Application of a weekly delay-difference model to commercial catch and effort data for tiger prawns in Australia’s Northern Prawn Fishery

2003 ◽  
Vol 65 (1-3) ◽  
pp. 335-350 ◽  
Author(s):  
C.M. Dichmont ◽  
A.E. Punt ◽  
A. Deng ◽  
Q. Dell ◽  
W. Venables
Keyword(s):  
Difference Model ◽  
Commercial Catch ◽  
Delay Difference ◽  
Northern Prawn Fishery

Relationship of Fishing Mortality to Natural Mortality and Growth at the Level of Maximum Sustainable Yield

1982 ◽  
Vol 39 (7) ◽  
pp. 1054-1058 ◽  
Author(s):  
R. B. Deriso
Keyword(s):  
Logistic Model ◽  
Mortality Rates ◽  
Maximum Sustainable Yield ◽  
Sustainable Yield ◽  
Natural Mortality ◽  
Fishing Mortality ◽  
Difference Model ◽  
Relationship Of ◽  
Yield Per Recruit ◽  
Delay Difference

Fishing mortality constraints are derived for fishes harvested at the maximum sustainable yield (MSY) determined by a delay-difference population model. Those constraints depend upon rates of natural mortality and growth as well as a simple constraint placed on abundance of the exploited population. The results are generalized for a wider class of population models where it is shown that MSY fishing mortality is constrained often to be less than the fishing mortality which maximizes yield per recruit. Fishing mortality rates are lower in the delay difference model in comparison to MSY fishing rates in the logistic model, when a quadratic spawner–recruit curve is applied.Key words: delay-difference model, logistic model, fishing mortality, maximum sustainable yield, yield per recruit

Bayesian stock assessment using a state–space implementation of the delay difference model

1999 ◽  
Vol 56 (1) ◽  
pp. 37-52 ◽  
Author(s):  
Renate Meyer ◽  
Russell B Millar
Keyword(s):  
State Space ◽  
Bayesian Approach ◽  
Stock Assessment ◽  
State Space Model ◽  
Random Errors ◽  
Difference Model ◽  
Spawning Stock ◽  
The Common ◽  
Biomass Dynamics ◽  
Delay Difference

This paper presents a Bayesian approach to fisheries stock assessment using the delay difference model to describe nonlinear population dynamics. Given a time series of annual catch and effort data, models in the Deriso-Schnute family predict exploitable biomass in the following year from biomass in the current and previous year and from past spawning stock. A state-space model is used, as it allows incorporation of random errors in both the biomass dynamics equations and the observations. Because the biomass dynamics are nonlinear, the common Kalman filter is generally not applicable for parameter estimation. However, it is demonstrated that the Bayesian approach can handle any form of nonlinear relationship in the state and observation equations as well as realistic distributional assumptions. Difficulties with posterior calculations are overcome by the Gibbs sampler in conjunction with the adaptive rejection Metropolis sampling algorithm.

The impact of global positioning systems and plotters on fishing power in the northern prawn fishery, Australia

1998 ◽  
Vol 55 (7) ◽  
pp. 1645-1651 ◽  
Author(s):  
Carolyn M Robins ◽  
You-Gan Wang ◽  
David Die
Keyword(s):  
Linear Model ◽  
Generalized Linear Model ◽  
Global Positioning Systems ◽  
Commercial Catch ◽  
Positioning Systems ◽  
Catch Data ◽  
Global Positioning ◽  
Management Controls ◽  
The Impact ◽  
Northern Prawn Fishery

The impact of global positioning systems (GPS) and plotter systems on the relative fishing power of the northern prawn fishery fleet on tiger prawns (Penaeus esculentus Haswell, 1879, and P. semisulcatus de Haan, 1850) was investigated from commercial catch data. A generalized linear model was used to account for differences in fishing power between boats and changes in prawn abundance. It was found that boats that used a GPS alone had 4% greater fishing power than boats without a GPS. The addition of a plotter raised the power by 7% over boats without the equipment. For each year between the first to third that a fisher has been working with plotters, there is an additional 2 or 3% increase. It appears that when all boats have a GPS and plotter for at least 3 years, the fishing power of the fleet will increase by 12%. Management controls have reduced the efficiency of each boat and lowered the number of days available to fish, but this may not have been sufficient to counteract the increases. Further limits will be needed to maintain the desired levels of mortality.

