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At least 19 recordsLinked to original sources

Restructuring and serving web-accessible streamflow data from the NOAA National Water Model historic simulations

In 2016, the National Oceanic and Atmospheric Administration deployed the first iteration of an operational National Water Model (NWM) to forecast the water cycle in the continental United States. With many versions, an hourly, multi-decadal historic simulation is made available to the public. In all released to date, the files containing simulated streamflow contain a snapshot of model conditions across the entire domain for a single timestep which makes accessing time series a technical and resource-intensive challenge. In the most recent release, extracting a complete streamflow time series for a single location requires managing 367,920 files (~16.2 TB). In this work we describe a reproducible process for restructuring a sequential set of NWM steamflow files for efficient time series access and provide restructured datasets for versions 1.2 (1993–2018), 2.0 (1993–2020), and 2.1 (1979–2022). These datasets have been made accessible via an OPeNDAP enabled THREDDS data server for public use and a brief analysis highlights the latest version of the model should not be assumed best for all locations. Lastly we describe an R package that expedites data retrieval with examples for multiple use-cases.

Nature, Scientific Data

Chlorophyll a in lakes and streams of the United States (2005–2022)

The concentration of chlorophyll a in phytoplankton and periphyton represents the amount of algal biomass. We compiled an 18-year record (2005–2022) of pigment data from water bodies across the United States (US) to support efforts to develop process-based, machine learning, and remote sensing models for prediction of harmful algal blooms (HABs). To our knowledge, this dataset of nearly 84,000 sites and over 1,374,000 pigment measurements is the largest compilation of harmonized discrete, laboratory-extracted chlorophyll data for the US. These data were compiled from the Water Quality Portal (WQP) and previously unpublished U.S. Geological Survey’s National Water Quality Laboratory (NWQL) data. Data were harmonized for reporting units, pigment type, duplicate values, collection depth, site name, negative values, and some extreme values. Across the country, data show great variation by state in sampling frequency, distribution, and methods. Uses for such data include the calibration of models, calibration of field sensors, examination of relationship to nutrients and other drivers, evaluation of temporal trends, and other applications addressing local to national scale concerns.

Nature Scientific Data

A global long-term daily reanalysis of reference evapotranspiration for drought and food-security monitoring

NOAA has developed a global reference evapotranspiration (ET 0 ) reanalysis using the UN Food and Agriculture Organization formulation (FAO-56) of the Penman-Monteith equation forced by MERRA phase 2 (MERRA2) meteorological and radiative drivers. The NOAA ET 0 reanalysis is provided daily from January 1, 1980 to the near-present at a resolution of 0.5° latitude × 0.625° longitude. The reanalysis is verified against station data across southern Africa, a region presenting both significant challenges regarding hydroclimatic variability and observational quantity and quality and significant potential benefits to food-insecure populations. These data are generated from observations from the Southern African Science Service Centre for Climate Change and Adaptive Land Management (SASSCAL) network. We further verified globally against spatially distributed ET 0 derived from two reanalyses–the Global Data Assimilation System (GDAS) and Princeton Global Forcing (PGF)–and these verifications produced similar results, yet demonstrated wide regional and seasonal differences. We also present cases that verify the operational applicability of the reanalysis in long-established drought, famine, crop- and pastoral-stress metrics, and in predictability assessments of drought forecasts.

Nature Scientific Data

Characterizing storm-induced coastal change hazards along the United States West Coast

Traditional methods to assess the probability of storm-induced erosion and flooding from extreme water levels have limited use along the U.S. West Coast where swell dominates erosion and storm surge is limited. This effort presents methodology to assess the probability of erosion and flooding for the U.S. West Coast from extreme total water levels (TWLs), but the approach is applicable to coastal settings worldwide. TWLs were derived from 61 years of wave and water level data at shore-perpendicular transects every 100-m along open coast shorelines. At each location, wave data from the Global Ocean Waves model were downscaled to the nearshore and used to empirically calculate wave run-up. Tides were simulated using the Oregon State University’s tidal data inversion model and non-tidal residuals were calculated from sea-surface temperature and pressure anomalies. Wave run-up was combined with still water levels to generate hourly TWL estimates and extreme TWLs for multiple return periods. Extremes were compared to onshore morphology to determine erosion hazards and define the probability of collision, overwash, and inundation.

