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 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.

The null-hypothesis significance-test procedure is still warranted

1998 ◽  
Vol 21 (2) ◽  
pp. 228-235 ◽  
Author(s):  
Siu L. Chow
Keyword(s):  
Null Hypothesis ◽  
Statistical Power ◽  
Meta Analysis ◽  
Statistical Significance ◽  
Test Procedure ◽  
Significance Test ◽  
Null Hypothesis Significance Test ◽  
Wide Range ◽  
Statistical Hypotheses ◽  
Alternative Hypotheses

Entertaining diverse assumptions about empirical research, commentators give a wide range of verdicts on the NHSTP defence in Statistical significance. The null-hypothesis significance-test procedure (NHSTP) is defended in a framework in which deductive and inductive rules are deployed in theory corroboration in the spirit of Popper's Conjectures and refutations (1968b). The defensible hypothetico-deductive structure of the framework is used to make explicit the distinctions between (1) substantive and statistical hypotheses, (2) statistical alternative and conceptual alternative hypotheses, and (3) making statistical decisions and drawing theoretical conclusions. These distinctions make it easier to show that (1) H0 can be true, (2) the effect size is irrelevant to theory corroboration, and (3) “strong” hypotheses make no difference to NHSTP. Reservations about statistical power, meta-analysis, and the Bayesian approach are still warranted.

scholarly journals Population variability under stressors is dependent on body mass growth and asymptotic body size

2020 ◽  
Vol 7 (2) ◽  
pp. 192011
Author(s):  
Leonie Färber ◽  
Rob van Gemert ◽  
Øystein Langangen ◽  
Joël M. Durant ◽  
Ken H. Andersen
Keyword(s):  
Body Mass ◽  
Life Histories ◽  
Random Noise ◽  
Fish Stock ◽  
Vital Rates ◽  
Anthropogenic Pressures ◽  
Fish Stocks ◽  
Asymptotic Size ◽  
Wide Range ◽  
Stock Recruitment

The recruitment and biomass of a fish stock are influenced by their environmental conditions and anthropogenic pressures such as fishing. The variability in the environment often translates into fluctuations in recruitment, which then propagate throughout the stock biomass. In order to manage fish stocks sustainably, it is necessary to understand their dynamics. Here, we systematically explore the dynamics and sensitivity of fish stock recruitment and biomass to environmental noise. Using an age-structured and trait-based model, we explore random noise (white noise) and autocorrelated noise (red noise) in combination with low to high levels of harvesting. We determine the vital rates of stocks covering a wide range of possible body mass (size) growth rates and asymptotic size parameter combinations. Our study indicates that the variability of stock recruitment and biomass are probably correlated with the stock's asymptotic size and growth rate. We find that fast-growing and large-sized fish stocks are likely to be less vulnerable to disturbances than slow-growing and small-sized fish stocks. We show how the natural variability in fish stocks is amplified by fishing, not just for one stock but for a broad range of fish life histories.

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 Assessing causal links in fish stock–recruitment relationships

2017 ◽  
Vol 75 (3) ◽  
pp. 903-911 ◽  
Author(s):  
Maud Pierre ◽  
Tristan Rouyer ◽  
Sylvain Bonhommeau ◽  
J M Fromentin
Keyword(s):  
Time Series ◽  
Dynamical Systems ◽  
Surface Temperature ◽  
Sea Surface ◽  
Fish Stock ◽  
Stochastic Forcing ◽  
Forecasting Methods ◽  
Stock Biomass ◽  
Spawning Stock ◽  
Stock Recruitment

Abstract Understanding whether recruitment fluctuations in fish stock arise from stochastic forcing (e.g. environmental variations) rather than deterministic forces (e.g. intrinsic dynamics) is a long standing question with important applied consequences for fisheries ecology. In particular, the relationship between recruitment, spawning stock biomass and environmental factors is still poorly understood, even though this aspect is crucial for fisheries management. Fisheries data are often short, but arise from complex dynamical systems with a high degree of stochastic forcing, which are difficult to capture through classic modelling approaches. In the present study, recent statistical approaches based on the approximation of the attractors of dynamical systems are applied on a large dataset of time series to assess (i) the directionality of potential causal relationships between recruitment and spawning stock biomass and potential influence of sea-surface temperature on recruitment and (ii) their performance to forecast recruitment. Our study shows that (i) whereas spawning stock biomass and sea surface temperature influence the recruitment to a lesser extent, recruitment causes also parental stock size and (ii) that non-linear forecasting methods performed well for the short-term predictions of recruitment time series. Our results underline that the complex and stochastic nature of the processes characterizing recruitment are unlikely to be captured by classical stock–recruitment relationships, but that non-linear forecasting methods provide interesting perspectives in that respect.

