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Age and growth of yellowfin tuna (Thunnus albacares) from the western and central pacific ocean as indicated by daily growth increments and tagging data
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... When all the parameters were considered at the same time, the equations did not converge. Therefore, in the estimation of parameters for each animal, one parameter was fixed to obtain a reasonable estimate of the two other parameters according to the method of Lehodey and Leroy (1999). ...
... Researchers have previously used a similar approach in which they settled one parameter at a presumed value rather than estimating it. Lehodey and Leroy (1999) estimated growth parameters according to the Bertalanffy growth model with K fixed and K varying. In our study, we used a two-step approach as proposed by Petráš et al. (2014). ...
The objectives of this study were a) to compare growth functions for describing the early growth curve of Romane sheep based on weighing records, b) to estimate the heritability of the growth curve parameters, and c) to estimate genetic parameters for 90-days-old bodyweight utilizing the data of earlier age. The raw data included 662 lambs (316 males and 346 females) bred at the Romane Sheep Research Center, INRAE, France. The studied trait was the bodyweight of lambs at birth, 15, 21, 35, 60, and 90 days of age. The number of measurements was approximately six for each animal. Dataset after mining consisted of 3261 weight records of 574 lambs. We applied four non-linear growth functions, including Gompertz, Brody, Logistic, and Richards. The goodness of fit for each equation was compared using the Akaike information criterion (AIC), coefficient of determination (R 2) and residual mean square (MSE). Predicting abilities of the included models were evaluated by comparing the predicted and observed phenotypes until 90 days of age. Genetic parameters of the non-linear functions were obtained using a specific two steps approach; in first step, the parameters of the different functions were estimated, and in the second, the parameters were considered as observations and we analyzed them using a multiple trait animal models. Residual mean square and R 2 for the models of Brody, Gompertz, Logistic and Richards were 106.71 and 0.37, 4.79 and 0.94, 7.41 and 0.88, and 9.04 and 0.88, respectively. The Logistic function had the smallest AIC and MSE values, and also had the highest R 2 value, indicating the best fit. The estimated heritability of the parameters in the logistic function were low (ranging from 0.007 to 0.017). In our study, the correlation between BV90 and BV35 was 0.54 with a confidence interval of 0.47-0.61. Since BV90 and BV35 have a positive genetic correlation, BV35 could be used to select the lambs for best growth until the slaughter age of Romane using the Logistic model.
... In particular, some growth studies conducted in the Atlantic, Indian and Western-Central Pacific Oceans support a two-stanza growth pattern with a sharp acceleration in growth rate at about 60-65 cm fork length Eveson et al., 2015;Gascuel et al., 1992;Lehodey and Leroy, 1999). ...
... Tropical tuna growth is the major focus of current research in the Pacific Ocean (Farley et al., 2018). In the Western-Central Pacific Ocean, the growth model used for assessing the stock of YFT predicts a growth rate slowing between about 40 and 70 cm, similarly to that observed in the Indian Ocean (Lehodey and Leroy, 1999;Tremblay-Boyer et al., 2017). Changes in configuration of the YFT population model also suggest some regional differences in estimated growth rates consistently with direct age estimates and mark-recapture experiments (Tremblay-Boyer et al., 2017). ...
... It is commonly assumed that TS depends on fish size according to a specific relationship (Eq. 1 ), with two parameters that are defined as a function of the growth rate of the resonance organs relative to the growth rate of the fish. To date it has been widely accepted that yellowfin tuna of under nearly 2 kg do not have a gas-filled swimbladder (Magnuson 1973 , Lehodey andLeroy 1999 ), with the uncertainty that this may introduce into TS-length estimates. However, in this study, there was one specimen in set 1 that weighted under 2 kg ( Table 3 ) and had a well-developed swimbladder as observed on radiographs. ...
