scholarly journals Trends in Growth Modeling in Fisheries Science

Fishes ◽  
2021 ◽  
Vol 6 (1) ◽  
pp. 1
Author(s):  
Shane A. Flinn ◽  
Stephen R. Midway
Keyword(s):  
Model Selection ◽  
Growth Model ◽  
Growth Models ◽  
Growth Modeling ◽  
Age And Growth ◽  
Von Bertalanffy ◽  
Fisheries Science ◽  
Growth Studies ◽  
Stock Assessments ◽  
Von Bertalanffy Growth Model

Growth models estimate life history parameters (e.g., growth rates and asymptotic size) that are used in the management of fisheries stocks. Traditionally in fisheries science, it was common to fit one growth model—the von Bertalanffy growth model—to size-at-age data. However, in recent years, fisheries science has seen an increase in the number of growth models available and the evaluation of multiple growth models for a given species or study. We reviewed n = 196 peer-reviewed age and growth studies and n = 50 NOAA (National Oceanic and Atmospheric Administration) regional stock assessments to examine trends in the use of growth models and model selection in fisheries over time. Our results indicate that the total number of age and growth studies increased annually since 1988 with a slight proportional increase in the use of multi-model frameworks. Information theoretic approaches are replacing goodness-of-fit and a priori model selection in fisheries studies; however, this trend is not reflected in NOAA stock assessments, which almost exclusively rely on the von Bertalanffy growth model. Covariates such as system (e.g., marine or fresh), location of study, diet, family, maximum age, and range of age data used in model fitting did not contribute to which model was ultimately the best fitting, suggesting that there are no large-scale patterns of specific growth models being applied to species with common life histories or other attributes. Given the importance and ubiquity of growth modeling to fisheries science, a historical and contemporary understanding of the practice is critical to evaluate improvements that have been made and future challenges.

Red Snapper: Ecology and Fisheries in the U.S. Gulf of Mexico

2007 ◽  
Keyword(s):  
Gulf Of Mexico ◽  
Growth Model ◽  
Fisheries Management ◽  
Red Snapper ◽  
Age And Growth ◽  
Von Bertalanffy ◽  
Lutjanus Campechanus ◽  
History Of ◽  
Von Bertalanffy Growth Model ◽  
The U.S

<em>Abstract.</em>—The red snapper, <em>Lutjanus campechanus</em>, is one of the most economically important fish species in the Gulf of Mexico (GOM). Concerns over the declines in red snapper landings during the 1980s in the GOM exposed the paucity of information regarding the species’ age, growth, and population dynamics, all fundamental in fisheries management. This paper reviews the history of red snapper age and growth research in the GOM demonstrating an evolution of fisheries aging and validation techniques. These refinements in aging over time have also impacted management of the red snapper stock in the GOM. Also discussed are efforts to standardize aging techniques throughout the GOM in an effort to improve data accuracy. A number of studies have used the von Bertalanffy growth model to describe a pattern of rapid growth followed by slower growth after the age of ten years for red snapper in the GOM. Additional applications of the von Bertalanffy growth model have also been applied to corroborate red snapper age estimates derived from sectioned otoliths and to discern demographic differences in red snapper growth throughout the GOM.

scholarly journals Age and growth of the deep water mud shrimp Solenocera melantho (De Man, 1907) off Visakhapatnam coast, India

2016 ◽  
Vol 63 (4) ◽  
Author(s):  
P. R. C. Ganesh ◽  
Myla. S. Chakravarty
Keyword(s):  
Growth Model ◽  
Deep Water ◽  
Growth Parameters ◽  
Age And Growth ◽  
Von Bertalanffy ◽  
Males And Females ◽  
Von Bertalanffy Growth Model ◽  
Mud Shrimp ◽  
De Man ◽  
Visakhapatnam Coast

Age and growth of the deep water mud shrimp Solenocera melantho (De Man, 1907) was estimated using von Bertalanffy growth model employing modal progression analysis, Ford-Walford method for L∞ and K and t0 by Gulland’s method as well as ELEFAN I (FiSAT II software version 1.2.2) method. The growth parameters estimated by the former method were: L∞= 107.9 mm, K = 2.61 y-1, t0 = 0.1344, φ’ = 4.4825 for males and L∞ = 116.4 mm, K = 3.69 y-1, t0 = 0.1346, φ’ = 4.6997 for females and by the latter method were : L∞ = 106.1 mm, K = 2.17 y-1, t0 = -0.05, φ’ = 4.3879 for males and L∞ = 116.8 mm, K = 2.1 y-1, t0 = -0.05, φ’ = 4.4571 for females. The longevity estimated for both males and females of S. melantho was about 36 months. The females were observed to grow faster than the males.

