Ontogenetic Development of Growth Rates in Larval Pacific Herrings, Clupea harengus pallasi, Measured with RNA–DNA Ratios in the Strait of Georgia, British Columbia

1988 ◽  
Vol 45 (8) ◽  
pp. 1422-1429 ◽  
Author(s):  
S. M. C. Robinson ◽  
D. M. Ware
Keyword(s):  
Growth Rate ◽  
Growth Rates ◽  
Clupea Harengus ◽  
Critical Ratio ◽  
Strait Of Georgia ◽  
Frequency Distributions ◽  
Clupea Harengus Pallasi ◽  
In Captivity ◽  
The Mean ◽  
Mass Starvation

During the spring of 1986, a cohort of Pacific herring, Clupea harengus pallasi, larvae was sampled for 36 d in the Strait of Georgia to measure growth rates using RNA–DNA ratios for individual larvae. Concurrent with the field study, a population of herring larvae was starved from hatching in captivity for comparison with those caught in the field. The mean RNA–DNA ratio at hatching for the starved larvae was close to 2 but it quickly rose to 3.4 by age 4 d. The mean RNA–DNA ratio subsequently dropped back to 2 and below by age 8 d, presumably reflecting the exhaustion of the endogenous food supply of the yolk sac. The mean RNA–DNA ratio at the calculated point-of-no-return was 2.06 which was very similar to the zero protein growth rate or what we define as the "critical ratio." Herring larvae from the field generally showed an increase in the RNA–DNA ratio over the 36 d from approximately 2 to 7 although the first 18 d showed more variation than the latter. There was no evidence of mass starvation ("critical period") for the 1986 year class but there was a noticeable drop in the growth rate during the change to exogenous feeding. We suggest that starvation probably only directly affected the developing larvae during a window of about 11 d. Frequency distributions of the RNA–DNA ratios are shown for larvae over time.

The Age Structure and Growth Dynamics of Young-Of-The-Year Bass, Dicentrarchus Labrax, Populations

1991 ◽  
Vol 71 (4) ◽  
pp. 799-810 ◽  
Author(s):  
S. Jennings ◽  
J. E. Lancaster ◽  
J. S. Ryland ◽  
S. E. Shackley
Keyword(s):  
Growth Rate ◽  
Growth Rates ◽  
Dicentrarchus Labrax ◽  
Growth Dynamics ◽  
Frequency Distributions ◽  
South Wales ◽  
Nursery Habitats ◽  
The Mean ◽  
Young Of The Year ◽  
Time Of Year

Back-calculated egg fertilization (spawned) dates and growth rates for young-of-the-year bass, Dicentrarchus labrax (L), captured from Loughor Estuary, Oxwich Bay and Ogmore Estuary, south Wales, UK, during 1988 and 1989 were compared. Spawned date frequency distributions indicated that the bass spawning season began in late February and continued until early June in 1988 and early July in 1989.There were no significant differences in the frequency distributions of back-calculated spawned dates for the bass populations, between either sites or years, which suggested that any variations in growth rates were attributable to characteristics of their respective environments. Growth rates were determined for bass cohorts resulting from early, midor late-season spawnings at Oxwich and Loughor in 1988 and Oxwich, Loughor and Ogmore in 1989. There were only slight intra-annual differences between the mean growth rates of bass cohorts at the same site, suggesting that bass from early cohorts would be larger at any given time of year. In 1989, growth was considerably faster at Oxwich and Loughor than at Ogmore, where food supply was considered limiting. However, between-site variations in growth rate were small in comparison with inter-annual differences. The faster growth rates observed at Loughor and Oxwich in 1989 were attributed to higher water temperatures.Relationships between growth rate and subsequent survival of young-of-the-year bass, and the relative importance of estuaries as nursery habitats for juvenile bass, are discussed.

scholarly journals Ultrasound Surveillance of Ectatic Abdominal Aortas

2008 ◽  
Vol 90 (6) ◽  
pp. 477-482 ◽  
Author(s):  
S Devaraj ◽  
SR Dodds
Keyword(s):  
Growth Rate ◽  
Growth Rates ◽  
Screening Programme ◽  
T Test ◽  
Aortic Aneurysms ◽  
Aortic Diameter ◽  
Ultrasound Screening ◽  
The Mean ◽  
Clinically Significant

