Some Aspects Of Fish Population Dynamics Of The Commercial Fish Species In Pakistan

This study is the first to describe maximum sustainable yield （MSY） of fish andshellfish resources of Pakistan. MSY of a fish species ladypees, Sillago sihama andshellfish spiny lobster, Panulirus sp were analyzed. The computer packages of astock-surplus production model incorporating covariates （ASPIC） and catch andeffort data analysis （CEDA） used here were based on the non-equilibriumassumption of the state of the stocks.ASPIC estimates the parameters of MSY （maximum sustainable yield）, Fmsy（fishing mortality at MSY）, q （catchability coefficient）, K （carrying capacity orunexploited biomass） and B1/K （starting biomass carrying capacity）.The key parameters of CEDA are: MSY, K, q, and r （intrinsic growth）, andthe three error assumptions in the models are normal, log normal and gamma.The time series catch and effort data were applied to estimate MSY forSillago sihama fishery. The ASPIC estimate of the logistic model was598mt（metric tones） and that based on Fox model was415mt, which showed that theFox model estimation was more conservative than that with the logistic model.The R²with logistic model （0.702） is larger than that with the Fox model （0.541）,which indicates a better fit. The coefficient of variation （cv） of the estimated MSYwas about0.3, except for a larger value0.88and a smaller value of0.173.In contrast to the ASPIC results, the CEDA estimates of R2with Fox model（0.651–0.692） was larger than that with the Schaefer model （0.435–0.567）,indicating a better fit. Parameter estimates from the Schaefer and Pella-Tomlinsonmodels were identical. The MSY estimations from the above two models were398mt,549mt and398mt for normal, log-normal and gamma error distributionsrespectively. The MSY estimates from Fox model were381mt,366mt and366mtfor the above three error assumptions respectively. Fox model estimates weresmaller than those for Schaefer and Pella-Tomlinson models. In the light of theMSY estimations of415mt from ASPIC for Fox model and381mt from CEDA for Fox model, MSY for S. sihama is calculated to be about400mt. As the catch in2003was401mt, we would suggest the fishery is sustainable and should be keptat the current level. Production models used here depend on the assumption thatCPUE （catch per unit effort） data used in the study can reliably quantify temporalvariability in population abundance; hence the modeling results would be wrong ifsuch an assumption is not met. Because the reliability of this CPUE data inindexing fish population abundance is unknown, we should be cautious with theinterpretation and use of the derived population and management parameters.A comparison of logistic and generalized surplus-production models weremade and applied on the time series catch and effort data of ladypees, Sillagosihama to investigate the performances of two closely related estimators. Thelogistic model estimates of such as MSY were more reasonable than that of thegeneralized estimator. However, the R2in CPUE estimates in generalized modelwere more precise than the logistic. Simulation analyses were carried out on the S.sihama like simulated fishery. The estimated and observed abundance index （AI）showed that they were close for the logistic model, but different for thegeneralized production model. Standardized residuals were about distributedaround0.0for logistic model, but had a weak increasing trend for the generalizedmodel. Statistical outliers were seen in logistic model in1989and1993whereas ingeneralized in1981and1999. Simulated results reveal that the logistic estimateswere close to the true value for the low CV but largely dispersed for high CV, incontrast the generalized model estimates were loose for all the CV levels. Theestimated production model curve shape parameter was not reasonable at allthe white noise levels. When the noise level increased the R2values in catch perunit effort decreased. Therefore, we would like to conclude that the logistic modelappeared more reasonable than the generalized production model on the basis ofladypees fishery tested in this study.The estimation of MSY of spiny lobster Panulirus sp fishery in Pakistan wasmade using CEDA computer programme. The MSY outputs of three models of Fox, Schaefer and Pella-Tomlinson are:828mt,970mt and970mt respectively. Theoutputs of error assumption of normal and log normal are983mt （R²=0.57）&950mt （R²=0.53） in Schaefer and Pella-Tomlinson respectively. MSY outputs ofnormal error assumption of Fox are817mt （R²=0.56）. All the gamma errorassumptions are （790mt） similar. The coefficient of variation （cv） of theestimated MSY was about0.7and the larger value （1.0） whereas lowest （0.5）were recorded. The Fox model output are more conservative hence best fits maybe close to the annual average landings of the spiny lobster fishery in Pakistanwhich is480metric tones.The age and growth information of fish is important for assessment of thedynamics, planning, and management in fisheries. The research presented herestems from an attempt to use the parameters of different growth models tocompare the growth characteristics of different fishes in different environments.Also the goodness of fit of different models and the ability of Akaike informationcriterion （AIC） and Bayesian information criterion （BIC） in model selection wereanalysis in this thesis.The mean size at age data of10fish species were fitted by the five growthmodels e.g. of von Bertalanffy, Gompertz, Allometric, logistic and Polynomial andthe growth parameters were estimated by the maximum likelihood method. Thebest model was selected using the Akaike information criterion （AIC） andBayesian information criterion （BIC）. The growth of most species can be bestdescribed by the von Bertalanffy and Allometric growth models. The resultsshowed that both AIC and BIC have their advantages in the testing of significanceof the difference between the functions of models. As for the demersal fishes （e.g.snappers and groupers）, BIC is better than AIC in selecting the best growth model.As a part of this dissertation population biology and stock assessment ofkelee shad, Hilsa kelee was estimated using the computer programme of FiSAT(FAO, ICLARM, fisheries stock assessment. The growth parameters wereestimated with von Bertalanffy growth equation Lt=23.10（1–exp（-0.94（t+0.18））） cm. The length-at-first capture Lc=10.88cm was estimated. The estimatedparameters of total mortality （Z）, natural mortality （M） and fishing mortality （F）were2.08yr^-1,1.78yr^-1, and0.30yr^-1respectively. Biomass per recruitment （B’/R）and yield per recruitment （Y’/R） were estimated0.87and0.031respectively. Theannual exploitation rate was U=0.12. The exploitation ratio at MSY or E_max=0.73and fishing mortality at maximum sustainable yield F_max=1.52; biological referencepoint F_opt=0.89yr^-1and F_limit=1.18yr^-1. From the results obtained here it isinterpretable that the natural mortality was higher than fishing mortality in Hilsakelee, indicating that the state of the stock is sustainable. Therefore, we concludethat the standing stock should be kept at the current level.