While doing this, the BBS will work to improve the science behind the program to better meet its mission and the changing needs of the avian conservation community. In partnership with collaborators, the BBS will address detection probability bias and habitat bias, improve analytical methods, and more fully assess and account for observer quality. Moreover, the BBS will improve the quality and breadth of avian population data through strategic increases in route density and the establishment of a Mexican BBS program. Goal 2: Ensure BBS data and analytical results are widely available and easily accessible for use by the avian conservation and management communities. At the heart of the BBS lies a four-million-record database containing more than 40 years of data on more than 600 bird species. These data are of no value if not well maintained, appropriately analyzed, and widely and easily accessible. The USGS has greatly improved data management and accessibility in recent years. Trend estimates were first made available via the Internet in the mid-1990s, followed closely by the raw data with baseline metadata and standard operating procedures. Nevertheless, numerous enhancements to data management and the usability of BBS results will greatly improve the ability of the BBS to serve avian conservation goals. The BBS needs to ensure that BBS data and results presented on the web site use the best data-management practices and statistical methods, with adequate documentation for users to understand them and any differences between different trend estimates. Moreover, the BBS needs to increase communication with BBS partners and stakeholders to ensure that it continues to meet the avian population status and trends needs of the conservation community and to encourage the development of new products. Working with collaborators, the BBS will develop tools for integrating environmental parameters like habitat change into the analyses, and for integrating BBS data with other avian survey results. In addition, the BBS will continue to improve data and database management through the incorporation of additional data and data fields, such as georeferenced stop locations and more complete metadata for the raw data and results, thus enhancing the uses that can be made of the data.

Circular↗
USGS2020

Aligning climate models with stakeholder needs: Advances in communicating future rainfall uncertainties for south Florida decision makers

Changes in future precipitation are of great importance to climate data users in South Florida. A recent U.S. Geological Survey workshop, “Increasing Confidence in Precipitation Projections for Everglades Restoration,” highlighted a gap between standard climate model outputs and the climate information needs of some key Florida natural resource managers. These natural resource managers (hereafter broadly defined as “climate data users”) need more tailored output than is commonly provided by the climate modeling community. This study responds to these user needs by outlining and testing an adaptable methodology to select output from ensemble climate‐model simulations based on user‐defined precipitation drivers, using statistical methods common across scientific disciplines. This methodology is developed to provide a “decision matrix” that guides climate data users to specify the subset of models most important to their work based on each user's season (winter, summer, and annual) and the condition (dry, wet, neutral, and no threshold events) of interest. The decision matrix is intended to better communicate the subset of models best representing precipitation drivers. This information could increase users' confidence in climate models as a resource for natural resource planning and can be used to direct future dynamical downscaling efforts. This methodology is based in dynamical processes controlling precipitation via remote and local teleconnections. We also suggest that future climate studies in South Florida include high‐resolution climate model runs (i.e., ocean eddy resolving) in conjunction with dynamical downscaling to adequately capture precipitation variability.

South Florida↗
USGS2000

Statistical Approaches to Interpretation of Local, Regional, and National Highway-Runoff and Urban-Stormwater Data

Decision makers need viable methods for the interpretation of local, regional, and national-highway runoff and urban-stormwater data including flows, concentrations and loads of chemical constituents and sediment, potential effects on receiving waters, and the potential effectiveness of various best management practices (BMPs). Valid (useful for intended purposes), current, and technically defensible stormwater-runoff models are needed to interpret data collected in field studies, to support existing highway and urban-runoffplanning processes, to meet National Pollutant Discharge Elimination System (NPDES) requirements, and to provide methods for computation of Total Maximum Daily Loads (TMDLs) systematically and economically. Historically, conceptual, simulation, empirical, and statistical models of varying levels of detail, complexity, and uncertainty have been used to meet various data-quality objectives in the decision-making processes necessary for the planning, design, construction, and maintenance of highways and for other land-use applications. Water-quality simulation models attempt a detailed representation of the physical processes and mechanisms at a given site. Empirical and statistical regional water-quality assessment models provide a more general picture of water quality or changes in water quality over a region. All these modeling techniques share one common aspect-their predictive ability is poor without suitable site-specific data for calibration. To properly apply the correct model, one must understand the classification of variables, the unique characteristics of water-resources data, and the concept of population structure and analysis. Classifying variables being used to analyze data may determine which statistical methods are appropriate for data analysis. An understanding of the characteristics of water-resources data is necessary to evaluate the applicability of different statistical methods, to interpret the results of these techniques, and to use tools and techniques that account for the unique nature of water-resources data sets. Populations of data on stormwater-runoff quantity and quality are often best modeled as logarithmic transformations. Therefore, these factors need to be considered to form valid, current, and technically defensible stormwater-runoff models. Regression analysis is an accepted method for interpretation of water-resources data and for prediction of current or future conditions at sites that fit the input data model. Regression analysis is designed to provide an estimate of the average response of a system as it relates to variation in one or more known variables. To produce valid models, however, regression analysis should include visual analysis of scatterplots, an examination of the regression equation, evaluation of the method design assumptions, and regression diagnostics. A number of statistical techniques are described in the text and in the appendixes to provide information necessary to interpret data by use of appropriate methods. Uncertainty is an important part of any decisionmaking process. In order to deal with uncertainty problems, the analyst needs to know the severity of the statistical uncertainty of the methods used to predict water quality. Statistical models need to be based on information that is meaningful, representative, complete, precise, accurate, and comparable to be deemed valid, up to date, and technically supportable. To assess uncertainty in the analytical tools, the modeling methods, and the underlying data set, all of these components need be documented and communicated in an accessible format within project publications.

Open-File Report↗
USGS2020

An interactive decision-making tool for evaluating biological and statistical standards of migrating fish survival past hydroelectric dams

Quantifying the downstream survival of migrating fish past dams is critical for conservation efforts. Regulators require assessments of survival as a condition of operation. Failure to meet an established survival standard may result in required operational or costly structural changes at a facility. Establishing the survival standard, as well as the rules of assessment, is a point of contention between regulators and operators. Management goals are based on biological criteria, but there are inherent statistical and probabilistic trade-offs when choosing a standard value and the method for assessment. We make a distinction between a “biological” goal (the conservation goal) and a “statistical” standard (a function of the biological goal, sample size, assessment method, and years of consecutive evaluation). An effective statistical standard maximizes true positives (passing the standard when the biological goal is being met) and true negatives (failing the standard when the goal is not being met), while minimizing false negatives and false positives. We explored the effects of sample size, true survival, and assessment methods on the probability of passing different statistical standards by simulating survival studies (simulating mark-recapture experiments). We observed a strong influence of assessment methods on the probability of making the right decision (true positive or true negative), especially when sample size, and recapture probability was low. As a support tool, we developed an interactive user interface to explore specific scenarios, and to aid communication among decision-makers.

River Research and Applications↗
USGS2020

Economic valuation of health benefits from using geologic data to communicate radon risk potential

Background: Radon exposure is the second leading cause of lung cancer worldwide and represents a major health concern within and outside the United States. Mitigating exposure to radon is especially critical in places with high rates of tobacco smoking (e.g., Kentucky, USA), as radon-induced lung cancer is markedly greater among people exposed to tobacco smoke. Despite homes being a common source of radon exposure, convincing homeowners to test and mitigate for radon remains a challenge. A new communication strategy to increase radon testing among Kentucky homeowners utilizes fine-scale geologic map data to create detailed radon risk potential maps. We assessed the health benefits of this strategy via avoided lung cancer and associated premature mortality and quantified the economic value of these benefits to indicate the potential utility of using geologic map data in radon communication strategies. Methods: We estimated the change in radon testing among all 120 counties in Kentucky following a new communication strategy reliant on geologic maps. We approximated the resultant potential change in radon mitigation rates and subsequent expected lung cancer cases and mortality avoided among smokers and non-smokers exposed to ≥4 pCi/L of radon in the home. We then applied the value of a statistical life to derive the economic value of the expected avoided mortality. Results: The new communication strategy is estimated to help 75 Kentucky residents in one year avoid exposure to harmful radon levels via increased testing and mitigation rates. This equated to the potential avoidance of approximately one premature death due to lung cancer, with a net present value of \$3.4 to \$8.5 million (2016 USD). Conclusions: Our analysis illustrates the potential economic value of health benefits associated with geologic map data used as part of a communication strategy conveying radon risk to the public. Geologic map data are freely available in varying resolutions throughout the United States, suggesting Kentucky’s radon communication strategy using geologic maps can be employed in other states to educate the public about radon. As this is only a single application, in a single state, the economic and health benefits of geologic map data in educating the public about radon are likely to exceed our estimates.

