Estimated Growth Parameters Research Articles

Gomperzt non-linear model for predicting growth performance of commercial broiler chickens

An experiment was conducted to estimate growth parameters for commercial broiler chickens in Indonesia. The data was collected from July 2021 to June 2022. A total of 1,570 samples consisting of four strains of broiler chickens were collected from 74 houses. The samples were daily weighed from 0 to 7 days of age, and they were weekly weighed from 1 to 5 weeks of age. A nonlinear Gompertz growth model was fitted to the observed body weights (BW). The results for five growth parameters were as follows: the asymptotic value (A) of the mature live weight ranged from 3.733 to 5.044 kg; the turning point of growth (B) ranged from 4.499 to 4.561; the value growth rate constant (K) ranged from 0.049 to 0.059 kg/week; Inflection points in ranged from 25.292 – 30.970 days, and 1.373 – 1.855 kg for inflection age (IA) and inflection weight (IW), respectively. The model was an excellent fit for the growth data in the commercial broiler with a low Akaike information criterion (AIC), and high coeffi-cient determination (R2).

Comparing the accuracy and precision of novel bootstrapped length-frequency and length-at-age (otolith) analyses, with a case study of lane snapper (Lutjanus synagris) in the SW Atlantic

Length-at-age (LAA) and length-frequency analyses (LFA) are widely used to assess body growth in fish. The main objective of this study was to quantify and compare the uncertainty in growth parameter estimates obtained from novel bootstrapped length-at-age analysis (bootLAA) and bootstrapped length-frequency analysis (bootLFA), based on a case study of lane snapper (Lutjanus synagris) caught at the Abrolhos and Royal Charlotte banks (Brazil). Growth parameter estimates for bootLFA were based on 2564 total lengths. Data for bootLAA were obtained by reading 295 otoliths (sagittae). Otolith readings (bootLAA) were 3.6, 2.4 and 6.1 times more precise (for L∞, K and Φ’, respectively) than bootLFA. The median “optimum fit” growth model from bootLFA (n = 2564 total lengths) had the following soVBGF parameters: L∞ = 70.46 cm (95% CI: 56.37–96.84 cm), K = 0.153 y−1 (95% CI: 0.060–0.266 y−1), Φ' = 2.90 log10 (cm y−1) (95% CI: 2.60–2.99), t_anchor = 0.47 (95% CI: 0.12–0.82), C = 0.52 (95% CI: 0.17–0.89), and ts = 0.50 (95% CI: 0.13–0.85). Growth models obtained with different moving average widths (MA) showed significant differences in precision. BootLFA with MA = 5 was much more precise than estimates with wider MA spans. Median values of K and L∞ were not significantly different between bootLAA and bootLFA, indicating a good consistency and reliability of both methods. The median VBGF growth model from bootLAA (n = 295 otoliths) was: L∞ = 59.68 cm (95% CI: 55.94–67.26 cm), K = 0.199 y−1 (95% CI: 0.154–0.239 y−1), Φ' = 2.85 log10 (cm y−1) (95% CI: 2.82–2.89). Despite the higher precision of bootLAA based on otolith readings, its application is often hampered due to constraints in costs, available personnel and time. Our results and analyses indicate that when certain recommendations and criteria are met, bootLFA can be a reliable tool for assessing growth parameters, which are key inputs for fisheries stock assessment and management.

