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At least 775 records · Page 43Linked to original sources
USGS2020

Linking monitoring and data analysis to predictions and decisions for the range-wide eastern black rail status assessment

The US Fish and Wildlife Service has initiated a re-envisioned approach for providing decision makers with the best available science and synthesis of that information, called the Species Status Assessment (SSA), for endangered species decision making. The SSA report is a descriptive document that provides decision makers with an assessment of a species’ current status and predicted future status. These analyses support all manner of decisions under the US Endangered Species Act, such as listing, reclassification, recovery planning, etc. Novel scientific analysis and predictive modeling in SSAs could be an important part of rooting species conservation decisions in current data and cutting edge analytical and modeling techniques. Here we describe a novel analysis of available data to assess current condition of eastern black rail across its range in a dynamic occupancy analysis. We used the results of the analysis to develop a site occupancy projection model where the model parameters (initial occupancy, site persistence, colonization) were linked to environmental covariates, such as land management and land cover change (sea-level rise, development, etc.). We used the projection model to predict future conditions under multiple sea-level rise and habitat management scenarios. Occupancy probability and site colonization were low in all analysis units and site persistence was also low, suggesting low resiliency and redundancy currently. Extinction probability was high for all analysis units in all simulated scenarios except one with significant effort to preserve existing habitat, suggesting low future resiliency and redundancy. With results of these data analyses and predictive modeling, the US Fish and Wildlife Service concluded that protections of the Endangered Species Act were warranted for this subspecies.

Endangered Species Research↗
USGS2001

A metadata initiative for global information discovery

The Global Information Locator Service (GILS) encompasses a global vision framed by the fundamental values of open societies. Societal values such as a free flow of information impose certain requirements on the society's information infrastructure. These requirements in turn shape the various laws, policies, standards, and technologies that determine the infrastructure design. A particular focus of GILS is the requirement to provide the means for people to discover sources of data and information. Information discovery in the GILS vision is designed to be decentralized yet coherent, and globally comprehensive yet useful for detailed data. This article introduces basic concepts and design issues, with emphasis on the techniques by which GILS supports interoperability. It explains the practical implications of GILS for the common roles of organizations involved in handling information, from content provider through system engineer and intermediary to searcher. The article provides examples of GILS initiatives in various types of communities: bibliographic, geographic, environmental, and government. ?? 2001 Elsevier Science Inc.

Government Information Quarterly↗
USGS2020

Abundance and productivity of marbled murrelets ( Brachyramphus marmoratus ) off central California during the 2019 breeding season

Marbled murrelets ( Brachyramphus marmoratus ) have been listed as “endangered” by the State of California and “threatened” by the U.S. Fish and Wildlife Service since 1992 in California, Oregon, and Washington. Information regarding marbled murrelet abundance, distribution, population trends, and habitat associations is critical for risk assessment, effective management, evaluation of conservation efficacy, and ultimately, to meet Federal and State recovery efforts for this species. During June–August 2019, the U.S. Geological Survey Western Ecological Research Center continued previously established, long-term (1996–2019), at-sea surveys to estimate abundance and productivity of marbled murrelets in U.S. Fish and Wildlife Service Conservation Zone 6 (San Francisco Bay to Point Sur in central California). Using conventional distance sampling methods, we estimated marbled murrelet abundance using 125 detections of 216 murrelets (mean group size, 1.72) observed on 8 surveys. The abundance estimated for the entire study area using all surveys in 2019 was 404 birds (95-percent confidence interval, 272–601 birds). Estimated abundance from 2019 is comparable to most prior years of study. In 2019, we estimated reproductive productivity (calculated as the hatch-year [HY] to after-hatch-year [AHY] ratio) using three detections of three HY murrelets observed on six surveys. After date-correcting HY and AHY counts to account for birds expected to be absent from the water while inland at nests, the date-corrected juvenile ratio was 0.025±0.020 standard error. We discuss changes in methodologies during 1996–2019 that could be addressed in re-analysis of this long-term dataset. We updated a synthesized database of all Zone 6 marbled murrelet survey data since 1999 with 2019 data to allow scientists and managers to evaluate established survey methods and assess trends in abundance and productivity estimates.

