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At least 199 records · Page 11Linked to original sources
USGS2021

Informing future condition scenario planning for habitat specialists of the imperiled pine rockland ecosystem of South Florida

This project evaluated habitat conditions for two species found in the imperiled pine rockland ecosystem—the Rim Rock Crowned Snake ( Tantilla oolitica ) and the Key Ring-Necked Snake ( Diadophis punctatus acricus ). The Rim Rock Crowned Snake historically occurred in eastern Miami-Dade County (hereafter, mainland) as well as throughout the Florida Keys, whereas the Key Ring-Necked Snake occurs only in lower Florida Keys (Enge et al. 2004; Mays and Enge 2016). Both species are very elusive, small (< 20 cm in length) and primarily fossorial. Pine rockland habitat is rapidly disappearing in South Florida, with < 3 percent of its original extent remaining. Saltwater intrusion from hurricanes and sea-level rise (SLR), and human development pose the greatest threats to the longevity of this ecosystem which, in turn, places species that are endemic to this unique habitat at risk of extinction. The Rim Rock Crowned Snake and the Key Ringed-Necked Snake are being considered for listing by the U.S. Fish and Wildlife Service (USFWS). To aid the agency’s decision, it must be able to forecast species’ responses to potential future environmental conditions, as well as to different conservation and management actions. Yet, the information needed to complete these forecasts—such as population trends, life history traits, habitat use, and future land use and climate conditions—is often lacking for most rare species. This is especially problematic for assessments of species resiliency to changes in climate and land use. When these types of data are lacking, information on habitat quality can be used to help determine how a species will respond to change. First, this project gathered current and historical records for both species from various sources such as museum specimens, inventories, and other personal account. Then, we identified potential future changes in habitat that could result from different management actions, such as habitat acquisition or restoration, and environmental conditions, such as changes in the frequency and intensity of tropical storms and rates of SLR. Researchers then explored the potential impacts of these habitat condition changes on the Rim Rock Crowned Snake and Key Ring-Necked Snake. This information can be used by the USFWS to help make decisions about the need to protect these species under the Endangered Species Act and could inform the conservation, management, and recovery of other at-risk species found in the pine rockland ecosystem. This work supports the Secretary of Interior’s priority to create a conservation stewardship legacy by using science to identify best practices to manage land and water resource and adapt to changes in the environment.

Florida↗
USGS2023

Causality-informed Bayesian inference for rapid seismic ground failure and building damage estimation

Rapid and accurate estimates of seismic ground failure and building damage are beneficial to efficient emergency response and post-earthquake recovery. Traditional approaches, such as physical and geospatial models, have poor accuracy and resolution due to large uncertainties and the limited availability of informing geospatial layers. The introduction of remote sensing techniques has shown potential in providing supplementary information for rapid hazard estimation by analyzing earthquake-induced correlation changes between pre- and post-event satellite images. However, the changes in satellite images are the result of overlapping ground failure, building damage, and environmental noise, making it challenging to categorize and estimate different seismic hazards and impacts directly from satellite images.Here we design a novel causality-informed Bayesian network that continuously updates seismic ground failure and building damage estimates from satellite images by modeling the physical interdependencies between geospatial features, ground failure, building footprints, building damage, and satellite images. The incorporation of physical interdependencies allows an effective fusion of physical models and rich but noisy information from remote sensing observations and reduces bias and uncertainties in estimations. Our experiments show that integrating satellite images through our Bayesian network improves the accuracy of seismic ground failure and building damage estimations.

Conference Paper↗
USGS2003

Information technology challenges of biodiversity and ecosystems informatics

Computer scientists, biologists, and natural resource managers recently met to examine the prospects for advancing computer science and information technology research by focusing on the complex and often-unique challenges found in the biodiversity and ecosystem domain. The workshop and its final report reveal that the biodiversity and ecosystem sciences are fundamentally information sciences and often address problems having distinctive attributes of scale and socio-technical complexity. The paper provides an overview of the emerging field of biodiversity and ecosystem informatics and demonstrates how the demands of biodiversity and ecosystem research can advance our understanding and use of information technologies.

Information Systems↗
USGS1984

National Cartographic Information Center

The National Cartographic Information Center (NCIC) exists to help you find maps of all kinds and much of the data and materials used to compile and to print them. NCIC collects, sorts and describes all types of cartographic information from Federal, State and local government agencies and, where possible, from private companies in the mapping business. It is the public's primary source for cartographic information. (See partial list of Federal agencies and their map and other cartographic products.)

