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46 records · Page 3Linked to original sources
USGS1998

Quality-Assurance/Quality-Control Manual for Collection and Analysis of Water-Quality Data in the Ohio District, US Geological Survey

The U.S. Geological Survey (USGS), Water Resources Division (WRD), requires that quality-assurance/quality-control (QA/QC) activities be included in any sampling and analysis program. Operational QA/QC procedures address local needs while incorporating national policies. Therefore, specific technical policies were established for all activities associated with water-quality project being done by the Ohio District. The policies described in this report provide Ohio District personnel, cooperating agencies, and others with a reference manual on QA/QC procedures that are followed in collecitng and analyzing water-quality samples and reporting water-quality information in the Ohio District. The project chief, project support staff, District Water-Quality Specialist, and District Laboratory Coordinator are all involved in planning and implementing QA/QC activities at the district level. The District Chief and other district-level managers provide oversight, and the Regional Water-Quality Specialist, Office of Water Quality (USGS headquarters), and the Branch of Quality Systems within the Office of Water Quality create national QA/QC polices and provide assistance to District personnel. In the literature, the quality of all measurement data is expressed in terms of precision, variability, bias, accuracy, completeness, representativeness, and comparability. In the Ohio District, bias and variability will be used to describe quality-control data generated from samples in the field and laboratory. Each project chief must plan for implementation and financing of QA/QC activities necessary to achieve data-quality objectives. At least 15 percent of the total project effort must be directed toward QA/QC activities. Of this total, 5-10 percent will be used for collection and analysis of quality-control samples. This is an absolute minimum, and more may be required based on project objectives. Proper techniques must be followed in the collection and processing of surface-water, ground-water, biological, precipitation, bed-sediment, bedload, suspended-sediment, and solid-phase samples. These techniques are briefly described in this report and are extensively documented. The reference documents listed in this report will be kept by the District librarian and District Water-Quality Specialist and updated regularly so that they are available to all District staff. Proper handling and documentation before, during, and after field activities are essential to ensure the integrity of the sample and to correct erroneous reporting of data results. Field sites are to be properly identified and entered into the data base before field data-collection activities begin. During field activities, field notes are to be completed and sample bottles appropriately labeled a nd stored. After field activities, all paperwork is to be completed promptly and samples transferred to the laboratory within allowable holding times. All equipment used by District personnel for the collection and processing of water-quality samples is to be properly operated, maintained, and calibrated by project personnel. This includes equipment for onsite measurement of water-quality characteristics (temperature, specific conductance, pH, dissolved oxygen, alkalinity, acidity, and turbidity) and equipment and instruments used for biological sampling. The District Water-Quality Specialist and District Laboratory Coordinator are responsible for preventive maintenance and calibration of equipment in the Ohio District laboratory. The USGS National Water Quality Laboratory in Arvada, Colo., is the primary source of analytical services for most project work done by the Ohio District. Analyses done at the Ohio District laboratory are usually those that must be completed within a few hours of sample collection. Contract laboratories or other USGS laboratories are sometimes used instead of the NWQL or the Ohio District laboratory. When a contract laboratory is used, the projec

Water-Resources Investigations Report↗
USGS1975

Water-resources investigations of the U.S. Geological Survey in the northern Great Plains coal region of Wyoming, Montana, and North Dakota, 1975

The Geological Survey's Water Resources Division has for many years maintained a program of water-resources investigations that includes the coal regions of Wyoming, Montana, and North Dakota. These programs have been supported by State and local agencies and by other agencies of the Federal government, largely to provide data for water-resources development projects, allocations of water, and to inventory of water resources for future planning. The recent interest in coal has added new dimensions and greater intensity to the investigations. The work has expanded to include monitoring the environmental effects of coal mining and processing and to determine the availability of additional water supplies for coal-conversion plants and related demands. New objectives are now reflected in the program. Much of the work is to assist the Bureau of Land Management in its responsibilities to minimize the possible detrimental effects of coal mining on the public resource lands. The Environmental Protection Agency also supports a significant part of the program. Their support is to assure that water-quality information is collected at key locations, with types of water-quality data and frequency of sampling needed by that agency in the discharge of its function. Relatively large increases in the program have been funded by direct appropriation to the Geological Survey. This report describes the water-resources investigation program that is currently in operation. Locations of gaging stations and water-quality measuring sites, frequencies and parameters, and areas of groundwater studies are included in this report. Brief descriptions of coal-related studies by investigators who are headquartered outside the Northern Great Plains coal regions are also included. Such studies are research in topics related to coal extraction, water supply, and post-mining reclamation

