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Improving the Collection, Management, and Use of Marine Fisheries Data (2000)

Chapter: General Issues in the Collection, Management, and Use of Fisheries Data

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Suggested Citation:"General Issues in the Collection, Management, and Use of Fisheries Data." National Research Council. 2000. Improving the Collection, Management, and Use of Marine Fisheries Data. Washington, DC: The National Academies Press. doi: 10.17226/9969.
×

3

General Issues in the Collection, Management, and Use of Fisheries Data

WHAT ARE FISHERIES DATA?

The phrase “fisheries data” is a general way of referring to data that may be of use in the management of a fishery as well as for commercial, recreational, cultural, and scientific purposes. Such data usually include biological information about the exploited fish and associated species, economic information about the fishermen and the markets for the catch, and information about the environmental conditions that affect the productivity of the species. This information is collected from many sources.

A primary source of information is the commercial and recreational fishermen themselves, so-called fishery-dependent data. Logbooks (also called trip tickets) are designed to collect data on the time and place of fishing, the effort expended, catch by species, and other information. In many jurisdictions, completion of logbooks is a condition of participation in the fishery. Often, information from logbooks is the most timely information on current fishery conditions; mechanisms for self-reporting are rare in recreational fisheries.

Catch sampling programs are another important source of information. Fish can be measured and weighed either at sea (by observers) or at landing sites (by port agents). Observers are placed on commercial fishing vessels to provide information on fishing activities that are not always reported in logbooks, such as effects of fishing activities on protected species and the extent and fate of by catch and discarding. Samples can be obtained to determine the species composition, sex ratio, and age composition of the catch.

In some fisheries, scientific surveys are a vital component of the stock assessment process. Research vessels of the National Oceanic and Atmospheric Administration (NOAA) and commercial fishing vessels operating under charter agreements with NOAA are used to conduct surveys of fish abundance. These surveys are the primary source of fishery-independent data, including estimates of the age structure of fish populations and relative abundance of stocks. The National Research Council (NRC, 1998a) demonstrated the importance of accurate indices of abundance, which in many fisheries can be obtained only from fishery-independent surveys.

In fiscal year 1999, the National Marine Fisheries Service (NMFS) spent $28.8 million on ship time for surveys (not counting personnel and analyses), $3.9 million for recreational monitoring, $9.2 million on observer programs (with another $10 million provided by industry), and $2.8

Suggested Citation:"General Issues in the Collection, Management, and Use of Fisheries Data." National Research Council. 2000. Improving the Collection, Management, and Use of Marine Fisheries Data. Washington, DC: The National Academies Press. doi: 10.17226/9969.
×

million on vessel monitoring system (VMS) programs. The expenditure by NMFS for these data collection activities is thus on the order of $45 million. Additional expenditures were made by states and industry. The total fishery harvest in the United States (commercial and recreational) is valued at approximately $45.7 billion when the total economic effects are included (NMFS, 1995).

WHO USES FISHERIES DATA?

Fisheries data have many uses and many users—including stock assessment by scientists, strategic planning by industry, and fishery monitoring and allocation decisions by managers. Adequacy of data can be evaluated only in the context of the purposes for which they are used. Each use implies a set of users and a suite of requirements that the data must satisfy, including timeliness, level of detail, accuracy, accessibility to users, coverage or completeness, and credibility of the data collection process and the management process that uses the data.

Fisheries data are vital to strategic planning activities in coastal communities that rely on fisheries. Fishery management authorities are responsible to use fisheries data for creating policies for the orderly and sustainable development and management of fisheries. Civil authorities use fisheries data to site marinas, underwater pipes and cables, and other maritime facilities, and to develop infrastructure for the fishing industry. Bankers use fisheries data to plan economic development and loan packages to fishermen, fish processors, and ship suppliers. Fishermen themselves use fisheries data to plan future fishing activities, such as shifts to new fishing grounds, changes in fishing gear, and changes in species targeted. However, fishermen often use their own data sources, including their own logbooks and observations, and what they learn from other fishermen and buyers, instead of using government data. This may occur because of some fishermen's mistrust of government data, the frequent lag time in availability of such data (often too great to use government data in business planning), and the lack of data for the geographic area and type of fishery in which a specific fisherman is engaged.

Monitoring conditions in a fishery is the responsibility of regional fishery management councils and NMFS, and is the primary means of assessing compliance with and accomplishing enforcement of fishery regulations. Another major responsibility of the regional councils is allocation of harvest opportunities among different user groups. Environmental and other interest groups also have become increasingly involved in monitoring fishing activities. Monitoring often requires data with great detail in both time and space as well as frequent updates, often within a fishing season.

Stock assessment is a critical use of fisheries data and is often considered its primary use. The committee devoted a significant portion of its attention to the data used in stock assessments, using the summer flounder fishery as a case study. Scientists employed by state, interstate, national, and international fishery agencies are the primary users of data relevant to stock assessments; in addition, university and private sector scientists increasingly are becoming involved in stock assessments and related research. Current stock assessment practices use data aggregated over the entire fishing ground and over a fishing season. Although assessment methods may require a greater diversity of data, the resolution in space and time is usually rather coarse and may need updating only infrequently, such as annually or semi-annually.

The multiple users of fisheries data have different requirements in terms of resolution in time and space for each possible data element. Table 3-1 summarizes the requirements for data elements by various users (based on committee experience); specific details depend on the characteristics of individual fisheries. Data system designers, therefore, must consider that the demands will vary among users, and the system must be capable of accommodating users who require data at different spatial resolutions and different degrees of timeliness.

Suggested Citation:"General Issues in the Collection, Management, and Use of Fisheries Data." National Research Council. 2000. Improving the Collection, Management, and Use of Marine Fisheries Data. Washington, DC: The National Academies Press. doi: 10.17226/9969.
×

TABLE 3-1 Example of How Data Timeliness and Spatial Resolution Vary Among Users

 

USE

Users

 

MONITORING

Councils

NGOs

ASSESSMENT

NMFS Scientists

Academics

Fishermen

ALLOCATION

Councils

PLANNING

Councils

Local and State Governments

Economists

Bankers

Fishermen

Update Frequency (timeliness)

Within season

Between seasons

Within and between seasons

1-5 years

Spatial Resolution

Detailed/mandated jurisdiction

Stock-wide

Stock-wide

Ad hoc

Required Elements

       

Catch by species

Fishing effort

Catch at length

   

Age composition

 

   

Sex ratio

 

   

Credibility is one of the major concerns surrounding current fisheries data collection activities. Many stakeholders believe that data collected by NMFS are neither accurate nor complete. These misgivings are exacerbated by problems of timeliness and accessibility and by perceived conflicts of interest; NMFS not only collects the data but also conducts stock assessments, makes policy recommendations to councils, enforces fishery regulations, and makes judgments about the policy recommendations and fishery management plans prepared by the regional councils. For many fishermen these multiple responsibilities of a single agency create some mistrust regarding the collection and use of fisheries data.

Two recent reports stress the importance of greater collaboration among scientists and stakeholders in data collection. First, the Consortium for Oceanographic Research and Education states

Finally, collaborative data collection and research efforts should be encouraged among agency scientists, independent scientists, and representatives of industry and public interest groups. Not only would this build confidence among the different groups, but it would provide access to valuable, non-traditional sources of information (CORE, 2000).

Second, the General Accounting Office was asked by Congress to examine NMFS' compliance with several aspects of the MagnusonStevens Act, including use of the best available scientific information and consideration of economic effects of fisheries management on communities. The GAO recommended that NMFS:

  • increase the involvement of the fishing industry, its expertise, and its vessels in fishery research activities in order to expand the frequency and scope of NMFS' data collection efforts,

  • review data collection requirements placed on fishermen to limit requested informa-

Suggested Citation:"General Issues in the Collection, Management, and Use of Fisheries Data." National Research Council. 2000. Improving the Collection, Management, and Use of Marine Fisheries Data. Washington, DC: The National Academies Press. doi: 10.17226/9969.
×

tion to what is needed for conservation and management, regulation, and scientific purposes, and

  • review data collection procedures for fisheries where the recreational sector constitutes a major portion of the fish caught to minimize the inconsistent treatment of commercial and recreational fishermen (GAO, 2000, p. 29).

It is clear from these activities, both initiated by Congress, that improving data collection is a priority for Congress.

Each region of the United States uses different methods to collect, manage, and use fisheries data. In part, such differences are based on differences in the biology and social aspects of the fisheries. Many differences may be due to tradition and familiarity with certain approaches and the accumulation of past actions, rather than rational choice. Other differences arise from state and federal legislation that requires or permits specific activities.

Data Needed for Different Management Methods

What biological, economic, and social data are most needed to provide assessments suited to five common management methods?

  • current state of the fishery

  • management goals and measures of their achievement of intended effects

  • management actions needed to achieve management goals

Five common management methods include (Table 3-2):

  • Total allowable catch (TAC)

  • Effort management

  • Gear restrictions and fish size limits

  • Closed areas (see NRC, 2000)

  • Closed seasons

Current State of the Fishery

Fishery status questions address not only the current status of the stock but also the fishery as a whole, including social and economic factors. Relevant questions include

  • What is the current spawning stock biomass level?

  • What is the current level of fishing mortality?

  • Is recruitment being sustained?

  • Is growth potential maximized?

  • What is the effect of fishing, if any, on the ecosystem?

  • What is the essential habitat for the species and what is the status of the habitat?

  • What social and economic benefits are realized from this resource?

  • What is the relation between current fishing capacity and the sustainable yield of the fishery?

All types of management have specific needs for answering the system status question. For TAC-based management, it is essential to know the current catch, and for effort management to know the current effort. For management based on gear restrictions or individual size limits, it is important to know about the sizes of fish currently being caught and the selectivity of the gear used, and is probably desirable to know the size of fish at maturity, if a goal of management is to allow fish a chance to spawn at least once before capture. For closed areas, it is important to know the distribution of fish relative to the extent of the closed areas and the rate at which fish move in and out of these areas. With closed seasons, it is important to know the seasonal distribution of fish and the timing of spawning.

In practice, data requirements may be simplified by substituting measurements of effort for fishing mortality, catch per unit effort (CPUE) for biomass, length distributions in catch and surveys for age, and recruitment survey CPUE for recruitment. Hence, data of these types should be

Suggested Citation:"General Issues in the Collection, Management, and Use of Fisheries Data." National Research Council. 2000. Improving the Collection, Management, and Use of Marine Fisheries Data. Washington, DC: The National Academies Press. doi: 10.17226/9969.
×
TABLE 3-2 Requirements for Biological, Social, and Economic Data For Five Common Management Methods

Management Method

Data Requirements

TAC-based

Catch and effort data

Fishing mortality rate

Annual TACs and estimation of recruitment

Social and economic impacts of management

Likelihood that regulations will foster misreporting of fishery-dependent data, including economic and regulatory discardsa

Economic contributions of recreational and commercial fisheries, including supporting industries

Distribution of catch among gear types and between commercial and recreational fishermen

Effort management

Catch and effort data

Fishing mortality rate

Social and economic impacts of management

Optimal harvesting and processing capacity

Present participation of individuals in the fishery

Dependence on the fishery

How efficiency of effort has changed and how effort is allocated across different species and sizes of fish

Likelihood that regulations will foster misreporting of fishery-dependent data, including economic and regulatory discards

Economic contributions of recreational and commercial fisheries, including supporting industries

Distribution of effort and likely impacts of capacity reduction approaches

Gear restrictions and fish size limits

Catch and effort data

Size distribution of fish being caught

Selectivity of gear

Size at maturity

Age at first capture

Encounter rate and release mortality of undersized fish

Compliance with size limits

Social and economic impacts of management

Economic contributions of recreational and commercial fisheries, including supporting industries

Impact of regulations on fishing behavior, especially where fishery-dependent data are used for stock assessments

Closed areas

Distribution of fish (by size and maturity, within and outside the closed areas)

When and at what rate fish move in and out of the area

Catch and effort data outside the closed area

Social and economic impacts of management

Economic contributions of recreational and commercial fisheries, including supporting industries

Distribution of catch among gear groups and between commercial and recreational fishermen

Suggested Citation:"General Issues in the Collection, Management, and Use of Fisheries Data." National Research Council. 2000. Improving the Collection, Management, and Use of Marine Fisheries Data. Washington, DC: The National Academies Press. doi: 10.17226/9969.
×
 

Catch and effort data

Likelihood of regulations to foster misreporting of fishery-dependent data and economic and regulatory discards

Potential shifts in fishing areas and effort

Knowledge of essential habitat

Closed seasons

Seasonal distribution and timing of spawning

Catch and effort data

Distribution of fish in closed and open seasons

Social and economic impacts of management

Economic contributions of recreational and commercial fisheries, including supporting industries

Distribution of catch among gear groups and between commercial and recreational fishermen

Likelihood of regulations to foster misreporting of fishery-dependent data and economic and regulatory discards

Potential shifts in fishing times or areas

a Economic discards are fish discarded because they are unmarketable (because of their quality, size, species, or sex) or because a fisherman hopes to replace them with higher-value fish. Regulatory discards are fish discarded because they are prohibited by regulation from being landed, because of their size, species (prohibited species or species for which the seasonal quota has been filled), the gear used, or area fished.

desirable for almost any management system. However, for fisheries in which fishing mortality is a small proportion of total mortality, it might be argued that an intensive monitoring system is of marginal value relative to the low risk of overfishing.

Whatever method of management is chosen, managers need to know approximately what portion of a stock is being exploited and how exploitation must change to achieve management goals. A minimum requirement for such assessments would be some sort of general production model that includes at least catch and effort, hence the need for catch and effort data for all management types.

Management Goals and System Response

System response questions involve monitoring the changes in stock status in response to changes in the management control variable (e.g., catch, effort, gear, time, or area restrictions). In the case of catch and effort quotas, stock status usually is expressed by fishing mortality level or changes in relative abundance. In the case of mesh changes or size limits, system response is usually measurable in terms of average size of fish in the fishery. Closed areas or seasons are likely to require both catch and effort data, subdivided by area and time.

Management Actions

Answers to management implementation questions can help managers as they select actions to achieve management goals. Such questions require that biomass be estimated for TAC management and that recruitment also be monitored. However, for heavily exploited fisheries in which the spawning stock biomass has been substantially reduced from unfished levels, recruitment is often an important component that needs to be monitored, because only a few poor recruitment years are needed for the population to crash. Effort quotas require that changes in

Suggested Citation:"General Issues in the Collection, Management, and Use of Fisheries Data." National Research Council. 2000. Improving the Collection, Management, and Use of Marine Fisheries Data. Washington, DC: The National Academies Press. doi: 10.17226/9969.
×

gear efficiency and targeting practices also be monitored. Mesh size or size limit management requires an understanding of gear selectivity. Closed areas and seasons require information about the distribution of fish in areas that might form part of extended closures. An important focus of both monitoring and research is how fisheries respond to regulations. This is an essential component of sustainable management, and implementation uncertainty is often one of the largest sources to total uncertainty about a stock-fishery system.

Data Quality Required

In an ideal world, all advice would be completely accurate and precise, but in practice data contain some level of bias and random variation, and incremental gains in precision and accuracy often require ever greater relative expenditures for sampling and analysis. Moreover, some sources of inaccuracy or imprecision may be impossible to eliminate, even with infinite sampling, because of the inherent randomness and chaos in natural systems. Pressures to maximize total allowable catch can lead to excess fishing that can harm a fishery before managers understand the dynamics of the target fish population(s). Fisheries can also be damaged when pressures to maximize total allowable catch cause managers to attempt to manage at a level of detail finer than available information will allow.

Every management system should be evaluated in light of the amount of inaccuracy and imprecision in management advice that can be tolerated and still allow the system to achieve its goals. The precision of data needed depends on the management regime and objectives chosen. For example, management with closed areas would lower the precision needed for data outside the closed area.1 Taking a different management approach, with an objective of keeping catch (and employment) as high as possible, subject only to the fish being able to reproduce sustainably—the apparent goal of many U.S. fishery management plans—requires accurate and precise estimates of current stock status, minimum levels of spawning stock biomass, and fishing mortality. The higher the rate of exploitation, the more precision is needed to manage a stock adequately from a biological perspective. From economic and social views, a high level of precision may be necessary in order to avoid undue disruption in the industry.

Acceptable levels of imprecision and inaccuracy also depend on the extent of annual variations in management restrictions that will be tolerated by managers and fishermen and the ability of a stock to withstand inevitable over- or underexploitation caused by inaccurate or imprecise management. Fluctuations in total allowable catch due to imprecise data would require effort to move in or out of the fishery and would probably increase costs compared to a situation in which the TAC is lower but less variable. For a given level of precision, the amount of data required (though not necessarily its cost) is, as a first approximation, independent of the size of the stock. It would be wise to compare the management method (and data collection costs) to the potential benefits of management. Managers may not be prepared or able to pay for the levels of sampling that would provide an appropriately precise fisheries assessment for some low-value stocks.

If managers are not prepared to pay for greater precision, or if needed precision is not achievable at any price, managers may have to modify either their objectives or their control rules. One approach would be to select a lower level of exploitation so that stock abundances would change more slowly and fluctuations in numbers of young fish would be dampened by

1  

The amount of area that needs to be closed to avoid the need for high precision data is unknown in practice, but modeling studies have indicated that as much as 30-70 percent of total fishing area may need to be protected, if this is the only form of fishery management. See NRC (2000) for a summary of the state of knowledge regarding the use of marine protected areas for fisheries management.

Suggested Citation:"General Issues in the Collection, Management, and Use of Fisheries Data." National Research Council. 2000. Improving the Collection, Management, and Use of Marine Fisheries Data. Washington, DC: The National Academies Press. doi: 10.17226/9969.
×

the presence of more age classes in the fish stock. Another approach would be to adopt a form of management that needs less precision in estimates of the current stock status and estimates of next year 's catch, for example, managing a fishery by limiting fishing effort rather than by limiting catch. Closed area management requires even less assessment information and is more robust to any lack of precision in assessment. If a sufficiently large part of the range of a fish stock (including spawning areas and nursery areas) were closed, it is unlikely that fishing could damage it. However, closed areas would probably not reduce the need for precise data for highly migratory stocks.

Timeliness of data is a final aspect of data quality. Sampling may be designed adequately to ensure that data are accurate and precise enough for management purposes, but data analysis may not be timely. Lack of timeliness can hinder good management, particularly in the case of heavily exploited fish populations with few year classes and for fisheries that depend on inseason management. State data are sometimes only available a year after their collection and recreational data often are not available until the following season. This lag in data availability results in management that responds to the situation that existed one year ago, a situation that may no longer exist. This may explain, in part, the finding of NRC (1998a) that assessment results tend to lag behind the actual situation by one or more years in detecting stock declines and rebuilding. Timeliness of data is also affected by the frequency of surveys, discussed elsewhere in this report.

METHODS OF DATA COLLECTION

Data are available from a number of sources, including from ceremonial and subsistence fisheries, from fishery-independent surveys conducted by the states and NMFS, and from commercial and recreational fisheries.

Data from Ceremonial and Subsistence Users

Many fisheries are exploited for ceremonial or subsistence uses. For example, halibut and salmon are prominent fish species used by Native Americans in the Pacific Northwest and Alaska for both ceremonies and subsistence. Non-natives in these areas are also subsistence users. Pacific Islanders use coastal fish species and tuna for similar purposes. Data related to ceremonial and subsistence users are collected for inland waters and Pacific coastal waters and used in stock assessments. Most Pacific coast ceremonial and subsistence data relate to salmon fisheries, but groundfish catches for these uses also are included in landings data that NMFS receives from states.

Subsistence use, although small in comparison to recreational and commercial use, is still significant in many U.S. fisheries. In some cases, subsistence use may be included in the recreational fishing category, accounting for individuals who regularly fish off the shore, piers, and other coastal access points to provide food for themselves and their families. Such individuals may be contacted by MRFSS intercept samplers, but they may be missed in telephone surveys because of language difficulties, mistrust of government agencies, or because they do not have telephones. Non-commercial catches may form a large percentage of the diet in some communities, but this has not been studied extensively. Another small component of subsistence use is the catch that commercial fishermen take for personal use. In any case, except for the examples given earlier, catch for ceremonial and subsistence fishing is a minor portion of the catch in most fisheries.

Data from Fishery-Independent Surveys

NMFS and individual states conduct a variety of surveys throughout the year in offshore and inshore waters. Some federal surveys are conducted as many as three times per year (East

Suggested Citation:"General Issues in the Collection, Management, and Use of Fisheries Data." National Research Council. 2000. Improving the Collection, Management, and Use of Marine Fisheries Data. Washington, DC: The National Academies Press. doi: 10.17226/9969.
×

Coast flatfish), whereas other species may be surveyed every three years (many West Coast and Gulf of Alaska fisheries) or never (Table 3-3). Appendix C illustrates and analyzes the variety of surveys conducted for summer flounder. In addition to surveys of fish abundance and population characteristics, the states, NMFS, other agencies, and academic scientists collect data related to other components of marine ecosystems and marine environmental conditions in an attempt to understand how fishing affects marine ecosystems and how marine environmental conditions affect fish populations.

In general, the purpose of stock assessment activities is to monitor changes in the abundance of fish populations over time in order to evaluate the effects of past and present fishing activities on fish population trends and to predict the consequences of future fishery management decisions. Stock assessments, together with monitoring of physical and biological variables, are also needed to evaluate the effects of the environment on fish populations.

Monitoring changes in abundance of fish stocks over time requires having at least one measure that reflects these changes without biases or with constant known biases. Catches from the commercial fishery may fluctuate from year to year due to causes unrelated to changes in absolute abundance. For example, changes in commercial catch can result from changes in the amount of fishing effort in any one year as a function of the price and abundance of alternate fish species, improvements in fishing technology (better nets, more precise acoustic detectors or navigational equipment), changes in management measures (closed areas, seasons, trip limits), or inaccessibility of the stock due to changes in the ranges of fish populations caused by environmental factors.

Year-to-year changes in the distribution of fishing effort should be considered when using fishery CPUE data to measure fish abundance. If a fishing fleet moves from fishing grounds where fish densities are low to grounds where fish densities are high, CPUE will increase even though the overall stock abundance remains constant or declines. Analyses of CPUE data must adequately consider the spatial aspects of fish population distributions and the fishing effort applied to catching fish. Often, however, CPUE data are simply combined over broad (and inappropriate) spatial scales.

In most fisheries, the best measure of relative fish abundance is obtained from fishery-independent surveys, in which the gear (and usually vessel), timing, survey design, and procedures are kept constant from year to year. As a result, annual changes in the abundance or biomass of a species are assumed to reflect actual changes in relative abundance. Surveys are intended to determine whether populations have changed relative to previous years; typically they are not designed to determine absolute abundance. In addition to tracking the relative abundance of fish stocks over time, fishery-independent surveys provide a means to gather information unattainable from landed catch (e.g., maturity indices, fishery indices for sublegal-sized fish).

Operationally, the general practice of this kind of survey is to use fishing gear of a type commonly used in the fishery. However, there have been cases (e.g., the crab fisheries in the Bering Sea and the Gulf of St. Lawrence) in which bottom trawls were used for the survey while crab pots or traps were the only gear used by the fishery. Even if the gear chosen for the survey resembles that in common use when the surveys were initiated, the fishing industry can continue to upgrade and improve its gear. This usually creates the perception in the fishing industry, many years after the survey series has started, that the survey gear is old-fashioned and sub-optimal. Such perceptions also lead to charges that the outmoded survey series is not useful because of the fishing gear used in the survey. Although it is true that there have been many improvements to fishing gear and practice over the past thirty or more years, criticism of a survey series should be based more on whether the current gear is working properly and whether the selectivity of the gear is well known, rather than on whether that type of gear still is being used by the fishery (see Box 2-2 for details on gear selectivity). A further consideration is that when there is an important change in gear, both old and new gear should be used in parallel for a long-enough period of time to establish the conversion factor needed to use historical data.

