Seabird diets as bioindicators of Atlantic herring recruitment and stock size: a new tool for ecosystem-based fisheries management
Ecosystem-based fishery management requires understanding of relationships between exploited fish and their predators, such as seabirds. We used exploratory regression analyses to model relationships between Atlantic herring (Clupea harengus) in the diet of seabird chicks at nine nesting colonies in...
Published in: | Canadian Journal of Fisheries and Aquatic Sciences |
---|---|
Main Authors: | , , , , |
Format: | Article in Journal/Newspaper |
Language: | English |
Published: |
Canadian Science Publishing
2018
|
Subjects: | |
Online Access: | http://dx.doi.org/10.1139/cjfas-2017-0140 http://www.nrcresearchpress.com/doi/full-xml/10.1139/cjfas-2017-0140 http://www.nrcresearchpress.com/doi/pdf/10.1139/cjfas-2017-0140 |
Summary: | Ecosystem-based fishery management requires understanding of relationships between exploited fish and their predators, such as seabirds. We used exploratory regression analyses to model relationships between Atlantic herring (Clupea harengus) in the diet of seabird chicks at nine nesting colonies in the Gulf of Maine and four types of fishery- and survey-derived herring data. We found several strong relationships, which suggests spatial structuring in herring stocks and likely patterns of herring movements before they recruit into the fishery. Some types of herring data seldom used in stock assessments — notably acoustic surveys, fixed-gear landings, and mass-at-age (i.e., weight-at-age) — correlated as strongly with seabird data as more commonly used series, such as mobile-gear landings and modeled spawning stock biomass. Seabird chick diets collected at specific locations thus offer a promising means to assess the size, distribution, and abundance of juvenile herring across a broad area prior to recruitment, which is a major source of uncertainty in fisheries. Common terns (Sterna hirundo) showed the most potential as a bioindicator, correlating well and showing consistent spatial patterns with 11 of 13 fishery data series. |
---|