Bayesian modeling of individual growth variability using back-calculation: Application to pink cusk-eel (Genypterus blacodes) off Chile

2018 ◽  
Vol 385 ◽  
pp. 145-153 ◽  
Author(s):  
Javier E. Contreras-Reyes ◽  
Freddy O. López Quintero ◽  
Rodrigo Wiff
Keyword(s):  
Bayesian Modeling ◽  
Individual Growth ◽  
Growth Variability ◽  
Back Calculation

scholarly journals Correlated Response on Growth Traits and Their Variabilities to Selection for Ovulation Rate in Rabbits Using Genetic Trends and a Cryopreserved Control Population

Animals ◽  
2021 ◽  
Vol 11 (9) ◽  
pp. 2591
Author(s):  
Rosa Peiró ◽  
Celia Quirino ◽  
Agustín Blasco ◽  
María Antonia Santacreu
Keyword(s):  
Growth Traits ◽  
Ovulation Rate ◽  
Control Population ◽  
Individual Growth ◽  
Correlated Response ◽  
Phenotypic Variance ◽  
Correlated Responses ◽  
Growth Variability ◽  
Selection For ◽  
Genetic Trends

The aim of this work was to estimate correlated responses in growth traits and their variabilities in an experiment of selection for ovulation rate during 10 generations in rabbits. Individual weight at 28 days old (IW28, kg) and at 63 days old (IW63, kg) was analyzed, as well as individual growth rate (IGR = IW63 − IW28, kg). The variability of each growth trait was calculated as the absolute value of the difference between the individual value and the mean value of their litter. Data were analyzed using Bayesian methodology. The estimated heritabilities of IW28, IW63 and IGR were low, whereas negligible heritabilities were obtained for growth variability traits. The common litter effect was high for all growth traits, around 30% of the phenotypic variance, whereas low maternal effect for all growth traits was obtained. Low genetic correlations between ovulation rate and growth traits were found, and also between ovulation rate and the variability of growth traits. Therefore, genetic trends methods did not show correlated responses in growth traits. A similar result was also obtained using a cryopreserved control population.

Comparison of Otolith-Based Back-Calculation Methods to Determine Individual Growth Histories of Larval Striped Bass, Morone saxatilis

1992 ◽  
Vol 49 (7) ◽  
pp. 1439-1454 ◽  
Author(s):  
David H. Secor ◽  
John Mark Dean
Keyword(s):  
Striped Bass ◽  
Somatic Growth ◽  
Morone Saxatilis ◽  
Growth Effect ◽  
Individual Growth ◽  
Quadratic Model ◽  
Calculation Methods ◽  
Otolith Growth ◽  
Experimental Proof ◽  
Back Calculation

In rearing studies on 6- to 22-d-old larval striped bass, Morone saxatilis, we applied several back-calculation methods to known-growth larvae. A growth effect occurred on otolith diameter – standard length relationships, where slower growing larvae had relatively larger otoliths. Otolith growth was less affected by feeding regime than was somatic growth. Due to the conservative nature of otolith growth, proportional based (Biological Intercept Method) and simple linear regression methods linearized somatic growth transitions and did not estimate periods of negative growth. A quadratic regression method which used age as an additional predictor resulted in the accurate back-calculation of size at age in all groups of laboratory-reared larvae. However, when model coefficients were applied to a test population of pond-reared larvae, the quadratic model performed poorly. While differences in relative otolith size between pond- and laboratory-reared larvae could be ascribed to a temperature effect, the inability to apply the model also indicates a problem specific to regression-based methods. Theoretical rationale and experimental proof provided evidence for the inclusion of age in back-calculation models, but parameterization will have to occur for each field application.

An improved method for estimating individual growth variability in fish, and the correlation between von Bertalanffy growth parameters

2002 ◽  
Vol 59 (3) ◽  
pp. 424-432 ◽  
Author(s):  
Graham M Pilling ◽  
Geoffrey P Kirkwood ◽  
Stephen G Walker
Keyword(s):  
Random Effects ◽  
Standard Method ◽  
Growth Parameters ◽  
Growth Parameter ◽  
Individual Growth ◽  
Reliable Estimate ◽  
Random Effects Model ◽  
Von Bertalanffy ◽  
Data Set ◽  
Growth Variability

A new method for estimating individual variability in the von Bertalanffy growth parameters of fish species is presented. The method uses a nonlinear random effects model, which explicitly assumes that an individual's growth parameters represent samples from a multivariate population of growth parameters characteristic of a species or population. The method was applied to backcalculated length-at-age data from the tropical emperor, Lethrinus mahsena. Individual growth parameter variability estimates were compared with those derived using the current "standard" method, which characterizes the joint distribution of growth parameter estimates obtained by independently fitting a growth curve to each individual data set. Estimates of mean von Bertalanffy growth parameters from the two methods were similar. However, estimated growth parameter variances were much higher using the standard method. Using the random effects model, the estimated correlation between population mean values of L[Formula: see text] and K was –0.52 or –0.42, depending on the marginal distribution assumed for K. The latter estimate had a 95% posterior credibility interval of –0.62 to –0.17. These represent the first reliable estimate of this correlation and confirm the view that these parameters are negatively correlated in fish populations; however, the absolute correlation value is somewhat lower than has been assumed.