California↗
USGS2015

Towards automating measurements and predictions of Escherichia coli concentrations in the Cuyahoga River, Cuyahoga Valley National Park, Ohio, 2012–14

Nowcasts are systems that can provide estimates of the current bacterial water-quality conditions based on predictive models using easily-measured, explanatory variables; nowcasts can provide the public with the information to make informed decisions on the risk associated with recreational activities in natural water bodies. Previous studies on the Cuyahoga River within Cuyahoga Valley National Park (CVNP) have found that predictive models can be used to provide accurate assessments of the recreational water quality. However, in order to run the previously developed nowcasts for CVNP, manual collection and processing of samples is required on a daily basis to acquire the required explanatory variable data (laboratory-measured turbidity). The U.S. Geological Survey and the National Park Service collaborated to develop a more automated approach to provide more timely results to park visitors regarding the recreational water quality of the river. In May 2012, an in-stream water-quality sensor was installed by the U.S. Geological Survey at Jaite, Ohio (a site centrally located in CVNP on the Cuyahoga River), to provide near-real-time measurements of turbidity and water temperature. To transition from methods used during previous studies at CVNP, a relation between laboratory- and in-stream measured turbidity was developed after the recreational season of 2012. During the recreational seasons of 2012 through 2014, discrete water samples were collected and processed to determine Escherichia coli ( E. coli ) concentrations at Jaite and one site upstream of Jaite (Lock 29) within CVNP. Predictive models, using in-stream turbidity measurements, were developed for the recreational seasons of 2013 and 2014 to estimate recreational water quality in regards to Ohio’s single-sample water-quality standard for primary-contact recreation. A computer program was developed to manage the nowcasts by running the predictive models and posting the results to a publicly accessible Web site daily by 9 a.m. The nowcasts were able to correctly predict E. coli concentrations above or below the water-quality standard at Jaite for 79 percent of the samples compared with the measured concentrations. In comparison, the persistence model (using the previous day’s sample concentration) correctly predicted concentrations above or below the water-quality standard in only 68 percent of the samples. To determine if the Jaite nowcast could be used for the stretch of the river between Lock 29 and Jaite, the model predictions for Jaite were compared with the measured concentrations at Lock 29. The Jaite nowcast provided correct responses for 77 percent of the Lock 29 samples, which was a greater percentage than the percentage of correct responses (58 percent) from the persistence model at Lock 29.

Ohio↗
USGS2026

Morphometric properties of the CP-21 landing site on the Moon at Mons Gruithuisen Gamma

Characterizing terrain surface properties is an essential step in assessing the feasibility of landing successfully at a location on a planetary surface. Slopes and terrain ruggedness index (TRI) values derived from high-resolution (2 m pixel −1 ) digital terrain models provided important constraints in selecting the landing site for the upcoming Payloads and Research Investigations on the Surface of the Moon program as part of the Commercial Lunar Payload Services task order CP-21 mission. The selected landing site needed to balance safety requirements with the ability to achieve the science and exploration goals of the Lunar Vulkan Imaging and Spectroscopy Explorer payload. In this study, we compare several morphometric parameters in the context of the CP-21 landing site on Mons Gruithuisen Gamma, or the Gamma dome, and quantify the information they convey about lunar surface properties to assess their utility for future landing site evaluation. TRI was found to be a useful metric for assessing landing site safety. Metrics that better decouple slope and surface roughness, the vector ruggedness measure and the standard deviation of slope, provided additional information about surface characteristics and textures such as the degree to which roughness is isotropic.

