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At least 271 records · Page 15Linked to original sources
USGS2015

Estuarine water quality in parks of the Northeast Coastal and Barrier Network: vital signs estuarine nutrient-enrichment monitoring, 2006-11

This report summarizes results of water-quality monitoring within estuaries of the National Park Service Northeast Coastal and Barrier Network (NCBN) from 2006 through 2011. Data collection formed part of the NCBN Vital Signs Monitoring Program implemented to detect threats of estuarine nutrient enrichment. Data included here were collected from six parks at predetermined intervals: Cape Cod National Seashore, Massachusetts (2007, 2008, 2009, 2010, 2011); Fire Island National Seashore, New York (2009, 2011); Gateway National Recreation Area, New York and New Jersey (2010); Assateague Island National Seashore, Maryland and Virginia (2006, 2008, 2010); George Washington Birthplace National Monument, Virginia (2009, 2011); and Colonial National Historic Park, Virginia (2008, 2010). Monitoring variables consisted of dissolved-oxygen concentration, chlorophyll a concentration, attenuation of downwelling photosynthetically available radiation (PAR), turbidity, water temperature, and salinity. All monitoring was conducted during four-week summer index periods. The monitoring design incorporated data collection at multiple, complementary spatial and temporal scales. Within each park, a spatial survey was conducted once during the index period following a probability design using a grid of tessellated hexagons as the basis for sample site selection. The spatial survey was supplemented with weekly measurements at a subset of sites and continuous monitoring at a single reference site. Within parks, data were reported as area-weighted water-quality conditions during each index period, the location and extent of estuarine area within condition categories, and spatial and temporal trends. In addition, we used a repeated measures analysis of variance to determine the extent to which variability in three water quality metrics (chlorophyll a in surface water, dissolved oxygen in bottom water, and water clarity expressed by PAR attenuation) was explained by year to year changes in each park's respective estuary.

Maryland, Massachusetts, New Jersey, New York, Vir↗
USGS1983

Geohydrologic framework of the Roswell ground-water basin, Chaves and Eddy Counties, New Mexico

This report describes the geohydrology of the Roswell ground-water basin and shows the long-term hydrostatic-head changes in the aquifers. The Roswell ground-water basin consists of a carbonate artesian aquifer overlain by a leaky confining bed, which, in turn is overlain by an alluvial water-table aquifer. The water-table aquifer is hydraulically connected to the Pecos River. Ground-water pumpage from about 1,500 wells in the basin was about 378,000 acre-feet in 1978. Irrigation use on about 122,000 acres accounted for 95 percent of that pumpage.

New Mexico↗
USGS2010

Status and trends of selected resources in the Upper Mississippi River System

Like other large rivers, the Upper Mississippi River System (UMRS) serves a diversity of roles. The UMRS provides commercial and recreational fishing, floodplain agriculture, drinking water for many communities, an important bird migration pathway, a variety of recreational activities, and a navigation system that transports much of the country's agricultural exports. These multiple roles present significant management challenges. Regular assessment of the condition of the river is needed to improve management plans and evaluate their effectiveness. This report provides a summary of the recent status (mean and range of conditions) and trends (change in direction over time) for 24 indicators of the ecological condition of the Upper Mississippi and Illinois Rivers using data collected through the Long Term Resource Monitoring Program (LTRMP). The 24 indicators were grouped into seven categories: hydrology, sedimentation, water quality, land cover, aquatic vegetation, invertebrates, and fish. Most of the data used in the report were collected between about 1993 and 2004, although some older data were also used to compare to recent conditions.Historical observations and current LTRMP data clearly indicate that the UMRS has been changed by human activity in ways that have diminished the ecological health of the river. The data indicate that status and trends differ among regions, and we expect that regional responses to various ecological rehabilitation techniques will differ as well. The continuing role of the LTRMP will be to provide the data needed to assess changes in river conditions and to determine how those changes relate to management actions, natural variation, and the overall ecological integrity of the river system.

Long Term Resource Monitoring Program Technical Re↗
USGS2020

Hydrologic modeling for flow-ecology science in the Southeastern United States and Puerto Rico