Viability of Deficit Irrigation Pre-Exposure in Adapting Robusta Coffee to Drought Stress

Coffea canephora has high but inadequately exploited genetic diversity. This diversity, if well exploited, can sustain coffee productivity amidst climate change effects. Drought and heat stress are major global threats to coffee productivity, quality, and tradable volumes. It is not well understood if there is a selectable variation for drought stress tolerance in Robusta coffee half-sibs as a result of watering deficit pre-exposure at the germination stage. Half-sib seeds from selected commercial clones (KR5, KR6, KR7) and a pipeline clone X1 were primed with deficit watering at two growth stages followed by recovery and later evaluated for tolerance to watering deficit stress in three different temperature environments by estimation of plant growth and wilt parameters. Overall, the KR7 family performed the best in terms of the number of individuals excelling for tolerance to deficit watering. In order of decreasing tolerance, the 10 most promising individuals for drought and heat tolerance were identified as: 14.KR7.2, 25.X1.1, 35.KR5.5, 36.KR5.6, 41.KR7.5, 46.KR6.4, 47.KR6.5, 291.X1.3, 318.X1.3, and 15.KR7.3. This is the first prospect into the potential of C. canephora half-sibs’ diversity as an unbound source of genetic variation for abiotic stress tolerance breeding.

Effects of Aging Uncertainty on the Estimation of Growth Functions of Major Tuna Species

Fishery stock assessment requires accurate specification of the growth function of target species, and aging uncertainty is an important factor that affects the estimation of growth parameters. In this study, we used simulations to study the effects of two types of aging uncertainty, aging error and sampled age range, on the parameter estimation of the Von Bertalanffy growth function, including asymptotic length (L∞), growth coefficient (k), and theoretical age in the year at zero length (t0) of five important tuna species. We found that the uncertainty of the estimated growth curves increased with increasing aging errors. When aging errors were fixed among ages, the effects of age range on estimation error of growth parameters were different among species and growth parameters. When the aging error increased with age, the estimation uncertainty of L∞ and k was the greatest when only young age groups were sampled, while the estimation uncertainty of t0 was the greatest when only old age groups were sampled. Therefore, reducing the aging error and sampling individuals with a wider age range are important for increasing the accuracy and decreasing the uncertainty of the estimated growth function, which will further reduce the uncertainty in fishery stock assessment.

Information on the deep-water giant red shrimp Aristaeomorpha foliacea (Risso, 1827) (Crustacea, Decapoda, Aristeidae) population in Antalya Bay (Eastern Mediterranean Sea, South of Turkey) based on the MEDITS protocol

The main aim of this study was to contribute to the current knowledge on the population of Aristaeomorpha foliacea in Antalya Bay located on the southern coast of Turkey in the Mediterranean Sea. Monthly samples were collected between July 2016 and July 2017 from experimental trawl surveys in accordance with the International Bottom Trawl Survey in the Mediterranean (MEDITS) protocol. The abundance index was calculated as 4308.6 N/km 2 and the biomass index as 66.8 kg/km 2. The relationship between total weight (TW) and carapace length (CL) was estimated to be TW = 0.00078⋅CL2.76 for females and TW=0.00049⋅CL2.92 for males. The seasonalized von Bertalanffy growth parameter estimates were CL∞=66.12mm, K=0.43 years −1, tanchor=0.36 years, C=0.63 and ts=0.21 years for females, and CL∞=44.02mmK=0.39 year −1, tanchor=0.30 years, C=0.77 and ts=0.87 years for males. Female shrimps grew slightly faster and reached a larger asymptotic size hence exhibiting a greater growth performance than males. The spawning season was determined as the summer. Recruitment took place in spring, and the sex ratios were found to be 1.29:1 in favor of males. The median size at first maturity was estimated as 37.7 mm CL for females and 30.1 mm CL for males. The annual total mortality rate was 1.66 and 1.41, the annual natural mortality rate 0.57 and 0.72, and the exploitation rate 0.66 and 0.49 for females and males, respectively. The fishing ground for A. foliacea in Antalya Bay is situated within 12 nautical miles off the shore within the territorial waters, thus closed to commercial trawl fisheries between 15 April and 15 September in accordance with the Turkish fishery regulations. The closing period, which coincides with the spawning season and also provides a reduction in the fishing pressure, is clearly of great importance for the sustainability of this species in Antalya Bay.

