Albacore Stock Research Articles

Evaluation of the performance of alternative assessment configurations to account for the spatial heterogeneity in age-structure: a simulation study based on Indian Ocean albacore tuna

Various population structures or spatial heterogeneities in population distribution have been an important source of model misspecification and have had an impact on estimation performance in fisheries stock assessment. In this study, we simulated the Indian Ocean albacore spatial heterogeneity in age-structure using Stock Synthesis according to the stage-dependent migration rate and region-dependent fishing mortality rate and generated the stock assessment data. Based on these data, we investigated the performances of different spatial configurations, selectivity curves and selections of CPUE (catch per unit effort) indices of the assessment models which were used to account for spatial heterogeneity. The results showed: (1) although the spatially explicit configurations, which exactly matched the operating model, provided unbiased and accurate estimates of relative spawning biomass, relative fishing mortality rate and maximum sustainable yield in all simulation scenarios, their performance may be very poor if there were mismatches between them and the operating model due to gaps in knowledge and data; (2) for spatially explicit assessment configuration, the correct boundary was required, but for non-spatially explicit assessment configuration, it seemed more important for analysts to partition the area to properly reflect the transition in field data and to effectively account for the impacts of ignoring the spatial structure by using the additional spatially referenced parameters; (3) although the areas-as-fleets methods and flexible time-varying selectivity curves could be used as better alternative approaches to account for spatial structure, these configurations could not completely eliminate the impacts of model misspecification and the quality of estimates of different quantities from the same assessment model may be inconsistent or the performance of the same assessment configuration may fluctuate significantly between simulation scenarios; (4) although the worst estimates could generally be avoided by using multiple CPUE indices, there were no best solutions to select or regenerate the CPUE indices to account for the impacts of the ignored spatial structure to obviously improve the quality of stock assessment. Compared with the results of assessment model configurations which are used to account for the spatial structure by different modelers, the performances of the configurations are always casespecific except for spatially explicit configurations which exactly match the operating model. In this sense, our study will not only provide some insights into the current Indian Ocean albacore stock assessment but also enrich existing knowledge regarding the performance of assessment configurations to account for spatial structure.

Ovarian development of albacore (Thunnus alalunga Bonnaterre, 1788) in the Eastern Mediterranean Sea: a histological characterisation

In order to investigate the stages of oogenesis in the albacore Thunnus alalunga, 129 females (64.0‒83.5 cm fork length-FL) were captured by gill nets from April to August 2002–2008, in the eastern Mediterranean Sea. Based on histological examination of the ovaries, a total of seven ovarian developmental stages were identified: perinucleolar, lipid, early vitellogenesis, late vitellogenesis, migratory nucleus, pre-hydrated and hydrated. The monthly gonadosomatic index values and the results of the histological analysis indicated that the females mature in May. The spawning stage becomes predominant in June and reaches a maximum in July. The evidence reported here indicates that the size of females at first sexual maturity was lower for the Mediterranean albacore stock than for the Pacific and Atlantic stocks.

Verifier of the maximum sustainable yield estimates of the southern Atlantic albacore, Thunnus alalunga, stock

AbstractMaximum sustainable yield (MSY) has generally been accepted as one of the target biological reference points. Albacore, Thunnus alalunga Bonnaterre, is a temperate tuna species widely distributed in marine waters. The International Commission for the Conservation of Atlantic Tunas (ICCAT) and the International Seafood Sustainability Foundation (ISSF) had reported the southern Atlantic albacore stock status with different MSY reference points. In addition, the European Commission's Advisory Committee on Fisheries and Aquaculture (ACFA), on 15 September 2006, proposed to amend the Common Fisheries Policy according to the MSY principle, but there is little information on the verifier of the MSY estimates of this albacore stock. This study verifies the MSY estimates of this albacore (T. alalunga) stock to support the management (i.e. setting of MSY) for the southern Atlantic albacore (T. alalunga) stock. The MSY estimates of the albacore stock were evaluated and verified by different models (i.e. Bayesian surplus production model [BSPM], continuous time delay‐difference model [CD‐DM] and Fox surplus production model [SPM]). The MSY estimates from BSPM and CD‐DM were lower than those from conventional estimates; the relative biomass ratio (B2011/BMSY) and relative fishing mortality ratio (F2011/FMSY) from BSPM and CD‐DM were higher than those from ICCAT, which showed that measures should be taken for the sustainable utilisation of this fish stock.

