Salmon age, sex, and length data from Arctic-Yukon-Kuskokwim Region of Alaska, 1960-2017

• Main Author: Fish, Alaska Department Of
• Format: Dataset
• Language: English
• Published: KNB Data Repository 2018
• Subjects: Arctic; Sockeye; Varden; Yukon; Kuskokwim; Longnose sucker; Alaska
• Online Access: https://dx.doi.org/10.5063/f14m92r0; https://knb.ecoinformatics.org/view/doi:10.5063/F14M92R0

Age, sex and length data provide population dynamics information that can indicate how populations trends occur and may be changing. These data can help researchers estimate population growth rates, age-class distribution and population demographics. Knowing population demographics, growth rates and trends is particularly valuable to fisheries managers who must perform population assessments to inform management decisions. These data are therefore particularly important in valuable fisheries like the salmon fisheries of Alaska. This dataset includes age, sex and length data compiled from annual sampling of commercial and subsistence salmon harvests and research projects in the Arctic-Yukon-Kuskokwim region of Alaska. It includes data on five salmon species: chinook, chum, coho, pink and sockeye. There is some data on non-salmon species (whitefish, sheefish, longnose sucker, Dolly Varden) in the Yukon dataset. There is an additional data table for more specific information about the locations where samples were collected. Age estimates were made by examining scales or bony structures (e.g. otoliths - ear bones). Scales were removed from the side of the fish; usually the left side above the lateral line. Scales or bony structures were then mounted on gummed cards and pressed on acetate to make an impression. The number of freshwater and saltwater annuli (i.e. rings) was counted to estimate age in years. Fish sex was determined by either examining external morphology (eg. head and belly shape) or internal sex organ. Length was measured in millimeters, generally from mid-eye to the fork of the tail. This data package includes the original data files, reformatting scripts that reformat the original data files into a consistent format, and the reformatted datasets.