The estimation and robustness of FMSY and alternative fishing mortality reference points associated with high long-term yield

2012 ◽  
Vol 69 (9) ◽  
pp. 1468-1480 ◽  
Author(s):  
Jan Horbowy ◽  
Anna Luzeńczyk
Keyword(s):  
Total Yield ◽  
Reference Points ◽  
Superior Performance ◽  
Equilibrium Yield ◽  
Spawning Stock ◽  
Stock Recruitment ◽  
Yield Per Recruit ◽  
Different Sources ◽  
Recruitment Model

Equations for equilibrium yield and biomass are presented and used to derive FMSY and alternative reference points (ARPs). ARPs are analogues of the traditional points based on yield-per-recruit (YPR) or spawning stock-per-recruit (SPR) (F0.1, F40%, F50%), but refer to the equilibrium total yield or biomass. The method combines YPR and SPR analysis with stock–recruitment relationships. The sensitivity of FMSY and ARPs to the range of available stock–recruitment data, recruitment variance, various steepness levels in the stock–recruitment models, assessment variance, and bias are tested. The analysis showed that in most cases, F40%B and F50%B, defined by the equilibrium biomass (B), were the most robust relative to the different sources of uncertainty. However, in the case of the misspecification of the stock–recruitment relationship, FMSY showed superior performance. F40%B for the Beverton and Holt stock–recruitment model and F50%B for the Ricker recruitment model can be recommended as conservative fishing mortalities associated with high long-term yield. For the considered steepness, they produced yield up to 5%–10% lower than yield at FMSY.

scholarly journals An explicit solution for calculating optimum spawning stock size from Ricker’s stock recruitment model

PeerJ ◽  
2016 ◽  
Vol 4 ◽  
pp. e1623 ◽  
Author(s):  
Mark D. Scheuerell
Keyword(s):  
Explicit Solution ◽  
Model Fitting ◽  
Maximum Sustainable Yield ◽  
Reference Points ◽  
Stock Size ◽  
Points Of Interest ◽  
Spawning Stock ◽  
Stock Recruitment ◽  
Explicit Formulae ◽  
Recruitment Model

Stock-recruitment models have been used for decades in fisheries management as a means of formalizing the expected number of offspring that recruit to a fishery based on the number of parents. In particular, Ricker’s stock recruitment model is widely used due to its flexibility and ease with which the parameters can be estimated. After model fitting, the spawning stock size that produces the maximum sustainable yield (SMSY) to a fishery, and the harvest corresponding to it (UMSY), are two of the most common biological reference points of interest to fisheries managers. However, to date there has been no explicit solution for either reference point because of the transcendental nature of the equation needed to solve for them. Therefore, numerical or statistical approximations have been used for more than 30 years. Here I provide explicit formulae for calculating bothSMSYandUMSYin terms of the productivity and density-dependent parameters of Ricker’s model.

scholarly journals An explicit solution for calculating optimum spawning stock size from Ricker's stock recruitment curve

2015 ◽  
Author(s):  
Mark D. Scheuerell
Keyword(s):  
Explicit Solution ◽  
Model Fitting ◽  
Maximum Sustainable Yield ◽  
Reference Points ◽  
Stock Size ◽  
Points Of Interest ◽  
Spawning Stock ◽  
Stock Recruitment ◽  
Explicit Formulae ◽  
Recruitment Model

Ricker’s stock recruitment model is widely used to describe the spawner-offspring relationship for fishes. After model fitting, the spawning stock size that produces the maximum sustainable yield (SMSY), and the harvest corresponding to it (UMSY), are two of the most common biological reference points of interest to fisheries managers. However, to date there has been no explicit solution for either reference point because of the transcendental nature of the equation needed to solve for them. Therefore, numerical or statistical approximations have been used for more than 30 years. Here I provide explicit formulae for calculating both SMSY and UMSY in terms of the productivity and density-dependent parameters from Ricker’s model.

scholarly journals An explicit solution for calculating optimum spawning stock size from Ricker's stock recruitment curve