Suggested Citation:"General Issues in the Collection, Management, and Use of Fisheries Data." National Research Council. 2000. Improving the Collection, Management, and Use of Marine Fisheries Data. Washington, DC: The National Academies Press. doi: 10.17226/9969.
×

TABLE 3-3 Research and Charter Vessel Surveys, NMFS Fiscal Year 2000

Type of Survey

Area

Species or Species Complex

Frequency or Seasonality of Survey

Number of Stations

Atlantic and Gulf Surveys

Autumn bottom trawl survey

Cape Hatteras to Nova Scotia, 4-200 fathoms

Fish and macro-invertebrates

Annual

355 trawl/CTD stations

Winter bottom trawl survey

Cape Hatteras to Georges Bank, 15-100 fathoms

Fish and macro-invertebrates

Annual

155 trawl/CTD stations

Spring bottom trawl survey

Cape Hatteras to Nova Scotia, 4-200 fathoms

Fish and macro-invertebrates

Annual

335 trawl/CTD stations

Northern shrimp bottom trawl survey

Gulf of Maine, 50-120 fathoms

Northern shrimp

Annual

65 trawl stations

Sea scallop survey

Cape Hatteras to Georges Bank, 15-60 fathoms

Sea scallop

Annual

600 dredge stations and 300CTD profiles

Surf clam/ocean quahog survey

Cape Hatteras to Georges Bank, 4-40 fathoms

Surf clam/ocean quahog

Triennial

475 hydraulic dredge stationsand CTD profiles

Apex predator survey

Key West to Delaware Bay, 5-40 fathoms

Shark

Triennial

100 longline stations andprofiles

Atlantic herring hydroacoustic survey

Georges Bank and the Gulf of Maine, 10-200 fathoms

Atlantic herring

Annual

3,400 nautical miles of hydroacoustic trackline; ~70 pelagic trawl tows

Small pelagics hydroacoustic survey

Cape Hatteras to Nantucket Shoals, 10-100 fathoms

Atlantic mackerel, butterfish, loligo and illex squid, and Atlantic herring

Annual

3,400 nautical miles of hydroacoustic trackline; ~70 pelagic tows

Trawl survey standardization and technology development

Cape Hatteras to Nova Scotia, 5-100 fathoms

Gear efficiency study

Annual

Variable

Suggested Citation:"General Issues in the Collection, Management, and Use of Fisheries Data." National Research Council. 2000. Improving the Collection, Management, and Use of Marine Fisheries Data. Washington, DC: The National Academies Press. doi: 10.17226/9969.
×

Ecosystem monitoring survey—winter

Gulf of Maine, 15-200 fathoms Cape Hatteras to Georges Bank, 4-200 fathoms

Multi-species eggs and ichthyoplankton

Annual

30 bongo hauls 90 bongo hauls/CTD profiles

Ecosystem monitoring survey—early spring

Cape Hatteras to Nova Scotia, 4-200 fathoms

Multi-species eggs and ichthyoplankton

Annual: survey piggybacked

120 bongo hauls/CTDprofiles

Ecosystem monitoring survey—late spring

Cape Hatteras to Nova Scotia, 4-200 fathoms

Multi-species eggs and ichthyoplankton

Annual

120 bongo hauls/CTD profiles

Ecosystem monitoring survey—summer

Cape Hatteras to Nova Scotia, 4-200 fathoms

Multi-species eggs and ichthyoplankton

Annual

120 bongo hauls/CTD profiles

Ecosystem monitoring survey—early autumn

Cape Hatteras to Nova Scotia, 4-200 fathoms

Multi-species eggs and ichthyoplankton

Annual: survey piggybacked with autumn trawl survey

120 bongo hauls/CTD profiles

Ecosystem monitoring survey—late autumn

Cape Hatteras to Nova Scotia, 4-200 fathoms

Multi-species eggs and ichthyoplankton

Annual

120 bongo hauls/CTDprofiles

Northern right whale survey

Bay of Fundy to the Gulf of Maine, 15-200 fathoms

Whales

Annual

Visual line transect survey with 100 plankton andCTD stations

Harbor porpoise survey

Georges Bank and the Gulf of Maine, 15-200 fathoms

Harbor porpoise

Triennial

Visual line transect survey with 30 CTD profiles

Marine turtle survey

North Carolina to the Gulf of Maine, 4-200 fathoms

Turtles

Triennial

Visual line transect survey with 50 CTD profiles

Harbor porpoise and hydroacoustic survey

Gulf of Maine, 10-200 fathoms

Harbor porpoise

Annual

Visual line transect survey with 50 CTD profiles

Pelagic delphinid survey

North Carolina to the Gulf of Maine, 4 fathoms to EEZ boundary (abyssal depths)

Dolphins

Triennial

Visual line transect survey with ~10 plankton tows and 200 CTD profiles

SABRE/striped bass

North Carolina to Virginia, 5-100 fathoms

Striped bass and larval fish

Winter

80 striped bass stations 80-100 plankton tows

Suggested Citation:"General Issues in the Collection, Management, and Use of Fisheries Data." National Research Council. 2000. Improving the Collection, Management, and Use of Marine Fisheries Data. Washington, DC: The National Academies Press. doi: 10.17226/9969.
×

West Florida shelf fishing reserve

Gulf of Mexico off Florida, 5-100 fathoms

Reef fish

Winter

130 to 260 stations

SEAMAP reef fish

Gulf of Mexico from Texas to Florida, 5-60 fathoms

Reef fish

Spring

288 stations

SEAMAP groundfish

Gulf of Mexico from Texas to Alabama, 5-60 fathoms

Shrimp/groundfish

Summer

Fall

240 stations

240 stations

Shark survey

Gulf of Mexico/Caribbean from Florida to Texas, 10-40 fathoms; Cuba, 10-300 fathoms

Coastal sharks

Summer

250 to 300 stations

Gear comparison

Gulf of Mexico, Texas to Florida, 5-60 fathoms

Shrimp/groundfish

Fall

240 stations

Caribbean marine mammals

Caribbean-Puerto Rico to Venezuela—nearshore to 5,000 fathoms

Humpback whales

Winter

80 to 100 sightings

SEAMAP plankton/marine mammals

Gulf of Mexico, 100 fathoms to EEZ for spring survey 5-600 fathoms for fall survey

Bluefin tuna/cetaceans Mackerel/red drum/cetaceans

Spring

Fall

196 plankton stations

240 mammal stations

118 plankton stations

200 mammal stations

Snapper longline

Gulf of Mexico, Texas, 35-80 fathoms

Red snapper

Summer

88 stations

Sperm whale

Gulf of Mexico from Louisiana to Alabama, 100-2,000 fathoms

Sperm whales

Summer

52 sightings

Suggested Citation:"General Issues in the Collection, Management, and Use of Fisheries Data." National Research Council. 2000. Improving the Collection, Management, and Use of Marine Fisheries Data. Washington, DC: The National Academies Press. doi: 10.17226/9969.
×

Pacific Surveys

Bottom trawl

Bering Sea shelf

Groundfish, king crab, Tanner crab, snow crab

Annual

380 stations

Bottom trawl

Bering Sea continental slope

Groundfish, crab

Biennial

70-100 stations

Acoustic/trawl

Bering Sea-Bogoslof Island

Pollock

Annual

1,500 nautical miles of trackline

Acoustic/trawl

Bering Sea shelf

Pollock

Biennial

6,000 nautical miles of trackline

Bottom trawl

Aleutian Islands

Groundfish

Biennial

425 stations

Bottom trawl

Gulf of Alaska shelf and continental slope

Groundfish

Biennial

776 stations

Acoustic/trawl

Gulf of Alaska-Shelikof Straits

Pollock

Annual

900 nautical miles of trackline

Surface trawl

Bering Sea-Bristol Bay

Juvenile salmon

Semi-Annual

55 stations

Surface trawl

Gulf of Alaska

Juvenile salmon

Annual

Variable

Surface trawl

Southeast Alaska coastal monitoring

Young salmon, sablefish, other epipelagic species

Annual (five 7-day cruises)

24 stations (250 km spread)

Longline with limited surface gillnets

Gulf of Alaska (GOA), Bering Sea (BS) and Aleutian Islands (AI) outer shelf and slope

Sablefish and rockfish

GOA Annual BS and AI Biennial

74 to 76 stations

Egg and larval survey

Gulf of Alaska

Pollock

Annual

100 to 120 stations

Bottom trawl

West Coast shelf

Groundfish

Triennial

620 stations

Bottom trawl

West Coast continental slope

Groundfish

Annual

200 stations

Acoustic/trawl

West Coast

Pacific whiting

Triennial

6,700 nautical miles of trackline

Suggested Citation:"General Issues in the Collection, Management, and Use of Fisheries Data." National Research Council. 2000. Improving the Collection, Management, and Use of Marine Fisheries Data. Washington, DC: The National Academies Press. doi: 10.17226/9969.
×

Bottom trawl (4 charter vessels)

West continental slope

Groundfish

Annual

400 stations

CalCOFI

Monterey, California to Mexico 200-360 nautical miles offshore

220 (20 in groundfish FMP; 3 in pelagic FMP)

Quarterly

66 stations

Shark

Point Conception to Mexican border, offshore 120 nautical miles

4 species of pelagic sharks

1 to 3 years

40 Stations

Sardine

San Francisco to Mexican border, offshore 300 nautical miles

Sardine, jack mackerel, anchovy

2 to 6 years

1,000 Stations

Rockfish

Central California to 50 nautical miles offshore

Groundfish (rockfish, whiting, lingcod)

Annual

99 Stations

Antarctic

Antarctic Peninsula

Krill, groundfish

Annual

100 Stations

Lobster

Northwestern Hawaiian Islands

Spiny and slipper lobster

Annual

N/A

SOURCE: National Marine Fisheries Service.

NOTE: CalCOFI = California Cooperative Oceanic Fisheries Investigations; CTD = conductivity-temperature-depth recorder; FMP = fishery management plan; N/A = not applicable; SABRE = South Atlantic Bight Recruitment Experiment; SEAMAP = Southeast Assessment and Monitoring Program.

Suggested Citation:"General Issues in the Collection, Management, and Use of Fisheries Data." National Research Council. 2000. Improving the Collection, Management, and Use of Marine Fisheries Data. Washington, DC: The National Academies Press. doi: 10.17226/9969.
×

A question needs to be answered before a survey is changed by updating the gear: Does the existing survey produce data of quality adequate for use in an assessment? If the answer is “no,” the existing survey should be phased out and replaced with a better survey. If the answer is “yes,” and the data are still needed, the associated cost of changing gear is the cost of an adequate intercalibration experiment. This consists of many parallel samples using the new and existing gear. Many intercalibration studies have been conducted as part of regular surveys and the sample size for the number of parallel tows usually corresponds to the number of tows in the actual survey. Pelletier (1998), however, has presented results from a directed intercalibration study where 30 parallel tows appeared to be quite adequate to estimate conversion factors for most species observed. Managers and fishermen must decide fishery by fishery whether the gain in precision and compatibility with existing gear types is worth the cost of the transition.

Advanced Sampling Technologies for Fisheries

A complement to standard surveys based on fish capture are newer remote-sensing methods in which fish are counted or the biomass of a school estimated using sound (hydroacoustics), lasers (lidars [light detection and ranging]) and laser line scanners), and other optical techniques. Optical and acoustic techniques also can be used to estimate the number of larval fish and the phytoplankton and zooplankton biomass available as food. However, like any remote sensing technique, it is important to include a “ground truthing” component in sampling, in which samples of fish are collected from the remotely sensed areas for species identification to calibrate the sensors and validate the values obtained remotely.

Advantages of hydroacoustic techniques are that they cover more area in less time and can offer better three-dimensional coverage of the water column and can give a better indication of the total population, not just those fish that can be captured in nets. Hydroacoustic surveys transit an area with either single acoustic beams faced directly below the vessel or multiple beams arrayed from straight down to extending horizontally away from the vessel. Multibeam systems can sample a swath many kilometers wide. The vessels used for hydroacoustic surveys must be specially designed to be quiet. Limitations of hydroacoustic techniques include

  1. difficulties in species identification in mixed populations,

  2. inaccurate determination of size distributions of schools with individuals of many sizes,

  3. inability to estimate benthic species,

  4. lack of sensitivity to estimate species with no swim bladder, and

  5. requirement for special fishery research vessels.

Hydroacoustic surveys are used extensively by other nations and are used for a few U.S. surveys (see Table 3-3). Hydroacoustic techniques are most useful for estimating the abundance and biomass of single-species schools of mid-water fish, such as pollock and whiting in the North Pacific Ocean and herring, mackerel, butterfish, and squid in the North Atlantic Ocean. A new generation of fishery research vessels is being designed to meet standards developed by the International Council for the Exploration of the Sea (ICES, 1995) for acoustic quieting (see following section on survey vessels).

Lidar, which is more experimental than acoustic techniques at this time, is implemented using a laser projected from a small aircraft, so it

Suggested Citation:"General Issues in the Collection, Management, and Use of Fisheries Data." National Research Council. 2000. Improving the Collection, Management, and Use of Marine Fisheries Data. Washington, DC: The National Academies Press. doi: 10.17226/9969.
×

has the advantage of surveying an area 20 times faster than a trawl or hydroacoustic survey carried out by a fishery research vessel. It is most useful for species that school and spend a significant amount of time in the relatively transparent upper layer of the ocean (e.g., sardines, herring, squid). It suffers from the same target identification problems as acoustic methods.

Survey Vessels

NOAA has a fleet of 16 ships, staffed by officers of the uniformed NOAA Corps and by merchant marines. Nine of the vessels are designed for fishery surveys and fisheries oceanography. NMFS' estimates of ship time needed to fulfill its mission exceed the amount of time available on its limited and aged fleet. This situation has been highlighted in a number of reports (discussed below).

NMFS presently charters 40 percent of its days at sea on commercial and university vessels to supplement work done by its own vessels, but it must maintain its own survey capabilities, particularly for trawl surveys. Reasons to maintain strong survey capabilities within the agency include the need for consistency of survey vessels to reduce variability, the present lack of acoustically quiet ships in the commercial fishery and university fleets, the availability of proper equipment for surveys and fisheries oceanography on NOAA vessels, and flexible scheduling for NOAA vessels. New NOAA fishery research vessels are designed to be quieter than commercial vessels (to minimize the influences of vessel noise on the distribution of fish during sampling) and are equipped to take measurements that are not normally taken from commercial vessels (e.g., environmental variables, depth, acoustic measurements). When using private vessels for trawl surveys, NMFS prefers to enter long-term charters so that the time and expense related to intercalibrations are minimized.

NOAA has developed a series of fleet replacement and modernization (FRAM) plans that have been reviewed by the General Accounting Office (1986), National Research Council (1994b), and others. Many of these reports have considered whether NOAA should use chartering more extensively. The three interstate marine fishery commissions2 convened a workshop in 1996 to “discuss the fishery survey capabilities and the critical need to ensure compatibility and continuity with historic data sets” (ASMFC, 1996). The commissions issued a joint call for replacement of the aging NOAA fisheries fleet with quiet, modern, multipurpose fishery research vessels, either by purchase or long-term charter (ASMFC, 1996). They recommended that new vessels, gear, and methods be calibrated adequately to be comparable with existing methods and gear. Calibration is important, particularly for trawl fisheries, because each combination of vessel, gear, and skipper fishes differently and thus has a different catchability coefficient. This difference in catchability occurs because each vessel has a distinct acoustic signature (which may affect fish behavior) and each vessel pulls its nets through the water or over the bottom differently. An un-published memo from Dorman (1998) to the Office of Management and Budget also supports the construction and deployment of new fishery research vessels. Dorman endorsed the proposed design, although he also recommended that new vessels be planned in the context of a national plan for their use with other national assets for fisheries research, fisheries monitoring, and oceanography. A great deal of debate has ensued about whether NMFS should increase its charter of academic and industry vessels.

2  

Three interstate marine fishery commissions—the Atlantic States Marine Fisheries Commission, Gulf States Marine Fisheries Commission, and Pacific States Marine Fisheries Commission —were created to coordinate the management of stocks within their coastal waters, including 3 miles from shore on open coasts, bays, and estuaries. Congress passed the Interjurisdictional Fisheries Act in 1986, directing the Secretary of Commerce to “apportion funds for interjurisdictional fisheries research projects among the States. ” The act was extended by the Atlantic Coastal Fisheries Cooperative Management Act in 1993: “the responsibility for managing Atlantic coastal fisheries rests with the States, which carry out a cooperative program of fishery oversight and management through the Atlantic States Marine Fisheries Commission. It is the responsibility of the Federal Government to support such cooperative interstate management of coastal fishery resources.” (Sec. 802[a][4] of the Coast Guard Authorization Act of 1993). All the interstate commissions collect data and provide some level of coordination of fishery management activities. The Atlantic States Marine Fisheries Commission is the most active in coordination of management. The Pacific and Gulf commissions are less involved in management, focusing on data collection and data management. Data are sent from individual states to the commissions and NMFS. The commissions generally do not conduct their own commercial and recreational sampling although Congress established a budget line item in fiscal year 1999 for a Gulf of Mexico Fisheries Information Network (GulfFIN) to establish a data collection and analysis program for both commercial and recreational fisheries. Presently, the Gulf commission continues to conduct the MRFSS intercept surveys and newly adopted charter vessel data collections under a fiscal year 2000 cooperative agreement with NMFS. The same data are used for fisheries management within individual states and for federal management through NMFS stock assessments and regional fishery management council decisions.

Suggested Citation:"General Issues in the Collection, Management, and Use of Fisheries Data." National Research Council. 2000. Improving the Collection, Management, and Use of Marine Fisheries Data. Washington, DC: The National Academies Press. doi: 10.17226/9969.
×

Congress has appropriated funding for four fishery research vessels to meet ship time needs for fisheries surveys and research. About 86 percent of the funds for the first fishery research vessel were appropriated in fiscal year 2000 and the remaining funds to complete the ship have been requested by NMFS in its fiscal year 2001 budget request. NMFS plans to award the contract for the first vessel in the 4th quarter of fiscal year 2000 and expects to take delivery of it in fiscal year 2003. This ship will be stationed in Alaska. If funding is appropriated, the second, third, and fourth ships will be delivered in fiscal years 2005, 2006, and 2007. They will be stationed in Woods Hole, Massachusetts; the Pacific Northwest; and Pascagoula, Mississippi, respectively.

Sampling Designs

The sampling design of a fishery-independent survey determines where the fishing stations are to be located in the area or domain of the survey. Ideally, the survey domain should cover the stock area(s) for the target species at the same time each year. In practice, surveys gather information for a number of species, many of which may have overlapping but not identical spatial and temporal distributions. This requires the survey to cover a very large area to include the stock areas of all species. For example, the biannual East Coast bottom trawl survey covers the entire continental shelf from Cape Hatteras to Nova Scotia (4 to 200 fathoms depth). Traditionally, survey stations are located either randomly within stock areas each year (e.g., groundfish surveys off the east coast of Canada and the United States, acoustic surveys for pelagic fish off South Africa) or at sites fixed over time in the stock areas (e.g., longline survey for halibut off western North America, groundfish surveys off Iceland and in the North Sea). No matter how the sampling sites are selected, a standard fishing procedure is used at each station in terms of the length of time that gear is deployed or distance through the water that trawls are towed. The number and weight of each species caught at each station are recorded, along with size, sex, maturity, and age of fish caught. Measurements of depth, water temperature, salinity, and other environmental factors are often obtained at each fishing station.

The type of survey design chosen determines how the mean and total estimates (e.g., catch rates, abundance) are calculated. The most commonly used design is stratified random, for which the survey area is divided (stratified) into subareas based on such factors as depth ranges, stock areas, habitat, and management areas. Survey stations are located randomly within each subarea, which is called a stratum. A mean or total estimate is calculated within each stratum and an overall estimate is calculated by weighting each stratum estimate by the relative area covered by it. The validity of estimates of means, totals, and variances does not require any assumptions about the properties of the statistical or spatial distribution of organisms within strata. These kinds of estimates and their associated properties are called design based. The main advantage of a design-based strategy is that a property such as unbiasedness depends only on how the survey is designed, not on assumptions about the frequency

Suggested Citation:"General Issues in the Collection, Management, and Use of Fisheries Data." National Research Council. 2000. Improving the Collection, Management, and Use of Marine Fisheries Data. Washington, DC: The National Academies Press. doi: 10.17226/9969.
×

distributions of fish populations (e.g., normal or log-normal), spatial independence, or the existence of covariance of any particular form. Design-based methods do require selection of the sample according to the design, involving random or probability selection at some stage.

The second common survey method uses the same stations year after year. There are no definitive methods for calculating broad-area estimates from such fixed-station survey data. The methods that have been applied range from using design-based methods to complex spatial models. The latter methods generally model spatial patterns as a function of distances among stations and are not tied to specific locations. Indeed, fixed-station designs may be the most appropriate if a spatial model is the objective of the eventual analysis because these kinds of designs ensure that stations selected constitute an adequate range and distribution to construct an efficient estimate. The properties of estimates from survey data that are derived from a model are referred to as model based. Model-based estimation methods make statistical assumptions about the distribution of fish, such as a normal or log-normal spatial model, with an assumed spatial covariance structure. Under the assumed model, best linear unbiased or maximum likelihood estimation methods can be used. Such methods can provide good estimates even when the location of sample sites in the study region is uneven. These two methods have competing advantages and disadvantages, but generally, a model-based method should be chosen if, and only if, the assumptions in the model are approximately correct. Since this can never by fully assured, it is important to use both types of surveys in a balanced, self-correcting manner, but with an expectation that the balance will tilt more toward model-based surveys as increasing knowledge builds confidence in the model assumptions.

Limitations—Most fishery-independent surveys collect data in a short time period, on the order of weeks. It is important to consider timing in the interpretation of survey data because many species change their distribution over the seasons and seasonal movements may differ as a function of fish age. Surveys should be short enough in time and large enough in spatial extent to minimize possible biases due to large-scale movement or migration by some of the fish over the survey period. Conducting a survey at the same time each year may ensure that light regimes (the number of daylight versus night hours) are comparable from year to year, but fish migrations and biology are highly dependent on water temperatures, which can vary greatly on a specific date from year to year.

Many species move in the water column each day in response to light levels and vary in their availability to the fishing gear, particularly bottom trawls, over the course of each day. Thus, many large-area surveys estimate abundance from catches over the entire 24-hour period. Evaluating the possible effects of daily movements on estimates from survey data is difficult, because limits on sampling capability and the need to move vessels to new locations require that differences among catches made at different times of the day are also made at different locations. Studies of the same area over 24-hour periods are needed to determine whether and how daily migration affects estimates for various species (Jones and Pope, 1973; Atkinson, 1989; Engås and Soldal, 1989; Walsh, 1991; Jones et al., 1995; Korsbrekke and Nakken, 1999; Somerton et al., 1999).

Another limitation of fishery-independent surveys is that their high costs, demands for intensive labor, and major requirements for capital investment in vessels restrict the sampling intensity of a survey. In terms of days fished, surveys may represent a small fraction of the effort expended on the grounds by the commercial fleet. For example, for summer flounder, survey days equal about 0.1 percent of the days fished by commercial fishermen. Although the commercial information represents directed effort, it may be fruitful for scientists to develop ways to make the best use of both sources of information, rather than argue over the benefits of one versus the other or reject commercial data outright.

Suggested Citation:"General Issues in the Collection, Management, and Use of Fisheries Data." National Research Council. 2000. Improving the Collection, Management, and Use of Marine Fisheries Data. Washington, DC: The National Academies Press. doi: 10.17226/9969.
×

Evaluation of Survey Design—The design of each survey should be evaluated, just as the performance of the sampling gear and the coverage of the stock area of a survey are evaluated. Within the context of a random survey, this evaluation should determine whether the design is the most efficient attainable with available resources. For stratified random designs, precision is a function of how well the strata correspond to the distribution of the target species and whether the higher sampling intensities were assigned to the more variable strata, as they should be. Smith and Gavaris (1993) provide an evaluation of a stratified random design for a groundfish survey. Appendix C presents an evaluation specifically for the NMFS winter bottom trawl survey, including summer flounder. This evaluation also indicates how multispecies surveys will not necessarily be optimal for any single species.

Evaluation of fixed-site designs should be focused on ensuring that the number of fishing stations and their locations are adequate to estimate all the parameters of the model with adequate precision. For statistically optimal (best linear unbiased estimates) methods such as kriging,3 this evaluation may involve determining whether the range of distances between stations has been sampled adequately so that the variogram 4 usefully describes both the small- and large-scale variations.

Options for Increasing Survey Precision—Careful survey design can improve the precision of design-based estimates. For example, stratified random designs can be improved by modifying the existing stratification scheme, the station-to-strata allocation scheme, or both. Evaluation of completed surveys (see Appendix C) may provide insights into how these modifications can be made for future surveys, especially if the spatial distribution of the target species is reasonably constant from year to year. For multi-species surveys, optimal allocation or stratification for one species may not be optimal for others and a compromise allocation or stratification scheme may be needed (see Appendix C for an example).

Optimal survey design can also improve the precision of model-based estimates. Such designs typically have stations distributed more or less uniformly over the survey grounds (MacLennan and Simmonds, 1992). Additional stations may be warranted to distinguish small-scale from large-scale variation, or to characterize the influence of auxiliary variables on sampling density. The structure implied by the additional assumptions made in a model-based approach does not eliminate the careful attention that should be paid to traditional concerns about good survey design, and continuing validation of the assumptions under possibly changing conditions may require additional data.

Adaptive Sampling—The spatial distribution of fish can change in ways that are not entirely predictable and changes in the distribution of species that school or aggregate can have major effects on estimates. As a result, survey biologists may need to adapt their surveys to encountered patterns of abundance. In theory, adaptive sampling could reduce the standard error and coefficient of variation compared with a stratified random sampling design. In an adaptive sampling design, the selection of sites at which samples are taken depends on what has already been caught or observed during a survey. Adaptive survey design allows the optimization of survey data collection in light of current knowledge rather

3  

Kriging is a minimum-mean-square-error method of spatial prediction (Cressie, 1993), a method of interpolation using data observed at known locations to predict unknown intermediate values (http://www.tc.cornell.edu/visualization/contrib/cs490-95to95/clang/kriging.html ). Kriging has some problematic properties for estimating distributions and abundances of living organisms, particularly mobile species. Kriging is the best linear unbiased estimate for the mean of abundance, but can greatly underestimate the variance of estimated abundance.

4  

The variogram is defined as the variance of the difference of observations at different sample sites, and thus summarizes the spatial variation. This measure is used to predict observations at the unsampled sites when using geostatistical spatial models (Cressie, 1993).

Suggested Citation:"General Issues in the Collection, Management, and Use of Fisheries Data." National Research Council. 2000. Improving the Collection, Management, and Use of Marine Fisheries Data. Washington, DC: The National Academies Press. doi: 10.17226/9969.
×

than past knowledge, but such designs can be complex to implement, suffer from possibly poor data at earlier steps in the current survey, may not provide data needed for time series, and appear to be unusually subject to human error in implementation. Thus, they must be introduced and evaluated with some caution before they are adopted widely.

Types of adaptive sampling designs include adaptive allocation and stratification, adaptive cluster sampling, and optimal Bayesian designs. In adaptive allocation, the final sample sizes in each strata are determined during the survey based on observed abundances. Examples include the adaptive allocation designs for anchovies described by Jolly and Hampton (1990), and for mackerel and orange roughy described by Francis (1984), the design-unbiased adaptive-allocation shrimp survey design described by Thompson et al. (1992), and the adaptive allocation of effort for scallop surveys (Smith et al., 1999). In adaptive stratification, the stratum boundaries are determined adaptively during a survey, for example, by drawing a new stratum for intensive sampling where high concentrations of fish have been observed during the survey. In adaptive cluster sampling, neighboring units or sites are added to the sample whenever high abundances are observed (Thompson, 1990; Quinn et al., 1999). Optimal model-based designs rely on a spatial model of distribution of fish abundance and take into account abundances encountered at initial sites in the survey in selecting subsequent sampling sites, for the purpose of maximizing overall estimation precision for a given amount of effort (Chao and Thompson, 1997). Hanselman et al. (in press) demonstrated that adaptive sampling in their experiment with rockfish reduced variance by about the same extent as stratification of sampling by habitat. The combination of adaptive and stratified sampling yielded an even lower variance. Hanselman et al. suggested that adaptive sampling might be especially appropriate when not enough information about a species' habitat preferences and extent of specific habitats in an area is available to stratify by habitat. Adaptive sampling may decrease the travel time in a survey because similar sampling effort is clustered into fewer locations (Quinn et al., 1999). Adaptive designs of all types are described in Seber and Thompson (1993) and Thompson and Seber (1996).

