Abstract
We aim to construct marine ecosystem models of the past for northern British Columbia as a component of a Back to the Future (BTF) project. In order to satisfy the immense data requirements of an Ecopath with Ecosim (EwE) model, it has been necessary to recruit unconventional sources of information. Local ecological knowledge (LEK) has been called upon to supplement scientific, archeological, and naturalist records, particularly when dealing with data-limited species. The BTF team interviewed forty-eight northern British Columbia community members in 2001-2002: mainly commercial, aboriginal, and recreational fishers. Our LEK database now contains detailed anecdotal information on fisheries and some 130 marine species. The changes in abundance perceived by fishers are of special importance as we try to gauge anthropogenic effects over time. Validation showed that LEK comments agree with formal stock assessments in only 37% of instances, although agreement improves with reported fishing experience. LEK seems best suited to detect long time-scale changes: LEK abundance trends correlate poorly with stock assessment in species that exhibit high inter-annual variability. Trends offered by respondents are more likely to contradict stock assessment if they were reporting a decrease in abundance. This indicates that respondents are more likely to err on the side of pessimism and/or stock assessment is more likely to err on the side of optimism. The use of LEK information to supplement standard data sources may become an important tool. Besides consolidating and preserving community perception, we may establish criteria by which we can assess the quality of scientific data, challenging it with an independent authority and identifying where fi shers’ perceptions depart from the scientific,understanding.
Original language | American English |
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Title of host publication | Fisheries Assessment and Management in Data-Limited Situations |
DOIs | |
State | Published - Jan 1 2005 |
Externally published | Yes |
Disciplines
- Life Sciences