2015 ◽  
Author(s):  
Mark D. Scheuerell
Keyword(s):  
Explicit Solution ◽  
Model Fitting ◽  
Maximum Sustainable Yield ◽  
Reference Points ◽  
Stock Size ◽  
Points Of Interest ◽  
Spawning Stock ◽  
Stock Recruitment ◽  
Explicit Formulae ◽  
Recruitment Model

Ricker’s stock recruitment model is widely used to describe the spawner-offspring relationship for fishes. After model fitting, the spawning stock size that produces the maximum sustainable yield (SMSY), and the harvest corresponding to it (UMSY), are two of the most common biological reference points of interest to fisheries managers. However, to date there has been no explicit solution for either reference point because of the transcendental nature of the equation needed to solve for them. Therefore, numerical or statistical approximations have been used for more than 30 years. Here I provide explicit formulae for calculating both SMSY and UMSY in terms of the productivity and density-dependent parameters from Ricker’s model.

scholarly journals Quirky patterns in time-series of estimates of recruitment could be artefacts

2014 ◽  
Vol 72 (1) ◽  
pp. 111-116 ◽  
Author(s):  
M. Dickey-Collas ◽  
N. T. Hintzen ◽  
R. D. M. Nash ◽  
P-J. Schön ◽  
M. R. Payne
Keyword(s):  
Time Series ◽  
Stock Assessment ◽  
Meta Analysis ◽  
Reference Points ◽  
Fish Stocks ◽  
Stock Recruitment ◽  
Modelling Assumptions ◽  
Meta Analyses ◽  
Recruitment Model ◽  
Recruitment Time

Abstract The accessibility of databases of global or regional stock assessment outputs is leading to an increase in meta-analysis of the dynamics of fish stocks. In most of these analyses, each of the time-series is generally assumed to be directly comparable. However, the approach to stock assessment employed, and the associated modelling assumptions, can have an important influence on the characteristics of each time-series. We explore this idea by investigating recruitment time-series with three different recruitment parameterizations: a stock–recruitment model, a random-walk time-series model, and non-parametric “free” estimation of recruitment. We show that the recruitment time-series is sensitive to model assumptions and this can impact reference points in management, the perception of variability in recruitment and thus undermine meta-analyses. The assumption of the direct comparability of recruitment time-series in databases is therefore not consistent across or within species and stocks. Caution is therefore required as perhaps the characteristics of the time-series of stock dynamics may be determined by the model used to generate them, rather than underlying ecological phenomena. This is especially true when information about cohort abundance is noisy or lacking.

An Alternative Perspective on Recruitment Overfishing and Biological Reference Points

1987 ◽  
Vol 44 (4) ◽  
pp. 913-918 ◽  
Author(s):  
M. P. Sissenwine ◽  
J. G. Shepherd
Keyword(s):  
Fisheries Management ◽  
Reference Point ◽  
Reference Points ◽  
Fishing Mortality ◽  
Alternative Perspective ◽  
Conventional Models ◽  
Definition Of ◽  
Yield Per Recruit ◽  
Spawning Biomass

Biological reference points are used to guide fisheries management decisions. The reference points most often used are expressed in terms of fishing mortality rate (F). Fmsy relates to the maximization of sustainable yield. In principle, it is a most useful reference point, but in practice it is difficult to estimate. Fmax and F0.1 relate to certain levels of yield per recruit and are easily estimated, but they ignore conservation of the resource. Recruitment overfishing has usually been understood to occur when a population has been fished down to a point where recruitment is substantially reduced or fails. It has not been used as a basis for a biological reference point because the definition is vague and cannot be readily related to fishing mortality. Levels of spawning biomass below which recruitment seems to be reduced have been used, but their determination from available data is usually difficult and controversial. We propose an alternative definition of recruitment overfishing in terms of the level of fishing pressure that reduces the spawning biomass of a year class over its lifetime below the spawning biomass of its parents on average. Conventional models and types of data can be used to determine this level of F, denoted as Frep, which clearly relates to the replacement of spawning biomass and thus to sustainability of a population and yield in the long term.

