Model selection for fish growth patterns based on a Bayesian approach: A case study of five freshwater fish species

Selecting an appropriate growth pattern for individual fish is a meaningful but complex topic in fishery research. We model four growth functions − the commonly used von Bertalanffy growth model (VBGM), and the Gompertz growth model (GGM), Schnute–Richards growth model (SRGM), and generalized VBGM (G-VBGM) − to examine possible growth patterns. Mean total length-at-age fish datasets for five commercial fish species (yellow perch Perca flavescens, walleye Sander vitreus, northern pike Esox lucius, largemouth bass Micropterus salmoides and lake herring Coregonus artedi) from North American freshwater ecosystems, were analyzed. Using a Markov chain Monte Carlo (MCMC) algorithm, we structured four models combining informative priors of model parameters. It is the first time that deviance information criterion (DIC) and leave-one-out cross-validation (LOOCV) were combined to select the best growth model. During the model-selection process, the smooth LOOCV error successfully followed the trend of the LOOCV error, although there were difference in the curve shapes. Values of scale reduction factor (SRF) for all four models indicated convergence, ranging 1.02–1.06, below the 1.2 threshold. The GGM was selected for C. artedi, and the G-VBGM for the other four species. Our approach provided a robust process in model-selection uncertainty analysis, with the G-VBGM having the best prediction ability among our datasets

Population dynamics of bearded croaker Johnius dussumieri (Cuvier, 1830) from Pakistani waters

In this study the length frequency data of 2510 bearded croaker Johnius dussumieri (Cuvier, 1830), collected from the coast of Pakistan during 2015, were analysed. Total length of the specimens (male and female combined) varied from 4 to 25 cm with dominant individuals ranged between 12 and 15 cm whereas the body weight varied between 3 and 155 g. The length frequency data were analysed for the estimation of population dynamics and the power coefficient b of length weight relationship was estimated as 2.83. Other measurements were as follows: asymptotic length, L∞ = 26.25 cm; growth coefficient, K = 1.00 year–1; total mortality, Z = 2.43 year–1; and natural mortality, M = 1.82 year–1. The fishing mortality (F) and exploitation ratio (E) were 0.61 year–1 and 0.251 respectively. The Biological Reference Points (BRPs) with Gulland method for this fishery (Fopt) was estimated 1.82 year–1 which is higher than current fish mortality. Therefore the present study shows that the J. dussumieri fishery is safe in Pakistan

Assessing the Uncertainty of Total Seabird Bycatch Estimates Synthesized from Multiple Sources with a Scenario Analysis from the Western and Central Pacific

Each year, billions of seabirds undertake migrations, connecting remote regions of the world, potentially synchronizing population fluctuations among distant areas. This connectedness has implications for the uncertainty calculations of the total seabird bycatch estimate at a regional/global scale. Globally, fisheries bycatch poses a major problem in fishery management, and estimating the uncertainty associated with a regional/global seabird bycatch estimate is important because it characterizes the accuracy and reliability of the fisheries’ impact on the seabird populations. In this study, we evaluate different assumptions underlying the estimation of the variability of the total seabird bycatch at a regional/global scale based on local assessment reports. In addition to theoretical analysis, we also simulate multiple spatially distant separately managed areas with relatively low levels of observer coverage, based on bycatch data from the Western and Central Pacific Fisheries Commission convention area. The results show that assuming a completely synchronized variation produced the most conservative uncertainty estimate and it also missed an opportunity to improve the precision. Simplified correlation structures also failed to capture the complex dynamics of bycatch rates among spatially distant areas. It is recommended to empirically estimate the correlation of bycatch rates between each pair of sources based on bycatch rate time series

Model selection for fish growth patterns based on a Bayesian approach: A case study of five freshwater fish species

