Williams Benjamin C, Kruse Gordon H, Dorn Martin W
College of Fisheries and Ocean Sciences, University of Alaska Fairbanks, Juneau, Alaska, United States of America.
NOAA National Marine Fisheries Service, Alaska Fisheries Science Center, Seattle, Washington, United States of America.
PLoS One. 2016 Oct 13;11(10):e0164797. doi: 10.1371/journal.pone.0164797. eCollection 2016.
Catch quotas for walleye pollock Gadus chalcogrammus, the dominant species in the groundfish fishery off Alaska, are set by applying harvest control rules to annual estimates of spawning stock biomass (SSB) from age-structured stock assessments. Adult walleye pollock abundance and maturity status have been monitored in early spring in Shelikof Strait in the Gulf of Alaska for almost three decades. The sampling strategy for maturity status is largely characterized as targeted, albeit opportunistic, sampling of trawl tows made during hydroacoustic surveys. Trawl sampling during pre-spawning biomass surveys, which do not adequately account for spatial patterns in the distribution of immature and mature fish, can bias estimated maturity ogives from which SSB is calculated. Utilizing these maturity data, we developed mixed-effects generalized additive models to examine spatial and temporal patterns in walleye pollock maturity and the influence of these patterns on estimates of SSB. Current stock assessment practice is to estimate SSB as the product of annual estimates of numbers at age, weight at age, and mean maturity at age for 1983-present. In practice, we found this strategy to be conservative for a time period from 2003-2013 as, on average, it underestimates SSB by a 4.7 to 11.9% difference when compared to our estimates of SSB that account for spatial structure or both temporal and spatial structure. Inclusion of spatially explicit information for walleye pollock maturity has implications for understanding stock reproductive biology and thus the setting of sustainable harvest rates used to manage this valuable fishery.
阿拉斯加底层鱼类渔业中的主要物种狭鳕(Gadus chalcogrammus)的捕捞配额,是通过将捕捞控制规则应用于基于年龄结构的种群评估得出的产卵群体生物量(SSB)年度估计值来设定的。近三十年来,每年早春都会在阿拉斯加湾的谢利科夫海峡监测成年狭鳕的数量和成熟状态。成熟状态的采样策略在很大程度上被描述为在水声调查期间对拖网捕捞进行有针对性的(尽管是机会性的)采样。在产卵前生物量调查期间进行的拖网采样,没有充分考虑未成熟和成熟鱼类分布的空间模式,可能会使用于计算SSB的估计成熟度曲线产生偏差。利用这些成熟度数据,我们开发了混合效应广义相加模型,以研究狭鳕成熟度的空间和时间模式,以及这些模式对SSB估计值的影响。当前的种群评估做法是将1983年至今各年龄组的数量、各年龄组的体重和各年龄组的平均成熟度的年度估计值相乘来估计SSB。在实践中,我们发现这种策略在2003年至2013年期间较为保守,因为与我们考虑空间结构或时空结构的SSB估计值相比,平均而言,它低估了SSB 4.7%至11.9%。纳入狭鳕成熟度的空间明确信息对于理解种群繁殖生物学以及因此对于管理这一重要渔业所使用的可持续捕捞率的设定具有重要意义。