Pertumbuhan Ikan Tongkol Abu-Abu (Thunnus tonggol Bleeker, 1851) yang Tertangkap di Perairan Selat Bali

Longtail Tuna (Thunnus tonggol) in the waters of the Bali Strait is a by-catch fish, so that information on this fish resource was still very lacking and its management of longtail tuna was often neglected. The aimed of this study is to predict the signs of the unsustainability of longtail tuna resources based on growth aspects which include the distribution of length frequency, estimation of age groups, growth patterns and growth parameters. Data collection was carried out from December 2018 to February 2019. The growth pattern estimated by relationship of length and weight, cohort was identified using an analytical model based on the FISAT program (FAO I-CLARM Stock Assessment Tools) and growth parameters were analyzed using the Von Bertalanffy growth model. It can be seen that, the catch is dominated by the size of the fish that have matured gonads or adults (69% females and 73% males). The growth pattern of female and male of longtail tuna is negative allometric (length growth is more dominant than weight). So it can be assumed that there is an inconvenience in environmental conditions and competition in fighting for food and space in the waters of the Bali Strait.Longtail tuna had asymptotic length values of 784.71 mm (female) and 738.04 mm (male) with growth coefficients of 0.13 (female) and 0.18 (male). The growth performance inteprated as quite high when compared to other waters in Indonesia.

Population Parameters of Chama coralloides (Bivalvia: Chamidae) in the Rocky Intertidal of the South-Central Mexican Transitional Pacific

The density, dispersion, size, growth, longevity, natural mortality, and recruitment of Chama coralloides Reeve, 1846, a bivalve captured in artisanal fisheries, were studied. Sample collection was carried out in November 2016, March 2017, and February 2018 at eight sites in the rocky intertidal zone, located in the south-central region of the Mexican Transitional Pacific. Using a 1 x 1 m quadrat, 10 random quadrats were conducted at each site. Density was determined with Pennington's method of Δ distribution. The dispersion was estimated with the Morisita index and modal groups with multinomial analysis. Growth, natural mortality, and recruitment parameters were estimated with FiSAT II. Variable density between sampling dates and sites was observed, with the highest densities found at sites 1 and 4. The largest interquartile range of lengths was observed at site 6, and the smallest at site 5. Five modal groups were determined in November 2016 and March 2017, and four in February 2018. Estimated growth parameters were L ∞= 74.5 mm and K= 0.63; longevity was A .95 = 4.4 and A .99= 6.9 years, growth performance index ∅′= 3.5 and natural mortality M = 1.05 yr–1. Continuous recruitment was observed with a maximum peak in summer.

Age and growth of gangatic Mystus: Mystus cavasius (Hamilton-Buchanan, 1822) by length-frequency analysis from central Brahmaputra Valley, Assam

The Gangatic catfish Mystus cavasius is a native catfish found in Brahmaputra and Barak valley of Assam which is a very popular food fish with has high market price. Our study provides the first data on age and growth of this species in central Brahmaputra valley of Assam. A total number of 285 specimens comprising of 103 males and 182 females have been studied using von Bertalanffy growth model and computer-based FiSAT programme was used for the estimation of growth parameters. In the FiSAT programme, the direct fit of length–frequency data such as Electronic Length Frequency Analysis-I (ELEFAN)-I technique, Shepherd’s method and Powell–Wetherall plot were employed in the present study. The Asymptotic length (L∞) and growth co-efficient (K) (annual) values of Mystus cavasius estimated by ELEFAN I, Shepherd’s method and Powell and Wetherall method. The value of L∞ and K by ELEFAN I, Shepherd’s method and Powell and Wetherall method are 217.0 mm and 0.8 year-1, 215.25 mm and 0.79 year-1 and 220.73 mm and 0.94 year-1 respectively. The two values of Mystus cavasius estimated about -0.41. The total length attained by this fish is about 135 mm at the end of 1st year, 180 mm at the end of 2nd years, 201 mm at the end of 3rd year and 210 mm at the end of 4th year.

