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- HRM Program: Scales as growth history records for Pacific herring 13120111-N
Project Information
Title: HRM Program: Scales as growth history records for Pacific herring 13120111-N
Project Year and Number: 2013: 13120111-N
Other Fiscal Years and Numbers for this Project: 2012: 12120111-N
Principal Investigator (PI): Steve Moffitt
Managing Agency: ADFG
Assisting Personnel: None
Project Website: https://pwssc.org/scales-as-growth-history-records/
Research Location: Prince William Sound
Restoration Category: Research
Injured Resources Addressed: Pacific Herring
Abstract:Robust Pacific herring (Clupea pallasii) populations, suitable for exploitation by commercial fisheries, are typically sustained by periodic recruitment of strong year classes into the adult spawning population. However, the Prince William Sound (PWS) herring population has not had a strong recruitment class since 1989, when the Exxon Valdez Oil Spill (EVOS) occurred. Identification of conditions limiting herring recovery requires a series of focused process studies combined with monitoring of the natural conditions that affect herring survival. Fish grow in response to the extrinsic influences of their environment constrained by the intrinsic influences of genetic predisposition for growth and of size already attained. Understanding how these intrinsic and extrinsic sources of variability influence growth is important for several reasons. Variation in growth has a strong affect on the selection of appropriate harvest policies that are based on demographic models that reflect the natural processes. Analysis of growth increments between annular patterns on scales can provide a means to reconstruct past growth changes that can assist in determining the possible environmental and density-dependent causes of growth variation. Growth increment information incorporates a longitudinal history of growth that increases the effective degrees of freedom and can be used in modeling changes in growth in relationship to environmental and population indices Determining the underlying distribution of individual growth patterns can provide improved inputs into population dynamics models that are used to establish harvest guidelines.
Proposal: View (114 KB)
Reports:
Final Report: View (352 KB)
Publications from this Project: None Available