Application of a Bayesian method to data-poor stock assessment by using Indian Ocean albacore (Thunnus alalunga) stock assessment as an example

It is widely recognized that assessments of the status of data-poor fish stocks are challenging and that Bayesian analysis is one of the methods which can be used to improve the reliability of stock assessments in data-poor situations through borrowing strength from prior information deduced from species with good-quality data or other known information. Because there is considerable uncertainty remaining in the stock assessment of albacore tuna (Thunnus alalunga) in the Indian Ocean due to the limited and low-quality data, we investigate the advantages of a Bayesian method in data-poor stock assessment by using Indian Ocean albacore stock assessment as an example. Eight Bayesian biomass dynamics models with different prior assumptions and catch data series were developed to assess the stock. The results show (1) the rationality of choice of catch data series and assumption of parameters could be enhanced by analyzing the posterior distribution of the parameters; (2) the reliability of the stock assessment could be improved by using demographic methods to construct a prior for the intrinsic rate of increase (r). Because we can make use of more information to improve the rationality of parameter estimation and the reliability of the stock assessment compared with traditional statistical methods by incorporating any available knowledge into the informative priors and analyzing the posterior distribution based on Bayesian framework in data-poor situations, we suggest that the Bayesian method should be an alternative method to be applied in data-poor species stock assessment, such as Indian Ocean albacore.

A continuous time delay-difference type model (CTDDM) applied to stock assessment of the southern Atlantic albacore Thunnus alalunga

A continuous time delay-diff erence model (CTDDM) has been established that considers continuous time delays of biological processes. The southern Atlantic albacore (Thunnus alalunga) stock is the one of the commercially important tuna population in the marine world. The age structured production model (ASPM) and the surplus production model (SPM) have already been used to assess the albacore stock. However, the ASPM requires detailed biological information and the SPM lacks the biological realism. In this study, we focus on applying a CTDDM to the southern Atlantic albacore (T. alalunga) species, which provides an alternative method to assess this fishery. It is the first time that CTDDM has been provided for assessing the Atlantic albacore (T. alalunga) fishery. CTDDM obtained the 80% confidence interval of MSY (maximum sustainable yield) of (21 510 t, 23 118t). The catch in 2011 (24 100 t) is higher than the MSY values and the relative fishing mortality ratio (F2011/FMSY) is higher than 1.0. The results of CTDDM were analyzed to verify the proposed methodology and provide reference information for the sustainable management of the southern Atlantic albacore stock. The CTDDM treats the recruitment, the growth, and the mortality rates as all varying continuously over time and fills gaps between ASPM and SPM in this stock assessment.

Estimating individual growth variability in albacore (Thunnus alalunga) from the North Atlantic stock: Aging for assessment purposes

Length-frequency data and derived catch at age matrices are used in north Atlantic albacore (Thunnus alalunga) stock assessment conducted within the International Commission for the Conservation of Atlantic Tunas (ICCAT). Growth is assumed to follow the von Bertalanffy model with the assumption that growth parameters are constant over time and the same for all fish. However, individual growth variability is an important factor not considered and affecting the input into the modelling of the population. This study describes a Bayesian hierarchical model applied to model the individual variability in the parameters asymptotic length (L∞) and growth rate (K) of the von Bertalanffy growth model for North Atlantic albacore. The method assumes that the L∞ and K values for each individual fish are drawn from a random distribution centered on the population mean values, with estimated variances. Multiple observations of spine diameter at age for individual fish were obtained by direct reading of spine sections collected in 2011 and 2012. A suite of back calculation methods were then applied to the measurements of annuli diameters in the aged individuals observed to back-calculate lengths at each age. The von Bertalanffy model was fitted to the measured and back-calculated lengths. Models with and without individual growth variability were compared using the deviance information criterion (DIC) to find the best model. Normal and log-normal error distribution models were used to analyse the data. Additionally, subsamples of the data were used to evaluate whether an unbalanced age-distribution in the data affects estimates of growth parameters. It was found that North Atlantic albacore asymptotic length (L∞) varies significantly between individual fish but not individual rate growth (K), for all back-calculation methods. Furthermore, negatively correlated relationships between von Bertalanffy growth parameters of asymptotic mean (L∞) and growth rate (K) were estimated for North Atlantic albacore with the array of models explored. The overall estimated values of K and population mean L∞ parameters were similar to values estimates in previous north Atlantic albacore growth studies.

Influence of fronts on the spatial distribution of albacore tuna (Thunnus alalunga) in the Northeast Pacific over the past 30 years (1982–2011)

