Dataset Information

Discrimination of juvenile yellowfin (Thunnus albacares) and bigeye (T. obesus) Tunas using mitochondrial DNA control region and liver morphology.

ABSTRACT: Yellowfin tuna, Thunnus albacares (Bonnaterre, 1788) and bigeye tuna, Thunnus obesus (Lowe, 1839) are two of the most economically important tuna species in the world. However, identification of their juveniles, especially at sizes less than 40 cm, is very difficult, often leading to misidentification and miscalculation of their catch estimates. Here, we applied the mitochondrial DNA control region D-loop, a recently validated genetic marker used for identifying tuna species (Genus Thunnus), to discriminate juvenile tunas caught by purse seine and ringnet sets around fish aggregating devices (FADs) off the Southern Iloilo Peninsula in Central Philippines. We checked individual identifications using the Neighbor-Joining Method and compared results with morphometric analyses and the liver phenotype. We tested 48 specimens ranging from 13 to 31 cm fork length. Morpho-meristic analyses suggested that 12 specimens (25%) were bigeye tuna and 36 specimens (75%) were yellowfin tuna. In contrast, the genetic and liver analyses both showed that 5 specimens (10%) were bigeye tuna and 43 (90%) yellowfin tuna. This suggests that misidentification can occur even with highly stringent morpho-meristic characters and that the mtDNA control region and liver phenotype are excellent markers to discriminate juveniles of yellowfin and bigeye tunas.

SUBMITTER: Pedrosa-Gerasmio IR

PROVIDER: S-EPMC3334917 | biostudies-literature | 2012

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Discrimination of juvenile yellowfin (Thunnus albacares) and bigeye (T. obesus) Tunas using mitochondrial DNA control region and liver morphology.

Pedrosa-Gerasmio Ivane R IR Babaran Ricardo P RP Santos Mudjekeewis D MD

PloS one 20120419 4

Yellowfin tuna, Thunnus albacares (Bonnaterre, 1788) and bigeye tuna, Thunnus obesus (Lowe, 1839) are two of the most economically important tuna species in the world. However, identification of their juveniles, especially at sizes less than 40 cm, is very difficult, often leading to misidentification and miscalculation of their catch estimates. Here, we applied the mitochondrial DNA control region D-loop, a recently validated genetic marker used for identifying tuna species (Genus Thunnus), to ...[more]

PMID: 22536417

Similar Datasets

Project description:Tuna fisheries catch over three million tonnes of skipjack tuna (Katsuwonus pelamis) each year, the majority of which come from purse-seine vessels targeting fish associated with man-made fish aggregating devices (FADs). A significant challenge for fisheries management is to maximize the efficiency of skipjack tuna catches whilst minimizing the bycatch of small and immature bigeye (Thunnus obesus) and yellowfin (T. albacares) tuna, for which long-term sustainability is uncertain in 75% of the world's stocks. To better manage the issues common with this fishing method, an improved understanding of tuna behaviour around FADs is necessary. We probabilistically classified the vertical behavioural patterns of 50 bigeye and 35 yellowfin tuna (mean fork length 72cm and 70cm, respectively) electronically tagged throughout the western and central Pacific Ocean into shallow and deep states, using a state-space modelling approach. The occurrence of surface-association behaviours, defined as an individual remaining in a shallow state for 24-hours, was examined in relation to known capture events and FAD density. In general, surface-association events for both species were short and lasted on average less than three days, although events as long as 28 days were observed, and were more common in yellowfin when in archipelagic waters. Events were longest immediately following tagging in 62% and 17% of bigeye and yellowfin, respectively. Surface-association behaviour was not generally estimated just prior to recapture, being either non-existent or shorter than two days for 85% of bigeye and 74% of yellowfin. Current management measures in purse-seine tuna fisheries involve periodic or spatial closures for FAD use. If the chief benefit to purse-seine fishers of surface-association around floating objects is in locating schools in horizontal space at short-term time-scales, rather than holding fish near the surface for extended periods, controlling the number of sets made on FADs should be explored further as an additional management tool.

Project description:Age estimates, typically determined by counting periodic growth increments in calcified structures of vertebrates, are the basis of population dynamics models used for managing exploited or threatened species. In fisheries research, the use of otolith growth rings as an indicator of fish age has increased considerably in recent decades. However, otolith readings include various sources of uncertainty. Current ageing methods, which converts an average count of rings into age, only provide periodic age estimates in which the range of uncertainty is fully ignored. In this study, we describe a hierarchical model for estimating individual ages from repeated otolith readings. The model was developed within a Bayesian framework to explicitly represent the sources of uncertainty associated with age estimation, to allow for individual variations and to include knowledge on parameters from expertise. The performance of the proposed model was examined through simulations, and then it was coupled to a two-stanza somatic growth model to evaluate the impact of the age estimation method on the age composition of commercial fisheries catches. We illustrate our approach using the sagittal otoliths of yellowfin tuna of the Indian Ocean collected through large-scale mark-recapture experiments. The simulation performance suggested that the ageing error model was able to estimate the ageing biases and provide accurate age estimates, regardless of the age of the fish. Coupled with the growth model, this approach appeared suitable for modeling the growth of Indian Ocean yellowfin and is consistent with findings of previous studies. The simulations showed that the choice of the ageing method can strongly affect growth estimates with subsequent implications for age-structured data used as inputs for population models. Finally, our modeling approach revealed particularly useful to reflect uncertainty around age estimates into the process of growth estimation and it can be applied to any study relying on age estimation.

Dataset Information

Discrimination of juvenile yellowfin (Thunnus albacares) and bigeye (T. obesus) Tunas using mitochondrial DNA control region and liver morphology.

Publications

Discrimination of juvenile yellowfin (Thunnus albacares) and bigeye (T. obesus) Tunas using mitochondrial DNA control region and liver morphology.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets