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
U2 - 10.1080/19438151003716498
DO - 10.1080/19438151003716498
M3 - Article
AN - SCOPUS:79958274826
SN - 1943-815X
VL - 7
SP - 135
EP - 144
JO - Journal Of Integrative Environmental Sciences
JF - Journal Of Integrative Environmental Sciences
IS - 2
ER -