Improving estimates of growth for pearl perch (Glaucosoma scapulare) in Queensland, Australia

AbstractThe pearl perch (Glaucosoma scapulare) is endemic to the east coast of Australia in depths to 150 m. The species has a long history of exploitation, and the stock is currently depleted. Previous research indicated the species is long lived and slow growing based on fishery‐dependent sampling undertaken in the late 1990s and early 2000s on traditional fishing grounds at the southern end of the species’ range. Increasing fishing power has facilitated the expansion of the fishery to areas to the north and east of traditional grounds, which has resulted in the appearance of older fish (>10 yr) in fishery‐dependent samples not previously observed. The current study estimated the growth parameters using 1153 length‐at‐age observations from fish collected in Queensland between January 2020 and December 2021. The lack of significant numbers of individuals at either end of the age frequency distribution necessitated the estimation of growth in a Bayesian framework with informative priors for length‐at‐age‐zero and maximum length using a multi‐model approach. The von Bertalanffy growth function (VBGF) was found to best fit the observed length‐at‐age data and the estimated VBGF parameters were L∞ = 562 mm FL, L0 = 2.02 mm FL and k = 0.295 yr−1. The high proportion of older fish in samples, combined with prior information on relevant parameters, improves growth parameter estimation by reducing bias and facilitating improved model fits to observed length‐at‐age data.

Generalizing the Stochastic Approach to Price Indexes

I show that conventional price index formulas and time‐dummy hedonic regression techniques all consistently estimate growth parameters in the same generalized model of product pricing. I then use that result to make two points. First, the “stochastic approach” is not a helpful tool for choosing price index formulas, because in its complete form it can justify any of them. Second, the literature uses flawed arguments for replacing time‐dummy hedonic regression with hedonic imputation. The time‐dummy method is an excellent, underrated option.

Age and growth of the Pacific hake, Merluccius productus (Actinopterygii: Gadiformes: Merlucciidae), in the Gulf of California: A multimodel approach

Over the past decade, the fishery of Pacific hake, Merluccius productus (Ayres, 1855), has increased in the Gulf of California, Mexico; therefore, any biological–fisheries information is highly relevant for the management of this fishery, and information on age and individual growth would be fundamental to evaluate populations. The objective of the presently study was to assess age, based on otolith structure, and estimate growth parameters through a multimodel approach. Specimens were collected during research cruises of BIP XI from 2014 to 2019. Pacific hake from the Gulf of California ranged in length from 12.5 to 105 cm TL, reaching a maximum age of 13 years, and females were four years older than males. The logistic model was the best model to describe age–size data for both sexes. Females reached 50% of the maximum length at five years old and males reached that length at four years old.

Assessing the Population Structure of the Southern Brown Shrimp Farfantepenaeus subtilis (Pérez-Farfante 1967) Using Different Sampling Methods

We analyzed the population structure of Farfantepenaeus subtilis off Sergipe, northeastern Brazil, comparing different sampling methods. Samples were obtained between March 2015 and May 2016 from the commercial shrimp fleet based in the fishing ports of Aracaju (only shrimps categorized by size: small, medium, and large) and Pirambu (shrimps + bycatch), both operating in the same area. Each specimen was measured and weighed: total length – TL (mm), carapace length – CL (mm), and live weight – LW (g). The sex and maturity stage were identified. A total of 4,657 specimens was sampled, with 91.5% originating from Aracaju and 8.5% from Pirambu. Females were larger and heavier than males in both fleets (Aracaju and Pirambu). Inflexion points were observed in the relationships between TL and CL for both sexes (both fleets). The weight-length relationships indicated a negative allometry for both sexes (both fleets). The size at first maturity (CLm) for females was 19.75 mm and 18.94 mm for Aracaju and Pirambu, respectively, and 15.26 mm for males (only for the Aracaju fleet). The reproduction was continuous, with a peak observed in September–October. Except for growth, mortality, distribution, and abundance, both sampling methods allowed for estimating parameters for the population structure and dynamics of F. subtilis. Larger sample sizes would allow for the estimation of growth and mortality parameters when bycatch is included such as the case of the Pirambu fleet. Thus, fishery-dependent data may be used to partially monitor shrimp stocks in Sergipe and other localities where limiting resources are available.

