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At least 109 records · Page 6Linked to original sources

Evaluation of internet surveys for conducting statewide angler surveys in South Dakota

Stakeholder information is critical for effective fisheries management. Agencies have traditionally used infrequent mail surveys to collect human dimensions data. Internet surveys provide cost savings, but are associated with caution due to data quality issues. To improve study validity, survey access can be controlled using email invitations, but because these addresses are voluntary, results may not be applicable to the entire population. Additionally, internet surveys typically have lower response rates than mail surveys, thus, a greater potential for nonresponse bias. To identify potential coverage and nonresponse biases in information typically collected by statewide angler surveys, we emailed a link to a web-based survey to all anglers who provided South Dakota Game, Fish and Parks (SDGFP) with an email address at the end of the 2011 and 2012 fishing seasons (December 31). Next, we mailed the same questionnaire to both a random sample of anglers not providing an email address and a sample of non-respondents to the internet survey. Internet survey results were similar to both mail surveys for variables SDGFP typically monitors via statewide angler surveys with the exception of slightly over representing male anglers and younger anglers; however, these slight biases can be adjusted by weighting procedures. Results from this study were used by SDGFP to design a web-based, annual statewide angler survey that would collect angler information statistically comparable to information collected by traditional statewide mail surveys.

South Dakota

Long-term impacts of the Exxon Valdez oil spill on sea otters, assessed through age-dependent mortality patterns

We use age distributions of sea otters ( Enhydra lutris ) found dead on beaches of western Prince William Sound, Alaska, between 1976 and 1998 in conjunction with time-varying demographic models to test for lingering effects from the 1989 Exxon Valdez oil spill. Our results show that sea otters in this area had decreased survival rates in the years following the spill and that the effects of the spill on annual survival increased rather than dissipated for older animals. Otters born after the 1989 spill were affected less than those alive in March 1989, but do show continuing negative effects through 1998. Population-wide effects of the spill appear to have slowly dissipated through time, due largely to the loss of cohorts alive during the spill. Our results demonstrate that the difficult-to-detect long-term impacts of environmental disasters may still be highly significant and can be rigorously analyzed by using a combination of population data, modeling techniques, and statistical analyses.

Proceedings of the National Academy of Sciences of

Spread of hybridization between native westslope cutthroat trout, Oncorhynchus clarki lewisi, and nonnative rainbow trout, Oncorhynchus mykiss

We examined spatial and temporal patterns of hybridization between native westslope cutthroat trout, Oncorhynchus clarki lewisi , and nonnative rainbow trout, O. mykiss , in streams of the Flathead River system in Montana, U.S.A. We detected hybridization in 24 of 42 sites sampled from 1998 to 2001. We found new Oncorhynchus mykiss introgression in seven of 11 sample populations that were determined to be nonhybridized in 1984. Patterns of spatial autocorrelation and linkage disequilibrium indicated that hybridization is spreading among sites and is advancing primarily via post-F 1 hybrids. Although hybridized populations were distributed widely throughout the study area, the genetic contribution from O. mykiss decreased with increasing upstream distance from the Flathead River mainstem, suggesting that O. mykiss introgression is spreading in an upstream direction. The spread of hybridization may be constrained more by demographic than by environmental factors, given that ( i ) hybridized populations generally encompassed the range of environmental variability in nonhybridized populations, and ( ii ) hybridization status was more strongly associated with neighborhood statistics than measured environmental gradients.

Montana

The art and science of weed mapping

Land managers need cost-effective and informative tools for non-native plant species management. Many local, state, and federal agencies adopted mapping systems designed to collect comparable data for the early detection and monitoring of non-native species. We compared mapping information to statistically rigorous, plot-based methods to better understand the benefits and compatibility of the two techniques. Mapping non-native species locations provided a species list, associated species distributions, and infested area for subjectively selected survey sites. The value of this information may be compromised by crude estimates of cover and incomplete or biased estimations of species distributions. Incorporating plot-based assessments guided by a stratified-random sample design provided a less biased description of non-native species distributions and increased the comparability of data over time and across regions for the inventory, monitoring, and management of non-native and native plant species.