California, Oregon, Washington

HarvestStat Africa – Harmonized subnational crop statistics for sub-Saharan Africa

Sub-Saharan Africa (SSA) faces severe agricultural data scarcity amidst high food insecurity and a large agricultural yield gap, making crop production data crucial for understanding and enhancing food systems. To address this gap, HarvestStat Africa presents the largest compilation of open-access subnational crop statistics and time-series across SSA. Based on agricultural statistics collated by USAID’s Famine Early Warning Systems Network, the subnational crop statistics are standardized and calibrated across changing administrative units to produce consistent and continuous time-series. The dataset includes 546,605 records, primarily spanning from 1980 to 2022, detailing crop production, harvested areas, and yields for 33 countries and 90 crop types, including key cereals in SSA such as wheat, maize, rice, sorghum, barley, millet, and fonio. This new dataset enhances our understanding of how climate variability and change influence agricultural production, supports subnational food system analysis, and aids in operational yield forecasting. As an open-source resource, it sets an important precedent for sharing subnational crop statistics to inform decision-making and modeling efforts.

Scientific Data - Nature

Coastal bathymetry and backscatter data collected in 2012 from the Chandeleur Islands, Louisiana

As part of the Barrier Island Evolution Research Project, scientists from the U.S. Geological Survey St. Petersburg Coastal and Marine Science Center conducted nearshore geophysical surveys off the northern Chandeleur Islands, Louisiana, in July and August of 2012. The objective of the study is to better understand barrier island geomorphic evolution, particularly storm-related depositional and erosional processes that shape the islands over annual to interannual timescales (1-5 years). Collecting geophysical data will allow us to identify relationships between the geologic history of the island and its present day morphology and sediment distribution. This mapping effort was the second in a series of three planned surveys in this area. High resolution geophysical data collected in each of 3 consecutive years along this rapidly changing barrier island system will provide a unique time-series dataset that will significantly further the analyses and geomorphological interpretations of this and other coastal systems, improving our understanding of coastal response and evolution over short time scales (1-5 years). This Data Series report includes the geophysical data that were collected during two cruises ( USGS Field Activity Numbers 12BIM03 and 12BIM04 ) aboard the RV Survey Cat and the RV Twin Vee along the northern portion of the Chandeleur Islands, Breton National Wildlife Refuge, Louisiana. Data were acquired with the following equipment: a Systems Engineering and Assessment, Ltd., SWATHplus interferometric sonar (468 kilohertz (kHz)), an EdgeTech 424 (4-24 kHz) chirp sub-bottom profiling system, and a Knudsen 320BP (210 kHz) echosounder. This report serves as an archive of processed interferometric swath and single-beam bathymetry data. Geographic information system data products include an interpolated digital elevation model, an acoustic backscatter mosaic, trackline maps, and point data files. Additional files include error analysis maps, Field Activity Collection System logs, and formal Federal Geographic Data Committee metadata. NOTE: These data are scientific in nature and are not to be used for navigation.

Louisiana

Archive of bathymetry and backscatter data collected in 2014 nearshore Breton and Gosier Islands, Breton National Wildlife Refuge, Louisiana

As part of the Barrier Island Monitoring Project, scientists from the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center conducted nearshore geophysical surveys off Breton and Gosier Islands, Louisiana, in July and August of 2014. To assist the United States Fish and Wildlife Service (USFWS) with restoration planning efforts, the USGS was tasked with answering fundamental questions about the physical environment of the southern Chandeleur Islands, including the geology, morphology, and oceanography. Baseline data needed to answer these questions were either insufficient or missing. The USGS conducted a comprehensive geologic investigation in the summer of 2014, collecting geophysical and sedimentological data. Breton Island, located at the southern end of the Chandeleur Island chain in southeastern Louisiana, was recognized as a natural, globally significant nesting sanctuary for several bird species and was established as the Breton National Wildlife Refuge (NWR) in 1904. The areal extent of Breton Island has diminished 90 percent since 1920. Land loss is attributed to ongoing relative sea-level rise, diminished sediment supply, and storm impacts. The bird population on Breton Island has also declined over the years, most notably after Hurricane George in 1998 and after Hurricane Katrina in 2015; the latter completely submerged the island. Despite decreasing habitable acreage, migratory seabirds continue to return and nest on Breton Island. To prevent the island from being submerged in the future, and to protect, stabilize, and provide more nesting and foraging areas for the bird population, the USFWS proposed a restoration effort to rebuild Breton Island to its pre-Katrina footprint. This data series serves as an archive of processed interferometric swath and single-beam bathymetry data, and side-scan sonar data, collected in the nearshore of Breton and Gosier Islands, NWR, Louisiana. The data were collected during two USGS cruises (USGS Field Activity Numbers 2014-314-FA and 2014-317-FA) in July and August 2014. Geographic information system data products include a 100-meter-cell-size interpolated bathymetry grid, trackline maps, and point data files. Additional files include error analysis maps, Field Activity Collection System logs, and formal Federal Geographic Data Committee metadata. NOTE: These data are scientific in nature and are not to be used for navigation. Any use of trade names is for descriptive purposes only and does not imply endorsement by the U.S. Government.