scholarly journals Changing recruitment capacity in global fish stocks

2015 ◽  
Vol 113 (1) ◽  
pp. 134-139 ◽  
Author(s):  
Gregory L. Britten ◽  
Michael Dowd ◽  
Boris Worm
Keyword(s):  
Environmental Changes ◽  
Meta Analysis ◽  
Chlorophyll Concentration ◽  
Fish Stock ◽  
Productive Capacity ◽  
Large Variability ◽  
Fish Stocks ◽  
Large Marine Ecosystems ◽  
The North ◽  
Spawning Stock

Marine fish and invertebrates are shifting their regional and global distributions in response to climate change, but it is unclear whether their productivity is being affected as well. Here we tested for time-varying trends in biological productivity parameters across 262 fish stocks of 127 species in 39 large marine ecosystems and high-seas areas (hereafter LMEs). This global meta-analysis revealed widespread changes in the relationship between spawning stock size and the production of juvenile offspring (recruitment), suggesting fundamental biological change in fish stock productivity at early life stages. Across regions, we estimate that average recruitment capacity has declined at a rate approximately equal to 3% of the historical maximum per decade. However, we observed large variability among stocks and regions; for example, highly negative trends in the North Atlantic contrast with more neutral patterns in the North Pacific. The extent of biological change in each LME was significantly related to observed changes in phytoplankton chlorophyll concentration and the intensity of historical overfishing in that ecosystem. We conclude that both environmental changes and chronic overfishing have already affected the productive capacity of many stocks at the recruitment stage of the life cycle. These results provide a baseline for ecosystem-based fisheries management and may help adjust expectations for future food production from the oceans.

A CONSISTENT NONPARAMETRIC TEST ON SEMIPARAMETRIC SMOOTH COEFFICIENT MODELS WITH INTEGRATED TIME SERIES

2015 ◽  
Vol 32 (4) ◽  
pp. 988-1022 ◽  
Author(s):  
Yiguo Sun ◽  
Zongwu Cai ◽  
Qi Li
Keyword(s):  
Time Series ◽  
Nonparametric Test ◽  
Asymptotic Distributions ◽  
Varying Coefficient Model ◽  
Finite Sample ◽  
Test Statistic ◽  
Smooth Coefficients ◽  
Alternative Hypotheses ◽  
Constant Coefficients ◽  
Integrated Time Series

In this paper, we propose a simple nonparametric test for testing the null hypothesis of constant coefficients against nonparametric smooth coefficients in a semiparametric varying coefficient model with integrated time series. We establish the asymptotic distributions of the proposed test statistic under both null and alternative hypotheses. Moreover, we derive a central limit theorem for a degenerate second order U-statistic, which contains a mixture of stationary and nonstationary variables and is weighted locally on a stationary variable. This result is of independent interest and useful in other applications. Monte Carlo simulations are conducted to examine the finite sample performance of the proposed test.

scholarly journals A Density-Based Empirical Likelihood Ratio Approach for Goodness-of-fit Tests in Decreasing Densities

2020 ◽  
Vol 8 (1) ◽  
pp. 66-79
Author(s):  
Vahid Fakoor ◽  
Masoud Ajami ◽  
Seyed Mahdi Amir Jahanshahi ◽  
Ali Shariati
Keyword(s):  
Empirical Likelihood ◽  
Null Hypothesis ◽  
Goodness Of Fit ◽  
Real Data ◽  
Distribution Functions ◽  
Test Statistic ◽  
Goodness Of Fit Tests ◽  
Alternative Hypotheses ◽  
Ratio Approach ◽  
Consistency Of The Test

