scholarly journals Impact of survey design changes on stock assessment advice: sea scallops

2013 ◽  
Vol 71 (2) ◽  
pp. 320-327 ◽  
Author(s):  
Stephen J. Smith ◽  
Brad Hubley
Keyword(s):  
Nova Scotia ◽  
Survey Design ◽  
Stock Assessment ◽  
Error Component ◽  
Assessment Model ◽  
Observation Error ◽  
Design Changes ◽  
Process Error ◽  
Survey Estimates ◽  
Sea Scallops

Abstract Smith, S. J., and Hubley, B. 2014. Impact of survey design changes on stock assessment advice: sea scallops. – ICES Journal of Marine Science, 71: 320–327. Annual surveys of marine resources are used to monitor changes in population composition and abundance. Improvements in the performance and coverage of these surveys can readily be evaluated for the surveys themselves but should also be considered in the context of the stock assessment models that use the estimates from these surveys. For those surveys based on a probability design, improvements in the probability design are usually evaluated with respect to the resultant increase in precision of the survey estimates. Survey precision estimates can be included in many stock assessment models as observation error, as long as the process error component of the model is also identified. Advice on catch levels for sea scallop populations (Placopecten magellanicus) around Nova Scotia is developed using a Bayesian state space assessment model in which both observation and process error terms have been defined. Information on survey estimates of precision are included in the observation error component of the assessment model and the impacts of changes in survey precision on the provision of advice can be evaluated in terms of reference points and management advice. The sensitivity of stock assessment advice to changes in the level of precision of survey estimates was evaluated for three scallop fisheries around Nova Scotia. The results indicated that the impact of the changes depended upon the degree of concurrence between the annual changes in biomass as observed from the survey and those predicted by the model.

Estimating multifleet catchability coefficients and natural mortality from fishery catch and effort data: comparison of Bayesian state–space and observation error models

2011 ◽  
Vol 68 (7) ◽  
pp. 1171-1181 ◽  
Author(s):  
Shijie Zhou ◽  
André E. Punt ◽  
Roy Deng ◽  
Janet Bishop
Keyword(s):  
State Space ◽  
Stock Assessment ◽  
Observation Error ◽  
Natural Mortality ◽  
Posterior Median ◽  
Median Estimate ◽  
Penaeus Semisulcatus ◽  
Process Error ◽  
Two Parameters ◽  
Delay Difference

Catchability and natural mortality are key quantities in fisheries stock assessment. However, it is difficult to estimate these two parameters simultaneously using only fishery catch and effort data. A Bayesian state–space modified delay–difference model is outlined that can estimate time series of catchability by fleet as well as natural mortality. This model, and three variants thereof, is fitted to data for grooved tiger prawns ( Penaeus semisulcatus ) in Australia’s Northern Prawn Fishery during the period of the year when there is little recruitment. A model that allows for both observation and process error and estimates natural mortality is best, in terms of model selection criteria as well as fit diagnostics. The posterior median estimate for catchability for the primary target fleet ranges from 6.15 × 10−4 to 1.09 × 10−4 during 1980–2007, while the posterior median estimate for catchability for a fleet with P. semisulcatus as its byproduct is about 20% of that for the primary fleet. Fishing efficiency increased at approximately 2% annually during 1980–2007, while the weekly natural mortality is estimated to be 0.053 week–1.

scholarly journals Model averaging to streamline the stock assessment process

2014 ◽  
Vol 72 (1) ◽  
pp. 93-98 ◽  
Author(s):  
Colin P. Millar ◽  
Ernesto Jardim ◽  
Finlay Scott ◽  
Giacomo Chato Osio ◽  
Iago Mosqueira ◽  
...  
Keyword(s):  
Large Scale ◽  
Stock Assessment ◽  
Model Averaging ◽  
Assessment Model ◽  
Assessment Process ◽  
Fish Stock ◽  
Assessment Procedure ◽  
Observation Error ◽  
Fishery Policy ◽  
Fishery Science

Abstract The current fish stock assessment process in Europe can be very resource- and time-intensive. The scientists involved require a very particular set of skills, acquired over their career, drawing from biology, ecology, statistics, mathematical modelling, oceanography, fishery policy, and computing. There is a particular focus on producing a single “best” stock assessment model, but as fishery science advances, there are clear needs to address a range of hypotheses and uncertainties, from large-scale issues such as climate change to specific ones, such as high observation error on young hake. Key to our discussion is the use of the assessment for all frameworks to translate hypotheses into models. We propose a change to the current stock assessment procedure, driven by the use of model averaging to address a range of plausible hypotheses, where increased collaboration between the varied disciplines within fishery science will result in more robust advice.