scholarly journals Age and growth of franciscana dolphins, Pontoporia blainvillei (Cetacea: Pontoporiidae) incidentally caught off southern Brazil and northern Argentina

2010 ◽  
Vol 90 (8) ◽  
pp. 1493-1500 ◽  
Author(s):  
Silvina Botta ◽  
Eduardo R. Secchi ◽  
Mônica M.C. Muelbert ◽  
Daniel Danilewicz ◽  
Maria Fernanda Negri ◽  
...  
Keyword(s):  
Growth Models ◽  
Growth Curves ◽  
Small Sample ◽  
Age And Growth ◽  
Buenos Aires Province ◽  
Von Bertalanffy ◽  
Southern Brazil ◽  
Data Set ◽  
Males And Females ◽  
Pontoporia Blainvillei

Age and length data of 291 franciscana dolphins (Pontoporia blainvillei) incidentally captured on the coast of Rio Grande do Sul State (RS), southern Brazil, were used to fit growth curves using Gompertz and Von Bertalanffy growth models. A small sample of franciscanas (N = 35) from Buenos Aires Province (BA), Argentina, were used to see if there are apparent growth differences between the populations. Male and female franciscana samples from both areas were primarily (78–85%) <4 years of age. The Von Bertalanffy growth model with a data set that excluded animals <1 year of age provided the best fit to data. Based on this model, dolphins from the RS population reached asymptotic length at 136.0 cm and 158.4 cm, for males and females, respectively. No remarkable differences were observed in the growth trajectories of males and females between the RS and BA populations.

Growth of the saucer scallop, Amusium japonicum balloti Habe, in central eastern Queensland

1981 ◽  
Vol 32 (4) ◽  
pp. 657 ◽  
Author(s):  
MJ Williams ◽  
MCL Dredge
Keyword(s):  
Growth Model ◽  
Larval Stage ◽  
Size Range ◽  
Von Bertalanffy ◽  
Commercial Fishery ◽  
Long Distance ◽  
Von Bertalanffy Growth Model ◽  
Central Eastern

Tag-recapture data were used to determine growth and movement of A. japonicum balloti. The von Bertalanffy growth model was found to be suitable for describing growth in the latter half of the size range for A. japonicum balloti, and estimated S∞ of scallops varied with year and area. A. japonicum balloti grows rapidly, being recruited to the commercial fishery at about 6 months of age in some cases. Recapture data indicated that A. japonicum balloti does not undergo long-distance displacements in its post-larval stage.

Modelling individual variability in growth of bull trout in the Walla Walla River Basin using a hierarchical von Bertalanffy growth model

2016 ◽  
Vol 27 (1) ◽  
pp. 103-115 ◽  
Author(s):  
Julianne E. Harris ◽  
Courtney Newlon ◽  
Philip J. Howell ◽  
Ryan C. Koch ◽  
Steven L. Haeseker
Keyword(s):  
River Basin ◽  
Growth Model ◽  
Individual Variability ◽  
Bull Trout ◽  
Von Bertalanffy ◽  
Von Bertalanffy Growth Model ◽  
Walla Walla

Length-at-Age Analysis: Can You Get What You See?

1992 ◽  
Vol 49 (4) ◽  
pp. 632-643 ◽  
Author(s):  
T. J. Mulligan ◽  
B. M. Leaman
Keyword(s):  
Growth Model ◽  
Time Trend ◽  
Single Point ◽  
Mortality Rates ◽  
Individual Growth ◽  
Parameter Estimates ◽  
Von Bertalanffy ◽  
Model Ambiguity ◽  
Von Bertalanffy Growth Model ◽  
Single Set

Observations at a single point in time of length-at-age (LAA) for a long-lived rockfish (Sebastes alutus) show that old fish are shorter than intermediate-aged fish. Fitting of a von Bertalanffy growth model to these data produces a systematic trend in the residual of observed versus calculated LAA. We examined how such LAA data can lead to erroneous conclusions about individual growth, and whether asymptotic growth can give rise to such data. We considered two hypotheses: (i) that a time trend in growth rate resulted in larger fish in more recent years and (ii) that there are multiple growth types, where growth and mortality rates are directly related. Using a general growth model that incorporated both (i) and (ii), we show that both hypotheses can generate data identical to those for the rockfish. A single set of LAA data is inadequate for describing individual growth; however, if sufficient data are available, model ambiguity can be resolved and reasonable parameter estimates obtained. Analysis of the rockfish data indicates that (ii) is more likely to explain the observations than (i). We show how fisheries on such species may preclude our understanding these biological relationships.

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.

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