Montana, North Dakota, Wyoming↗
USGS1985

Federal-State Cooperative Program in Kansas, seminar proceedings, July 1985

During the past few years, water-resource management in Kansas has undergone reorientation with the creation of the Kansas Water Authority and the Kansas Water office. New thrusts toward long-term goals based on the Kansas State Water plan demand strong communication and coordination between all water-related agencies within the State. The seminar discussed in this report was an initial step by the Kansas Water Office to assure the continued presence of a technical-coordination process and to provide an opportunity for the U.S. Geological Survey to summarize their technical-informational activities in Kansas for the benefit of State and Federal water agencies with the State. The seminar was held on July 8 and 9, 1985, in Lawrence, Kansas. The agenda included a summary of the data-collection activities and short synopses of projects completed within the past year and those currently underway. The data program discussions described the information obtained at the surface water, groundwater, water quality, and sediment sites in Kansas. Interpretive projects summarized included studies in groundwater modeling, areal hydrologic analysis, regional analysis of floods , low-flow, high-flow, and flow-volume characteristics, water quality of groundwater and lakes, and traveltime and transit-loss analysis. (USGS)

Open-File Report↗
USGS2011

Quality assurance and quality control of geochemical data—A primer for the research scientist

Geochemistry is a constantly expanding science. More and more, scientists are employing geochemical tools to help answer questions about the Earth and earth system processes. Scientists may assume that the responsibility of examining and assessing the quality of the geochemical data they generate is not theirs but rather that of the analytical laboratories to which their samples have been submitted. This assumption may be partially based on knowledge about internal and external quality assurance and quality control (QA/QC) programs in which analytical laboratories typically participate. Or there may be a perceived lack of time or resources to adequately examine data quality. Regardless of the reason, the lack of QA/QC protocols can lead to the generation and publication of erroneous data. Because the interpretations drawn from the data are primary products to U.S. Geological Survey (USGS) stakeholders, the consequences of publishing erroneous results can be significant. The principal investigator of a scientific study ultimately is responsible for the quality and interpretation of the project's findings, and thus must also play a role in the understanding, implementation, and presentation of QA/QC information about the data. Although occasionally ignored, QA/QC protocols apply not only to procedures in the laboratory but also in the initial planning of a research study and throughout the life of the project. Many of the tenets of developing a sound QA/QC program or protocols also parallel the core concepts of developing a good study: What is the main objective of the study? Will the methods selected provide data of enough resolution to answer the hypothesis? How should samples be collected? Are there known or unknown artifacts or contamination sources in the sampling and analysis methods? Assessing data quality requires communication between the scientists responsible for designing the study and those collecting samples, analyzing samples, treating data, and interpreting results. This primer has been developed to provide basic information and guidance about developing QA/QC protocols for geochemical studies. It is not intended to be a comprehensive guide but rather an introduction to key concepts tied to a list of relevant references for further reading. The guidelines are presented in stepwise order beginning with presampling considerations and continuing through final data interpretation. The goal of this primer is to outline basic QA/QC practices that scientists can use before, during, and after chemical analysis to ensure the validity of the data they collect with the goal of providing defendable results and conclusions.

Open-File Report↗
USGS1952

Water resources of the Lake Erie shore region in Pennsylvania

An abundant supply of water is available to the Lake Erie Shore region in Pennsylvania. Lake i£rie furnishes an almost inexhaustible supply of water of satisfactory chemical quality. Small quantities of water are available from small streams in the area and from the ground. A satisfactory water supply is one of the factors that affect the economic growth of a region. Cities and towns must have adequate amounts of pure water for human consumption. Industries must have suitable water ih sufficient quantities for all purposes. In order to assure. success and economy, the development of water resources should be based on adequate knowledge of the quantity and quality of the water. As a nation, we can not afford to run the risk of dissipating our resources, especially in times of national emergency, by building projects that are not founded on sound engineering and adequate water-resources information. The purpose of this report is to summarize and interpret all available water-resources information for the Lake Erie Shore region in Pennsylvania. The report will be useful for initial guidance in the location or expansion of water facilities for defense and nondefense industries and the municipalities upon which they are dependent. It will also be useful in evaluating the adequacy of the Geological Survey's part of the basic research necessary to plan the orderly development of the water resources of the Lake Erie Shore region. Most of the data contained inthis report have been obtained'by the U. S. Geological Survey in cooperation with the Pennsylvania Department of Forests and Waters, the Pennsylvania Department of Internal Affairs, and the Pennsylvania State Planning Board, Department of Commerce. The Pennsylv~nia Department of Health furnished information on water pollution. The report was prepared in the Water Resources Division of the U. S. Geological Survey b:y John W. Mangan (Surface Water). Donald W. VanTuyl (Ground Water). and Walter F. White, Jr. (Quality of Water), under the general direction of C. G. Paulsen, chief hydraulic engineer.