INTRODUCTION Some studies have considered abdominal aortas of 2.6–2.9 cm diameter (ectatic aortas) at age 65 years as being abnormal and have recommended surveillance, whereas others have considered these normal and surveillance unnecessary. It is, therefore, not clear how to manage patients with an initial aortic diameter between 2.6–2.9 cm detected at screening. The aim of this study was to evaluate growth rates of ectatic aortas detected on initial ultrasound screening to determine if any developed into clinically significant abdominal aortic aneurysms (AAAs; > 5.0 cm) and clarify the appropriate surveillance intervals for these patients. PATIENTS AND METHODS Data were obtained from a prospective AAA screening programme which commenced in 1992. The group of patients with initial aortic diameters of 2.6–2.9 cm with a minimum of 1-year follow-up were included in this study (Group 2). This was further divided into two subgroups (Groups 3a and 3b) based on a minimum follow-up interval obtained from outcome analysis. Mean growth rate was calculated as change in aortic diameter with time. The comparison of growth rates in Groups 3a and 3b was performed using the t-test. The number and proportion of AAAs that expanded to ≥ 3.0 cm and ≥ 5.0 cm in diameter were also calculated. RESULTS Out of 999 patients with AAA ≥ 2.6 cm with minimum 1-year follow-up, 358 (36%) were classified as ectatic aortas (2.6–2.9 cm) at initial ultrasound screening with the mean growth rate of 1.69 mm/year (95% CI, 1.56–1.82 mm/year) with a mean follow-up of 5.4 years. Of these 358 ectatic aortas, 314 (88%) expanded into ≥ 3.0 cm, 45 (13%) expanded to ≥ 5.0 cm and only 8 (2%) expanded to ≥ 5.5 cm over a mean follow-up of 5.4 years (range, 1–14 years). No ectatic aortas expanded to ≥ 5.0 cm within the first 4 years of surveillance. Therefore, the minimum follow-up interval was set at 4 years and this threshold was then used for further analysis. The mean growth rate in Group 3a (< 5.0 cm at last scan) was 1.33 mm/year (95% CI, 1.23–1.44 mm/year) with a mean follow-up of 7 years compared to Group 3b (≥ 5.0 cm at last scan) with the mean growth rate of 3.33 mm/year (95% CI 3.05–3.61 mm/year) and a mean follow-up of 8 years. The comparison of mean growth rates between Groups 3a and 3b is statistically significant (t-test; T = 13.00; P < 0.001). CONCLUSIONS One-third of patients undergoing AAA screening will have ectatic aortas (2.6–2.9 cm) and at least 13% of these will expand to a size of ≥ 5.0 cm over a follow-up of 4–14 years. A threshold diameter of 2.6 cm for defining AAAs in a screening programme is recommended and ectatic aortas detected at age 65 years can be re-screened at 4 years after the initial scan. A statistically significant difference was found in the growth rates of ectatic aortas with minimum 4 years follow-up, expanding to ≥ 5.0 cm compared to those less than 5.0 cm at last surveillance scan. Further studies are required to test the hypothesis of whether growth rate over the first 4 years of surveillance will identify those who are most likely to expand to a clinically significant size (> 5.0 cm).

Alternative Harvest Strategies for Pacific Herring (Clupea harengus pallasi)

1988 ◽  
Vol 45 (5) ◽  
pp. 888-897 ◽  
Author(s):  
D. L. Hall ◽  
R. Hilborn ◽  
M. Stocker ◽  
C. J. Walters
Keyword(s):  
Management Strategies ◽  
Clupea Harengus ◽  
Pacific Herring ◽  
Harvest Rate ◽  
Strait Of Georgia ◽  
Clupea Harengus Pallasi ◽  
Current Management Strategy ◽  
Stock Recruitment ◽  
Spawning Biomass ◽  
Constant Escapement