Evaluation of alternative modelling approaches to account for spatial effects due to age-based movement

2017 ◽  
Vol 74 (11) ◽  
pp. 1832-1844 ◽  
Author(s):  
Hui-Hua Lee ◽  
Kevin R. Piner ◽  
Mark N. Maunder ◽  
Ian G. Taylor ◽  
Richard D. Methot
Keyword(s):  
Population Dynamics ◽  
Stock Assessment ◽  
Simulated Data ◽  
Assessment Method ◽  
Error Modeling ◽  
Assessment Model ◽  
Future Research ◽  
Observation Error ◽  
Time Varying ◽  
Spatial Effects

Spatial patterns due to age-specific movement have been a source of unmodelled process error. Modeling movement in spatially explicit stock assessments is feasible, but hampered by a paucity of data from appropriate tagging studies. This study uses simulation analyses to evaluate alternative model structures that either explicitly or implicitly account for the process of time-varying age-based movement in a population dynamics model. We simulated synthetic populations using a two-area stochastic population dynamics operating model. Simulated data were fit in seven different estimation models. Only the model that includes the correct spatial dynamic results in unbiased and precise estimates of derived and management quantities. In a single-area assessment model, using the fleets-as-area (FAA) approach may be the second best option to estimate both length-based and time-varying age-based selectivity to implicitly account for the contact selectivity and annual availability. An FAA approach adds additional observation error performed nearly as well. Future research could evaluate which stock assessment method is robust to uncertainty in movement and is more appropriate for achieving intended management objectives.

scholarly journals Effects of process and observation errors on effective sample size of fishery and survey age and length composition using variance ratio and likelihood methods

2011 ◽  
Vol 68 (7) ◽  
pp. 1548-1557 ◽  
Author(s):  
Peter-John F. Hulson ◽  
Dana H. Hanselman ◽  
Terrance J. Quinn
Keyword(s):  
Sample Size ◽  
Likelihood Function ◽  
Stock Assessment ◽  
Age Distribution ◽  
Multinomial Distribution ◽  
Effective Sample Size ◽  
Observation Error ◽  
Variance Ratio ◽  
Likelihood Methods ◽  
Process Error

Abstract Hulson, P-J. F., Hanselman, D. H., and Quinn, T. J. II. 2011. Effects of process and observation errors on effective sample size of fishery and survey age and length composition using variance ratio and likelihood methods. – ICES Journal of Marine Science, 68: 1548–1557. Observations of age or length composition from fisheries or research surveys are modelled frequently with the multinomial distribution. Violations of multinomial assumptions in data collection usually cause overdispersion of observations and consequent underestimation of uncertainty. This has led to the adoption of an effective sample size less than the actual sample size to approximate the likelihood function for age or length composition better in, for example, fishery stock assessment models. The behaviour of effective sample size is examined under different scenarios for population age distribution and sampling design. Effective sample size was approximated with three approaches: (i) the ratio of multinomial to empirical variance; (ii) sampling estimation; and (iii) the Dirichlet likelihood. The most significant changes in effective sample size were attributable to process error involving aggregation of ages within schools. In terms of observation error, effective sample size can be increased by increasing the number of tows from which samples are obtained for age or length composition, then, because of the reduced uncertainty in effective sample size, the Dirichlet likelihood can be integrated into the objective function of fishery stock assessment models to estimate the effective sample size in future assessments.

Estimate of the Ipswich Sparrow population on Sable Island, Nova Scotia, in 1998, using a random-transect survey design

2003 ◽  
Vol 81 (5) ◽  
pp. 771-779 ◽  
Author(s):  
Stephen J Smith ◽  
Zoe Lucas ◽  
Wayne T Stobo
Keyword(s):  
Nova Scotia ◽  
Patch Size ◽  
Survey Design ◽  
Breeding Habitat ◽  
Vegetation Types ◽  
Bird Population ◽  
Passerculus Sandwichensis ◽  
The Status ◽  
Survey Estimates ◽  
Statistical Survey

The Ipswich Sparrow (Passerculus sandwichensis princeps) population on Sable Island, Nova Scotia, has been designated as "vulnerable" by the Committee on the Status of Endangered Wildlife in Canada (COSEWIC). Previous surveys of this population during the nesting season have varied in coverage and the rigour of statistical-survey design. In 1998 we surveyed the population using a stratified random-transect design. Estimated total numbers (±SE) were obtained along with confidence intervals calculated using bootstrap methods. The precision of our survey estimates would permit detection of population differences on the order of 20%. Higher densities of birds were observed in areas with heath, grass (fescue), and beach grass and pea vegetation types than in areas with other vegetation types. However, densities within these favoured vegetation types were constant with increasing transect length, which appears to be contrary to patterns expected from using published models of the effects of breeding habitat patch size on bird population density. Topographical constraints characteristic of Sable Island may impose limits on the birds' territorial boundaries and constrain density, independently of patch size.

scholarly journals Stock assessment and projections incorporating discard estimates in some years: an application to the hake stock in ICES Divisions VIIIc and IXa