Planetary Science Journal↗
USGS2013

Assessing the risk of nitrogen deposition to natural resources in the Four Corners area

Nitrogen (N) deposition in the western U.S. is on the rise and is already dramatically affecting terrestrial ecosystems. For example, N deposition has repeatedly been shown to lower air and water quality, increase greenhouse gas emissions, alter plant community composition, and significantly modify fire regimes. Accordingly, the effects of N deposition represent one of our largest environmental challenges and make difficult the National Park Service’s (NPS) important mission to “preserve the scenery and the natural and historic objects and the wildlife… unimpaired for the enjoyment of future generations”. Due to increased population growth and energy development (e.g., natural gas wells), the Four Corners region has become a notable ‘hotspot’ for N deposition. However, our understanding of how increased N deposition will affect these unique ecosystems, as well as how much deposition is actually occurring, remains notably poor. Here we used a multi-disciplinary approach to gathering information in an effort to help NPS safeguard the Four Corners national parks, both now and into the future. We applied modeling, field, and laboratory techniques to clarify current N deposition gradients and to help elucidate the ecosystem consequences of N deposition to the national parks of the Four Corners area. Our results suggest that NOx deposition does indeed represent a significant source of N to Mesa Verde National Park and, as expected, N deposition significantly affects coupled biogeochemical cycling (N, carbon, and phosphorus) of these landscapes. We also found some surprising results. For example, perhaps due to the low nutrient availability in these (and other) dryland ecosystems, although most other research suggests that adding N reduces N fixation rates, N additions did not consistently reduce natural N inputs via biological N2 fixation at our dryland sites. While the timeline of this pilot project is too brief to elucidate all the potential insight from the approach utilized here (e.g., we have fertilization plots to explore how N deposition affects Bromus tectorum invasion that will surely yield provoking results), we plan to continue this exciting line of questioning and expect further insight to be forthcoming.

Arches National Park, Canyonland National Park, Me↗
USGS2015

Economic assessment of the use value of geospatial information

Geospatial data inform decision makers. An economic model that involves application of spatial and temporal scientific, technical, and economic data in decision making is described. The value of information (VOI) contained in geospatial data is the difference between the net benefits (in present value terms) of a decision with and without the information. A range of technologies is used to collect and distribute geospatial data. These technical activities are linked to examples that show how the data can be applied in decision making, which is a cultural activity. The economic model for assessing the VOI in geospatial data for decision making is applied to three examples: (1) a retrospective model about environmental regulation of agrochemicals; (2) a prospective model about the impact and mitigation of earthquakes in urban areas; and (3) a prospective model about developing private–public geospatial information for an ecosystem services market. Each example demonstrates the potential value of geospatial information in a decision with uncertain information.

ISPRS International Journal of Geo-Information↗
USGS2002

Distribution of grizzly bears in the Greater Yellowstone Ecosystem, 1990-2000

The Yellowstone grizzly bear ( Ursus arctos horribilis ) has been expanding its range during the past 2 decades and now occupies historic habitats that had been vacant. A current understanding of the distribution of grizzly bears within the ecosystem is useful in the recovery process and to help guide the state and federal land management agencies and state wildlife agencies of Idaho, Wyoming, and Montana as they prepare management plans. We used kernel estimators to develop distribution maps of occupied habitats based on initial sightings of unduplicated females (n = 300) with cubs-of-the-year, information from radiomarked bears (n = 105), and locations of conflicts, confrontations, and mortalities (n = 1,235). Although each data set was constrained by potential sampling bias, together they provided insight into areas within the Greater Yellowstone Ecosystem (GYE) currently occupied by grizzly bears. The current distribution (1990-2000) extends beyond the recovery zone identified in the U.S. Fish and Wildlife Service (USFWS) Recovery Plan. Range expansion is particularly evident in the southern portion of the ecosystem in Wyoming. A comparison of our results from the 1990s to previously published distribution maps show an approximate increase in occupied habitat of 48% and 34% from the 1970s and 1980s, respectively. We discuss data biases and problems implicit to the analysis.

