scholarly journals Trends in Pacific Canadian groundfish stock status

2021 ◽  
Author(s):  
Sean C Anderson ◽  
Brendan M Connors ◽  
Philina A English ◽  
Robyn E Forrest ◽  
Rowan Haigh ◽  
...  
Keyword(s):  
Time Series ◽  
Credible Interval ◽  
Maximum Sustainable Yield ◽  
Sustainable Yield ◽  
Pacific Cod ◽  
Strait Of Georgia ◽  
Individual Transferable Quotas ◽  
Stock Status ◽  
Stock Assessments ◽  
Trawl Surveys

We assembled estimated biomass (B) time series from stock assessments for 24 Pacific Canadian groundfish stocks and modelled average and stock status through 2020 based on biomass relative to each stock's (1) Limit Reference Point (B/LRP), (2) Upper Stock Reference (B/USR), and (3) biomass at maximum sustainable yield (B/BMSY). The overall mean B/LRP in 2020 was 3.2 (95% credible interval [CI]: 2.6-3.9). The overall mean B/USR and B/BMSY in 2020 was 1.5 (95% CI: 1.3-1.9) and 1.4 (95% CI: 1.1-1.7), respectively. Average stock status declined from 1950 to around 2000 and has remained relatively stable since then. The change around 2000 followed the implementation of ITQs (individual transferable quotas) for the trawl fleet and the commencement of the synoptic trawl surveys. As of their last assessment, four stocks (Strait of Georgia Lingcod [Area 4B], coastwide Bocaccio, and inside and outside Quillback Rockfish) had a greater than 5% probability of being below their LRP (i.e., in the "critical zone"); Pacific Cod in Area 3CD had a 4.6% probability. Roughly one-third of stocks had a greater than 1 in 4 chance of being below their USR (i.e., in the "cautious zone"). Conversely, two-thirds of assessed groundfish stocks had a high (>75%) probability of being above the USR (i.e., in the "healthy zone").

scholarly journals Delay in fishery management: diminished yield, longer rebuilding, and increased probability of stock collapse1

2006 ◽  
Vol 64 (1) ◽  
pp. 149-159 ◽  
Author(s):  
Kyle W. Shertzer ◽  
Michael H. Prager
Keyword(s):  
Fishery Management ◽  
Economic Loss ◽  
Maximum Sustainable Yield ◽  
Sustainable Yield ◽  
Short Term ◽  
Stock Status ◽  
Stock Biomass ◽  
Spawning Stock ◽  
Stock Recruitment ◽  
Stock Collapse

Abstract Shertzer, K. W., and Prager, M. H. 2007. Delay in fishery management: diminished yield, longer rebuilding, and increased probability of stock collapse. ICES Journal of Marine Science, 64: 149–159. When a stock is depleted, catch reductions are in order, but typically they are implemented only after considerable delay. Delay occurs because fishery management is political, and stricter management, which involves short-term economic loss, is unpopular. Informed of stock decline, managers often hesitate, perhaps pondering the uncertainty of scientific advice, perhaps hoping that a good year class will render action moot. However, management delay itself can have significant costs, when it exacerbates stock decline. To examine the biological consequences of delay, we simulated a spectrum of fisheries under various degrees of delay in management. Increased delay required larger catch reductions, for more years, to recover benchmark stock status (here, spawning-stock biomass at maximum sustainable yield). Management delay caused stock collapse most often under two conditions: (1) when the stock–recruitment relationship was depensatory, or (2) when catchability, unknown to the assessment, was density-dependent and fishing took juveniles. In contrast, prompt management resulted in quicker recoveries and higher cumulative yields from simulated fisheries. Benefits to stock biomass and fishery yield can be high from implementing management promptly.

scholarly journals The estimation of potential yield and stock status using life–history parameters

2005 ◽  
Vol 360 (1453) ◽  
pp. 163-170 ◽  
Author(s):  
J. R. Beddington ◽  
G. P. Kirkwood
Keyword(s):  
Life History ◽  
Growth Parameters ◽  
Maximum Yield ◽  
Maximum Sustainable Yield ◽  
Sustainable Yield ◽  
Fishing Mortality ◽  
Potential Yield ◽  
Stock Status ◽  
Fishing Capacity ◽  
Stock Recruitment

Using life–history invariants, this paper develops techniques that allow the estimation of maximum sustainable yield and the fishing mortality rate that produces the maximum yield from estimates of the growth parameters, the length at first capture and the steepness of the stock recruitment relationship. This allows sustainable yields and fishing capacity to be estimated from sparse data, such as those available for developing country fisheries.