A simulated Pacific herring (Clupea harengus pallasi) population is used to evaluate alternative management strategies of constant escapement versus constant harvest rate for a roe herring fishery. The biological parameters of the model are derived from data on the Strait of Georgia herring stock. The management strategies are evaluated using three criteria: average catch, catch variance, and risk. The constant escapement strategy provides highest average catches, but at the expense of increased catch variance. The harvest rate strategy is favored for its reduced variance in catch and only a slight decrease in mean catch relative to the fixed escapement strategy. The analysis is extended to include the effects of persistent recruitment patterns. Stock–recruitment analysis suggests that recruitment deviations are autocorrelated. Correlated deviations may cause bias in regression estimates of stock–recruitment parameters (overestimation of stock productivity) and increase in variation of spawning stock biomass. The latter effect favors the constant escapement strategy, which fully uses persistent positive recruitment fluctuations. Mean catch is depressed for the harvest rate strategy, since the spawning biomass is less often located in the productive region of the stock–recruitment relationship. The model is used to evaluate the current management strategy for Strait of Georgia herring. The strategy of maintaining a minimum spawning biomass reserve combines the safety of the constant escapement strategy and the catch variance reducing features of the harvest rate strategy.

Environmental Variation and Recruitment of Pacific Herring (Clupea harengus pallasi) in the Strait of Georgia

1985 ◽  
Vol 42 (S1) ◽  
pp. s174-s180 ◽  
Author(s):  
Max Stocker ◽  
Vivian Haist ◽  
David Fournier
Keyword(s):  
Environmental Variables ◽  
River Discharge ◽  
Clupea Harengus ◽  
Pacific Herring ◽  
Strait Of Georgia ◽  
Clupea Harengus Pallasi ◽  
Age Structured ◽  
Age Structured Model ◽  
The Relationship ◽  
Spawning Success

We used an age-structured model to estimate recruitment for the Strait of Georgia Pacific herring (Clupea harengus pallasi) population. The model used for herring is a version of the model described in Fournier and Archibald (1982. Can. J. Fish. Aquat. Sci. 39: 1195–1207), modified to include spawn survey information. Three structural assumptions are made to include the spawn data: (1) the form of the relationship between the actual spawn and the observed spawn, (2) the form of the relationship between escapement and actual spawn, and (3) the existence of a Ricker spawn–recruitment relationship, with a multiplicative environmental component. In order to determine which environmental factors had a significant effect on recruitment, we attempted to explain the residual variation from the Ricker curve with the environmental variables using exploratory correlations. Temperature, river discharge, sea level, and sunlight were examined. A multiplicative, environmental-dependent Ricker spawn–recruitment model was used to identify significant environmental variables. The model suggests a significant dome-shaped relationship between temperature and spawning success with an optimal temperature during larval stages resulting in maximum production of recruits. Also, increased spawning success is associated with increased summer river discharge. The significant environmental variables were included in the age-structured model in a stock–environment–recruitment relationship, and all model parameters were reestimated. The overall model fit improved only marginally with the inclusion of environmental variables, as indicated by the objective function value. However, the S–R component of the objective function dropped by 23% when environmental variables were included.

scholarly journals Growth Rate Variation and Larval Survival: Inferences from an Individual-Based Size-Dependent Predation Model

1993 ◽  
Vol 50 (1) ◽  
pp. 133-142 ◽  
Author(s):  
James A. Rice ◽  
Thomas J. Miller ◽  
Kenneth A. Rose ◽  
Larry B. Crowder ◽  
Elizabeth A. Marschall ◽  
...  
Keyword(s):  
Growth Rate ◽  
Growth Rates ◽  
Individual Variability ◽  
Individual Growth ◽  
Rate Variation ◽  
High Survival ◽  
Initial Growth ◽  
Size Dependent ◽  
The Mean ◽  
Selection For