Wyoming↗
USGS2014

Fitting statistical distributions to sea duck count data: implications for survey design and abundance estimation

Determining appropriate statistical distributions for modeling animal count data is important for accurate estimation of abundance, distribution, and trends. In the case of sea ducks along the U.S. Atlantic coast, managers want to estimate local and regional abundance to detect and track population declines, to define areas of high and low use, and to predict the impact of future habitat change on populations. In this paper, we used a modified marked point process to model survey data that recorded flock sizes of Common eiders, Long-tailed ducks, and Black, Surf, and White-winged scoters. The data come from an experimental aerial survey, conducted by the United States Fish & Wildlife Service (USFWS) Division of Migratory Bird Management, during which east-west transects were flown along the Atlantic Coast from Maine to Florida during the winters of 2009–2011. To model the number of flocks per transect (the points), we compared the fit of four statistical distributions (zero-inflated Poisson, zero-inflated geometric, zero-inflated negative binomial and negative binomial) to data on the number of species-specific sea duck flocks that were recorded for each transect flown. To model the flock sizes (the marks), we compared the fit of flock size data for each species to seven statistical distributions: positive Poisson, positive negative binomial, positive geometric, logarithmic, discretized lognormal, zeta and Yule–Simon. Akaike’s Information Criterion and Vuong’s closeness tests indicated that the negative binomial and discretized lognormal were the best distributions for all species for the points and marks, respectively. These findings have important implications for estimating sea duck abundances as the discretized lognormal is a more skewed distribution than the Poisson and negative binomial, which are frequently used to model avian counts; the lognormal is also less heavy-tailed than the power law distributions (e.g., zeta and Yule–Simon), which are becoming increasingly popular for group size modeling. Choosing appropriate statistical distributions for modeling flock size data is fundamental to accurately estimating population summaries, determining required survey effort, and assessing and propagating uncertainty through decision-making processes.

Statistical Methodology↗
USGS2019

National earthquake information center strategic plan, 2019–23

Executive Summary Damaging earthquakes occur regularly around the world; since the turn of the 20th century, hundreds of earthquakes have caused significant loss of life and (or) millions of dollars or more in economic losses. While most of these did not directly affect the United States and its Territories, by studying worldwide seismicity we can better understand how to mitigate the effects of earthquakes when they do occur within U.S. borders. Within the U.S. Government, this mandate falls on the U.S. Geological Survey (USGS) National Earthquake Information Center (NEIC), which has the statutory responsibility for monitoring and reporting on earthquakes domestically and globally. The NEIC has been operating since 1966, and throughout its history has been recognized as a world leader for earthquake information. For much of this time, NEIC has been cooperating with a number of regional seismic networks (RSNs) which operate in areas of heightened seismicity in the United States. In 2000, the Advanced National Seismic System (ANSS) was founded as a cooperative umbrella for earthquake-related data collection, analysis, and dissemination in the United States, thereby promoting advanced interoperability between the NEIC and RSN partners. The NEIC also cooperates and coordinates with dozens of global seismic networks. At present (2019), NEIC acquires real-time waveform data from more than 2,000 seismic stations worldwide, contributed from more than 130 seismic networks. Since 2006, the NEIC has operated on a 24-hour, 7-days per week (24/7) basis, and reports on about 30,000 earthquakes per year. Soon after the occurrence of a significant global earthquake, notifications are issued to government representatives, aid agencies, the press, and members of the general public by the Earthquake Notification Service (ENS), electronic feeds, and through the USGS Earthquake Hazards Program (EHP) website. Event-specific web pages provide detailed source parameter information outlining the location and magnitude of the earthquake, including more detailed source characteristics like moment magnitude and focal mechanisms and finite fault solutions. Further, NEIC produces a suite of real-time situational awareness products, including ShakeMap, ShakeCast, Did-You-Feel-It? (DYFI?), and Prompt Assessment of Global Earthquakes for Response (PAGER), to characterize the shaking resulting from the earthquake and the impact it is likely to have on nearby populations and infrastructure. All of these products are ultimately archived in the ANSS Comprehensive Catalog (ComCat), hosted and served by the NEIC. The NEIC also pursues an active research program to improve its ability to characterize earthquakes and understand their hazards. These efforts are all aimed at mitigating the risks of earthquakes to humankind. To maintain its prominent position in earthquake monitoring, the NEIC must continue to evolve, concurrently improving its operations and 24/7 robustness, streamlining services and infrastructure, and keeping pace with research and innovation in the field of seismology. This document outlines how the NEIC might best achieve such goals, by describing specific avenues and opportunities for development in the next five years (2019–23). Several key areas of operational and research focus are identified in this plan as being of the highest importance. First, NEIC must finalize improvements to its regional monitoring capabilities, including the implementation of a variety of improved earthquake detection and association algorithms. One of the most exciting avenues of recent research expansion in earthquake monitoring has involved the use of machine learning; NEIC must explore the benefits of machine learning for improved earthquake detection and source characterization. NEIC also needs to address issues related to the timeliness of earthquake information, exploring the benefits of distributing information as it becomes available, rather than when certain quality criteria are met. To that end, the incorporation of real-time Global Positioning System (GPS) data into the NEIC operational workflow will help improve the speed and accuracy of information for moderate-to-large earthquakes. Finally, NEIC should explore how to further expand and improve the quality and content of the products served during earthquake response efforts, including the generation of new earthquake sequence-specific products, adding an evolutionary component to earthquake information, and continued improvements to earthquake impact products.