Kentucky↗
USGS2017

Visitor spending effects: assessing and showcasing America's investment in national parks

This paper provides an overview of the evolution, future, and global applicability of the U.S. National Park Service's (NPS) visitor spending effects framework and discusses the methods used to effectively communicate the economic return on investment in America's national parks. The 417 parks represent many of America's most iconic destinations: in 2016, they received a record 331 million visits. Competing federal budgetary demands necessitate that, in addition to meeting their mission to preserve unimpaired natural and cultural resources for the enjoyment of the people, parks also assess and showcase their contributions to the economic vitality of their regions and the nation. Key approaches explained include the original Money Generation Model (MGM) from 1990, MGM2 used from 2001, and the visitor spending effects model which replaced MGM2 in 2012. Detailed discussion explains the NPS's visitor use statistics system, the formal program for collecting, compiling, and reporting visitor use data. The NPS is now establishing a formal socioeconomic monitoring (SEM) program to provide a standard visitor survey instrument and a long-term, systematic sampling design for in-park visitor surveys. The pilot SEM survey is discussed, along with the need for international standardization of research methods.

Journal of Sustainable Tourism↗
USGS2012

National wildlife refuge visitor survey 2010/2011: Individual refuge results

The National Wildlife Refuge System (Refuge System), established in 1903 and managed by the U.S. Fish and Wildlife Service (Service), is the leading network of protected lands and waters in the world dedicated to the conservation of fish, wildlife and their habitats. There are 556 national wildlife refuges and 38 wetland management districts nationwide, encompassing more than 150 million acres. The Refuge System attracts more than 45 million visitors annually, including 25 million people per year to observe and photograph wildlife, over 9 million to hunt and fish, and more than 10 million to participate in educational and interpretation programs. Understanding visitors and characterizing their experiences on national wildlife refuges are critical elements of managing these lands and meeting the goals of the Refuge System. The Service collaborated with the U.S. Geological Survey to conduct a national survey of visitors regarding their experiences on national wildlife refuges. The survey was conducted to better understand visitor needs and experiences and to design programs and facilities that respond to those needs. The survey results will inform Service performance planning, budget, and communications goals. Results will also inform Comprehensive Conservation Plan (CCPs), Visitor Services, and Transportation Planning processes. This data series consists of 53 separate data files. Each file describes the results of the survey for an individual refuge and contains the following information: * Introduction: An overview of the Refuge System and the goals of the national surveying effort. * Methods: The procedures for the national surveying effort, including selecting refuges, developing the survey instrument, contacting visitors, and guidance for interpreting the results. * Refuge Description: A brief description of the refuge location, acreage, purpose, recreational activities, and visitation statistics, including a map (where available) and refuge website link. * Sampling at This Refuge: The sampling periods, locations, and response rate for the refuge. * Selected Survey Results: Key findings for the refuge, including: - Visitor and Trip Characteristics - Visitor Spending in the Local Communities - Visitors Opinions about This Refuge - Visitor Opinions about National Wildlife Refuge System Topics * Conclusion * References * Survey Frequencies (Appendix A): The survey instrument with the frequency results for this refuge. * Visitor Comments (Appendix B): The verbatim responses to the open-ended survey questions for this refuge. Combined results for the 53 participating refuges are available at http://pubs.usgs.gov/ds/685/ as part of USGS Data Series 685.

