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.

Towards a new recruitment paradigm for fish stocks

1997 ◽  
Vol 54 (4) ◽  
pp. 969-977 ◽  
Author(s):  
D J Gilbert
Keyword(s):  
Time Series ◽  
Null Hypothesis ◽  
Meta Analysis ◽  
Fish Stock ◽  
Test Statistic ◽  
Mean Values ◽  
Fish Stocks ◽  
Independent Events ◽  
Alternative Hypotheses ◽  
Stock Recruitment

The stock recruitment paradigm involves the hypothesis that recruitment (R) to a fish stock is positively related to the spawning stock biomass (SSB) of the stock, at low SSB. I propose a ``recruitment states'' hypothesis wherein R is independent of SSB but has different mean values during successive periods. Meta-analysis was used to test the null hypothesis that recruitment is a series of random, independent events, against these two alternative hypotheses, for 153 marine spawning bony fish stocks and 31 salmonid stocks. A test statistic for the stock recruitment paradigm, based on estimating derivatives from the first differences of the time series, was not significant for the marine stocks. The null hypothesis was rejected for the salmonid stocks. Recruitment states models significantly fitted time series for the marine stocks. Ricker models also significantly fitted these data, conflicting with the derivatives test result. However, because SSB is dependent on R, lagged by the age at maturity, a period in a low recruitment state would tend to lead to a period of low SSB. Therefore, the significance of the fit to the Ricker model may have been spurious. The recruitment states model best explained the meta-dataset for the marine stocks.

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.

Estimating steepness of the stock-recruitment relationship in Chilean fish stocks using meta-analysis

2018 ◽  
Vol 200 ◽  
pp. 61-67 ◽  
Author(s):  
Rodrigo Wiff ◽  
Andrés Flores ◽  
Sergio Neira ◽  
Bruno Caneco
Keyword(s):  
Meta Analysis ◽  
Fish Stocks ◽  
Stock Recruitment

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.

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 Age-structure-dependent recruitment: a meta-analysis applied to Northeast Atlantic fish stocks

2010 ◽  
Vol 67 (9) ◽  
pp. 1921-1930 ◽  
Author(s):  
Thomas Brunel
Keyword(s):  
Opposite Direction ◽  
Age Structure ◽  
Environmental Variability ◽  
Meta Analysis ◽  
Stock Level ◽  
Fish Stocks ◽  
Biological Basis ◽  
Northeast Atlantic ◽  
Age Diversity ◽  
Meta Analyses

Abstract Brunel, T. 2010. Age-structure-dependent recruitment: a meta-analysis applied to Northeast Atlantic fish stocks. – ICES Journal of Marine Science, 67: 1921–1930. Exploitation alters the age structure of fish stocks. Several stock-specific studies have suggested that changes in the age structure might have consequences for subsequent recruitment, but the evidence is not universal. To investigate how common such effects are among 39 Northeast Atlantic fish stocks, relationships were tested between age structure (spawner mean age, age diversity, and proportion of recruit spawners) and recruitment (number of recruits, sensitivity to environment, and recruitment variability). Significant correlations in the expected direction were observed for a few stocks, but not for the majority; significant correlations in the opposite direction were also found. Meta-analyses combining the stock-level tests revealed that none of the effects were significant overall. However, effects were significant for some species (cod, haddock, and plaice) and indices. The low variability in the age structure might explain the absence of significant effects for individual stocks. Other reasons could be the absence of a biological basis (reproductive characteristics not dependent on age) or the stronger influence of environmental variability than of age structure on recruitment.

scholarly journals Methods used to meta-analyse results from interrupted time series studies: A methodological systematic review protocol

F1000Research ◽  
2020 ◽  
Vol 9 ◽  
pp. 110
Author(s):  
Elizabeth Korevaar ◽  
Amalia Karahalios ◽  
Andrew B. Forbes ◽  
Simon L. Turner ◽  
Steve McDonald ◽  
...  
Keyword(s):  
Public Health ◽  
Time Series ◽  
Systematic Reviews ◽  
Data Extraction ◽  
Meta Analysis ◽  
Interrupted Time Series ◽  
Analysis Methods ◽  
Study Selection ◽  
The Individual ◽  
Meta Analyses

Background: Systematic reviews are used to inform healthcare decision making. In reviews that aim to examine the effects of organisational, policy change or public health interventions, or exposures, evidence from interrupted time series (ITS) studies may be included. A core component of many systematic reviews is meta-analysis, which is the statistical synthesis of results across studies. There is currently a lack of guidance informing the choice of meta-analysis methods for combining results from ITS studies, and there have been no studies examining the meta-analysis methods used in practice. This study therefore aims to describe current meta-analysis methods used in a cohort of reviews of ITS studies. Methods: We will identify the 100 most recent reviews (published between 1 January 2000 and 11 October 2019) that include meta-analyses of ITS studies from a search of eight electronic databases covering several disciplines (public health, psychology, education, economics). Study selection will be undertaken independently by two authors. Data extraction will be undertaken by one author, and for a random sample of the reviews, two authors. From eligible reviews we will extract details at the review level including discipline, type of interruption and any tools used to assess the risk of bias / methodological quality of included ITS studies; at the meta-analytic level we will extract type of outcome, effect measure(s), meta-analytic methods, and any methods used to re-analyse the individual ITS studies. Descriptive statistics will be used to summarise the data. Conclusions: This review will describe the methods used to meta-analyse results from ITS studies. Results from this review will inform future methods research examining how different meta-analysis methods perform, and ultimately, the development of guidance.