General Information Product↗
USGS2012

Freedom of Information Act

The Freedom of Information Act( FOIA), 5 U.S.C.§ 552, as amended, generally provides that any person has a right to request access to Federal agency records. The USGS proactively promotes information disclosure as inherent to its mission of providing objective science to inform decisionmakers and the general public. USGS scientists disseminate up-to-date and historical scientific data that are critical to addressing national and global priorities.

General Information Product↗
USGS1992

Global Land Information System (GLIS)

The Global Land Information System (GLIS) is an interactive computer system developed by the U.S. Geological Survey (USGS) for scientists seeking sources of information about the Earth's land surfaces. GLIS contains "metadata," that is, descriptive information about data sets. Through GLIS, scientists can evaluate data sets, determine their availability, and place online requests for products. GLIS is more, however, than a mere list of products. It offers online samples of earth science data that may be ordered through the system.

General Information Product↗
USGS2012

Freedom of Information Act-Employee responsibilities

The Freedom of Information Act( FOIA), 5 U.S.C. § 552, as amended, generally provides that any person has a right to request access to Federal agency records. The USGS proactively promotes information disclosure as inherent to its mission of providing objective science to inform decisionmakers and the general public. USGS scientists disseminate up-to-date and historical scientific data that are critical to addressing national and global priorities.

General Information Product↗
USGS2020

Western bumble bee: Declines in United States and range-wide information gaps

In recent decades, many bumble bee species have declined due to changes in habitat, climate, and pressures from pathogens, pesticides, and introduced species. The western bumble bee ( Bombus occidentalis ), once common throughout western North America, is a species of concern and will be considered for listing by the U.S. Fish and Wildlife Service (USFWS) under the Endangered Species Act (ESA). We attempt to improve alignment of data collection and research with USFWS needs to consider redundancy, resiliency, and representation in the upcoming species status assessment. We reviewed existing data and literature on B. occidentalis , highlighting information gaps and priority topics for research. Priorities include increased knowledge of trends, basic information on several life‐history stages, and improved understanding of the relative and interacting effects of stressors on population trends, especially the effects of pathogens, pesticides, climate change, and habitat loss. An understanding of how and where geographic range extent has changed for the two subspecies of B. occidentalis is also needed. We outline data that could be easily collected in other research projects that would increase their utility for understanding range‐wide trends of bumble bees. We modeled the overall trend in occupancy from 1998 to 2018 of Bombus occidentalis within the continental United States using existing data. The probability of local occupancy declined by 93% over 21 yr from 0.81 (95% CRI = 0.43, 0.98) in 1998 to 0.06 (95% CRI = 0.02, 0.16) in 2018. The decline in occupancy varied spatially by landcover and other environmental factors. Detection rates vary in both space and time, but peak detection across the continental United States occurs in mid‐July. We found considerable spatial gaps in recent sampling, with limited sampling in many regions, including most of Alaska, northwestern Canada, and the southwestern United States. We therefore propose a sampling design to address these gaps to best inform the ESA species status assessment through improved assessment of how the spatial distribution of stressors influences occupancy changes. Finally, we request involvement via data sharing, participation in occupancy sampling with repeated visits to distributed survey sites, and complementary research to address priorities outlined in this paper.

Ecosphere↗
USGS2023

Prioritizing science efforts to inform decision making on public lands

Public land management agencies in the US are committed to using science-informed decision making, but there has been little research on the types and topics of science that managers need most to inform their decisions. We used the National Environmental Policy Act to identify four types of science information needed for making decisions relevant to public lands: (1) data on resources of concern, (2) scientific studies relevant to potential effects of proposed actions, (3) methods for quantifying potential effects of proposed actions, and (4) effective mitigation measures. We then used this framework to analyze 70 Environmental Assessments completed by the Bureau of Land Management in Colorado. Commonly proposed actions were oil and gas development, livestock grazing, land transactions, and recreation. Commonly analyzed resources included terrestrial wildlife, protected birds, vegetation, and soils. Focusing research efforts on the intersection of these resources and actions, and on developing and evaluating the effectiveness of mitigation measures to protect these resources, could strengthen the science foundation for public lands decision making.