UAV Image-Based Crop Growth Analysis of 3D-Reconstructed Crop Canopies.

Plant growth rate is an essential phenotypic parameter for quantifying potential crop productivity. Under field conditions, manual measurement of plant growth rate is less accurate in most cases. Image-based high-throughput platforms offer great potential for rapid, non-destructive, and objective estimation of plant growth parameters. The aim of this study was to assess the potential for quantifying plant growth rate using UAV-based (unoccupied aerial vehicle) imagery collected multiple times throughout the growing season. In this study, six diverse lines of lentils were grown in three replicates of 1 m2 microplots with six biomass collection time-points throughout the growing season over five site-years. Aerial imagery was collected simultaneously with each manual measurement of the above-ground biomass time-point and was used to produce two-dimensional orthomosaics and three-dimensional point clouds. Non-linear logistic models were fit to multiple data collection points throughout the growing season. Overall, remotely detected vegetation area and crop volume were found to produce trends comparable to the accumulation of dry weight biomass throughout the growing season. The growth rate and G50 (days to 50% of maximum growth) parameters of the model effectively quantified lentil growth rate indicating significant potential for image-based tools to be used in plant breeding programs. Comparing image-based groundcover and vegetation volume estimates with manually measured above-ground biomass suggested strong correlations. Vegetation area measured from a UAV has utility in quantifying lentil biomass and is indicative of leaf area early in the growing season. For mid- to late-season biomass estimation, plot volume was determined to be a better estimator. Apart from traditional traits, the estimation and analysis of plant parameters not typically collected in traditional breeding programs are possible with image-based methods, and this can create new opportunities to improve breeding efficiency mainly by offering new phenotypes and affecting selection intensity.

Reliable growth estimation from mark–recapture tagging data in elasmobranchs

The somatic growth of individuals governs many aspects of a species’ life history and is an important parameter in the assessment of populations. Population growth parameters are typically derived by relating the length of individuals to their age, with ages commonly estimated from growth bands formed in calcified structures such as the vertebrae or dorsal fin spines. However, routinely utilized vertebrae aging methods may not be reliable for many elasmobranchs (sharks, rays and skates), motivating alternative approaches. This study evaluates the performance of seven techniques that estimate von Bertalanffy growth parameters from mark-recapture tagging data. Evaluation of the performance was done by applying each estimation technique to: 1) simulated error-free mark-recapture tagging data and comparing the estimated versus known simulated growth parameters; 2) simulated mark-recapture data considering individual growth variability, measurement error, different length-at-capture distributions, as well as different sample sizes and comparing the estimated versus known simulated growth parameters; and 3) mark-recapture data of 14 North Atlantic elasmobranch stocks and discussing the estimated growth parameters with respect to biological plausibility and conventional length-at-age data. All investigated estimation techniques returned the known simulated growth parameters when the data is without error. When errors are introduced in the simulation, Bayesian implementations of Fabens' (BFa) and Francis’ (BFr) methods were found to be most reliable. For the observed mark-recapture data only BFa gave biologically plausible results for all 14 elasmobranch stocks. Overall, the results suggest that BFa is a reliable alternative to conventional length-at-age methods for estimating growth parameters, especially in data-limited situations which commonly occur with elasmobranchs. The only prior information needed is limited expert knowledge on maximum length in the population or stock in question. A user guide is provided to facilitate application of the method.