An understanding of the applicability and utility of hydrologic models is critical to support the effective management of water resources throughout the Southeastern United States (SEUS) and Puerto Rico (PR). Hydrologic models have the capacity to provide an estimate of the quantity of available water at ungauged locations (i.e., areas of the country where a U.S. Geological Survey [USGS] continuous record gauge is not installed) and provide the baseline flow information necessary to develop the linkages between water availability and characteristics of streamflow that support ecological communities (i.e., support the development of flow-ecology response models). This report inventories and then directly examines and compares a subset of hydrologic models used to estimate streamflow at a number of gauged basins across the SEUS and PR. This effort was designed to evaluate, quantify, and compare the magnitude of error and to investigate the potential causes of error associated with predicted streamflows from seven hydrologic models of varying complexity and calibration strategy. This was accomplished by computing and then comparing classical hydrologic model fit statistics (e.g., mean bias, coefficient of determination [R2], root mean squared error [RMSE], Nash-Sutcliffe Efficiency [NSE]) and understanding the bias in the prediction in these and a subset of ecologically relevant flow metrics (ERFMs). Additionally, streamflow predictions from a larger regional-scale hydrologic model were compared to those of several fine-scale hydrologic models under a range of hypothetical climate change scenarios to determine the range of predicted streamflow responses to fixed climate perturbations. A pilot study was conducted using predicted streamflow and boosted regression trees to develop a set of predictive flow-ecology response models to assess the potential change in fish species richness in the North Carolina Piedmont under several scenarios of water availability change. This report is intended to provide a general assessment of all the tools and techniques available to support hydrologic modeling for flow-ecology science in the SEUS and PR. It is our hope that the approach used herein to understand differences in streamflow predictions among a subset of hydrologic models that have been applied in the SEUS for developing flow-ecology response models will provide water resource managers and stakeholders with an informed pathway for developing the capacity to link streamflow and ecological response and an understanding of some of the limitations associated with these type of modeling efforts.

Alabama, Florida, Georgia, Mississippi, North Caro↗
USGS2000

The derivation of World Magnetic Model 2000

This report contains a detailed summary of the data used, the modelling techniques employed and the results obtained in the production of the World Magnetic Model 2000. This model is designed for use in air and sea navigation systems and is valid till 2005.0. The derivation of World Magnetic Model 2000 has been the joint responsibility of the British Geological Survey (BGS) and the United States Geological Survey (USGS). The World Magnetic Model is the standard model in UK Ministry of Defence and US Department of Defense, the North Atlantic Treaty Organization (NATO), and the World Hydrographic Office (WHO) navigation and attitude/heading referencing systems. It is also used widely in civilian navigation systems.

British Geological Survey Technical Report↗
USGS2014

Status of whitebarkpine in the Greater Yellowstone Ecosystem: A step-trend analysis comparing 2004-2007 to 2008-2011