Tropical tuna fisheries support some of the largest artisanal and industrial fisheries worldwide. Approximately 37% of the tropical tuna catch by industrial purse seiners is obtained from tuna associated with drifting fish aggregating devices (DFADs), where three tuna species coexist: skipjack (Katsuwonus pelamis), bigeye (Thunnus obesus), and yellowfin tuna (Thunnus albacares), with stocks subject to different health status. Purse seine fishers heavily rely on acoustic technology to detect and assess the quantity of tuna at DFADs. Yet, accurately distinguishing between species using solely acoustic methods is limited by insufficient knowledge about each species' acoustic response across frequencies. This study was carried out on six swimbladdered individuals belonging to two sets with mean lengths of 51.9 ± 9.5 and 52.9 ± 2 cm. It focuses on the frequency response obtained from ex situ measurements of yellowfin tuna recorded at 38, 70, 120, and 200 kHz, which revealed a flat response across frequencies, with b20 values of −72.4 ± 9, −73.2 ± 8, -72.3 ± 8, and −72.3 ± 9 dB, respectively. These results, contrast with previous findings on bigeye and skipjack, demonstrating the discrimination potential of acoustics in these three species. To harness this potential, a discrimination algorithm was developed.
... Based on the data, it can be seen that the catch is dominated by YFT with sizes below the proper catch size, reflected by the Lc value obtained, 65.7 cm. It is known that the value of Lm of YFT in the Indian Ocean is in the range of 100-110 cm (Lehodey & Leroy 1999;FAO 2010), while in the tropical western and central Pacific the value of Lm is higher, namely above 110 cm for males and 119 cm for females (Shi et al 2022). Different Lm values can be caused by stressors from the environment or from the fish itself (Arula et al 2017). ...
The production of yellowfin tuna (Thunnus albacares) in West Nusa Tenggara (NTB) Province has continued to increase from 2011 to 2021. The data from the Indian Ocean Tuna Commission (IOTC) shows that yellowfin tuna (YFT) originating from the Indian Ocean has been over-exploited since 2018. Thus, it is necessary to carry out research related to the biology of YFT, to aid making fisheries management policies. The data collection was carried out at the Labuhan Lombok Fishing Port. The primary data were collected from 2017 to 2021. The data were collected using stratified sampling for the size of tuna fishing vessels and systematic sampling for YFT <10 kg in size. The length frequency, the relationship between length and weight of fish, length at first catch, growth parameters, mortality, and exploitation rate were determined. The results of this study indicate that the growth of YFT landed at the Labuhan Lombok Fishing Port is negatively allometric. The size of the dominant YFT caught and landed was under 100 cm, with a length of 65.7 cm at first catch. The YFT growth parameters were: growth coefficient (K), of 0.28 year-1 and maximum body length (L∞), of 176.4 cm, with a fishing mortality rate (F) of 0.19 year-1 and a natural mortality rate (M) of 0.48 year-1. The exploitation rate (Z) of YFT landed at the Labuhan Lombok Fishing Port was 0.28.
... The longevity of yellowfin tuna can be 18 years [25]. The first phase of growth is slow until the fork length reaches 65~75 cm [24,26,27]. In the second phase, the growth rate reaches a peak, and then decreases when individuals grow to~145 cm. ...
Fishery stock assessment requires accurate specification of the growth function of target species, and aging uncertainty is an important factor that affects the estimation of growth parameters. In this study, we used simulations to study the effects of two types of aging uncertainty, aging error and sampled age range, on the parameter estimation of the Von Bertalanffy growth function, including asymptotic length (L∞), growth coefficient (k), and theoretical age in the year at zero length (t0) of five important tuna species. We found that the uncertainty of the estimated growth curves increased with increasing aging errors. When aging errors were fixed among ages, the effects of age range on estimation error of growth parameters were different among species and growth parameters. When the aging error increased with age, the estimation uncertainty of L∞ and k was the greatest when only young age groups were sampled, while the estimation uncertainty of t0 was the greatest when only old age groups were sampled. Therefore, reducing the aging error and sampling individuals with a wider age range are important for increasing the accuracy and decreasing the uncertainty of the estimated growth function, which will further reduce the uncertainty in fishery stock assessment.
... However, closer examination of these studies demonstrates one of the risks with the meta-analysis approach. The M estimates for tropical tunas are based on the Hampton (2000) Western Pacific tagging study discussed above, including an M estimate for yellowfin tuna of 1.085 year − 1 , and A max of 7 years (Lehodey and Leroy, 1999). The tagging estimates of M are likely biased (see above) and subsequent ageing using annual increments has more than doubled this estimate of maximum age. ...