Louisiana

Archive of Sidescan Sonar and Swath Bathymetry Data Collected During USGS Cruise 13CCT04 Offshore of Petit Bois Island, Gulf Islands National Seashore, Mississippi, August 2013

In August of 2013, the U.S. Geological Survey conducted a geophysical survey offshore of Petit Bois Island, Mississippi. This effort was part of the U.S. Geological Survey Gulf of Mexico Science Coordination partnership with the U.S. Army Corps of Engineers to assist the Mississippi Coastal Improvements Program and the Northern Gulf of Mexico Ecosystem Change and Hazards Susceptibility Project, by mapping the shallow geologic stratigraphic framework of the Mississippi Barrier Island Complex. This geophysical survey will provide additional data necessary for scientists to define, interpret, and provide baseline bathymetry and seafloor habitat for this area, and to aid scientists in predicting future geomorphological changes of the islands with respect to climate change, storm impact, and sea-level rise. Furthermore, these data will provide information for barrier island restoration, particularly in Camille Cut, and protection for the historical Fort Massachusetts on Ship Island, Mississippi. The geophysical data were collected during one cruise ( USGS Field Activity Numbers 13CCT04 ) aboard the Research Vessel Tommy Munro offshore along the gulf side of Petit Bois Island, Gulf Islands National Seashore, Mississippi. Data were acquired with the following equipment: a Systems Engineering and Assessment, Ltd., SWATH plus interferometric sonar (468 kilohertz (kHz)), an EdgeTech 424 (4-24 kHz), an EdgeTech 525i chirp subbottom profiling system, and a Klein 3900 sidescan sonar system. This report serves as an archive of the processed interferometric swath bathymetry and sidescan sonar data. Geographic information system data products include an interpolated digital elevation model, an acoustic backscatter mosaic, trackline maps, and point data files. Additional files include error analysis maps, Field Activity Collection System logs, and formal Federal Geographic Data Committee metadata. NOTE: These data are scientific in nature and are not to be used for navigation. Any use of trade names is for descriptive purposes only and does not imply endorsement by the U.S. Government.

Mississippi

U.S. Geological Survey Activities Related to American Indians and Alaska Natives: Fiscal Year 2005

