Age and growth estimates of the jumbo flying squid (Dosidicus gigas) off Peru

2019 ◽  
Vol 32 ◽  
pp. 7
Author(s):  
Carlos Goicochea-Vigo ◽  
Enrique Morales-Bojórquez ◽  
Viridiana Y. Zepeda-Benitez ◽  
José Ángel Hidalgo-de-la-Toba ◽  
Hugo Aguirre-Villaseñor ◽  
...  
Keyword(s):  
Growth Model ◽  
Growth Pattern ◽  
Growth Models ◽  
Information Criterion ◽  
Growth Patterns ◽  
Age And Growth ◽  
Dosidicus Gigas ◽  
Asymptotic Growth ◽  
Schnute Model ◽  
Gompertz Growth Model

Mantle length (ML) and age data were analyzed to describe the growth patterns of the flying jumbo squid, Dosidicus gigas, in Peruvian waters. Six non-asymptotic growth models and four asymptotic growth models were fitted. Length-at-age data for males and females were analysed separately to assess the growth pattern. Multi-model inference and Akaike's information criterion were used to identify the best fitting model. For females, the best candidate growth model was the Schnute model with L∞ = 106.96 cm ML (CI 101.23–110.27 cm ML, P < 0.05), age at growth inflection 244.71 days (CI 232.82–284.86 days, P < 0.05), and length at growth inflection 57.26 cm ML (CI 55.42–58.51 cm ML, P < 0.05). The growth pattern in males was best described by a Gompertz growth model with L∞ = 127.58 cm ML (CI 115.27–131.80 cm ML, P < 0.05), t0 = 21.8 (CI 20.06–22.41, P < 0.05), and k = 0.007 (CI 0.006–0.007, P < 0.05). These results contrast with the growth model previously reported for D. gigas in the region, where the growth pattern was identified as non-asymptotic.

scholarly journals Selecting the best growth model for elasmobranches

2015 ◽  
Author(s):  
Kwang-Ming Liu ◽  
Chiao-Bin Wu ◽  
Shoou-Jeng Joung ◽  
Wen-Pei Tsai
Keyword(s):  
Growth Model ◽  
Growth Models ◽  
Stock Assessment ◽  
Gompertz Model ◽  
Information Criterion ◽  
Age And Growth ◽  
Deep Waters ◽  
Extended Longevity ◽  
Best Fit ◽  
Two Parameter

Age and growth information is essential for accurate stock assessment of fish, and growth model selection may influence the result of stock assessment. Previous descriptions of the age and growth of elasmobranches relied mainly on the von Bertalanffy growth model (VBGM). However, it has been noted that sharks, skates and rays exhibit significant variety in size, shape, and life-history traits. Given this variation, the VBGM may not necessarily provide the best fit for all elasmobranches. This study attempts to improve the accuracy of age estimates by testing four growth models—the VBGM, two-parameter VBGM, Robertson (Logistic) and Gompertz models—to fit observed and simulated length-at-age data for 37 species of elasmobranches. The best growth model was selected based on corrected Akaike’s Information Criterion (AICc), the AICc difference, and the AICc weight. The VBGM and two-parameter VBGM provide the best fit for species with slow growth and extended longevity (L∞ > 100 cm TL, 0.05 < k < 0.15 yr-1), such as pelagic sharks. For fast-growing small sharks (L∞ < 100 cm TL, kr or kg > 0.2 yr-1) in deep waters and for small-sized demersal skates/rays, the Robertson and the Gompertz models provide the best fit. The best growth models for small sharks in shallow waters are the two-parameter VBGM and the Robertson model, while all the species best fit by the Gompertz model are skates and rays.

scholarly journals Multi-Model Approach on Growth Estimation and Association With Life History Trait for Elasmobranchs

2021 ◽  
Vol 8 ◽  
Author(s):  
Kwang-Ming Liu ◽  
Chiao-Bin Wu ◽  
Shoou-Jeng Joung ◽  
Wen-Pei Tsai ◽  
Kuan-Yu Su
Keyword(s):  
Life History ◽  
Growth Model ◽  
Growth Models ◽  
Stock Assessment ◽  
Information Criterion ◽  
Age And Growth ◽  
Life History Trait ◽  
Best Fit ◽  
Two Parameter ◽  
Model Approach

