Growth estimation for a shared stock under uneven size-at-age coverage: classical and Bayesian von Bertalanffy models for whiting, Merlangius merlangus
Hydrobiologia, 2026 (SCI-Expanded, Scopus)
- Yayın Türü: Makale / Tam Makale
- Basım Tarihi: 2026
- Doi Numarası: 10.1007/s10750-026-06420-8
- Dergi Adı: Hydrobiologia
- Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus, BIOSIS, CAB Abstracts, Environment Index, Geobase, Public Affairs Index, Zoological Record, Academic Search Ultimate (EBSCO), Natural Science Collection (ProQuest), Biological Science Database (ProQuest), Biomedical Reference Collection: Corporate Edition (EBSCO), Engineering Source (EBSCO), Pharma Collection (ProQuest)
- Anahtar Kelimeler: Bayesian inference, Black Sea, Growth, Merlangius merlangus, Natural mortality, Otolith age reading
- Orta Doğu Teknik Üniversitesi Adresli: Evet
Özet
Whiting in the Black Sea is assessed as a single shared stock within the General Fisheries Commission for the Mediterranean framework using biological data provided by the riparian countries. Because these data originate from different national monitoring programmes, uneven size coverage may influence growth estimation. To evaluate the implications of such data limitations, a harmonised multinational age–length dataset from Bulgaria, Georgia, Romania, and Türkiye was analysed using both classical and Bayesian von Bertalanffy growth models. Jointly standardised otolith readings were used to minimise reader-related bias, while biologically informed priors were incorporated in the Bayesian framework to stabilise estimation where parts of the size spectrum were poorly represented. Bayesian estimates were less affected by truncated size distributions while preserving the main growth patterns observed in the classical analyses. Although similar regional patterns were evident under both modelling approaches, the available data do not allow the relative contributions of sampling structure and biological variation to be distinguished. Growth-based natural mortality trajectories further demonstrated that differences in growth estimates propagate into assessment parameters. These findings highlight the value of Bayesian growth modelling for shared stock assessments based on heterogeneous multinational datasets, while emphasising the need for cautious biological interpretation when sampling coverage is uneven.