We used an individual-based Monte Carlo simulation model to explore how changes in the mean and variance of growth rates of individuals in a larval fish cohort interact with size-dependent predation to affect the number and characteristics of individual survivors. Small changes in initial cohort mean growth rate can change survival over the first 60 d of life 10-to 30-fold. But when variance in growth rate among individuals is high, survival can be substantially higher than expected from the initial mean cohort growth rate. Selection for faster-growing individuals becomes stronger with increasing variance and increasing predation rate. In some cases, > 80% of the survivors may come from the upper 25% of the initial growth rate distribution, and the mean growth rate of the survivors may exceed twice the initial mean growth rate. When individual growth rates change from day to day rather than remaining constant, the contribution of atypical individuals is accentuated even further. Counterintuitively, most of the selection for faster-growing individuals happens only after the majority of mortality has already taken place. These results suggest that interactions between individual variability and selective mortality may have important cohort-level implications for survival in fishes.

Factors Affecting the Distribution, Abundance, and Measurement of Pacific Herring (Clupea harengus pallasi) Spawn

1987 ◽  
Vol 44 (6) ◽  
pp. 1181-1194 ◽  
Author(s):  
D. E. Hay ◽  
A. R. Kronlund
Keyword(s):  
Survey Methods ◽  
Abiotic Factors ◽  
Early Years ◽  
Clupea Harengus ◽  
Pacific Herring ◽  
Biological Factors ◽  
Factors Affecting ◽  
Clupea Harengus Pallasi ◽  
The Mean ◽  
Stock Abundance

Records of the date, location, and magnitude of Pacific herring (Clupea harengus pallasi) spawnings in British Columbia, collected since 1928, were compiled and analysed. In the early years of spawn surveys, adjacent spawnings were often reported as single events. Gradually, this practice has changed so that each spawning has a separate record. As a consequence of this change in methods, the mean length of spawnings has decreased in recent years but the total numbers of records has increased. Estimates of mean spawning width and intensity have also changed, partly due to changing survey methods as well as changing spawning distributions. A spawn abundance index is developed to account for these temporal changes. Abiotic factors affecting the distribution and abundance of spawn deposition include sea surface temperatures and the fishery. Biological factors affecting spawn distribution and abundance are not as well defined, but it is shown that in some situations, spawn dimensions may change as a function of stock abundance.

Growth and Maturation of Pacific Herring (Clupea harengus pallasi) in the Strait of Georgia

1985 ◽  
Vol 42 (S1) ◽  
pp. s138-s146 ◽  
Author(s):  
V. Haist ◽  
M. Stocker
Keyword(s):  
Surface Temperature ◽  
Sea Surface Temperature ◽  
Clupea Harengus ◽  
Sea Surface ◽  
Pacific Herring ◽  
Juvenile Growth ◽  
Strait Of Georgia ◽  
Surplus Energy ◽  
Clupea Harengus Pallasi ◽  
Stock Biomass

Juvenile growth rate, adult surplus energy, and the maturation schedule for the Strait of Georgia Pacific herring (Clupea harengus pallasi) stock were investigated over the period 1950–81. The variance in weight at age 2 is largely accounted for by juvenile abundance and sea surface temperature, indicating density-dependent juvenile growth moderated by environmental factors. Density and environmental factors have been equally important in moderating juvenile growth. Yearly variation in maturation of 3-yr-old herring is related to their average length; however, in two of the eight years studied the 3-yr-olds matured at considerably smaller sizes. The variance in adult surplus energy (growth plus gonad production) was largely accounted for by body weight, adult biomass, and sea surface temperature. A dome-shaped relationship between surplus energy and biomass was indicated, suggesting that over a broad range of population size, adult surplus energy is not density dependent. The relationship of sea surface temperature to both juvenile growth and adult surplus energy was quadratic with an optimum value. Recruitment biomass has been a relatively larger component than adult production of total stock growth, particularly during the period of high fishing intensity. This resulted in large fluctuations in stock biomass; in recent years, with lower fishing intensity, adult production has been a larger component of stock growth, and the stock biomass has become more stable.

scholarly journals The Growth Rate Of Verruca Stroemia (O. Müller)

1958 ◽  
Vol 37 (2) ◽  
pp. 427-433 ◽  
Author(s):  
H. Barnes
Keyword(s):  
Growth Rate ◽  
Growth Rates ◽  
Specific Growth ◽  
Maximum Size ◽  
Rhythmic Pattern ◽  
The Mean ◽  
Rhythmic Growth ◽  
Specific Growth Rates ◽  
High Level ◽  
Balanus Balanoides

