Diets of top predators indicate pelagic juvenile rockfish ( Sebastesspp.) abundance in the California Current System

• Published in: Fisheries Oceanography
• Main Authors: MILLS, K. L., LAIDIG, T., RALSTON, S., SYDEMAN, W. J.
• Format: Article in Journal/Newspaper
• Language: English
• Published: Wiley 2007
• Subjects: Common Murre; Uria aalge; uria
• Online Access: http://dx.doi.org/10.1111/j.1365-2419.2007.00429.x; https://api.wiley.com/onlinelibrary/tdm/v1/articles/10.1111%2Fj.1365-2419.2007.00429.x; https://onlinelibrary.wiley.com/doi/pdf/10.1111/j.1365-2419.2007.00429.x

ABSTRACT Diets of top predators may be useful indicators to the availability of forage fish in marine ecosystems. Juvenile rockfish (young‐of‐the‐year Sebastes spp.) compose a significant part of the diet for many predators in the central California Current, including chinook salmon ( Oncorhynchus tshawytscha ), and several species of marine birds and mammals. Herein, we develop annual indices of juvenile rockfish relative abundance by collating time series data sets on: (i) the proportion of rockfish in the diet of three species of seabirds breeding on Southeast Farallon Island (1975–2002); (ii) the number of rockfish in chinook salmon stomachs (1980–99); and (iii) the abundance of rockfish captured in scientific mid‐water trawl net surveys (1983–2002). We used Principal Component Analysis (PCA) to combine indices, and refer to these as ‘Multivariate Rockfish Indices’ (MRI). Combining time series verifies the patterns shown by each alone and provides a synoptic perspective on juvenile rockfish relative abundance. The diets of predators with the largest foraging ranges (Common Murre, Uria aalge ) and chinook salmon co‐varied strongly with the net samples, and appear to be the best indicators. The salmon also sampled species of Sebastes not caught in the nets. The MRI reveals interannual variability in juvenile rockfish abundance, a substantial decline in abundance in the 1990s, and a partial recovery in the early 2000s. Predator‐based sampling is a cost‐effective enhancement of scientific net sampling.