Whitebark pine (Pinus albicaulis) is a foundation and keystone species in upper subalpine environments of the northern Rocky Mountains that strongly influences the biodiversity and productivity of high-elevation ecosystems (Tomback et al. 2001, Ellison et al. 2005). Throughout its historic range, whitebark pine has decreased significantly as a major component of high-elevation forests. As a result, it is critical to understand the challenges to whitebark pine—not only at the tree and stand level, but also as these factors influence the distribution of whitebark pine across the Greater Yellowstone Ecosystem (GYE). In 2003, the National Park Service (NPS) Greater Yellowstone Inventory & Monitoring Network identified whitebark pine as one of twelve significant natural resource indicators or vital signs to monitor (Jean et al. 2005, Fancy et al. 2009) and initiated a long-term, collaborative monitoring program. Partners in this effort include the U.S. Geological Survey, U.S. Forest Service, and Montana State University with representatives from each comprising the Greater Yellowstone Whitebark Pine Monitoring Working Group. The objectives of the monitoring program are to assess trends in (1) the proportion of live, whitebark pine trees (>1.4-m tall) infected with white pine blister rust (blister rust); (2) to document blister rust infection severity by the occurrence and location of persisting and new infections; (3) to determine mortality of whitebark pine trees and describe potential factors contributing to the death of trees; and (4) to assess the multiple components of the recruitment of understory whitebark pine into the reproductive population. In this report we summarize the past eight years (2004-2011) of whitebark pine status and trend monitoring in the GYE. Our study area encompasses six national forests (NF), two national parks (NP), as well as state and private lands in portions of Wyoming, Montana, and Idaho; this area is collectively described as the GYE here and in other studies. The sampling design is a probabilistic, twostage cluster design with stands of whitebark pine as the primary units and 10x50 m belt transects as the secondary units. Primary sampling units (stands) were selected randomly from a sample frame of approximately 10,770 mapped pure and mixed whitebark pine stands ≥2.0 hectares in the GYE (Dixon 1997, Landenburger 2012). From 2004 through 2007 (monitoring transect establishment or initial time-step), we established 176 permanent belt transects (secondary sampling units=176) in 150 whitebark pine stands and permanently marked approximately 4,740 individual trees >1.4 m tall to monitor long-term changes in blister rust infection and survival rates. Between 2008 and 2011 (revisit time-step), these same 176 transects were surveyed and again all previously tagged trees were observed for changes in blister rust infection and survival status. Objective 1. Using a combined ratio estimator, we estimated the proportion of live trees infected in the GYE in the initial time-step (2004-2007) to be 0.22 (0.031 SE). Following the completion of all surveys in the revisit time-step (2008-2011), we estimated the proportion of live trees infected with white pine blister rust as 0.23 (0.028 SE; Table 2). We detected no significant change in the proportion of trees infected in the GYE between the two time-steps. Objective 2. We documented blister rust canker locations as occurring in the canopy or bole. We compared changes in canker position between the initial time-step (2004-2007) and the revisit time-step (2008-2011) in order to assess changes in infection severity. This analysis included the 3,795 trees tagged during the initial time-step that were located and documented as alive at the end of the revisit time-step. At the end of the revisit time-step, we found 1,217 trees infected with blister rust. This includes the 287 newly tagged trees in the revisit time step of which 14 had documented infections. Of these 1,217 trees, 780 trees were infected with blister rust in both time steps. Trees with only canopy cankers made up approximately 43% (519 trees) of the total number of trees infected with blister rust at the end of the revisit time-step, while trees with only bole cankers comprised 20% (252 trees), and those with both canopy and bole cankers included 37% (446 trees) of the infected sample. A bole infection is considered to be more consequential than a canopy canker, as it compromises not only the overall longevity of the tree, but its functional capacity for reproductive output as well (Kendall and Arno 1990, Campbell and Antos 2000, McDonald and Hoff 2001, Schwandt and Kegley 2004). In addition to infection location, we also documented infection transition between the canopy and bole. Of the 780 live trees that were infected with blister rust in both time-steps, approximately 31% (242) maintained canopy cankers and 36% (281) retained bole infections at the end of the revisit time-step. Infection transition from canopy to bole occurred in 30% (234) of the revisit time-step trees while 3% (23) transitioned from bole to canopy infections during this period. Objective 3. To determine whitebark pine mortality, we resurveyed all belt transects to reassess the life status of permanently tagged trees >1.4 m tall. We compared the total number of live tagged trees recorded during monitoring transect establishment to the total number of resurveyed dead tagged trees recorded during the revisit time-step and identified all potential mortality-influencing conditions (blister rust, mountain pine beetle, fire and other). By the end of the revisit time-step, we observed a total of 975 dead tagged whitebark pine trees; using a ratio estimator, this represents a loss of approximately 20% (SE=4.35%) of the original live tagged tree population (GYWPMWG 2012). Objective 4. To investigate the proportion of live, reproducing tagged trees, we divided the total number of positively identified cone-bearing trees by the total number of live trees in the tagged tree sample at the end of the revisit time-step. To approximate the average density of recruitment trees per stand, trees ≤1.4 m tall were summed by stand (within the 500 m² transect area) and divided by the total number of stands. Reproducing trees made up approximately 24% (996 trees) of the total live tagged population at the end of the revisit time-step. Differentiating between whitebark pine and limber pine seedlings or saplings is problematic given the absence of cones or cone scars. Therefore, understory summaries as presented in this report may include individuals of both species when they are sympatric in a stand. The average density of small trees ≤1.4 m tall was 53 understory trees per 500 m². Raw counts of these understory individuals ranged from 0-635 small trees per belt transect. In addition, a total of 287 trees were added to the tagged tree population by the end of 2011. These newly tagged trees were individuals that upon subsequent revisits had reached a height of >1.4 m tall and subsequently added to the sample. Throughout the past decade in the GYE, monitoring has helped document shifts in whitebark pine forests; whitebark pine stands have been impacted by insect, pathogen, wildland fire, and other disturbance events. Blister rust infection is ubiquitous throughout the ecosystem and infection proportions are variable across the region. And while we have documented mortality of whitebark pine, we have also recorded considerable recruitment. We provide this first step-trend report as a quantifiable baseline for understanding the state of whitebark pine in the GYE. Many aspects of whitebark pine health are highly variable across the range of its distribution in the GYE. Through sustained implementation of the monitoring program, we will continue efforts to document and quantify whitebark pine forest dynamics as they arise under periodic upsurges in insect, pathogen, fire episodes, and climatic events in the GYE. Since its inception, this monitoring program perseveres as one of the only sustained longterm efforts conducted in the GYE with a singular purpose to track the health and status of this prominent keystone species.