The values used for natural mortality (M) are very influential in stock assessment models, affecting model outcomes and management advice. Natural mortality is one of the most difficult demographic parameters to estimate, and there is often limited information about the true levels. Here, we summarise the evidence used to estimate natural mortality at age for the four main stocks of yellowfin tuna (Indian, Western and Central Pacific, Eastern Pacific, and Atlantic Oceans), including catch curves, tagging experiments, and maximum observed age. We identify important issues for estimating M such as variation with age linked to size, maturity state or senescence, and highlight information gaps. We describe the history of natural mortality values used in stock assessments by the tuna Regional Fisheries Management Organisations responsible for managing each stock and assess the evidence supporting these values. In June 2021, an online meeting was held by the Center for the Advancement of Population Assessment Methodology (CAPAM), to provide advice and guidance on practices for modelling natural mortality in fishery assessments. Based on approaches presented and discussed at the meeting, we develop a range of yellowfin tuna natural mortality estimates for each stock. We also recommend future research to improve these estimates of natural mortality.
... Micro-increment counts were conducted at various magnifications ranging between 400 and 1000x. The method for the interpretation of the microstructure was consistent with those methods published for reading transverse sections (Lehodey and Leroy, 1999;Sardenne et al., 2015;Shuford et al., 2007). After a count of between 150 and 180 the internal micro-structure becomes increasingly difficult to interpret. ...
The International Commission for the Conservation of Atlantic Tunas (ICCAT) concluded the Atlantic Ocean tropical Tuna Tagging Programme (AOTTP) in 2021. This project had the objectives of enhancing food security, stimulating economic growth, and improving management through research on tropical tuna resources in the Atlantic Ocean, including bigeye tuna (Thunnus obesus). Here, we combine tagging data and otolith data from the AOTTP program, Panama City Lab and the Pelagic Fisheries Lab at the University of Maine with historical tagging data and otolith data from ICCAT and other sources to fit integrated growth models with the goal of providing the most complete growth curve (in terms of data inclusion and validation of age-at-length) for bigeye tuna in the Atlantic Ocean. Both Richards and von Bertalanffy growth models were fitted. A variety of models were fitted to subsets of the data to investigate the consistency of growth information. In all cases for the integrated model, the Richards and von Bertalanffy models were very similar with the von Bertalannfy model being preferred for parsimony. The preferred model, based on fit to old fish, was the von Bertalanffy curve based on length-age pair data from multiple sources. The addition of tagging data to create an integrated model showed patterns of lack of fit to both the tagging and otolith data suggesting conflict between the tagging and otolith data. The preferred model (length-age pair data only) gave the estimates: asymptotic length L∞ (fork length) equals 161.21 cm (95% bootstrap CI 154.39, 166.84), growth parameter K equals 0.392 yr⁻¹ (95% bootstrap CI 0.355, 0.441), and the time-axis intercept t0 equals − 0.239 yr (95% bootstrap CI –0.306, −0.175). For the best fitting integrated model, the asymptotic length L∞(fork length, in cm) was estimated to be 185.78 (SD 6.298), the growth parameter K was 0.252 yr⁻¹ (SD 0.014), and the time-axis intercept t0 was − 0.524 yr (SE 0.025). The value for asymptotic length L∞ from the integrated model was larger than the lengths of all the old fish in the sample whereas the value for the curve based on otoliths passes through the cloud of points for old fish.
... Due to the influence of feeding on the ratio between organic and inorganic matter deposited in the otolith, distinct bands can appear as seasonal rings in adult fish and daily rings in larval fishes (Pannella 1971;Campana and Neilson 1985;Jones 1986). Otolith microstructures are widely used in fisheries studies to provide information supporting stock assessment and recruitment predictions, including evaluation of age and growth rates (Lehodey and Leroy 1999), the nutritional condition of larvae (Clemmesen and Doan 1996), and the relative contribution of wild and hatchery fish to the fishery ( Barnett-Johnson et al. 2007). As the bands are formed by daily growth rhythms, they can be influenced by feeding and temperature, both of which have profound effects on fish growth. ...
