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Fishery statistics are the primary means to measure the performance of a fishery within the social, economic, biological and environmental framework in which it is conducted. The collection of fishery data is based on a relatively small group of concepts and approaches, including most importantly the quantities harvested (catch), the related type and duration of fishing operations (fishing effort), the economic costs and returns of fishing and the distribution of these in time and space.

Sections 1-5 of this handbook outline these key concepts and describe the general approach to achieving them through sample-based fishery surveys. Sections 6-10 take a more detailed look at basic survey types, from Frame Surveys to Landings Surveys. Sections 11 and 12 address basic approaches to data processing and information dissemination.

This section presents some general aspects of sample-based fishery surveys with emphasis on:


In this handbook basic fishery data refers to catch, catch by species, fishing effort, first-sale prices (i.e. prices at landing), values, and fish size (in weight units). These are the general-purpose datasets that may be subsequently used for a variety of statistical applications.

Justification for regularly conducted and costly fishery surveys can be achieved through reference to a long list of potential uses of basic fishery data, the commonest of which include:

1.1.1 Food security

Food security is often the over-riding concern for senior policy-makers, planners and administrators of natural living resources. In many communities, particularly in developing countries, fish is the major source of animal protein and many people are entirely dependent on fish as a food source.

Food balance sheets constitute a principal source of information for studies concerned with food security. Estimated total production of fish, when combined with data on catch distribution, imports and exports, constitute the basis for calculating per capita consumption of fish and the subsequent formulation of food balance sheets.

Basic data: total catch, catch by species, imports, exports, human population

1.1.2 Fishing mortality

Fishing mortality is a fundamental variable in stock assessment; representing the proportion of stock that is removed due to fishing, i.e. separate from the stock reductions due to natural population mortality. Effort is one of the variables used to estimate fishing mortality. Controlling the amount of fishing effort (and hence the resulting fishing mortality), say through limits to vessel numbers or fishing days, is one of the most common methods to control the extent of stock removals.

Basic data: fishing effort

1.1.3 Fishing operations

Fishing operations indicators describe the composition of fishing fleets and fishing patterns and are the basis of many management decisions. They are important for monitoring compliance with fishery management controls, such as fleet numbers, days fishing, or seasonal and area limits.

Basic data: locations of homeports and landing sites, numbers of fishing units by gear category, fishing effort by boat/gear category

1.1.4 Species/gear selectivity

It is always important to obtain data on the species that are targeted by different boat/gear categories and fishing methods, together with other information relating to the size of the fish being caught. These datasets are used for a wide variety of temporal (in-time) and spatial (in-space) comparisons of gear selectivity indicators.

Basic data: species composition, average weight (and size) of fish by boat/gear type

1.1.5 Abundance and exploitation

Catch-Per-Unit-Effort (CPUE) - also called catch rate - is frequently the single most useful index for long-term monitoring of a fishery. Declines in CPUE may mean that the fish population cannot support the level of harvesting. Increases in CPUE may mean that a fish stock is recovering and more fishing effort can be applied.

CPUE can therefore be used as an index of stock abundance, where some relationship is assumed between that index and the stock size. Catch rates by boat and gear categories, often combined with data on fish size at capture, permit a large number of analyses relating to gear selectivity, indices of exploitation and monitoring of economic efficiency.

Basic data: catch by species, effort by boat/gear category

1.1.6 Importance to national economy

For national and local policy-making and planning it is essential to describe the contribution of fisheries to the economy by taking into account important variables and indicators, such as product prices and gross value of production.

Basic data: total catch, catch and price by species

1.1.7 Fleet performance and profitability

Boat profitability is a vital micro-economic indicator of fishery performance since it provides a measure of economic sustainability of artisanal fleets. Prices at landing, combined with data on investment and operational costs can provide indices of fleet performance.

Basic data: catch, fishing effort, average price of catch

1.1.8 Socio-economic studies

Time series of fishing effort, catch (hence CPUE) and prices are often used in socio-economic studies in which declining or increasing trends of fisheries in districts and regions can be used for the determination of appropriate fishery management controls or in infrastructure investment.

Basic data: catch, effort (hence CPUE), prices and values


Regularly conducted fishery surveys are costly and will include field and office personnel costs, field operations costs and other overhead and maintenance costs relating to office infrastructure and operations. In many developing countries these total costs may constitute a major constraint on the effective development of fishery statistics. However, cost-effective sample-based fishery surveys can be achieved when:


Statistical analysis most often requires time-series of data through regularly conducted fishery surveys. A sample-based fishery survey is considered sustainable when:


The backbone of a fishery survey is the field team of data collectors and their supervisors who form the primary interface between fishers and fisheries management. They collect and submit data to the fishery statistical units for further processing. The following points underline the important role of field staff involved in data collection:

1.4.1 Quality and utility of collected data

The quality of produced statistics is a direct function of the effectiveness and timeliness of field operations involving data collectors and supervisors. Data quality affects its utility in meeting the aims of its collection and in satisfying acceptable statistical reliability.

1.4.2 Training

Training and re-training of data collectors must be thorough, appropriate to their tasks and take into consideration their capacity to carry out instructions.

1.4.3 Realistic survey design

All survey designs must be broken down into achievable tasks which can be accomplished within realistic work schedules and through unambiguous instructions for data collectors.

1.4.4 Mobility of data collectors and supervisors

The mobility of data collectors and their supervisors (to provide support and guidance) affects the quantity of collected data as well as their representativeness. Low mobility due to lack of transportation usually results in reduced statistical coverage (time and area) and increases the risks of biased data, since survey data collection will usually be conducted at the same few locations.

1.4.5 Motivation and operational experience

Data collectors and supervisors should be motivated to perform their work, and not only financially. They should have a good understanding of the purpose and utility of their work, feel part of the overall statistics team and be provided with recognised feedback mechanisms to enable their participation in the structuring and implementation of surveys. To enable this, field staff should attend workshops and training courses concerning operational aspects of data collection, since their operational experience would contribute positively in survey planning and the revision of survey design.


Primary data collected by field staff are of little or no utility unless there is appropriate statistical office infrastructure. The responsibilities and functions of statistical office staff are:

1.5.1 Design and planning

Design and planning of fishery surveys, including implementation scheduling, training, equipment and logistics support and the co-ordination and monitoring of all of the field and office activities involved.

1.5.2 Monitoring

Organizing and reviewing primary data obtained from the field, including editing and data checking, and undertaking corrective actions as necessary.

1.5.3 Computer operations

Operating computer-based procedures for the effective storage of primary data, derivation of estimates and preparation of working documents, statistical bulletins and yearbooks.

1.5.4 Data Processing and Dissemination

Statistical office staff should be trained in basic statistical analysis for the preparation of statistical reports and the correct interpretation of statistical indicators and diagnostics. Although some compilation and filing of raw data may be paper-based it is more usual that robust and user-friendly computing tools and methods, and adequate computing capacity, are available for routine and ad hoc processing, analysis and dissemination of fishery statistical data to fishery managers and other national, regional and international user groups.


In this introductory section readers have been introduced to:

(a) Importance and utility of basic fishery data such as catch, effort, prices and values and a list of commonly used applications that make use of such data.

(b) Need for sample-based fishery surveys to be cost-effective and sustainable and some criteria for evaluating them from these two standpoints.

(c) Key role of field staff in data collection operations and the important role of office staff and equipment for the effective analysis and dissemination of fishery statistical data.

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