Introduction This report describes the activities that the U.S. Geological Survey (USGS) conducted with American Indian and Alaska Native governments, educational institutions, and individuals during Federal fiscal year (FY) 2005. Most of these USGS activities were collaborations with Tribes, Tribal organizations, or professional societies. Others were conducted cooperatively with the Bureau of Indian Affairs (BIA) or other Federal entities. The USGS is the earth and natural science bureau within the U.S. Department of the Interior (DOI). The USGS does not have regulatory or land management responsibilities. As described in this report, there are many USGS activities that are directly relevant to American Indians, Alaska Natives, and to Native lands. A USGS website, dedicated to making USGS more accessible to American Indians, Alaska Natives, their governments, and institutions, is available at www.usgs.gov/indian. This website includes information on how to contact USGS American Indian/Alaska Native Liaisons, training opportunities, and links to other information resources. This report and previous editions are also available through the website. The USGS realizes that Native knowledge and cultural traditions of living in harmony with nature result in unique Native perspectives that enrich USGS studies. USGS seeks to increase the sensitivity and openness of its scientists to the breadth of Native knowledge, expanding the information on which their research is based. USGS scientific studies include data collection, mapping, natural resource modeling, and research projects. These projects typically last 2 or 3 years, although some are parts of longer-term activities. Some projects are funded cooperatively, with USGS funds matched or supplemented by individual Tribal governments, or by the BIA. These projects may also receive funding from the U.S. Environmental Protection Agency (USEPA), the Indian Health Service (part of the Department of Health and Human Services), or other Federal agencies. The USGS routinely works with its sister bureaus in the Department of the Interior to provide the scientific information and expertise needed to meet the Department's science priorities. Some USGS activities described in this report are conducted as collateral tasks that result from USGS employees identifying and responding to perceived needs. These endeavors are usually prompted by employee interests and frequently involve educational activities. The education is often a reciprocal learning and teaching experience for USGS employees and for Native participants. Through these activities, USGS employees help to fulfill a mission of the USGS - to demonstrate scientific relevance - while helping their fellow citizens. Increasingly, some of the educational activities are becoming parts of formal USGS projects. USGS employees also take initiative in assisting American Indians and Alaska Natives by participating in several organizations that promote awareness of science career opportunities among Native peoples and help build support and communication networks. One such group is the American Indian Science and Engineering Society (AISES). USGS employees join this organization on a voluntary basis, bringing the benefits of this expanded network to the USGS, as many employees do with other professional organizations. The studies briefly described in this report span subsistence issues, wildlife health, water quality, mineral resources, monitoring and modeling to gather information and predict what may happen in the future. Although each project description relates to Native Americans in some way, the projects vary widely, including who conducted the work, the goals and products, the duration of the study, and whether it was local or covered a broad area. Each major organizational unit of the USGS has identified an American Indian/Alaska Native liaison. The USGS has a regional organizational structure, with Western, Central,

Circular

A methods framework for evaluating measurement consistency across spectrometers for multispectral uncrewed aerial system vegetation mapping applications

The U.S. Geological Survey collects remote sensing data to support national scientific assessments of natural resources, hazards, and landscape change. Spectrometers and spectroradiometers are essential for gathering point-based spectral measurements used in applications such as uncrewed aerial systems (UAS) multispectral image calibration, validation, and analysis. Evaluating how different instruments perform in laboratory and field environments helps determine whether they provide consistent, interoperable measurements. Such verification can expand access to spectral ground data during UAS operations by allowing scientists to use alternative instruments when budgets, logistics, or field conditions limit options. We propose and test a methodological framework for evaluating spectrometers for measurement consistency during UAS multispectral vegetation mapping applications. There are three central evaluation components to the framework: laboratory, field, and relative to UAS multispectral imagery. By evaluating the instruments in both relatively controlled and uncontrolled environments, we thoroughly examine measurement consistency and when/why measurements may differ. We opportunistically selected two instruments for a case study in a coastal marsh setting: a compact laboratory spectrometer we modified for field use and a field-ready spectroradiometer. The instruments produced consistent measurements in both environments. We found differences between the field spectra and UAS spectra that likely reflect the perspectives of ground vs. aerial data and indicate that further radiometric calibration may be needed.

Massachusetts

Interactive terrain visualization enables virtual field work during rapid scientific response to the 2010 Haiti earthquake

The moment magnitude (M w ) 7.0 12 January 2010 Haiti earthquake is the first major earthquake for which a large-footprint LiDAR (light detection and ranging) survey was acquired within several weeks of the event. Here, we describe the use of virtual reality data visualization to analyze massive amounts (67 GB on disk) of multiresolution terrain data during the rapid scientific response to a major natural disaster. In particular, we describe a method for conducting virtual field work using both desktop computers and a 4-sided, 22 m 3 CAVE immersive virtual reality environment, along with KeckCAVES (Keck Center for Active Visualization in the Earth Sciences) software tools LiDAR Viewer, to analyze LiDAR point-cloud data, and Crusta, for 2.5 dimensional surficial geologic mapping on a bare-earth digital elevation model. This system enabled virtual field work that yielded remote observations of the topographic expression of active faulting within an ∼75-km-long section of the eastern Enriquillo–Plantain Garden fault spanning the 2010 epicenter. Virtual field observations indicated that the geomorphic evidence of active faulting and ancient surface rupture varies along strike. Landform offsets of 6–50 m along the Enriquillo–Plantain Garden fault east of the 2010 epicenter and closest to Port-au-Prince attest to repeated recent surface-rupturing earthquakes there. In the west, the fault trace is well defined by displaced landforms, but it is not as clear as in the east. The 2010 epicenter is within a transition zone between these sections that extends from Grand Goâve in the west to Fayette in the east. Within this transition, between L'Acul (lat 72°40′W) and the Rouillone River (lat 72°35′W), the Enriquillo–Plantain Garden fault is undefined along an embayed low-relief range front, with little evidence of recent surface rupture. Based on the geometry of the eastern and western faults that show evidence of recent surface rupture, we propose that the 2010 event occurred within a stepover that appears to have served as a long-lived boundary between rupture segments, explaining the lack of 2010 surface rupture. This study demonstrates how virtual reality–based data visualization has the potential to transform rapid scientific response by enabling virtual field studies and real-time interactive analysis of massive terrain data sets.