Age and growth information is essential for stock assessment of fish, and growth model selection may influence the accuracy of stock assessment and subsequent fishery management decision making. Previous descriptions of the age and growth of elasmobranchs relied mainly on the von Bertalanffy growth model (VBGM). However, it has been noted that sharks, skates and rays exhibit significant variety in size, shape, and life history traits. Given this variation, the VBGM may not necessarily provide the best fit for all elasmobranchs. This study attempts to improve the growth estimates by using multi-model approach to test four growth models—the VBGM, the two-parameter VBGM, the Robertson (Logistic) and the Gompertz models to fit observed or simulated length-at-age data for 38 species (44 cases) of elasmobranchs. The best-fit growth model was selected based on the bias corrected Akaike’s Information Criterion (AICc), the AICc difference, the AICc weight, the Bayesian Information Criterion (BIC), and the Leave-one-out cross-validation (LOOCV). The VBGM and two-parameter VBGM provide the best fit for species with slow growth and extended longevity (L∞ &gt; 100 cm TL, 0.02 &lt; k &lt; 0.25 yr–1), such as pelagic sharks. For fast-growing small sharks (L∞ &lt; 100 cm TL, kr or kg &gt; 0.2 yr–1) in deep waters and for small-sized demersal skates/rays, the Robertson and the Gompertz models provide the best fit. The best-fit growth models for small sharks in shallow waters are the two-parameter VBGM and the Robertson model. Although it was found that the best-fit growth models for elasmobranchs were associated with their life history trait, exceptions were also noted. Therefore, a multi-model approach incorporating with the best-fit model selected for each group in this study was recommended in growth estimation for elasmobranchs.

scholarly journals Selecting the best growth model for elasmobranches

2015 ◽  
Author(s):  
Kwang-Ming Liu ◽  
Chiao-Bin Wu ◽  
Shoou-Jeng Joung ◽  
Wen-Pei Tsai
Keyword(s):  
Growth Model ◽  
Growth Models ◽  
Stock Assessment ◽  
Gompertz Model ◽  
Information Criterion ◽  
Age And Growth ◽  
Deep Waters ◽  
Extended Longevity ◽  
Best Fit ◽  
Two Parameter

Age and growth information is essential for accurate stock assessment of fish, and growth model selection may influence the result of stock assessment. Previous descriptions of the age and growth of elasmobranches relied mainly on the von Bertalanffy growth model (VBGM). However, it has been noted that sharks, skates and rays exhibit significant variety in size, shape, and life-history traits. Given this variation, the VBGM may not necessarily provide the best fit for all elasmobranches. This study attempts to improve the accuracy of age estimates by testing four growth models—the VBGM, two-parameter VBGM, Robertson (Logistic) and Gompertz models—to fit observed and simulated length-at-age data for 37 species of elasmobranches. The best growth model was selected based on corrected Akaike’s Information Criterion (AICc), the AICc difference, and the AICc weight. The VBGM and two-parameter VBGM provide the best fit for species with slow growth and extended longevity (L∞ > 100 cm TL, 0.05 < k < 0.15 yr-1), such as pelagic sharks. For fast-growing small sharks (L∞ < 100 cm TL, kr or kg > 0.2 yr-1) in deep waters and for small-sized demersal skates/rays, the Robertson and the Gompertz models provide the best fit. The best growth models for small sharks in shallow waters are the two-parameter VBGM and the Robertson model, while all the species best fit by the Gompertz model are skates and rays.

scholarly journals Comparison of growth models to describe growth from birth to 6 years in a Beninese cohort of children with repeated measurements

BMJ Open ◽  
2020 ◽  
Vol 10 (9) ◽  
pp. e035785
Author(s):  
Shukrullah Ahmadi ◽  
Florence Bodeau-Livinec ◽  
Roméo Zoumenou ◽  
André Garcia ◽  
David Courtin ◽  
...  
Keyword(s):  
Growth Model ◽  
Goodness Of Fit ◽  
Growth Models ◽  
Information Criterion ◽  
Height Growth ◽  
Sub Saharan Africa ◽  
Individual Growth ◽  
Secondary Outcome ◽  
Growth Trajectories ◽  
Best Fitting

