scholarly journals Review of integrated size-structured models for stock assessment of hard-to-age crustacean and mollusc species

2013 ◽  
Vol 70 (1) ◽  
pp. 16-33 ◽  
Author(s):  
Andre E. Punt ◽  
TzuChuan Huang ◽  
Mark N. Maunder
Keyword(s):  
Stock Assessment ◽  
Age Distribution ◽  
Size Composition ◽  
Data Sources ◽  
Multiple Sources ◽  
Surplus Production ◽  
Production Models ◽  
Stock Assessments ◽  
Mollusc Species ◽  
Size At Age

Abstract Punt, A. E., Huang, T., and Maunder, M. N. 2013. Review of integrated size-structured models for stock assessment of hard-to-age crustacean and mollusc species. – ICES Journal of Marine Science, 70:16–33. Crustaceans and molluscs such as crabs, rock lobsters, prawns, abalone, and oysters constitute large and valuable fisheries. However, assessments of these species are hampered because they cannot be production aged, in contrast to many teleosts. The major data sources for these species, in addition to catch and abundance index data, are the size compositions of the catches and of any fishery-independent indices. Assessments of such species have been conducted using age-based methods of stock assessment, as well as surplus production models. However, size-structured methods are now preferred because they can make full use of size-composition data, are able to integrate multiple sources of data, and produce the types of outputs which are needed for management purposes. An advantage of size-based models over age-based models is that all processes can be size-based, and these processes can modify the (unmodelled) size-at-age distribution. We review these methods, highlighting the choices that need to be made when developing integrated size-structured stock assessments, the data sources which are typically available and how they are used for parameter estimation, and contrast a number of such assessments worldwide.

scholarly journals Bayesian state-space models with multiple CPUE data: the case of a mullet fishery

2017 ◽  
Vol 81 (3) ◽  
pp. 361 ◽  
Author(s):  
Rodrigo Sant’Ana ◽  
Paul Gerhard Kinas ◽  
Laura Villwock de Miranda ◽  
Paulo Ricardo Schwingel ◽  
Jorge Pablo Castello ◽  
...  
Keyword(s):  
State Space ◽  
Stock Assessment ◽  
Reference Points ◽  
State Space Models ◽  
Southern Population ◽  
Catch Per Unit Effort ◽  
Bayesian Hierarchical ◽  
Surplus Production ◽  
Production Models ◽  
Borrowing Strength

We propose a novel Bayesian hierarchical structure of state-space surplus production models that accommodate multiple catch per unit effort (CPUE) data of various fisheries exploiting the same stock. The advantage of this approach in data-limited stock assessment is the possibility of borrowing strength among different data sources to estimate reference points useful for management decisions. The model is applied to thirteen years of data from seven fisheries of the lebranche mullet (Mugil liza) southern population, distributed along the southern and southeastern shelf regions of Brazil. The results indicate that this modelling strategy is useful and has room for extensions. There are reasons for concern about the sustainability of the mullet stock, although the wide posterior credibility intervals for key reference points preclude conclusive statistical evidence at this time

scholarly journals Simulation testing the robustness of stock assessment models to error: some results from the ICES strategic initiative on stock assessment methods

2014 ◽  
Vol 72 (1) ◽  
pp. 19-30 ◽  
Author(s):  
J.J. Deroba ◽  
D.S. Butterworth ◽  
R.D. Methot ◽  
J.A.A. De Oliveira ◽  
C. Fernandez ◽  
...  
Keyword(s):  
Large Scale ◽  
Stock Assessment ◽  
Assessment Methods ◽  
Fish Stocks ◽  
Production Models ◽  
Self Testing ◽  
Stock Assessments ◽  
The World ◽  
Simulation Testing ◽  
Pseudo Data

Abstract The World Conference on Stock Assessment Methods (July 2013) included a workshop on testing assessment methods through simulations. The exercise was made up of two steps applied to datasets from 14 representative fish stocks from around the world. Step 1 involved applying stock assessments to datasets with varying degrees of effort dedicated to optimizing fit. Step 2 was applied to a subset of the stocks and involved characteristics of given model fits being used to generate pseudo-data with error. These pseudo-data were then provided to assessment modellers and fits to the pseudo-data provided consistency checks within (self-tests) and among (cross-tests) assessment models. Although trends in biomass were often similar across models, the scaling of absolute biomass was not consistent across models. Similar types of models tended to perform similarly (e.g. age based or production models). Self-testing and cross-testing of models are a useful diagnostic approach, and suggested that estimates in the most recent years of time-series were the least robust. Results from the simulation exercise provide a basis for guidance on future large-scale simulation experiments and demonstrate the need for strategic investments in the evaluation and development of stock assessment methods.

