An evaluation of alternative assessment approaches for intermixing fish populations: a case study with Great Lakes lake whitefish

We used simulation modeling to explore how three statistical catch-at-age approaches for assessing intermixed fisheries performed in terms of assessment accuracy andmanagement performance, under differing productivity, mixing, and harvest levels. Simulations were based on intermixing lakewhitefish (Coregonus clupeaformis) populations in theupper LaurentianGreat Lakes ofNorthAmerica.We found thatwith intermixing, the “separate” assessment approach, which ignored intermixing and treatedmixed populations as unit stocks, produced biased estimates of spawning stock biomass (SSB); however, the “pooled” assessment approach, which lumped populations and assessed them as a single stock, was nearly unbiased in estimating SSB. The “overlap” assessment approach, which estimated the populations in one combined assessment model by incorporating actual mixing rates, was most strongly biased in estimating SSB in the absence of mixing, with bias decreasing asmixing levels increased.With highmixing levels, the overlapmethodhaddifficulty converging onunique solutions. The pooled approachprovidedbettermanagement performance than the separate approachwith intermixing.When the overlapmethod could be applied, it provided the greatest SSBwith little reductions in yield and the lowest inter-annual variation in yield. Relative performances of the assessment approaches were robust to assumed harvest levels.