Data Series↗
USGS2013

National wildlife refuge visitor survey 2012--Individual refuge results

The National Wildlife Refuge System (Refuge System), established in 1903 and managed by the U.S. Fish and Wildlife Service (Service), is the leading network of protected lands and waters in the world dedicated to the conservation of fish, wildlife and their habitats. There are 560 national wildlife refuges and 38 wetland management districts nationwide, encompassing more than 150 million acres. The Refuge System attracts nearly 45 million visitors annually, including 34.8 million people who observe and photograph wildlife, 9.6 million who hunt and fish, and nearly 675,000 teachers and students who use refuges as outdoor classrooms. Understanding visitor perceptions of refuges and characterizing their experiences on refuges are critical elements of managing these lands and meeting the goals of the Refuge System. The Service collaborated with the U.S. Geological Survey to conduct a national survey of visitors regarding their experiences on national wildlife refuges. The purpose of the survey was to better understand visitor experiences and trip characteristics, to gauge visitors’ levels of satisfaction with existing recreational opportunities, and to garner feedback to inform the design of programs and facilities. The survey results will inform performance, planning, budget, and communications goals. Results will also inform Comprehensive Conservation Plans (CCPs), visitor services, and transportation planning processes. This Data Series consists of 25 separate data files. Each file describes the results of the survey for an individual refuge and contains the following information: • Introduction: An overview of the Refuge System and the goals of the national surveying effort. • Methods: The procedures for the national surveying effort, including selecting refuges, developing the survey instrument, contacting visitors, and guidance for interpreting the results.• Refuge Description: A brief description of the refuge location, acreage, purpose, recreational activities, and visitation statistics, including a map (where available) and refuge website link. • Sampling at This Refuge: The sampling periods, locations, and response rate for the refuge. • Selected Survey Results: Key findings for the refuge, including: o Visitor and trip characteristics o Visitor spending in the local communities o Visitors opinions about the refuge o Visitor opinions about National Wildlife Refuge System topics • Conclusion • References Cited • Survey Frequencies (Appendix A): The survey instrument with frequency results for the refuge. • Visitor Comments (Appendix B): The verbatim responses to the open-ended survey questions for the refuge.Individual-refuge results for the 53 participating refuges in the 2010-2011 national effort are available at http://pubs.usgs.gov/ds/643/ as part of USGS Data Series 643. Combined results for the 53 participating refuges in the 2010-2011 national effort are available at http://pubs.usgs.gov/ds/685/ as part of USGS Data Series 685.

Data Series↗
USGS2024

Use of Doppler velocity radars to monitor and predict debris and flood wave velocities and travel times in post-wildfire basins

The magnitude and timing of extreme events such as debris and floodflows (collectively referred to as floodflows) in post-wildfire basins are difficult to measure and are even more difficult to predict. To address this challenge, a sensor ensemble consisting of noncontact, ground-based (near-field), Doppler velocity (velocity) and pulsed (stage or gage height) radars, rain gages, and a redundant radio communication network was leveraged to monitor flood wave velocities, to validate travel times, and to compliment observations from NEXRAD weather radar. The sensor ensemble (DEbris and Floodflow Early warNing System, DEFENS) was deployed in Waldo Canyon, Pike National Forest, Colorado, USA, which was burned entirely (100 percent burned) by the Waldo Canyon fire during the summer of 2012 ( MTBS, 2020 ). Surface velocity, stage, and precipitation time series collected during the DEFENS deployment on 10 August 2015 were used to monitor and predict flood wave velocities and travel times as a function of stream discharge (discharge; streamflow). The 10 August 2015 event exhibited spatial and temporal variations in rainfall intensity and duration that resulted in a discharge equal to 5.01 cubic meters per second (m 3 /s). Discharge was estimated post-event using a slope-conveyance indirect discharge method and was verified using velocity radars and the probability concept algorithm. Mean flood wave velocities – represented by the kinematic celerity ( c k = 2.619 m e t e r s p e r s e c o n d , m / s ± 0.556 p e r c e n t "> 𝑐 𝑘 = 2.619 𝑚𝑒𝑡𝑒𝑟𝑠 𝑝𝑒𝑟 𝑠𝑒𝑐𝑜𝑛𝑑, m/s ± 0.556 𝑝𝑒𝑟𝑐𝑒𝑛𝑡) and dynamic celerity ( c d = 3.533 m / s ± 0.181 p e r c e n t a n d t h e i r u n c e r t a i n t i e s "> 𝑐 𝑑 = 3.533 m/s ± 0.181 𝑝𝑒𝑟𝑐𝑒𝑛𝑡) and their uncertainties were computed. L-moments were computed to establish probability density functions (PDFs) and associated statistics for each of the at-a-section hydraulic parameters to serve as a workflow for implementing alert networks in hydrologically similar basins that lack data. Measured flood wave velocities and travel times agreed well with predicted values. Absolute percent differences between predicted and measured flood wave velocities ranged from 1.6 percent to 49 percent and varied with water slope, hydraulic radius, and depth. The kinematic celerity was a better predictor for steep slopes and wide flood plains associated with the Upper Waldo and Middle Waldo radar streamgages; whereas, the dynamic celerity was a better surrogate for shallow slopes and incised channels such as the Lower Waldo radar streamgage. The method demonstrates the potential extensibility of a post-wildfire warning system by (1) leveraging multiple systems (i.e., weather radar, near-field velocity and stage radars, and rain gages) for accurate and timely warnings of debris and floodflows, (2) establishing an order of operations to site, install, and operate near-field radars and conventional rain gages to record floodflows, forecast travel times, and document geomorphic change in this basin and hydrologically similar basins that lack data, and (3) communicating data operationally with the Colorado Department of Transportation engineering staff, National Weather Service forecasters, and emergency managers.