Natural Resource Technical Report↗
USGS2023

2021–2022 Statewide Abundance Estimates for the Florida Manatee

Knowing the population size of Florida manatees ( Trichechus manatus latirostris ) is critical for conservation and management of this threatened species. Martin et al. (2015) and Hostetler et al. (2018) applied statistical models that incorporated multiple data sources to estimate the statewide abundance of manatees from aerial surveys f lown in 2011–2012 and 2015–2016. We conducted additional aerial surveys in 2021–2022 and applied similar models to provide an updated abundance estimate. This report serves as an update to Hostetler et al. (2018), with most of the text and methodology adapted from the previous report, and provides updated population estimates based on the newly available data. We estimate that the number of manatees in Florida in 2021–2022 was 9,790 (95% Bayesian credible interval 8,350–11,730), of which 4,630 (3,960–5,420) were on the west coast of Florida and 5,160 (3,940–6,980) were on the east coast. These estimates and the associated uncertainty, in addition to being of immediate value to wildlife managers, are essential new data for incorporation into integrated population models and population viability analyses. We also provide context for interpreting the new estimates and perspectives for future modeling improvements.

Florida↗
USGS2000

A comprehensive review of Farm Bill contributions to wildlife conservation, 1985-2000

A comprehensive review of the scientific literature was undertaken to determine wildlife responses to programs established under the conservation title of the 1985 Food Security Act as amended in 1990 and 1996 (Farm Bill). Literature was annotated and summaries of wildlife responses were provided for the Conservation Reserve Program CRP, Wetlands Reserve Program (WRP), Wildlife Habitat Incentives Program (WHIP) and Environmental Quality Incentives Program (EQIP). The report recognized that Farm Bill conservation programs were created to serve many purposes. Foremost among these purposes was to enable Americaa??s farmers and ranchers to be better stewards of their lands. In general, wildlife responded positively to improvements in land stewardship, particularly when the needs of wildlife were considered in conservation planning and implementation. Whereas authors acknowledged that their understanding of wildlife responses to Farm Bill conservation programs was still incomplete, they concluded that these programs were making significant contributions toward conservation of the nationa??s fish and wildlife resources.

Technical Report↗
USGS1959

Annual water-level measurements in observation wells, 1951-1955, and atlas of maps showing changes in water levels for various periods from beginning of record through 1954, New Mexico

This report tabulates the annual measurements of water level in the observation wells in the various irrigated areas, primarily from 1951 through 1955. It summarizes changes in water level by discussion and with an atlas of nearly all the maps of change of water level for the period of record to 1955 for each area in which observations are being made. Included also are hydrographs for the period of record through 1954 of several selected wells in the various areas irrigated from ground-water sources. The annual measurements of water level before 1951, seasonal measurements, and daily records of water levels in wells equipped with recording gages have been published in an annual series of U. S. Geological Survey water-supply papers.

New Mexico↗
USGS2016

Climate change and indigenous peoples: A synthesis of current impacts and experiences

A growing body of literature examines the vulnerability, risk, resilience, and adaptation of indigenous peoples to climate change. This synthesis of literature brings together research pertaining to the impacts of climate change on sovereignty, culture, health, and economies that are currently being experienced by Alaska Native and American Indian tribes and other indigenous communities in the United States. The knowledge and science of how climate change impacts are affecting indigenous peoples contributes to the development of policies, plans, and programs for adapting to climate change and reducing greenhouse gas emissions. This report defines and describes the key frameworks that inform indigenous understandings of climate change impacts and pathways for adaptation and mitigation, namely, tribal sovereignty and self-determination, culture and cultural identity, and indigenous community health indicators. It also provides a comprehensive synthesis of climate knowledge, science, and strategies that indigenous communities are exploring, as well as an understanding of the gaps in research on these issues. This literature synthesis is intended to make a contribution to future efforts such as the 4th National Climate Assessment, while serving as a resource for future research, tribal and agency climate initiatives, and policy development.

General Technical Report↗
USGS2010

Establishing a nationwide baseline of historical burn-severity data to support monitoring of trends in wildfire effects and national fire policies

There is a need to provide agency leaders, elected officials, and the general public with summary information regarding the effects of large wildfires. Recently, the Wildland Fire Leadership Council (WFLC), which implements and coordinates National Fire Plan (NFP) and Federal Wildland Fire Management Policies adopted a strategy to monitor the effectiveness and effects of the National Fire Plan and the Healthy Forests Restoration Act. One component of this strategy is to assess the environmental impacts of large wildland fires and identify the trends of burn severity on all lands across the United States. To that end, WFLC has sponsored a 6-year project, Monitoring Trends in Burn Severity (MTBS), which requires the U.S. Department of Agriculture, Forest Service (USDA-FS) and the U.S. Geological Survey (USGS) to map and assess the burn severity for all large current and historical fires. Using Landsat data and the differenced Normalized Burn Ratio (dNBR) algorithm, the USGS/EROS Data Center and USDA-FS/ Remote Sensing Applications Center will map burn severity of all fires occurring from 1984 to 2010. Only fires that are greater than 500 ac in the East, and 1,000 ac in the West will be included. We anticipate mapping a total of more than 9,000 historical fires and fires that occur during the course of the study. The MTBS project will generate burn-severity data, maps, and reports, which will be available for use at local, State, and national levels to evaluate trends in burn severity and help develop and assess the effectiveness of land management decisions. Additionally, the information developed will provide a baseline from which to monitor the recovery and health of fire-affected landscapes over time. Spatial and tabular data quantifying burn severity will augment existing information used to estimate risk associated with a range of current and future resource threats. For example, fire severity data along with associated biophysical characteristics provide an analytical basis for assessing risk from invasive species as well as native insects and pathogens. All data and results will be distributed to the public via a Web interface.

