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Madera y bosques

On-line version ISSN 2448-7597Print version ISSN 1405-0471

Abstract

ARAUJO, Rafael J.  and  SHIDELER, Geoffrey S.. An R package for computation of mangrove forest structural parameters using plot and plotless methods. Madera bosques [online]. 2019, vol.25, n.1, e2511696.  Epub July 29, 2019. ISSN 2448-7597.  https://doi.org/10.21829/myb.2019.2511696.

Mangrove structure is influenced not only by the magnitude and periodicity of favorable energy inputs (temperature, hydroperiod, tides, sunlight, and nutrients), but also by stressors (salinity, drought, storms, and frost), which may have a diminishing effect on forest structure. In worldwide characterization of mangrove forests, researchers use several structural parameters to inform, compare, classify, and evaluate mangrove communities for both research and management. However, the calculation of these structural parameters involves a multi-step series of protocols and formula applications that are error-prone and time consuming. Using standard mangrove structure methodologies found in the literature, the mangroveStructure package for R was developed to deliver a simple tool to quickly calculate mangrove forest structure based on either plot or plotless methods. Outputs of the package include density, diameter, basal area, height, as well as relative values of density, dominance, frequency, and importance value. Output also includes common structural indices (complexity index and mean stand diameter) and visual representations of relative values, diameter and height histograms, and canopy height distributions along the transect line. This package will be useful to scientists interested in mangrove field surveys and those seeking a better understanding of mangrove ecosystems structural variability. To familiarize users with its many features, the package includes example data sets collected in the mangroves of Darién, Panama, and south Florida, USA.

Keywords : basal area; diameter; mangrove ecology; mangrove sampling; mangrove structure; point-centered quarter method (PCQM).

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