An important application of adaptive sampling could feature commercial fishermen as adaptive samplers in joint NMFS and industry sampling activities. Generally, commercial fishing vessel skippers do not fish at pre-determined locations but respond to encountered fish abundances. When few fish are caught at one location, the vessel may travel some distance to try a new area, and when many fish are caught the vessel may spend more time at nearby locations. Because of aggregation tendencies in fish abundance, considerably more fish may be caught this way than could be caught through any non-responsive (random or fixed station) strategy. Thus, the commercial fishing pattern is adaptive, and conventional estimators that ignore the non-random spatial distribution of the fishing effort, such as a sample mean of catch or CPUE, can have a significant bias. This would be the case, for example, if the skill of vessel skippers together with the aggregation tendencies of the fish allow CPUE to remain high even while total stock abundance declines substantially. These features have rightly been recognized as invalidating standard procedures for estimating abundance that assume a proportional relationship between CPUE and population size. Recognizing the adaptive nature of commercial fishing practices, better estimates of fish abundance might be obtained by working with industry to conduct cooperative adaptive sampling using likelihood model-based estimates, taking into account the spatial locations of catches. Fishing patterns can be taken into account in several different ways. The simplest would be to partition the catch into much smaller geographic regions than is usually done, so that averaging of CPUE would be in areas of more uniform effort than is the case when a larger geographic unit is used. A more sophisticated approach would use a spatial statistical model together with accurate geographic location

Suggested Citation:"General Issues in the Collection, Management, and Use of Fisheries Data." National Research Council. 2000. Improving the Collection, Management, and Use of Marine Fisheries Data. Washington, DC: The National Academies Press. doi: 10.17226/9969.
×

information on where each catch was made, and ideally would take into account any auxiliary information available, such as acoustic measures of fish biomass or numbers.

Adaptive commercial surveys seem to be catching on in some places for a number of practical reasons. In the surveys described by Quinn et al. (1999), in which the commercial fleet was used to survey marine fish in Alaska, the adaptive design was well received because fishermen were reimbursed for their costs with fish caught in the survey and most of the catch came from adaptively added sites. Even though more fish were being caught, unbiased or nearly unbiased estimates of fish abundance were available, since the adaptive survey had been well designed by the biologists involved—whose primary concern was increasing precision—by focusing more of the sampling effort in areas with greater fish abundance. To implement such adaptive sampling programs widely, more research is needed regarding the most effective designs to use in cooperation with commercial fisheries, data needs (including accurate geographic information and use of acoustic and other auxiliary data), data analysis methods, and the social and economic aspects of cooperation of commercial fishermen in adaptive surveys. The methodology for adaptive sampling will have to be developed on a fishery-by-fishery basis, so the results can be incorporated into assessments appropriately.

Interpretation of Survey Results

Uncertainties concerning selectivity, catch-ability, and availability of fish to survey gear are usually cited as reasons for interpreting survey estimates of abundance as relative indices rather than estimates of actual population size or biomass (Somerton et al., 1999). Users generally assume that the relationship between the survey index and actual population abundance is constant, although both fluctuate in absolute terms over time.

Survey indices are rarely used by themselves to evaluate the impact of fishing on a population of fish, but are instead incorporated into integrated fishery models along with other information about the fishery. Although design- and model-based strategies can provide variance estimates for the survey indices of abundance, these variance estimates are rarely incorporated into the fishery models. This increases the difficulty of assessing gains in precision versus improvements in design on the estimates and predictions from the fishery models (e.g., Nandram et al., 1997). With today's modern integrated fishery models, estimates of uncertainty can and should be incorporated directly into the assessment. Appropriately weighting likelihood components is one way to incorporate uncertainty, although some research will be needed to figure out the best way to do this. Determining appropriate weights is not a trivial task and if an analysis weights the components incorrectly, the uncertainty of the results will increase. Knowledge of the biology of a species and characteristics of the data available (e.g., its precision) can help in the choice of weights to apply to individual data sources. Once incorporated, precision in the estimates of interest should be carried through the methods of approximations to statistical distributions (e.g., Gaussian), bootstrap, or Monte Carlo techniques. Carrying precision through analyses will provide an incentive to increase or optimize the precision of the various input data so that they yield the required precision of the estimates (e.g., the TAC) in the most cost-effective fashion. Such an approach is desirable to avoid the expense of increases in sampling precision that result in insignificant increase in the precision of stock assessment advice. There is little reason to make one measurement with a micrometer if it is to be added to another measurement made with a meterstick, since the precision of the sum will reflect the precision of the meterstick.

Ecosystem Data

Fisheries impact the wider ecosystem in various ways (Hall, 1999; Kaiser and deGroots, 1999) because they

Suggested Citation:"General Issues in the Collection, Management, and Use of Fisheries Data." National Research Council. 2000. Improving the Collection, Management, and Use of Marine Fisheries Data. Washington, DC: The National Academies Press. doi: 10.17226/9969.
×
  • Generate mortality on target and non-target species by direct capture and by less obvious interactions with the fishing gear (e.g., escape or bycatch mortality).

  • Provide food to scavenging species.

  • Generate litter and cause “ghost fishing” from broken, lost, or discarded fishing gear.

  • Disturb the seafloor or other habitat.

  • Change the life history characteristics of target and possibly non-target species (e.g., mean weight at age, growth rates, size composition) by selectively removing larger (and faster growing) elements of the population.

  • Change behavior of target and non-target species.

These effects can result at any intensity level of fishing. In addition, severe overfishing can alter the structure of marine food webs (Hall, 1999) and one species may replace another in the same ecological niche (e.g., spiny dogfish and other sharks and rays for cod and haddock on Georges Bank; Fogarty and Murawski, 1998). The prevalence of niche replacements is a crucial issue in regards to the feasibility and desirability of stock rebuilding programs as mandated by the Magnuson-Stevens Act, because such replacements could make stock rebuilding ineffective. Alterations in food webs increase in significance as gear selectivity increases (Wainright et al., 1993). Because the abundance of species depends in part on the effects of fishing but also on the effects of climate, pollution, habitat loss, and natural fluctuations (e.g., Hofmann and Powell, 1998), understanding the relation between a species' abundance and fishing activity requires more than merely monitoring these latter two factors. For some species that are not harvested, such as marine mammals and seabirds, dedicated surveys may be needed to determine their abundance and distribution. Additional studies, such as predator-prey and gear bycatch studies, may be needed to verify correlations seen in these observations. In other cases, routine fisheries monitoring may provide adequate data.

Five main routine sources exist for ecosystem-level fisheries data:

  1. Commercial catches and catch rates

  2. Fishery-independent surveys

  3. Onboard observer programs

  4. Recreational catches

  5. Plankton surveys

  6. Surveys of marine mammals and seabirds

In each of these types of monitoring, sampling is focused on target species or species assemblages. However, monitoring the status of the ecosystems more inclusively requires maintaining or enhancing the collection of abundance data for non-target species (e.g., the California Cooperative Oceanic Fisheries Investigations) and conducting process studies such as the Global Ocean Ecosystems Dynamics program. Likewise, essential fish habitat must be identified and its status monitored (Benaka, 1999).

Another way that fisheries monitoring could be of value is in providing overviews of ecosystem health. Ecosystem health is a somewhat ambiguous concept, but includes such things as an ecosystem's productivity, the diversity of its organisms (in terms of species and age classes), its stability and resilience in the face of disturbances, the general health and fecundity of component species, and the maintenance of unimpaired ecosystems processes. Size spectra of all species, resulting from fishing surveys, could be a robust measure of the integrated effect of fisheries on a marine ecosystem. Other integrative measures, such as fish fecundity, liver condition indices (e.g., Marshall et al., 1999), and growth and condition factors may also be possible indicators of ecosystem health if they are measured for representative sets of species. Taking samples to detect fish diseases and measure immunity levels have been proposed as approaches for monitoring the effects of contamination of the marine environment. All of these indicators are, or could be, byproducts of the ongoing monitoring of fish stocks.

Fisheries sampling could, therefore, serve

Suggested Citation:"General Issues in the Collection, Management, and Use of Fisheries Data." National Research Council. 2000. Improving the Collection, Management, and Use of Marine Fisheries Data. Washington, DC: The National Academies Press. doi: 10.17226/9969.
×

wider requirements than those they were set up to achieve. It is important that, while rendering the basic monitoring effective and efficient, these other uses are properly recognized and maintained.

Environmental Data

The strength of a given year-class of fish depends on both the size of the spawning stock biomass and environmental conditions from the time of spawning through recruitment. Ocean temperature, salinity, dissolved oxygen concentration, prey type and abundance, availability of essential fish habitat, and predation can have significant effects on recruitment and subsequent year-class strength (Murawski, 1993; Hixon and Carr, 1997). Important examples of fish and shellfish species that may be particularly vulnerable to environmental conditions are those that exhibit a small number of dominant year classes (e.g., surf clams, ocean quahogs, West Coast rockfish, Pacific whiting) or short life spans (e.g., shrimp).

Most stock assessment models and most management control rules still assume that recruitment is related to spawning stock biomass and that the major dynamics of populations are driven by fishing-induced mortality, not by environmental factors. Unfortunately, methods that focus on spawning stock biomass to the exclusion of environmental factors may ignore regime shifts (Steele, 1998) occurring in these systems. Therefore, collection of environmental data and use of such data in future stock assessments is an important adjunct to estimation of spawning stock biomass.

Regime shifts can change the productivity of major ocean basins and there is evidence that this has occurred in the North Pacific Ocean (Francis and Hare, 1994; Francis et al., 1998; Hare et al., 1999) and other areas. If ecosystems have shifted to conditions less favorable for the growth of one or more fish species, the Magnuson-Stevens Act's requirement for rebuilding fish populations to historic high levels may not be attainable because such levels may have occurred under more favorable environmental conditions.

In many cases, environmental data are being collected by other government agencies (e.g., other parts of NOAA, the National Aeronautics and Space Administration [NASA], the Environmental Protection Agency [EPA]) and are available from these sources. It will be necessary to provide environmental data on a scale and reference grid that is compatible with fisheries data. High-quality, long-term, spatially referenced data sets will continue to be required to assess the influence of environmental effects on fish populations. There is also a need for the development of scientific methods to facilitate recognition of regime shifts and to incorporate such recognition where necessary (e.g., incorporating realistic expected recruitment in short-term projections that consider existing environmental regimes). Continued research on the effects of the environment on fish population size, individual growth, survivorship, and spawning potential in conjunction with densitydependent effects is crucial for determining the kinds of data collection and stock assessments that should be used for any given species.

Fishery-Dependent Data

Data gathered from commercial and recreational fisheries are essential for assessing the mortality and other stresses that result from fishing and these data provide a direct measure of the effectiveness of management regulations. Such data can also provide information on many other aspects of a fishery, including fish population structure, gear selectivity over time, and the behavior of fish and fishermen. Fishery-dependent data can sometimes be used to provide a measure of relative abundance that can be compared with that determined from fishery-independent sources. Data costs for fishery-dependent data tend to be lower than for fishery-independent data because the former are a byproduct of commercial fishing activity, but fishery-dependent data are substantially more subject to bias and do not

Suggested Citation:"General Issues in the Collection, Management, and Use of Fisheries Data." National Research Council. 2000. Improving the Collection, Management, and Use of Marine Fisheries Data. Washington, DC: The National Academies Press. doi: 10.17226/9969.
×

TABLE 3-4 Information Available from Commercial and Recreational Fisheries

 

Source

Information

Commercial

Recreational

Total catch by species (biomass, number)

Logbooks, observers

Intercept surveys, angler diariesa

Total catch and discards

Logbooks, observers

Intercept surveys, angler diaries

Proportion caught—by age, size class, market category, sex, and life history stage

Port sampling of landings, observers

Limited sampling from intercept surveys

Harvest location (GPS, latitude-longitude, loran)

Logbooks, landing surveys, VMS, observers

Intercept surveys, angler diaries

Landing location (port)

Landing sales receipts

Intercept surveys, angler diaries

Effort (number of hooks, tow length, angler hours, boat days)

Logbooks, landing surveys, observers

Telephone and intercept surveys

Cost of fishing

Logbooks, landing surveys

Surveys, angler diaries

Catch per unit effort

Logbooks, landing surveys

Intercept surveys, angler diaries

Gear type

Logbooks, landing surveys, observers

Intercept surveys, angler diaries

Vessel size and power

Logbooks, landing surveys

N/A

Crew size

Logbooks, landing surveys, observers

N/A

Fisherman or fishing vessel identifier

Logbooks, landing surveys

N/A

NOTE: GPS = global positioning system; N/A = not applicable; VMS = vessel monitoring system.

a Angler diaries are a method of obtaining these data, but are more frequently used in freshwater fishing.

include all important data elements. Thus, their collection, use, and integration with fishery-independent data require some care. Table 3-4 lists the kinds of information that can be gathered from commercial and recreational fisheries. The nature, scope, and reliability of this information are influenced by the time and effort required to gather, process, and store them. As a consequence, clear objectives are required if the datagathering processes are to run effectively. To assist in specifying objectives it is necessary to understand the costs of precision and the likelihood of avoiding bias. In that context, the following issues should be considered.

Many commercial fisheries in the United States are required by law to report fish landings. For these fisheries, total landings are estimated from the landing reports, and thus are really a

Suggested Citation:"General Issues in the Collection, Management, and Use of Fisheries Data." National Research Council. 2000. Improving the Collection, Management, and Use of Marine Fisheries Data. Washington, DC: The National Academies Press. doi: 10.17226/9969.
×

census of the harvest rather than a statistical estimate. Recreational fisheries generally are characterized by smaller landings, often of one or two fish by each angler, and usually are not required to be reported; thus, statistical sampling approaches must be used to estimate total harvest and discards for recreational fisheries. Statistical sampling approaches are also used to collect and process the auxiliary data that come from landings (e.g., age and size composition). Therefore, it becomes important to use appropriate random sampling protocols (Cochran, 1977) and recognize that (1) certain steps can improve statistical efficiency (e.g., stratification), (2) variation decreases with increasing sample size (Figure 3-1), (3) bias may exist in the data, and (4) the error associated with this process, whether random or systematic, will propagate itself into assessment estimates.

Commercial Fisheries

Stock assessment scientists have long been concerned about biases and other inadequacies in commercial fishery-dependent data of all types (Fox and Starr, 1996). These concerns include uncertainty about reporting accuracy, the component of the population encountered by the fishery, and the scale on which the observations are taken. Although it may be easy to react to such concerns by ignoring fishery-dependent data, such an approach is not prudent because information contained in such data cannot be obtained from other sources. Moreover, fishery-dependent data frequently cover a broader geographic area and a greater portion of the year than do survey data. Finally, fisherydependent data are necessary for both scientist and fishermen to understand how data from fishery-independent sources relate to situations in managed fisheries (see Chapter 4 for recommendations about increased user group participation in data collection).

FIGURE 3-1 Coefficient of variation and cost as a function of sample size. Note that certain levels of precision are unattainable for limited cost levels. Above certain sample sizes not much additional precision is obtained while costs continue to rise.

The following sections describe the variety of commercial data sources listed in Table 3-4. Many of these sources are in transition from manual methods to methods that are automated or otherwise take advantage of new technologies. The application of appropriate technology to collection of commercial fisheries data requires an

Suggested Citation:"General Issues in the Collection, Management, and Use of Fisheries Data." National Research Council. 2000. Improving the Collection, Management, and Use of Marine Fisheries Data. Washington, DC: The National Academies Press. doi: 10.17226/9969.
×

intimate knowledge of fisheries management and of the equipment available to fishermen and other data providers. Equipment that might be sensible in an office may be totally inappropriate on a fishing vessel that may encounter high winds, waves, and corrosive seawater. Nonetheless, fishing vessels today often carry and use personal computers, global positioning systems (GPS), cellular phones, vessel monitoring systems that work with GPS, electronic chart systems, sonar, and fishing net sensors. The value added by any new technology must be balanced against the incremental cost to fishermen, regulatory agencies, and managers. Any proposal for use of a new technology must take into account the impacts on existing systems, the potential for data fouling,5 constraints imposed by the need to use historic data, resistance to change by data managers and users, and costs. Managers wanting to encourage implementation of new technologies should consider incentives, particularly cost sharing, provision of free equipment, or provision of value-added services. Tax credits are another possibility.

Logbooks—In many fisheries, commercial vessel operators are required to submit detailed records, called logbooks, logs, or vessel trip reports (VTRs), of their fishing activities. Table 3-5 lists U.S. federal fisheries that have logbook requirements. Some additional federal and state fisheries are managed by the interstate commissions or by states and have their own logbook programs. For example, Washington, Oregon, and California have a mandatory tri-state trawl logbook program coordinated by the Pacific States Marine Fisheries Commission. This and other non-federal logbook programs may provide useful data for regional and national fishery data management systems. The information required in logbooks varies from fishery to fishery but generally includes the following:

  • The vessel's identity

  • Date, time of day, and position (longitude and latitude) of fishing activity

  • Information about weather

  • Details of fishing gear used

  • Amount of fishing activity (e.g., tow length, number of hooks, or trips)

  • Catch of target species

  • Catch of other species, including protected species

Logbooks for the commercial summer flounder fishery contain the same general information. VTRs are to be completed at sea and submitted to NMFS within 15 days after the end of the month in which the fishing occurred. In some regions, logbooks are collected at dockside. This practice ensures that data are submitted in a timely fashion, adds a level of verification to the data, and establishes a point of contact between NMFS personnel and fishermen. Logbooks can also be validated —at least in terms of catch, discards, and misreporting—by comparing data from unobserved trips with observed trips employing the same fishing strategy6 for the same species, and with dealer records. Data from paper logbooks often are entered into a computer database without verification or double entry, and are considered confidential.

The Electronic Fish Catch Logbook Project represents an innovative effort to automate and standardize logbook data (Box 3-1). Electronic logbooks are also being tested or used operationally in other countries (e.g., South Africa).

Dealer Reports—In some states, fish dealers are required to report the amounts of fish bought and sold. This information can be used to adjust retained catch estimates from logbooks, but is not considered to be a substitute for the detailed information contained in logbooks. For summer flounder and other species taken with federal per-

5  

Data fouling is a phenomenon in which changes in regulations diminish the ability of managers to compare new and old data or that make the newly available data represent the fishery less accurately or precisely.

6  

A fishing strategy involves the type of gear used and the location at which it is fished.

Suggested Citation:"General Issues in the Collection, Management, and Use of Fisheries Data." National Research Council. 2000. Improving the Collection, Management, and Use of Marine Fisheries Data. Washington, DC: The National Academies Press. doi: 10.17226/9969.
×

TABLE 3-5 U.S. Fisheries7 With Mandatory Federal Logbook Requirements

Region

Fishery

Alaska

Groundfish

Halibut

Northeast

Sea scallops, summer flounder, squid, scup, mackerel, butterfish, black sea bass, and northeast groundfish

Atlantic purse seine

Bluefish

Northwest

None

Southeast and Gulf of Mexico

Shrimp

Pelagic longline

Snapper/grouper and Gulf reef fish

King mackerel

Golden crab

Wreckfish

Shark

Headboat

Charterboat

Southwest and Western Pacific

Pacific pelagic longline

Lobster

Precious corals

Eastern Pacific purse seine

Western Pacific purse seine (South Pacific Tuna Treaty)

Antarctic (Convention for the Conservation of Antarctic Living Marine Resources)

SOURCE: National Marine Fisheries Service.

mits, dealers in the mid-Atlantic and Northeast regions submit data of two types by two different methods. First, dealers submit weekly reports (weighout slips) of fishery landings by vessel to either NMFS statistical port agents or to states first (for Delaware and Connecticut) and then to port agents. The port agents enter dealer data in electronic form and transmit them to their regional office and the Northeast Fishery Science Center. Dealers are also required to report by phone (via the Interactive Voice Response [IVR] system) weekly landings by species, either directly to federal scientists or via states (for Massachusetts). NMFS received funds in fiscal year 2000 to establish a coastwide IVR system for all state and federal voice reporting requirements. On the U.S. West Coast, dealer reports are collected by the states, rather than by NMFS.

mits, dealers in the mid-Atlantic and Northeast regions submit data of two types by two different methods. First, dealers submit weekly reports (weighout slips) of fishery landings by vessel to either NMFS statistical port agents or to states first (for Delaware and Connecticut) and then to port agents. The port agents enter dealer data in electronic form and transmit them to their regional office and the Northeast Fishery Science Center. Dealers are also required to report by phone (via the Interactive Voice Response [IVR] system) weekly landings by species, either directly to federal scientists or via states (for Massachusetts). NMFS received funds in fiscal year 2000 to establish a coastwide IVR system for all state and federal voice reporting requirements. On the U.S. West Coast, dealer reports are collected by the states, rather than by NMFS.

The weekly and IVR reports are used for seasonal monitoring of total allowable catch and other quotas. These reports provide timely verification of reports obtained by other methods. They can be compared with logbook data, biological data, days-at-sea estimates made from call-in systems, slips and IVR data also can be analyzed and used to monitor vessel compliance with trip limits. Most importantly, they provide the principal source of price data of landings by market category and species. and observer data. The weighout

7  

Fisheries can be defined in different ways, as illustrated in this table. Fisheries can be defined in terms of species or species complex targeted, gear/area combination, area alone, and type of vessel. In each case, the fishery encompasses a fleet and its associated activities. A specific vessel may be involved in more than one fishery.

Suggested Citation:"General Issues in the Collection, Management, and Use of Fisheries Data." National Research Council. 2000. Improving the Collection, Management, and Use of Marine Fisheries Data. Washington, DC: The National Academies Press. doi: 10.17226/9969.
×

BOX 3-1

Electronic Fish Catch Log

The Northwest Fishery Science Center designed a prototype electronic logbook for commercial fisheries operating out of California, Oregon, and Washington. West Coast fishermen requested such a system to reduce the effort required for data entry with paper logbooks and to make logbook data more useful. The Innovation Fund Committee of the National Performance Review provided funds for this project. The project uses personal computers that are already onboard many fishing vessels, combined with ship-to-shore communications, and a secure onshore database. The project will standardize methods of logbook data collection and will seek opportunities to improve data quality, quantity, and timeliness. Both logbook and fish ticket data will be reported electronically, thus allowing for independent verification of the data and combination of biological and economic data. System design is such that the Electronic Fish Catch Log will be transferable to other regions and can be integrated with vessel monitoring systems. The technology exists for electronic logbook data to be transmitted to shore-side data servers while vessels are still at sea. The timeliness of data analysis can certainly be increased where near-to-real time tracking of a fishery's performance is required. In addition, reducing the number of steps and handling of data from the recording step by fishermen to the availability of data to analysts in electronic form can improve the timeliness of resulting analyses and provide quicker feedback to respondents on the quality and content of their submissions. This compares to the current situation, in which the majority of logbook data typically are unavailable for analysis until weeks or months after landings are made because of time needed for mailing/faxing, handling/sorting, data entry, and quality control of the data entry. Currently, other technologies using form-based scanning/imaging of key logbook data and Interactive Voice Response systems are in widespread use on the Atlantic coast for tracking fisheries managed by total allowable catch. NMFS is engaged in a wide variety of initiatives related to planning, research, and implementation of data collection that seek to capitalize on the speed and cost-efficiency of new technologies for capturing, analyzing, and disseminating data.

The Electronic Fish Catch Log development process has included three stages:

Stage 1: Review existing data collection processes and identify potential uses of the new system. It was determined that an Electronic Fish Catch Log should allow electronic reporting of logbook and observer data and electronic reconciliation of catch data with fish ticket information. It was hoped that such a system would make more and better data available to fishermen and processors to manage their businesses more effectively and to improve the quality, quantity, and timeliness of fisheries data available to them. Stage 1 identified a number of other goals, such as improving confidence in the data; reducing the labor and cost involved in collecting, analyzing, and reporting data; and making logbook data more accessible to a wider range of users.

Stage 2: Analyze available technical alternatives and develop a design.

Stage 3: Develop a field-ready prototype partnership with commercial entities.

The program is presently in stage 3 and has identified potential commercial partners.

Suggested Citation:"General Issues in the Collection, Management, and Use of Fisheries Data." National Research Council. 2000. Improving the Collection, Management, and Use of Marine Fisheries Data. Washington, DC: The National Academies Press. doi: 10.17226/9969.
×

Port Sampling—Dealers and auction houses in ports can add to the reports of onboard observers (see below) about biological informatioin such as size and sex of captured fish, as they can be a source of samples of tissues (scales, fins, otoliths) for age determination. NMFS port samples or their representatives are authorized to gather biological information from state- and federally permitted dealers (CFR 648.7, Section G, Additional Data and Sampling). Access to the fish, however, often is restricted because the dealers are concerned that the sampling process will diminish product quality by disfiguring the fish and/or delaying shipping. The authority of the port samplers varies in different regions and with different management systems. For example, most U.S. individual fishing quota systems require advance notice of landing so a port agent can be present when the catch is landed. Other management systems use a more ad hoc approach to port sampling. On the U.S. West Coast, port sampling is conducted by the states, with partial support from NMFS for such activities. For the states of Washington, Oregon, and California, port sampling is conducted by the states and the Pacific States Marine Fisheries Commission, with partial support from NMFS for such activities. The laws of all three states provide the state with the right to sample the fish being landed, even if this means disfiguring the fish to remove otoliths. In some cases, the states purchase the damaged fish.