Geosphere

Technology transfer opportunities: partnership opportunities for states: U.S. Geological Survey assistance to state business economy

As a research and information laboratory of the Federal government, the U.S. Geological Survey (USGS) is committed to making its developments readily available to customers within the private sector. The USGS is the Nation's premier earth science agency, providing unique scientific data and technology in the areas of natural hazards, environment, resources, and information. Often USGS research and information activities lead to developments that have significant commercial applications and that can help increase the global competitiveness of our domestic economy. The agency uses a proactive technology transfer program to encourage the adoption and use of these developments. In addition, the agency welcomes collaborative opportunities with private industry.

Fact Sheet

A Natural Resource Condition Assessment for Rocky Mountain National Park

We conducted a natural resource assessment of Rocky Mountain National Park (ROMO) to provide a synthesis of existing scientific data and knowledge to address the current conditions for a subset of important park natural resources. The intent is for this report to help provide park resource managers with data and information, particularly in the form of spatially-explicit maps and GIS databases, about those natural resources and to place emerging issues within a local, regional, national, or global context. With an advisory team, we identified the following condition indicators that would be useful to assess the condition of the park: Air and Climate: Condition of alpine lakes and atmospheric deposition Water: Extent and connectivity of wetland and riparian areas Biotic Integrity: Extent of exotic terrestrial plant species, extent of fish distributions, and extent of suitable beaver habitat Landscapes: Extent and pattern of major ecological systems and natural landscapes connectivity These indicators are summarized in the following pages. We also developed two maps of important issues for use by park managers: visitor use (thru accessibility modeling) and proportion of watersheds affected by beetle kill. Based on our analysis, we believe that there is a high degree of concern for the following indicators: condition of alpine lakes; extent and connectivity of riparian/wetland areas; extent of exotic terrestrial plants (especially below 9,500’); extent of fish distributions; extent of suitable beaver habitat; and natural landscapes and connectivity. We found a low degree of concern for: the extent and pattern of major ecological systems. The indicators and issues were also summarized by the 34 watershed units (HUC12) within the park. Generally, we found six watersheds to be in “pristine” condition: Black Canyon Creek, Comanche Creek, Middle Saint Vrain Creek, South Fork of the Cache la Poudre, Buchanan Creek, and East Inlet. Four watersheds were found to have strong restoration opportunities: Big Thompson River West, Cache la Poudre South, Colorado River North, and Onahu Creek. Ten watersheds were found to have substantial near-term issues: Aspen Brook, Big Thompson River West, Black Canyon Creek, Cabin Creek, Cache la Poudre South, Fall River, Hague Creek, La Poudre Pass Creek, North Fork Big Thompson (East), and Colorado River North.

Report

Maximizing the utility of monitoring to the adaptive management of natural resources

