An index of relative biomass, abundance, and condition of juvenile Pacific Herring (Clupea
pallasi) in the Strait of Georgia, British Columbia
Jennifer L. Boldt1, Matthew Thompson1, Charles Fort1, Chris Rooper2, Jake Schweigert1,
Terrance J. Quinn II3, Doug Hay1 and Thomas W. Therriault1
1
Fisheries and Oceans Canada, Nanaimo, Canada. E-mail: Jennifer.Boldt@dfo-mpo.gc.ca
National Marine Fisheries Service, Alaska Fisheries Science Center, Seattle, USA
3
Juneau Center, School of Fisheries and Ocean Sciences, University of Alaska Fairbanks,
Juneau, USA
2
Small pelagic fish, such as Pacific Herring (Clupea pallasi), are an important prey species for a
variety of predators and, in the case of herring, are also culturally, commercially, and
recreationally important. Herring abundance can be affected by the carrying capacity of the
ecosystem, and by a variety of factors affecting survival and recruitment to the adult population.
To understand which factors influence herring first requires a time series of the relative
abundance of herring. British Columbia’s Strait of Georgia juvenile herring and nearshore
pelagic ecosystem survey has collected data from ten core transects in September-October since
1992. This time-series can be used to estimate the relative abundance of age-0 herring,
potentially forecast recruitment to the adult spawning population, and represent trends in prey
availability to predators, such as salmon. The objectives of this report were to: 1.) update the
time series and identify suitable data and statistical methods for estimating an index (and
associated variance) of the relative biomass or abundance of age-0 herring, 2.) compare survey
estimates of age-0 herring biomass (abundance) to stock assessment model estimates of
recruitment, and 3.) examine trends in herring condition (length-weight residuals) which may
have implications for herring survival and for predators of herring. To calculate unbiased
estimates of the relative biomass (abundance) of age-0 herring, we applied two methods (twostage and two-stage stratified) to a variety of data types for three scenarios (based on
assumptions about nets used). Based on these results, we make several recommendations for the
survey.