In this paper, we propose a test for the null hypothesis that a decreasing density function belongs to a givenparametric family of distribution functions against the non-parametric alternative. This method, which is based on an empirical likelihood (EL) ratio statistic, is similar to the test introduced by Vexler and Gurevich [23]. The consistency of the test statistic proposed is derived under the null and alternative hypotheses. A simulation study is conducted to inspect the power of the proposed test under various decreasing alternatives. In each scenario, the critical region of the test is obtained using a Monte Carlo technique. The applicability of the proposed test in practice is demonstrated through a few real data examples.  

scholarly journals A meta-analysis of the status of ICES fish stocks during the past half century

2007 ◽  
Vol 64 (4) ◽  
pp. 707-713 ◽  
Author(s):  
Henrik Sparholt ◽  
Mette Bertelsen ◽  
Hans Lassen
Keyword(s):  
Time Series ◽  
Meta Analysis ◽  
Fishing Mortality ◽  
Fish Stocks ◽  
Half Century ◽  
The Past ◽  
Past Half Century ◽  
The Status ◽  
1960S And 1970S ◽  
Past Half

Abstract Sparholt, H., Bertelsen, M., and Lassen, H. 2007. A meta-analysis of the status of ICES fish stocks during the past half century. – ICES Journal of Marine Science, 64: 707–713. Based on a meta-analysis of time-series of stock size, recruitment, and fishing mortality, the general status of fish stocks within the ICES Area (i.e. the Northeast Atlantic) is evaluated. The analysis is based on data for 34 (7 pelagic, 27 demersal) commercial stocks. The stocks were selected based on the quality of the data and the length of the time-series. The analysis indicates that most pelagic stocks recovered to sustainable levels with high productivity after several had collapsed in the 1960s and 1970s. In contrast, most demersal stocks have continued to decline over the past half century and are now recruitment-overfished. By reducing fishing mortality on demersal stocks on average by half and building up the stocks by a factor of about two, management could be brought in line with international agreements. If recruitment-overfishing is avoided for all demersal stocks and discarding is minimized, their yield might be almost doubled over the current yield. Among the major management initiatives during the past half century, only the closure of the pelagic fisheries in the mid-1970s can be clearly identified in the time-series as having had a direct effect on stock status.

scholarly journals A MAX-CORRELATION WHITE NOISE TEST FOR WEAKLY DEPENDENT TIME SERIES

2020 ◽  
Vol 36 (5) ◽  
pp. 907-960
Author(s):  
Jonathan B. Hill ◽  
Kaiji Motegi
Keyword(s):  
Time Series ◽  
White Noise ◽  
Null Hypothesis ◽  
Gaussian Approximation ◽  
Value Theory ◽  
Parametric Models ◽  
Test Statistic ◽  
Sample Correlation ◽  
Noise Test ◽  
Weakly Dependent

This article presents a bootstrapped p-value white noise test based on the maximum correlation, for a time series that may be weakly dependent under the null hypothesis. The time series may be prefiltered residuals. The test statistic is a normalized weighted maximum sample correlation coefficient $ \max _{1\leq h\leq \mathcal {L}_{n}}\sqrt {n}|\hat {\omega }_{n}(h)\hat {\rho }_{n}(h)|$, where $\hat {\omega }_{n}(h)$ are weights and the maximum lag $ \mathcal {L}_{n}$ increases at a rate slower than the sample size n. We only require uncorrelatedness under the null hypothesis, along with a moment contraction dependence property that includes mixing and nonmixing sequences. We show Shao’s (2011, Annals of Statistics 35, 1773–1801) dependent wild bootstrap is valid for a much larger class of processes than originally considered. It is also valid for residuals from a general class of parametric models as long as the bootstrap is applied to a first-order expansion of the sample correlation. We prove the bootstrap is asymptotically valid without exploiting extreme value theory (standard in the literature) or recent Gaussian approximation theory. Finally, we extend Escanciano and Lobato’s (2009, Journal of Econometrics 151, 140–149) automatic maximum lag selection to our setting with an unbounded lag set that ensures a consistent white noise test, and find it works extremely well in controlled experiments.

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