Frontiers in Ecology and the Environment↗
USGS2014

Uncertainty, robustness, and the value of information in managing a population of northern bobwhites

The abundance of northern bobwhites (Colinus virginianus) has decreased throughout their range. Managers often respond by considering improvements in harvest and habitat management practices, but this can be challenging if substantial uncertainty exists concerning the cause(s) of the decline. We were interested in how application of decision science could be used to help managers on a large, public management area in southwestern Florida where the bobwhite is a featured species and where abundance has severely declined. We conducted a workshop with managers and scientists to elicit management objectives, alternative hypotheses concerning population limitation in bobwhites, potential management actions, and predicted management outcomes. Using standard and robust approaches to decision making, we determined that improved water management and perhaps some changes in hunting practices would be expected to produce the best management outcomes in the face of uncertainty about what is limiting bobwhite abundance. We used a criterion called the expected value of perfect information to determine that a robust management strategy may perform nearly as well as an optimal management strategy (i.e., a strategy that is expected to perform best, given the relative importance of different management objectives) with all uncertainty resolved. We used the expected value of partial information to determine that management performance could be increased most by eliminating uncertainty over excessive-harvest and human-disturbance hypotheses. Beyond learning about the factors limiting bobwhites, adoption of a dynamic management strategy, which recognizes temporal changes in resource and environmental conditions, might produce the greatest management benefit. Our research demonstrates that robust approaches to decision making, combined with estimates of the value of information, can offer considerable insight into preferred management approaches when great uncertainty exists about system dynamics and the effects of management.

Florida↗
USGS2018

Species‐ and habitat‐specific otolith chemistry patterns inform riverine fisheries management

Geology and hydrology are drivers of water chemistry and thus important considerations for fish otolith chemistry research. However, other factors such as species and habitat identity may have predictive ability, enabling selection of appropriate elemental signatures prior to costly, perhaps unnecessary water/age‐0 fish sampling. The goal of this study was to develop a predictive methodology for using species and habitat identity to design efficient otolith chemistry studies. Duplicate water samples and age‐0 fish were collected from 61 sites in 4 Missouri River reservoirs for walleye Sander vitreus and one impoundment (Lake Sharpe, South Dakota) for other fishes (bluegill Lepomis macrochirus , black crappie Pomoxis nigromaculatus , gizzard shad Dorosoma cepedianum , largemouth bass Micropterus salmoides , smallmouth bass M. dolomieu , white bass Morone chrysops , white crappie P. annularis , and yellow perch Perca flavescens ). Water chemistry (barium:calcium [Ba:Ca], strontium:calcium [Sr:Ca]) was temporally stable, spatially variable, and highly correlated with otolith chemistry for all species except yellow perch. Classification accuracies based on bivariate Ba:Ca and Sr:Ca signatures were high (84% across species) yet varied between floodplain and main‐channel habitats in a species‐specific manner. Thus, to maximize the reliability of otolith chemistry, researchers can use species classifications presented herein to inform habitat selection (e.g., study reservoir‐oriented species such as white bass in main‐channel environments) and habitat‐based classifications to inform species selection (e.g., focus floodplain studies on littoral species such as largemouth bass). Overall, species and habitat identity are important considerations for efficient, effective otolith chemistry studies that inform and advance fisheries and aquatic resource management.

North Dakota, South Dakota↗
USGS2026

Co-producing coastal bird research on the Gulf Coast through structured decision making (SDM) and constructed value of information (CVoI)

Conservation practitioners face the complex challenge of addressing global biodiversity threats within social-ecological systems with multiple jurisdictions, numerous interest groups, and changing environmental conditions. Bridging the research-to-implementation gap between scientists and managers, which integrates diverse perspectives that represent the variety of considerations impacting management outcomes can help to inform efficient and effective conservation. Avian conservation programs along the U.S. Gulf Coast exemplify these challenges, as management decisions must address diverse threats to declining coastal bird populations across large breeding, wintering, and migratory ranges while facing uncertainty surrounding the efficacy of large-scale strategies. This provides opportunities for improving management through co-produced research with structured decision making (SDM). We present a case study that demonstrates the application of co-production principles and SDM to collaboratively develop high-priority research questions informing effective avian conservation and management. Additionally, we applied a constructed value of information (CVoI) framework to identify and prioritize which uncertainties to reduce and better understand how research questions impact management actions. The integration of SDM’s five-step decision making framework ensured key principles of co-production were met, while co-production enhanced SDM outcomes by incorporating diverse perspectives and knowledge bases. CVoI further allowed participants to collectively determine final high-priority research questions in the face of complexity and uncertainty. Together, these approaches supported co-produced knowledge-generation, strategic hypothesis prioritization, and identification of research questions most likely to improve conservation decisions. This case study from the U.S. Gulf Coast demonstrates how co-produced research through SDM offers a broadly applicable approach for navigating ecological complexity and bridging the research-to-implementation gap in avian conservation.