Stock-recruitment relationships of the tiger prawns (Penaeus esculentus and Penaeus semisulcatus) in the Australian northern prawn fishery

1996 ◽  
Vol 47 (1) ◽  
pp. 87 ◽  
Author(s):  
YG Wang ◽  
D Die
Keyword(s):  
Population Model ◽  
Fishing Effort ◽  
Maximum Sustainable Yield ◽  
Production Model ◽  
Commercial Catch ◽  
Penaeus Semisulcatus ◽  
Spawning Stock ◽  
Tiger Prawn ◽  
Stock Recruitment ◽  
Northern Prawn Fishery

This paper investigates the stock-recruitment and equilibrium yield dynamics for the two species of tiger prawns (Penaeus esculentus and Penaeus semisulcatus) in Australia's most productive prawn fishery: the Northern Prawn Fishery. Commercial trawl logbooks for 1970-93 and research surveys are used to develop population models for these prawns. A population model that incorporates continuous recruitment is developed. Annual spawning stock and recruitment indices are then estimated from the population model. Spawning stock indices represent the abundance of female prawns that are likely to spawn; recruitment indices represent the abundance of all prawns less than a certain size. The relationships between spawning stock and subsequent recruitment (SRR), between recruitment and subsequent spawning stock (RSR), and between recruitment and commercial catch were estimated through maximum-likelihood models that incorporated autoregressive terms. Yield as a function of fishing effort was estimated by constraining to equilibrium the SRR and RSR. The resulting production model was then used to determine maximum sustainable yield (MSY) and its corresponding fishing effort (fMSY). Long-term yield estimates for the two tiger prawn species range between 3700 and 5300 t. The fishing effort at present is close to the level that should produce MSY for both species of tiger prawns. However, current landings, recruitment and spawning stock are below the equilibrium values predicted by the models. This may be because of uncertainty in the spawning stock-recruitment relationships, a change in carrying capacity, biased estimates of fishing effort, unreliable catch statistics, or simplistic assumptions about stock structure. Although our predictions of tiger prawn yields are uncertain, management will soon have to consider new measures to counteract the effects of future increases in fishing effort.

Incidental capture and mortality of Sea Turtles in Australia's northern Prawn Fishery

1990 ◽  
Vol 41 (1) ◽  
pp. 97 ◽  
Author(s):  
IR Poiner ◽  
RC Buckworth ◽  
ANM Harris
Keyword(s):  
Sea Turtles ◽  
Chelonia Mydas ◽  
Fishing Effort ◽  
Olive Ridley ◽  
Commercial Catch ◽  
Lepidochelys Olivacea ◽  
Incidental Capture ◽  
Management Measures ◽  
The Impact ◽  
Northern Prawn Fishery

Species composition, catch and mortality rates of sea turtles captured in the tiger prawn segment of Australia's northern prawn fishery were estimated from six prawn research surveys and three commercial catch monitoring programmes. Four species of turtles were captured in the research surveys: the flatback (Natator depressa, 43%) was the dominant species, although the loggerhead (Caretta caretta, 19%) and the olive Ridley (Lepidochelys olivacea, 15%) were common and the green turtle (Chelonia mydas, 4%) was occasionally captured. The size of the turtle catches varied with the duration of the trawl and water depth: the highest catch rates (turtles per standard net-h) were from trawls of 90 min or more in water less than 25 m deep: no turtles were captured in water deeper than 43 m. The rate of mortality amongst captured turtles also varied with trawl duration; there was no mortality recorded in trawls of less than 90 min, 5% mortality in trawls of 165 min, and 7% in trawls of 180 min. The incidence of capture in the commercial fishery was 0.045 (�0.006) turtles per 180-min trawl, with 0.0027 (�0.0014) turtles per 180-min trawl drowning in the nets. If it is assumed that these rates have been constant over the history of the fishery, then on the basis of the annual fishing effort, an average of 5730 (�1907) turtles have been caught per year [of which an average of 344 (�125) drowned]. Since the introduction of management measures in 1987 to reduce effort in the fishery, the number captured declined to about 4114 (�1369) turtles in 1988, of which an estimated 247 (k90) turtles drowned. It is concluded that the impact of trawl-induced drownings on the turtle populations is probably not of such proportions as to create immediate concern.