Analytical reference points for age-structured models: application to data-poor fisheries

2009 ◽  
Vol 67 (1) ◽  
pp. 165-175 ◽  
Author(s):  
Elizabeth N. Brooks ◽  
Joseph E. Powers ◽  
Enric Cortés
Keyword(s):  
Stock Assessment ◽  
Meta Analysis ◽  
Reproductive Rate ◽  
Biological Data ◽  
Reference Points ◽  
Assessment Model ◽  
Shark Species ◽  
Stock Status ◽  
Age Structured ◽  
Analytical Reference

AbstractBrooks, E. N., Powers, J. E., and Cortés, E. 2010. Analytical reference points for age-structured models: application to data-poor fisheries. – ICES Journal of Marine Science, 67: 165–175. Analytical solutions for biological reference points are derived in terms of maximum lifetime reproductive rate. This rate can be calculated directly from biological parameters of maturity, fecundity, and natural mortality or a distribution for this rate can be derived from appropriate metadata. Minimal data needs and assumptions for determining stock status are discussed. The derivations lead to a re-parameterization of the common stock–recruit relationships, Beverton–Holt and Ricker, in terms of spawning potential ratio. Often, parameters in stock–recruit relationships are restricted by tight prior distributions or are fixed based on a hypothesized level of stock resilience. Fixing those parameters is equivalent to specifying the biological reference points. An ability to directly calculate reference points from biological data, or a meta-analysis, without need of a full assessment model or fisheries data, makes the method an attractive option for data-poor fisheries. The derivations reveal an explicit link between the biological characteristics of a species and appropriate management. Predicted stock status for a suite of shark species was compared with recent stock assessment results, and the method successfully identified whether each stock was overfished.

scholarly journals Linking the performance of a data-limited empirical catch rule to life-history traits

2020 ◽  
Vol 77 (5) ◽  
pp. 1914-1926
Author(s):  
Simon H Fischer ◽  
José A A De Oliveira ◽  
Laurence T Kell
Keyword(s):  
Time Series ◽  
Life History ◽  
Life Histories ◽  
Life History Traits ◽  
Growth Parameter ◽  
Reference Points ◽  
Total Allowable Catch ◽  
Fish Stocks ◽  
Wide Range ◽  
Spawning Stock

Abstract Worldwide, the majorities of fish stocks are data-limited and lack fully quantitative stock assessments. Within ICES, such data-limited stocks are currently managed by setting total allowable catch without the use of target reference points. To ensure that such advice is precautionary, we used management strategy evaluation to evaluate an empirical rule that bases catch advice on recent catches, information from a biomass survey index, catch length frequencies, and MSY reference point proxies. Twenty-nine fish stocks were simulated covering a wide range of life histories. The performance of the rule varied substantially between stocks, and the risk of breaching limit reference points was inversely correlated to the von Bertalanffy growth parameter k. Stocks with k>0.32 year−1 had a high probability of stock collapse. A time series cluster analysis revealed four types of dynamics, i.e. groups with similar terminal spawning stock biomass (collapsed, BMSY, 2BMSY, 3BMSY). It was shown that a single generic catch rule cannot be applied across all life histories, and management should instead be linked to life-history traits, and in particular, the nature of the time series of stock metrics. The lessons learnt can help future work to shape scientific research into data-limited fisheries management and to ensure that fisheries are MSY compliant and precautionary.

Practical application of meta-analysis results: avoiding the double use of data

2005 ◽  
Vol 62 (4) ◽  
pp. 925-929 ◽  
Author(s):  
C V Minte-Vera ◽  
T A Branch ◽  
I J Stewart ◽  
M W Dorn
Keyword(s):  
Input Data ◽  
Stock Assessment ◽  
Meta Analysis ◽  
Data Set ◽  
Use Of Data ◽  
Type C ◽  
The Individual ◽  
Meta Analyses ◽  
The Impact ◽  
Additional Form

Meta-analysis is an important new tool for synthesizing scientific knowledge from many previous studies. In fisheries, meta-analyses can be used to obtain prior distributions or penalty functions for parameters used in stock assessment models. Two types of results are generally published in a meta-analysis: Type A, the updated results for each stock used in the meta-analysis, and Type B, the results that would best describe a new stock. Including these results in assessments for the individual stocks would result in double use of the data if the assessments include the input data used in the meta-analyses, which they typically would. To solve this problem, we recommend that an additional form of results should be reported in meta-analyses: Type C, the results for a new stock obtained by sequentially excluding each stock's data set and repeating the meta-analysis. Type C results should be used whenever the assessment input data overlap with the meta-analysis input data, avoiding the double use of data. We illustrate the impact of this reporting change on the results of a recent meta-analysis.

Sign in / Sign up

Export Citation Format

Share Document