Data are presented on the growth rate of Verruca stroemia under natural conditions and when exposed continuously and cleaned repeatedly. Several series exposed at different times of the year were followed.Rapid growth takes place (under raft conditions) following settlement; the maximum size is virtually reached in one season's growth between spring and early winter. There is little growth in midwinter.Differences between the mean specific growth rates of the various series can be ascribed to differences in the availability of food.The question is discussed as to whether there is any seasonal rhythm; the evidence indicates that no marked rhythmic pattern of growth exists.Observations on deep-water populations would be of value for comparison and to unmask any relatively weak rhythmic growth.The mean specific growth rates at half their maximum size are compared for several species—Balanus balanoides, B. crenatus, B. balanus, Chthamalus stellatus and Verruca stroemia; it is similar for all species except Chthamalus stellatus. The high level barnacle may require stimulation such as is provided by wave action to elicit full metabolic activity.

On the Age and Growth Rate of Giant Cacti: Radiocarbon Dating of the Spines of Cardon (Pachycereus Pringlei)

Radiocarbon ◽  
2016 ◽  
Vol 58 (3) ◽  
pp. 479-490 ◽  
Author(s):  
Mariana Delgado-Fernández ◽  
Pedro P Garcillán ◽  
Exequiel Ezcurra
Keyword(s):  
Growth Rate ◽  
Growth Rates ◽  
Annual Growth ◽  
Age And Growth ◽  
Limiting Factor ◽  
Annual Growth Rate ◽  
Columnar Cacti ◽  
Rate Versus ◽  
The Mean ◽  
Pachycereus Pringlei

AbstractAge estimation has been a limiting factor in the study of giant columnar cacti. In order to test the feasibility of using radiocarbon methods to estimate the age of the giant cardon cacti (Pachycereus pringlei), we selected six sites spanning the latitudinal and precipitation range of the species in the Baja California peninsula. In each site, we selected four individuals of different heights and sampled a spine from the lowest areole in the stem. The age of the spine was estimated using 14C dating, and the mean annual growth rate of the plant was calculated dividing the height of the lead shoot by the plant’s age. Mean annual growth rate was 0.098 m/yr, with values varying between 0.03 and 0.23 m/yr. Within the range of plants sampled, mean annual growth rates were significantly correlated with the height of the plant (r2=0.82, P<0.0001), and no other site-specific variable such as precipitation or latitude was a significant predictor of mean annual growth rates. A model integrating mean growth rate versus height showed that relatively small differences in growth rates between plants accumulate during the plants’ lifetime, so that plants of similar size may have very different ages. We conclude that 14C dating provides a robust method to explore the growth and demography of columnar cacti.

Are Growth Parameters Estimated from Tagging and Age–Length Data Comparable?

1988 ◽  
Vol 45 (6) ◽  
pp. 936-942 ◽  
Author(s):  
R. I. C. C. Francis
Keyword(s):  
Growth Rate ◽  
Growth Rates ◽  
Growth Parameters ◽  
Growth Models ◽  
Maximum Length ◽  
Fish Growth ◽  
Data Sets ◽  
Von Bertalanffy ◽  
Length Data ◽  
The Mean

The two most common ways of estimating fish growth use age–length data and tagging data. It is shown that growth parameters estimated from these two types of data have different meanings and thus are not directly comparable. In particular, the von Bertalanffy parameter l∞ means asymptotic mean length at age for age–length data, and maximum length for tagging data, when estimated by conventional methods. New parameterizations are given for the von Bertalanffy equation which avoid this ambiguity and better represent the growth information in the two types of data. The comparison between growth estimates from these data sets is shown to be equivalent to comparing the mean growth rate of fish of a given age with that of fish of length equal to the mean length at that age. How much these growth rates may differ in real populations remains unresolved: estimates for two species of fish produced markedly different results, neither of which could be reproduced using growth models. Existing growth models are shown to be inadequate to answer this question.

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