In the U.S. Northeast region, suggested sampling schedules (by species, quarter, gear, area, market category) are provided to port agents by NMFS stock assessment scientists (Burns et al., 1983). For West Coast groundfish, the suggestions for sampling schedules come primarily from the Pacific Fishery Management Council's Groundfish Management Team. NMFS stock assessment scientists are involved, but so too are scientists from the state agencies that do almost all of the port sampling. On-site biological sampling procedures are governed by port agent sampling manuals. Port agents can supplement the sampling suggested by stock assessment scientists with opportunistic sampling. The sampling unit is a box, which may not be representative of the entire catch of the vessel from which the box is obtained. Fish are measured and hard parts are collected from the sampled fish. Some concern exists regarding possible biases in the samples because of non-random sampling and because samplers may not be permitted access to the highest quality fish.

Onboard Scientific Observers—Commercial fisheries can also provide data from independent observers onboard commercial vessels. Scientific observers are placed on fishing vessels for a variety of purposes, including monitoring of (1) interactions with protected species under various fishery management plans, (2) catch, and (3) bycatch and discards (Table 3-6) (Karp and McElderry, 2000). Some observer programs are mandated (e.g., all foreign vessels in the U.S. EEZ [Sec. 201(h)] and some North Pacific vessels [Sec. 313]) under the Magnuson-Stevens Act and for marine mammals under the Marine Mammal Protection Act (e.g., Secs. 114[b][3][B], 114[e]). Even when the primary purpose of observers is to monitor fishery interactions with protected species, they can often keep records of bycatch and discards, and occasionally take biological samples of the catch.

The extent to which vessel operators misreport bycatch and discards is unknown. Observer data can be used to verify log sheet information and to provide correction factors for bycatch on unobserved trips. Observer data provide information that makes it possible to manage by what is caught, not merely what is landed and reported. This is important because the difference— bycatch and unreported catch—affects the assumptions about the mortality of non-target species or age classes. Observers are also important for fisheries in which fish are processed at sea and cannot be sampled by port agents.

Suggested Citation:"General Issues in the Collection, Management, and Use of Fisheries Data." National Research Council. 2000. Improving the Collection, Management, and Use of Marine Fisheries Data. Washington, DC: The National Academies Press. doi: 10.17226/9969.
×

TABLE 3-6 U.S. Fisheries in Federal Waters That Use Observers (excludes state programs and salmon observations)

Region

Agency

Fishery

Percentage of Catch Observed

How Observers are Placed

Purpose

Funding

Mandatory vs. Voluntary

Alaska

NMFS

Groundfish (at sea and shoreside)

30 percent for 60-125 ft. vessels 100 percent for vessels > 125 ft

Contractors

Landings

Industry (80 percent)NMFS (20percent)

Mandatory

 

NMFS

CDQ Fisheries

100 percent

Contractors

Total catch monotoring

Industry

Mandatory

 

ADF&G

Aleutian Island King Crab Fishery

100 percent

Contractors and ADF&G

Landings/bycatch biologacal data

Industry ADF&G

Mandatory

 

ADF&G

Bering Sea King/Tanner Crab Fishery

14 percent

Contractors and ADF&G

Landings/bycatch biological data

Industry ADF&G

Mandatory

 

ADF&G

Scallop Dredge Fishery

100 percent

Contractors and ADF&G

Landings/bycatch biological data

Industry ADF&G/AKFIN

Mandatory

West Coast & Western Pacific

NMFS

Offshore Pacific Whiting Fishery

100 percent

NMFS-certified cantractors

Landings/bycatch

Industry/NMFS

Voluntry

 

NMFS

Shoreside Landings of Pacific Whiting

13 percent

ODFW Admin.;contractors placedby PSMFC

Landings/bycatch

Industry/NMFS ODFW/WDFW/CADFG

Voluntary

 

NMFS

California/Oregon Drift Gillnet Fishery

20 Percent

NMFS and contractors

Landings/bycatch, marine mammal interractions

NMFS

Mandatory

 

NMFS

Monterey Bay Halibut Set Gillnet Fishrey

30 percent

NMFS

Landings/bycatch, marine mammal interractions

NMFS

Mandatory

 

NMFS

Hawaii Pelagic Longline Fishrey

4 percent

NMFS

Landings/bycatch biological data

NMFS

Mandatory

 

NMFS

Northwestern Hawaiian Islands Lobster Fishery

100 percent

NMFS

Landings/bycatch biological data

NMFS

Mandatory

Northeast

NMFS

Atlantic Sea Scallop Dredge Fishery

25 percent (in 1999)

NMFS/National Fish and Wildlife Foundation

Landings/bycatch biological data

Industry/NMFS

Mandatory

Suggested Citation:"General Issues in the Collection, Management, and Use of Fisheries Data." National Research Council. 2000. Improving the Collection, Management, and Use of Marine Fisheries Data. Washington, DC: The National Academies Press. doi: 10.17226/9969.
×
 

NMFS

Giant Bluefin Tuna Purse Seine Fishery

96 percent

Contractors

Fishery interactions

NMFS

Mandatory

 

NMFS

Large Pelagic Drift Gillnet Fishery

81 percent (program ended after 1998 season)

Contractors

Catch, management, and economic data

NMFS

Mandatory

 

NMFS

Lobster Pot Fishery

<1 percent

Contractors

Scientific, economic, compliance, and management data

NMFS

Mandatory

 

NMFS

New England and Mid-Atlantic Gillnet Fishery

2-4 percent

Contractors

Scientific, economic, compliance, and management data

NMFS

Mandatory

 

NMFS

Northwest Atlantic Trawl Fisheries

<1 percent

Contractors

Scientific, economic, compliance, and management data

NMFS

Mandatory

Southeast

NMFS

Southeastern Shrimp Otter Trawl

<0.1 percent

Contractors

Bycatch and turtle interactions

NMFS

Voluntary

 

NMFS

Swordfish and Pelagic Longline Fishery species

2.5-5 percent

Contractors

Bycatch, effort, interactions,biological data

NMFS

Mandatory

 

NMFS

Southeast Atlantic Shark Drift Gillnet/Strike Net Fishery

<100 percent

NMFS/Contractors

Landings/bycatch

NMFS

Mandatory

 

NMFS

Directed Large Coastal Shark Fishery

4 percent

NMFS/University of Florida

Landings/bycatch biological data

NMFS

Mandatory

SOURCE: National Marine Fisheries Service.

NOTE: ADF&G = Alaska Department of Fish and Game; AKFIN = Alaska Fisheries Information Network; CADFG = California Department of Fish and Game; CDQ = community development quota; NMFS = National Marine Fisheries Service; ODFW = Oregon Department of Fish and Wildlife; PSMFC = Pacific States Marine Fisheries Commission; WDFW = Washington Department of Fish and Wildlife.

Suggested Citation:"General Issues in the Collection, Management, and Use of Fisheries Data." National Research Council. 2000. Improving the Collection, Management, and Use of Marine Fisheries Data. Washington, DC: The National Academies Press. doi: 10.17226/9969.
×

FIGURE 3-2 Percent error as a function of observer coverage associated with estimates of catch and bycatch species in the autumn 1996 trawl fishery for walleye pollock in the Bering Sea/Aleutian Islands region. Reprinted from Figure 3-1 in Precautionary Approach to Fisheries with permission from the authors and the Food and Agriculture Organization of the United Nations.

SOURCE: Dorn et al. (1997).

Sampling designs allocate observer effort at three levels: among vessels, among hauls taken by a given vessel, and among samples in a given haul. Random selection of vessels can be difficult to achieve (Karp and McElderry, 2000). Random sampling among hauls is easier to achieve, but sampling within a haul can be difficult, depending on the size of the haul, the commonness of the species of interest, and operating constraints of the shipboard working environment.

Low levels of observer coverage yield high levels of uncertainty in the observed variables for most species (Dorn et al., 1997). For target species and some non-target species, most reductions in uncertainty are achieved by the time 30 percent of the effort is observed (Dorn et al., 1997; Vølstad et al., 1997) (Figure 3-2). However, Turnock and Karp (1997) showed that variability of estimates remain high until 50-70 percent of hauls are sampled and for rare bycatch species, uncertainty can remain high even when 100 percent of vessels are covered.

Observer programs are expensive and tend to focus on fisheries for which the probability of interactions of fishing operations with protected species (e.g., marine mammals, marine turtles, and seabirds) is high. Observer programs are more common in large-scale “industrial ” fisher-

Suggested Citation:"General Issues in the Collection, Management, and Use of Fisheries Data." National Research Council. 2000. Improving the Collection, Management, and Use of Marine Fisheries Data. Washington, DC: The National Academies Press. doi: 10.17226/9969.
×

ies because vessels in these industries are most able to fund such programs and most likely to have bunk space for observers. Observer programs have been set up for many specific fisheries (Table 3-6), yet many of the largest U.S. fisheries have inadequate observer coverage. In 1998 and 1999, onboard observers monitored fishing operations that resulted in 0.6 percent and 0.8 percent respectively, of landings of summer flounder.

Most observer programs are funded solely by the government, although the Alaskan ground-fish fishery observer program—the nation's largest—is funded 80 percent by industry. Some other West Coast observer programs have also received industry and state support. This differs from the system generally used in Canadian fisheries, in which the government pays program administration costs (about 30 percent of the total) and the industry pays for the costs of the observers. The total U.S. observer coverage is approximately 60,000 to 70,000 days per year (Karp and McElderry, 2000), equal to about 300 yearly fulltime equivalents. The direct costs of these observers, plus overhead, thus account for a substantial fraction of all data-generation costs of monitoring fisheries.

Data from observers are considered proprietary company information and such data are usually collected and maintained separately from vessel logbook data by NMFS. Observer data are kept confidential to preserve proprietary information reflecting the location of high-quality fishing grounds. Although such an effort is appropriate to protect the rights and needs of fishermen, in some instances confidentiality has proved to be a barrier to the fishing industry in its attempts to reduce bycatch. Dave Fraser, a commercial fisherman, noted that one innovative approach taken by fishermen in the Gulf of Alaska and Bering Sea pollock fisheries is for the captain to ask observers for their bycatch records as they are collected during the trip. The captain can then share that information with fishermen on other vessels (this is done through a commercial firm that produces and distributes bycatch maps [see Figure 3-4]), so they can jointly identify and avoid areas of high bycatch—an effort that benefits all, because the entire fishery is closed when the bycatch limits for a protected species are reached. More widespread voluntary sharing of bycatch data could help reduce bycatch and keep bycatch-limited fisheries open for a greater part of their allotted seasons.

Observer programs are being used increasingly in innovative management plans in exchange for program features desired by industry. For example, the community development quota (CDQ) pollock fisheries in the Bering Sea require two observers on each vessel so the catch of these non-stop fisheries with at-sea processing can be fully observed. Another example is the 25 percent observer coverage of the scallop harvesters in the 1999 experimental opening of Georges Bank closed areas designed by the New England Fishery Management Council. This provision was included in the management package to obtain better information related to the bycatch and discard of yellowtail flounder and other species that the closed areas were designed to protect, and to help gauge the impact of scalloping on the seafloor habitat. Observers were randomly assigned to 25 percent of the harvesting trips. Vessels with an observer were allowed to land an additional 200 pounds of scallop meats for each day at sea in order to pay the cost of carrying the observer. The New England Fishery Management Council has extended this program to other closed areas in 2000.

The use of prohibited species bycatch limits as a management tool requires observers, which is why many of the Alaskan fisheries are observed. This region features these limits for halibut, king crab, and salmon, and zero quotas for endangered species such as Stellar sea lions and short-tail albatrosses. The observer program in the northeastern United States has focused on marine mammal-fishery interactions, but also produces useful fishery data.

Vessel Monitoring Systems—Vessel monitoring systems have been used since 1988 for foreign

Suggested Citation:"General Issues in the Collection, Management, and Use of Fisheries Data." National Research Council. 2000. Improving the Collection, Management, and Use of Marine Fisheries Data. Washington, DC: The National Academies Press. doi: 10.17226/9969.
×

TABLE 3-7 Fisheries Using Vessel Monitoring Systems

Fishery

Year Implemented

Number of Vessels

Foreign high-seas drift net vessels

1988

1,000

Hawaii/Western Pacific pelagic and lobster

1994

120

Western Pacific foreign fleet

1995

24

Atlantic sea scallops

1999

250

Georges Bank scallop fishery

1999

185

Atlantic swordfish

2000

20

Planned

400

Alaska pollock

2000

28

Planned

250

Alaska Atka mackerel

Planned

12

Southeast Calico scallop

Planned

30

Southeast Gulf of Mexico shrimp

Planned

50

Southeast gag grouper

Planned

100

Highly migratory species/Atlantic pelagic longline

Planned

800

Northeast groundfish

Planned

400

Northeast herring

Planned

10

Northeast monkfish

Planned

50

SOURCE: National Marine Fisheries Service.

high-seas drift-net vessels and since 1994 on a variety of U.S. vessels (Table 3-7). Vessels are tracked by either the ARGOS or INMARSAT satellites. The on-board VMS unit periodically reports its position to a central tracking facility and can be controlled by the tracking facility to change the frequency of reporting. VMS programs are used by treaty organizations—for example, the International Commission for the Conservation of Atlantic Tunas, the North Atlantic Fisheries Organization, and the Commission for the Conservation of Antarctic Marine Living Resources —to help regulate several international fisheries.

Congress asked NOAA in the NOAA Authorization Act of 1992 (P.L. 102-567) to conduct a study that would consider “active, transponderbased systems and passive, vessel signaturebased technologies capable of localizing or identifying individual vessels without the use of vessel-carried transmitters.” NOAA reported back to Congress on satellite capabilities for fisheries enforcement (NOAA, 1993), concluding that no single satellite possesses all the necessary attributes for passive monitoring. NOAA also tested the ARGOS and INMARSAT systems in 1991 for transponder-based monitoring and found that both systems provided the necessary characteristics. Of the two available satellite systems, the ARGOS system is somewhat cheaper, but less capable, than the INMARSAT system. The INMARSAT system has a 5-10 minute delay versus 2 hours for ARGOS, and ARGOS is a oneway (ship-to-satellite-to-shore) system versus INMARSAT' S two-way capability. INMARSAT units collect information from GPS satellites and transmit position and other information to INMARSAT satellites. INMARSAT also provides more precise position information (because it uses the GPS positioning) and enables vessel operators to keep in close touch with fishing company staff to increase coordination of shore-side and at-sea operations. The two-way communication feature allows near-real-time reporting of daily catches for quota monitoring purposes.

VMSs are used most often for monitoring vessel position, but in their most advanced form they also can be used to enhance a fisherman' s business practice and to automate catch and effort reporting. VMSs have the potential of pro-

Suggested Citation:"General Issues in the Collection, Management, and Use of Fisheries Data." National Research Council. 2000. Improving the Collection, Management, and Use of Marine Fisheries Data. Washington, DC: The National Academies Press. doi: 10.17226/9969.
×

ducing reliable and useful information for both management and research and at a minimum can be used to verify times and dates reported on both fishing and observer logbooks and can provide efficient monitoring of vessel position (e.g., to enforce closed areas and seasons) and days at sea. VMS programs can reduce the costs of certain types of surveillance and allow targeting of enforcement resources.

VMS programs have some limitations. They are unable to monitor the fishing gear being used, or whether vessels stay within their catch quota; neither can they detect unlicensed fishermen or arrest violators. Therefore, VMS units must be augmented by vessel-, aerial-, port-, and observer-based monitoring programs. The costs associated with purchasing and installing VMS units may be prohibitively high for some fisheries or fishing vessels (estimated at $8,000 per vessel plus $100,000 for the shore station).

The NMFS Office for Law Enforcement is sponsoring a National Vessel Monitoring Project. To date, approximately 375 U.S. commercial vessels have been equipped with a VMS unit as part of this project. For the most part, NMFS paid for the necessary equipment, although there have been a few cases in which fishermen paid for the on-board equipment. Acceptance of and reactions to the VMS implementation have varied considerably, with fishermen in the Hawaii region being most accepting and those on the East Coast least accepting (S. Yin, NMFS, personal communication, 1999). VMS programs are more likely to be accepted if costs are offset by incentives or significant benefits to fishing businesses. NMFS believes that sophisticated VMS programs can provide value-added services in the form of weather and environmental data, market conditions, currency exchange rates, fleet management information, port services information, automated licensing, and automated transfer of quota shares.

Confidentiality restrictions designed to limit the public availability of proprietary business information prevent sharing of VMS data among different branches of NMFS, thereby hindering research. Although these systems have been perceived by some as an unwanted intrusion into confidential business information, the benefits to the fishery as well as to the personal safety of fishermen may well outweigh other concerns. NMFS should work with fishermen to jointly develop and implement this critical fisheries science and management information technology.

Misreporting and Data Fouling—Gallagher (1987) reviewed several factors that may contribute to commercial fishermen's lack of cooperation with mandated reporting and other management requirements, including allowable gear. He noted that efforts to eliminate “impasses between fishermen and regulatory authorities with regard to reporting catch data” were needed to create a cooperative atmosphere in which fisheries data could be generated, shared, and used.

Restrictions on gear may not be observed by fishermen for several reasons. Kaplan (1998) observed that conch fishermen did not abide by gear limits and marking requirements because of the problems associated with frequently replacing lost gear and being “unable” to keep up with the marking requirements for that new gear.

Gallagher (1987) suggested that management systems based on total allowable catch reduce the reliability of commercial catch data because fishermen may believe it is in their best interest to misreport or underreport catches or to discard sub-optimal catches. Gallagher characterized many problems associated with a logbook system that make it difficult to match catch data with individual vessels accurately, such as: (1) concerns related to financial privacy; (2) the extent to which knowledge about a fisherman's preferred area would become public knowledge; and (3) misreporting of amounts and locations of fish catches to evade regulations or restrictions that might be based on such data. Gallagher also noted that certain regulatory restrictions, such as species-based vessel quotas, may reduce the commercial fisherman 's motivation to report catch data accurately.

Extent of bycatch discarding and underreporting are important parameters in many stock

Suggested Citation:"General Issues in the Collection, Management, and Use of Fisheries Data." National Research Council. 2000. Improving the Collection, Management, and Use of Marine Fisheries Data. Washington, DC: The National Academies Press. doi: 10.17226/9969.
×

assessments. Discards can be increased by vessel quotas (Palmer and Sinclair, 1996), individual fishing quotas (Squires et al., 1998), and trip limits (Chambers, 1998); Kennelly and Broadhurst (1996) asserted that it is usually in the fishermen's best interest not to report discards. At-sea discards are estimated by comparing commercial fishermen's logbooks and data from fishery observers. Measures of by catch are notoriously difficult to collect, and both processors and fishermen have financial incentives to underreport the true discard rate and catch (Palmer and Sinclair, 1996; Chambers, 1998). Hanna and Smith (1993) observed, however, that fishermen are concerned with the discard waste resulting from minimum fish sizes and trip limits.

Kennelly and Broadhurst (1996) suggested that a partnership between fishermen and scientists, beginning with observer programs on commercial vessels, is the best means to reduce bycatch and the data fouling that results because the bycatch amount and/or species composition is either unknown or misreported. The Alaskan pollock fishery has incentives for timely and accurate reporting of bycatch and other data, and vessel-specific bycatch rates of prohibited species in the North Pacific are available on the World Wide Web at www.fakr.noaa.gov/1999/pscinfo.html. (Information provided elsewhere in the report describes how fishermen, observers, and commercial data management firms have teamed up to help pollock and other fishermen avoid high bycatch areas.)

Although the work of Kennelly and Broadhurst was focused on identifying the best bycatchreduction gear and encouraging its adoption by industry, their success in establishing partnerships between fishermen and scientists bodes well for such partnering efforts to address stock assessment needs. Kennelly and Broadhurst (1996) reported that the initial phase, involving scientists as observers on commercial vessels, helped establish productive working relationships that served as the basis for improved credibility, respect, communication, and collaboration in other efforts. Ongoing conferences and workshops to discuss the data and their implications continue to support this notion of shared responsibility for the fishery.

Kaplan (1998) reported that fishermen's perceptions that government is not interested in their suggestions about managing a fishery contribute to the fishermen's lack of compliance with and attitudes about enforcement of regulations. Incorporating fishermen more actively into aspects of the management and data-gathering process could help alleviate some of these concerns and increase incentives to comply with regulations to report catch and discard data accurately. Kaplan (1998) emphasized that fishermen were concerned that their experiences and knowledge were not recognized and incorporated during decision-making processes and that they were asked only to react to policies that had already been formulated.

Smith (1995), however, suggested that problems of noncompliance by commercial fishermen are rooted in fundamental differences in worldview between fishermen and scientists. These differences, she argued, center on differences in their beliefs regarding (1) what data are important or relevant; (2) how data should be gathered; (3) how data should be analyzed; (4) how those analyses should be interpreted; and (5) what responses should be crafted.

Recreational Fisheries

Survey Series—Historically, mortality from recreational fishing was thought to be low compared to that of commercial fisheries. This perspective changed for some marine fisheries as an increasing number of persons moved to coastal counties and as growth in disposable income resulted in increased marine recreational fishing. The importance of recreational fishing is illustrated in Table 3-8; in 1998 and 1999 the recreational catch of summer flounder was more than half the total landings for this species (see also Figure 2-1). The Marine Recreational Fisheries Statistics Survey (MRFSS) was established in 1979 to provide information on marine recreational fishing to complement data collected by NMFS from U.S.

Suggested Citation:"General Issues in the Collection, Management, and Use of Fisheries Data." National Research Council. 2000. Improving the Collection, Management, and Use of Marine Fisheries Data. Washington, DC: The National Academies Press. doi: 10.17226/9969.
×

TABLE 3-8 Comparison of U.S. Recreational and Commercial Catches for Popular Recreational Species in 1998

Fish Species

Recreational Catch (thousand metric tons)

Commercial Catch (thousand metric tons)

Bluefish

(Pomatomus saltatrix)

5.80

3.77

Red snapper

(Lutjanus campechanus)

1.98

1.85

Spotted seatrout

(Cynoscion nebulosus)

4.33

0.27

Summer flounder

(Paralichthys dentatus)

5.68

4.99

SOURCE: data from www.st.nmfs.gov/st1/commercial/landings/annual_landings.html and www.st.nmfs.gov/st1/recreational/database/index.html, accessed 02/03/00.

marine commercial fisheries. Recreational data are obtained from a broad-scale survey of coastal residents. According to NMFS the volume of MRFSS records handled and processed is more than an order of magnitude greater than for commercial fisheries. Three significant problems with the survey data are (1) the imprecision of estimates for some fishing modes,8 (2) the lack of funding for collection of data for some states, and (3) the lag of data availability and perhaps lack of interest from the regional councils that hinders inseason management of recreational fisheries.

MRFSS was conceived and designed to provide accurate and reasonably precise estimates of fishing for specific regions (e.g., mid-Atlantic states). The survey has to cover large geographic areas with numerous access sites throughout the year for all major and most minor target species. No single survey can achieve all of these goals without some compromises. The precision of estimates is best at the regional scale; fisheries that are heavily targeted over a broad season provide the best estimates of catch and effort. Precision is lower at finer geographic scales and for species that have shorter seasons of exploitation (typically migratory species) or are not targeted as heavily. For many states, the survey contracts with samplers to collect recreational data. Other states, such as Texas and Alaska, do their own sampling. Texas has collected recreational data since 1976 and funds collection of such data at a higher level than MRFSS could afford to do. Recreational fisheries data from Texas are provided to NMFS for stock assessments, but are not included in the MRFSS database. The survey does not conduct data collection for Hawaii, where a large portion of the population is involved in non-commercial fishing; the recreational catch is relatively unknown there. This situation persists even though the Western Pacific Fishery Management Council has requested survey coverage. Other states share responsibilities with the survey (Figure 3-3).

To accomplish a broad regional estimate of marine recreational fishing, MRFSS uses two complementary surveys to estimate total catch and effort annually: (1) a telephone survey and

8  

MRFSS uses the term “fishing modes” to indicate different forms of access to the fishery by recreational anglers. MRFSS modes include fishing from (1) shore, (2) party and charter boat, and (3) private and rented boat.

Suggested Citation:"General Issues in the Collection, Management, and Use of Fisheries Data." National Research Council. 2000. Improving the Collection, Management, and Use of Marine Fisheries Data. Washington, DC: The National Academies Press. doi: 10.17226/9969.
×

FIGURE 3-3 States with light shading are included in MRFSS. Darker shading indicates counties sampled with telephone surveys.

SOURCE: http:/www.st.nmfs.gov/st1/recreational/survey/coverage.html, accessed 06/12/00.

(2) an intercept survey. The telephone survey was designed to assess effort by estimating numbers of fishing trips per year, categorized by mode, where mode is defined as shore, party and charter vessel, or private and rental boat access. Each survey is conducted during a two-month period, called a wave, to reduce errors in anglers' memories. The intercept survey was designed to estimate catch and effort by species, length, and weight of fish caught by sending interviewers into the field to speak with anglers and observe their catch. The two data sources are combined to develop an estimate of total catch for each species in each wave for each access mode, as follows: catch = efforttelephonesurvey* (catch/effort)interceptsurvey* Thus, the intercept survey is intended to supply the ratio needed to expand effort estimates from telephone surveys to total catch. Intercept surveys also provide the ratio estimate of directed effort that is expanded from the telephone survey to estimate total directed effort.

Telephone Survey—The telephone survey is used to sample coastal counties to determine fishing patterns, for example, how many people actually go fishing. Coastal counties are those in which some part of the county is within 25 miles of the coast, except in North Carolina, where the limit is 50 miles (Figure 3-3). The survey interviewer calls households using a system of random-digit dialing and computer-assisted telephone interviewing, with telephone prefixes that include all the coastal counties. Only a small percentage of households contacted actually participate in fishing activities, even though this proportion is higher in the coastal counties than farther inland. The telephone survey also samples anglers who use both public and private access to the fishery to provide a more accurate estimate of total fishing effort than can be gained from onsite surveys alone (Pollock et al., 1994). Given the great difficulty in obtaining unbiased estimates of access mode using on-site surveys, the

Suggested Citation:"General Issues in the Collection, Management, and Use of Fisheries Data." National Research Council. 2000. Improving the Collection, Management, and Use of Marine Fisheries Data. Washington, DC: The National Academies Press. doi: 10.17226/9969.
×

telephone survey provides a more efficient and less biased estimate of this angling characteristic.