Sturgeon populations are endangered worldwide, mainly due to habitat degradation and overexploitation causing recruitment failure. Understanding of early development, survival and growth in sturgeon is limited by a lack of a validated method to directly estimate larval age. In a laboratory calibration study, we reared white sturgeon (Acipenser transmontanus) larvae from hatch for 3 weeks at 12 and 16 °C and two feeding regimes (fed and unfed) to determine the usefulness of their vateritic microotoconia for larval ageing and the influence of environmental factors on ring structure and size. By marking the otoliths twice at known ages with Alizarin Red S, we were able to confirm the presence of daily rings in the largest microotoconia and the feasibility of ageing larval sturgeon using otoliths. Three observers blind to age and treatment assessed larval age from daily rings with an overall precision of 67%–82% and 30%–70% accuracy, dependent on larval age. Neither temperature nor feeding had a significant effect on ring width or readability. Thus, ageing sturgeon larvae using otolith microstructures is a promising tool for sturgeon conservation efforts.
... We also found that tmax was smaller than the fish captured in the western pacific, namely 7.65 years. Lehodey and Leroy [16] found a maximum fish age of 7.5 years in the Western Pacific and Central Region. Table 1 shows differences in age of yellowfin tuna captured from various locations. ...
... To identify initial patterns of yellowfin tuna movement and behavior throughout the acoustic array, we generated abacus plots of individual detections at each FAD that indicate a date of arrival at a given location for each tagged fish. To test for differences in retention time within the coastal FAD network and residency to FADs between age classes, we pooled tagged fish by year class based on their fork length at time of capture and the growth characteristics of yellowfin tuna in the Western Pacific Ocean (Lehodey and Leroy, 1999). Yellowfin tuna < 60 cm FL were classified as young-of-the-year (YOY) and those from 60 to 100 cm FL were classified as year 1 (Y1). ...
Pacific Island nations and territories must build their capacity to harvest pelagic fishes to ensure domestic food security into the future. The Republic of Palau recently created the Palau National Marine Sanctuary, a Marine Managed Area that was intended to conserve marine resources and enhance local pelagic fisheries. However, the capacity of the nation’s domestic fishery to exploit pelagic species must be built to meet these objectives and, to this aim, the development of a coastal network of Fish Attracting Devices (FADs) has been proposed. To inform the development of the nation’s FAD program, we used acoustic telemetry to study the movements of yellowfin tuna (Thunnus albacares) within Palau’s existing FAD network. Subadult yellowfin tuna (50−79 cm FL) remained within the FAD network for up to 175 days and young-of-the-year yellowfin tuna spent significantly more time in association with FADs in comparison to year-1 fish. A network analysis suggests that the Ngardmau and Peleliu FADs were the most important components of the current FAD network, and a mixed effects Poisson generalized linear model indicated that the residency of yellowfin tuna to these FADs was significantly related to mooring depth and distance from the reef. These results provide a description of yellowfin tuna movements within Palau’s FAD network and recommendations to improve the nation’s FAD program that are also applicable to other Pacific Island nations and territories that desire to improve domestic access to pelagic fish stocks.
Both skipjack and yellowfin tunas are recruited to all areas of the fishery at 30-46 cm fork length. Skipjack tuna remain in the exploited phase up to an average 69 cm fork length and yellowfin tuna up to an average 85 cm fork length. Estimated von Bertalanffy parameters are k = 0.0429 and Linfinity = 74.8 cm for skipjack tuna; and k = 0.0243 and Linfinity = 180.9 cm for yellowfin tuna (k on a monthly basis). Modal progressions indicate a 12-month periodicity in mass movement of yellowfin tuna stocks in northerly and southerly directions. The presence of 2 skipjack tuna spawning groups, one spawning during the northern summer, the other during the northern winter, is indicated.-from Author
Le modèle composite, communément admis pour décrire les deux stances de croissance de l'albacore dans l'Atlantique Est, est ré-examiné... L'équation de croissance est exprimée en fonction d'un âge conventionnel. Les limites de ce modèle sont soulignées. Différents modèles continus sont ensuite ajustés sur les données de Capisano et Fonteneau (1991), qui estiment l'âge par décomposition polymodale des fréquences de tailles des captures réalisées par les senneurs, durant la période 1983-1988. On montre que l'ajustement des modèles à 3 ou 4 paramètres (Gompertz, Richards et Von Bertalanffy généralisé) est peu satisfaisant. On propose un modèle à 5 paramètres, combinant une fonction linéaire et une loi de Von Bertalanffy généralisée. La validité et l'ajustement de ce modèle sont analysés