Environmental Monitoring and Assessment

Guidelines to classification and nomenclature of Arabian felsic plutonic rocks

Well-defined procedures for classifying the felsic plutonic rocks of the Arabian Shield on the basis of petrographic, chemical and lithostratigraphic criteria and mineral-resource potential have been adopted and developed in the Saudi Arabian Deputy Ministry for Mineral Resources over the past decade. A number of problems with conventional classification schemes have been identified and resolved; others, notably those arising from difficulties in identifying precise mineral compositions, continue to present difficulties. The petrographic nomenclature used is essentially that recommended by the International Union of Geological Sciences. Problems that have arisen include the definition of: (1) rocks with sodic, zoned or perthitic feldspar, (2) trondhjemites, and (3) alkali granites. Chemical classification has been largely based on relative molar amounts of alumina, lime and alkalis, and the use of conventional variation diagrams, but pilot studies utilizing univariate and multivariate statistical techniques have been made. The classification used in Saudi Arabia for stratigraphic purposes is a hierarchy of formation-rank units, suites and super-suites as defined in the Saudi Arabian stratigraphic code. For genetic and petrological studies, a grouping as ‘associations’ of similar and genetically related lithologies is commonly used. In order to indicate mineral-resource potential, the felsic plutons are classed as common, precursor, specialized or mineralized, in order of increasing exploration significance.

Journal of African Earth Sciences

Estimates of global surface water dynamics harnessing near real-time land cover observations and open science geospatial capabilities

Spatio-temporal changes to our world’s surface water resources are escalating. Translating how these changes impact communities and ecosystems requires time-varying data of Global Surface Water Extents (GSWE). Traditionally, GSWE mapping has been limited to static estimates, with recent efforts focusing on annual averages, frequency and occurrence of long-term variations. Building upon these foundational capabilities, we harnessed remotely sensed Sentinel-2 based near real-time Dynamic World (DW) land cover products to produce the first-of-its-kind 10 m resolution GSWE dataset representing 2015–2023. Our dataset estimated 2.5 million km 2 of permanent waters and 8 million km 2 of seasonal waters worldwide. Comparing our Sentinel-2 based data to contemporary Landsat-based GSWE, we observed that our data mapped less water within the >50% probability of occurrence range, suggesting a lower presence of open permanent water especially in high latitudes, deviating from what we previously learnt from Landsat data. Statistical analysis compared to well-established observational products and widely used GSWE datasets across some of the world’s most ecologically significant regions, including Pantanal in South America and Haor in South Asia, supports the overall physical realism of our data in predicting global open surface water dynamics. Our key contribution is a prototype Open Science operational framework that extracts routinely available DW products, runs geospatial analytics, and creates actionable water information for educators, researchers, and stakeholders at any scale of practical interest. We present examples of this operational capability through instant mapping of flood in Spain and drought in Lake Urmia, Central Asia, frequent monitoring of river extent changes at the Ganges–Brahmaputra confluence, and above all, interoperability with other existing GSWE applications.

Environmental Research Letters

Using the Lomb-Scargle method for wave statistics from gappy time series

Sandwich Town Neck Beach in Sandwich, MA, has experienced substantial erosion and has been the subject of efforts by the town and private landowners to limit the sand loss. Erosion has been particularly dramatic in the past five years with the loss of dwellings. Sandwich's nourishment efforts presented a unique opportunity for scientists at the U.S. Geological Survey Woods Hole Coastal and Marine Science Center to monitor beach morphology and to test new technologies and techniques such as geo-referenced drone imaging. Two bottom lander deployments were performed in Cape Cod Bay at a location that was key to model the fate of waves at Sandwich Town Neck Beach and to support the study of beach morphological evolution. The study period was after the town nourished the beach and during a time when several intense winter storms reshaped the beach and removed much of the nourished sand. A TRDI Workhorse Sentinel V ADCP was used for both deployments. For wave bursts, the instruments collected 2048 samples at 2 Hz every hour. The first deployment during the winter of 2016 returned good quality data. The second deployment during the following winter had gaps throughout the time series from a wiring problem in the external battery pack. The timing of the gaps was random, the duration approximately 100 s. While most of the bursts started at the top of each hour, many had 1-3 gaps within. Time series data with random gaps are problematic for computing spectral density, and thus, wave statistics. This kind of situation is familiar in other scientific disciplines such as astrophysics [1], where techniques exist to find stationary signals in sparse data. One of these methods is the Lomb-Scargle technique for computing periodograms. The most useful feature of the Lomb-Scargle (LS) method is that it allows the spectral analysis of incomplete records, without having to manipulate the record to extrapolate from or replace missing data. We compared the effectiveness of LS against common methods of averaging Fourier transforms such as a simple un-windowed Fast Fourier transform (FFT), Welch's method, and TRDI's Wavesmon software; methods that are commonly used in oceanography for non-gappy data. Synthetic data series that have been artificially modified to introduce gaps were used to evaluate the performance of each method. The LS approach was able to recover spectral density even with several 100-s gaps present. The method was applied here to the gappy and non-gappy data from both Sandwich deployments, and wave statistics were obtained and compared to the wave-buoy data. LS was used to process data that contains gaps that was rejected by Wavesmon, which was approximately 39% of the dataset. Significant wave height and peak period from LS compared well with buoy data. Mean period computed on gappy data using LS produced values biased low, compared with other methods when gaps were filled with the mean value. The LS technique has potential to uncover low-frequency signals such as infragravity waves from gappy records where the non-gappy segments are not long enough to resolve them. It has potential to unlock new information from older data sets.

Massachusetts

Simultaneous autoregressive (SAR) model

Simultaneous autoregressive (SAR) models are useful for accommodating various forms of dependence among data that have discrete support in a space of interest. These models are often specified hierarchically as mixed-effects regression models with first-moment structure controlled by a conventional linear regression term and second-moment structure induced by correlated random effects. In their general form, SAR models resemble conditional autoregressive (CAR) models, and can be made equivalent but are often parameterized differently. Importantly, SAR models can be specified by simultaneously regressing a discrete spatial process on itself. Thus, they allow one to construct statistical models for processes with directional graphical properties that pertain to data generating mechanisms. Most commonly SAR models have been used to account for structure among data with areal spatial support in applications involving ecology, epidemiology, sociology, and environmental science.

Book chapter

Predicting the potential distribution of invasive exotic species using GIS and information-theoretic approaches: A case of ragweed (Ambrosia artemisiifolia L.) distribution in China

Invasive exotic species pose a growing threat to the economy, public health, and ecological integrity of nations worldwide. Explaining and predicting the spatial distribution of invasive exotic species is of great importance to prevention and early warning efforts. We are investigating the potential distribution of invasive exotic species, the environmental factors that influence these distributions, and the ability to predict them using statistical and information-theoretic approaches. For some species, detailed presence/absence occurrence data are available, allowing the use of a variety of standard statistical techniques. However, for most species, absence data are not available. Presented with the challenge of developing a model based on presence-only information, we developed an improved logistic regression approach using Information Theory and Frequency Statistics to produce a relative suitability map. This paper generated a variety of distributions of ragweed (Ambrosia artemisiifolia L.) from logistic regression models applied to herbarium specimen location data and a suite of GIS layers including climatic, topographic, and land cover information. Our logistic regression model was based on Akaike's Information Criterion (AIC) from a suite of ecologically reasonable predictor variables. Based on the results we provided a new Frequency Statistical method to compartmentalize habitat-suitability in the native range. Finally, we used the model and the compartmentalized criterion developed in native ranges to "project" a potential distribution onto the exotic ranges to build habitat-suitability maps. ?? Science in China Press 2007.

