Using age compositions derived from spatio-temporal models and acoustic data collected by uncrewed surface vessels to estimate Pacific hake (Merluccius productus) biomass-at-age

Frontiers in Marine Science

Marine Science

Derek G. Bolser¹  Lorenzo Ciannelli²  Rebecca E. Thomas³  John Wallace³  Jim Hastie³  John Pohl³  Dezhang Chu³  Steve de Blois³  Julia Clemons⁴  Aaron M. Berger⁴ 

[1] Cooperative Institute for Marine Ecosystem and Resources Studies, Oregon State University, Newport, OR, United States;Cooperative Institute for Marine Ecosystem and Resources Studies, Oregon State University, Newport, OR, United States;College of Earth, Ocean, and Atmospheric Studies, Oregon State University, Corvallis, OR, United States;Fisheries Research Analysis and Monitoring Division, Northwest Fisheries Science Center, National Marine Fisheries Service, National Oceanic and Atmospheric Administration, Seattle, WA, United States;Fishery Resource Analysis and Monitoring Division, Northwest Fisheries Science Center, National Marine Fisheries Service, National Oceanic and Atmospheric Administration, Newport, OR, United States;

关键词: USV;    acoustic-trawl survey;    spatio-temporal model;    VAST;    Pacific hake;    biomass estimation;    fishery-independent survey;    age composition;   

DOI  :  10.3389/fmars.2023.1214798

 received in 2023-04-30, accepted in 2023-08-21,  发布年份 2023

来源: Frontiers

【 摘 要 】

Generating biomass-at-age indices for fisheries stock assessments with acoustic data collected by uncrewed surface vessels (USVs) has been hampered by the need to resolve acoustic backscatter with contemporaneous biological (e.g., age) composition data. To address this limitation, Pacific hake (Merluccius productus; “hake”) acoustic data were gathered from a USV survey (in 2019) and acoustic-trawl survey (ATS; 2019 and eight previous years), and biological data were gathered from fishery-dependent and non-target (i.e., not specifically targeting hake) fishery-independent sources (2019 and eight previous years). To overcome the lack of contemporaneous biological sampling in the USV survey, age class compositions were estimated from a generalized linear mixed spatio-temporal model (STM) fit to the fishery-dependent and non-target fishery-independent data. The validity of the STM age composition estimation procedure was assessed by comparing estimates to age compositions from the ATS in each year. Hake biomass-at-age was estimated from all combinations of acoustics (USV or ATS in 2019, ATS only in other years) and age composition information (STM or ATS in all years). Across the survey area, proportional age class compositions derived from the best STM differed from ATS observations by 0.09 on average in 2019 (median relative error (MRE): 19.45%) and 0.14 across all years (MRE: 79.03%). In data-rich areas (i.e., areas with regular fishery operations), proportional age class compositions from the STM differed from ATS observations by 0.03 on average in 2019 (MRE: 11.46%) and 0.09 across years (MRE: 54.96%). On average, total biomass estimates derived using STM age compositions differed from ATS age composition-based estimates by approximately 7% across the study period (~ 3% in 2019) given the same source of acoustic data. When biomass estimates from different sources of acoustic data (USV or ATS) were compared given the same source of age composition data, differences were nearly ten-fold greater (22% or 27%, depending on if ATS or STM age compositions were used). STMs fit to non-contemporaneous data may provide suitable information for assigning population structure to acoustic backscatter in data-rich areas, but advancements in acoustic data processing (e.g., automated echo classification) may be needed to generate viable USV-based estimates of biomass-at-age.

【 授权许可】

Unknown   
Copyright © 2023 Bolser, Berger, Chu, de Blois, Pohl, Thomas, Wallace, Hastie, Clemons and Ciannelli