Using Local Knowledge as a Research Tool in the Study of River Fish Biology: Experiences from the Mekong View Full Text


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Article Info

DATE

2000-09

AUTHORS

John Valbo-Jørgensen, Anders F. Poulsen

ABSTRACT

River fisheries are extremely important for food-security among the rural poor in many tropical countries. The growing populations and rapid industrialisation of these countries require that appropriate action should be taken to sustain the resources for future generations. However, an incomplete understanding of river fisheries biology, at the managerial level, often hampers proper planning and management. This is partly due to the difficult access to large parts of such river basins, the complex nature of the fisheries, and in many cases a severe lack of research funds. In contrast, the thousands, or often millions of people who live along the shores of the rivers and rely on the fishery for their daily survival, have a very intimate knowledge of the behaviour and biology of the fish. In this situation, gathering the knowledge of the fishers may provide politicians or planners with baseline knowledge in a relatively quick and cheap way. This paper discusses two years of research using local knowledge in the study of fish migration and spawning in the Lower Mekong Basin. The study involves semi-structured interviews with 355 expert fishermen in four countries along 2,400 km of the Mekong mainstream. By piecing together information from fishermen in different areas, we were able to construct migration maps, and provide rough estimates of the spawning period for 50 fish species. We conclude that river fisheries research can benefit significantly from local knowledge as the basis for future research. More... »

PAGES

253-376

References to SciGraph publications

  • 1986. The Mekong River system in THE ECOLOGY OF RIVER SYSTEMS
  • 1977-05. Towards a model of a floodplain fish population and its fishery in ENVIRONMENTAL BIOLOGY OF FISHES
  • Identifiers

    URI

    http://scigraph.springernature.com/pub.10.1023/a:1011418225338

    DOI

    http://dx.doi.org/10.1023/a:1011418225338

    DIMENSIONS

    https://app.dimensions.ai/details/publication/pub.1029372027


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