The physiological basis for inter-individual growth variability in the spat of clams (Ruditapes philippinarum)

Aquaculture ◽  
2011 ◽  
Vol 321 (1-2) ◽  
pp. 113-120 ◽  
Author(s):  
David Tamayo ◽  
Irrintzi Ibarrola ◽  
Miren B. Urrutia ◽  
Enrique Navarro
Keyword(s):  
Ruditapes Philippinarum ◽  
Individual Growth ◽  
Physiological Basis ◽  
Growth Variability

scholarly journals Inter- and intraspecific variability of plant individual growth and its role on species ranking in grasslands

2020 ◽  
Vol 13 (3) ◽  
pp. 378-386
Author(s):  
Rémi Perronne ◽  
Franck Jabot ◽  
Julien Pottier
Keyword(s):  
Plant Growth ◽  
Soil Properties ◽  
Growth Rates ◽  
Environmental Conditions ◽  
Intraspecific Variability ◽  
Individual Variability ◽  
Individual Growth ◽  
Biomass Estimation ◽  
Massif Central ◽  
Growth Variability

Abstract Aims Individual growth constitutes a major component of individual fitness. However, measuring growth rates of herbaceous plants non-destructively at the individual level is notoriously difficult. This study, based on an accurate non-destructive method of aboveground biomass estimation, aims to assess individual relative growth rates (RGRs) of some species, identify its environmental drivers and test its consequences on community patterning. We specifically address three questions: (i) to what extent environmental conditions explain differences in individual plant growth between sites, (ii) what is the magnitude of intraspecific variability of plant individual growth within and between sites and (iii) do species-averaged (dis-)advantage of individual growth compared with the whole vegetation within a site correlate with species ranking at the community level? Methods We monitored the growth of individuals of four common perennial species in 18 permanent grasslands chosen along a large pedoclimatic gradient located in the Massif Central, France. We measured soil properties, levels of resources and meteorological parameters to characterize environmental conditions at the site level. This design enables us to assess the influence of environmental conditions on individual growth and the relative extent of inter-individual variability of growth explained within and between sites. We determined the ranking of each of the four species in each site with botanical surveys to assess the relationship between species-averaged growth (dis-)advantage relative to the whole community and species rank in the community. Important Findings We found that environmental conditions explain a significant proportion of individual growth variability, and that this proportion is strongly variable between species. Light availability was the main driver of plant growth, followed by rainfall amount and potential evapotranspiration, while soil properties had only a slight effect. We further highlighted a moderate to high within-site inter-individual variability of growth. We finally showed that there was no correlation between species ranking and species-averaged individual growth.

Scale analyses to estimate somatic growth in sockeye salmon, Oncorhynchus nerka

1997 ◽  
Vol 54 (3) ◽  
pp. 631-636 ◽  
Author(s):  
M Fukuwaka ◽  
M Kaeriyama
Keyword(s):  
Sockeye Salmon ◽  
Oncorhynchus Nerka ◽  
Somatic Growth ◽  
Individual Growth ◽  
Path Coefficient ◽  
Passive Integrated Transponder ◽  
Linear Path ◽  
Absolute Growth ◽  
Back Calculation ◽  
The Relationship

The relationships between individual growth and scale pattern were examined for juvenile sockeye salmon (Oncorhynchus nerka) marked with passive integrated transponder (PIT) tags to assess the usefulness of scale analyses for estimating somatic growth. The relationship between absolute somatic growth and increment of scale radius was linear. The relationship between increment of scale radius and number of circuli was also linear. Path analysis showed that the number of circuli was directly correlated with absolute growth. A negative path coefficient (-0.200) between absolute growth and number of circuli indicated that circulus spacing was positively correlated with somatic growth. The relationship between circulus spacing and absolute growth was linear (circulus spacing ( µm) = 0.528 times absolute growth (mm) - 9.57). Results indicate that somatic growth affects circulus spacing directly. Circulus spacing was useful for comparing mean growth from the above equation, while back-calculation was useful for estimating individual growth.

Consequences of assuming an incorrect error structure in von Bertalanffy growth models: a simulation study

2007 ◽  
Vol 64 (4) ◽  
pp. 602-617 ◽  
Author(s):  
J Paige Eveson ◽  
Tom Polacheck ◽  
Geoff M Laslett
Keyword(s):  
Model Selection ◽  
Growth Models ◽  
Individual Variability ◽  
Individual Growth ◽  
Von Bertalanffy ◽  
Selection Procedures ◽  
Error Structure ◽  
Growth Variability ◽  
Length Data ◽  
Data Coverage

The underlying sources of growth variability in a population cannot generally be known, so when modelling growth it is important to understand the consequences of assuming an incorrect error structure. In this study, four error models for a von Bertalanffy growth curve with asymptotic length parameter L∞ and growth rate parameter k are considered. Simulations are carried out in which data are generated according to one of the models and fitted assuming each of the models to be true. This is done for two types of data: direct age–length and tag–recapture. For direct age–length data, the consequences of not accounting for individual growth variability, or assuming the wrong source of variability, are minor, even when individual variability is high or data coverage is poor. For tag–recapture data, some substantial biases in growth estimates can arise when individual variability exists but is not accounted for. Importantly, however, incorporating variability in just one parameter (be it L∞ or k), even if the variability truly stems from the other or both parameters, generally leads to much smaller biases than assuming no individual variability. Often the alternative models cannot be distinguished using standard model selection procedures, so caution is warranted in using model selection to draw inferences about underlying sources of growth variability.

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