Data reconstruction can improve abundance index estimation: An example using Taiwanese longline data for Pacific bluefin tuna.

Catch-per-unit-effort (CPUE) is often the main piece of information used in fisheries stock assessment; however, the catch and effort data that are traditionally compiled from commercial logbooks can be incomplete or unreliable due to many reasons. Pacific bluefin tuna (PBF) is a seasonal target species in the Taiwanese longline fishery. Since 2010, detailed catch information for each PBF has been made available through a catch documentation scheme. However, previously, only market landing data with a low coverage of logbooks were available. Therefore, several nontraditional procedures were performed to reconstruct catch and effort data from many alternative data sources not directly obtained from fishers for 2001-2015: (1) Estimating the catch number from the landing weight for 2001-2003, for which the catch number information was incomplete, based on Monte Carlo simulation; (2) deriving fishing days for 2007-2009 from voyage data recorder data, based on a newly developed algorithm; and (3) deriving fishing days for 2001-2006 from vessel trip information, based on linear relationships between fishing and at-sea days. Subsequently, generalized linear mixed models were developed with the delta-lognormal assumption for standardizing the CPUE calculated from the reconstructed data, and three-stage model evaluation was performed using (1) Akaike and Bayesian information criteria to determine the most favorable variable composition of standardization models, (2) overall R2 via cross-validation to compare fitting performance between area-separated and area-combined standardizations, and (3) system-based testing to explore the consistency of the standardized CPUEs with auxiliary data in the PBF stock assessment model. The last stage of evaluation revealed high consistency among the data, thus demonstrating improvements in data reconstruction for estimating the abundance index, and consequently the stock assessment.

Complete mitogenome of three flyingfishes Cheilopogon unicolor, Cheilopogon arcticeps and Cheilopogon atrisignis (Teleostei: Exocoetidae).

The complete mitogenomes of Cheilopogon unicolor, C. arcticeps and C. atrisignis were determined by the next-generation sequencing (NGS) method. The assembled mitogenome of C. unicolor, C. arcticeps and C. atrisignis consist of 16 529 bp, 16 530 bp and 16 530 bp, respectively. Three mitogenomes contain the typical gene complement including 13 protein-coding genes, 22 transfer RNAs, two ribosomal RNA genes and a non-coding D-loop. The length of D-loop is 870 bp (C. unicolor and C. arcticeps) and 869 bp (C. atrisignis), located between tRNA-Pro and tRNA-Phe. Phylogenetic analysis indicates that Cheilopogon is not monophyly. The mitogenomes of C. unicolor, C. atrisignis and C. arcticeps may provide useful information for phylogentic and population genetic analysis for flyingfishes.

Population structure of Hirundichthys oxycephalus in the northwestern Pacific inferred from mitochondrial cytochrome oxidase I gene.

BACKGROUND: Hirundichthys oxycephalus is an important flyingfish resource in eastern Taiwan and northwestern Japan. A substantial catch decline in Taiwan has caused serious concerns on stock status of the fish, prompting the government to impose a set of regulations on flyingfish egg fishery since 2008. However, the regulations were set in a precautionary manner, without considering the fundamental understanding of the population genetic structure. This study aims to investigate the population genetic structure of H. oxycephalus in the region based on mtDNA cytochrome oxidase I (COI) gene and to thus provide scientific information for sustainable management of theresource. RESULTS: Tissue samples (156) from six localities of eastern Taiwan and western Japan were collected, and 616 bpof mtDNA COI gene were sequenced. Seventy haplotypes were determined, and the haplotype diversity and nucleotide diversity were estimated as 0.93% and 0.57%, respectively. Results of various statistical analyses suggested that the genetic differentiations among the six localities were small and most variation occurred within populations, indicating a high gene flow in the region with undergoing population expansion. Although the study showed that the fishes were genetically divided into two groups, the support was low and the separation was not geologically evident. CONCLUSIONS: Thestudy revealed two groups of H.oxycephalus inthe northwestern Pacific Ocean. However, due to high gene flow, an association of either group to a spatial distribution was not observed, and so the two groups may be considered as one population. Thus, the results favored the conclusion that H. oxycephalus from eastern Taiwan and western Japan belong to the same population and, consequently, that the management unit of the current regulations only covering eastern Taiwan does not match the spatial structure of the population. Rather, the results suggest that joint efforts from countries within the population boundary are necessary to maintain a sustainable exploitation.