Conservation of eelgrass relies on transplants and evaluation of success depends on nondestructive measurements of average leaf biomass in shoots among other variables. Allometric proxies offer a convenient way to assessments. Identifying surrogates via log transformation and linear regression can set biased results. Views conceive this approach to be meaningful, asserting that curvature in geometrical space explains bias. Inappropriateness of correction factor of retransformation bias could also explain inconsistencies. Accounting for nonlinearity of the log transformed response relied on a generalized allometric model. Scaling parameters depend continuously on the descriptor. Joining correction factor is conceived as the partial sum of series expansion of mean retransformed residuals leading to highest reproducibility strength. Fits of particular characterizations of the generalized curvature model conveyed outstanding reproducibility of average eelgrass leaf biomass in shoots. Although nonlinear heteroscedastic regression resulted also to be suitable, only log transformation approaches can unmask a size related differentiation in growth form of the leaf. Generally, whenever structure of regression error is undetermined, choosing a suitable form of retransformation correction factor becomes elusive. Compared to customary nonparametric characterizations of this correction factor, present form proved more efficient. We expect that offered generalized allometric model along with proposed correction factor form provides a suitable analytical arrangement for the general settings of allometric examination.

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The rate of production of leaf biomass in eelgrass (Zostera marina L.) is an indicator variable for environmental influences on the growth of this important seagrass species. The efforts to restore eelgrass meadows from the harmful human influences make the use of nondestructive evaluations essential. We present, here, an indirect procedure for the estimation of the growth rates of eelgrass leaves by using easily obtained measurements of leaf length and increases in leaf length, and allometric parameters linked to the scaling of leaf biomass and leaf length. This allometric method includes criteria that allow the estimation of leaf growth rates even when the sizes of some of the leaves cannot be determined because of herbivory or other environmental factors. To validate the proposed method, we performed simulation studies and analyzed data from two natural eelgrass populations in the East Pacific (México). These allometric projections of leaf growth rates displayed a high level of correspondence with observed values. We show that whenever the allometric parameters for the scaling of eelgrass leaf dry weight in terms of leaf length have been previously fitted, the method proposed here can provide an alternative for estimating biomass production that is both accurate and nondestructive and uses easily obtained data on leaf length and increases in leaf length between the sampling periods.