Selecting an appropriate growth pattern for individual fish is a meaningful but complex topic in fishery research. We model four growth functions − the commonly used von Bertalanffy growth model (VBGM), and the Gompertz growth model (GGM), Schnute–Richards growth model (SRGM), and generalized VBGM (G-VBGM) − to examine possible growth patterns. Mean total length-at-age fish datasets for five commercial fish species (yellow perch Perca flavescens, walleye Sander vitreus, northern pike Esox lucius, largemouth bass Micropterus salmoides and lake herring Coregonus artedi) from North American freshwater ecosystems, were analyzed. Using a Markov chain Monte Carlo (MCMC) algorithm, we structured four models combining informative priors of model parameters. It is the first time that deviance information criterion (DIC) and leave-one-out cross-validation (LOOCV) were combined to select the best growth model. During the model-selection process, the smooth LOOCV error successfully followed the trend of the LOOCV error, although there were difference in the curve shapes. Values of scale reduction factor (SRF) for all four models indicated convergence, ranging 1.02–1.06, below the 1.2 threshold. The GGM was selected for C. artedi, and the G-VBGM for the other four species. Our approach provided a robust process in model-selection uncertainty analysis, with the G-VBGM having the best prediction ability among our datasets

Population dynamics of Rainbow Sardines, Dussumieria acuta (Valenciennes, 1847) from Pakistani waters

Length frequency data of Rainbow Sardines, Dussumieria acuta were collected and measured from the coast of Pakistan during 2015, ranging from 5 to 19 cm (total length). Weight ranges were measured from 2 to 64 g. The length frequency data were analysed for the estimation of population dynamics, so b was estimated at 2.70. The estimated von Bertalanffy growth function parameters of 19.95 cm (L∞) and 0.730 year-1 (K). The mortality rate Z= 1.84 year-1, M= 1.59 year-1 F= 0.25 year-1 and E= F/Z= 0.135. The yield-per-recruit analysis indicated that when tc was 1, Fmax was 1 year-1. Currently, the age at first capture is about 1 year and Fcurrent was 0.25 year-1. Therefore, Fcurrent was smaller than Fmax. With Gulland method, the biological reference point for fishery (Fopt) was estimated as 1.59 year1, which is also higher than current fish mortality. Therefore, the present study shows that the Dussumieria acuta fishery is safe in Pakistan.&nbsp;&nbsp;</p

Growth and mortality parameters of Indian squid Uroteuthis (Photololigo) duvaucelii (D'Orbigny,1835) from Pakistani waters(Arabian Sea) based on length frequency data.

1598-1603Present study was carried out to understand the Growth and Mortality parameters of commercially important Indian Squid Uroteuthis Duvauceli (D’ Orbigny.1985) based on length frequency data from Pakistani waters. The pooled n=1138 pair length-weight data of both sexes combined were used to calculate the length weight relationship as: W=0.278*L2.122 (R2=0.9520) length frequency data n=10008 were used to estimate VBGF growth parameters as =26.25(ML-cm) and K= 0.270 year-1 with goodness of fit model were estimated at Rn=0.335. The t0 value was calculated at t0=-0.442. Length converted catch curve analysis gave a Z value of 1.14 year-1. Natural mortality (M) obtained from Srinath’s method using empirical formula M = 0.4603+1.4753K, M=0.853 year-1. Fishing mortality was calculated as F=Z-M = 0.287 year and the exploitation rate (E) was calculated from F/Z = 0.251 year because the exploitation rate in present study is lower than 0.5

Application of Bayesian surplus production model and traditional surplus production model on stock assessment of the southern Atlantic albacore (<i>Thunnus alalunga</i>)

922-928Bayesian surplus Production model (BSP) and traditional surplus Production models (TSP) were used to evaluate the southern Atlantic albacore (Thunnusalalunga) stock. Population parameterswere estimated using CEDA (catch-effort data analysis) and ASPIC (a surplus-production model incorporate covariates) computer software packages. Performance of the BSP model and TSP model were compared by a Bayesian information criterion (BIC). Maximum sustainable yield (MSY) from the TSP model and BSP model were used to verify the MSY estimations by International Commission for the Conservation of Atlantic Tunas (ICCAT). Catch of 2011 (24122 t) was higher than the MSY from BSP (21756t, 23408t), and the relative fishing mortality ratio (F2011/FMSY) of the stock was higher than 1.0, which shows thatthis stock over-exploited. Different harvest strategies were set to assess the risk for this stock, and these estimates were used topredict the biomass and catch in 2025 (B2025, C2025) and other five indexes (B2025 /BMSY, B2025 /K, P (B2025> B2012), P (B2025> BMSY), P (B2025MSY/4)). Evaluated biological reference points (BRPs) from Bayesian model were compared with the results from traditional modeling method on the southern Atlantic albacore (T. alalunga) stock, and results showed that the measures should be taken for the sustainable utilization of this fish stock, and the harvest rate of 0.15 seemed tobe the best management measures

Assessment of maximum sustainable yield of <i>Acanthopagrus berda</i> from Pakistani marine waters by applying surplus production models

1410-1416Picnic Sea bream (Acanthopagrus berda) fishery in the Northern Arabian Sea from Pakistani marine waters was analyzed using catch and effort data (1991-2008). Maximum, minimum and average catch was recorded as 1088 mt in 1999, 586 mt in 1991 and 828 mt year-1 respectively. MSY (Maximum sustainable yield) and other key fish population parameters of K (carrying capacity), q (catchability coefficient), r (intrinsic population growth rate) and CV (coefficient variation) values of the calculated MSY were estimated by CEDA (catch and effort data analysis) and ASPIC (a surplus production model incorporating covariates) computer software packages. The fishing mortality at maximum sustainable yield FMSY = 0.114 from logistic model and FMSY= 0.057 from Fox model was estimated by ASPIC. The stock biomass given MSY BMSY = 11990 (CV= 0.083) from Fox model and MSY BMSY = 13630 (CV= 0.037) was estimated in ASPIC. In CEDA the initial proportion (IP) of 0.5 was used, because starting catch was approximately 50% of the maximum catch. The estimated results of MSY using CEDA with three surplus production models Fox, Schaefer and Pella Tomlinson under three error assumptions of Normal, Log-Normal and Gamma were about 620-800 mt, which was lower than the catch of 897 mt in 2008, indicating that the A. berda fishery in the marine waters of Pakistan has been overexploited, therefore it is suggested that measures should be taken to reduce fishing effort for the rational exploitation of the fishery

Growth parameters and mortality rates of giant river-catfish <i>Sperata seenghala </i> from the Indus river, Pakistan

1462-1469Length frequency of Sperata seenghala1 from the Indus River were collected during the months of February, March, April, May and June in 2011. The sample consisted of n= 133 pairs of length and weight data. The length ranged from 46 to 113 cm TL (65.661±15.995 cm), while the weight varied from 500 to 7500 g TW (1806.391±1481.456 g). Length-weight relationship was calculated as a= 0.04, b= 3.047 (R2= 0.99). The von Bertalanffy growth function parameters for S. seenghala were L∞= 117.60 (TL cm) and K= 0.370 year-1, while the age at zero length was t0= -0.513 year. The total instantaneous mortality rate (Z) was estimated at 95% CI of 0.77-1.22 (Z= 1.00 year-1) in the Indus River. The natural mortality (M) was computed as M= 0.556 year-1 at an average annual temperature of surface water of 21oC, whereas the fishing mortality was estimated as F= 0.444 year-1. Therefore, exploitation ratio (E= F/Z) was calculated as E= 0.444. The growth performances indices for L∞ and W∞ were computed Φ'= 3.709 and Φ= 2.175 respectively. When tc was at 1, the yield per recruit analysis found that Fmax was at 0.85 year-1 and F0.1 at 0.75 year-1. The current age at first capture was about 1 year, the Fcurrent rate was 0.444 year-1. Thus the current fishing mortality rate was smaller than Fopt= 0.556 year-1, Fmax= 0.85 year-1 and F0.1= 0.75 year-1. Therefore, we can assume that the current stock of this important fishery resource is not over-fished