Chinese Science Bulletin

Updating estimates of low-streamflow statistics to account for possible trends

Accurate estimators of streamflow statistics are critical to the design, planning, and management of water resources. Given increasing evidence of trends in low-streamflow, new approaches to estimating low-streamflow statistics are needed. Here we investigate simple approaches to select a recent subset of the low-flow record to update the commonly used statistic of 7 Q 10, the annual minimum 7-day streamflow exceeded in 9 out of 10 years on average. Informed by low-streamflow records at 174 US Geological Survey streamgages, Monte Carlo simulation experiments evaluate competing approaches. We find that a strategy which estimates 7 Q 10 using the most recent 30 years of record when a trend is detected, reduces error and bias in 7 Q 10 estimators compared to use of the full record. This simple rule-based approach has potential as the basis for a framework for updating frequency-based statistics in the context of possible trends.

Hydrologic Sciences Journal

Book review: Bird census techniques, Second edition

Conservation concerns, federal mandates to monitor birds, and citizen science programs have spawned a variety of surveys that collect information on bird populations. Unfortunately, all too frequently these surveys are poorly designed and use inappropriate counting methods. Some of the flawed approaches reflect a lack of understanding of statistical design; many ornithologists simply are not aware that many of our most entrenched counting methods (such as point counts) cannot appropriately be used in studies that compare densities of birds over space and time. It is likely that most of the readers of The Condor have participated in a bird population survey that has been criticized for poor sampling methods. For example, North American readers may be surprised to read in Bird Census Techniques that the North American Breeding Bird Survey 'is seriously flawed in its design,' and that 'Analysis of trends is impossible from points that are positioned along roads' (p. 109). Our conservation efforts are at risk if we do not acknowledge these concerns and improve our survey designs. Other surveys suffer from a lack of focus. In Bird Census Techniques, the authors emphasize that all surveys require clear statements of objectives and an understanding of appropriate survey designs to meet their objectives. Too often, we view survey design as the realm of ornithologists who know the life histories and logistical issues relevant to counting birds. This view reflects pure hubris: survey design is a collaboration between ornithologists, statisticians, and managers, in which goals based on management needs are met by applying statistical principles for design to the biological context of the species of interest. Poor survey design is often due to exclusion of some of these partners from survey development. Because ornithologists are too frequently unaware of these issues, books such as Bird Census Techniques take on added importance as manuals for educating ornithologists about the relevance of survey design and methods and the often subtle interdisciplinary nature of surveys. Review info: Bird Census Techniques, Second Edition. By Colin J. Bibby, Neil D. Burgess, David A. Hill, and Simon H. Mustoe. 2000. Academic Press, London, UK. xvii 1 302 pp. ISBN 0- 12-095831-7.

Condor

U.S. Geological Survey Earthquake Hazards Program decadal science strategy, 2024–33