Circular↗
USGS2018

Abundance and productivity of marbled murrelets (Brachyramphus marmoratus) off central California during the 2017 breeding season

Marbled murrelets ( Brachyramphus marmoratus ) have been listed as “Endangered” by the State of California and “Threatened” by the U.S. Fish and Wildlife Service since 1992 in California, Oregon, and Washington. Information regarding marbled murrelet abundance, distribution, population trends, and habitat associations is critical for risk assessment, effective management and evaluation of conservation efficacy, and ultimately to meet Federal- and State-mandated recovery efforts for this species. During June–August 2017, the U.S. Geological Survey Western Ecological Research Center continued previously established, long-term (1999–2016), at-sea surveys to estimate abundance and productivity of marbled murrelets in U.S. Fish and Wildlife Service Conservation Zone 6 (central California—San Francisco Bay to Monterey Bay). Using conventional distance sampling methods, we estimated marbled murrelet abundance using 189 detections of 321 individuals observed on nine unique surveys. The abundance estimated for the entire study area using all surveys in 2017 was 530 birds (95-percent confidence interval, 384–732 birds). Estimated abundance from 2017 is comparable to most prior years of study, except for 2008 and 2015, which had anomalously low abundances. We estimated productivity (calculated as the hatch-year [HY] to after-hatch-year [AHY] ratio) in 2017 using three detections of three individuals observed in six surveys. After date-correcting HY and AHY counts to account for birds expected to be absent from the water while inland at nests, the date-corrected juvenile ratio was 0.022 ± 0.014 standard error. We created a synthesized database of all marbled murrelet survey data from 1999 to 2017 to allow scientists and managers to evaluate established survey methods and assess trends in abundance and productivity estimates. Future modifications of survey design could help reduce variance in abundance estimation.

California↗
USGS2019

Abundance and productivity of marbled murrelets (Brachyramphus marmoratus) off central California during the 2018 breeding season

Executive Summary Marbled murrelets ( Brachyramphus marmoratus ) have been listed as “endangered” by the State of California and “threatened” by the U.S. Fish and Wildlife Service since 1992 in California, Oregon, and Washington. Information regarding marbled murrelet abundance, distribution, population trends, and habitat associations is critical for risk assessment, effective management, evaluation of conservation efficacy, and ultimately, to meet Federal- and State-mandated recovery efforts for this species. During June–August 2018, the U.S. Geological Survey Western Ecological Research Center continued previously established, long-term (1999–2018), at-sea surveys to estimate abundance and productivity of marbled murrelets in U.S. Fish and Wildlife Service Conservation Zone 6 (San Francisco Bay to Point Sur in central California). Using conventional distance sampling methods, we estimated marbled murrelet abundance using 137 detections of 227 individuals observed on 9 surveys. The abundance estimated for the entire study area using all surveys in 2018 was 370 birds (95-percent confidence interval, 250–546 birds). Estimated abundance from 2018 is comparable to most prior years of study, except for 2001–03, when greater abundances were estimated. In 2018, we estimated reproductive productivity (calculated as the hatch-year [HY] to after-hatch-year [AHY] ratio) using four detections of four HY individuals observed on six surveys. After date-correcting HY and AHY counts to account for birds expected to be absent from the water while inland at nests, the date-corrected juvenile ratio was 0.047 ± 0.024 standard error. We updated a synthesized database of all Zone 6 marbled murrelet survey data since 1999 with 2018 data to allow scientists and managers to evaluate established survey methods and assess trends in abundance and productivity estimates.