2010 ◽  
Vol 67 (6) ◽  
pp. 1185-1197 ◽  
Author(s):  
C. Fernández ◽  
S. Cerviño ◽  
N. Pérez ◽  
E. Jardim
Keyword(s):  
Time Series ◽  
Stock Assessment ◽  
Reference Points ◽  
Assessment Model ◽  
Marine Science ◽  
Fishing Mortality ◽  
Change Over Time ◽  
Age Structured ◽  
Available Information ◽  
Over Time

Abstract Fernández, C., Cerviño, S., Pérez, N., and Jardim, E. 2010. Stock assessment and projections incorporating discard estimates in some years: an application to the hake stock in ICES Divisions VIIIc and IXa. – ICES Journal of Marine Science, 67: 1185–1197. A Bayesian age-structured stock assessment model is developed to take into account available information on discards and to handle gaps in the time-series of discard estimates. The model incorporates mortality attributable to discarding, and appropriate assumptions about how this mortality may change over time are made. The result is a stock assessment that accounts for information on discards while, at the same time, producing a complete time-series of discard estimates. The method is applied to the hake stock in ICES Divisions VIIIc and IXa, for which the available data indicate that some 60% of the individuals caught are discarded. The stock is fished by Spain and Portugal, and for each country, there are discard estimates for recent years only. Moreover, the years for which Portuguese estimates are available are only a subset of those with Spanish estimates. Two runs of the model are performed; one assuming zero discards and another incorporating discards. When discards are incorporated, estimated recruitment and fishing mortality for young (discarded) ages increase, resulting in lower values of the biological reference points Fmax and F0.1 and, generally, more optimistic future stock trajectories under F-reduction scenarios.

scholarly journals Correcting density-dependent effects in abundance estimates from bottom-trawl surveys

2014 ◽  
Vol 71 (5) ◽  
pp. 1107-1116 ◽  
Author(s):  
Stan Kotwicki ◽  
James N. Ianelli ◽  
André E. Punt
Keyword(s):  
Stock Assessment ◽  
Dead Zone ◽  
Walleye Pollock ◽  
Assessment Model ◽  
Bottom Trawl ◽  
Trawl Survey ◽  
Negative Consequences ◽  
Catch Per Unit Effort ◽  
Density Dependent ◽  
Index Of Abundance

Abstract Indices of abundance are important for estimating population trends in stock assessment and ideally should be based on fishery-independent surveys to avoid problems associated with the hyperstability of the commercial catch per unit effort (cpue) data. However, recent studies indicate that the efficiency of the survey bottom trawl (BT) for some species can be density-dependent, which could affect the reliability of survey-derived indices of abundance. A function qe∼f(u), where qe is the BT efficiency and u the catch rate, was derived using experimentally derived acoustic dead-zone correction and BT efficiency parameters obtained from combining a subset of BT catch data with synchronously collected acoustic data from walleye pollock (Theragra chalcogramma) in the eastern Bering Sea (EBS). We found that qe decreased with increasing BT catches resulting in hyperstability of the index of abundance derived from BT survey. Density-dependent qe resulted in spatially and temporarily variable bias in survey cpue and biased population age structure derived from survey data. We used the relationship qe∼f(u) to correct the EBS trawl survey index of abundance for density-dependence. We also obtained a variance–covariance matrix for a new index that accounted for sampling variability and the uncertainty associated with the qe. We found that incorporating estimates of the new index of abundance changed outputs from the walleye pollock stock assessment model. Although changes were minor, we advocate incorporating estimates of density-dependent qe into the walleye pollock stock assessment as a precautionary measure that should be undertaken to avoid negative consequences of the density-dependent qe.

Spatiotemporal modelling for the annual egg production method of stock assessment using generalized additive models

1998 ◽  
Vol 55 (12) ◽  
pp. 2608-2621 ◽  
Author(s):  
N H Augustin ◽  
D L Borchers ◽  
E D Clarke ◽  
S T Buckland ◽  
M Walsh
Keyword(s):  
Environmental Variables ◽  
Egg Production ◽  
Survey Design ◽  
Stock Assessment ◽  
Generalized Additive Models ◽  
Production Method ◽  
Additive Models ◽  
Atlantic Mackerel ◽  
Egg Density ◽  
Survey Designs

Generalized additive models (GAMs) are used to model the spatiotemporal distribution of egg density as a function of locational and environmental variables. The main aim of using GAMs is to improve precision of egg abundance estimates needed for the annual egg production method. The application of GAMs requires a survey design with good coverage in space and time. If the only results available are from less optimal survey designs, they can be improved by using historical data for spawning boundaries. The method is applied to plankton egg survey data of Atlantic mackerel (Scomber scombrus) in 1995. The GAM-based method improves the precision of estimates substantially and is also useful in explaining complex space-time trends using environmental variables.

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