scholarly journals Effects of fish density distribution and effort distribution on catchability

2006 ◽  
Vol 64 (1) ◽  
pp. 178-191 ◽  
Author(s):  
Nick Ellis ◽  
You-Gan Wang
Keyword(s):  
Density Distribution ◽  
Fish Density ◽  
Catch Per Unit Effort ◽  
Commercial Catch ◽  
Aggregation Index ◽  
Management Advice ◽  
Analytical Expressions ◽  
Northern Prawn Fishery ◽  
Stock Abundance ◽  
Effort Distribution

Abstract Ellis, N., and Wang, Y-G. 2007. Effects of fish density distribution and effort distribution on catchability – ICES Journal of Marine Science, 64, 178–191. The effects of fish density distribution and effort distribution on the overall catchability coefficient are examined. Emphasis is also on how aggregation and effort distribution interact to affect overall catch rate [catch per unit effort (cpue)]. In particular, it is proposed to evaluate three indices, the catchability index, the knowledge parameter, and the aggregation index, to describe the effectiveness of targeting and the effects on overall catchability in the stock area. Analytical expressions are provided so that these indices can easily be calculated. The average of the cpue calculated from small units where fishing is random is a better index for measuring the stock abundance. The overall cpue, the ratio of lumped catch and effort, together with the average cpue, can be used to assess the effectiveness of targeting. The proposed methods are applied to the commercial catch and effort data from the Australian northern prawn fishery. The indices are obtained assuming a power law for the effort distribution as an approximation of targeting during the fishing operation. Targeting increased catchability in some areas by 10%, which may have important implications on management advice.

A Length-Based Stock Assessment Method Utilizing a Generalized Delay-Difference Model

1987 ◽  
Vol 44 (2) ◽  
pp. 422-437 ◽  
Author(s):  
David A. Fournier ◽  
Ian J. Doonan
Keyword(s):  
Stock Assessment ◽  
Length Distribution ◽  
Optimal Level ◽  
Fish Population ◽  
Assessment Method ◽  
Fishing Effort ◽  
Difference Model ◽  
Difference Methods ◽  
Stock Depletion ◽  
Delay Difference

We present a length-based stock assessment method based on a generalization of the delay-difference methods of Deriso. Data inputs to the model include the estimated weight of the catch, the estimated fishing effort, the estimated mean weight of the catch, and the estimated central moments of the length distribution of the catch. The model's performance is demonstrated by applying it to data from a simulated exploited fish population exhibiting biomass-dependent catchability which would cause conventional catch–effort models to seriously underestimate the extent of stock depletion. The model was generally able to detect the presence of the biomass-dependent catchability and to correctly estimate the optimal level of fishing effort.

scholarly journals Modelling of stock dynamics for spiny king crab Paralithodes brevipes at southern Kuril Islands using a finite-difference model with delay

2016 ◽  
Vol 185 (2) ◽  
pp. 102-111
Author(s):  
Igor S. Chernienko
Keyword(s):  
Finite Difference ◽  
Kuril Islands ◽  
Difference Model ◽  
Commercial Catch ◽  
King Crab ◽  
Finite Difference Model ◽  
Production Models ◽  
Living Species ◽  
Biomass Dynamics ◽  
Catch Per Effort

The information on fishery object limited by CPUE data and fragmentary data on age and size is sufficient for production models. However, this type of models is improper for long-living species, as crabs, because of problem with assumption on equilibrium stock. Describing dynamics of a single year-class, these models average the parameters for all generations that impedes to use them for assessment of crabs stocks. Finite-difference models with delay are more promising in this case. Deriso-Snute finite-difference model with delay was used for simulating of the spiny king crab biomass dynamics at southern Kuril Islands and forecasting of TAC for this species. Parameters of the model were estimated using the algorithm of sampling by scheme of Markov chain. The model is relatively simple and undemanding to data - time-series of commercial catch per effort is sufficient for its simplest version. Results of modeling are comparable with the results of cohort models.

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