Executive Summary Earthquakes represent one of our Nation’s most significant and costly natural hazards, with estimated annual loses from earthquakes close to $15 billion in 2023. Over the past two centuries, 37 U.S. States have experienced an earthquake exceeding a magnitude of 5, and 50 percent of States have a significant potential for future damaging shaking; these statistics speak to the need for nationwide interest and investment in earthquake hazard characterization and risk reduction. Authorized under the Earthquake Hazards Reduction Authorization Act, the U.S. Geological Survey (USGS) Earthquake Hazards Program (EHP) provides the scientific information, situational awareness, and knowledge necessary to reduce deaths, injuries, and economic losses from earthquakes and earthquake-induced tsunamis, landslides, and soil liquefaction. The EHP supports activities in three focused topical areas: (1) earthquake monitoring, (2) hazard assessment, and (3) applied research, using the results of each—and the coordination among them—to further support risk translation and communication in regions at risk nationwide. For earthquake monitoring, the Advanced National Seismic System (ANSS), a cooperative effort of USGS networks, university partner regional seismic networks, and real-time geodetic networks, collects and analyzes data on earthquakes; issues timely, reliable notifications of their occurrence and impacts; and provides data for earthquake research, hazard, and risk assessment as a foundation for building an earthquake-resilient Nation. The USGS-operated ShakeAlert Earthquake Early Warning system is a recent addition to EHP’s ANSS infrastructure. In the realm of earthquake hazard assessment, the EHP contributes to earthquake risk mitigation strategies by developing the National Seismic Hazard Model and maps, and other related products, that describe the likelihood and potential effects of earthquakes nationwide, especially in the urban areas of highest risk. The EHP also conducts research on the causes, characteristics, and effects of earthquakes and prioritizes work that directly increases the accuracy and precision of earthquake hazards assessments, earthquake forecasts, and earthquake monitoring and situational-awareness products and that supports the Nation’s earthquake mitigation practices. Bridging the EHP’s efforts across research, hazard assessments, and earthquake monitoring is a broad and comprehensive collection of earthquake information products, including the National Seismic Hazard Model, ShakeAlert, and other products describing impact, such as ShakeMap and PAGER (Prompt Assessment of Global Earthquakes for Response), which have been developed and integrated into EHP’s real-time monitoring systems. EHP funds external partners to carry out many important collaborative activities through an active external grants program—one of the largest in the USGS—and through cooperative agreements with other partners such as the university-operated regional seismic networks, funded as part of the ANSS. To continue its support of earthquake hazard characterization and risk reduction, the EHP aims to strengthen its foundational products and practices while positioning itself to respond to the evolving needs of the Nation and follow best practices of the scientific community. This document describes a strategy for the program to ensure it can meet these demands. The foundational priorities outlined in this strategy represent those activities that remain critical to the core functionality of the program and those that can be supported under current fiscal year 2024-level appropriations. Priorities described as aspirational are important for future growth, and to maintain the program’s position as a leading global resource in earthquake science, but would require increases in appropriated funding to be fully realized. Across the program’s portfolio of activities, several major themes have been identified as the most critical activities to advance EHP science over the coming decade. Together, these activities provide the framework necessary to integrate critical hazard characterization and risk reduction activities across the program. They provide the structure for research to advance the understanding of where, when, and why earthquakes occur and how we can use improved knowledge to drive short-term and actionable forecasts of seismic activity. They expand the usefulness of critical earthquake products and advance the sophistication of those products to keep pace with the rapidly evolving needs of an ever-expanding user base while maintaining the position of the USGS as a global leader in earthquake science. Focus on system-level science. Establish an automated earthquake-processing pipeline. Enhance the accuracy and reliability of the ShakeAlert Earthquake Early Warning system and plan for extension to other regions. Implement time-dependent earthquake forecasting. Develop physically realistic models. Expand computational capacity. This science strategy is organized into three primary sections. The first section provides an overview of the EHP and its budget, governance, and program council. Readers familiar with the program may wish to focus on the second section, which describes the core of the science strategy, including priorities across each of the EHP’s major program activities in monitoring, hazard assessment, and targeted research. The third section outlines science priorities that cut across program activities, including those involving collaborations external to the EHP.

American Samoa, Guam, Northern Marianas Islands, U

Greater sage-grouse ( Centrocercus urophasianus ) nesting and brood-rearing microhabitat in Nevada and California—Spatial variation in selection and survival patterns

Greater sage-grouse ( Centrocercus urophasianus ; hereinafter, "sage-grouse") are highly dependent on sagebrush ( Artemisia spp.) dominated vegetation communities for food and cover from predators. Although this species requires the presence of sagebrush shrubs in the overstory, it also inhabits a broad geographic distribution with significant gradients in precipitation and temperature that drive variation in sagebrush ecosystem structure and concomitant shrub understory conditions. Variability in understory conditions across the species’ range may be responsible for the sometimes contradictory findings in the scientific literature describing sage-grouse habitat use and selection during important life history stages, such as nesting. To help understand the importance of this variability and to help guide management actions, we evaluated the nesting and brood-rearing microhabitat factors that influence selection and survival patterns in the Great Basin using a large dataset of microhabitat characteristics from study areas spanning northern Nevada and a portion of northeastern California from 2009 to 2016. The spatial and temporal coverage of the dataset provided a powerful opportunity to evaluate microhabitat factors important to sage-grouse reproduction, while also considering habitat variation associated with different climatic conditions and areas affected by wildfire. The summary statistics for numerous microhabitat factors, and the strength of their association with sage-grouse habitat selection and survival, are provided in this report to support decisions by land managers, policy-makers, and others with the best-available science in a timely manner.