California↗
USGS2020

Social Values for Ecosystem Services, version 4.0 (SolVES 4.0)—Documentation and user manual

The geographic information system tool, Social Values for Ecosystem Services (SolVES), was developed to incorporate quantified and spatially explicit measures of social values into ecosystem service assessments. SolVES 4.0 provides an open-source version of SolVES, which was designed to assess, map, and quantify the social values of ecosystem services. Social values—the perceived, nonmarket values the public ascribes to ecosystem services, particularly cultural services, such as aesthetics and recreation—can be evaluated for various stakeholder groups. These groups are distinguishable by factors such as their attitudes and preferences regarding public uses (for example, motorized recreation and logging). As with previous versions, SolVES 4.0 derives a quantitative 10-point, social-values metric—the value index—from a combination of spatial and nonspatial responses to public value and preference surveys. The tool also calculates metrics characterizing the underlying environment, such as average distance to water and dominant landcover. SolVES 4.0 has been developed with Python using a QGIS user interface and a PostgreSQL database for required data. SolVES is integrated with Maxent maximum entropy modeling software to generate more complete social-value maps and offer robust statistical models describing the relation between the value index and explanatory environmental variables. A model’s goodness of fit to a primary study area and its potential performance in transferring social values to similar areas using value-transfer methods can be evaluated. SolVES 4.0 provides an improved open-source, public-domain tool for decision makers and researchers to evaluate the social values of ecosystem services and to facilitate discussions among diverse stakeholders regarding the tradeoffs among ecosystem services in a variety of biophysical and social contexts including mountain, forest, coastal, riparian, agricultural, and urban environments around the globe.

Techniques and Methods↗
USGS1994

Ecological perspective: Linking ecology, GIS, and remote sensing to ecosystem management

Awareness of significant human impacts on the ecology of Earth's landscapes is not new (Thomas 1956). Over the past decade (Forman and Godron 1986, Urban et a1. 1987) applications of geographic information systems (GIS) and remote sensing technologies have supported a rapid rise in landscape.stale research. The heightened recognition within the research community of the ecological linkages between local sites and larger spatial scales has spawned increasing calls for more holistic management of landscapes (Noss 1983, Harris 1984, Risser 1985, Norse et al. 1986, Agee and Johnson 1988, Franklin 1989, Brooks and Grant 1992, Endangered Species Update-Special Issue 1993, Crow 1994, Grumbine 1994). As a result agencies such as the U.S. Forest Service, U.S. Fish and Wildlife Service, and National Park Service are now converging on "ecosystem management" as a new paradigm to sustainably manage wildlands and maintain biodiversity. However, as this transition occurs, several impediments to implementation of this new paradigm persist, including (1) significant uncenainty among many land managers about the definition and goals of ecosystem management, (2) inadequate ecological information on the past and present processes and structural conditions of target ecosystems, (3) insufficient experience on the part of land managers with the rapidly diversifying array of GIS and remote sensing tools to effectively use them to support ecology-based land management, and (4) a paucity of intimate, long-term relationships between people (including land managers) and the particular landscape communities to which they belong. This chapter provides an ecological perspective on these issues as applied to ecosystem management in a southwestern U.S. landscape.

Book chapter↗
USGS2020

InFish: A professional network to promote global conservation and responsible use of inland fish

Inland fishes and fisheries make substantial contributions to individuals, society, and the environment in a changing global landscape that includes climate, water allocations, and societal changes. However, current limitations to valuing the services provided by inland fish and their fisheries often leaves them out of key decision‐making discussions. InFish is a voluntary professional network with over 120 members from over 50 organizations in over 20 countries that seeks to address challenges facing inland fish through novel approaches and international collaborations. InFish fosters opportunities to share knowledge, pursue proposals, publications, and conference‐related events focused on inland fisheries. InFish has become a source of inland fisheries expertise, working collectively towards global conservation and sustainable use of inland fish through informing scientifically sound management practices. As such, InFish may serve as a model network for other natural resource challenges now and into the future.

