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Title: Methods for Combining Ichthyoplankton Datasets for Predicting Annual Larval Fish Abundances in the Gulf of Alaska
NOAA’s Alaska Fisheries Science Center’s (AFSC) Ecosystems and Fisheries-Oceanography Coordinated Investigations (EcoFOCI) program has collected spring ichthyoplankton abundance data in the Gulf of Alaska since 1981. Collections were made nearly annually until 2011 when sampling was reduced to only odd years. This dataset is used to better understand population recruitment of major fish species in the GOA and provides early warning of potential year-class strength to inform fisheries management. However, gaps in the time series during even years have made it more difficult to interpret the interannual variability of ichthyoplankton abundance in such a dynamic ecosystem. Recent collaboration with the Northern Gulf of Alaska Long Term Ecological Research (NGA LTER) program has allowed for additional spring sampling of ichthyoplankton in the GOA annually since 2018. Larval fish data collected by the NGA LTER were combined with EcoFOCI data and used to estimate abundance in years when EcoFOCI had no field presence in the GOA. Five taxa were determined to be suitable for this approach based on their percent occurrence in both surveys. A generalized additive model (GAM) was fit to ichthyoplankton data from 1981 to 2022 collected by both EcoFOCI and NGA LTER and used to predict larval abundances in 2018, 2020, and 2022. For each species, models with two different error distributions were compared and shown to produce similar predictions of larval abundance. This report provides a model framework for predicting interannual larval fish abundance while controlling for differences in sampling methodologies, timing, and location, and identifies a subset of taxa for which this framework is currently appropriate. As additional years of concurrent sampling are added in future, this approach has the potential to improve our understanding of interannual variation in ichthyoplankton dynamics and provide more comprehensive indicators for ecosystem-based fisheries management.  more » « less
Award ID(s):
2222376
PAR ID:
10533487
Author(s) / Creator(s):
; ;
Publisher / Repository:
NOAA Technical Memorandum
Date Published:
Edition / Version:
NMFS-TM-AFSC-485
Page Range / eLocation ID:
1-29
Subject(s) / Keyword(s):
biological oceanography plankton longterm monitoring program
Format(s):
Medium: X
Sponsoring Org:
National Science Foundation
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