Colorado↗
USGS2020

Scientist’s guide to developing explanatory statistical models using causal analysis principles

Recent discussions of model selection and multimodel inference highlight a general challenge for researchers, which is how to clearly convey the explanatory content of a hypothesized model or set of competing models. The advice from statisticians for scientists employing multimodel inference is to develop a well‐thought‐out set of candidate models for comparison, though precise instructions for how to do that are typically not given. A coherent body of knowledge, which falls under the general term causal analysis, now exists for examining the explanatory scientific content of candidate models. Much of the literature on causal analysis has been recently developed and we suspect may not be familiar to many ecologists. This body of knowledge comprises a set of graphical tools and axiomatic principles to support scientists in their endeavors to create “well‐formed hypotheses”, as statisticians are asking them to do. Causal analysis is complementary to methods such as structural equation modeling, which provides the means for evaluation of proposed hypotheses against data. In this paper, we summarize and illustrate a set of principles that can guide scientists in their quest to develop explanatory hypotheses for evaluation. The principles presented in this paper have the capacity to close the communication gap between statisticians, who urge scientists to develop well‐thought‐out coherent models, and scientists, who would like some practical advice for exactly how to do that.

Ecology↗
USGS2002

δ 13 C and δ 18 O isotopic composition of CaCO 3 measured by continuous flow isotope ratio mass spectrometry: statistical evaluation and verification by application to Devils Hole core DH-11 calcite

A new method was developed to analyze the stable carbon and oxygen isotope ratios of small samples (400 ± 20 µg) of calcium carbonate. This new method streamlines the classical phosphoric acid/calcium carbonate (H 3 PO 4 /CaCO 3 ) reaction method by making use of a recently available Thermoquest-Finnigan GasBench II preparation device and a Delta Plus XL continuous flow isotope ratio mass spectrometer. Conditions for which the H 3 PO 4 /CaCO 3 reaction produced reproducible and accurate results with minimal error had to be determined. When the acid/carbonate reaction temperature was kept at 26 °C and the reaction time was between 24 and 54 h, the precision of the carbon and oxygen isotope ratios for pooled samples from three reference standard materials was ≤0.1 and ≤0.2 per mill or ‰, respectively, although later analysis showed that materials from one specific standard required reaction time between 34 and 54 h for δ 18 O to achieve this level of precision. Aliquot screening methods were shown to further minimize the total error. The accuracy and precision of the new method were analyzed and confirmed by statistical analysis. The utility of the method was verified by analyzing calcite from Devils Hole, Nevada, for which isotope-ratio values had previously been obtained by the classical method. Devils Hole core DH-11 recently had been re-cut and re-sampled, and isotope-ratio values were obtained using the new method. The results were comparable with those obtained by the classical method with correlation = +0.96 for both isotope ratios. The consistency of the isotopic results is such that an alignment offset could be identified in the re-sampled core material, and two cutting errors that occurred during re-sampling then were confirmed independently. This result indicates that the new method is a viable alternative to the classical reaction method. In particular, the new method requires less sample material permitting finer resolution and allows automation of some processes resulting in considerable time savings.