Fisheries Magazine↗
USGS2025

Decision support tools for brown pelican management in the northern Gulf of America (Gulf of Mexico)

Management plans with clear priorities can help to achieve brown pelican Pelecanus occidentalis conservation objectives in the northern Gulf of America (Gulf of Mexico). Efforts to establish clear priorities can be hindered by information gaps, especially those related to the uncertainty associated with changing conditions that influence brown pelican populations. We addressed these gaps by creating a model that uses island-specific conditions (e.g., geomorphology; predator-related conditions; brown pelican terrestrial nesting, roosting, and loafing habitats) to predict the nest count as a proxy for breeding pairs on the island. We used the model and 2000–2015 brown pelican nest count data to estimate if breeding pair targets that we identified or estimated for 10 U.S Fish and Wildlife Service Gulf Coast Biological Planning Units were met while accounting for uncertainty. Our results indicate that breeding pair targets were met in 7 of the 10 units by existing conditions. Our confidence in judging nest deficits tended to decrease from west to east because the model over-predicted total nests in the east Gulf Coast. Using an island from our data, we show how the model could be used to quantify the uncertainty of nest count outcomes under simulated changes in island conditions. The model indicated that the island's existing conditions most probably result in nests (probability = 0.51) and that increasing the area of nesting habitat (shrubs) could increase the probability of nests from 49% to 70%. Increasing shrub habitat in the model also increased nest count uncertainty by 60%, but this was due to a greater probability of larger nest counts. Our model suggests that nest count uncertainty could be reduced by improving data on island size, shrub area, and predator presence, depending on the unit and how isolated the island is from the mainland. These tools could help managers understand and incorporate the uncertainty associated with creating island conditions that are intended to help achieve brown pelican conservation objectives.

Alabama, Florida, Louisiana, Mississippi, Texas↗
USGS2019

Let’s agree to disagree: Comparing auto-acoustic identification programs for northeastern bats

With the declines in abundance and changing distribution of white-nose syndrome–affected bat species, increased reliance on acoustic monitoring is now the new “normal.” As such, the ability to accurately identify individual bat species with acoustic identification programs has become increasingly important. We assessed rates of disagreement between the three U.S. Fish and Wildlife Service–approved acoustic identification software programs (Kaleidoscope Pro 4.2.0, Echoclass 3.1, and Bat Call Identification 2.7d) and manual visual identification using acoustic data collected during summers from 2003 to 2017 at Fort Drum, New York. We assessed the percentage of agreement between programs through pairwise comparisons on a total nightly count level, individual file level (e.g., individual echolocation pass call file), and grouped maximum likelihood estimate level (e.g., probability values that a species is misclassified as present when in fact it is absent) using preplanned contrasts, Akaike Information Criterion, and annual confusion matrices. Interprogram agreement on an individual file level was low, as measured by Cohen's Kappa (0.2–0.6). However, site-night level pairwise comparative analysis indicated that program agreement was higher (40–90%) using single season occupancy metrics. In comparing analytical outcomes of our different datasets (i.e., how comparable programs and visual identification are regarding the relationship between environmental conditions and bat activity), we determined high levels of congruency in the relative rankings of the model as well as the relative level of support for each individual model. This indicated that among individual software packages, when analyzing bat calls, there was consistent ecological inference beyond the file-by-file level at the scales used by managers. Depending on objectives, we believe our results can help users choose automated software and maximum likelihood estimate thresholds more appropriate for their needs and allow for better cross-comparison of studies using different automated acoustic software.