Analyzing Catch–Effort Data Allowing for Randomness in the Catching Process

1986 ◽  
Vol 43 (1) ◽  
pp. 174-186 ◽  
Author(s):  
William J. Reed
Keyword(s):  
Time Series ◽  
Dynamic Model ◽  
Stochastic Dynamics ◽  
Maximum Sustainable Yield ◽  
Reliable Data ◽  
Model Parameters ◽  
Sustainable Yield ◽  
Deterministic Dynamic ◽  
Method Of Maximum Likelihood ◽  
Bivariate Time Series

For many fisheries the only reliable data is a (bivariate) time series of catches and efforts. Most existing methods of analyzing such data implicitly assume that the main source of randomness is in the dynamics of the population, while ignoring randomness in the catching process. The assumption of a deterministic catch production function (usually of the Schaefer form C = qEX) must be contrary to the experience of almost everyone who has ever gone fishing. In this paper a stochastic catch model coupled with a deterministic dynamic model is used in the analysis of catch–effort data and shown to give very plausible results. Estimates (with confidence intervais) of catchability, maximum sustainable yield, and other dynamic model parameters are obtained numerically by the method of maximum likelihood. The incorporation of stochastic dynamics with the stochastic catch model is difficult.

scholarly journals Extracting groundfish survey indices from the Ocean Biogeographic Information System (OBIS): an example from Fisheries and Oceans Canada

2009 ◽  
Vol 67 (4) ◽  
pp. 638-645 ◽  
Author(s):  
Daniel Ricard ◽  
Robert M. Branton ◽  
Donald W. Clark ◽  
Peter Hurley
Keyword(s):  
Time Series ◽  
Information System ◽  
Trawl Survey ◽  
Independent Information ◽  
Stock Assessments ◽  
The World ◽  
Abundance Trends ◽  
Selected Subset ◽  
Temporal Abundance ◽  
Trawl Surveys

Abstract Ricard, D., Branton, R. M., Clark, D. W., and Hurley, P. 2010. Extracting groundfish survey indices from the Ocean Biogeographic Information System (OBIS): an example from Fisheries and Oceans Canada. – ICES Journal of Marine Science, 67: 638–645. Scientific trawl surveys have been conducted in different regions of the world and by a variety of countries and agencies since the mid-1900s. Although the data are collected in a scientifically and statistically appropriate context and represent an important source of fishery-independent information for agency-specific stock assessments, their use and dissemination has often been limited to the agencies conducting the surveys. In recent years, Internet data portals such as the Ocean Biogeographic Information System have provided an arena for the wider distribution and use of marine fish data. Despite the increased accessibility of such data, their scientific acceptability has been limited by a lack of reproducibility in data analyses. We present a methodology for the computation of time-series of groundfish stock indices using publicly available trawl survey data derived from the Canadian Department of Fisheries and Oceans Maritimes region. Potential pitfalls associated with the computation of time-series are discussed and proper stratified random estimates of temporal abundance trends are compared with other methods for a selected subset of species. Also, the broader applicability of the methods for datasets collected under similar sampling designs is discussed, along with the reproducibility of the analyses and results.

scholarly journals Implications of late-in-life density-dependent growth for fishery size-at-entry leading to maximum sustainable yield

2018 ◽  
Vol 75 (4) ◽  
pp. 1296-1305 ◽  
Author(s):  
Rob van Gemert ◽  
Ken H Andersen
Keyword(s):  
Density Dependence ◽  
Maximum Sustainable Yield ◽  
Sustainable Yield ◽  
Fish Stocks ◽  
Density Dependent ◽  
Large Size ◽  
Adult Growth ◽  
Stock Assessments ◽  
Stock Recruitment ◽  
Dependent Growth

Abstract Currently applied fisheries models and stock assessments rely on the assumption that density-dependent regulation only affects processes early in life, as described by stock–recruitment relationships. However, many fish stocks also experience density-dependent processes late in life, such as density-dependent adult growth. Theoretical studies have found that, for stocks which experience strong late-in-life density dependence, maximum sustainable yield (MSY) is obtained with a small fishery size-at-entry that also targets juveniles. This goes against common fisheries advice, which dictates that primarily adults should be fished. This study aims to examine whether the strength of density-dependent growth in actual fish stocks is sufficiently strong to reduce optimal fishery size-at-entry to below size-at-maturity. A size-structured model is fitted to three stocks that have shown indications of late-in-life density-dependent growth: North Sea plaice (Pleuronectes platessa), Northeast Atlantic (NEA) mackerel (Scomber scombrus), and Baltic sprat (Sprattus sprattus balticus). For all stocks, the model predicts exploitation at MSY with a large size-at-entry into the fishery, indicating that late-in-life density dependence in fish stocks is generally not strong enough to warrant the targeting of juveniles. This result lends credibility to the practise of predominantly targeting adults in spite of the presence of late-in-life density-dependent growth.