The association of albacore tuna distribution with subtropical fronts in the Northeast Pacific was examined on seasonal and interannual scales from 1982 to 2011. Spatial analyses were performed on commercial logbook data from US and Canadian troll and pole-and-line fisheries targeting albacore tuna that were matched with corresponding satellite images from the Advanced Very High Resolution Radiometer (AVHRR). Subtropical fronts were detected by deriving sea surface temperature (SST) gradients on large basin-scales and by using an improved version of the Cayula–Cornillon frontal detection algorithm. Based on our results, we suggest that areas with high albacore catch-per-unit-effort (CPUE) tend to occur in regions with high SST gradients, such as the North Pacific Transition Zone (NPTZ) and the North American coast. Approaching the North American coast along the NPTZ, SST gradients drop off substantially around 130°W before increasing rapidly near the coast, which corresponded to a similar pattern in albacore CPUE. In the NPTZ, the centroid of albacore CPUE showed a seasonal shift northwards in summer and southwards in fall, which coincided with seasonal spatial shifts of areas with high SST gradients. A similar pattern was found on an interannual scale, with the exception of several years with limited fishery data in the NPTZ due to changes in fishery operations. A fine-scale analysis of frontal locations suggested that areas with high albacore CPUE are associated with oceanic fronts, with the highest albacore CPUEs observed within 100km of the nearest front. In addition, albacore distribution is related to frontal strength, with the highest CPUE found near fronts with high SST gradient values in the range of 0.12–0.16°Ckm−1. Integrating our findings on the influence of frontal areas on albacore distribution and abundance in the NEPO should improve the standardization model used to derive abundance indices for North Pacific albacore stock assessments.

Application of a Delay-difference model for the stock assessment of southern Atlantic albacore (Thunnus alalunga)

Delay-difference models are intermediate between simple surplus-production models and complicated age-structured models. Such intermediate models are more efficient and require less data than age-structured models. In this study, a delay-difference model was applied to fit catch and catch per unit effort (CPUE) data (1975–2011) of the southern Atlantic albacore (Thunnus alalunga) stock. The proposed delay-difference model captures annual fluctuations in predicted CPUE data better than Fox model. In a Monte Carlo simulation, white noises (CVs) were superimposed on the observed CPUE data at four levels. Relative estimate error was then calculated to compare the estimated results with the true values of parameters α and β in Ricker stock-recruitment model and the catchability coefficient q. a is more sensitive to CV than β and q. We also calculated an 80% percentile confidence interval of the maximum sustainable yield (MSY, 21756 t to 23408 t; median 22490 t) with the delay-difference model. The yield of the southern Atlantic albacore stock in 2011 was 24122 t, and the estimated ratios of catch against MSY for the past seven years were approximately 1.0. We suggest that care should be taken to protect the albacore fishery in the southern Atlantic Ocean. The proposed delay-difference model provides a good fit to the data of southern Atlantic albacore stock and may be a useful choice for the assessment of regional albacore stock.

Insights into mixing and movement of South Pacific albacore Thunnus alalunga derived from trace elements in otoliths

Information on the movement and stock structure of commercially important tunas underpins the effective management of exploited populations. In the case of the South Pacific albacore (Thunnus alalunga) stock, longstanding questions remain regarding the degree of connectivity among larval pools, the migration routes of juveniles and adults and the biophysical factors influencing these processes. We measured trace elements (Li, Mg, Mn, Cu, Sr, Ba, Pb, Ca) in albacore otoliths collected across a broad geographical range in the South Pacific Ocean to address these knowledge gaps. Capture locations in French Polynesia, New Caledonia and New Zealand were discriminated with high accuracy (overall 85% of individuals correctly classified) based on analyses at the otolith edge (reflecting the final <1 month of life) using LA-ICPMS. Spatial comparisons of otolith core chemistry (reflecting the first ∼2 weeks of life post-hatch) from the 2005/06 cohort suggest some mixing of larval pools for fish sampled from New Caledonia and New Zealand, whereas French Polynesian fish may have originated from a chemically and/or geographically distinct larval source. Annual and/or sub-annual cycles in Sr:Ca and Ba:Ca were evident along ablation transects encompassing the full life history of individuals. These patterns may reflect seasonal north-south movements across ocean fronts; however, the vertical behaviours of albacore and the lack of opportunities for controlled experiments on temperature effects and time-lags in elemental incorporation complicates environmental reconstructions based on trace element data alone. Expanding the present analysis across multiple years and regions, and integrating data from several sources (e.g. commercial catch data, tag returns, otolith δ13C and δ18O, ocean circulation models) could help clarify the linkages between environmental factors and mixing and movement patterns in albacore.

Testes development and maturity classification of albacore (Thunnus alalunga ( Bonaterre, 1788)) from the Eastern Mediterranean Sea

Summary The criteria of testicular maturity during the spawning season and for maturity rates are described according to age for 140 male albacore (Thunnus alalunga, Bonnaterre, 1788) sampled between April and August, 2002–2008 in the Eastern Mediterranean Sea. Histology of gonad samples was used to determine maturity status. Spermatogenesis and its relation to reproductive biology are reported. Fish ranged in fork length (FL) from 63 to 90 cm. The reproductive classes were based upon changes in the testicular morphology and stages of the germinative cells, i.e. immature, developing, maturing, spawning, and spent. Mature stages of testes including the smallest sample of a 63 cm male were observed from May to August of each year during the study. The reported evidence indicates that the size and age of first sexual maturity values of males of the Eastern Mediterranean population are nearly the same as in the Western Mediterranean population, but lower than in the Atlantic stock. The results of this histological investigation, conducted for the first time on this species in the Mediterranean Sea, will enable more precise future estimations for sustainability of the male albacore stock in the Eastern Mediterranean.