Spatiotemporal modeling of mature‐at‐length data using a sliding window approach

AbstractAssessing maturity status of fish and invertebrate species is important for understanding population dynamics with results (e.g., estimates of reproductive potential) often used to inform fisheries management strategies (e.g., the setting of minimum legal size requirements for fishing). Maturity rates may vary substantially across a population's range, as well as between years. In addition, maturity data are typically obtained from fisheries‐independent surveys that may be incomplete (or missing) from year to year. Here we propose a spatial generalized linear mixed model (GLMM) framework for maturity data that includes spatially correlated random effects to address variations in space, and a sliding window approach to deal with unbalanced maturity data in both space and time. We demonstrate, with both real data and a simulation study, that this combined approach results in unbiased estimates of important growth parameters. Results of using our spatial GLMM framework with Greenland halibut (Rheinhardtius hippoglossoides) mature‐at‐length data from surveys of the eastern Canadian Arctic show that females mature at a much larger size than do males. The length at which 50% of the stock is mature () is found to be higher in Baffin Bay compared to Davis Strait, and a declining trend in the in recent years is revealed for both sexes. Our proposed methodology extends far beyond our current application in being useful for analyzing unbalanced spatiotemporal data from an array of diverse scientific fields.

Estimation of Leaf Area Index and Above-Ground Biomass of Winter Wheat Based on Optimal Spectral Index

Leaf area index (LAI) and above-ground biomass are both vital indicators for evaluating crop growth and development, while rapid and non-destructive estimation of crop LAI and above-ground biomass is of considerable significance for crop field management. Owing to the advantages of repeatable and high-throughput observations, spectral technology provides a feasible method for obtaining LAI and above-ground biomass of crops. In the present study, the spectral, LAI and above-ground biomass data of winter wheat were collected, and 7 species (14 in total) were calculated based on the original and first-order differential spectrum correlation spectral indices with LAI. Then, the correlation matrix method was used for correlation with LAI. The optimal wavelength combination was extracted, and the results were calculated as the optimal spectral index related to LAI. The calculation process of the optimal spectral index related to above-ground biomass was the same as that aforementioned. Finally, the optimal spectral index was divided into three groups of model input variables, winter wheat LAI and above-ground biomass estimation models were constructed using support vector machine (SVM), random forest (RF) and a back propagation neural network (BPNN), and the models were verified. The results show that the correlation coefficient between the highest of the optimal spectral indices, the LAI, and the above-ground biomass of winter wheat exceeded 0.6, and the correlation was good. The methods for establishing the optimal estimation models for LAI and above-ground biomass of winter wheat are all modeling methods in which the input variables are the combination of the first-order differential spectral index (combination 2) and RF. The R2 of the LAI estimation model validation set was 0.830, the RMSE was 0.276, and the MRE was 6.920; the R2 of the above-ground biomass estimation model validation set was 0.682, RMSE was 235.016, MRE was 4.336, and the accuracies of both models were high. The present research results can provide a theoretical basis for crop monitoring based on spectral technology and provide an application reference for the rapid estimation of crop growth parameters.

Exploitation of striped snakehead (Channa striata) in Sempor Reservoir, Central Java, Indonesia: A proposed conservation strategy

Abstract. Setyaningrum N, Lestari W, Krismono, Nuryanto A. 2022. Exploitation of striped snakehead (Channa striata) in Sempor Reservoir, Central Java, Indonesia: A proposed conservation strategy. Biodiversitas 23: 3584-3592. Striped snakehead (Channa striata) has important economic value in freshwater systems, including Sempor Reservoir in Indonesia, where increases in catch sizes have resulted in a declining population. In this study, we determined its population size based on abundance and distribution of length and assessed the rate of exploitation based on estimated growth and mortality rates to determine a conservation strategy in Sempor Reservoir. The study was undertaken from March to October 2020. The method used was a purposive random sampling survey. Fish samples were taken from five stations with different land uses. The estimated growth, mortality, and exploitation rates were analyzed by Pauly's model using FISAT II. Channa striata abundance data were analyzed using a Kruskal-Wallis test. The results showed that the highest abundance of C. striata at the KW station was almost three times higher than at the BK station. The average size of the gonads at first maturity was 277.4 mm in females and 284 mm in males. The estimated growth parameters indicated an asymptotic length (L?) of 409.5 mm. An exploitation rate of 0.74 was classified as overfishing. The proposed conservation strategy is to limit the number of catches by as much as 44% and prohibit the catching of individuals with a length of 230-349 mm. Kedungwringin Station was defined as a reference area with the largest abundance and complete size distribution, namely, the pre-reproduction, reproduction, and post-reproduction stages. Bangkong Station was defined as a spawning ground because there were many fish in the reproductive stage and Sempor River Station was the nursery ground with mostly juvenile fish. These two sites must be protected for sustainable striped snakehead populations in the river and reservoir.