scholarly journals STOCK ASSESSMENT AND LONG-TERM DYNAMICS OF AZOV SEA ROACH (RUSSIAN WATERS), BASED ON CMSY MODEL FOR DATA-LIMITED MODELLING IN PERIOD (1999-2019)

Fisheries ◽  
2020 ◽  
Vol 2020 (6) ◽  
pp. 88-94
Author(s):  
Nikolay Zherdev ◽  
M. Pyatinsky ◽  
Inna Kozobrod
Keyword(s):  
River Flow ◽  
Stock Assessment ◽  
Rutilus Rutilus ◽  
Roach Rutilus Rutilus ◽  
Surplus Production ◽  
Azov Sea ◽  
Production Models ◽  
Stock Biomass ◽  
Russian Waters

Stock assessment of Azov sea roach Rutilus rutilus (Linnaeus, 1758) has been performed by CMSY model in period 1999-2019 by data-limited modelling in R. The current population status – in biological safe zone for stock biomass and no overfishing signals (B2019/BMSY = 1,32, F2019/FMSY = 0,53). Perhaps, current paper results can be a slightly incomplete in background that there is no relevant data about IUU fishery ever exists, which can lead to fishing mortality underestimation. Azov sea roach population continue to be in “depleted” status after river flow regulation in 1950’s. Joined continuous biomass estimates time series over whole fishing his-tory 1932–2019 showed at least 2 population collapses: in 1940’s and 1980’s years. According to model re-sults TAC (total allowed catch) should be accepted at level 516.9 t. If the recommendation is followed stock biomass will stay at safety in level 1828.1 t. Data limited modelling shows a good performance for sea roach in background of data lucking and in this reason still the best choose against cohor or surplus production models.

Fishery stock assessment of Kiddi shrimp (Parapenaeopsis stylifera) in the Northern Arabian Sea Coast of Pakistan by using surplus production models

2016 ◽  
Vol 35 (4) ◽  
pp. 936-946 ◽  
Author(s):  
Muhammad Mohsin ◽  
Yongtong Mu ◽  
Aamir Mahmood Memon ◽  
Muhammad Talib Kalhoro ◽  
Syed Baber Hussain Shah
Keyword(s):  
Arabian Sea ◽  
Stock Assessment ◽  
Surplus Production ◽  
Production Models ◽  
Northern Arabian Sea ◽  
Sea Coast

scholarly journals Censored catch data in fisheries stock assessment

2005 ◽  
Vol 62 (6) ◽  
pp. 1118-1130 ◽  
Author(s):  
T.R. Hammond ◽  
V.M. Trenkel
Keyword(s):  
Stock Assessment ◽  
Recursive Partitioning ◽  
Maximum Sustainable Yield ◽  
Production Model ◽  
Model Parameters ◽  
Commercial Fish ◽  
Surplus Production ◽  
Stock Assessments ◽  
Surplus Production Model ◽  
Simulation Parameters

Abstract Landings statistics can be lower than true catches because many fish are discarded or landed illegally. Since many discards do not survive, treating landings as true catches can lead to biased stock assessments. This paper proposes treating catch as censored by bounding it below by the landings, L, and above by cL (for scalar c > 1). We demonstrate the approach with a simulation study, using a Schaefer surplus production model. Parameters were estimated in a Bayesian framework with BUGS software using two sets of priors. Both the traditional true-catch method and a survey-and-effort method (which was landings free) performed worse on average than the censored approach, as measured by the Bayes risk associated with estimates of maximum sustainable yield (MSY) and of an index of depletion (X). Recursive partitioning (regression trees) was used to associate simulation parameters to best-performing methods, showing that higher commercial fish catchability favoured the censored method at estimating X. In conclusion, censored methods provide a means of dealing with discarding and misreporting that can outperform some traditional alternatives.

Stock Assessment Problems in Atlantic Herring (Clupea harengus) in the Northwest Atlantic

1985 ◽  
Vol 42 (5) ◽  
pp. 888-898 ◽  
Author(s):  
M. Sinclair ◽  
V. C. Anthony ◽  
T. D. Iles ◽  
R. N. O'Boyle
Keyword(s):  
Stock Assessment ◽  
Population Analysis ◽  
Age Distribution ◽  
Clupea Harengus ◽  
Assessment Process ◽  
Atlantic Herring ◽  
Management Units ◽  
Management Measures ◽  
Stock Assessments ◽  
Assessment Problems