Circular↗
USGS2008

Using the U.S. Geological Survey National Water Quality Laboratory LT-MDL to Evaluate and Analyze Data

A long-term method detection level (LT-MDL) and laboratory reporting level (LRL) are used by the U.S. Geological Survey?s National Water Quality Laboratory (NWQL) when reporting results from most chemical analyses of water samples. Changing to this method provided data users with additional information about their data and often resulted in more reported values in the low concentration range. Before this method was implemented, many of these values would have been censored. The use of the LT-MDL and LRL presents some challenges for the data user. Interpreting data in the low concentration range increases the need for adequate quality assurance because even small contamination or recovery problems can be relatively large compared to concentrations near the LT-MDL and LRL. In addition, the definition of the LT-MDL, as well as the inclusion of low values, can result in complex data sets with multiple censoring levels and reported values that are less than a censoring level. Improper interpretation or statistical manipulation of low-range results in these data sets can result in bias and incorrect conclusions. This document is designed to help data users use and interpret data reported with the LTMDL/ LRL method. The calculation and application of the LT-MDL and LRL are described. This document shows how to extract statistical information from the LT-MDL and LRL and how to use that information in USGS investigations, such as assessing the quality of field data, interpreting field data, and planning data collection for new projects. A set of 19 detailed examples are included in this document to help data users think about their data and properly interpret lowrange data without introducing bias. Although this document is not meant to be a comprehensive resource of statistical methods, several useful methods of analyzing censored data are demonstrated, including Regression on Order Statistics and Kaplan-Meier Estimation. These two statistical methods handle complex censored data sets without resorting to substitution, thereby avoiding a common source of bias and inaccuracy.

Open-File Report↗
USGS2013

Saltwater intrusion in the surficial aquifer system of the Big Cypress Basin, southwest Florida, and a proposed plan for improved salinity monitoring

The installation of drainage canals, poorly cased wells, and water-supply withdrawals have led to saltwater intrusion in the primary water-use aquifers in southwest Florida. Increasing population and water use have exacerbated this problem. Installation of water-control structures, well-plugging projects, and regulation of water use have slowed saltwater intrusion, but the chloride concentration of samples from some of the monitoring wells in this area indicates that saltwater intrusion continues to occur. In addition, rising sea level could increase the rate and extent of saltwater intrusion. The existing saltwater intrusion monitoring network was examined and found to lack the necessary organization, spatial distribution, and design to properly evaluate saltwater intrusion. The most recent hydrogeologic framework of southwest Florida indicates that some wells may be open to multiple aquifers or have an incorrect aquifer designation. Some of the sampling methods being used could result in poor-quality data. Some older wells are badly corroded, obstructed, or damaged and may not yield useable samples. Saltwater in some of the canals is in close proximity to coastal well fields. In some instances, saltwater occasionally occurs upstream from coastal salinity control structures. These factors lead to an incomplete understanding of the extent and threat of saltwater intrusion in southwest Florida. A proposed plan to improve the saltwater intrusion monitoring network in the South Florida Water Management District’s Big Cypress Basin describes improvements in (1) network management, (2) quality assurance, (3) documentation, (4) training, and (5) data accessibility. The plan describes improvements to hydrostratigraphic and geospatial network coverage that can be accomplished using additional monitoring, surface geophysical surveys, and borehole geophysical logging. Sampling methods and improvements to monitoring well design are described in detail. Geochemical analyses that provide insights concerning the sources of saltwater in the aquifers are described. The requirement to abandon inactive wells is discussed.

