The degree of error can be substantial in some cases, and appears to explain many reported cases of Lee's Phenomenon. Such a systematic variation implies that growth backcalculations made with any of the traditional equations (eg- regression, Fraser-Lee or those of Francis (1990)) will tend to underestimate previous lengths at age, with the degree of error varying with the range of growth rates that are present in the population. However, many studies have demonstrated that otoliths of slow-growing fish tend to be larger and heavier than those of fast-growing fish of the same size, whether at the daily or yearly scale. Conversely, if the relationship is nonlinear, a more complicated conversion must be applied.Ī major constraint to most existing backcalculation procedures is the assumption that the fish-otolith relationship is not only linear, but does not vary systematically with the growth rate of the fish. If the fish length:otolith length relationship is linear, the increment widths are roughly proportional to the growth of the fish. Similarly, the radius of the otolith at a given age/increment is a reflection of the length of the fish at that age and on that date. Since the fish length:otolith length relationship can be determined, the widths of the daily (or yearly) growth increments in an otolith reflect the daily (or yearly) growth rates of the fish at that age and on those dates.
#When backcalculation is not series#
Growth backcalculations used to estimate fish length at a previous age or date can be derived from a series of growth increments (either daily or yearly) and represent one of the most powerful applications of the otolith. Also presented in Campana and Jones (1992) is the equation for a growth model which incorporates both age and temperature on a daily basis, thus allowing for changes in growth rate through time due to temperature changes. Equations for all of these, as well as others, are presented in Campana and Jones (1992). Frequently-used models include linear regression, Gompertz, von Bertalanffy, exponential and the logistic model. There are many possible growth models, all of which can be applied to either length or weight data and use either daily or yearly ages.
In most cases, the rationale for model preparation is to allow prediction of an expected mean size or growth rate at a given age, or to facilitate comparisons of estimated growth with other published estimates.Ĭalculations of growth rate may be based on equations derived from either empirically-fitted curves or one of the generally accepted growth models. The models can vary in complexity from that of a simple straight line through length at age data (simple linear regression), to sophisticated maximum likelihood estimates of size at age. 4 refs., 3 figs.Growth models are a standard product of length at age data. Consequently, it is pointed out that while using the deflection of the center of the load layer, investigating correctly the load distribution and using the real load distribution as far as possible in the backcalculation are very important. According to the calculation results of the present study, when the backcalculation is carried out, the estimated value of the young's modulus of the surface and the base layer may be increased possibly if the deflection at load points is included. Therefore in the present paper, the effects of the assumption on the backcalculated young's modulus are discussed. When the backcalculation is carried out, assumptions commonly made in backcalculation are uniformloading and completely bonded interface between two adjacent layers as the load effects.
uses backcalculation to explain measurement value of surface deflection data by FWD test is noticed. In the recent years, nondestructive test method as a structure evaluation method for pavement condition that.
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