ObjectiveTo select a growth model that best describes individual growth trajectories of children and to present some growth characteristics of this population.SettingsParticipants were selected from a prospective cohort conducted in three health centres (Allada, Sekou and Attogon) in a semirural region of Benin, sub-Saharan Africa.ParticipantsChildren aged 0 to 6 years were recruited in a cohort study with at least two valid height and weight measurements included (n=961).Primary and secondary outcome measuresThis study compared the goodness-of-fit of three structural growth models (Jenss-Bayley, Reed and a newly adapted version of the Gompertz growth model) on longitudinal weight and height growth data of boys and girls. The goodness-of-fit of the models was assessed using residual distribution over age and compared with the Akaike Information Criterion (AIC) and Bayesian Information Criterion (BIC). The best-fitting model allowed estimating mean weight and height growth trajectories, individual growth and growth velocities. Underweight, stunting and wasting were also estimated at age 6 years.ResultsThe three models were able to fit well both weight and height data. The Jenss-Bayley model presented the best fit for weight and height, both in boys and girls. Mean height growth trajectories were identical in shape and direction for boys and girls while the mean weight growth curve of girls fell slightly below the curve of boys after neonatal life. Finally, 35%, 27.7% and 8% of boys; and 34%, 38.4% and 4% of girls were estimated to be underweight, wasted and stunted at age 6 years, respectively.ConclusionThe growth parameters of the best-fitting Jenss-Bayley model can be used to describe growth trajectories and study their determinants.

Statistical modeling of baleen and body length at age in bowhead whales (Balaena mysticetus)

2012 ◽  
Vol 90 (8) ◽  
pp. 915-931 ◽  
Author(s):  
S.C. Lubetkin ◽  
J.E. Zeh ◽  
J.C. George
Keyword(s):  
Body Length ◽  
Growth Model ◽  
Growth Models ◽  
Information Criterion ◽  
Single Stage ◽  
Von Bertalanffy ◽  
Balaena Mysticetus ◽  
Bowhead Whales ◽  
Multi Stage ◽  
Age Estimates

We used baleen lengths and age estimates from 175 whales and body lengths and age estimates from 205 whales to test which of several single- and multi-stage growth models best characterized age-specific baleen and body lengths for bowhead whales ( Balaena mysticetus L., 1758) with the goal of determining which would be best for predicting whale age based on baleen or body length. Previous age estimates were compiled from several techniques, each of which is valid over a relatively limited set of physical characteristics. The best fitting single-stage growth model was a variation of the von Bertalanffy growth model for both baleen and body length data. Based on Bayesian information criterion, the two- and three-stage versions of the von Bertalanffy model fit the data better than did the single-stage models for both baleen and body length. The best baleen length models can be used to estimate expected ages for bowhead whales with up to 300–325 cm baleen, depending on sex, which correspond to age estimates approaching 60 years. The best body length models can be used to estimate expected ages for male bowhead whales up to 14 m, and female bowheads up to 15.5 m or ages up to approximately 40 years.

scholarly journals Age estimation and the best growth model selection of the tentacled blenny Parablennius tentacularis (Brünnich, 1768) in the southeastern Black Sea

2021 ◽  
Vol 38 (2) ◽  
pp. 229-236
Author(s):  
Ayşe Van ◽  
Aysun Gümüş ◽  
Melek Özpiçak ◽  
Serdar Süer
Keyword(s):  
Growth Model ◽  
Black Sea ◽  
Growth Parameters ◽  
Growth Models ◽  
Information Criterion ◽  
Current Data ◽  
Logistic Growth ◽  
Data Set ◽  
Frequency Distributions ◽  
Selection Of

By the study's coverage, 522 individuals of tentacled blenny (Parablennius tentacularis (Brünnich, 1768)), were caught with the bottom trawl operations (commercial fisheries and scientific field surveys) between May 2010 and March 2012 from the southeastern Black Sea. The size distribution range of the sample varied between 4.8-10.8 cm. The difference between sex length (K-S test, Z=3.729, P=0.000) and weight frequency distributions (K-S test, Z=3.605, P=0.000) was found to be statistically significant. The length-weight relationship models were defined as isometric with W = 0.009L3.034 in male individuals and positive allometric with W = 0.006L3.226 in female individuals. Otolith and vertebra samples were compared for the selection of the most accurate hard structure that can be used to determine the age. Otolith was chosen as the most suitable hard structure. The current data set was used to predict the best growth model. For this purpose, the growth parameters were estimated with the widely used von Bertalanffy, Gompertz and Logistic growth functions. Akaike's Information Criterion (AIC), Lmak./L∞ ratio, and R2 criteria were used to select the most accurate growth models established through these functions. Model averaged parameters were calculated with multi-model inference (MMI): L'∞ = 15.091 cm, S.E. (L'∞) = 3.966, K'= 0.232 year-1, S.E. (K') = 0.122.