California, Nevada

Testing and validating environmental models

Generally accepted standards for testing and validating ecosystem models would benefit both modellers and model users. Universally applicable test procedures are difficult to prescribe, given the diversity of modelling approaches and the many uses for models. However, the generally accepted scientific principles of documentation and disclosure provide a useful framework for devising general standards for model evaluation. Adequately documenting model tests requires explicit performance criteria, and explicit benchmarks against which model performance is compared. A model's validity, reliability, and accuracy can be most meaningfully judged by explicit comparison against the available alternatives. In contrast, current practice is often characterized by vague, subjective claims that model predictions show 'acceptable' agreement with data; such claims provide little basis for choosing among alternative models. Strict model tests (those that invalid models are unlikely to pass) are the only ones capable of convincing rational skeptics that a model is probably valid. However, 'false positive' rates as low as 10% can substantially erode the power of validation tests, making them insufficiently strict to convince rational skeptics. Validation tests are often undermined by excessive parameter calibration and overuse of ad hoc model features. Tests are often also divorced from the conditions under which a model will be used, particularly when it is designed to forecast beyond the range of historical experience. In such situations, data from laboratory and field manipulation experiments can provide particularly effective tests, because one can create experimental conditions quite different from historical data, and because experimental data can provide a more precisely defined 'target' for the model to hit. We present a simple demonstration showing that the two most common methods for comparing model predictions to environmental time series (plotting model time series against data time series, and plotting predicted versus observed values) have little diagnostic power. We propose that it may be more useful to statistically extract the relationships of primary interest from the time series, and test the model directly against them.

Science of the Total Environment

Population declines in North American birds that migrate to the neotropics

Using data from the North American Breeding Bird Survey, we determined that most neotropical migrant bird species that breed in forests of the eastern United States and Canada have recently (1978-1987) declined in abundance after a period of stable or increasing populations. Most permanent residents and temperate-zone migrants did not show a general pattern of decrease during this period. Field data from Mexico were used to classify a subset of the neotropical migrants as using forest or scrub habitats during winter. Population declines during 1978-1987 were significantly greater among the forest-wintering species, while populations of scrub-wintering species increased. The same subset of neotropical migrants also showed overall declines in forest-breeding species, but no significant differences existed between species breeding in forest and scrub habitats. Neotropical migrant species that primarily use forested habitats in either wintering or breeding areas are declining, but a statistically significant association between habitat and population declines was detected only in the tropics.

Proceedings of the National Academy of Sciences

Origins and philosophy of building a temporal database to examine human transformation processes

The U.S. Geological Survey (USGS), in partnership with the University of Maryland Baltimore County, is using historical maps and satellite images to map human-induced land transformations for the Baltimore-Washington metropolitan area. This work builds on an earlier effort that documented the historical urban development for the San Francisco Bay area. That effort used a geographic information system to compile a database that provided a visual and historical perspective of the urban growth experienced in the Bay area between 1850 and 1990. Historical overviews of urban development can be used to provide insights into the future. The Bay area work was inspired by the desire to draw upon the USGS's rich 100-year topographic map, and 20-year Landsat satellite data archives. A methodology was developed to combine the information from a variety of sources into an integrated, multi-scale, and multi-resolution dataset. Temporal urban mapping is used to examine past landscapes by incorporating historic maps, census statistics, and commerce records to generate a progressive geo-referenced representation of the past changes in the region. Contemporary analysis focuses on the use of remotely sensed data, existing digital land use data, digital census information, and a variety of Earth science infrastructure data, such as Digital Line Graphs, Digital Elevation Models, and key ancillary demographic information. The resulting database of temporal urban demographic changes provides an ideal source of test data and information for both urban geographers and global change research scientists.