Data collection is an important step in any investigation about the structure or processes related to a natural system. In a purely scientific investigation (experiments, quasi-experiments, observational studies), data collection is part of the scientific method, preceded by the identification of hypotheses and the design of any manipulations of the system to test those hypotheses. Data collection and the manipulations that precede it are ideally designed to maximize the information that is derived from the study. That is, such investigations should be designed for maximum power to evaluate the relative validity of the hypotheses posed. When data collection is intended to inform the management of ecological systems, we call it monitoring. Note that our definition of monitoring encompasses a broader range of data-collection efforts than some alternative definitions – e.g. Chapter 3. The purpose of monitoring as we use the term can vary, from surveillance or “thumb on the pulse” monitoring (see Nichols and Williams 2006), intended to detect changes in a system due to any non-specified source (e.g. the North American Breeding Bird Survey), to very specific and targeted monitoring of the results of specific management actions (e.g. banding and aerial survey efforts related to North American waterfowl harvest management). Although a role of surveillance monitoring is to detect unanticipated changes in a system, the same result is possible from a collection of targeted monitoring programs distributed across the same spatial range (Box 4.1). In the face of limited budgets and many specific management questions, tying monitoring as closely as possible to management needs is warranted (Nichols and Williams 2006). Adaptive resource management (ARM; Walters 1986, Williams 1997, Kendall 2001, Moore and Conroy 2006, McCarthy and Possingham 2007, Conroy et al. 2008a) provides a context and specific purpose for monitoring: to evaluate decisions with respect to achievement of specific management objectives; and to evaluate the relative validity of predictive system models. This latter purpose is analogous to the role of data collection within the scientific method, in a research context.

Book chapter

Optical satellite data volcano monitoring: a multi-sensor rapid response system

In this chapter, the use of satellite remote sensing to monitor active geological processes is described. Specifically, threats posed by volcanic eruptions are briefly outlined, and essential monitoring requirements are discussed. As an application example, a collaborative, multi-agency operational volcano monitoring system in the north Pacific is highlighted with a focus on the 2007 eruption of Kliuchevskoi volcano, Russia. The data from this system have been used since 2004 to detect the onset of volcanic activity, support the emergency response to large eruptions, and assess the volcanic products produced following the eruption. The overall utility of such integrative assessments is also summarized. The work described in this chapter was originally funded through two National Aeronautics and Space Administration (NASA) Earth System Science research grants that focused on the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) instrument. A skilled team of volcanologists, geologists, satellite tasking experts, satellite ground system experts, system engineers and software developers collaborated to accomplish the objectives. The first project, Automation of the ASTER Emergency Data Acquisition Protocol for Scientific Analysis, Disaster Monitoring, and Preparedness , established the original collaborative research and monitoring program between the University of Pittsburgh (UP), the Alaska Volcano Observatory (AVO), the NASA Land Processes Distributed Active Archive Center (LP DAAC) at the U.S. Geological Survey (USGS) Earth Resources Observation and Science (EROS) Center, and affiliates on the ASTER Science Team at the Jet Propulsion Laboratory (JPL) as well as associates at the Earth Remote Sensing Data Analysis Center (ERSDAC) in Japan. This grant, completed in 2008, also allowed for detailed volcanic analyses and data validation during three separate summer field campaigns to Kamchatka Russia. The second project, Expansion and synergistic use of the ASTER Urgent Request Protocol (URP) for natural disaster monitoring and scientific analysis , has expanded the project to other volcanoes around the world and is in progress through 2011. The focus on ASTER data is due to the suitability of the sensor for natural disaster monitoring and the availability of data. The instrument has several unique facets that make it especially attractive for volcanic observations (Ramsey and Dehn, 2004). Specifically, ASTER routinely collects data at night, it has the ability to generate digital elevation models using stereo imaging, it can collect data in various gain states to minimize data saturation, it has a cross-track pointing capability for faster targeting, and it collects data up to ±85° latitude for better global coverage. As with any optical imaging-based remote sensing, the viewing conditions can negatively impact the data quality. This impact varies across the optical and thermal infrared wavelengths as well as being a function of the specific atmospheric window within a given wavelength region. Water vapor and cloud formation can obscure surface data in the visible and near infrared (VNIR)/shortwave infrared (SWIR) region due mainly to non-selective scattering of the incident photons. In the longer wavelengths of the thermal infrared (TIR), scattering is less of an issue, but heavy cloud cover can still obscure the ground due to atmospheric absorption. Thin clouds can be optically-transparent in the VNIR and TIR regions, but can cause errors in the extracted surface reflectance or derived surface temperatures. In regions prone to heavy cloud cover, optical remote sensing can be improved through increased temporal resolution. As more images are acquired in a given time period the chances of a clear image improve dramatically. The Advanced Very High Resolution Radiometer (AVHRR) routine monitoring, which commonly collects 4-6 images per day of any north Pacific volcano, takes advantage of this fact. The rapid response program described in this chapter also improves the temporal resolution of the ASTER instrument. ASTER has been acquiring images of volcanic eruptions since soon after its launch in December 1999. An early example included the observations of the large pyroclastic flow deposit emplaced at Bezymianny volcano in Kamchatka, Russia. The first images in March 2000, just weeks after the eruption, revealed the extent, composition, and cooling history of this large deposit and of the active lava dome (Ramsey and Dehn, 2004). The initial results from these early datasets spurred interest in using ASTER data for expanded volcano monitoring in the north Pacific. It also gave rise to the multi-year NASA-funded programs of rapid response scheduling and imaging throughout the Aleutian, Kamchatka and Kurile arcs. Since the formal establishment of the programs, the data have provided detailed descriptions of the eruptions of Augustine, Bezymianny, Kliuchevskoi and Sheveluch volcanoes over the past nine years (Wessels et al., in press; Carter et al., 2007, 2008; Ramsey et al., 2008; Rose and Ramsey, 2009). The initial research focus of this rapid response program was specifically on automating the ASTER sensor’s ability for targeted observational scheduling using the expedited data system. This urgent request protocol is one of the unique characteristics of ASTER. It provides a limited number of emergency observations, typically at a much-improved temporal resolution and quicker turnaround with data processing in the United States rather than in Japan. This can speed the reception of the processed data by several days to a week. The ongoing multi-agency research and operational collaboration has been highly successful. AVO serves as the primary source for status information on volcanic activity, working closely with the National Weather Service (NWS), Federal Aviation Administration (FAA), military and other state and federal emergency services. Collaboration with the Russian Institute of Volcanology and Seismology (IVS)/Kamchatka Volcanic Eruption Response Team (KVERT) is also maintained. Once a volcano is identified as having increased thermal output, ASTER is automatically tasked and the volcano is targeted at the next available opportunity. After the data are acquired, scientists at all the agencies have access to the images, with the primary science analysis carried out at the University of Pittsburgh and AVO. Results are disseminated to the responsible monitoring agencies and the global community through e-mail mailing lists.