For the telephone survey, sample size is allocated on the basis of the square root of population size in a coastal county. In some cases, less than 100 phone calls are made in a county. This means that a few successful calls (i.e., those households with anglers) greatly influence county totals. It is unclear why each county is analyzed separately, thereby acting as de facto strata. It would be more efficient to group counties and to stratify on region within the state, based on similar angling patterns. Overstratification in sampling generally decreases statistical efficiency (Cochran, 1977). MRFSS has a wealth of historic data that would allow for a successful reduction in the number of strata.

Intercept Survey—The proportion of effort (i.e., number of trips) made by anglers from non-coastal counties is estimated from the intercept survey; the survey does not account for possible correlations between distance of residence from the coast and frequency of fishing. The intercept surveys are also the only source of information on the species and size composition of marine recreational harvests. This is used to correct effort-to-state totals. For this survey to be reasonable an assumption needs to be made that the intercept survey equally measures coastal and non-coastal fishermen within each mode, wave, and state. Another assumption is that fishing patterns with respect to types of fish caught are the same within these categories for coastal and non-coastal counties. It is not economically feasible to sample all non-coastal counties; therefore, a study designed to compare coastal and non-coastal fishing patterns may be warranted. Electronic data entry in the field is not cost effective at this time because of the power requirements of available computers and their susceptibility to contamination with salt water, sand, and biological material. However, the MRFSS team and the prime contractor are focusing on other uses of technology to improve the MRFSS process, including supplying all regional representatives with laptop computers, creating interactive Web applications for scheduling interview assignments, data review and clean-up, and providing on-line weekly tallies of quota status.

The intercept survey is conducted on-site, largely at public access points such as boat ramps, piers, and marinas, and yields catch rates for targeted species. Lists of access sites were compiled initially for MRFSS and are periodically updated as new sites are developed and old sites fall into disuse. The magnitude of use is evaluated by observation, size of the site (e.g., number of ramps), and historic use patterns. The amount of on-site sampling at access points is allocated proportionally to their use. Thus, heavily used sites are sampled more than lightly used sites. Interviews are obtained as anglers complete their fishing trips, at which time total catch and trip length are known.

In general, little sampling is directed toward private access fishing, which is difficult to survey because of private-property concerns and because the fishing trips in this mode are diffuse and difficult to observe. Unless otherwise indicated, it is assumed that target species and catch rates are similar for public and private access fishing. However, catch rates can differ between public and private access when fishing patterns are influenced by factors that correlate with access type. For example, if larger boats predominate at private access points and if these boats fish farther offshore where fish species and abundance change, estimated catch rates could be biased. This is a special concern in Maryland, Virginia, and New Jersey, which have appreciable private-access use.

Interviews are more difficult to obtain when anglers fish from shore. To increase the number of anglers interviewed, the survey agent walks along the shore or pier and interviews anglers encountered. Shore and pier surveys have a large percentage of “incomplete trips” because anglers are not finished for the day. Typically, the angler is in the midst of fishing and this type of sampling (roving survey) assumes that the catch rates are the same before and after the interview. An-

Suggested Citation:"General Issues in the Collection, Management, and Use of Fisheries Data." National Research Council. 2000. Improving the Collection, Management, and Use of Marine Fisheries Data. Washington, DC: The National Academies Press. doi: 10.17226/9969.
×

other assumption is that the total catch can be estimated from the catch at that time and the proportion of the trip finished at the time of the interview (e.g., if a trip is half over, one can double the number of fish caught in the first half to estimate the angler 's total catch for the day). The committee was not presented with evidence to support this assumption, which may not be valid if weather changes during the day. In addition, it was unclear how time of day impacts survey outcome. For example, do early morning catch composition and numbers differ from afternoon catch? Is sampling across time of day conducted in an appropriate fashion? How interviewers attempt to sample a cross-section of fishermen within each mode is not clear from MRFSS documentation. This may be a larger issue with some fish species than others because some species or certain size classes within a species are not as likely to be caught from shore. Because the probabilities of encountering an angler differ between the access and roving survey types, different calculations for estimating CPUE must be employed (Jones et al., 1995; Hoenig et al., 1997; Pollock et al., 1997).

Interviewers occasionally ride on party boats to interview anglers and to examine their catch. Private and rental boat anglers are interviewed while recovering or cleaning their boats at ramps or docks. It is unclear how interviewers choose one interviewing method over another. A small study comparing dock interviews with onboard observations would be useful to assess bias. Clearly, surveying on a party boat is apt to be more accurate but considerably more expensive than dock interviews. Either method must make the assumption that fishing practices are not influenced by the presence of an observer.

MRFSS analyses treat data from each fisherman on a single boat as being independent (ASFMC, 1994), implying that the skill of each fisherman is more important than the fact that a group of fishermen is fishing in the same location. But, the data cannot be assumed to be completely independent. If fishermen coming off the same boat have similar catches, the estimated standard error will be too low. The MRFSS document does indicate a cluster effect for charter vessel fisheries for anglers who have similar demographic characteristics (ASMFC, 1994, pp. 1-10). Adjustments are made case by case. Adjustments for clustering effects should be better documented with objective criteria. Clustering has a significant impact on uncertainty in the estimates because the formulas are based on a random sample of fishermen within strata.

MRFSS recognizes that survey intensity impacts estimates of numbers of fishing trips. MRFSS is designed to assess national landings and coastwide harvest limits, and may give reasonable estimates for each coast, but sampling effort is not sufficient to provide precise totals of effort for each coastal state for some fisheries. Several states have chosen to augment the MRFSS recreational survey effort, primarily through additional questions, rather than additional interviews. More interviews can be added if needed, but at additional cost. The average cost for intercept interviews nationwide ranges from approximately $22 to $51 per interview, and the average cost of a telephone interview is $2.87 per interview, with a three-fold range among regions of the United States.

MRFSS deals with missing and unusual values in a way that is not explained and justified in its documents. For example, when a fisherman is not home, the telephone survey method assumes that the absent person has the same patterns of fishing as those already surveyed at that home. Also, “[a]ny household [that] reports more fishing trips than the 95th percentile for the five-year distribution is reduced to the value of the 95th percentile.” (ASMFC, 1994, pp. 1-9). It is not clear why these observations are altered.

Marine Recreational Licenses—Some coastal states require licensing of marine anglers, although many states exempt various categories of anglers—primarily the elderly, young, disabled, and individuals fishing from shore (Table 3-9). Selecting individuals to contact in telephone surveys using sampling frames based on licenses or re-contacting known recreational anglers could be more cost-effective and efficient, although many factors need to be considered in making such an assessment. Random-digit dialing is most effective (in terms of cost and precision of estimates) when the target group forms a substantial portion of the general population. This is not true for marine anglers because they make up only a small percentage of the contacted households.

Suggested Citation:"General Issues in the Collection, Management, and Use of Fisheries Data." National Research Council. 2000. Improving the Collection, Management, and Use of Marine Fisheries Data. Washington, DC: The National Academies Press. doi: 10.17226/9969.
×

TABLE 3-9 Salt Water Recreational Fishing License Requirements and Exemptions

State

License Required (Yes/No)

License Exemptions

Maine

N

 

New Hampshire

N

 

Massachusetts

N

 

Rhode Island

N

 

Connecticut

N

 

New York

N

 

New Jersey

N

 

Delaware

N

 

Maryland

Ya

Residents under age 16 or older than 65 years, disabled veterans and former prisoners of war, the blind, fishermen on charter boats, and persons fishing outside Chesapeake Bay.

Virginia

Ya

Children under 16 years of age; persons 65 years or older, individual purchasers of a saltwater recreational boat license; persons fishing on a recreational boat, charter boat, headboat, partyboat, commercial fishing pier, or rental boat which possesses a valid Virginia recreational fishing license covering all persons using such craft or structure; persons fishing with commercial gear licensed by the Virginia Marine Resources Commission; persons fishing in coastal salt waters and ocean waters outside of the easternmost boundary of the Chesapeake Bay; and organized groups of individuals with physical or mental limitations, veterans in veterans hospitals, and school groups (K-12) with permission from the Virginia Marine Fisheries Commission.

North Carolina

N

 

South Carolina

Yb

Residents under the age of 16 and over the age of 65; residents fishing from a public fishing pier; and disabled residents.

Georgia

Y

Residents under the age of 16 and over the age of 65, blind residents, and disabled residents.

Florida

Y

Florida residents fishing from land or a structure fixed to the land —a pier, bridge, dock, floating dock, jetty or similar structure—but not from a boat; residents older than 65; residents who are a member of the U.S. Armed Forces stationed outside of Florida and home on leave for 30 days or less; residents under age 16; anyone fishing from a boat that has a valid commercial saltwater products license or a valid recreational vessel saltwater fishing license; and disabled persons.

Suggested Citation:"General Issues in the Collection, Management, and Use of Fisheries Data." National Research Council. 2000. Improving the Collection, Management, and Use of Marine Fisheries Data. Washington, DC: The National Academies Press. doi: 10.17226/9969.
×

Alabama

Y

Residents under the age of 16 and over the age of 65; residents fishing from a public fishing pier; and disabled residents.

Mississippi

Y

Residents who are blind, paraplegic, a multiple-amputee, adjudged totally disabled by the Social Security Administration or totally service-connected disabled by the Veterans Administration.

Louisiana

Y

Residents under the age of 16 and over the age of 65; citizens of the state who are on active military duty; veterans having a permanent service-connected disability; a resident who is totally and permanently disabled; and residents who have artificial limbs or permanent braces or are mobility impaired.

Texas

Y

Residents who are disabled veterans, under the age of 17 or over the age of 65, or who are mentally disabled.

Alaska

Y

Residents who are blind, under the age of 16, who are 60 years old or older and have a permanent ID card, and residents who qualify for a disabled veterans license.

Washington

Y

Residents under the age of 14 and over the age of 70, and disabled veterans.

Oregon

Y

Residents under the age of 14; disabled persons qualify for special permits.

California

Y

Residents who are under the age of 16, blind; low-income American Indians; wards of the State residing in a State hospital; developmentally disabled persons receiving services from a State regional center; residents who are so severely physically disabled that they are permanently developmentally disabled; persons receiving services from a State regional center; and residents who are so severely physically disabled that they are permanently unable to move from place to place without the use of a wheelchair, walker, forearm crutches, or a comparable mobility-related device.

Hawaii

N

 

SOURCE: National Marine Fisheries Service.

NOTES: Only basic saltwater licensing information is indicated. Some states also require additional permits or tags (e.g., snook, rockfish, salmon) and may have differing exemptions for these special permits. Some states, such as Oregon, have an “angling” license, which is for both fresh and saltwater fishing. Other states sometimes issue special recreational gear licenses or single-species licenses. In some states “exempted” persons don't have to buy a license, but must carry a license they receive at no cost.

a In Virginia and Maryland a license is only needed to fish in Chesapeake Bay waters, not for ocean waters.

b South Carolina officially doesn't have a saltwater license, but they do require that fishermen purchase a “stamp” that functionally is equivalent to a license.

Suggested Citation:"General Issues in the Collection, Management, and Use of Fisheries Data." National Research Council. 2000. Improving the Collection, Management, and Use of Marine Fisheries Data. Washington, DC: The National Academies Press. doi: 10.17226/9969.
×

Requiring licenses for marine angling (even free licenses) could improve data collection efforts by making a comprehensive sampling frame available and eliminating the inefficient randomdigit dialing approach for the telephone survey (but not the expensive intercept surveys). In theory, recreational effort assessments could be less costly (in terms of time, money, and staff) than current methods if based on license sample frames because anglers would be identifiable and sampled more easily. MRFSS compared the use of a license sampling frame from the State of Oregon with random-digit dialing to explore increasing precision and efficiency of estimates of recreational effort (Gray, 1997). The comparison yielded mixed results. Precision was improved in the shore and private boat modes at no additional cost by using the license frame, but the precision of data from the party/charter mode was not improved. This pilot study indicates that a more detailed test of license frames is in order.

States have jurisdiction over implementing marine recreational fishing licenses, over who must be licensed, and over the administration and structure of the resulting databases. Inconsistencies in the data that are included in state sampling programs, insufficiency of the frame, their tendency to become outdated quickly, and issues of confidentiality temper the value of license sampling frames. Further testing should include the standard measures of precision and accuracy, along with a detailed study of the costs involved in maintaining the license frames, access to the frames if they are maintained by the states, adequacy of the frames, and the data management issues that will ensue from combining separate frames. The use of the license frame should also be compared with the use of partial frames (random-digit dialing used with a partial license frame) and with longitudinal retention of anglers previously contacted in the random-digit dialing component of MRFSS. The issue of saltwater recreational licenses is controversial because many states do not presently require licenses, and anglers in those states do not want to face additional bureaucratic hurdles and a perceived intrusion of government into their private lives. Also, for a licensing system to achieve statistical and cost efficiencies, it would probably need to feature more uniform criteria for licenses among states. Different exemptions on licenses in each state would require NMFS to determine the fishing characteristics of unlicensed fisherman, requiring reversion to a system like MRFSS.

Social and Economic Data

Collection of social and economic data is important for several reasons. As described in Chapter 1, using social and economic information to better understand fishery-dependent data can improve the process of estimating the current status of the stock. This may be the most cost-effective method of improving stock assessments.

The Magnuson-Stevens Act requires the use of social and economic information in fisheries management. Section 301 of the Magnuson-Stevens Act contains the national standards for fisheries management. National Standard 1 requires that a fishery be managed for optimum yield. The definition of optimum yield is “. the maximum sustainable yield from the fishery as reduced by any relevant economic, social, or ecological factor.” Conservation and rebuilding of fish stocks are required by National Standard 1. National Standard 4 requires that allocations among fishermen be “fair and equitable.” National Standard 5 requires that management “. consider efficiency in the utilization of fishery resources. ” National Standard 7 requires that management measures “. where practicable, minimize costs. ” National Standard 8 re-

Suggested Citation:"General Issues in the Collection, Management, and Use of Fisheries Data." National Research Council. 2000. Improving the Collection, Management, and Use of Marine Fisheries Data. Washington, DC: The National Academies Press. doi: 10.17226/9969.
×

quires that management “. minimize adverse economic impacts on such communities.” Most of the other standards are not absolute, but instead recognize a trade-off between competing goals. Social and economic data are required to analyze the trade-offs required by the MagnusonStevens Act.

Changes in harvest levels designed to conserve and sustain fishery resources can usually be accomplished by several alternative combinations of regulations. Different regulations have different economic impacts, and it is incumbent on fishery managers to minimize the costs of conservation and the adverse economic impact on fishing communities (National Standards 7 and 8). GAO (2000) notes that the regional councils and NMFS seldom consider the economic impact of alternative conservation measures. Typically, conservation measures are enacted and the economic impacts are calculated, but there is no consideration of the economic impacts of a range of alternatives so that the least costly alternative may be chosen.

Studies of social and economic factors that affect summer flounder and other fisheries could benefit fisheries management by

  • making is easier to create more cost-effective regulations that encourage accurate data reporting,

  • improving knowledge of which fishermen (commercial and recreational) and processors would be affected by new regulations and how seriously,

  • increasing the equity of regulations among different parts of a council region and distributing data collection efforts to best meet data needs, and

  • improving communication among fishery stakeholders.

Social and economic assessments should evaluate a number of factors, including

  1. distribution of costs and benefits of current and proposed regulations;

  2. incentives driving data-reporting accuracy, with the goal of increasing accuracy of reported data;

  3. numbers of vessels, fishermen, crew, and processors and their economic dependence on the fishery;

  4. regional differences in socioeconomic status of fishermen throughout the fish stock range;

  5. information and communication needs perceived by affected fishermen, other industry members, environmental groups, recreational fishermen, and other stakeholders;

  6. numbers and distribution of recreational anglers and associated industries; and

  7. need for communication among decision-makers at all levels, including councils, NMFS, states, and legislatures.

In addition, it would be useful to conduct systematic social research to understand the factors that motivate compliance with both the spirit and the letter of conservation regulations. The results of such research could be the basis for improved management.

Cooperation, Communication, and Review

The committee attempted to determine whether data are collected cooperatively, how communication related to data collection is handled, and how the methods and results of data collection are reviewed.

Cooperation

Cooperation with Industry—Cooperation between commercial fishermen and fishery managers to improve fishery management, broadly called co-management, is not new. Hersoug and Ranes (1997) provided an overview of the comanagement concept and why it is receiving increasing attention: “By engaging fishermen in management, they would act more responsibly towards the long-term goal of sustainability. In other words, by being partly responsible for the management of ‘their own resources,' the need

Suggested Citation:"General Issues in the Collection, Management, and Use of Fisheries Data." National Research Council. 2000. Improving the Collection, Management, and Use of Marine Fisheries Data. Washington, DC: The National Academies Press. doi: 10.17226/9969.
×

BOX 3-2

Examples of Assistance Fishermen Have Provided to Research Efforts

Gallagher (1987) mentioned several examples of assistance that fishermen have provided to research efforts:

  • specimens for analysis and identification of new species (e.g., at the Smithsonian Institution)

  • observations that aid in behavioral studies

  • information about the habits, distribution, and abundance of commercially exploited fish species based on observations on the water

  • manpower for research and experiments (e.g., effects of fish-handling methods and evaluation of harvesting gear types)

  • vessel time and equipment for research efforts

  • aiding in research efforts to develop fisheries for underutilized species (e.g., red crab on Georges Bank)

  • tagging fish

  • providing stomach contents for feeding studies or hard parts for age and growth studies (e.g., swordfish).

for costly control, monitoring, and surveillance could be substantially reduced.”

Arguments for co-management also are based in democratic theory about the fairness and legitimacy of decision-making processes (McCay and Jentoft, 1996), including the need to involve those affected by the decisions. Jentoft et al. (1998) offered a compelling argument why fishermen should have an opportunity to become involved more actively in the entire management process, and the reasons included (1) improved management decisions, because those with hands-on knowledge of the fishery are involved; (2) improved communication among all parties; and (3) increased consideration of the socioeconomic aspects of the fishery in decisions.

In this report, discussion of co-management is limited to partnerships involving commercial fishermen in the data collection and research aspects of fisheries management (i.e., selection of methods, data gathering, and data interpretation), rather than in the policy and regulatory aspects of management (e.g., Jentoft, 1989; Pinkerton, 1989a,b). Gallagher (1987) described different types of assistance fishermen have provided to research efforts (Box 3-2). With co-management, fishermen have provided local knowledge of fish stock movements and distribution; funding for research; and stimulus for academic scientists to become more involved in generating scientific data (Pinkerton, 1989a,b). Johnston (1992) hypothesized several benefits that would accrue through improved partnerships among fishermen, scientists, and managers. These include “(1) a greater commitment to success by fishers who plan an active role in the design of management strategies; (2) reduced public cost through the use of data provided by fishers (through their organizations); and (3) a better understanding of the behavior of fishers.” Other benefits include enhanced credibility of the management process, and sensitizing scientists and other decision-makers to the sociopolitical context in which the fishing industry is embedded, leading to acceptance of fishing regulations (Palmer and Sinclair, 1996). Hersoug and Ranes (1997) suggested that “by involving fishers more directly into the decision-making process and by bringing the man-

Suggested Citation:"General Issues in the Collection, Management, and Use of Fisheries Data." National Research Council. 2000. Improving the Collection, Management, and Use of Marine Fisheries Data. Washington, DC: The National Academies Press. doi: 10.17226/9969.
×

agement process closer to those fishers who are affected, their willingness to come to an agreement and comply with the rules and regulations is enhanced.” They also noted that many authors have hypothesized or anticipated benefits of co-management, with little empirical demonstration of the benefits or costs of co-management in fisheries.

Fox and Starr (1996) suggested that information derived from commercial logbooks could be a valuable complement to survey data and could “improve estimates of the distribution and relative abundance of commercial fish species.” They advocated the use of commercial data, particularly given the growing availability of GIS tools to help analyze the large spatial databases provided through logbooks. Thus, they suggested that logbooks could be used to redesign the stratification scheme used for the NMFS triennial trawl survey. Like any data used in stock assessments, however, logbook data are only useful if they are reported accurately and completely for all fishermen, are subjected to appropriate quality control, and are used in the stock assessments with appropriate adjustments and assumptions (Fox and Starr, 1996). However, the extensive data available from West Coast trawl logbooks from the groundfish fisheries is virtually unused in management of these species, so that potential cooperation is not realized. Because the logbooks are mandatory, fishermen maintain them, despite the fact that only a handful of scientists have used the data contained in them.

Furthermore, information gathered and recorded by fishermen in logbooks is sometimes questioned even when it is quantitative in nature. The reason for this is that logbook information can be compromised in at least two ways. First, inaccuracies in reporting may take place with respect to species caught, area fished, and amount caught if such statistics are viewed as intrusive, irrelevant, invasive of proprietary information, or of low priority in the daily operation of the vessel. Even when the information is accurate, it may not be useable as changes in technology, experience, targeting practices, or regulations can all modify catch rates in ways that makes it difficult to track changes in species abundance. For these reasons, stock assessment scientists often feel they must rely solely upon fishery-independent measures of stock abundance (Fox and Starr, 1996; Rose and Kulka, 1999).

Partnerships between the commercial fishing industry and the agencies responsible for scientific research and management can take several forms. Cooperative sampling efforts can involve researchers actually employing commercial vessels and crews to gather data (e.g., Kennelly and Broadhurst, 1996). Use of commercial vessels is most feasible with long-term charter situations or non-trawl fisheries.9

Benefits from improved cooperation accrue not only to managers and scientists but also to commercial fishermen, who may benefit through improved stock assessments, leading to more comprehensive and appropriate management plans and ultimately ensuring the continuation of the fishery that provides their livelihoods (Gallagher, 1987). Hanna and Smith (1993) demonstrated that fishermen supported increased adoption of cooperative fishery management approaches, involving fishermen, processors, and managers, particularly with regard to ensuring “regulations that are compatible with the economic aspects of the fishery.” They also characterized fishermen as concerned with long-term sustainability of the fishery rather than a sole concern with short-term profits (Hanna and Smith, 1993). Such perspectives help justify the effort needed to develop long-term partnerships and cooperation.

Using commercial vessels and crew (in addition to research vessels) can improve data-gathering efforts by providing a crew with important

9  

Trawl fisheries drag a trawl net through the water in such a way that a net, trawl lines, and vessel are an integrated system with a unique acoustic signature and physical action that affect the catch of fish. Fixed gear systems are not integrated with a vessel. Of course, standardized gear is important for both trawl fisheries and fixed-gear fisheries.

Suggested Citation:"General Issues in the Collection, Management, and Use of Fisheries Data." National Research Council. 2000. Improving the Collection, Management, and Use of Marine Fisheries Data. Washington, DC: The National Academies Press. doi: 10.17226/9969.
×

BOX 3-3

New England Council Fisheries Research Program

In the past decade, the U.S. Congress has provided financial support to New England fishermen in several forms, including vessel buyouts, as well as a $5 million appropriation in 1998 and a $21 million appropriation in 1999 for cooperative research between NMFS and industry. The funding is intended to engage commercial fishermen in cooperative research and management as a disaster relief measure. The New England Fishery Management Council, through its new Experimental Fisheries Research Steering Committee, is responsible for reviewing proposals and selecting research that will most appropriately fit the needs of managers. The NMFS regional administrator will make the final decision on what research is funded. Fishermen who receive disaster assistance in payments based on equivalent days at sea will be required (upon request) to contribute an equal amount of time assisting in research. In addition to providing disaster relief and building cooperation, this program resulted from a desire by fishermen and the New England Council to be able to direct some research support to issues they believe are a priority.

local knowledge specific to the sites or species of concern, providing data based on gear similar to what is or will be used in the commercial fishery, and improving confidence in the data among those commercial operators not directly involved in the research because they can observe the commercial research vessel in known fishing areas, using familiar gear (Kennelly and Broadhurst, 1996). Commercial fishermen believe strongly that data provided by commercial fishermen can improve the information on which stock assessments are based, by providing a sample size much larger than can be obtained with standard surveys conducted by dedicated research vessels (J. Easley, Oregon Trawl Commission, personal communication, 1999).

Examples of partnerships among commercial fishermen and research scientists can be found in the United States and other nations. Canada has made considerable strides in forging partnerships between scientists and managers.

Researchers at Oregon State University (funded by NMFS) are currently analyzing the potential for industry-scientist cooperative fisheries research programs (G. Sylvia, Oregon State University, personal communication, 1999). The initial stage of this work included a summary description of fisheries incorporating industry-scientist partnerships for fisheries research, including examples from Australian inland and trawl fisheries, Canadian marine fisheries on the east and west coasts, and a new initiative by the Oregon Department of Fish and Wildlife to begin a cooperative research effort (Sylvia and Harms, undated).

In another example, Northeast Fishery Science Center (NEFSC) scientists completed an at-sea survey in December 1998 as part of the Advanced Fisheries Management Information System (AFMIS), using commercial trawl vessels, paid in part with the scallops they caught. In 1999 the New England Fishery Management Council received new funding for council-identified research carried out with industry (Box 3-3). The Magnuson-Stevens Act allows councils the discretion to develop fishery management plans that “reserve a portion of the allowable biological catch of the fishery for use in scientific research” (Sec. 303[b][1]). Some councils have taken advantage of this provision to engage commercial fishermen in research activities, allowing them to harvest additional fish. The Northwest Fishery Science Cen-

Suggested Citation:"General Issues in the Collection, Management, and Use of Fisheries Data." National Research Council. 2000. Improving the Collection, Management, and Use of Marine Fisheries Data. Washington, DC: The National Academies Press. doi: 10.17226/9969.
×

ter is in its second year of conducting surveys using commercial vessels and paying cooperating commercial fishermen with fish caught.

