Assessing Changes in Fisheries Using Fishers' Knowledge to Generate Long Time Series of Catch Rates: a Case Study from the Red Sea

The data requirements for most quantitative fishery assessment models are extensive, and most of the fisheries in the world lack time series of the required biological and socioeconomic data. Many innovative approaches have been developed to improve data collection for fisheries. We explored the use...

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Bibliographic Details
Main Authors: Dawit Tesfamichael, Tony J. Pitcher, Daniel Pauly
Format: Article
Language:English
Published: Resilience Alliance 2014-03-01
Series:Ecology and Society
Subjects:
Online Access:http://www.ecologyandsociety.org/vol19/iss1/art18/
Description
Summary:The data requirements for most quantitative fishery assessment models are extensive, and most of the fisheries in the world lack time series of the required biological and socioeconomic data. Many innovative approaches have been developed to improve data collection for fisheries. We explored the use of data from fishers' interviews to estimate time series of approximate "best" catch rates. A total of 472 standardized interviews were conducted with 423 fishers along the southern Red Sea coast recording the best catch recalled and the change in average catch rates throughout the fishing career of interviewees. The results showed a decline of best catch rates in all fisheries, ranging from 4% to 10% per year for more than 50 years. The estimated rates of decline of the typical catch were higher for fishers who started fishing in recent years, suggesting that the resource base is declining, in concordance with other indicators. It is suggested that analysis of approximate data, quickly acquired at low cost from fishers through interviews, can be used to supplement other data-recording systems or used independently to document the changes that have occurred in the resource base over a lifetime of fishing. The results can be used to guide the assessment and management of resources to conserve ecosystems and livelihoods.
ISSN:1708-3087