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Productivity (Recruits-per-Spawner) Data for Sockeye, Pink, and Chum Salmon from British Columbia

author A.D. Ogden, J.R. Irvine, K.K. English, S. Grant, K.D. Hyatt, L. Godbout, and C.A. Holt
published year 2015
document type data
species chum, pink, sockeye
location British Columbia
subjects Productivity, Recruits-per-Spawner
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In order to be able to track patterns of salmon recruitment variability among salmon populations in British Columbia and to improve our understanding of the environmental and biological mechanisms that influence these patterns, we assembled productivity (i.e. recruits per spawner) estimates for British Columbian Sockeye, Pink, and Chum Salmon and provide these on a publicly accessible internet link. Annual estimates, by brood year, of spawner numbers, catch, and population and age composition were obtained from regional experts and organized in a simple database that we describe in this report. Time series were organized by species and biological or spatial unit (Conservation Unit, Pacific Fisheries Management Area, or aggregates of these). Data quality criteria that delineated three categories of data quality, unique to each data type (spawner, catch, and age structure estimates), were used to rate each data type by return year in each time series, and the overall recruit-per-spawner estimates were rated by brood year. The annual data quality ratings of the component data were then used to rate annual recruit-per-spawner data by species and biological or spatial unit and also to generate global estimates across all years for each time series. These data replace previously published estimates, given our more detailed exploration of temporal changes in both field assessment methods and data quality, where both will serve as a useful starting point to assist analysts with their interpretation of data reliability and results. Included in the report are two example plots of recruits-per-spawner time series. We recommend that these data be updated on a regular basis and consideration be given to expanding the dataset to other species and areas.