In Norway, partnerships show potential to lead to improved knowledge about local fish stocks, environmental influences on fish distribution and abundance, and potential implications of alternative management regimes on the fish stocks as well as on local communities (Maurstad and Sundet, 1994).

In Canada, the Department of Fisheries and Oceans (DFO) and the Pacific Blackcod10 Fishermen's Association (PBFA) have established a co-management relationship that, in their own assessment, “has benefited both DFO and the PBFA, and has improved the overall research, assessment, monitoring, enforcement, and management of the fishery” (DFO and PBFA, 1998). PBFA members assist by providing vessels and crew to conduct tagging operations for mark-recapture studies, returning tagged fish through a tag-return incentive program, collecting and synthesizing the data from the tagged fish program, collecting biological samples based on sampling procedures provided to each vessel, and contracting with scientists to conduct both the annual assessments and longer-term research. PBFA has provided “all of the costs directly associated with the research and assessment of the sablefish resource,” including DFO salaries, benefits, and operating expenses. PBFA also coordinates the dockside monitoring program, including reporting compliance problems to enforcement authorities. DFO and PBFA (1998) concluded that “ the additions of dockside monitoring, dedicated enforcement resources, industry funding, and a more responsible attitude by sablefish fishery participants have resulted in improved compliance with the sablefish fishery rules and regulations. This is supported by a study of the sablefish fishery released by DFO's Internal Audit and Evaluation Branch in 1993.” Key to this co-management relationship is clear and frequent communication among all participants.

Also in Canada, the Fishermen and Scientists Research Society (FSRS) operates in the Atlantic region. Since 1994, the society has supported participation of fishermen in the stock assessment process, enhancing the process by making available information that only the fishermen can obtain on a daily basis, and encouraging the participation of fishermen in developing a sound information base to lead to more effective resource management (see http://www.fsrs.ns.ca). Funding originally came through DFO and other government sources, although some funding since that time has derived from contracting out society expertise. Communication among fishermen, scientists, and the general public is an essential part of the mission of the society (King et al., 1994). The society produces a quarterly newsletter —Hook, Line, and Thinker—that is distributed internationally to fishermen, scientists, academics, and others interested in sustainability of fishery resources.

Although the regional fishery management councils established under the Magnuson-Stevens Act were designed to provide a vehicle for cooperation and outreach between NMFS and stakeholders, council activities have sometimes not been successful in this goal.11 The problem may be inherent in the present management structure, the state of regulated fisheries, and regulator-regulated dynamics of conflict, and may be solved only by making “local incentives compatible with global goals” (Ecosystem Principles Advisory Panel, 1999). Greater attention to co-management ideals of involving stakeholders more closely in data collection and decisionmaking may help. The Canadian development of a joint industry-science Fisheries Resource Conservation Council committed to wide consultation and the fullest use of fishery-dependent data could be a pattern for U.S. regional fishery management councils to follow (Box 3-4).

10  

Blackcod and sablefish are interchangeable names for Anoplopoma fimbria.

11  

Center for Marine Conservation, Missing the Boat, www.cmc-ocean.org/missingboat.

Suggested Citation:"General Issues in the Collection, Management, and Use of Fisheries Data." National Research Council. 2000. Improving the Collection, Management, and Use of Marine Fisheries Data. Washington, DC: The National Academies Press. doi: 10.17226/9969.
×

BOX 3-4

Fisheries Resource Conservation Councila

The Minister of Fisheries and Oceans has established the Fisheries Resource Conservation Council as a partnership between government, the scientific community, and the direct stakeholders in the fishery. Its mission is to contribute to the management of the Atlantic fisheries on a “sustainable” basis by ensuring that stock assessments are conducted in a multidisciplinary and integrated fashion and that appropriate methodologies and approaches are employed; by reviewing these assessments together with other relevant information and recommending to the minister total allowable catches (TACs) and other conservation measures, including some idea of the level of risk and uncertainty associated with these recommendations: and by advising on the appropriate priorities for science.

Council Objectives

  • To help the government achieve its conservation, economic, and social objectives for the fishery. The conservation objectives include, but are not restricted to (1) rebuilding stocks to their “optimum ” levels and thereafter maintaining them at or near these levels, subject to natural fluctuations, and with “sufficient” spawning biomass to allow a continuing strong production of young fish; and (2) managing the pattern of fishing over the sizes and ages present in fish stocks and catching fish of optimal size.

  • To develop a more profound understanding of fish-producing ecosystems, including the interrelationships between species and the effects of changes in the marine environment on stocks.

  • To review scientific research, resource assessments, and conservation proposals, including, where appropriate, through a process of public hearings.

  • To ensure that the operational and economic realities of the fishery, in addition to scientific stock assessments, are taken into account in recommending measures to achieve the conservation objectives.

  • To better integrate scientific expertise with the knowledge and experience of all sectors of the industry and thus develop a strong working partnership.

  • To provide a mechanism for public and industry advice and review of stock assessment information.

  • To make public recommendations to the minister.

Activities

  • Review appropriate Department of Fisheries and Oceans science research programs and recommend priorities, objectives, and resource requirements.

  • Consider scientific information—including biology, and physical and chemical oceanography, taking into account fisheries management, fishing practices, economics, and enforcement information.

  • Conduct public hearings wherein scientific information is presented or proposed and conservation measures and options are reviewed and discussed.

  • Recommend TACs and other conservation measures.

  • Prepare a comprehensive, long-term plan and a work plan for the council that are reviewed annually at a workshop with international scientists and appropriate industry representatives.

  • Ensure an open and effective exchange of information with the fishing industry and contribute to a better public understanding of the conservation and management of Canada's fisheries resources.

Suggested Citation:"General Issues in the Collection, Management, and Use of Fisheries Data." National Research Council. 2000. Improving the Collection, Management, and Use of Marine Fisheries Data. Washington, DC: The National Academies Press. doi: 10.17226/9969.
×

O'Boyle et al. (1995) describe joint government-industry surveys in Atlantic Canadian waters, which outnumbered the government surveys there in 1995. New Zealand has an extensive system of data collection and uses an open stock assessment process in which all stakeholders participate; fishermen are increasingly involved in data collection and research (NRC, 1999b).

Palmer and Sinclair (1996) cautioned that cooperative management and research efforts may be difficult to implement because local knowledge and perceptions are rarely uniform. Others have also warned that lack of unity among commercial fishermen and differences in motivation and perceptions can reduce the potential usefulness of partnerships (e.g., Felt, 1994; Jentoft and McCay, 1995). Many of these concerns relate to broad co-management proposals or arrangements, rather than more limited partnerships involving the employment of commercial fishermen and vessels to complement or augment fishery-independent data collected by research vessels. Additionally, differences in perceptions between fishermen and scientists must be overcome. Harms and Sylvia (1999), studying the West Coast groundfish fishery, found that scientists and fishermen share very few opinions about the extent to which NMFS currently encourages industry-scientist cooperation, the strength of a conservation ethic among industry, and the degree of interest among scientists in sustaining a long-term, profitable fishing industry. In that study, majorities of both fishermen and scientists agree that “there is currently very little or no trust between industry and scientists” (Harms and Sylvia, 1999). On the positive side, most scientists and industry respondents agreed that “industry-scientist cooperative research has ‘significant' or ‘moderate' potential for improving the science used in management of groundfish ” (Harms and Sylvia, 1999).

Effects of Existing and Potential Fishery Regulations on the Quality of Fishery-Dependent Data—For many fisheries, harvest capacity grows to the point where it substantially exceeds the maximum sustainable yield of the fish stock. In this case, increasingly stringent regulations are required to keep total catches within acceptable bounds. As regulations decrease fishing opportunities, fishermen's short-term interests may become very different from the long-term interests of fishery managers. This can have profound effects on how fishermen react to existing and future regulations, and may reduce the possibilities for cooperation and co-management discussed earlier. Decreases in fishing opportunities can also have substantial effects on fishery-dependent data, including:

  • strategic bias—regulations can create a strategic bias in unverifiable fisheries data. For example, catch and bycatch may be under-reported or misrepresented in terms of the species, weight caught, or locations fished.

  • increased costs—regulations that require expensive data collection will discourage such collection and create sparse data sets. This is true whether the government or industry is paying.

  • refusal to cooperate.

  • data fouling—different regulatory systems can have unintended effects on the quality of data collected from the fishery. Data fouling can be manifested as increased bias in the size distribution of the catch and in the nominal CPUE due to shortened trips and seasons and changes in fishing practices.

  • regulatory discards—implementation of new management programs, such as trip limits and closed seasons, can increase discards of specific species in a multispecies fishery.

Managers should anticipate such effects when designing new management schemes. Regardless of the way a fishery is regulated, efficient management should achieve the desired effect at the least cost to the individuals being regulated, to the management system itself, and to the remainder of society. When new regulations are developed and implemented, their costs and effectiveness in terms of levels of compliance and whether they are having their intended effect(s) can only be determined through con-

Suggested Citation:"General Issues in the Collection, Management, and Use of Fisheries Data." National Research Council. 2000. Improving the Collection, Management, and Use of Marine Fisheries Data. Washington, DC: The National Academies Press. doi: 10.17226/9969.
×

comitant monitoring of the biological, economic, and social results of the regulations. Monitoring systems should also be able to detect unexpected and unintended effects, which would require supplemental research to determine the cause(s) of such effects.

Cooperation with Recreational Fishermen— Fishery managers and scientists have rarely developed cooperative programs that include marine recreational anglers, largely because this sector is composed of many more individuals than the commercial sector and is more dispersed. These factors make it harder to identify contact points and to coordinate scientifically designed projects. One level of cooperation that does occur is anglers participating in MRFSS and statesponsored surveys. Another occurs when anglers return tagged fish.

Government agencies, private-sector organizations, and scientists have attempted to include anglers in fish-tagging programs. However, the data provided from these programs can be problematic when anglers tag and release fish in an ad hoc fashion, because the value of the tag returns are limited to general patterns of movement (at least for life stages and in areas where anglers fish), and inspiring conservation interests. For example, the non-profit American Littoral Society has a 35-year-old program that now includes approximately 1,200 marine recreational anglers and 95 clubs who buy tagging kits and tag over 30,000 fish each year. Most of the tagged fish are striped bass, but summer flounder and blue-fish are also commonly tagged. About 4% of the tags are returned and data are supplied to the Northeast Fishery Science Center. This tag return rate is on the lower end of the range listed in the literature for scientifically designed tagging studies. For example, tag return rates for tropical tunas range between 2 and 13 percent (Hampton and Gunn, 1998; Kaltongga, 1998; Itano and Holland, 2000). Most summer flounder are recaptured within months of being tagged. The number of tags returned does provide a very rough indication of the fishing mortality, but accurate measures depend on random introductions of tags, measures of tag loss and tagging mortality, and knowledge of reporting rates that are not available from such ad hoc surveys. Many in the academic community doubt the usefulness of tagging programs such as this that are conducted non-systematically.

Tagging studies must be implemented from scientifically-designed procedures to obtain information on the behavior of individual fish, estimate mortality rates, and determine the mixing between two populations of fish. Recent advances in tagging models now allow the estimation of natural and fishing mortality in mixed-use fisheries (see for example Brooks et al., 1998 and Pollock et al., 1991 for creel surveys combined with tagging studies). An important recent example of cooperation of scientists and anglers is the “Tag a Giant” program, in which recreational anglers and charterboat operators are assisting scientists in placing archival, acoustic, and popup (Block et al., 1998) tags on medium and giant Atlantic bluefin tuna. The New England Aquarium is conducting a similar program.

Communication

Data, and the information associated with them, must flow from fishermen to scientists and managers and vice versa for use in stock assessments and for implementation of fishery management actions. What makes communication difficult is the disparity in how data are perceived, the difference in the language used to communicate the issues, and the preconceptions that exist among scientists and fishermen as to the other's motivations for gathering or presenting certain types of data. Even when fishermen, scientists, and managers agree on the data available, they may not understand them in the same way, and they may disagree about interpretations, hypotheses, and implications. This was obvious during the committee's public sessions, as issues were raised by fishermen concerning, for example, exactly how and why NMFS conducted their surveys. Surveys are a natural focus of concern for

Suggested Citation:"General Issues in the Collection, Management, and Use of Fisheries Data." National Research Council. 2000. Improving the Collection, Management, and Use of Marine Fisheries Data. Washington, DC: The National Academies Press. doi: 10.17226/9969.
×

fishermen when they perceive that TACs are lower than justified by their observations of fish populations because a survey is the information component they can most closely relate to their own fishing activities.

NMFS personnel informed the committee that opportunities had been provided for fishermen to participate in surveys, but that these opportunities were seldom used. As discussed previously, co-management arrangements may facilitate better communication, directly and indirectly, through closer ties between agencies and industry. It is difficult to determine what steps would improve communication and change the adversarial relationships that exist between scientists and managers and fishermen and that hinder communication in many U.S. fisheries. Meetings mandated by an agency obviously will not work, but neither will missed industry opportunities to participate in NMFS cruises. Some communication about data collection occurs at council meetings, but the council setting may be inappropriate for the extended presentation and discussion that may be necessary. The most effective communication could involve a coordinated program of meetings, lectures, and demonstrations at sea.

Communicating data gathered from commercial vessels engaged in research can face challenges similar to those of sharing data from survey research vessels. Kennelly and Broadhurst (1996) suggested that photographs, videos, and other visual presentations at meetings or other interactive arenas may be most successful at convincing commercial vessel operators who were not involved directly in the data-gathering efforts. For example, a scallop fisherman participated in a joint U.S.-Canada research trip in the Bay of Fundy during the summer of 1998. The scallop fisherman was taken down in a submersible to look at the bottom he had dragged for scallops and was completely surprised by the deserted appearance of the bottom. The view from underwater did not match his perception while scallop dragging with his own boat (S. Smith, Bedford Institute of Oceanography, personal communication, 1999). In addition, public presentations to concerned stakeholder groups and involvement of both scientists and fishermen in mass media outreach (print, radio, television) are critical to fostering greater public understanding of fishery issues (Kennelly and Broadhurst, 1996). Ticheler et al. (1998) emphasized the essential role of proper communication of data gathered from commercial fishermen back to the larger commercial fishing communities, including associated interpretations by scientists. They suggested that improved information exchange could enhance community awareness about harvest patterns, management implications, and the reasons for management decisions. Kaplan (1998) noted that fishermen have emphasized the importance of timing such information exchanges to coincide with non-fishing hours or seasons to enable fishermen to participate.

Review

NMFS conducts annual and semi-annual reviews of many of its assessments and associated data collection practices (e.g., Stock Assessment Review Committees panels on the East Coast and STock Assessment Review panels on the West Coast). Because of constraints arising from scheduling and financing such reviews, and the scarcity of stock assessment scientists outside NMFS, most participants in these review panels are employed by NMFS. Such reviews provide a useful quality assurance function, can be completed quickly, and can produce high-quality results that are comparable from year to year. Because of the limited number of stock assessment scientists outside NMFS and the large number of stock assessments that must be reviewed, the reality is that NMFS employees will have to form a major part of most regular reviews.

The National Research Council's only previous review of stock assessments in the U.S. north-east region found that the assessments for cod, haddock, and yellowtail flounder used methods accepted worldwide and yielded results that rightly guided the New England Fishery Man-

Suggested Citation:"General Issues in the Collection, Management, and Use of Fisheries Data." National Research Council. 2000. Improving the Collection, Management, and Use of Marine Fisheries Data. Washington, DC: The National Academies Press. doi: 10.17226/9969.
×

agement Council to make conservative management decisions (NRC, 1998b). The committee has no reason to doubt that NMFS scientists are just as capable and professional as academic scientists and that the SARC and STAR panels provide an appropriate means of routine reviews. The committee found no evidence of bias in the summer flounder assessment.

One consequence of reviews that are not conducted by groups of external scientists is that they may inhibit the influx of new ideas into the system and another is that the industry and environmental groups may perceive the assessments as being biased. NMFS itself has recognized this problem in setting up its Center for Independent Experts. Academic institutions and departments recognize the same issue when they occasionally appoint committees of visitors. The key is to make sure that review panels work independently, and are perceived to be giving independent advice. There are ways to do that, such as making the review meetings more open and transparent, with industry participation (under strict rules of engagement) and non-NMFS chairspersons.

The committee could find few examples of truly independent reviews of data collection and stock assessment procedures for U.S. fisheries. Congress asked the NRC to review the assessments of Atlantic bluefin tuna (NRC, 1994a), northeast groundfish (NRC, 1998b), and summer flounder (this study), including various aspects of data collection. The Pacific Council commissioned an independent review of the groundfish assessments (West Coast Groundfish Assessment Review Panel, 1995). Such extensive reviews are typically brought on by concerns that the review system is somehow not operating properly. What is needed are thorough, periodic, independent reviews of assessment and data collection procedures as part of the ongoing data collection and assessment process for each fishery. These reviews do not need to be conducted at each assessment, but periodically, especially when there is a change in methodology or a significant change in the fish population or fishery. Periodic, rather than assessment-by-assessment, reviews could overcome logistical and other constraints. Independence of such reviews might be enhanced if they were conducted under the direction of the regional fishery management councils, perhaps through ad hoc review panels overseen by the scientific and statistical advisory committees to these councils (assuming these committees themselves are made up primarily of scientists outside NMFS).

An alternative could be the Center for Independent Experts, in which NMFS is funding a pilot project at one of its joint institutes (the University of Miami) to put together teams of independent reviewers. The center's steering committee, formed by the University of Miami, selects reviewers, oversees the reviews, and transmits the review results to NMFS. The center has been active since 1998 and has conducted reviews of a number of stock assessments (by individual reviewers) and of the science conducted pursuant to the International Dolphin Protection Act (by a team of three reviewers). It remains to be seen whether the reviews of this type will be acceptable to stakeholders.

Finally, stakeholders should play a more substantial role in the review process than the 30 minutes or so of public testimony currently allowed at assessment and management meetings. Commercial fishermen, recreational fishermen, and other stakeholders need to take the incentive in developing that role. Many successful examples exist of stakeholder involvement in the review process (e.g., the International Pacific Halibut Commission, and New Zealand fisheries management). Stakeholder involvement may require that independent scientists be brought into the process to facilitate communication, although this has not been uniformly successful.

For recreational data, MRFSS provides somewhat more nationwide structure, standardization, and control. MRFSS has had extensive review by the scientific and statistical communities (Hayne, 1977; Jones et al., 1990; Bolstein, 1992, 1993; Osborn and Lazauski, 1995), although many of the recommendations of earlier reviews have not been implemented.

Suggested Citation:"General Issues in the Collection, Management, and Use of Fisheries Data." National Research Council. 2000. Improving the Collection, Management, and Use of Marine Fisheries Data. Washington, DC: The National Academies Press. doi: 10.17226/9969.
×

DATA MANAGEMENT

Confidentiality

Fishery management agencies, both state and federal, usually have procedures to ensure data confidentiality. NOAA Administrative Order 216-100, dated July 16, 1994, defines the conditions under which information collected by NMFS may be shared with others. Confidential data are defined as data identifiable with any individual, corporation, or other entity. In other words, if the identity of the fisherman or processor can be determined from the data, the data are confidential and cannot be shared without permission from the fisherman or processor. If the identity of the fisherman or processor can be obscured by aggregation into strata by time or space or both, the data are not confidential and can be shared. There is no sunset clause on data confidentiality; data are confidential in perpetuity. These constraints make it illegal to share data under some circumstances even with a scientific and statistical committee (SSC) of a regional fishery management council. In the case of summer flounder, the number of fishermen or processors in some states is so small (e.g., Delaware and Maryland) that landings by state cannot be made public in some years. Confidentiality provisions can hinder development of models of how management measures work, except on a very large scale.

Institutional Arrangements for Data Management

Fisheries data management systems are maintained at state, regional, federal, and international levels. Additional systems are under development, including at least one research system. The following section describes the range of existing and incipient systems.

Federal Data Sources

NMFS collects a variety of data needed for stock assessments and other fishery management purposes, as described in the first part of this chapter. NMFS has the primary responsibility for collecting biological, social, and economic data to monitor activities in the U.S. exclusive economic zone. The U.S. Coast Guard also provides data related to enforcement activities; such information can be useful in evaluating the effectiveness of different management approaches. The federal government is responsible for gathering data from states, interstate commissions, and international commissions, as needed, for federal fisheries management activities.

The federal government pays for most of the data collection and management needed for its uses, whether done directly or through the commissions or states. Decentralized data collection activities create extra requirements for coordination and quality control. Ensuring that the data needed are available and accurate can be difficult when NMFS can exert only limited control over collection, standardization, and quality control.

States

Coastal states generally have fisheries management responsibilities within state waters (up to 3 nautical miles from shore in most states; up to 9 miles in Texas, the west coast of Florida, and Puerto Rico; and in bays and estuaries). States issue commercial fishing licenses and may require marine recreational fishing licenses. States are also responsible for regulating ports and for maintaining environmental quality in state waters. Some states maintain hatchery programs for fish and shellfish to enhance natural stocks. States must collect their data and have access to data from adjacent states and NMFS. However, states may conduct their fishery surveys in different ways and for different purposes. Many types of statefederal cooperation in data collection and fisheries management can be found around the United States, including sole state involvement in nearshore species (e.g., sea trout and mullet), state management of federal fisheries in adjacent federal waters (e.g., spiny lobster in Florida), and federal management of fisheries that cross state-fed-

Suggested Citation:"General Issues in the Collection, Management, and Use of Fisheries Data." National Research Council. 2000. Improving the Collection, Management, and Use of Marine Fisheries Data. Washington, DC: The National Academies Press. doi: 10.17226/9969.
×

eral boundaries (e.g., shrimp in the Gulf of Mexico).

Interstate Commissions

Since fish stocks don't respect political boundaries, states need a mechanism to coordinate the collection of data and to manage stocks shared among states and among regional councils. This need became particularly apparent at the time of the decline of the striped bass stocks in the mid-Atlantic region in the 1980s, which led to the Interjurisdictional Fisheries Act of 1986. The three interstate commissions play a major role in coordinating management and use of data from individual states.

International Commissions

The United States participates in several binational and multinational commissions that manage fish stocks that span the national waters of two or more nations or extend into international waters. Examples of international commissions include the International Pacific Halibut Commission and Inter-American Tropical Tuna Commission in the Pacific region and the International Commission for the Conservation of Atlantic Tunas. Most commissions combine data collected from national fishery agencies with data they collect themselves. NMFS and the councils must obtain data from the commissions for fisheries under U.S. jurisdiction. Management may be joint with commissions, councils, and NMFS (e.g., for North Pacific halibut).

Fisheries Data Management Systems

As fisheries data have become more voluminous and complex, fisheries data management systems have been developed. State-federal collaborative data management efforts were started as early as the 1970s and 1980s, for example, the state-federal cooperative statistics program in the southeast and Gulf of Mexico and the Northeast Marine Fisheries Information System. Systems today include the Alaska Fisheries Information Network (AKFIN) and the Pacific Fisheries Information Network (PacFIN) for the Pacific Coast States, FIN in the Gulf of Mexico, and most recently, the Atlantic Cooperative Coastal Statistics Program (ACCSP). A nationwide umbrella Fisheries Information System (FIS) has been proposed.

PacFIN (Daspit et al., 1997) and AKFIN—Commercial data from fisheries in the ocean areas off Washington, Oregon, and California submitted by state fishery agencies are central to the PacFIN database. The states are primarily responsible for data quality control. PacFIN also includes limited Alaska groundfish information, which is supplied in aggregate form. The PSMFC sponsors AKFIN to provide the “framework needed to consolidate collection, processing, analysis and reporting of a variety of information essential to management of Alaska fisheries” (NMFS, undated). AKFIN system partners are coordinating the development of data element standards and coding systems in concert with other Pacific area fisheries data. Thus, AKFIN is adopting the PacFIN code sets with some modifications to accommodate unique Alaskan requirements. Currently AKFIN data reports are available through PacFIN.

PacFIN includes a publicly accessible Web site with summary reports and a restricted access site accessible by dial-up or telnet. The PacFIN restricted area is run on a system named ack1 (formerly ORCA). The initial setup requires new users to enter Unix commands to complete setup of the environment. This procedure might be difficult for new users with no Unix experience. Using the ack1 database requires some knowledge of Structured Query Language (SQL).12 However, over 4,000 scripts are available to users on the system that can be used to generate a number of different reports. On-line help is available for both Unix and SQL. Additionally, staff members offer support to those who need help mastering ack1's command line interface.

12  

Structured Query Language (SQL) provides basic language constructs for querying and processing data in a relational database. SQL is a standard of both the International Organization for Standardization and the American National Standards Institute. Over time, SQL has evolved to provide additional facilities such as those for schema manipulation and data administration and language for the definition and management of persistent, complex objects.

Suggested Citation:"General Issues in the Collection, Management, and Use of Fisheries Data." National Research Council. 2000. Improving the Collection, Management, and Use of Marine Fisheries Data. Washington, DC: The National Academies Press. doi: 10.17226/9969.
×

Ack1 includes tables that contain summary data; therefore, users writing their own queries rather than using scripts must take care to ensure that they are not capturing both the detail and the summarized data in custom reports. Summary data were initially included to avoid dealing with the complex issue of confidentiality. As the database evolved, finer detail levels were included, but some data providers, such as the State of Alaska, provide only summary data for inclusion in PacFIN. The SGI server that supports PacFIN was replaced by a new Sun Microsystems server, ofis450a, on December 6, 1999. The primary applications on the new server will be Oracle 8i, SPSS, SPLUS, IMSL, and FORTRAN software libraries. Also included are linkages to applications such as Oracle/ArcInfo/ Arcview and Oracle/SAS.