scholarly journals A New Flexible Sigmoidal Growth Model

Symmetry ◽  
2019 ◽  
Vol 11 (2) ◽  
pp. 204 ◽  
Author(s):  
Liying Cao ◽  
Pei-Jian Shi ◽  
Lin Li ◽  
Guifen Chen
Keyword(s):  
Growth Rate ◽  
Growth Model ◽  
Growth Models ◽  
Differential Evolution Algorithm ◽  
Growth Patterns ◽  
Growth Data ◽  
Ecological Processes ◽  
Maximum Biomass ◽  
Sigmoidal Growth ◽  
Growth Of Animals

Biological growth is driven by numerous functions, such as hormones and mineral nutrients, and is also involved in various ecological processes. Therefore, it is necessary to accurately capture the growth trajectory of various species in ecosystems. A new sigmoidal growth (NSG) model is presented here for describing the growth of animals and plants when the assumption is that the growth rate curve is asymmetric. The NSG model was compared with four classic sigmoidal growth models, including the logistic equation, Richards, Gompertz, and ontogenetic growth models. Results indicated that all models fit well with the empirical growth data of 12 species, except the ontogenetic growth model, which only captures the growth of animals. The estimated maximum asymptotic biomass wmax of plants from the ontogenetic growth model was not reliable. The experiment result shows that the NSG model can more precisely estimate the value and time of reaching maximum biomass when growth rate becomes close to zero near the end of growth. The NSG model contains three other parameters besides the value and time of reaching maximum biomass, and thereby, it can be difficult to assign initial values for parameterization using local optimization methods (e.g., using Gauss–Newton or Levenberg–Marquardt methods). We demonstrate the use of a differential evolution algorithm for resolving this issue efficiently. As such, the NSG model can be applied to describing the growth patterns of a variety of species and estimating the value and time of achieving maximum biomass simultaneously.

Growth and sexual size dimorphism in Alberta populations of the eastern short-horned lizard, Phrynosoma douglassi brevirostre

1985 ◽  
Vol 63 (1) ◽  
pp. 139-154 ◽  
Author(s):  
G. Lawrence Powell ◽  
Anthony P. Russell
Keyword(s):  
Growth Model ◽  
Sexual Difference ◽  
Sexual Size Dimorphism ◽  
Growth Models ◽  
Tail Length ◽  
Growth Patterns ◽  
Head Width ◽  
Adult Size ◽  
Adult Males ◽  
Size Dimorphism

Alberta populations of Phrynosoma douglassi brevirostre display marked sexual size dimorphism, adult females being considerably larger than adult males. Discriminant analyses of whole mensural characters and of scaled mensural characters indicate that this dimorphism is present from birth, although it is more strongly expressed after sexual maturity. Recapture data were used to generate modified logistic by weight growth models for snout–vent length (SVL), and allometric models for each sex were generated for growth in tail length, head length, and head width. The SVL growth model for females indicates delayed maturity leading to greater adult size, an expected feature of a female viviparine. The SVL growth model for males indicates that growth ceases sooner than in females, resulting in a smaller adult size. This is possibly a result of male dispersal competition, an hypothesis further borne out by the results of a preliminary analysis of mobility in the two sexes, and may also be influenced by intersexual dietary competition. Differences in head dimensions between the sexes are a function of the differences in SVL at adulthood, but there is a significant sexual difference in the allometric relationship of tail length to SVL. No difference in the growth patterns and adult size of either sex was found to exist over the range in Alberta.