Florida↗
USGS2020

USGS Telemetry Project

Telemetry of acoustically tagged bigheaded carp (i.e., bighead carp Hypophthalmichthys nobilis and silver carp H. molitrix ) and surrogate fish species has become an invaluable tool in management for these species in the upper Illinois Waterway Systems (i.e., upper Illinois River, lower Des Plaines River, and Chicago Area Waterway System). For example, movement probabilities between adjacent navigation pools need to be estimated to parameterize the Spatially Explicit Asian Carp Population Model (SEAcarP). SEAcarP is a population model used in scenario planning by the Monitoring and Response Workgroup (MRWG) to evaluate alternative management actions. These movement probabilities are estimated from the telemetry data obtained from a longitudinal network of strategically placed receivers that detect bigheaded carp that have been implanted with acoustic transmitters. In addition, fish removal by contracted fishers has become the primary method of controlling bigheaded carp in the upper Illinois and lower Des Plaines Rivers. Variable patterns in bigheaded carp distribution, habitat, and movement, influenced by seasonal and environmental conditions, make targeting bigheaded carp for removal and containment challenging and costly. Understanding these movement patterns for bigheaded carp through modeling and real-time telemetry applications informs removal efforts and facilitates monitoring and contingency actions based on fish movements. To develop a better understanding of fish movement dynamics to meet management objectives, an existing network of real-time and data-logging acoustic receivers in the upper Illinois Waterway Systems is collaboratively managed by a multi-agency team (see Participating Agencies section above). A Telemetry Workgroup has been established by the MRWG to ensure that the multi-agency telemetry efforts are coordinated to efficiently and effectively meet the MRWG goals. This workgroup plans and executes the placement of receivers, tagging of bigheaded carp with acoustic tags, and management of the telemetry data. Three primary objectives to meet MRWG goals identified by the Telemetry Workgroup included (1) development of a common standardized telemetry database with visualization and analysis tools, (2) transitioning from Program MARK (http://www.phidot.org/software/mark/) to a custom Bayesian multi-state model for estimating movement probabilities needed for SEAcarP and (3) deploying, maintaining, and serving data from real-time acoustic receivers to inform contingency planning and fish removal. A telemetry database and visualization tools (FishTracks) will facilitate standardization, archiving, sharing, quality assurance, visualization and analysis of the telemetry data needed for management. Modifications and additions to FishTracks will facilitate more problem-free use of the database and associated applications, as well as useful extraction of information to meet management goals. The transition to a custom Bayesian multi-state model to estimate movement probabilities will support more efficient, effective, and robust population modeling with SEAcarP by overcoming short comings of Program MARK for this purpose. These shortcomings include lack of customizability and extensibility, problems of singularities and poor-convergence, software crashes, parameter exclusion from models, an inability to consistently generate estimates of movement probability, and a lack of uncertainty estimates for movement probabilities. A real-time receiver network that is maintained and tested annually will ensure reliability and accuracy of the real-time alerts to bigheaded carp movements that can be used by management to plan contingency actions.

Illinois↗
USGS2018

Alaska

Alaska is the largest state in the Nation, almost one-fifth the size of the combined lower 48 United States, and is rich in natural capital resources. Alaska is often identified as being on the front lines of climate change since it is warming faster than any other state and faces a myriad of issues associated with a changing climate. The cost of infrastructure damage from a warming climate is projected to be very large, potentially ranging from $110 to $270 million per year, assuming timely repair and maintenance. Although climate change does and will continue to dramatically transform the climate and environment of the Arctic, proactive adaptation in Alaska has the potential to reduce costs associated with these impacts. This includes the dissemination of several tools, such as guidebooks to support adaptation planning, some of which focus on Indigenous communities. While many opportunities exist with a changing climate, economic prospects are not well captured in the literature at this time. As the climate continues to warm, there is likely to be a nearly sea ice-free Arctic during the summer by mid-century. Ocean acidification is an emerging global problem that will intensify with continued carbon dioxide (CO 2 ) emissions and negatively affects organisms. Climate change will likely affect management actions and economic drivers, including fisheries, in complex ways. The use of multiple alternative models to appropriately characterize uncertainty in future fisheries biomass trajectories and harvests could help manage these challenges. As temperature and precipitation increase across the Alaska landscape, physical and biological changes are also occurring throughout Alaska’s terrestrial ecosystems. Degradation of permafrost is expected to continue, with associated impacts to infrastructure, river and stream discharge, water quality, and fish and wildlife habitat. Longer sea ice-free seasons, higher ground temperatures, and relative sea level rise are expected to exacerbate flooding and accelerate erosion in many regions, leading to the loss of terrestrial habitat in the future and in some cases requiring entire communities or portions of communities to relocate to safer terrain. The influence of climate change on human health in Alaska can be traced to three sources: direct exposures, indirect effects, and social or psychological disruption. Each of these will have different manifestations for Alaskans when compared to residents elsewhere in the United States. Climate change exerts indirect effects on human health in Alaska through changes to water, air, and soil and through ecosystem changes affecting disease ecology and food security, especially in rural communities. Alaska’s rural communities are predominantly inhabited by Indigenous peoples who may be disproportionately vulnerable to socioeconomic and environmental change; however, they also have rich cultural traditions of resilience and adaptation. The impacts of climate change will likely affect all aspects of Alaska Native societies, from nutrition, infrastructure, economics, and health consequences to language, education, and the communities themselves. The profound and diverse climate-driven changes in Alaska’s physical environment and ecosystems generate economic impacts through their effects on environmental services. These services include positive benefits directly from ecosystems (for example, food, water, and other resources), as well as services provided directly from the physical environment (for example, temperature moderation, stable ground for supporting infrastructure, and smooth surface for overland transportation). Some of these effects are relatively assured and in some cases are already occurring. Other impacts are highly uncertain, due to their dependence on the structure of global and regional economies and future human alterations to the environment decades into the future, but they could be large. In Alaska, a range of adaptations to changing climate and related environmental conditions are underway and others have been proposed as potential actions, including measures to reduce vulnerability and risk, as well as more systemic institutional transformation.

Report↗
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↗