FIN—The Fisheries Information Network (FIN) is a state-federal cooperative program to collect, manage, and disseminate statistical data and information on the commercial and recreational fisheries of the southeast region, including the Gulf of Mexico. FIN encompasses two separate programs: the Commercial Fisheries Information Network (ComFIN) and the Recreational Fisheries Information Network (RecFIN-SE). FIN came into being as a result of a memorandum of understanding signed in 1996 that resulted from efforts by state and federal agencies to develop a cooperative program for the collection and management of commercial and recreational fisheries data in the southeast region. GSMFC (1996) indicates that the ComFIN and RecFIN-SE are comprehensive programs comprised of coordinated data collection activities, an integrated data management and retrieval system, and procedures for information dissemination, as outlined in the mission, goals, and objectives of its Framework Plan. Databases to be included are the MRFSS files, the NMFS trip interview program (TIP) files (which primarily hold biological data on catch from commercial fishing trips but also include length-frequency data from recreational trips), the NMFS headboat survey, and a variety of state and federal databases.

In his June 1999 presentation to the committee, David Donaldson of the Gulf States Marine Fisheries Commission told the committee that only Louisiana and Florida have put in place the trip ticket programs needed to implement ComFIN, and that trip ticket programs are still needed in Texas, Mississippi, and Alabama. The FIN Committee emphasizes in its framework document how communication with the Pacific and Atlantic coasts will also be established and maintained to coordinate with and benefit from their data management efforts and to ensure compatibility with a planned national commercial and recreational fisheries database system (GSMFC, 1996). The Framework Plan mentions the need to develop standard protocols and documentation, including quality assurance and quality control standards for data formats, data element definitions, input, editing storage, access, transfer, dissemination, and applications.

ACCSP—The Atlantic Coastal Cooperative Statistics Program is a “cooperative state-federal marine and coastal fisheries data collection program. It is intended to coordinate present and future marine and coastal data collection and data management activities through cooperative planning, innovative uses of statistical theory and design, and consolidation of appropriate data into a useful database system.”13 Planners believe that the program must serve not only the needs of fishery scientists and managers but also fishermen, fishing companies, and the public. The program is based on the assumptions that (1) the migratory nature and transboundary distribution of many Atlantic coastal stocks require coastwide cooperation in management, and (2) good data and statistics are needed for effective management. Toward this end, ASSCP plans include elements related to (1) collection, management, and dissemination of statistical data and information for the conservation and management of fishery resources of the Atlantic coast in a cooperative manner, and (2) support of the continued development and operation of a national data collection and data management program.

Suggested Citation:"General Issues in the Collection, Management, and Use of Fisheries Data." National Research Council. 2000. Improving the Collection, Management, and Use of Marine Fisheries Data. Washington, DC: The National Academies Press. doi: 10.17226/9969.
×

Mike Cahall, Information Systems Program Manager for the ACCSP, indicates that the ACCSP is built “according to the best commercial practice ” rather than emphasizing federal or other standards. However, many vendors incorporate Federal Information Processing Standards (FIPS) and other federal data standards in their products. If the ACCSP does not adhere to federal data standards, it should not serve as a model for a federally funded national data collection and data management program for marine fisheries. OMB Circular A-130 Section 8b(4) requires that “Federal agency management and technical frameworks for information resources should address agency strategies to move toward an open systems environment.” Standardizing data formats is one aspect of creating an open-systems environment, rather than a proprietary, non-accessible, and non-standardized environment. The commercial approach has not precluded the use of some FIPS, such as the codes for state and county. The program has standardized on the emerging Integrated Taxonomic Information System (ITIS) to provide scientifically credible taxonomic information.14

The ACCSP is testing its system concept through its Prototype Data System, which began with multiple years of data from the NMFS Northeast Region and 1 year of data from the Florida Department of Environmental Protection. The program initially is focusing on fishery-dependent data, both commercial and recreational, but will eventually include fishery-independent data. Recreational catch and effort data were available beginning in December 1999. A proposed cornerstone of the program will be an ability to track individual vessels through time and space. This vessel information could be linked with biological, social, and economic information, and joined with catch and landings data to provide trip summary information for each fishing vessel. ACCSP will limit access to unaggregated data to specific “named users ” who are members of the ACCSP partner organizations. “Unnamed users” from the general public and non-partner organizations will be limited to viewing highly aggregated, non-confidential data. Although no definite date is available, the ACCSP system is likely to be available to users in a preproduction mode between October 2000 and January 2001 (M. Cahall, NMFS, personal communication, 1999).

The ACCSP prototype architecture consists of three layers: the operational layer, the reconciled data layer, and the information layer. A data reconciliation component and a data derivation component are the bridges between the layers (ACCSP, 1997). The operational layer consists of the disparate systems maintained by the partners that provide data for the system. The data reconciliation component includes those processes that are necessary to transform the data from the source operational system into a consistent base in the reconciled data layer. The reconciled data layer is the standardized or common data repository. This layer is derived from the minimum critical data elements and associated standards required by the system. The data derivation component consists of processes required to derive the data from the reconciled data layer to the information layer. The information layer consists of the information repository and data

14  

ITIS is a taxonomic database for terrestrial and aquatic plants and animals developed through a partnership of federal agencies and systematists from government and the private sector. This database is a partnership of U.S., Canadian, and Mexican agencies, other organizations, and taxonomic specialists to develop an online, scientifically credible, list of biological names for the biota of North America. ITIS is also a member of Species 2000, an international project to index the world's known species.

Suggested Citation:"General Issues in the Collection, Management, and Use of Fisheries Data." National Research Council. 2000. Improving the Collection, Management, and Use of Marine Fisheries Data. Washington, DC: The National Academies Press. doi: 10.17226/9969.
×

manipulation tools that support end-user data access and analysis.

The conceptual architecture provides an effective representation of the planned system. According to the documentation, the components described above can be addressed in terms of views of the architecture, such as the data view, the tools view, the hardware and communications view, and the administrative and operational view. As presented in the otherwise comprehensive planning documentation, none of these views specify the federal, national, or international standards with which the system will or should comply. Although the program is a regional and not a federal system, providing information on standards would promote a better understanding of the system and aid those hoping to use it as a model, or to interface with it.

Fisheries Information System—In the Sustainable Fisheries Act of 1996, Congress requested that the Secretary of Commerce “develop recommendations for implementation of a standardized fishing vessel registration and information management system on a regional basis.” (SFA, Sec. 401). The act further specified that the recommendations should “integrate information collection programs under existing fishery management plans into a non-duplicate information collection and management system” (Sec. 401[a][2]); that the recommendations should be implementable through cooperative agreements with state, regional, and tribal entities; and that it should “establish standardized units of measurement, nomenclature, and formats for the collection and submission of information” (Sec. 401[a][6]).

The NMFS response to this congressional mandate (NMFS, undated15) recommends that the Fisheries Information System (FIS) create a nationwide umbrella for ongoing regional activities such as ACCSP, FIN, and PacFIN. Furthermore, the Vessel Registration System (VRS) would be implemented as the Vessel Information System being developed by the U.S. Coast Guard that provides a system for national registration of commercial and charter vessels. Access to the data would be controlled to balance ease of access and confidentiality. Use of common codes or bridges among coding systems was recommended. The combined system would associate individual vessels with a record of their fishing activity and would cost an estimated $51.9 million, 80 percent of which would recur annually. This funding would be applied in three major areas: data collection ($43.9 million), information technology and architecture ($7.2 million), and institutional arrangements ($1.65 million). The recurring cost related to information technology and architecture includes networking and infrastructure costs (routine upgrades of hardware and software), data quality assurance and quality control, technology and electronic reporting, and database integration and harmonization (which includes archiving and integration of “ a regional detail/central summary” VRS-FIS) in excess of existing activities.

NMFS emphasizes the “umbrella concept of building links among existing regional statistics systems,” rather than creating an entirely new national system. In building the links, the FIS would reconcile data across the regional repositories into interregional and nationwide summary information. Instead of presenting a detailed architecture at this very early conceptual period, NMFS provided a very high-level summary of plans to indicate that “a nationwide view of summary-level data implemented in regional data ‘warehouses' is the likely model for a nationwide FIS” (NMFS, undated). Rather than describe interfaces and specific standards that are not yet available in this conceptual level document, NMFS emphasizes that the FIS will provide a single, complete view of the data, providing consistency by eliminating regional data differences, and providing data to users in a consistent, understandable way. The FIS conceptual model presents the information flows, along with sources, systems, and repositories at the state, regional, and national levels.

15  

This report will be referred to as the VRS-FIS document.

Suggested Citation:"General Issues in the Collection, Management, and Use of Fisheries Data." National Research Council. 2000. Improving the Collection, Management, and Use of Marine Fisheries Data. Washington, DC: The National Academies Press. doi: 10.17226/9969.
×

AFMIS/LOOPS/AOSN—The Advanced Fishery Management Information System, a consortium of investigators from the University of Massachusetts, Harvard University, and a private corporation, has obtained funding from NASA for a research project to develop a prototype fisheries management information system that incorporates physical, biological, and fisheries data.16 Fishery managers are responsible for setting regulations governing where and when fishing can occur and the types of gear that can be used to fish for different species. The goal of the AFMIS is to construct, validate, and demonstrate a prototype system that will apply state-of-the-art technology and expertise from multiple disciplines to help fishery managers improve the allocation of fishing effort in time and space. This system also will be used in attempts to understand how environmental factors affect the distribution of fish and influence recruitment of young fish. Major system features are the involvement of the fishing industry in data collection and research and the inclusion of a fishing vessel subsystem. The system uses satellite-borne sensors (sea-surface temperature and ocean color) and will synthesize and analyze previously unanalyzed, novel, very large data sets with modern statistical techniques. The system will cover the Atlantic shelf off the New England states.

The Littoral Ocean Observing and Prediction System (LOOPS) and Autonomous Oceanographic Sampling Network (AOSN) are funded by the Office of Naval Research and are coordinating with AFMIS. The LOOPS concept links models, observational networks, and data assimilation algorithms. LOOPS activities include (1) development of a modular structural concept for linking models and measurements through data assimilation, 17 using adaptive sampling; (2) observational system simulation experiments for the design of quantitative sampling strategies; and (3) sea trials to demonstrate the concepts of system integration and real-time implementation. The AOSN couples autonomous underwater vehicles with moorings and existing remote sensors monitor the ocean, using acoustic and other means.

Commercial and Cooperative Data Management

New sources of data management services are companies that specialize in collecting voluntary data from fishing fleets and the rapid processing and distribution of NMFS data for specific purposes. In some cases, individual vessels waive their confidentiality rights to provide data to and use data from other vessels in their fishery cooperative or their fleet. These systems emphasize direct fisherman contact with the commercial data manager and illustrate the kind of services NMFS could provide if it had the flexibility and resources to do so.

The committee was provided several examples of commercial data management from the North Pacific region (Dave Fraser, commercial fisherman, personal communication, 1999). The first example is SeaState,18 which provides two primary services to the North Pacific catchers and processors: (1) real-time monitoring of catch and bycatch quotas and (2) provision of bycatch hotspot maps based on GIS (Figure 3-4). SeaState obtains its data directly from observers or indirectly through NMFS. These data are used by the general fleet, members of fishery cooperatives, and vessels engaged in the community development quota fisheries. For the latter fisheries, access to data is available through password-protected Web sites.

The Alaska Groundfish Data Bank (AGDB) provides a variety of services to fishing fleets operating in the Gulf of Alaska, ranging from analyzing and disseminating NMFS data to coor-

16  

http://afmis.cmast.umassd.edu, accessed 3/3/00.

17  

Data assimilation is the use of actual measurements of model parameters to constrain the range of input parameters in a model.

18  

The committee and the NRC do not necessarily endorse the companies mentioned in this section.

Suggested Citation:"General Issues in the Collection, Management, and Use of Fisheries Data." National Research Council. 2000. Improving the Collection, Management, and Use of Marine Fisheries Data. Washington, DC: The National Academies Press. doi: 10.17226/9969.
×

FIGURE 3-4 Example of SeaState product for halibut bycatch in southern Bering Sea yellowfin sole and cod fisheries. Used with permission from SeaState, Inc.

dinating the flow of information from harvesters and processors to NMFS. The AGDB works mostly with smaller catcher vessels (less than 125 feet in length) and monitors catches delivered to processors in Kodiak, Alaska. It also works with NMFS to set closure dates and with the fleet to advise fishery managers about trip limits. The AGDB serves as a conduit of information between fishery biologists and the fleet.

A final example from the North Pacific region is Fisheries Information Services, which provides bycatch hotspot reports, based on observer data, to the freezer longliner fleet. Fisheries Information Services is also involved in a logbook program for the Alaskan sablefish individual fishing quota fishery. Other companies provide software to help fishermen manage their own data and remote sensing products to target their fishing activities.

Data Quality Control Procedures

The slogan appearing on the cover of the ACCSP outreach brochure is “Good Data, Good Decisions For Fisheries Management.” This slogan epitomizes the need for good data quality for fisheries management and emphasizes that uncertainties in fisheries data—and the assessments for which they are used—make it difficult to balance the needs of fishermen with the conservation requirements of the resource (ACCSP, undated a).

The “Glossary of Quality Assurance Terms”19 defines data quality indicators as “quantitative statistics and qualitative descriptors that are used to interpret the degree of acceptability or utility of data to the user.” The principal data quality indicators are bias, precision, accuracy, comparability, completeness, and representativeness (EPA, undated). A number of data management systems at regional and national levels have grappled with the issues surrounding maintenance of sufficient data quality to allow effective management.

19  

Developed by the Quality Assurance Management Staff (QAMS) in the Office of Modeling, Monitoring Systems, and Quality Assurance in the EPA's Office of Research and Development.

Suggested Citation:"General Issues in the Collection, Management, and Use of Fisheries Data." National Research Council. 2000. Improving the Collection, Management, and Use of Marine Fisheries Data. Washington, DC: The National Academies Press. doi: 10.17226/9969.
×

BOX 3-5

Data Exchange Standards

CORBA - Common Object Request Broker Architecture is a standard from the Object Management Group (OMG) for communicating between distributed objects. CORBA provides a way to execute programs written in any language without regard to network location or platform.

HTML - HyperText Markup Language is a document format used on the World Wide Web. HTML is a document type of Standard Generalized Markup Language (SGML) that uses fixed tags to describe pages. SGML is a standard of the International Organization for Standardization (ISO) for defining the format in a document. More information on SGML can be found at: http://www.oasis-open.org/cover/sgml-xml.html.

XML - Extensible Markup Language is a subset of SGML used on the World Wide Web that provides flexibility by defining the codes used in each document. More information on XML can be found at: http://www.oasis-open.org/cover/sgml-xml.html.

HTTP - HyperText Transport Protocol is the communications protocol used to connect to servers on the World Wide Web.

TCP/IP - The Transmission Control Protocol/Internet Protocol is the protocol suite used by the Internet. TCP/IP handles network communications between network nodes.

Z39.50 is ANSI Z39.50 (also ISO 10161/62) which is a standard for information retrieval that provides a standard means for a search application to submit a query to databases without regard to the kind of hardware or software the database uses.

Standards for Exchanging Data

Although some consider the World Wide Web to be the answer to all data exchange concerns, an examination of existing fisheries data management systems highlights the continuing need to address standards for exchanging data and information. Internet computing is based on universal standards, but these standards still fall short in certain areas. Data held in disparate distributed databases must be integrated to facilitate single-search access and retrieval. Concerns linger regarding security, privacy, recall, and precision of retrieval methods. Groups such as the Open GIS Consortium are just beginning to address access to Web-based geospatial information. Important data exchange standards are defined in Box 3-5.

In its VRS-FIS document, NMFS (undated) recommends establishment of a temporary liaison office in OMB to facilitate reviews and approvals of collection of the additional federally sponsored information needed to implement the VRS and FIS. The VRS-FIS is planned as a partnership of states, interstate marine fisheries com-

Suggested Citation:"General Issues in the Collection, Management, and Use of Fisheries Data." National Research Council. 2000. Improving the Collection, Management, and Use of Marine Fisheries Data. Washington, DC: The National Academies Press. doi: 10.17226/9969.
×

missions, and federal agencies, including NMFS. The latter intends the FIS to complement existing data collection and management planning efforts by “providing a common thread among programs to take advantage of opportunities in technology, economies of scale, and efficiencies in re-use of survey and information management experiences, and to develop a context for assessing how to pay for these activities. ” (NMFS, undated).

Legal Requirements—The Paperwork Reduction Act and other federal laws, regulations, policies, and guidance are important considerations in choosing data standards. For example, Federal Information Processing Standards (FIPS),20 Records Act provisions, the Clinger-Cohen Act, General Services Administration (GSA) regulations, and OMB Circular A-130 and other OMB guidance and memorandums may prove helpful to developers of fisheries data management systems. The regional information systems discussed earlier that are expected to participate in the FIS addressed the Privacy Act provisions and the Magnuson-Stevens Act confidentiality regulations codified at 50 CFR part 600. It is not clear how the FIS plans to provide information technology access for persons with disabilities as required by 41 CFR 201-20, 103-7. In addition, the U.S. Access Board, the federal agency set up to implement the Americans with Disabilities Act, has recently completed a set of standards for access to government Web sites.

OMB Circular A-130 Section 8b(4) instructs agencies to use strategies that consist of “one or more profiles (an internally consistent set of standards), based on the current version of the NIST's (National Institute of Standards and Technology's) Application Portability Profile. These profiles should satisfy user requirements, accommodate officially recognized or de facto standards, and promote interoperability, application portability, and scalability by choosing interfaces that are broadly accepted in the marketplace to allow for as many suppliers as possible over the long term.”

Software Compatibility—Daspit et al. (1997) stated that in May 1992, NMFS announced that all of its computing resources would be replaced by the UNIX operating system and the Oracle relational database management system. An example of an implementation of this standard is PacFIN's use of Silicon Graphics workstations running IRIX, a version of the UNIX operating system, along with Oracle 7 Server Release 7.3.3.5.0. The ACCSP currently under development complies with the above organizational standard by including Oracle as the backend with Businessobjects Webintelligence software providing the front-end user interface and query capabilities (M. Cahall, NMFS, personal communication, 1999).

Development of organizational standards (e.g., the core set of data elements, standardized data quality assurance and quality control procedures, coding standards, and metadata) and earlier standardization on the proprietary Oracle relational database management system facilitate data interchange within NMFS. However, caution is in order when standardizing on proprietary systems rather than on open standards that facilitate interchangeability among products. For example, Oracle 7.x SQL conforms to the first or entry level of SQL-92 rather than the intermediate or full level. Entry level SQL-92 is similar to SQL-89 to which Oracle has added enhancements or extensions (Harrison, 1997). These noncompliant enhancements make migration to a competing vendor's SQL-compliant database management system more difficult. When a proprietary product is used, the organization often becomes locked into the single vendor 's products. The vendor is then under little pressure to reduce cost or improve and differentiate the product. The single vendor approach also limits systems design flexibility because the user of the proprietary product must

20  

The FIPS Program was established in the 1960s to standardize federal computer usage for federal agencies and organizations.

Suggested Citation:"General Issues in the Collection, Management, and Use of Fisheries Data." National Research Council. 2000. Improving the Collection, Management, and Use of Marine Fisheries Data. Washington, DC: The National Academies Press. doi: 10.17226/9969.
×

wait until the vendor is willing to provide the new products that the customer needs. The latest version of Oracle (8i) includes both proprietary SQL features and somewhat greater open systems support than in previous versions. The open systems approach achieves interoperability by defining interfaces, services, protocols, and data formats favoring the use of non-proprietary specifications (OMB Circular A-130). Whether Oracle represents the best commercial practice of today, users who may someday wish to change vendors must deal with migration to a new system that will not support Oracle's proprietary SQL enhancements. Such migration issues are best handled by advance planning.

Compliance with Interagency Data Standards— NMFS summarized for the committee the status of its standards of compliance by saying that “due to historical regional and programmatic autonomy, NMFS and its partners do not have a single, national, integrated system or standard for data collection.” At the same time, NMFS acknowledges in the FVR-FIS document the need for coordination in the design of data collection forms, quality assurance and quality control, coding standards, and metadata. NMFS is participating in the NOAA Biodata Working Group to ensure that all NOAA staff members document data sets, make them available, and ensure that the data are available for use in the future according to the National Archives and Records Administration's requirements for archiving data (G. Barton, NOAA, personal communication, 1999).

To implement a national FIS, NMFS will provide the extensive coordination necessary to define and implement organizational standards. Since the FIS is at the conceptual stage of development, NMFS has an opportunity now to expand its current plans for developing national standards for certain data elements or coding systems to include development of an architectural framework for interoperability among fisheries data management systems. In fact, the ClingerCohen Act of 1996 instructs federal agency chief information officers to take responsibility for developing, maintaining, and facilitating the implementation of a sound and integrated information technology architecture (ITA). An ITA is an integrated framework for evolving and maintaining existing and new information technology to achieve an agency's strategic goals and information management goals.

A great deal of effort must still be expended to complete the critical task of translating incompatible data formats now used by the regional systems to allow the level of interoperability necessary for the proposed FIS umbrella system. The ACCSP's use of standardized nomenclature provided by the Integrated Taxonomic Information System (ITIS) is an example of using an emerging standard to help ensure successful biological data discovery and retrieval.

Documentation of how data were collected and analyzed (metadata) provides a way to understand data sets. Formal metadata standards employ a controlled or common set of terms to use when describing data. Metadata standards of potential importance to fisheries include the Federal Geophysical Data Committee (FGDC) standard implemented by the National Geospatial Data Clearinghouse and the National Biological Information Infrastructure (NBII) biological profile of the FGDC 's content standards for digital geospatial metadata.

The NBII biological profile includes fields for analytical tools and methodologies. It also includes a supplemental information data element in the FGDC format for input of additional relevant information. Inclusion of information supporting the robustness of the data, such as the following, could be made available through supplying metadata along with fisheries data sets to promote understanding of the data and how it should be used: methodologies used; how much information has been directly measured as opposed to inferred, extrapolated, or produced by models; and level of uncertainty (do all included parameters hold true?), assumptions made, and uncontrolled variables. If estimates of uncertainty are incorporated directly into the assessment, this should be explained in the metadata.

Suggested Citation:"General Issues in the Collection, Management, and Use of Fisheries Data." National Research Council. 2000. Improving the Collection, Management, and Use of Marine Fisheries Data. Washington, DC: The National Academies Press. doi: 10.17226/9969.
×

The biological profile also includes a taxonomy data element that would be of particular use to biological data sets, such as fisheries data. More complete metadata would also facilitate peer review of the data and results and foster better quality control.

The U.S. Fish and Wildlife Service has developed a process for identifying, defining, monitoring, and promoting data standards to ensure the compatibility of data management and usage throughout the agency. The standards and the process for their development are described at http://www.fws.gov/stand/.

Information Management Architecture—Although the documents that describe existing and planned regional fisheries data management systems address many issues of great importance to information sharing, they need to expand on their description and justification of information management architecture. For the most part, the planning documents for fisheries data management provide comprehensive discussions of information system organization and policy and emphasize data collection and data element standards, but could benefit greatly from more detailed computational information, particularly on the topic of compliance with open-system standards. For example, the Reference Model of Open Distributed Processing (RM-ODP) ISO/IEC 10746 models an architectural hierarchy of viewpoints that is being used by the U.S. Geological Survey, NASA, NOAA, and other participants in the interagency Digital Earth Project to serve as a guide for project participants. The technology viewpoint is defined as the specific collection of technology products implemented in the system. The Digital Earth Reference Model provides a listing of interoperability standards by infrastructure category. Emphasis is placed on identifying relevant federal, national, and international standards rather than on defining proprietary products or organizational standard products that must be used by participants. As a final step, the organization identifies the specific technologies that can be used to meet the standards. For example, the FIS designers could decide at this time that they require only SQL-92 level-1 compliance, so that Oracle would be a viable technology choice to fit the fisheries information system architecture. Vendors other than Oracle, however, may meet the required standard. In fact, in its VRS-FIS document, NMFS (undated) indicates that a process will be designed to identify and evaluate candidate technologies according to specific criteria.

The Raines Rules (OMB Memorandum 9702) indicate that agencies must report how well they developed information architectures and evaluated prototypes. Executive Order 12906, issued in 1994, established in the Executive Branch of the federal government a National Spatial Data Infrastructure (NSDI) and a National Geospatial Data Clearinghouse. This executive order directed the FGDC to develop standards for implementing the NSDI and directed individual agencies to use such standards or require their use by entities from which they obtain data. The executive order also directed the FGDC to submit a plan for implementing a national digital geospatial data framework.

Earlier in this section, the statistical aspects of data quality were discussed. The following section describes the approaches to quality control used by planned and existing fishery data management systems.

PacFIN

The content of each PacFIN data file is the responsibility of the agency that provides the data; thus, the current PacFIN system does not include comprehensive validation routines, though some data validation routines are in place. An example of a current PacFIN validation routine is the standard duplicate check. If a transaction is a duplicate or includes out-of-range values, it is flagged as an error and rejected (B. Stenberg, PSMFC, personal communication, 1999).

Sampson and Crone (1997) documented data collection procedures for U.S. Pacific Coast groundfish. Some data are subjected to rigorous

Suggested Citation:"General Issues in the Collection, Management, and Use of Fisheries Data." National Research Council. 2000. Improving the Collection, Management, and Use of Marine Fisheries Data. Washington, DC: The National Academies Press. doi: 10.17226/9969.
×

quality control before submission to PacFIN. The groundfish trawl logbooks used in Washington, Oregon, and California provide examples of the data quality procedures followed before transmission to and entry into PacFIN (Tagart, 1997). The trawl logbooks in Washington State typically are collected by the port sampler each time a fisherman completes a trip. The port sampler records the logbook data to disk with the aid of custom software that conducts cursory error checking. Coded logbook data are then sent to the state Marine Resources Division, where the data are stored and transmitted to a data specialist, who ensures that individual files are filtered through a comprehensive error-checking program, after which they are considered to be processed data. An errorscreening program checks raw logbook data for out-of-range errors in Loran or GPS coordinates, depth, fishing block, species, port, and trip type. It also screens for such errors as tow information entered in the wrong column and missing data. Records with errors are flagged in the database and a separate file is generated that describes the type of error and records the data line in the raw trawl data file in which the error occurred. The data specialist then rectifies the error by reviewing the raw data or returns the coded data to the port sampler for clarification. This procedure results in more than 95 percent of the logbooks being free of coding errors after two passes through the errorscreening program (Sampson and Crone, 1997). Processed data are then aggregated into a single file and further processed into tow-expanded logbook data to account for tows that were not keypunched.21 Tow-expanded data are next processed with fish ticket data to generate expanded trawl logbook data.

