Growth parameters for Lates niloticus (L.), Bagrus docmak (Forsskal), Oreochromis niloticus (L.), Clarias gariepinus (Burchell) and Synodontis species derived from tag returns

In a tagging experiment carried out in the Kenyan waters of Lake Victoria, an annual growth increment of 29 cm yr was obtained for Lates niloticus (L.). Growth parameters obtained using the von Bertalanffy model on the growth curve fitted by eye were L (inf.) = 122 cm yr and k = 0.26 yr. Data for other species tagged were inadequate to obtain meaningful results.

The impact of physical processes on algal growth

Mixing and transport processes in surface waters strongly influence the structure of aquatic ecosystems. The impact of mixing on algal growth is species-dependent, affecting the competition among species and acting as a selective factor for the composition of the biocoenose. Were it not for the ever-changing ”aquatic weather”, the composition of pelagic ecosystems would be relatively simple. Probably just a few optimally adapted algal species would survive in a given water-body. In contrast to terrestrial ecosystems, in which the spatial heterogeneity is primarily responsible for the abundance of niches, in aquatic systems (especially in the pelagic zone) the niches are provided by the temporal structure of physical processes. The latter are discussed in terms of the relative sizes of physical versus biological time-scales. The relevant time-scales of mixing and transport cover the range between seconds and years. Correspondingly, their influence on growth of algae is based on different mechanisms: rapid changes are relevant for the fast biological processes such as nutrient uptake and photosynthesis, and the slower changes are relevant for the less dynamic processes such as growth, respiration, mineralization, and settling of algal cells. Mixing time-scales are combined with a dynamic model of photosynthesis to demonstrate their influence on algal growth.

Estimation of the growth curve parameters in Macrobrachium rosenbergii

Growth is one of the most important characteristics of cultured species. The objective of this study was to determine the fitness of linear, log linear, polynomial, exponential and Logistic functions to the growth curves of Macrobrachium rosenbergii obtained by using weekly records of live weight, total length, head length, claw length, and last segment length from 20 to 192 days of age. The models were evaluated according to the coefficient of determination (R2), and error sum off square (ESS) and helps in formulating breeders in selective breeding programs. Twenty full-sib families consisting 400 PLs each were stocked in 20 different hapas and reared till 8 weeks after which a total of 1200 animals were transferred to earthen ponds and reared up to 192 days. The R2 values of the models ranged from 56 – 96 in case of overall body weight with logistic model being the highest. The R2 value for total length ranged from 62 to 90 with logistic model being the highest. In case of head length, the R2 value ranged between 55 and 95 with logistic model being the highest. The R2 value for claw length ranged from 44 to 94 with logistic model being the highest. For last segment length, R2 value ranged from 55 – 80 with polynomial model being the highest. However, the log linear model registered low ESS value followed by linear model for overall body weight while exponential model showed low ESS value followed by log linear model in case of head length. For total length the low ESS value was given by log linear model followed by logistic model and for claw length exponential model showed low ESS value followed by log linear model. In case of last segment length, linear model showed lowest ESS value followed by log linear model. Since, the model that shows highest R2 value with low ESS value is generally considered as the best fit model. Among the five models tested, logistic model, log linear model and linear models were found to be the best models for overall body weight, total length and head length respectively. For claw length and last segment length, log linear model was found to be the best model. These models can be used to predict growth rates in M. rosenbergii. However, further studies need to be conducted with more growth traits taken into consideration

A note on the von Bertalanffy growth function concerning the allocation of surplus energy to reproduction

We propose an extended form of the von Bertalanffy growth function (VBGF), where the allocation of surplus energy to reproduction is considered. Any function can be used in our model to describe the ratio of energy allocation for reproduction to that for somatic growth. As an example, two models for energy allocation were derived: a step-function and a logistic function. The extended model can jointly describe growth in adult and juvenile stages. The change in growth rate between the two stages can be either gradual or steep; the latter gives a biphasic VBGF. The results of curve fitting indicated that a consideration of reproductive energy is meaningful for model extension. By controlling parameter values, our comprehensive model gives various growth curve shapes ranging from indeterminate to determinate growth. An increase in the number of parameters is unavoidable in practical applications of this new model. Additional information on reproduction will improve the reliability of model estimates.

Growth and survival of sockeye salmon (Oncorhynchus nerka) from Karluk Lake and River, Alaska, in relation to climatic and oceanic regimes and indices, 1922–2000

We examined whether the relationship between climate and salmon production was linked through the effect of climate on the growth of sockeye salmon (Oncorhynchus nerka) at sea. Smolt length and juvenile, immature, and maturing growth rates were estimated from increments on scales of adult sockeye salmon that returned to the Karluk River and Lake system on Kodiak Island, Alaska, over 77 years, 1924–2000. Survival was higher during the warm climate regimes and lower during the cool regime. Growth was not correlated with survival, as estimated from the residuals of the Ricker stock-recruitment model. Juvenile growth was correlated with an atmospheric forcing index and immature growth was correlated with the amount of coastal precipitation, but the magnitude of winter and spring coastal downwelling in the Gulf of Alaska and the Pacific Northwest atmospheric patterns that influence the directional bifurcation of the Pacific Current were not related to the growth of Karluk sockeye salmon. However, indices of sea surface temperature, coastal precipitation, and atmospheric circulation in the eastern North Pacific were correlated with the survival of Karluk sockeye salmon. Winter and spring precipitation and atmospheric circulation are possible processes linking survival to climate variation in Karluk sockeye salmon.

Interdecadal change in growth of sablefish (Anoplopoma fimbria) in the northeast Pacific Ocean

Errors in growth estimates can affect drastically the spawner-perrecruit threshold used to recommend quotas for commercial fish catches. Growth parameters for sablefish (Anoplopoma fimbria) in Alaska have not been updated for stock assessment purposes for more than 20 years, although aging of sablefish has continued. In this study, length-stratified data (1981–93 data from the annual longline survey conducted cooperatively by the Fisheries Agency of Japan and the Alaska Fisheries Science Center of the National Marine Fisheries Service) were updated and corrected for discovered sampling bias. In addition, more recent, randomly collected samples (1996–2004 data from the annual longline survey conducted by the Alaska Fisheries Science Center) were analyzed and new length-at-age and weight-at-age parameters were estimated. Results were similar between this analysis with length-at-age data from 1981 to 2004 and analysis with updated longline survey data through 2010; therefore, we used our initial results from analysis done with data through 2004. We found that, because of a stratified sampling scheme, growth estimates of sablefish were overestimated with the older data (1981–93), and growth parameters used in the Alaskan sablefish assessment model were, thus, too large. In addition, a comparison of the bias-corrected 1981–93 data and the 1996–2004 data showed that, in more recent years, sablefish grew larger and growth differed among regions. The updated growth information improves the fit of the data to the sablefish stock assessment model with biologically reasonable results. These findings indicate that when the updated growth data (1996–2004) are used in the existing sablefish assessment model, estimates of fishing mortality increase slightly and estimates of female spawning biomass decrease slightly. This study provides evidence of the importance of periodically revisiting biological parameter estimates, especially as data accumulate, because the addition of more recent data often will be more biologically realistic. In addition, it exemplifies the importance of correcting biases from sampling that may contribute to erroneous parameter estimates.

Estimating consumption rates of juvenile sandbar sharks (Carcharhinus plumbeus) in Chesapeake Bay, Virginia, using a bioenergetics model*

Using a bioenergetics model, we estimated daily ration and seasonal prey consumption rates for six age classes of juvenile sandbar sharks (Carcharhinus plumbeus) in the lower Chesapeake Bay summer nursery area. The model, incorporating habitat and species-specific data on growth rates, metabolic rate, diet composition, water temperature (range 16.8−27.9°C), and population structure, predicted mean daily rations between 2.17 ±0.03 (age-0) and 1.30 ±0.02 (age-5) % body mass/day. These daily rations are higher than earlier predictions for sandbar sharks but are comparable to those for ecologically similar shark species. The total nursery population of sandbar sharks was predicted to consume ~124,000 kg of prey during their 4.5 month stay in the Chesapeake Bay nursery. The predicted consumption rates support the conclusion that juvenile sandbar sharks exert a lesser top-down effect on the Chesapeake Bay ecosystem than do teleost piscivores and hu

Growth and length-weight parameters of Pacific mackerel (Scomber japonicus) in the Gulf of Guayaquil, Ecuador

The seasonally oscillating growth parameters and length-weight relationships for Scomber japonicus caught in the Gulf of Guayaquil, Ecuador, were determined based on length-frequency data from 1989 to 1996, using the FiSAT software package of Gayanilo et al. (1996). Estimates of growth parameters are in general agreement with previous studies on the same species. Results also imply that the growth of Scomber japonicus slows down during the cold season by approximately 50% with respect to the average growth. The mean value of the power b is significantly larger than 3, indicating that the model of allometric growth should be used for the length-weight relationship and calculation of the condition factor.

