Counting fish: A typology for fisheries catch data

Jennifer Jacquet, Dirk Zeller, Daniel Pauly

    Research output: Contribution to journalArticle

    Abstract

    Good decisions ideally require good data. Here, we present a straightforward typology for the broad classification of fisheries catch data. At each stage in the reporting chain, from fisher to national/international agencies, fisheries catches can be: known and reported; known and underreported; unknown and overreported; or unknown and underreported. Here, we consider largely the data reporting at the national/international level. Unfortunately, experience has shown that scientists and managers often do not know or are unconcerned with which category their data falls within a country's complete data system, or how to deal with this problem, leading to considerable implications for management. Of these four categories, the underreporting of catches seems the likeliest and most common outcome, which inevitably leads to mismanagement and misallocations of fisheries resources. Attempts to improve catch data should be undertaken, particularly via the development of catch baselines through catch reconstructions and adoption of a transparent and comprehensive country-wide expansion approach. Such an approach not only helps address shifting baselines but identifies aspects of data improvement that can be implemented in future data collection. The taxonomy presented here is a conceptual first-order analytical tool to classify data status, and hence influence management decisions.

    Original languageEnglish (US)
    Pages (from-to)135-144
    Number of pages10
    JournalJournal of Integrative Environmental Sciences
    Volume7
    Issue number2
    DOIs
    StatePublished - Jun 2010

    Fingerprint

    Fisheries
    catch statistics
    typology
    Fish
    Fishes
    fishery
    fish
    International Agencies
    Taxonomies
    Information Systems
    Managers
    Research Design

    Keywords

    • Catch data
    • Catch reconstruction
    • Data reporting
    • Fisheries management
    • Uncertainty

    ASJC Scopus subject areas

    • Environmental Science(all)
    • Renewable Energy, Sustainability and the Environment
    • Public Health, Environmental and Occupational Health

    Cite this

    Counting fish : A typology for fisheries catch data. / Jacquet, Jennifer; Zeller, Dirk; Pauly, Daniel.

    In: Journal of Integrative Environmental Sciences, Vol. 7, No. 2, 06.2010, p. 135-144.

    Research output: Contribution to journalArticle

    Jacquet, Jennifer ; Zeller, Dirk ; Pauly, Daniel. / Counting fish : A typology for fisheries catch data. In: Journal of Integrative Environmental Sciences. 2010 ; Vol. 7, No. 2. pp. 135-144.
    @article{0a1fb0591f3947bca2508e625ac8f25e,
    title = "Counting fish: A typology for fisheries catch data",
    abstract = "Good decisions ideally require good data. Here, we present a straightforward typology for the broad classification of fisheries catch data. At each stage in the reporting chain, from fisher to national/international agencies, fisheries catches can be: known and reported; known and underreported; unknown and overreported; or unknown and underreported. Here, we consider largely the data reporting at the national/international level. Unfortunately, experience has shown that scientists and managers often do not know or are unconcerned with which category their data falls within a country's complete data system, or how to deal with this problem, leading to considerable implications for management. Of these four categories, the underreporting of catches seems the likeliest and most common outcome, which inevitably leads to mismanagement and misallocations of fisheries resources. Attempts to improve catch data should be undertaken, particularly via the development of catch baselines through catch reconstructions and adoption of a transparent and comprehensive country-wide expansion approach. Such an approach not only helps address shifting baselines but identifies aspects of data improvement that can be implemented in future data collection. The taxonomy presented here is a conceptual first-order analytical tool to classify data status, and hence influence management decisions.",
    keywords = "Catch data, Catch reconstruction, Data reporting, Fisheries management, Uncertainty",
    author = "Jennifer Jacquet and Dirk Zeller and Daniel Pauly",
    year = "2010",
    month = "6",
    doi = "10.1080/19438151003716498",
    language = "English (US)",
    volume = "7",
    pages = "135--144",
    journal = "Journal of Integrative Environmental Sciences",
    issn = "1943-815X",
    publisher = "Taylor and Francis Ltd.",
    number = "2",

    }

    TY - JOUR

    T1 - Counting fish

    T2 - A typology for fisheries catch data

    AU - Jacquet, Jennifer

    AU - Zeller, Dirk

    AU - Pauly, Daniel

    PY - 2010/6

    Y1 - 2010/6

    N2 - Good decisions ideally require good data. Here, we present a straightforward typology for the broad classification of fisheries catch data. At each stage in the reporting chain, from fisher to national/international agencies, fisheries catches can be: known and reported; known and underreported; unknown and overreported; or unknown and underreported. Here, we consider largely the data reporting at the national/international level. Unfortunately, experience has shown that scientists and managers often do not know or are unconcerned with which category their data falls within a country's complete data system, or how to deal with this problem, leading to considerable implications for management. Of these four categories, the underreporting of catches seems the likeliest and most common outcome, which inevitably leads to mismanagement and misallocations of fisheries resources. Attempts to improve catch data should be undertaken, particularly via the development of catch baselines through catch reconstructions and adoption of a transparent and comprehensive country-wide expansion approach. Such an approach not only helps address shifting baselines but identifies aspects of data improvement that can be implemented in future data collection. The taxonomy presented here is a conceptual first-order analytical tool to classify data status, and hence influence management decisions.

    AB - Good decisions ideally require good data. Here, we present a straightforward typology for the broad classification of fisheries catch data. At each stage in the reporting chain, from fisher to national/international agencies, fisheries catches can be: known and reported; known and underreported; unknown and overreported; or unknown and underreported. Here, we consider largely the data reporting at the national/international level. Unfortunately, experience has shown that scientists and managers often do not know or are unconcerned with which category their data falls within a country's complete data system, or how to deal with this problem, leading to considerable implications for management. Of these four categories, the underreporting of catches seems the likeliest and most common outcome, which inevitably leads to mismanagement and misallocations of fisheries resources. Attempts to improve catch data should be undertaken, particularly via the development of catch baselines through catch reconstructions and adoption of a transparent and comprehensive country-wide expansion approach. Such an approach not only helps address shifting baselines but identifies aspects of data improvement that can be implemented in future data collection. The taxonomy presented here is a conceptual first-order analytical tool to classify data status, and hence influence management decisions.

    KW - Catch data

    KW - Catch reconstruction

    KW - Data reporting

    KW - Fisheries management

    KW - Uncertainty

    UR - http://www.scopus.com/inward/record.url?scp=79958274826&partnerID=8YFLogxK

    UR - http://www.scopus.com/inward/citedby.url?scp=79958274826&partnerID=8YFLogxK

    U2 - 10.1080/19438151003716498

    DO - 10.1080/19438151003716498

    M3 - Article

    AN - SCOPUS:79958274826

    VL - 7

    SP - 135

    EP - 144

    JO - Journal of Integrative Environmental Sciences

    JF - Journal of Integrative Environmental Sciences

    SN - 1943-815X

    IS - 2

    ER -