Different error-checking protocols are implemented in Oregon and California, with no single standard. Oregon accepts incomplete logbooks, but codes them with a number indicating their incomplete status. According to Sampson and Crone (1997), the Oregon local port biologist “evaluates every logbook for completeness and consistency. The process includes checking the logbook for incorrect temporal sequencing of the tows or inappropriate dates or times, and filling in the following items: (1) the ticket number(s) corresponding to each trip, (2) missing depths based on the tow location and the depths indicated on the nautical charts, and (3) missing target species based on the most prevalent species hailed. The port biologist assigns each logbook a code of 1, 2, or 3, depending on its degree of completeness.” Sampson and Crone report that the port biologist will attempt to obtain missing information by interviewing the captain (the logbook has only partial information on the tow location or hail weights).22 If the captain does not provide the missing information, the port biologist will assign the logbook a code 2 if only hail weights are missing, or a code 3 if tow locations are missing. Logbooks assigned a code 3 are excluded from further processing (Sampson and Crone, 1997).

ACCSP

The ACCSP database planning document notes that data should be checked for accuracy and consistency before being submitted to the coastwide database. The data form review re-

21  

According to Sampson and Crone (1997), Washington State did not record tow-by-tow logbook data until 1985. Originally, they keypunched every fourth tow from each logged trip, in effect subsampling tow-by-tow data. Thus, their system accommodates subsampling and provides for data expansion for subsampled trips, for example, the tows that were not keypunched.

22  

The hail weight is an estimate by fishermen of either tow-by-tow landings (entered into the logbook), or of the total weight the fishermen tells the fish buyer he has on the boat as he returns from a fishing trip. When the fish are subsequently weighed, this “landed weight ” is usually used to adjust the estimated weight for each tow in the logbook. This is why it is so critical to link fish tickets (weight at the dock) with logbooks (estimated catch by depth and location).

Suggested Citation:"General Issues in the Collection, Management, and Use of Fisheries Data." National Research Council. 2000. Improving the Collection, Management, and Use of Marine Fisheries Data. Washington, DC: The National Academies Press. doi: 10.17226/9969.
×

quires that records should be checked for at least the following items:

  • legibility

  • completion of all necessary fields

  • reasonableness of dates and times

  • accuracy of species and gear combinations

The ACCSP recommends that:

  • incorrect or inconsistent entries follow data protocols that include contacting the data provider. (Problem data providers who consistently make errors may be given additional training or legal action may be considered [e.g., fines, license revocation].)

  • reviewed data forms be entered into the database by adequately trained data entry clerks, with an error rate of less than 0.5 percent for the set of all data entered, through use of a double entry system (each data point is entered twice and not accepted unless both entries are identical).

  • someone other than a data entry clerk should perform a spot check for errors on 5-10 percent of a year's entries.

  • the following standard computer data edit checks, at a minimum, are run:

    • species ranges, lengths, and weights

    • dates of catch

    • fisherman and dealer licenses

    • fishing gear used

    • invalid codes

    • outliers

    • blank fields

    • comparisons with tracking database

The edit checks flag errors and probable errors, alerting the data entry clerk and permitting changes before the data reach the database (ACCSP, undated b). The program design document also mentions that unannounced audits of dealers' and fishermen's records may be used as a data verification tool (ACCSP, undated b).

Version 1.5 of the application also advocates that summary reports, similar to monthly bank statements, be sent to fishermen on a periodic basis for data verification. Benefits of such reports include (1) allowing fishermen and dealers to see the data after they have been entered, increasing confidence that their data are being used; (2) giving fishermen an opportunity to correct erroneous data, thus improving accuracy; and (3) providing fishermen with an official record of what they have caught and their revenues.

All the data quality routines discussed here supplement those implemented by the data sources, since the ACCSP agreement vests responsibility for the quality and completeness of the archived records with the agencies that originally collect the information (ACCSP, 1999). ACCSP requests that the states implement standard operating procedures (SOP) and develop SOP manuals, and that members sign agreements to use a specified standard of data collection elements and reporting formats. Data will be collected by individual fishing trips, including a standardized collection of elements such as species, area fished, gear type, quantity and value of catch, and vessel identification number. Members will also use standardized units of measure, coding systems, and nomenclature whenever possible.

The Georgia program that will provide data to ACCSP is illustrative. The draft SOP manual notes that the Georgia Coastal Resources Division 's statistics project is under the Commercial Fisheries Program in the Marine Fisheries Section. Historically, the project has been funded by the NMFS Cooperative Statistics Program. In 1999 the project received additional funding through the Atlantic Coast Fisheries Cooperative Management Act (ACFCMA) to implement a commercial fisheries trip ticket program that would comply with the ACCSP (Anonymous, 1999).

Commercial landings data are collected with each fishery's self-coded trip tickets, which contain pre-labeled columns for the market grade and condition of the predominant species. In some fisheries, the gear quantity and area fished are

Suggested Citation:"General Issues in the Collection, Management, and Use of Fisheries Data." National Research Council. 2000. Improving the Collection, Management, and Use of Marine Fisheries Data. Washington, DC: The National Academies Press. doi: 10.17226/9969.
×

also labeled. Seafood dealers receive the trip ticket forms, postage-paid envelopes, and a plastic card imprinter engraved with their business name and dealer code. Seafood harvesters are provided with a personalized plastic card embossed with their name and commercial fishing license number. Port agents code the remaining fields using four-digit species codes and threedigit gear codes provided by NMFS and 6-digit area codes supplied by the Georgia Department of Natural Resources.

After all data have been reviewed for completeness, they are entered by the port agents and a data clerk into a customized database implemented with the PROGRESS relational database management system. The data are edited at three different points. First, while coding and conversion take place port agents identify illegible fields and odd species and gear combinations, and track down missing data. Second, as data are entered, the data entry software checks for invalid codes, gear combinations, and price ranges. Final data editing is accomplished by running edit programs to check for outliers and by spot checking data forms against the data set. All data are entered within 10 days of receipt by the statistics program (Anonymous, 1999).

According to the Georgia SOP, the PROGRESS database does not contain the fields that were added to bring Georgia into conformance with ACCSP data standards. A new database is under development in Oracle. The Oracle application is currently being tested.

Sometime later, scanning of the trip ticket form will begin and images of the form itself will be created and archived on read-only CDs and stored in a safe deposit box. This will eliminate the need to store paper documents and still meet Georgia's requirements for archived records.

After completed landings data are run through a PROGRESS program that converts all fields to the SEFHost format in ASCII code, data are then transferred to NMFS monthly by email (Anonymous, 1999).

Fisheries Information System

The VRS-FIS report to Congress (NMFS, undated) presents the following design principles for standards of measurement and quality for a future FIS:

  • Establish standardized units of measurement and nomenclature, where possible.

  • Establish standard coding systems, where possible, or build logical bridges or translations between separate coding systems, where necessary.

  • Establish reasonable minimum data quality standards.

  • Establish standard (minimum critical) data elements.

  • Minimize number of coding systems.

  • Develop processes to ensure the timely release of information to the public.

The FIS design principles indicate that the shortcomings of the existing fisheries data management systems are well known. The need for standardized data elements to allow comparability among systems is apparent. The proposed FIS includes funding of $1.575 million to establish and implement criteria and processes for evaluation of data quality and data quality standards. These funds would be used to:

  • research and adopt nationwide data quality standards, with help from individuals from universities, other federal agencies, and private research contractors familiar with large-scale data quality issues.

  • establish nationwide data quality control groups to provide continuous oversight and peer review of both data collection and data quality processes.

  • research, design, and implement validation methods for self-reported statistical systems (e.g., logbooks) to measure and document the biases and accuracy of such data.

  • create online metadata files containing system statistical information to improve avail-

Suggested Citation:"General Issues in the Collection, Management, and Use of Fisheries Data." National Research Council. 2000. Improving the Collection, Management, and Use of Marine Fisheries Data. Washington, DC: The National Academies Press. doi: 10.17226/9969.
×

ability of documentation on quality of the information.

Technologies for Data Management

Fisheries data collection, analysis, use, and archival storage present a challenge to the organizations responsible for providing accurate, timely, and easily accessible fisheries data. It is evident not only from existing systems, but also systems in various stages of planning and development, that the existing fisheries data management systems are heterogeneous, are often incompatible and/or duplicative, are developed by different organizational entities, have a regional focus (so far), do not necessarily share data elements, and may or may not comply with federal data management standards.

NMFS acknowledges that “despite some regional successes, it is clear that the current overall approach to collecting and managing fisheries data needs to be re-thought, revised and reworked. The quality and completeness of fishery data are often inadequate. Data are often not accessible in an appropriate form or a timely manner. ” (NMFS, undated).

Fisheries Data Integration

Since existing fisheries data management systems are heterogeneous, integration is of primary importance to enable data synthesis on regional and national scales. The lack of standardized data elements necessitates implementation of “translators” to allow incompatible data elements residing in different databases to be accessed through a single interface. The ACCSP is an example of a regional fisheries data management system that initially will employ translators to reconcile incompatible data elements now collected by participating states (ACCSP, undated b), including both commercial and recreational data. The FIS will take the process one step further by integrating ongoing regional fisheries data management activities (e.g., FIN and PacFIN) under a nationwide umbrella (NMFS, undated). The proposed system recognizes the need for implementing national standards for a core set of data elements, data quality protocols, coding standards, and metadata. The importance of fully defining and implementing these standards cannot be overemphasized. NMFS' current FIS plans could be enhanced by development of a framework that provides more detailed computational information with particular attention to compliance with open-system standards.

Another aspect of data integration is use of a format that allows full exploitation of the data asset, for example, verification of different data sources used in management and research. This could be as simple as matching logbook data against trip tickets. The existence of a unique identifier for each fishing vessel as planned in the FVR system—together with the date and time of each trip—will facilitate data verification by providing positive identification of vessels and trips that can be used across databases. Such a feature should enhance the confidence of managers in data from different sources.

Historically, fisheries data have focused on individual species and their population dynamics. In recent years, more attention has been given to the predatory and competitive relationships among species, as well as finding commonalties across species (e.g., meta-analysis, Myers et al., 1995). Research on biological interactions and other ecosystems research would benefit if data were collected in compatible formats and were integrated in ways that facilitate study of the complex interrelationships in marine ecosystems. This could be a useful adjunct to traditional (and still necessary) stomach content analysis.

Geographic Information Systems—Geographic information systems (GISs) allow spatial data from many sources, such as sampling tows, to be referenced to a single grid of spatial coordinates. The use of GIS techniques offers promise for combining data from many sources into a single spatial grid, with new possibilities for understanding how various factors affect fish populations at various spatial scales.

Suggested Citation:"General Issues in the Collection, Management, and Use of Fisheries Data." National Research Council. 2000. Improving the Collection, Management, and Use of Marine Fisheries Data. Washington, DC: The National Academies Press. doi: 10.17226/9969.
×

GIS applications and visualizations show promise as outreach tools to improve communication of the results of fisheries science and management activities to the general public. They could also promote better understanding among fishery scientists. Because these applications already exist, making them more widely available and easily used could benefit all stakeholders in fisheries management and promote cooperation among data providers and other stakeholders. The Open GIS Consortium states that “GIS information is available on the Web —in stovepipes.23 Users must possess considerable expertise and special GIS software to overlay or otherwise combine different map layers. ” (Open GIS Consortium, 1999). This limits the ability of scientists, managers, fishermen, and others to use such data.

The Open GIS Consortium is currently conducting a Web Mapping Testbed (WMT) project. This project is an “accelerated, multi-phase effort to meet the market's demand for interoperable geo-enabled Web technology. The project is advancing the state of Web technology to support diverse applications that access distributed geospatial information sources across the Web. Applications include environmental analysis and management. ” (Open GIS Consortium, 1999). Sponsors of WMT include the FGDC, United States Geological Survey (USGS), NASA, the U.S. Department of Agriculture (USDA), a group of 24 Australian government and commercial organizations, Pennsylvania State University, 23 vendor companies (including Microsoft, ESRI, Sun, Oracle, Cubewerx [Canada] and others [Anonymous, 1999; Open GIS Consortium, 1999]). Participants in the WMT are combining their expertise to make it possible for overlays and combinations of complex and essentially different kinds of GIS information to happen automatically over the Internet, despite differences in the underlying software (Open GIS Consortium, 1999). NMFS and other fishery organizations should consider responding to the Open GIS Consortium 's call for participants in subsequent project phases.

Visualizations—Most fisheries data are presented in tabular format in reports, papers, and Web pages. In some cases, plots on two-dimensional maps represent sampling results. Many opportunities exist to provide better visualizations of fisheries data to promote better understanding by scientists, fishermen, and the general public. These could include 3-D virtual underwater worlds highlighting bottom topography, currents, concentrations of fish, and other features. Examples using Virtual Reality Modeling Language (VRML) technology are available at the Web site of NOAA 's Pacific Marine Environmental Laboratory (http://www.pmel.noaa.gov/home/visualization/visual.html). The Fisheries Oceanography Coordinated Investigations Web site (http://pmel.noaa.gov/foci/visualizations/visual.html) includes a virtual reality world, as well as other visualizations. The Pacific Fisheries Environment Laboratory (PFEL) Web site at www.pfeg.noaa.gov features a live access server that allows visitors to visualize and download selected PFEL data products. Visualizations could be used as a tool in fisheries simulations for both teaching and consensus-building purposes.

DATA USE

Data use is discussed only briefly here because it was the focus of the NRC's Improving Fish Stock Assessments (NRC, 1998a).

Uncertainties of Data in Stock Assessments

A good example of the potential complexity of data sources used in any fishery is the summer flounder fishery. All the forms of data discussed earlier in this chapter are available for this fishery (Table 3-10). Stock assessments are subject to uncertainties of various types, ranging from uncertainties in observations to implementation of management.

23  

Stovepipes are systems that stand alone and do not inter-operate.

Suggested Citation:"General Issues in the Collection, Management, and Use of Fisheries Data." National Research Council. 2000. Improving the Collection, Management, and Use of Marine Fisheries Data. Washington, DC: The National Academies Press. doi: 10.17226/9969.
×

TABLE 3-10 Summary of Data Sources and Source Attributes for Summer Flounder

 

Types of Data

Attributes of Sources

 

Spatial Information

Species Composition

Size Composition

Age, Sex Composition

Price

Confidential

Accessiblea

     

Federal

     

Mandatory logbooks

2

2

0

0

0

2

1

Scientific observers

2

2

1

1

0

2

1

Scientific survey

2

2

2

2

0

1

2

Recreational survey

1

1

1

0

0

2

2

Port sampling

1

2

2

2

1

0

2

VMS

2

0

0

0

0

2

0

     

States (see Appendix C for listing of states)

 

Landings

1

2

0

0

2

0

1

Surveys

2

1

1

1

0

0

2

Key: 0 = none; 1 = some; 2 = complete.

a Accessible refers to the extent that data are shared between those with the responsibility to collect the data and those who may have use for the data (e.g., scientists, managers).

One level is the degree of uncertainty reflected in an observation, typically referred to as the observation error. This is the variation that would be seen under repeated sampling. The observation might be survey CPUE for a given year, and so would be a statistic summarizing a number of points gathered under a prespecified sampling design. A second level of uncertainty in information comes in through the natural variation that occurs in the environment, so that even if every individual in the population is measured, variation in size and abundance is still expected from one year to the next due to the natural variation in the individual growth and population dynamics. This variation is referred to as process uncertainty and does not represent our ability to measure but rather represents expected natural variation in the process.

The third level of uncertainty is reflected in how the system is characterized, which is typically done through specification of a model. The choice of model interacts with the previous two levels of uncertainty and reflects to a degree a choice between bias and variance in the estimation process. Models may characterize the system simply or with more complexity, but they may also mischaracterize the system through selection of a model that does not represent actual processes well (model misspecification). The uncertainty in model specification can be estimated only by challenging the data with different models and/or additional kinds of data, as was done through the committee's analysis of summer flounder data. Added to this is the fact that only a single realization of the data is available, a single series through time, and thus the overall uncertainty cannot be assessed with repeated time series. It is sometimes possible to get around this problem by using meta-analysis across similar systems or through adaptive management that allows informative exploration of the system. Finally, implementation uncertainty is an expression of “the

Suggested Citation:"General Issues in the Collection, Management, and Use of Fisheries Data." National Research Council. 2000. Improving the Collection, Management, and Use of Marine Fisheries Data. Washington, DC: The National Academies Press. doi: 10.17226/9969.
×

ability of management to achieve a particular harvest rate in any one year” (Rosenberg and Brault, 1993) and institutional uncertainty arises from “the interaction of the individuals and groups (scientists, economists, fishermen, etc.) that compose the management process ” (O'Boyle, 1993). In the end, the output from our assessments poorly represents the levels of uncertainty that exist, impeding an adequate assessment of risk in decisionmaking and informed development of research priorities.

Access to Data

Users of fisheries data management systems include fishery managers, scientists, fishermen, industry groups, and other interested parties. Because fishery databases contain sensitive business information, most restrict access and usage to those with a need to know. The specific approach chosen for authorization and access controls varies among existing fishery databases. PacFIN, for example, uses logins and a list of authorized or allowed Internet Protocol addresses. There is currently no interactive Web access to PacFIN. PacFIN and several other fishery databases provide summary reports on the World Wide Web for public access. The separation of general public access and restricted access to the data may impact the number of visitors recorded at fishery data Web sites.

Aside from the traditional sources of fisheries data, opportunities exist for overlaying data from other studies. GISs could help in accomplishing such overlays. For example, the U.S. Global Change Research Program is supporting field studies of the dynamics of fish and plankton populations and of the causes of variations of marine biological populations in the Global Ocean Ecosystems Dynamics (GLOBEC) and other activities (Our Changing Planet, fiscal year 1999). The California Cooperative Oceanic Fisheries Investigation (CalCOFI) has compiled a long time series of data related to fisheries for the California Current System. In these cases, fisheries data management could either gain from or contribute to overlaying data from other studies.

Management Information Needed by Councils

The committee sent a list of questions regarding fishery data issues to the executive directors of each of the eight fishery management councils. Some councils responded by stating that they wanted annual assessments for each species rather than the staggered subset of assessments available each year. The staggered schedule is a result of inadequate funding for assessment personnel and ship time, but councils with fisheries in an overfished and rebuilding mode have said that they need annual assessment updates, so they can manage the rebuilding process more effectively. Information relevant to management priorities was requested. Several councils noted that NMFS is limited by the availability of assessment personnel and that NMFS cannot go beyond its minimal fulfillment of legal mandates.

The councils identified several specific information needs (beyond what they already receive), including the following:

  • Baseline information to manage the new national standards established by the Sustainable Fisheries Act, particularly in relation to by catch and effects on fishing communities. Although fishery management plans must contain social and economic impact analyses, NMFS and states are still not doing an adequate job of collecting data and providing them to the councils.

  • Economic data, such as would be required to estimate consumer benefits, construct bioeconomic models, analyze vessel costs and returns, and describe fishing community structure.

  • Enforcement data from NMFS, for example, how many landings are examined for rates of compliance and non-compliance with management measures such as trip limits.

  • Data on the stock status of artisanal fisheries.

  • Tagging data to study stock interactions and fish movements.

Suggested Citation:"General Issues in the Collection, Management, and Use of Fisheries Data." National Research Council. 2000. Improving the Collection, Management, and Use of Marine Fisheries Data. Washington, DC: The National Academies Press. doi: 10.17226/9969.
×
Fisheries Data Discovery

Users must discover fisheries data in order to use it. Most fishery databases have a public component with Web access to standardized reports. These sites have home pages indexed by the common search engines that allow discovery by the public, made possible by metatags. 24 However, not all fisheries Web sites are currently using metatags. As of June 1999, among the AKFIN, PacFIN, RecFIN, and ACCSP home pages, only RecFIN included metatags in the document source. The use of metatags should be promoted because they are used by many search engines when indexing pages and thus provide an aid to document discovery.

Fishery databases also have a private component, with access restricted to researchers, managers, and others with a need to know (see earlier section on confidentiality). This restriction is related to the inclusion of sensitive business information in the database and in some cases is mandated by state or federal law or both. In general, persons who desire access to restricted fisheries information must sign a non-disclosure agreement and fill out a database access request form that must be approved by a database official.

The NOAA server (http://www.noaa.gov) provides unified access to fishery data sets held by the NMFS Northwest Fisheries Science Center, with discovery through a query of FGDC metadata. The server system is now being redesigned so that access to planning documents will require a password. The existing system allows a user to select a query term, but the terms are very general. There is also a spatial query interface based on either latitude-longitude or a map. This appears to be a secondary access method with only minimal metadata included about NMFS fisheries data sets. It is often necessary to contact the individual listed in the metadata to gain access to the data. Landings information is available from the NOAA Web site for commercial (www.st.nmfs.gov/commercial/index.html) and recreational (www.st.nmfs.gov/recreational/index.html) fisheries.

Cooperation and Communication

The committee did not investigate all possible communication links, but it did query the regional fishery management councils about how they obtain the data they need for management decisions and whether they wanted information in a different form or wanted different information.

It is obvious that cooperation in data use is essential for effective management. Different regional councils accomplish cooperation differently. In some cases, councils receive data and information on a regular basis. Most councils rely greatly on members from NMFS, the Coast Guard, states, and other organizations to ensure that the necessary information is transferred to the councils and used in management.

One council expressed the desire to gain access to non-aggregated data and requested a more efficient means of data access than transfer of data disks. Another council noted the need for better ways to “analyze and reduce information so that it may be readily assimilated by council members and the public during the decision process.” The councils believe that greater efforts and resources need to be devoted to improving communication of the reasons why data are collected in specific ways, for example, using outdated trawl gear and random, stratified sampling. It was also suggested that information communication specialists be enlisted to improve communication between councils and stakeholders. Most of the councils have extensive Web sites that include their fishery management plans, other reports, meeting schedules, committee rosters, and other information. These Web sites can be very efficient communication tools, if kept current.

24  

Metatags are information in World Wide Web documents that have a number of functions, including providing keywords and descriptions of the document that are accessed by search engines to categorize Web documents.

Suggested Citation:"General Issues in the Collection, Management, and Use of Fisheries Data." National Research Council. 2000. Improving the Collection, Management, and Use of Marine Fisheries Data. Washington, DC: The National Academies Press. doi: 10.17226/9969.
×
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Suggested Citation:"General Issues in the Collection, Management, and Use of Fisheries Data." National Research Council. 2000. Improving the Collection, Management, and Use of Marine Fisheries Data. Washington, DC: The National Academies Press. doi: 10.17226/9969.
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Suggested Citation:"General Issues in the Collection, Management, and Use of Fisheries Data." National Research Council. 2000. Improving the Collection, Management, and Use of Marine Fisheries Data. Washington, DC: The National Academies Press. doi: 10.17226/9969.
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Suggested Citation:"General Issues in the Collection, Management, and Use of Fisheries Data." National Research Council. 2000. Improving the Collection, Management, and Use of Marine Fisheries Data. Washington, DC: The National Academies Press. doi: 10.17226/9969.
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Suggested Citation:"General Issues in the Collection, Management, and Use of Fisheries Data." National Research Council. 2000. Improving the Collection, Management, and Use of Marine Fisheries Data. Washington, DC: The National Academies Press. doi: 10.17226/9969.
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Suggested Citation:"General Issues in the Collection, Management, and Use of Fisheries Data." National Research Council. 2000. Improving the Collection, Management, and Use of Marine Fisheries Data. Washington, DC: The National Academies Press. doi: 10.17226/9969.
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Suggested Citation:"General Issues in the Collection, Management, and Use of Fisheries Data." National Research Council. 2000. Improving the Collection, Management, and Use of Marine Fisheries Data. Washington, DC: The National Academies Press. doi: 10.17226/9969.
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Suggested Citation:"General Issues in the Collection, Management, and Use of Fisheries Data." National Research Council. 2000. Improving the Collection, Management, and Use of Marine Fisheries Data. Washington, DC: The National Academies Press. doi: 10.17226/9969.
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Suggested Citation:"General Issues in the Collection, Management, and Use of Fisheries Data." National Research Council. 2000. Improving the Collection, Management, and Use of Marine Fisheries Data. Washington, DC: The National Academies Press. doi: 10.17226/9969.
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Suggested Citation:"General Issues in the Collection, Management, and Use of Fisheries Data." National Research Council. 2000. Improving the Collection, Management, and Use of Marine Fisheries Data. Washington, DC: The National Academies Press. doi: 10.17226/9969.
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Suggested Citation:"General Issues in the Collection, Management, and Use of Fisheries Data." National Research Council. 2000. Improving the Collection, Management, and Use of Marine Fisheries Data. Washington, DC: The National Academies Press. doi: 10.17226/9969.
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Suggested Citation:"General Issues in the Collection, Management, and Use of Fisheries Data." National Research Council. 2000. Improving the Collection, Management, and Use of Marine Fisheries Data. Washington, DC: The National Academies Press. doi: 10.17226/9969.
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Suggested Citation:"General Issues in the Collection, Management, and Use of Fisheries Data." National Research Council. 2000. Improving the Collection, Management, and Use of Marine Fisheries Data. Washington, DC: The National Academies Press. doi: 10.17226/9969.
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Congress has promoted fisheries science for over a century and its involvement in fisheries management took a great leap forward with passage of the Fisheries Conservation and Management Act of 1976. In the past decade, Congress has requested advice from the National Research Council (NRC) on both national issues (e.g., individual fishing quotas and community development quotas) and the assessments related to specific fisheries (Northeast groundfish). This report was produced, in part, in response to another congressional request, this time related to the assessments of the summer flounder stocks along the East Coast of the United States. Following the initial request, the NRC, National Marine Fisheries Service (NMFS), and congressional staff agreed to broaden the study into a more comprehensive review of marine fisheries data collection, management, and use.

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