Gulf Coast↗
USGS1987

Use of historical information in a maximum-likelihood framework

This paper discusses flood-quantile estimators which can employ historical and paleoflood information, both when the magnitudes of historical flood peaks are known, and when only threshold-exceedance information is available. Maximum likelihood, quasi-maximum likelihood and curve fitting methods for simultaneous estimation of 1, 2 and 3 unknown parameters are examined. The information contained in a 100 yr record of historical observations, during which the flood perception threshold was near the 10 yr flood level (i.e., on average, one flood in ten is above the threshold and hence is recorded), is equivalent to roughly 43, 64 and 78 years of systematic record in terms of the improvement of the precision of 100 yr flood estimators when estimating 1, 2 and 3 parameters, respectively. With the perception threshold at the 100 yr flood level, the historical data was worth 13, 20 and 46 years of systematic data when estimating 1, 2 and 3 parameters, respectively.

Journal of Hydrology↗
USGS2011

Which uncertainty? Using expert elicitation and expected value of information to design an adaptive program

Natural resource management is plagued with uncertainty of many kinds, but not all uncertainties are equally important to resolve. The promise of adaptive management is that learning in the short-term will improve management in the long-term; that promise is best kept if the focus of learning is on those uncertainties that most impede achievement of management objectives. In this context, an existing tool of decision analysis, the expected value of perfect information (EVPI), is particularly valuable in identifying the most important uncertainties. Expert elicitation can be used to develop preliminary predictions of management response under a series of hypotheses, as well as prior weights for those hypotheses, and the EVPI can be used to determine how much management could improve if uncertainty was resolved. These methods were applied to management of whooping cranes ( Grus americana ), an endangered migratory bird that is being reintroduced in several places in North America. The Eastern Migratory Population of whooping cranes had exhibited almost no successful reproduction through 2009. Several dozen hypotheses can be advanced to explain this failure, and many of them lead to very different management responses. An expert panel articulated the hypotheses, provided prior weights for them, developed potential management strategies, and made predictions about the response of the population to each strategy under each hypothesis. Multi-criteria decision analysis identified a preferred strategy in the face of uncertainty, and analysis of the expected value of information identified how informative each strategy could be. These results provide the foundation for design of an adaptive management program.

Biological Conservation↗
USGS2026

Hierarchical mixture models and high-resolution monitoring data can inform siting and operational strategies to mitigate bat fatalities at wind turbines

Bats provide critical ecosystem services, but bat fatalities due to wind energy development may imperil some bat populations. Statistical models are used to estimate the total fatalities that occur based on carcasses observed during monitoring surveys. Current models often estimate fatalities aggregated across species, time, and/or turbines, but fall short of reliably informing siting and operational collision mitigation strategies that account for species-specific fatality patterns on a fine spatiotemporal scale. We developed a hierarchical mixture model for estimating species-specific covariate effects and total fatalities per species at each turbine on weekly intervals. We applied the model to a high-resolution dataset of bat carcasses found during turbine searches across nineteen wind facilities in Iowa over two years. Our model explains species-specific variation in bat fatalities at individual wind turbines according to turbine proximity to bat habitat, turbine design specifications, seasonal trends, and weather conditions such as nightly air temperature, air pressure, and wind speed. Turbines located on the edge of wind facilities had higher fatalities, and proximity to roosting and foraging habitat accounted for variation in species-specific fatality estimates. These insights into turbine placement effects can inform siting strategies. We also discovered species-specific relationships with average nightly wind speed and air temperature, among other weather conditions, that could inform operational mitigation strategies such as smart curtailment. Our model can transform observations of carcasses found during turbine searches across multiple facilities, years, and variable search efforts into estimates of total fatalities per species associated with species-specific spatial, temporal, and environmental covariate effects.

Ecological Informatics↗
USGS2013

An algorithmic and information-theoretic approach to multimetric index construction

The use of multimetric indices (MMIs), such as the widely used index of biological integrity (IBI), to measure, track, summarize and infer the overall impact of human disturbance on biological communities has been steadily growing in recent years. Initially, MMIs were developed for aquatic communities using pre-selected biological metrics as indicators of system integrity. As interest in these bioassessment tools has grown, so have the types of biological systems to which they are applied. For many ecosystem types the appropriate biological metrics to use as measures of biological integrity are not known a priori. As a result, a variety of ad hoc protocols for selecting metrics empirically has developed. However, the assumptions made by proposed protocols have not be explicitly described or justified, causing many investigators to call for a clear, repeatable methodology for developing empirically derived metrics and indices that can be applied to any biological system. An issue of particular importance that has not been sufficiently addressed is the way that individual metrics combine to produce an MMI that is a sensitive composite indicator of human disturbance. In this paper, we present and demonstrate an algorithm for constructing MMIs given a set of candidate metrics and a measure of human disturbance. The algorithm uses each metric to inform a candidate MMI, and then uses information-theoretic principles to select MMIs that capture the information in the multidimensional system response from among possible MMIs. Such an approach can be used to create purely empirical (data-based) MMIs or can, optionally, be influenced by expert opinion or biological theory through the use of a weighting vector to create value-weighted MMIs. We demonstrate the algorithm with simulated data to demonstrate the predictive capacity of the final MMIs and with real data from wetlands from Acadia and Rocky Mountain National Parks. For the Acadia wetland data, the algorithm identified 4 metrics that combined to produce a -0.88 correlation with the human disturbance index. When compared to other methods, we find this algorithmic approach resulted in MMIs that were more predictive and comprise fewer metrics.

