An R package for computation of mangrove forest structural parameters using plot and plotless methods

Abstract

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.

Macrozoobenthic community assemblage as key indicator for mangrove restoration success in North Sumatra and Aceh, Indonesia

“…All statistical analyses were conducted using R, version 4.0.3 (R Core Team 2020). Specific used packages were: mangroveStructure (Araújo & Shideler 2019) to compute forest structure parameters; vegan (Oksanen et al 2019) for PCA, CCA, NMDS, and ANOSIM; and indicspecies (De Cáceres et al 2010) to detect site‐group and site‐group combinations for indicator species. To plot all figures, we used package ggplot2 (Wickham 2016) in combination with ggpubr (Kassmbara 2020).…”

“…All statistical analyses were conducted using R, version 4.0.3 (R Core Team 2020). Specific used packages were: mangroveStructure (Araújo & Shideler 2019)…”