Estimates of growth and comparisons of growth rates determined from length- and age-based models for populations of purple wrasse (Notolabrus fucicola)

Growth of a temperate reefa-ssociated fish, the purple wrasse (Notolabrus fucicola), was examined from two sites on the east coast of Tasmania by using age- and length-based models. Models based on the von Bertalanffy growth function, in the standard and a reparameterized form, were constructed by using otolith-derived age estimates. Growth trajectories from tag-recaptures were used to construct length-based growth models derived from the GROTAG model, in turn a reparameterization of the Fabens model. Likelihood ratio tests (LRTs) determined the optimal parameterization of the GROTAG model, including estimators of individual growth variability, seasonal growth, measurement error, and outliers for each data set. Growth models and parameter estimates were compared by bootstrap confidence intervals, LRTs, and randomization tests and plots of bootstrap parameter estimates. The relative merit of these methods for comparing models and parameters was evaluated; LRTs combined with bootstrapping and randomization tests provided the most insight into the relationships between parameter estimates. Significant differences in growth of purple wrasse were found between sites in both length- and age-based models. A significant difference in the peak growth season was found between sites, and a large difference in growth rate between sexes was found at one site with the use of length-based models.

Maximum likelihood estimation of mortality and growth with individual variability from multiple length-frequency data

We consider estimation of mortality rates and growth parameters from length-frequency data of a fish stock and derive the underlying length distribution of the population and the catch when there is individual variability in the von Bertalanffy growth parameter L∞. The model is flexible enough to accommodate 1) any recruitment pattern as a function of both time and length, 2) length-specific selectivity, and 3) varying fishing effort over time. The maximum likelihood method gives consistent estimates, provided the underlying distribution for individual variation in growth is correctly specified. Simulation results indicate that our method is reasonably robust to violations in the assumptions. The method is applied to tiger prawn data (Penaeus semisulcatus) to obtain estimates of natural and fishing mortality.

Effects of fishing on growth traits: a simulation analysis

Abstract—Fisheries often target individuals based on size. Size-selective fishing can create selection differentials on life-history traits and, when those traits have a genetic basis, may cause evolution. The evolution of life history traits affects potential yield and sustainability of fishing, and it is therefore an issue for fishery management. Yet fishery managers usually disregard the possibility of evolution, because little guidance is available to predict evolutionary consequences of management strategies. We attempt to provide some generic guidance. We develop an individual-based model of a population with overlapping generations and continuous reproduction. We simulate model populations under size-selective fishing to generate and quantify selection differentials on growth. The analysis comprises a variety of common life-history and fishery characteristics: variability in growth, correlation between von Bertalanffy growth parameters (K and L∞), maturity rate, natural mortality rate (M), M/K ratio, duration of spawning season, fishing mortality rate (F), maximum size limit, slope of selectivity curve, age at 50% selectivity, and duration of fishing season. We found that each characteristic affected the magnitude of selection differentials. The most vulnerable stocks were those with a short spawning or fishing season. Under almost all life-history and fishery characteristics examined, selection differentials created by realistic fishing mortality rates are considerable.

Growth, mortality, and hatchdate distributions of larval and juvenile spotted seatrout (Cynoscion nebulosus) in Florida Bay, Everglades National Park

Life history aspects of larval and, mainly, juvenile spotted seatrout (Cynoscion nebulosus) were studied in Florida Bay, Everglades National Park, Florida. Collections were made in 1994−97, although the majority of juveniles were collected in 1995. The main objective was to obtain life history data to eventually develop a spatially explicit model and provide baseline data to understand how Everglades restoration plans (i.e. increased freshwater flows) could influence spotted seatrout vital rates. Growth of larvae and juveniles (<80 mm SL) was best described by the equation loge standard length = –1.31 + 1.2162 (loge age). Growth in length of juveniles (12–80 mm SL) was best described by the equation standard length = –7.50 + 0.8417 (age). Growth in wet weight of juveniles (15–69 mm SL) was best described by the equation loge wet-weight = –4.44 + 0.0748 (age). There were no significant differences in juvenile growth in length of spotted seatrout in 1995 between three geographical subdivisions of Florida Bay: central, western, and waters adjacent to the Gulf of Mexico. We found a significant difference in wet-weight for one of six cohorts categorized by month of hatchdate in 1995, and a significant difference in length for another cohort. Juveniles (i.e. survivors) used to calculate weekly hatchdate distributions during 1995 had estimated spawning times that were cyclical and protracted, and there was no correlation between spawning and moon phase. Temperature influenced otolith increment widths during certain growth periods in 1995. There was no evidence of a relationship between otolith growth rate and temperature for the first 21 increments. For increments 22–60, otolith growth rates decreased with increasing age and the extent of the decrease depended strongly in a quadratic fashion on the temperature to which the fish was exposed. For temperatures at the lower and higher range, increment growth rates were highest. We suggest that this quadratic relationship might be influenced by an environmental factor other than temperature. There was insufficient information to obtain reliable inferences on the relationship of increment growth rate to salinity.