Journal of Fish and Wildlife Management↗
USGS2010

Southeast Regional Assessment Project for the National Climate Change and Wildlife Science Center, U.S. Geological Survey

The Southeastern United States spans a broad range of physiographic settings and maintains exceptionally high levels of faunal diversity. Unfortunately, many of these ecosystems are increasingly under threat due to rapid human development, and management agencies are increasingly aware of the potential effects that climate change will have on these ecosystems. Natural resource managers and conservation planners can be effective at preserving ecosystems in the face of these stressors only if they can adapt current conservation efforts to increase the overall resilience of the system. Climate change, in particular, challenges many of the basic assumptions used by conservation planners and managers. Previous conservation planning efforts identified and prioritized areas for conservation based on the current environmental conditions, such as habitat quality, and assumed that conditions in conservation lands would be largely controlled by management actions (including no action). Climate change, however, will likely alter important system drivers (temperature, precipitation, and sea-level rise) and make it difficult, if not impossible, to maintain recent historic conditions in conservation lands into the future. Climate change will also influence the future conservation potential of non-conservation lands, further complicating conservation planning. Therefore, there is a need to develop and adapt effective conservation strategies to cope with the effects of climate and landscape change on future environmental conditions. Congress recognized this important issue and authorized the U.S. Geological Survey (USGS) National Climate Change and Wildlife Science Center (NCCWSC; http://nccw.usgs.gov/) in the Fiscal Year 2008. The NCCWSC will produce science that will help resource management agencies anticipate and adapt to climate change impacts to fish, wildlife, and their habitats. With the release of Secretarial Order 3289 on September 14, 2009, the mandate of the NCCWSC was expanded to address climate change-related impacts on all Department of the Interior (DOI) resources. The NCCWSC will establish a network of eight DOI Regional Climate Science Centers (RCSCs) that will work with a variety of partners to provide natural resource managers with tools and information that will help them anticipate and adapt conservation planning and design for projected climate change. The forecasting products produced by the RCSCs will aid fish, wildlife, and land managers in designing suitable adaptive management approaches for their programs. The DOI also is developing Landscape Conservation Cooperatives (LCCs) as science and conservation action partnerships at subregional scales. The USGS is working with the Southeast Region of the U.S. Fish and Wildlife Service (FWS) to develop science collaboration between the future Southeast RCSC and future LCCs. The NCCWSC Southeast Regional Assessment Project (SERAP) will begin to develop regional downscaled climate models, land cover change models, regional ecological models, regional watershed models, and other science tools. Models and data produced by SERAP will be used in a collaborative process between the USGS, the FWS (LCCs), State and federal partners, nongovernmental organizations, and academia to produce science at appropriate scales to answer resource management questions. The SERAP will produce an assessment of climate change, and impacts on land cover, ecosystems, and priority species in the region. The predictive tools developed by the SERAP project team will allow end users to better understand potential impacts of climate change and sea level rise on terrestrial and aquatic populations in the Southeastern United States. The SERAP capitalizes on the integration of five existing projects: (1) the Multi-State Conservation Grants Program project "Designing Sustainable Landscapes," (2) the USGS multidisciplinary Science Thrust project "Water Availability for Ecological Needs," (3) the USGS Southeast Pilot Project "Climate Change in the Southeastern U.S. and its Impacts on Bird Distributions and Habitats," (4) a sea-level rise impacts study envisioned jointly with the National Oceanic and Atmospheric Administration (NOAA), and (5) two USGS sea-level rise impact assessment projects that address inundation hazards and provide probabilistic forecasts of coastal geomorphic change. The SERAP will expand on these existing projects and include the following tasks, which were initiated in summer 2009: * Regionally downscaled probabilistic climate-change projections * Integrated coastal assessment * Integrated terrestrial assessment * Multi-resolution assessment of potential climate change effects on biological resources: aquatic and hydrologic dynamics * Optimal conservation strategies to cope with climate change The SERAP seeks to formally integrate these tasks to aid conservation planning and design so that ecosystem management decisions can be optimized for providing desirable outcomes across a range of species and environments. The following chapters detail SERAP's efforts in providing a suite of regional climate, watershed, and landscape-change analyses and develop the interdisciplinary framework required for the biological planning phases of adaptive management and strategic conservation. The planning phase will include the identification of conservation alternatives, development of predictive models and decision support tools, and development of a template to address similar challenges and goals in other regions. The project teams will explore and develop ways to link the various ecological models arising from each component. The SERAP project team also will work closely with members of the LCCs and other partnerships throughout the life of the project to ensure that the objectives of the project meet resources mangers needs in the Southeast.

Open-File Report↗