General Technical Report↗
USGS2012

Palila abundance estimates and trend

The Palila (Loxioides bailleui) is an endangered, seed-eating, finch-billed honeycreeper found only on Hawai`i Island. Once occurring on the islands of Kaua`i and O`ahu and Mauna Loa and Hualālai volcanoes of Hawai`i, Palila are now found only in subalpine, dry-forest habitats on Mauna Kea (Banko et al. 2002). Previous analyses showed that Palila numbers fluctuated throughout the 1980s and 1990s but declined rapidly and steadily since 2003 (Jacobi et al. 1996, Leonard et al. 2008, Banko et al. 2009, Gorresen et al. 2009, Banko et al. in press). The aim of this report is to update abundance estimates for the Palila based on the 2012 surveys. We assess Palila trends over two periods: 1) the long-term trend during 1998–2012 and 2) the short-term trajectory between 2003 and 2012. The first period evaluates the population trend for the entire time series since additional transects were established (Johnson et al. 2006). These additional transects were established to produce a more precise population estimate and provide more complete coverage of the Palila range. The initial year for short-term trajectory was chosen subjectively to coincide with the recent decline in the Palila population. Additionally, stations in the core Palila habitat were surveyed on two occasions in 2012, thus allowing us to address the question of how repeat samples improve estimate precision.

Technical Report↗
USGS2014

Geospatial optimization of siting large-scale solar projects

Recent policy and economic conditions have encouraged a renewed interest in developing large-scale solar projects in the U.S. Southwest. However, siting some large-scale solar projects, such as concentrating solar power (CSP), is complex. In addition to the quality of the solar resource, solar developers must take into consideration many environmental, social, and economic factors when evaluating a potential site. This report describes a proof-of-concept, Web-based Geographical Information Systems (GIS) tool that evaluates multiple user-defined criteria in an optimization algorithm to inform discussions and decisions regarding the locations of utility- scale solar projects. Existing siting recommendations for large-scale solar projects from governmental and non-governmental organizations are not consistent with each other, are often not transparent in methods, and do not take into consideration the differing priorities of stakeholders. The siting assistance GIS tool we have developed improves upon the existing siting guidelines by being user-driven, transparent, interactive, capable of incorporating multiple criteria, and flexible. This work provides the foundation for a dynamic siting assistance tool that can greatly facilitate siting decisions among multiple stakeholders.

Arizona;California;Colorado;Idaho;Montana;Nevada;N↗
USGS2024

Analysis and review of fishery-dependent data for Hawaiian nearshore noncommercial fisheries