Age determination and growth of the night shark (Carcharhinus signatus) off the northeastern Brazilian coast

Age and growth of the night shark (Carcharhinus signatus) from areas off northeastern Brazil were determined from 317 unstained vertebral sections of 182 males (113–215 cm total length [TL]), 132 females (111.5–234.9 cm) and three individuals of unknown sex (169–242 cm). Although marginal increment (MI) analysis suggests that band formation occurs in the third and fourth trimesters in juveniles, it was inconclusive for adults. Thus, it was assumed that one band is formed annually. Births that occur over a protracted period may be the most important source of bias in MI analysis. An estimated average percent error of 2.4% was found in readings for individuals between two and seventeen years. The von Bertalanffy growth function (VBGF) showed no significant differences between sexes, and the model derived from back-calculated mean length at age best represented growth for the species (L∞=270 cm, K=0.11/yr, t0=–2.71 yr) when compared to the observed mean lengths at age and the Fabens’ method. Length-frequency analysis on 1055 specimens (93–260 cm) was used to verify age determination. Back-calculated size at birth was 66.8 cm and maturity was reached at 180–190 cm (age 8) for males and 200–205 cm (age ten) for females. Age composition, estimated from an age-length key, indicated that juveniles predominate in commercial catches, representing 74.3% of the catch. A growth rate of 25.4 cm/yr was estimated from birth to the first band (i.e. juveniles grow 38% of their birth length during the first year), and a growth rate of 8.55 cm/yr was estimated for eight- to ten-year-old adults.

Modeling red sea urchin (Strongylocentrotus franciscanus) growth using six growth functions

The growth of red sea urchins (Strongylocentrotus franciscanus) was modeled by using tag-recapture data from northern California. Red sea urchins (n=211) ranging in test diameter from 7 to 131 mm were examined for changes in size over one year. We used the function Jt+1 = Jt + f(Jt) to model growth, in which Jt is the jaw size (mm) at tagging, and Jt+1 is the jaw size one year later. The function f(Jt), represents one of six deterministic models: logistic dose response, Gaussian, Tanaka, Ricker, Richards, and von Bertalanffy with 3, 3, 3, 2, 3, and 2 minimization parameters, respectively. We found that three measures of goodness of fi t ranked the models similarly, in the order given. The results from these six models indicate that red sea urchins are slow growing animals (mean of 7.2 ±1.3 years to enter the fishery). We show that poor model selection or data from a limited range of urchin sizes (or both) produces erroneous growth parameter estimates and years-to-fishery estimates. Individual variation in growth dominated spatial variation at shallow and deep sites (F=0.246, n=199, P=0.62). We summarize the six models using a composite growth curve of jaw size, J, as a function of time, t: J = A(B – e–Ct) + Dt, in which each model is distinguished by the constants A, B, C, and D. We suggest that this composite model has the flexibility of the other six models and could be broadly applied. Given the robustness of our results regarding the number of years to enter the fishery, this information could be incorporated into future fishery management plans for red sea urchins in northern California.

Scales of spatial variation in demography of a large coral-reef fish: an exception to the typical model?

Spatial variation in demographic parameters of the red throat emperor (Lethrinus miniatus) was examined among 12 coral reefs in three geographic regions (Townsville, Mackay, and Storm Cay) spanning over 3° of latitude of the Great Barrier Reef, Australia. Estimates of demographic parameters were based on age estimates from counts of annuli in whole otoliths because there was no significant difference in age estimates between whole and sectioned otoliths. There were significant regional differences in age structures, rates of somatic and otolith growth, and total mortality. The Townsville region was characterized by the greatest proportion of older fish, the smallest maximum size, and the lowest rates of otolith growth and total mortality. In contrast the Mackay region was characterized by the highest proportion of younger fish, the largest maximum size, and the highest rates of otolith growth and total mortality. Demographic parameters for the Storm Cay region were intermediate between the other two regions. Historic differences in fishing pressure and regional differences in productivity are two alternative hypotheses given to explain the regional patterns in demographic parameters. All demographic parameters were similar among the four reefs within each region. Thus, subpopulations with relatively homogeneous demographic parameters occurred on scales of reef clusters. Previous studies, by contrast, have found substantial between-reef variation in demographic parameters within regions. Thus spatial variation in demographic parameters for L. miniatus may differ from what is assumed typical for a coral-reef fish metapopulation.