Rapid Communications in Mass Spectrometry↗
USGS2026

End-user needs for remote sensing wetlands of the Prairie Pothole Region of North America

The Prairie Pothole Region (PPR) of North America comprises globally important grassland and wetland ecosystems critical for numerous populations of migratory birds. Due to the importance of this region for migratory birds, and particularly waterfowl, and the threats of habitat loss due to intensifying agriculture, there is a mature and diverse system of conservation organizations, agencies, and partnerships that spends hundreds of millions of dollars annually on habitat conservation to support migratory bird populations. Remote sensing can be a powerful tool for observing and evaluating global change at large scales as well as expanding inferences from field studies to the broader landscape with statistical models. However, development and utilization of these tools has lagged behind their demand for several reasons, including concerns over spatial and temporal resolution and accuracy of products; perception of a misalignment with decision-maker needs; technological barriers such as skill sets of conservation professionals, computing resources, data access, and usability. In this report, we summarize the needs of conservation professionals and scientists who use or want to use remote sensing data products to inform science about wetland change and conservation of wetlands in the PPR. We assembled this information through several methods leading up to, during, and following a January 2026 PPR Wetland Remote Sensing Workshop. The workshop included United States and Canadian scientists, conservation professionals, and policy experts. Our goal was to bring together end-users and remote sensing product developers jointly to explore reducing the lag between product development and utilization of products to inform science and conservation. Specifically, we aimed to identify gaps in wetland remote sensing that limit effective monitoring, management, and conservation in the PPR, and to develop a framework that outlines pathways to address these gaps by fostering collaboration, improving communication networks, encouraging discussion, and building on existing and ongoing efforts. This report summarizes our participants’ descriptions of end-user needs and the outcomes of the workshop.

Prairie Pothole region↗
USGS2024

Birdwatching preferences reveal synergies and tradeoffs among recreation, carbon, and fisheries ecosystem services in Pacific Northwest estuaries, USA

Coastal ecosystems provide multiple ecosystem services that are valued in diverse ways. The Nisqually River Delta (the Delta), an estuary in Puget Sound, Washington, U.S.A., is co-managed by the Nisqually Indian Tribe and the Billy Frank Jr. Nisqually National Wildlife Refuge. In an ecosystem services assessment, we used different service-appropriate methods including citizen science, statistical and geospatial models, and scenario analysis to evaluate three ecosystem services – recreational birdwatching, soil carbon accumulation and fishery production – indicated as priorities for the Refuge, Nisqually Indian Tribe, and surrounding communities. We developed a generalized additive mixed model set based on eBird mobile application birdwatching observations to understand the biological and landscape features that influence birdwatching and to project birdwatching visitation based on scenarios of Delta habitat change. We evaluated ecosystem service synergies and tradeoffs associated with habitat change for three coastal habitat types using scenario outputs from the birdwatching model and published results on Delta soil carbon accumulation and fishery production. The highest-ranked birdwatching models explained 88 % of the deviance and showed that visitation was greatest in winter months when distance to major cities was approximately 20 km. Recreational birdwatching increased with increasing area of forested wetland, emergent wetland, aquatic vegetation bed, open access, and total estuary. With increasing forested and emergent wetland area, recreational birdwatching, out-migrating juvenile Chinook salmon weight and soil carbon accumulation all increased. With increasing aquatic vegetation bed (resulting from sea level rise), recreational birdwatching increased, but salmon weight and soil carbon accumulation decreased. We identified practical ways in which ecosystem services may be incorporated into adaptive management frameworks that support climate adaptation decision making. This study illustrated how use of ecosystem services can help managers make decisions that have greater benefit for wildlife and people, communicate the societal value of decisions and increase local support and participation.