Noncommercial, shore-based fisheries provide economic, social, and cultural services to communities throughout the Hawaiian Islands. The State of Hawai‘i Department of Land and Natural Resources (DLNR), Division of Aquatic Resources (DAR) routinely conducts surveys to monitor noncommercial fisheries such that estimates of fishing effort and catch by gear type can be generated and used to implement more sustainable management practices. DAR executes both the Hawai‘i Marine Recreational Fishery Survey (HMRFS), a nationally standardized survey that focuses on intercepting fishers at access points (i.e., boat ramps) across the main Hawaiian Islands, and a set of roving creel surveys on O‘ahu, Maui Nui, and Kaua‘i that observe and intercept fishers at locations along the shoreline outside of those targeted by HMRFS. The latter set of creel surveys were designed to complement HMRFS by expanding its geographic coverage and thus providing a more representative picture of noncommercial fishing in Hawai‘i. Sustainable management priorities set by DAR rely on the availability of statewide, fishery- dependent data. Thus, we collate information from island-based roving creel surveys into a cohesive Statewide Creel Survey Database. Further, we provide preliminary analyses and describe ways that surveys could be streamlined to improve future data collection, analysis, and utility. In so doing, we synthesize the most detailed information to-date about noncommercial shore-based fisheries of Hawai‘i. The unprecedented spatial and temporal coverage of DAR’s dataset reveals the value of their survey efforts over the last decade to address fishery management needs. Our primary objectives, results, and conclusions are summarized below: 1) Integrate DAR roving creel survey data from different islands into a single Statewide Creel Survey Dataset (Chapter II). We describe the collation of creel survey data from O‘ahu, Maui Nui, and Kaua‘i into a statewide dataset. We also offer ways in which these surveys could be streamlined to meet the needs of managers and decision makers. Briefly, these are to create a statewide strategic plan, standardize the execution of standard operating procedures, centralize the creel survey database and associated metadata, and consider using technology that improves the data pipeline, including transitioning from paper-based to electronic systems for data entry and processing. 2) Assess whether the new Statewide Creel Survey Dataset can provide inputs for length-based stock assessments (Chapter III). Only on Maui were interviews conducted with associated catch data. There was reasonably high taxonomic coverage (42 species from 186 interviews with 310 fishers), but low sample sizes for nearly all species precluded the development of length-based stock assessments. We provide summary statistics from the existing data and briefly discuss how technologies could be used to automate analysis of images of noncommercial catch. 3) Analyze the Statewide Creel Survey Dataset for spatial and temporal patterns in fishing effort (Chapter IV): a. Visualizing noncommercial fishing pressure . We found that fishing effort (mean number of fishers observed per survey event at a site) on O'ahu was over three times greater than that recorded during similar surveys conducted on Maui or Kaua'i. We create maps that display the distribution of angling and spearfishing effort around each of the three islands. b. Factors that predict fishing “hotspots” around Maui . Fishing effort on Maui was associated with areas with more wave power and less parking availability. There were half as many fishers in areas with parking lots than in areas with parking on the road shoulder only. c. Changes in fishing effort during the COVID-19 pandemic . There was no change in fishing effort on O‘ahu during the first year of the pandemic, but there was a 20% decline in year 2 and a 33% decline in year 3, both in comparison to pre-pandemic levels. Pre-pandemic creel survey data were unavailable for Maui and Kaua‘i, but fishing effort on these islands also declined as the pandemic progressed at similar or greater rates than those observed on O‘ahu. 4) Quantify potential bias in survey methods by experimentally deriving fisher detection probabilities of shore-based and drone-based surveys (Chapter V): a. Shore-based surveys . We conducted roving creel surveys for four months at three locations around Hilo Bay, designed to emulate and estimate the efficacy of DAR standard operating procedures. There was high agreement between paired observers in counting fishers, leading to near-perfect detection probabilities of both anglers (94%) and spearfishers (97%), but relatively low agreement and detection probabilities of other fishers (throw net, ‘opihi picking, etc.) (52%). b. Drone-based surveys . We used an unmanned aerial vehicle (UAV; operated by DAR staff) to collect imagery of fishers along the Hilo Bay shoreline. We used still images and video clips (with known fishing activity) to build an online survey that was distributed to DAR and HCFRU personnel, asking them to count and categorize resource users as a snorkeler, spearfisher, angler, or other fisher. Only 40.0% of the responses correctly counted and categorized resource users in the image. Anglers were correctly identified and enumerated in 90.0% of the responses, but the correct response rates of the other three user categories ranged from 67.8% – 79.4%. Snorkelers and anglers tended to be undercounted while spearfishers and other fishers were overcounted. 5) Review the potential for incorporating emerging technologies that will improve, augment, and evolve creel survey data collection, especially for spearfishing (Chapter VI). Within the context of monitoring shore-based noncommercial fishing, we review the use of electronic data entry/processing systems with geospatial and image capabilities, field cameras, drones, smart buoys, citizen science apps, data mining social media, artificial intelligence and machine learning. We highlight several of the challenges and considerations when implementing these technologies into creel surveys and provide a synthesis of options that could be used to better estimate spearfishing. The general conclusion of this assessment is that the DAR roving creel survey program is collecting valuable data that supplement the existing HMRFS efforts. However, there are a number of areas that could be improved to make these efforts a more effective tool for decision-making processes in resource management and conservation: 1) Establishment of clear statewide and island objectives for the Statewide Creel Survey Dataset. Currently, data collection efforts are focused towards addressing a very broad purpose – supplementing the HMRFS data collection efforts. However, the results of the preliminary analyses conducted as part of this project suggest that the data could be used to address other areas of need if these objectives were clearly defined. Further, the design of the creel survey would benefit from greater standardization of survey protocols between islands and an effort to define a) the acceptable margins of error associated with the estimates generated by these data and b) the minimum level of change that the surveys would need to detect to be useful to managers. 2) Centralization of data entry, data quality assessment, and data accessibility. Currently, each DAR office manages data entry, checks the data for errors, and is responsible for managing and storing the data. Instituting a centralized data entry system, particularly an online database that can receive survey data from tablets or smartphones running a standardized data collection application would improve efficiency, reduce data entry errors, and accelerate the availability of data to managers. A substantial amount of time and effort from the project described in this report was devoted to checking the dataset for errors. The development and application of data quality assurance protocols would ensure that the data are reliable and available in a timely fashion to support management decisions. 3) Address lingering questions regarding the efficacy of current survey protocols to capture and characterize the spearfishing component of the noncommercial fishery. The results presented in the report suggest that the current creel survey protocols do a good job detecting spearfishers when present but are not capturing sufficient data about their catch or total effort. There are also questions remaining as to whether the survey times and sites are sufficiently capturing the behavior of spearfishers in Hawai‘i. A more thorough assessment – whether through additional research, alteration of survey design, or review of data by representatives of the spearfishing community – would provide insight on how to use the Statewide Creel Survey Database to inform management of spearfishing. 4) Investigate the integration of technological advancements into the creel survey methods. As priorities and needs are developed and formalized, it would be valuable to consider how various technological advancements might enhance and streamline data collection or open new avenues of inquiry.