Spatial and Sex-Specific Variation in Growth of Albacore Tuna (Thunnus alalunga) across the South Pacific Ocean

Spatial variation in growth is a common feature of demersal fish populations which often exist as discrete adult sub-populations linked by a pelagic larval stage. However, it remains unclear whether variation in growth occurs at similar spatial scales for populations of highly migratory pelagic species, such as tuna. We examined spatial variation in growth of albacore Thunnus alalunga across 90° of longitude in the South Pacific Ocean from the east coast of Australia to the Pitcairn Islands. Using length-at-age data from a validated ageing method we found evidence for significant variation in length-at-age and growth parameters (L ∞ and k) between sexes and across longitudes. Growth trajectories were similar between sexes up until four years of age, after which the length-at-age for males was, on average, greater than that for females. Males reached an average maximum size more than 8 cm larger than females. Length-at-age and growth parameters were consistently greater at more easterly longitudes than at westerly longitudes for both females and males. Our results provide strong evidence that finer spatial structure exists within the South Pacific albacore stock and raises the question of whether the scale of their “highly migratory” nature should be re-assessed. Future stock assessment models for South Pacific albacore should consider sex-specific growth curves and spatial variation in growth within the stock.

Microsatellite analysis of albacore tuna (Thunnus alalunga): population genetic structure in the North-East Atlantic Ocean and Mediterranean Sea

Stock heterogeneity was investigated in albacore tuna (Thunnus alalunga, Bonnaterre 1788), a commercially important species in the North Atlantic Ocean and Mediterranean Sea. Twelve polymorphic microsatellite loci were examined in 581 albacore tuna from nine locations, four in the north-east Atlantic Ocean (NEA), three in the Mediterranean Sea (MED) and two in the south-western Pacific Ocean (SWP). Maximum numbers of alleles per locus ranged from 9 to 38 (sample mean, 5.2–22.6 per locus; overall mean, 14.2 ± 0.47 SE), and observed heterozygosities per locus ranged from 0.44 to 1.00 (overall mean: 0.79 ± 0.19 SE). Significant deficits of heterozygotes were observed in 20% of tests. Multilocus F ST values were observed ranging from 0.00 to Θ = 0.036 and Θ′ = 0.253, with a mean of Θ = 0.013 and Θ′ = 0.079. Pairwise F ST values showed that the SWP, NEA and MED stocks were significantly distinct from one another, thus corroborating findings in previous studies based on mitochondrial DNA, nuclear DNA (other than microsatellites) and allozyme analyses. Heterogeneity was observed for the first time between samples within the Mediterranean Sea. GENELAND indicated the potential presence of three populations across the NEA and two separate populations in the Mediterranean Sea. Observed genetic structure may be related to migration patterns and timing of movements of subpopulations to the feeding grounds in either summer or autumn. We suggest that a more intensive survey be conducted throughout the entire fishing season to ratify or refute the currently accepted genetic homogeneity within the NEA albacore stock.

Assessment of South Pacific albacore stock (Thunnus alalunga) by improved Schaefer model

Based on catch and effort data of tuna longline fishery operating in the South Pacific Ocean, the South Pacific albacore stock was assessed by an improved Schaefer model. The results revealed that the intrinsic growth rate was about 1.283 74 and carrying capacities vareied in the range from 73 734 to 266 732 metric tons. The growth ability of this species is remarkable. Stock dynamics mainly depends on environmental conditions. The stock is still in good condition. However, the continuous decreasing of biomass in recent years should be noticed.

Management implication on Indian Ocean albacore from simple yield analysis incorporating parameter uncertainty

Many studies have been conducted to estimate the parameters of Indian Ocean albacore ( Thunnus alalunga) fishery. Various estimates on the same parameter from these studies have resulted in uncertainty and confusion when management strategies are made. This study incorporates these estimates in the simple yield-per-recruit model through Monte Carlo simulations to derive management implication under parameter uncertainty. The results provided an optimal management suggestion under the following conditions. First, the probability of obtaining feasible simulation results was greater than 95%; second, the probability of increase to yield-per-recruit after regulatory change was also greater than 95%. Under these conditions, the results suggested if the goal of management was to increase the relative yield-per-recruit of the Indian Ocean albacore stock by 30% and more, the relative selection size should be changed by +0.15 to +0.25 and the exploitation rate by −0.5 to +0.15.