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Journal of Coastal Conservation

, Volume 23, Issue 1, pp 71–91 | Cite as

Improved allometric proxies for eelgrass conservation

  • A. Montesinos-López
  • E. Villa-Diharce
  • H. Echavarría-HerasEmail author
  • C. Leal-Ramírez
Article

Abstract

Current anthropogenic influences threaten the permanence of eelgrass, a relevant macrophyte that brings about important ecological benefits including nursery for waterfowl and fish species, shoreline stabilization, nutrient recycling and carbon sequestration. Eelgrass restoration normally involves transplanted plots and monitoring success requires noninvasive assessments of standing stock and productivity. Allometric scaling of eelgrass leaf biomass and length can provide proxies for these assessments, but accuracy of allometric projections is mainly resultant of uncertainty propagation of parameters, so for the sake of suitability it is very important ensuring the most accurate estimates. The traditional approach for producing estimates of allometric parameters considers a linear regression model involving logarithms of the original response and explanatory variables along with a normally distributed additive error. The suitability of this method has been questioned on the ground of biased results raising nonlinear regression as a necessary amendment. Here we demonstrate that this controversy can be surpassed allowing for a logistic error structure and heteroscedasticity in the traditional method. The present arrangement delivered parameter estimates from raw data surpassing inconveniences of the traditional fitting procedure. Moreover, associated allometric proxies for average leaf biomass in shoots entailed similar reproducibilities than produced by using nonlinear regression and quality controlled data. In achieving suitable accuracy levels, the present approach required a sample of raw data of about 9% of involved in prior estimations based on quality controlled data. The improvements associated to the present approach grant highly consistent non-destructive assessments for the sake of eelgrass conservation.

Keywords

Eelgrass conservation Allometric scaling Eelgrass leaf biomass Traditional analysis method of allometry Logistically distributed error term Heteroscedasticity 

Notes

Acknowledgements

Completion of this work was achieved while Enrique Villa (CVU:208964) was on a sabbatical leave at Centro de Investigación Científica y de Educación Superior de Ensenada, partially funded by a grant from México’s Consejo Nacional de Ciencia y Tecnología.

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Copyright information

© The Author(s) 2018
corrected publication August/2018

Authors and Affiliations

  • A. Montesinos-López
    • 1
  • E. Villa-Diharce
    • 2
  • H. Echavarría-Heras
    • 3
    Email author
  • C. Leal-Ramírez
    • 3
  1. 1.Departamento de MatemáticasCentro Universitario de Ciencias Exactas e Ingenierías (CUCEI)GuadalajaraMéxico
  2. 2.Centro de Investigación en MatemáticasValencianaMexico
  3. 3.Centro de Investigación Cientifica y de Estudios Superiores de EnsenadaFraccionamiento Zona PlayitasMexico

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