ArticlePloS one2016
More than Anecdotes: Fishers' Ecological Knowledge Can Fill Gaps for Ecosystem Modeling.
Article in PloS one, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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Who cites it
8 citing papers in PubMed.
- Global-scale parameters for ecological models.Scientific data · 2023Article
- Fishers' knowledge on a large floodplain river in South America. Contributions for sustainable management of inland fisheries.Reviews in fish biology and fisheries · 2022Article
- Perceptions and attitudes towards climate change in fishing communities of the Sudd Wetlands, South Sudan.Regional environmental change · 2022Article
- Known but not called by name: recreational fishers' ecological knowledge of freshwater plants in Hungary.Journal of ethnobiology and ethnomedicine · 2021Article
- Telling the same story: Fishers and landing data reveal changes in fisheries on the Southeastern Brazilian Coast.PloS one · 2021Article
- The ability of artisanal fishers to recognize the dolphins they cooperate with.Journal of ethnobiology and ethnomedicine · 2020Article
- Article
- The use of Local Ecological Knowledge as a complementary approach to understand the temporal and spatial patterns of fishery resources distribution.Journal of ethnobiology and ethnomedicine · 2017Article
Corrections and comments
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Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundEcosystem modeling applied to fisheries remains hampered by a lack of local information. Fishers' knowledge could fill this gap, improving participation in and the management of fisheries. METHODOLOGY: The same fishing area was modeled using two approaches: based on fishers' knowledge and based on scientific information. For the former, the data was collected by interviews through the Delphi methodology, and for the latter, the data was gathered from the literature. Agreement between the attributes generated by the fishers' knowledge model and scientific model is discussed and explored, aiming to improve data availability, the ecosystem model, and fisheries management. PRINCIPAL
findingsThe ecosystem attributes produced from the fishers' knowledge model were consistent with the ecosystem attributes produced by the scientific model, and elaborated using only the scientific data from literature. CONCLUSIONS/SIGNIFICANCE: This study provides evidence that fishers' knowledge may suitably complement scientific data, and may improve the modeling tools for the research and management of fisheries.
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