Recruitment variation in abalone: Its importance to fisheries management

1995 ◽  
Vol 46 (3) ◽  
pp. 555 ◽  
Author(s):  
PE McShane
Keyword(s):  
Egg Production ◽  
Field Experiments ◽  
Stock Assessment ◽  
Reference Points ◽  
High Fecundity ◽  
Spatial And Temporal Scales ◽  
Recruitment Failure ◽  
Spawning Stock ◽  
Stock Recruitment ◽  
Many Sources

Recruitment failure has been implicated in the decline of several abalone fisheries. Traditionally, fisheries scientists invoke theoretical stock-recruitment relationships to predict trends in abundance of an exploited stock under various harvest regimes. The empirical evidence in support of a positive relationship between spawning stock and recruits is not strong. A further problem in interpretation of such relationships is that both 'stock' and 'recruitment' have various definitions in fisheries and ecological literature. The definition of a stock for abalone is not clear. As emphasized in this review, which considers each stage in the life history of abalone, the abundance of spawners is one of many sources of variation in recruitment. The evidence for invertebrates, particularly those with high fecundity, is that recruitment varies independently of the abundance of spawners. This is also the case for abalone, where recruits have been measured as the density of immediate post-settlement individuals, juveniles, or as adults entering the exploitable stock. A problem with stock-recruitment hypotheses is that they have intuitive appeal. It is considered 'dangerous' to manage fisheries under the assumption that a reduction in the number of spawners by fishing will not affect recruitment. Such danger to abalone stocks has been more recently assessed by egg-per-recruit analyses, whereby various harvest strategies are examined relative to reference points for egg production. These studies are reviewed and assessed relative to the often conflicting aims of managers and scientists. This review of studies of recruitment variation in abalone emphasizes the need for a more rigorous, autecological approach to stock assessment in which field experiments are conducted over realistic spatial and temporal scales, permitting robust testing of hypotheses.

scholarly journals Reference point based management of Norwegian Atlantic salmon populations

2013 ◽  
Vol 40 (4) ◽  
pp. 356-366 ◽  
Author(s):  
TORBJØRN FORSETH ◽  
PEDER FISKE ◽  
BJØRN BARLAUP ◽  
HARALD GJØSÆTER ◽  
KJETIL HINDAR ◽  
...  
Keyword(s):  
Atlantic Salmon ◽  
Reference Point ◽  
Reference Points ◽  
Reproductive Capacity ◽  
Management Scheme ◽  
Average Maximum ◽  
Stock Recruitment ◽  
Catch Statistics ◽  
Management And Conservation

SUMMARYWhile management according to biological reference points is well established for many commercial marine fisheries, similar systems for more leisure based fisheries for freshwater fishes are less common. This paper describes the scientific foundation for management according to conservation limits and management targets for Norwegian populations of Atlantic salmon, a highly valued and heavily exploited anadromous fish species. Based on stock recruitment relationships during the freshwater phase, the biomass of females necessary to attain the carrying capacity (yielding average maximum recruitment) has been established as conservation limits for each of the 439 Norwegian populations. Using a simulation model based on reported catch and estimates of exploitation rates, the probability and percentage attainment of the conservation limits have been assessed annually since 2008, and exploitation advice provided for 176 of the largest populations. The number of populations that attained their conservation limits increased substantially after the new management scheme was introduced, despite that the number of returning salmon remained at historical low levels. Overall the populations evaluated in 2011 were at 95% of their conservation limits compared to 91% in 2008 and 85% in 2005. The improvement could largely be attributed to reduced exploitation rates, due to new restrictions in both the marine and river fisheries. The new management scheme also improved the catch statistics and stimulated data acquisition for management. Implementation of management according to conservation limits has been a success in terms of attaining the main management goal of protecting the Atlantic salmon populations by ensuring that an increasing number of the populations likely are at their maximum reproductive capacity. Long-term increases in fisheries yield, the secondary management goal, are likely to be attained, but remain to be documented. Reference point based management of Atlantic salmon exemplifies management within the intersection of fisheries management and conservation biology, borrowing principles from both sides.