San Francisco Bay

Geospatial Technology Applications and Infrastructure in the Biological Resources Division

Executive Summary -- Automated spatial processing technology such as geographic information systems (GIS), telemetry, and satellite-based remote sensing are some of the more recent developments in the long history of geographic inquiry. For millennia, humankind has endeavored to map the Earth's surface and identify spatial relationships. But the precision with which we can locate geographic features has increased exponentially with satellite positioning systems. Remote sensing, GIS, thematic mapping, telemetry, and satellite positioning systems such as the Global Positioning System (GPS) are tools that greatly enhance the quality and rapidity of analysis of biological resources. These technologies allow researchers, planners, and managers to more quickly and accurately determine appropriate strategies and actions. Researchers and managers can view information from new and varying perspectives using GIS and remote sensing, and GPS receivers allow the researcher or manager to identify the exact location of interest. These geospatial technologies support the mission of the U.S. Geological Survey (USGS) Biological Resources Division (BRD) and the Strategic Science Plan (BRD 1996) by providing a cost-effective and efficient method for collection, analysis, and display of information. The BRD mission is 'to work with others to provide the scientific understanding and technologies needed to support the sound management and conservation of our Nation's biological resources.' A major responsibility of the BRD is to develop and employ advanced technologies needed to synthesize, analyze, and disseminate biological and ecological information. As the Strategic Science Plan (BRD 1996) states, 'fulfilling this mission depends on effectively balancing the immediate need for information to guide management of biological resources with the need for technical assistance and long-range, strategic information to understand and predict emerging patterns and trends in ecological systems.' Information sharing plays a key role in nearly everything BRD does. The Strategic Science Plan discusses the need to (1) develop tools and standards for information transfer, (2) disseminate information, and (3) facilitate effective use of information. This effort centers around the National Biological Information Infrastructure (NBII) and the National Spatial Data Infrastructure (NSDI), components of the National Information Infrastructure. The NBII and NSDI are distributed electronic networks of biological and geographical data and information, as well as tools to help users around the world easily find and retrieve the biological and geographical data and information they need. The BRD is responsible for developing scientifically and statistically reliable methods and protocols to assess the status and trends of the Nation's biological resources. Scientists also conduct important inventory and monitoring studies to maintain baseline information on these same resources. Research on those species for which the Department of the Interior (DOI) has trust responsibilities (including endangered species and migratory species) involves laboratory and field studies of individual animals and the environments in which they live. Researchboth tactical and strategicis conducted at the BRD's 17 science centers and 81 field stations, 54 Cooperative Fish and Wildlife Research Units in 40 states, and at 11 former Cooperative Park Study Units. Studies encompass fish, birds, mammals, and plants, as well as their ecosystems and the surrounding landscape. Biological Resources Division researchers use a variety of scientific tools in their endeavors to understand the causes of biological and ecological trends. Research results are used by managers to predict environmental changes and to help them take appropriate measures to manage resources effectively. The BRD Geospatial Technology Program facilitates the collection, analysis, and dissemination of data and informat

Information and Technology Report

A global ensemble of ocean wave climate statistics from contemporary wave reanalysis and hindcasts

There are numerous global ocean wave reanalysis and hindcast products currently being distributed and used across different scientific fields. However, there is not a consistent dataset that can sample across all existing products based on a standardized framework. Here, we present and describe the first coordinated multi-product ensemble of present-day global wave fields available to date. This dataset, produced through the Coordinated Ocean Wave Climate Project (COWCLIP) phase 2, includes general and extreme statistics of significant wave height ( H s ), mean wave period ( T m ) and mean wave direction ( θ m ) computed across 1980–2014, at different frequency resolutions (monthly, seasonally, and annually). This coordinated global ensemble has been derived from fourteen state-of-the-science global wave products obtained from different atmospheric reanalysis forcing and downscaling methods. This data set has been processed, under a specific framework for consistency and quality, following standard Data Reference Syntax, Directory Structures and Metadata specifications. This new comprehensive dataset provides support to future broad-scale analysis of historical wave climatology and variability as well as coastal risk and vulnerability assessments across offshore and coastal engineering applications.

Scientific Data