Ecological Indicators↗
USGS2019

Statistical power of dynamic occupancy models to identify temporal change: Informing the North American Bat Monitoring Program

Dynamic occupancy models provide a flexible framework for estimating and mapping species occupancy patterns over space and time for large-scale monitoring programs (e.g., the North American Bat Monitoring Program (NABat), the Amphibian Research and Monitoring Initiative). Challenges for designing surveys using the dynamic occupancy modeling framework include defining appropriate derived trend parameters, and providing usable tools for researchers to conduct project-specific sample size investigations. We present a simulation-based power analysis framework for dynamic occupancy models that allows for the incorporation of the underlying environmental space (i.e., as covariates) within a specific study region to inform sample size estimation. We investigate two definitions of temporal trend: (1) a gradual, sustained (linear or nonlinear) change over a period of many years, and (2) an abrupt increase or decrease between two time periods. We draw upon pilot data collected following NABat protocols to inform assumed data generating values in a demonstration of our approach. Due to the complicated parameter structure of dynamic occupancy models, we emphasize the importance of visualizing simulated changes over time based on different parameter settings prior to conducting a power analysis. Our simulations revealed that the linearity of short-term trends (five years in our investigation) conferred higher power with lower sample size than longer trends where occupancy probabilities approached zero (ten years in our investigation). We provide an example of how to use our tools to conduct customized investigations using questions posed by NABat, and in doing so, we shed light on general guidelines that can be applied to programs monitoring species occupancy for other taxa. Importantly, we created an R package to execute our approach for informing program-, species-, and study-specific investigations aimed at identifying changes in species occupancy.

Ecological Indicators↗
USGS2024

Integrating monitoring and modeling information to develop an indicator of watershed progress toward nutrient reduction goals

Eutrophication has been a major environmental issue in many coastal and inland ecosystems, which is primarily attributed to excessive anthropogenic inputs of nutrients. Restoration efforts have therefore focused on the reduction of watershed nutrient loads, including in the Chesapeake Bay (USA). To facilitate watershed management, watershed models are often developed and used to assess the expected impact of scenarios of past and future management policies and practices and the impact of watershed conditions. However, the level of load reductions estimated using monitoring data often does not match with model predictions, which may cast doubt on the effectiveness of the restoration efforts, the reliability of the model, and the prospect of achieving pre-established reduction goals. To better reconcile such inconsistencies between expectation (i.e., modeling estimates) and reality (i.e., monitoring information), a watershed-wide indicator was developed for the Chesapeake Bay watershed to explicitly quantify the progress toward nutrient reduction goals in the context of the Chesapeake Bay Total Maximum Daily Load (TMDL). Results of the indicator show that since 1995 long-term progress has been made toward the TMDL planning targets for both nitrogen and phosphorus. Specifically, management practices that are implemented and realized (in monitoring data) have been increasing over time, whereas management practices that need to be implemented in the future to meet the goals have been decreasing. In addition, the progress of nutrient reduction toward meeting the goals has varied with source sectors and watershed locations: i.e., point source management has been fully or nearly fully implemented, whereas nonpoint source management has been implemented by 50%-70%. In summary, this indicator, which is largely based on monitoring data, can provide at least four benefits: (1) evaluating the validity of the modeled estimates of nutrient reductions by comparing them to monitoring information; (2) placing the monitored riverine trends into a management context; (3) comparing progress between different nutrient source sectors and watershed locations; and (4) facilitating communication of the progress to the Chesapeake Bay Program Partnership and the public. Although we focus on the indicator development and interpretation for the Chesapeake Bay watershed, the framework can be transferred to watersheds within and beyond this watershed, where similar modeling and monitoring information exists, to gauge expectations on the trajectory and pace of the progress toward meeting restoration goals.

Chesapeake Bay watershed↗