Book chapter

Making Recursive Bayesian inference accessible

Bayesian models provide recursive inference naturally because they can formally reconcile new data and existing scientific information. However, popular use of Bayesian methods often avoids priors that are based on exact posterior distributions resulting from former studies. Two existing Recursive Bayesian methods are: Prior- and Proposal-Recursive Bayes. Prior-Recursive Bayes uses Bayesian updating, fitting models to partitions of data sequentially, and provides a way to accommodate new data as they become available using the posterior from the previous stage as the prior in the new stage based on the latest data. ProposalRecursive Bayes is intended for use with hierarchical Bayesian models and uses a set of transient priors in first stage independent analyses of the data partitions. The second stage of Proposal-Recursive Bayes uses the posteriors from the first stage as proposals in an MCMC algorithm to fit the full model. We combine Prior- and Proposal-Recursive concepts to fit any Bayesian model, and often with computational improvements. We demonstrate our method with two case studies. Our approach has implications for big data, streaming data, and optimal adaptive design situations.

American Statistician

Murky waters: Divergent ways scientists, practitioners, and landowners evaluate beaver mimicry

Beaver mimicry is a fast-growing conservation technique to restore streams and manage water that is gaining popularity within the natural resource management community because of a wide variety of claimed socio-environmental benefits. Despite a growing number of projects, many questions and concerns about beaver mimicry remain. This study draws on qualitative data from 49 interviews with scientists, practitioners, and landowners, to explore the question of how beaver mimicry projects continue to be promoted and implemented, despite the lack of comprehensive scientific studies and unclear regulatory requirements. Specifically, we investigate how these three groups differentially assess the salience, credibility, and legitimacy of evidence for beaver mimicry and analyze how those assessments affect each group’s conclusions about the feasibility, desirability, and scalability of beaver mimicry. By highlighting the interaction between how someone assesses evidence and how they draw conclusions about an emerging natural resource management approach, we draw attention to the roles of experiential evidence and scientific data in debates over beaver mimicry. Our research emphasizes that understanding how different groups perceive salience, credibility, and legitimacy of scientific information is necessary for understanding how they make assessments about conservation and natural resource management strategies.

Ecology and Society