Incorporating climate changes into population dynamic modelling: an individual-based modelling approach for lobster

2011 ◽  
Vol 68 (1) ◽  
pp. 122-136 ◽  
Author(s):  
Yi-Jay Chang ◽  
Chi-Lu Sun ◽  
Yong Chen ◽  
Yuying Zhang ◽  
Su-Zan Yeh
Keyword(s):  
Fisheries Management ◽  
Spiny Lobster ◽  
Dynamic Modelling ◽  
Reference Points ◽  
Eastern Coast ◽  
Biological Processes ◽  
Temperature Dependent ◽  
Yield Per Recruit ◽  
Modelling Approach

One of the most challenging issues in fisheries management is the evaluation of the effects of fishing in the context of a changing environment. Using the pronghorn spiny lobster ( Panulirus penicillatus ) fishery off the eastern coast of Taiwan as an example, we developed an individual-based model (IBM) that is capable of describing the temperature-dependent life history processes and fishery practices for the spiny lobster. We then used the model to evaluate potential impacts of increased ocean temperature on the estimation of mortality-based biological reference points for fisheries management. We demonstrate that a warming temperature would increase the yield-per-recruit and eggs-per-recruit values and consequently reduce the risk of overexploitation under the current exploitation level. However, there is likely a high risk of overexploitation in the long term if higher temperatures induce extra-high natural mortality. The evaluation of effectiveness of size regulations suggests that increasing minimum legal size is proposed as a good candidate measure to reduce the risk of overexploitation for pessimistically unfavorable environmental conditions. This study suggests that an explicit incorporation of the relationships between environmental variables and biological processes can greatly improve fisheries assessment and management.

Improving the stock-recruitment relationship in Icelandic cod (Gadus morhua) by including age diversity of spawners

1998 ◽  
Vol 55 (6) ◽  
pp. 1372-1377 ◽  
Author(s):  
Gudrun Marteinsdottir ◽  
Kristjan Thorarinsson
Keyword(s):  
Gadus Morhua ◽  
Extended Period ◽  
Shannon Index ◽  
Age Composition ◽  
Stock Size ◽  
Age Diversity ◽  
Spawning Stock ◽  
Stock Recruitment ◽  
Mature Fish

The size of the Icelandic cod stock has been gradually declining since the middle of this century. Recruitment has been poor over an extended period of time and much below the long-term average since 1985. Except for the concurrent decrease in stock size and recruitment during this period, the stock size - recruitment relationship is weak. This relationship is improved by including the age composition of the spawning stock. Spawning stock age diversity in each year from 1955 to 1992 was estimated with the Shannon index using the number of mature fish in each age group. By including information on age composition, 31% of the total variation in recruitment was accounted for by the model with stock size, age diversity, and the interaction between the two, compared with less than 15% by single factor models of either age diversity or stock size. These results indicate that age diversity is an important component in stock-recruitment models and that one of the management goals for fish species should be to maintain high age diversity in the spawning stocks.

Escapement goal analysis and stock reconstruction of sockeye salmon populations (Oncorhynchus nerka) using life-history models

2008 ◽  
Vol 65 (10) ◽  
pp. 2269-2278 ◽  
Author(s):  
Robert B. Lessard ◽  
Ray Hilborn ◽  
Brandon E. Chasco
Keyword(s):  
Life History ◽  
Sockeye Salmon ◽  
Model Estimate ◽  
Policy Variable ◽  
Optimal Harvest ◽  
Spawning Stock ◽  
Maximum Sustained Yield ◽  
History Of ◽  
Stock Recruitment

We compare life-history models with the Beverton–Holt approach of escapement goal analysis. We model the life history of a sockeye salmon ( Onchorhynchus nerka ) population from a spawning stage, through juvenile and adult stages, and ending with adults that return to spawn. We fit models to data by statistically comparing predicted and observed numbers of four dominant adult ages. Posterior estimates of parameters from Markov chain Monte Carlo simulations are then used to assess optimal harvest policies. We search for policies that produce the highest average yield. We find that it is possible to detect density dependence with a life-history model where analysis of Beverton–Holt stock–recruitment relationship fails to do so. We find that Beverton–Holt relationships produce policies and long-term yield estimates that are inconsistent with empirical trends. Conversely, we find that optimal spawning stock sizes and maximum sustained yield estimates using the life-history model estimate are consistent with the historical behavior of fisheries examined. Adding smolt data to the analysis does not substantially change predicted optimal spawning stock size, but decreases the variance in estimated posterior parameter distributions and policy variable distributions.

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