Estimation of growth within Stock Synthesis models: Management implications when using length-composition data

Zhu, Jiangfeng; Maunder, Mark N.; Aires-da-Silva, Alexandre; Chen, Yong

doi:10.1016/j.fishres.2015.09.019

Cited by 18 publications

(13 citation statements)

References 9 publications

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“…; Zhu et al. ). Consequently, the growth estimates emerging from the analyses are conditioned on the accuracy of the other variables estimated at the same time (Maunder and Punt ; Aires‐da‐Silva et al.…”

Section: Discussionmentioning

confidence: 98%

“…; Zhu et al. ). In principle, the assessment models can simultaneously estimate time‐varying size and age selectivities, growth, recruitment, fishing mortality ( F ), and M that account for the size–age structure of the population and remove their effects from growth.…”

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confidence: 98%

“…; Zhu et al. ). These efforts are also distinguished by extensive time series of ancillary data needed to estimate F and M that are not often available to research programs with more limited resources.…”

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confidence: 98%

“…; Zhu et al. ; Maunder and Piner ). The requirement to disentangle the influences of factors other than growth has invigorated research into methods to quantify and remove errors in growth (e.g., Schueller et al.…”

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confidence: 99%

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Modeling Growth: Consequences from Selecting Samples by Size

Goodyear¹

2019

Trans Am Fish Soc

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Simulated size-age observations were collected from hypothetical populations with known growth to quantify potential bias in estimates of growth and mortality that can result from size-selective sampling. The population lengths at ages were normally distributed around means predicted by published von Bertalanffy (VB) equations for the Striped Marlin Kajikia audax or Vermilion Snapper Rhomboplites aurorubens. Parameter estimates for the VB equation were accurate when the data were collected with random and age-stratified sampling. Size-stratified sampling caused important bias in estimates of length at age and fitted VB parameters. The bias increased with the coefficient of variation of mean size at age and total mortality. It became more severe when sampling effort was increased to compensate for low sample numbers in bins within the upper tail of the distribution of sizes in the populations. Error occasionally exceeded 100% for asymptotic length L ∞ and 50% for the Brody growth coefficient K. When a random sample was supplemented with ≤10% large fish, the bias was sometimes greater than that observed when a completely size-stratified design was used. Such error could corrupt the reliability of analyses that depend on VB parameters. For Striped Marlins, natural mortality computed with the Pauly (1980) equation using results from length-selective sampling strategies often deviated 50% or more from the values predicted using the "true" growth coefficients. Potential for nonrepresentative sampling of lengths at age should be routinely described when VB models are first published and should be considered whenever the growth estimates are later used for other purposes. * METHODSThis study used simulated size-age growth data from hypothetical populations in which mean sizes at age conformed to known growth. The VB model has been the model of choice in fisheries and was adopted here as true for the population simulations and for data analyses. The main features included the population model of the numbers at age and size, simulated sampling of growth data, estimation of parameters of the VB equation from simulated data, and finally an assessment of the reliability of growth estimates and ofM estimated using Pauly's (1980) method. (Herein, M denotes the true values assumed for the population model, andM identifies the values estimated from fitted VB parameters using Pauly's equation.) Population ModelSize-age samples were drawn from an age-length matrix of population relative abundances (N a,l ). The population model was adapted from Goodyear (1989Goodyear ( , 1995. First, a vector of population numbers N a at age (a) was created for an assumed constant level of total mortality (Z) as N a = 1e ÀaZ . CONSEQUENCES OF SELECTING SAMPLES BY SIZE 529

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Modeling Growth: Consequences from Selecting Samples by Size

Goodyear¹

2019

Trans Am Fish Soc

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“…This framework is particularly relevant when dealing with harvested fish populations for which length-at-age data collected from fishing operations usually contain missing observations and indicate bias toward fast-growing individuals of each age class. A correct specification of the VBGF is critical because growth is an important aspect of contemporary stock assessment models (Zhu et al, 2016) upon which biomass estimates and conservation measures are based.…”

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Flexible Bayesian analysis of the von Bertalanffy growth function with the use of a log-skew-t distribution

Quintero¹,

Contreras-Reyes²,

Wiff³

et al. 2016

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Abstract-The von Bertalanffygrowth function is the model most widely applied to describe growth in fish populations. Parameters describing this function usually are estimated from observed lengths at different ages by using maximum likelihood and by assuming Gaussian distributed errors. In harvested populations, observed length at age usually involves a high level of skewness and extreme values because of the size-selective sampling process. Some approaches, based on the maximum-likelihood method for making inferences, have been developed to resolve such issues. We propose a Bayesian framework for estimating growth parameters for nonlinear regression models-a framework that is based on the family of log-skew-t distributions and which provides an approach that is flexible enough for modeling the presence of asymmetries and heavy tails. This framework based on a method in which 1) the error accounts for both skewness and heavy-tailed distributions of a log-skew-t model, and 2) the observed length at each age has a heteroscedastic error distribution. The proposed method was applied and compared with the methods of previous models by using observed length-at-age data for the southern blue whiting (Micromesistius australis), an important fish species harvested in the southeast Pacific. Comparisons indicated that the proposed model is the best for describing data on southern blue whiting.

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Cross‐Shelf Variability of Deacon Rockfish Sebastes diaconus Age, Growth, and Maturity in Oregon Waters and Their Effect on Stock Status

et al. 2021

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Understanding the basic biology of exploited fish populations, and how it changes across the waterscape, is essential to sustainable management. Biological features (age, growth, reproductive investment, and fish condition) for the newly described Deacon Rockfish Sebastes diaconus were evaluated between two different population segments, an exploited nearshore population and an unexploited offshore population, and were used to parameterize population dynamics models to evaluate how area-specific biological features influence measures of stock status. Monthly hookand-line sampling was conducted for 1 year, with~50 fish collected per area per sampling period. Despite the relatively small (<50 km) distance between the two sampling areas, there were discernible differences in the biology of Deacon Rockfish. When fish of the same size-class were compared between offshore and nearshore segments, the unexploited offshore fish were older, suggesting that fishing may have decreased the overall age structure of the exploited nearshore population segment. Parameters of the von Bertalanffy growth model differed the most between the sexes and secondarily between the nearshore and offshore population segments. Length at 50% maturity was 28 cm and age at 50% maturity was 4.1 years for females, which is smaller and younger than previously reported in the literature. Deacon Rockfish were captured in both the nearshore and offshore areas throughout the year, which suggests that at least some component(s) of the population is present in both areas throughout the year. These differences had a nontrivial influence on measures of stock status and will be important to consider during future stock assessments and as management considers the effect of the recent reopening of the offshore population segment to fishing.

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Estimation of growth within Stock Synthesis models: Management implications when using length-composition data

Cited by 18 publications

References 9 publications

Modeling Growth: Consequences from Selecting Samples by Size

Modeling Growth: Consequences from Selecting Samples by Size

Flexible Bayesian analysis of the von Bertalanffy growth function with the use of a log-skew-t distribution

Cross‐Shelf Variability of Deacon Rockfish Sebastes diaconus Age, Growth, and Maturity in Oregon Waters and Their Effect on Stock Status

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