Growth patterns of two widely distributed freshwater turtles and a comparison of common methods used to estimate age

2002 ◽  
Vol 50 (5) ◽  
pp. 477 ◽  
Author(s):  
Ricky-John Spencer
Keyword(s):  
Growth Models ◽  
Sympatric Species ◽  
Growth Patterns ◽  
Juvenile Stage ◽  
Age And Growth ◽  
Logistic Growth ◽  
Freshwater Turtles ◽  
Dietary Shift ◽  
Demographic Models ◽  
Murray River

Turtles are long lived and demographic models requiring estimates of age, growth, fecundity and survival are central for management. Most studies that estimate age and growth of freshwater turtles use annuli as an index of age without estimating its error and very few studies that use growth models include many juveniles, where growth is often large and variable. In this paper, I compare the reliability of growth annuli and common models in determining age and growth of two widely distributed turtles in Australia. Most turtles are carnivorous during the juvenile stage but many species shift to a lower-quality omnivorous diet prior to maturing. Patterns of growth are often characterised by this dietary shift and I compared the growth of a common omnivorous turtle (Emydura macquarii) and a vulnerable sympatric species that is an obligate carnivore (Chelodina expansa). Mark–recapture programs were established in three lagoons on the Murray River. In total, 1218 hatchling E. macquarii were released into two of the lagoons and growth annuli were found to be unreliable in estimating their age by Year 2. The von Bertalanffy and logistic growth models can reliably estimate age of both male and female E. macquarii and C. expansa respectively. Growth is extremely rapid during the juvenile stage of E. macquarii, but is highly variable in C. expansa, with rapid growth occurring only beyond three years of age. Hence growth models fail to predict age when juveniles are excluded from the analyses. Female E. macquarii delay maturity until 9–12 years of age because clutch size is positively related to body size and they can produce only one large clutch per year. Female C.�expansa mature later (at ~14 years) than female E. macquarii and both species are sexually dimorphic, as males mature earlier at smaller sizes than females. Common growth models describe the growth of two widely distributed freshwater turtles, but different patterns of growth and age at maturity relate to quality of diet and reproduction.

scholarly journals The influence of sample distribution on growth model output for a highly-exploited marine fish, the Gulf Corvina (Cynoscion othonopterus)

PeerJ ◽  
2018 ◽  
Vol 6 ◽  
pp. e5582 ◽  
Author(s):  
Derek G. Bolser ◽  
Arnaud Grüss ◽  
Mark A. Lopez ◽  
Erin M. Reed ◽  
Ismael Mascareñas-Osorio ◽  
...  
Keyword(s):  
Growth Model ◽  
Marine Fish ◽  
Growth Models ◽  
Growth Patterns ◽  
Von Bertalanffy ◽  
Model Output ◽  
Age Classes ◽  
Equal Distribution ◽  
Sample Distribution ◽  
Richards Model

Estimating the growth of fishes is critical to understanding their life history and conducting fisheries assessments. It is imperative to sufficiently sample each size and age class of fishes to construct models that accurately reflect biological growth patterns, but this may be a challenging endeavor for highly-exploited species in which older fish are rare. Here, we use the Gulf Corvina (Cynoscion othonopterus), a vulnerable marine fish that has been persistently overfished for two decades, as a model species to compare the performance of several growth models. We fit the von Bertalanffy, Gompertz, logistic, Schnute, and Schnute–Richards growth models to length-at-age data by nonlinear least squares regression and used simple indicators to reveal biased data and ensure our results were biologically feasible. We then explored the consequences of selecting a biased growth model with a per-recruit model that estimated female spawning-stock-biomass-per-recruit and yield-per-recruit. Based on statistics alone, we found that the Schnute–Richards model described our data best. However, it was evident that our data were biased by a bimodal distribution of samples and underrepresentation of large, old individuals, and we found the Schnute–Richards model output to be biologically implausible. By simulating an equal distribution of samples across all age classes, we found that sample distribution distinctly influenced model output for all growth models tested. Consequently, we determined that the growth pattern of the Gulf Corvina was best described by the von Bertalanffy growth model, which was the most robust to biased data, comparable across studies, and statistically comparable to the Schnute–Richards model. Growth model selection had important consequences for assessment, as the per-recruit model employing the Schnute–Richards model fit to raw data predicted the stock to be in a much healthier state than per-recruit models employing other growth models. Our results serve as a reminder of the importance of complete sampling of all size and age classes when possible and transparent identification of biased data when complete sampling is not possible.

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