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Research about Thunder Bay

Source-linked reports with geographic coverage including Thunder Bay.

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Evaluating the sustainability of a cisco fishery in Thunder Bay, Ontario, under alternative harvest policies

Sustainable management of fish stocks is promoted through the application of management strategy evaluations (MSEs), providing information to managers on the relative performance of alternative management approaches (strategies) while accounting for uncertainty. In this study, we developed a simplified MSE of a stock of Cisco Coregonus artedi in Thunder Bay, Ontario, to determine both the sustainability of the current harvest control rule (i.e., a constant exploitation rate [ U ] of 10%) and the performance of alternative harvest control rules in meeting fishery objectives. Success in meeting fishery objectives was evaluated through attained yields, interannual variation in yields, magnitude of spawning stock biomass (SB), and the risk of reaching low SB—performance metrics established based on consultation with an advisory group to Lake Superior fishery managers. Our simulations explicitly accounted for uncertainty in the frequency of strong year‐classes being produced by Cisco, the stock–recruit relationship, stock abundance, and the sex‐specific nature of roe harvest. Assuming that future productivity is similar to the productivity observed over the period from 1985 to 2015, results suggest that the current U of 10% is sustainable in terms of maintaining SB above 20% of the unfished level. Variants of constant U control rules that included thresholds defining when U is to decrease as a function of SB increased yield, decreased risk, and increased the magnitude of SB at the end of the simulation period. However, these advantages came at the expense of greater interannual variation in yield. Constant catch control rules greatly underperformed constant U control rules in terms of magnitude in yield; however, they did reduce interannual variation in yield compared to constant U control rules. Furthermore, conditional versions of constant catch control rules (i.e., threshold stock sizes below which the catch limit was reduced) mitigated risks of staying at low stock size.

Thunder Bay

A comparison of age- and size-structured assessment models applied to a stock of cisco in Thunder Bay, Ontario

Stock assessments are critical to modern fisheries management, supporting the calculation of key reference variables used to make informed management decisions. However, there is still considerable uncertainty as to which class of assessment models is appropriate to use under different circumstances. A common class of models used when age data are available are statistical catch-at-age assessment (SCAA) models, which track annual cohorts through time. When age data are unavailable, as is often the case in invertebrate fisheries where the lack of a bony structure such as otoliths makes aging difficult, statistical catch-at-size assessment (SCSA) models are more often employed, tracking fish or invertebrates through time by size-classes rather than ages. Do SCAA models actually perform better than SCSA models when age data are available, or is this just an assumption we make in fisheries research and management? We examined this question by evaluating the effectiveness of both SCAA and SCSA models in characterizing cisco, Coregonus artedi , population dynamics in Thunder Bay, Ontario. Both models were fit using an integrated framework with multiple sources of data including hydroacoustic estimates of spawning stock, fishery-dependent and -independent age/length compositions, and harvest data. Our results suggest that for cisco in Thunder Bay, data-limitations related to lack of size-composition data over the size range for which cisco growth is rapid resulted in difficulty estimating relative year-class strength within a SCSA. This led to parameter confounding and ultimately the inability to estimate natural mortality within a SCSA. This hampered the utility of a SCSA model in comparison with a SCAA model when age-composition data were available.

Ontario

How systematic age underestimation can impede understanding of fish population dynamics: Lessons learned from a Lake Superior cisco stock

Systematic underestimation of fish age can impede understanding of recruitment variability and adaptive strategies (like longevity) and can bias estimates of survivorship. We suspected that previous estimates of annual survival ( S ; range = 0.20-0.44) for Lake Superior ciscoes Coregonus artedi developed from scale ages were biased low. To test this hypothesis, we estimated the total instantaneous mortality rate of adult ciscoes from the Thunder Bay, Ontario, stock by use of cohort-based catch curves developed from commercial gill-net catches and otolith-aged fish. Mean S based on otolith ages was greater for adult females (0.80) than for adult males (0.75), but these differences were not significant. Applying the results of a study of agreement between scale and otolith ages, we modeled a scale age for each otolith-aged fish to reconstruct catch curves. Using modeled scale ages, estimates of S (0.42 for females, 0.36 for males) were comparable with those reported in past studies. We conducted a November 2005 acoustic and midwater trawl survey to estimate the abundance of ciscoes when the fish were being harvested for roe. Estimated exploitation rates were 0.085 for females and 0.025 for males, and the instantaneous rates of fishing mortality were 0.089 for females and 0.025 for males. The instantaneous rates of natural mortality were 0.131 and 0.265 for females and males, respectively. Using otolith ages, we found that strong year-classes at large during November 2005 were caught in high numbers as age-1 fish in previous annual bottom trawl surveys, whereas weak or absent year-classes were not. For decades, large-scale fisheries on the Great Lakes were allowed to operate because ciscoes were assumed to be short lived and to have regular recruitment. We postulate that the collapse of these fisheries was linked in part to a misunderstanding of cisco biology driven by scale-ageing error.

Thunder Bay