Revista de Biología Tropical ISSN Impreso: 0034-7744 ISSN electrónico: 2215-2075

OAI: https://revistas.ucr.ac.cr/index.php/rbt/oai
An economical non-destructive method for estimating eelgrass, Zostera marina (Potamogetonaceae) leaf growth rates: formal development and use in northwestern Baja California
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Keywords

Zostera marina
tasa de crecimiento foliar
estimaciones analíticas
Eelgrass
growth rates
analytical estimations

How to Cite

Soreana Arellano, E., Echeverría Heras, H., & Franco Bizcaíno, E. (2008). An economical non-destructive method for estimating eelgrass, Zostera marina (Potamogetonaceae) leaf growth rates: formal development and use in northwestern Baja California. Revista De Biología Tropical, 56(3), 1003–1013. https://doi.org/10.15517/rbt.v56i3.5688

Abstract

Seagrass beds provide much of the primary production in estuaries; host many fishes and fish larvae, and abate erosion. The present study presents original analytical methods for estimating mean leaf-growth rates of eelgrass (Zostera marina). The method was calibrated by using data collected in a Z. marina meadow at Punta Banda estuary in Baja California, Mexico. The analytical assessments were based on measurements of leaf length and standard regression procedures. We present a detailed explanation of the formal procedures involved in the derivation of these analytical methods. The measured daily leaf-growth rate was 10.9 mm d-1 leaf-1. The corresponding value projected by our method was 10.2 mm d-1 leaf-1. The associated standard errors were of 0.53 and 0.56 mm d-1 leaf-1 respectively. The method was validated by projecting leaf-growth rates from an independent data set, which gave consistent results. The use of the method to obtain the mean leaf growth rate of a transplanted plot is also illustrated. Comparison of our leaf-growth data with previously reported assessments show the significant forcing of sea-surface temperature on eelgrass leaf dynamics. The formal constructs provided here are of general scope and can be applied to equivalent eelgrass data sets in a straightforward manner.
https://doi.org/10.15517/rbt.v56i3.5688
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