Local ecological knowledge predicting fish behaviour: a diverse and holistic approach to fish ecology
LE3 .A278 2021
Bachelor of Science
Current fisheries management is dominated by Western science. However, the incorporation of other knowledge systems is gaining inertia, used to diversify decision-making processes and offer additional information about species ecology. Through discussions with Mi’kmaq and Fisher members of the Apoqnmatulti’k project, a list of Local Ecological Knowledge links between fish behaviour and biological and physical variables was created. Two case studies were chosen and explored by using Western-Scientific data to strengthen our understanding of a cue provided by Local Ecological Knowledge holders. The first case study related the abundance of Atlantic sturgeon (Acipenser oxyrinchus oxyrinchus) in the Saint John River, New Brunswick, to the first harvest of hay. It was determined that the first harvest occurs in late May or early June. After the annual June mandated closure of the sturgeon fishery, the number caught increased. The highest numbers of aturgeon were generally seen in early July, and the number of females caught at this time dominated the number of males. This can be used as a low-cost predictor of behaviour and can indicate when you are likely to interact with the species. The second case study related the rainbow smelt (Osmerus mordax) run in the Gaspereau River, Nova Scotia, to moon phases. As the best fishing for smelt during their run was predicted to occur at the full or new moon. The Rayleigh’s Test of uniformity indicated a uniform distribution of start dates in the lunar cycle, showing no correlation. A Chi-squared test indicated no statistically significant difference between lunar phases. An additional analysis was completed, investigating a possible correlation between degree days of one and two weeks prior to the smelt run with the start date. This analysis demonstrated no relationship for either interval. These results could be for several reasons, including air temperatures being used as a proxy for water temperature increases variability, the short scale of the degree days used in the analysis, or lack of variability in the run date. These case studies wove a variety of knowledge types, rather than relying on one alone, and this model demonstrates potential for further investigation. Alternative knowledge systems were crucial in these analyses and the completion of this study.
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