Total annual catches of Atlantic herring (Clupea harengus) in NAFO statistical areas 3–6 have declined steadily since 1968, and have not rebounded after management measures were implemented in the late 1970's (unlike demersal species in the area). The accuracy of the biomass estimates generated by sequential population analysis is evaluated by a retrospective analysis for 3 of the 10 management units for herring fisheries. In each case, the stock assessments have tended to seriously underestimate the declines in stock abundance and overestimate the upswings. Fishing mortalities have exceeded F0.1, but they have rarely exceeded Fmax, the level below which growth overfishing is prevented. Three assumptions in the stock assessment process are evaluated in relation to the 4WX management unit: (1) the various management units are in fact self-sustaining populations; (2) catchability (i.e. fishing mortality per unit of effort) is constant and independent of stock size; and (3) the population is in the stable age distribution. We conclude that at least part of the management failures are due to invalid assumptions in the stock assessment models. An approach that has prevented growth overfishing may well have caused recruitment overfishing. Atlantic herring should be managed on principles suited to salmon rather than those applied to groundfish.

scholarly journals Assessing the Potential of Catch-Only Models to Inform on the State of Global Fisheries and the UN’s SDGs

2021 ◽  
Vol 13 (11) ◽  
pp. 6101
Author(s):  
Rishi Sharma ◽  
Henning Winker ◽  
Polina Levontin ◽  
Laurence Kell ◽  
Dan Ovando ◽  
...  
Keyword(s):  
Stock Assessment ◽  
Fishing Effort ◽  
The State ◽  
Sources Of Information ◽  
Ongoing Research ◽  
Traditional Assessment ◽  
Stock Status ◽  
Stock Assessments ◽  
Recent Developments ◽  
Measure Of Performance

Catch-only models (COMs) have been the focus of ongoing research into data-poor stock assessment methods. Two of the most recent models that are especially promising are (i) CMSY+, the latest refined version of CMSY that has progressed from Catch-MSY, and (ii) SRA+ (Stock Reduction Analysis Plus) a recent developments in field. Comparing COMs and evaluating their relative performance is essential for determining the state of regional and global fisheries that may be lacking necessary data that would be required to run traditional assessment models. In this paper we interrogate how performance of COMs can be improved by incorporating additional sources of information. We evaluate the performance of COMs on a dataset of 48 data-rich ICES (International Council for the Exploration of Seas) stock assessments. As one measure of performance, we consider the ability of the model to correctly classify stock status using FAO’s 3-tier classification that is also used for reporting on sustainable development goals to the UN. Both COMs showed notable bias when run with their inbuilt default heuristics, but as the quality of prior information increased, classification rates for the terminal year improved substantially. We conclude that although further COM refinements show some potential, most promising is the ongoing research into developing biomass or fishing effort priors for COMs in order to be able to reliably track stock status for the majority of the world’s fisheries currently lacking stock assessments.

scholarly journals Photovoltaic Power Forecasting: Assessment of the Impact of Multiple Sources of Spatio-Temporal Data on Forecast Accuracy

Energies ◽  
2021 ◽  
Vol 14 (5) ◽  
pp. 1432
Author(s):  
Xwégnon Ghislain Agoua ◽  
Robin Girard ◽  
Georges Kariniotakis
Keyword(s):  
Satellite Images ◽  
Forecast Accuracy ◽  
Absolute Error ◽  
Data Sources ◽  
Test Case ◽  
Temporal Data ◽  
Multiple Sources ◽  
Forecasting Error ◽  
Spatio Temporal ◽  
The Impact

The efficient integration of photovoltaic (PV) production in energy systems is conditioned by the capacity to anticipate its variability, that is, the capacity to provide accurate forecasts. From the classical forecasting methods in the state of the art dealing with a single power plant, the focus has moved in recent years to spatio-temporal approaches, where geographically dispersed data are used as input to improve forecasts of a site for the horizons up to 6 h ahead. These spatio-temporal approaches provide different performances according to the data sources available but the question of the impact of each source on the actual forecasting performance is still not evaluated. In this paper, we propose a flexible spatio-temporal model to generate PV production forecasts for horizons up to 6 h ahead and we use this model to evaluate the effect of different spatial and temporal data sources on the accuracy of the forecasts. The sources considered are measurements from neighboring PV plants, local meteorological stations, Numerical Weather Predictions, and satellite images. The evaluation of the performance is carried out using a real-world test case featuring a high number of 136 PV plants. The forecasting error has been evaluated for each data source using the Mean Absolute Error and Root Mean Square Error. The results show that neighboring PV plants help to achieve around 10% reduction in forecasting error for the first three hours, followed by satellite images which help to gain an additional 3% all over the horizons up to 6 h ahead. The NWP data show no improvement for horizons up to 6 h but is essential for greater horizons.

Collating stock assessment packages to improve stock assessments

2021 ◽  
Vol 236 ◽  
pp. 105844
Author(s):  
Catherine M. Dichmont ◽  
Roy A. Deng ◽  
Natalie Dowling ◽  
André E. Punt
Keyword(s):  
Stock Assessment ◽  
Stock Assessments
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