Washington↗
USGS2022

Seismic multi-hazard and impact estimation via causal inference from satellite imagery

Rapid post-earthquake reconnaissance is important for emergency responses and rehabilitation by providing accurate and timely information about secondary hazards and impacts, including landslide, liquefaction, and building damage. Despite the extensive collection of geospatial data and satellite images, existing physics-based and data-driven methods suffer from low estimation performance due to the complex and event-specific causal dependencies underlying the cascading processes of earthquake-triggered hazards and impacts. Herein, we present a rapid seismic multi-hazard and impact estimation system that leverages advanced statistical causal inference and remote sensing techniques. The unique feature of this system is that it provides accurate and high-resolution estimations on a regional scale by jointly inferring multiple hazards and building damage from satellite images through modeling their causal dependencies. We evaluate our system on multiple seismic events from diverse countries around the globe. Our results corroborate that incorporating causal dependencies significantly improves large-scale estimation accuracy for multiple hazards and impacts compared to existing systems. The results also reveal quantitative causal mechanisms among earthquake-triggered multi-hazard and impact for multiple seismic events. Our system establishes a new way to extract and utilize the complex interactions of multiple hazards and impacts for effective disaster responses and advancing understanding of seismic geological processes.

Nature Communications↗
USGS2018

Effect of heat and singeing on stable hydrogen isotope ratios of bird feathers and implications for their use in determining geographic origin

Rationale Stable hydrogen isotope ( δ 2 H) ratios of animal tissues are useful for assessing movement and geographic origin of mobile organisms. However, it is uncertain whether heat and singeing affects feather δ 2 H values and thus subsequent geographic assignments. This is relevant for birds of conservation interest that are burned and killed at concentrating solar‐energy facilities that reflect sunlight to a receiving tower and generate a solar flux field. Methods We used a controlled experiment to test the effect of known heat loads (exposure to 200, 250 or 300°C for 1 min) on the morphology and δ 2 H values of feathers from two songbird species. Subsequently, we examined the effects of singeing on δ 2 H values of feathers from three other songbird species that were found dead in the field at a concentrating solar‐energy facility. Results Relative to control samples, heating caused visual morphological changes to feathers, including shriveling at 250°C and charring at 300°C. The δ 2 H values significantly declined by a mean of 27.8‰ in experimental samples exposed to 300°C. There was no statistically detectable difference between δ 2 H values of the singed and unsinged portions of field‐collected feathers from the same bird. Conclusions Limited singeing that did not dramatically alter the feather morphology did not substantially affect δ 2 H values of feathers from these songbirds. However, higher temperatures induced charring and reduced δ 2 H values. Therefore, severely charred feathers should be avoided when selecting feathers for δ 2 H‐based assessment of geographic origin.

Rapid Communications in Mass Spectrometry↗
USGS2020

Characterizing benthic macroinvertebrate and algal biological condition gradient models for California wadeable Streams, USA

The Biological Condition Gradient (BCG) is a conceptual model that describes changes in aquatic communities under increasing levels of anthropogenic stress. The BCG helps decision-makers connect narrative water quality goals (e.g., maintenance of natural structure and function) to quantitative measures of ecological condition by linking index thresholds based on statistical distributions (e.g., percentiles of reference distributions) to expert descriptions of changes in biological condition along disturbance gradients. As a result, the BCG may be more meaningful to managers and the public than indices alone. To develop a BCG model, biological response to stress is divided into 6 levels of condition, represented as changes in biological structure (abundance and diversity of pollution sensitive versus tolerant taxa) and function. We developed benthic macroinvertebrate (BMI) and algal BCG models for California perennial wadeable streams to support interpretation of percentiles of reference-based thresholds for bioassessment indices (i.e., the California Stream Condition Index [CSCI] for BMI and the Algal Stream Condition Index [ASCI] for diatoms and soft-bodied algae). Two panels (one of BMI ecologists and the other of algal ecologists) each calibrated a general BCG model to California wadeable streams by first assigning taxa to specific tolerance and sensitivity attributes, and then independently assigning test samples (264 BMI and 248 algae samples) to BCG Levels 1–6. Consensus on the assignments was developed within each assemblage panel using a modified Delphi method. Panels then developed detailed narratives of changes in BMI and algal taxa that correspond to the 6 BCG levels. Consensus among experts was high, with 81% and 82% expert agreement within 0.5 units of assigned BCG level for BMIs and algae, respectively. According to both BCG models, the 10th percentiles index scores at reference sites corresponded to a BCG Level 3, suggesting that this type of threshold would protect against moderate changes in structure and function while allowing loss of some sensitive taxa. The BCG provides a framework to interpret changes in aquatic biological condition along a gradient of stress. The resulting relationship between index scores and BCG levels and narratives can help decision-makers select thresholds and communicate how these values protect aquatic life use goals.

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