Age and growth of skipjack tuna (Katsuwonus pelamis) in the western equatorial Atlantic based on dorsal spines analysis

The skipjack tuna (Katsuwonus pelamis) is a migratory pelagic fish occurring in all tropical and subtropical oceans of the world. Due to its economic importance and the unbridled increase in fishing efforts, stocks may collapse if this resource is not managed properly. The present study aimed to estimate growth parameters from different growth models based on annual rings from the dorsal spines of skipjack tuna caught in the western equatorial Atlantic. The first dorsal spine of each individual was extracted to produce cross-sections with 0.6 to 0.8 mm in thickness. We used a multi-model approach to select the best growth model based on the Akaike information criterion (AIC). Two hundred seventy individuals were analyzed, with an average length of 49.58 ± 7.72 cm. The von Bertalanffy growth model had the best fit to the data, but the Gompertz and Logistic models also had essential support. Average asymptotic length () was estimated to be 114.05 and 102.63 cm for observed and back-calculated data, respectively. The dorsal spines are indeed efficient tools for estimating growth parameters and multi-model inference is a novel approach for adjusting discrepancies that likely result from a single-model approach.

Estimating somatic growth of fishes from maximum age or maturity

Growth in body size is a key life-history trait that has coevolved and is interlinked with maturation, maximum age, mortality, generation time, and the intrinsic rate of population growth. Growth parameters are therefore required inputs in the majority of assessment models used in conservation or fisheries management. However, because of the difficulties involved in the proper aging of individuals, growth parameters are unknown for the vast majority of species. Here, two new data-limited methods are presented to estimate somatic growth from maximum length combined with either length or age at maturation or with maximum age. A comparison with existing growth parameters of fishes (Actinopterygii and Elasmobranchii) shows that the estimates of the new methods fall within the range of established methods. The new methods apply to species with indeterminate growth, such as fishes or invertebrates, and were used here to produce the first growth parameter estimates for 110 species of fishes.

An assessment of sampling approaches for estimating growth from fishery-dependent biological samples

Abstract Accuracy of fish growth estimates depends greatly on how samples are collected. A total of three common sampling strategies are random, fixed otolith sampling (FOS), and proportional otolith sampling (POS). Random sampling is inefficient and rarely random. While POS has been shown to produce more accurate estimates of growth compared to FOS under ideal conditions, it is unclear how variables such as sample size, fishery selectivity, and fishing mortality influence sampling bias. Simulated age-at-length observations from two tropical deepwater species were used to evaluate the accuracy of von Bertalanffy growth parameter estimates comparing FOS and POS for a fast-growing, short-lived fish (Prisitipomoides auricilla) and a slow-growing, long-lived fish (Etelis coruscans). A total of 24 scenarios were tested to examine the influence of sample size, minimum size selected in the fishery, fishery exploitation rates, and supplemental sampling on growth parameter estimates. Furthermore, tests were applied to real fishery age–length observations for P. auricilla. POS consistently performed better than FOS, especially when the catch was representative of the population. However, FOS performed better when catch was not representative. This research demonstrates the importance of considering effects of fishery selectivity, fishing mortality, and sample size on sampling strategy and provides a tool to select an appropriate approach.