Hawaii↗
USGS2025

Gulf Coast Basin CORE-CM initiative final report

The Bureau of Economic Geology at the University of Texas at Austin (UT-BEG) is leading the Gulf Coast Carbon Ore, Rare Earth, and Critical Minerals (CORE-CM) Initiative to assess the potential to produce critical minerals (CMs), including rare earth elements (REEs) from coal, coal ash, and produced water related to oil and gas production, and related materials (alumina processing waste [red mud], heavy mineral sands, graphite, and zeolite) within the Gulf Coast Basin. This project represents the first phase in a long-term program and provides reconnaissance data that will be foundational for future work by assessing resources and suggesting plans to be conducted in future work and expanding stakeholder engagement. The project includes several tasks designed to identify, characterize, and assess several necessary aspects for development of CMs and REEs in the Gulf Coast Basin.

Gulf Coast basin↗
USGS2023

Partnering in search of answers: Seabird die-offs in the Bering and Chukchi Seas

Prior to 2015, seabird die-offs in Alaskan waters were rare; they typically occurred in mid-winter, linked to epizootic disease events or above-average ocean temperatures associated with strong El Nino-Southern Oscillation events (Bodenstein et al. 2015, Jones et al. 2019, Romano et al. 2020). Since 2015, the U.S. Fish and Wildlife Service (USFWS) has monitored mortality events that have become annual occurrences in Alaska (Fig. 1). Since 2017, communities on the coasts of the northern Bering and southern Chukchi Seas have annually observed dead and dying seabirds along their coasts, although such die-offs have not been reported from communities north of Point Hope. (Fig. 2). Affected species included planktivorous birds such as auklets ( Aethia spp.) and shearwaters ( Ardenna spp.), piscivorous murres ( Uria spp.), puffins ( Fratercula spp.), and kittiwakes ( Rissa spp.), as well as low numbers of benthic feeding sea ducks ( Somateria spp.). The range of seabird species and the different prey species involved, with localized events throughout summer and over widespread areas, indicate environmental causes at multiple trophic levels. Such wildlife mortality events are a public health concern for coastal communities that rely on ocean resources for their nutritional, cultural, and economic well-being. They have also been seen as a harbinger of concern for the state of the Arctic Ocean itself.

Alaska↗
USGS2013

National Park Service Vegetation Inventory Program, Cuyahoga Valley National Park, Ohio