Practical uses of non-parametric methods in fisheries assessment modelling

2012 ◽  
Vol 63 (7) ◽  
pp. 606 ◽  
Author(s):  
R. M. Hillary
Keyword(s):  
Neural Networks ◽  
Artificial Neural Networks ◽  
Stock Assessment ◽  
Maximum Sustainable Yield ◽  
Sustainable Yield ◽  
Data Sets ◽  
Scientific Advice ◽  
Parametric Methods ◽  
Stock Status ◽  
Statistical Framework

The vast majority of fisheries stock assessment modelling is parametric, where specific models are assumed and fitted to data, the results of which are used to assess stock status and provide scientific advice. Often, the assumed models may not acceptably explain the data, or the data are not informative enough to estimate the parameters of even the most simple models. Using a fully inferential statistical framework, artificial neural networks were fitted to example data sets (stock-recruit, catch and relative abundance) and key assessment quantities such as maximum sustainable yield and relative biomass depletion were estimated. The combination of flexibility and statistical rigor suggests there is an as yet under-utilised role for such approaches in stock assessment, and not just in data-poor scenarios.

scholarly journals STATUS STOK GENUS Rastrelliger spp. SEBAGAI DASAR PENGELOLAAN PERIKANAN (STUDI KASUS PERAIRAN SELAT SUNDA)

2016 ◽  
Vol 18 (2) ◽  
pp. 73
Author(s):  
Wulandari Sarasati ◽  
Mennofatria Boer ◽  
Sulistiono Sulistiono
Keyword(s):  
Maximum Sustainable Yield ◽  
Production Model ◽  
Sustainable Yield ◽  
Growth Coefficient ◽  
Surplus Production ◽  
Stock Status ◽  
Surplus Production Model ◽  
Exploitation Rate ◽  
Two Peaks ◽  
Recruitment Period

The Rastrelliger spp. is one of the important commodities of the Sunda Strait. This research aimsto analyze the stock status of Rastrelliger spp. Including R. faughni, R. kanagurta and R. brachysoma in Sunda Strait that landed at the Fishery Harbor (PPP) Labuan, Banten. The sampling was conducted in April-August 2015. The data was collected using Random stratified sampling based on the fish size, small, medium and large. The length of the sample was measured and classified into male and female. The data were analyzed using FISAT II ELEFAN I software to present the stock with growth, recruitment, surplus production model, and mortality and rate of exploitation parameters. The results show that R. faughni has L∞ values for females and males respectively of 264.00 mm and 288.69 mm, 293.09 mm and 330.24 mm R. kanagurta and R. brachysoma 272.04 mm and 286.42. Growth Performs Index (GPI) on R. faughni of 4.2758, R. kanagurta of 4.1673, and on R. brachysoma of 4.2076. The growth coefficient of female and male R. faughni was 0.22 and 0.16, R. kanagurta of 0.24 and 0.10, and R. brachysoma 0.20 and 0.13. The level of recruitment of each varies but overall undergoes two peaks during the recruitment period. Maximum Sustainable Yield (MSY) for the Rastrelliger spp. 1,919.02 tons and FMSY (Effort MSY) for 16,766 trips. Furthermore, the mortality rate of arrest (F) R. faughni amounted to 14.53, R. kanagurta 9.43, and R. brachysoma 1.74. The estimation of stock status has never been detached from the exploitation rate. The rate of exploitation for R. faughni, and that is equal to 0.98, R. kanagurta of 0.98, and R. brachysoma 0.85. Judging from the rate of exploitation can be expected the three fish of the Rastrelliger spp. In the Sunda Strait has been over exploited because it has exceeded the limits of optimum exploitation rate.

Rose vs. Rho: a comparison of two approaches to address retrospective patterns in stock assessments

2020 ◽  
Author(s):  
Christopher M Legault
Keyword(s):  
Time Series ◽  
Single Model ◽  
Stock Status ◽  
Wide Range ◽  
Stock Assessments ◽  
Abundance Trends ◽  
Pros And Cons ◽  
The Difference ◽  
Parameter Values ◽  
The Rose

Abstract Two approaches to address retrospective patterns in stock assessments are compared. The Rose approach is an ensemble of models that all remove the retrospective pattern through changes in data, parameter values, or model assumptions. It is time intensive and can result in a wide range of historical abundance trends. The Rho approach modifies the terminal year estimates of a single model that exhibits a retrospective pattern. It is fast and easy to apply but results in a discontinuous time series. Neither approach identifies the source of the retrospective pattern. The pros and cons of these two approaches are compared in terms of catch advice and stock status using four examples with varying strength and direction of retrospective patterns. The choice of which approach to use could be based on time and expertise available to conduct and maintain an assessment, with Rose preferred if a lot of both are available while Rho preferred otherwise. If the Rho approach is used, managers should consider adjusting their control rule or risk buffer to account for the difference between Rose and Rho results shown here.

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