The National Park Service (NPS) Vegetation Inventory Program (VIP) is an effort to classify, describe, and map existing vegetation of national park units for the NPS Natural Resource Inventory and Monitoring (I&M) Program. The NPS VIP is managed by the NPS Biological Resources Management Division and provides baseline vegetation information to the NPS Natural Resource I&M Program. The U.S. Geological Survey (USGS) Vegetation Characterization Program lends a cooperative role in the NPS VIP. The USGS Upper Midwest Environmental Sciences Center, NatureServe, and NPS Cuyahoga Valley National Park (CUVA) have completed vegetation classification and mapping of CUVA. Mappers, ecologists, and botanists collaborated to identify and describe vegetation types within the National Vegetation Classification Standard (NVCS) and to determine how best to map them by using aerial imagery. The team collected data from 221 vegetation plots within CUVA to develop detailed descriptions of vegetation types. Data from 50 verification sites were also collected to test both the key to vegetation types and the application of vegetation types to a sample set of map polygons. Furthermore, data from 647 accuracy assessment (AA) sites were collected (of which 643 were used to test accuracy of the vegetation map layer). These data sets led to the identification of 45 vegetation types at the association level in the NVCS at CUVA. A total of 44 map classes were developed to map the vegetation and general land cover of CUVA, including the following: 29 map classes represent natural/semi-natural vegetation types in the NVCS, 12 map classes represent cultural vegetation (agricultural and developed) in the NVCS, and 3 map classes represent non-vegetation features (open-water bodies). Features were interpreted from viewing color-infrared digital aerial imagery dated October 2010 (during peak leaf-phenology change of trees) via digital onscreen three-dimensional stereoscopic workflow systems in geographic information systems (GIS). The interpreted data were digitally and spatially referenced, thus making the spatial database layers usable in GIS. Polygon units were mapped to either a 0.5 ha or 0.25 ha minimum mapping unit, depending on vegetation type. A geodatabase containing various feature-class layers and tables shows the locations of vegetation types and general land cover (vegetation map), vegetation plot samples, verification sites, AA sites, project boundary extent, and aerial photographic centers. The feature-class layer and relate tables for the CUVA vegetation map provides 4,640 polygons of detailed attribute data covering 13,288.4 ha, with an average polygon size of 2.9 ha. Summary reports generated from the vegetation map layer show map classes representing natural/semi-natural types in the NVCS apply to 4,151 polygons (89.4% of polygons) and cover 11,225.0 ha (84.5%) of the map extent. Of these polygons, the map layer shows CUVA to be 74.4% forest (9,888.8 ha), 2.5% shrubland (329.7 ha), and 7.6% herbaceous vegetation cover (1,006.5 ha). Map classes representing cultural types in the NVCS apply to 435 polygons (9.4% of polygons) and cover 1,825.7 ha (13.7%) of the map extent. Map classes representing non-NVCS units (open water) apply to 54 polygons (1.2% of polygons) and cover 237.7 ha (1.8%) of the map extent. A thematic AA study was conducted of map classes representing natural/semi-natural types in the NVCS. Results present an overall accuracy of 80.7% (kappa index of 79.5%) based on data from 643 of the 647 AA sites. Most individual map-class themes exceed the NPS VIP standard of 80% with a 90% confidence interval. The CUVA vegetation mapping project delivers many geospatial and vegetation data products in hardcopy and/or digital formats. These products consist of an in-depth project report discussing methods and results, which include descriptions and a dichotomous key to vegetation types, map classification and map-class descriptions, and a contingency table showing AA results. The suite of products also includes a database of vegetation plots, verification sites, and AA sites; digital pictures of field sites; field data sheets; aerial photographic imagery; hardcopy and digital maps; and a geodatabase of vegetation types and land cover (map layer), fieldwork locations (vegetation plots, verification sites, and AA sites), aerial photographic index, project boundary, and metadata. All geospatial products are projected in Universal Transverse Mercator, Zone 17, by using the North American Datum of 1983. Information on the NPS VIP and completed park mapping projects are located on the Internet at <http://science.nature.nps.gov/im/inventory/veg> and <http://www.usgs.gov/core_science_systems/csas/vip/index.html>.

Natural Resource Technical Report↗
USGS2017

Extent and persistence of secondary water quality impacts after enhanced reductive bioremediation

Electron donor (ED) addition can be very effective in stimulating enhanced reductive bioremediation (ERB) of a wide variety of groundwater contaminants. However, ERB can result in Secondary Water Quality Impacts (SWQIs) including decreased levels of dissolved oxygen (O 2 ), nitrate (NO 3- ), and sulfate (SO 4 2- ), and elevated levels of dissolved manganese (Mn 2+ ), dissolved iron (Fe 2+ ), methane (CH 4 ), sulfide (S 2- ), organic carbon, and naturally occurring hazardous compounds (e.g., arsenic). Fortunately, this ‘plume’ of impacted groundwater is usually confined within the original contaminant plume and is unlikely to adversely impact potable water supplies. This report summarizes available information on processes controlling the production and natural attenuation of SWQI parameters and can be used as a guide in understanding the magnitude, areal extent, and duration of SWQIs in ERB treatment zones and the natural attenuation of SWQI parameters as the dissolved solutes migrate downgradient with ambient groundwater flow. This information was compiled from a wide variety of sources including a survey and statistical analysis of SWQIs from 47 ERB sites, geochemical model simulations, field studies at sites where organic-rich materials have entered the subsurface (e.g., wastewater, landfill leachate, and hydrocarbon plumes), and basic information on physical, chemical, and biological processes in the subsurface. This information is then integrated to provide a general conceptual model of the major processes controlling SWQI production and attenuation.

Technical Report↗