README.md

In gshideler/mangroveStructure: tools for calculating mangrove forest structure

Mangrove forest structure package in R

Description

Set of tools to calculate mangrove forest structure using either the Point-Centered Quarter Method or fixed-area sampling methods (i.e., square, rectangular or circular plot designs). Outputs include density, diameter, basal area, height, as well as relative comparisons of density, dominance, frequency, and importance value (IV). Output also includes functions for common structural indices [e.g., Holdridge Complexity Index (Holdridge 1967) and Mean Stand Diameter (Cintrón and Schaeffer Novelli 1984)] and visual representations of relative values and canopy height.

For a full description of the package and the theories behind it, visit https://myb.ojs.inecol.mx/index.php/myb/article/view/e2511696/1928.

The package was updated in October 2021 (v0.3.0) and now includes the funtions circle.method() and circle.indices() to process data collected from fixed-radius (circular) plots. Although the publication does not include a detailed description of these added functions, the rationale, outputs, and mechanics are similar to the ones described in the publication for plot sampling.

Installation

Using devtools to install

Type the following into R

install.packages('devtools')
devtools::install_github('gshideler/mangroveStructure')

You can skip the first line if you already have devtools installed.

Overview of package functions

A column with height measurements is required for canopy.plot(), for all others it is optional. If included, height-related metrics are displayed for each function.

Functions will not compute if missing values (NAs) are present.

pcqm.method()

This function allows you to estimate mangrove forest structure based on sampling using the Point-Centered Quarter Method (PCQM) (Cottam and Curtis 1956). Following Cintrón and Schaeffer Novelli (1984): (1) an individual tree must be present in each quarter, and (2) a single tree should not be measured twice. Outputs a data frame of the table of relative metrics, importance values, and ranking.

pcqm.indices()

This function allows you to calculate the Holdridge Complexity Index (Holdridge 1967) and Mean Stand Diameter (Cintrón and Schaeffer Novelli 1984) based on sampling using the Point-Centered Quarter Method (PCQM). Following Cintrón and Schaeffer Novelli (1984): (1) an individual tree must be present in each quarter, and (2) a single tree should not be measured twice. Height is required for the Holdridge Complexity Index.

canopy.profile()

This function allows you to plot canopy height across distance from Point-Centered Quarter Method transect data. Following Cintrón and Schaeffer Novelli (1984): (1) an individual tree must be present in each quarter, and (2) a single tree should not be measured twice.

plot.method()

This function allows you to estimate mangrove forest structure based on fixed-area sampling (plot). Outputs a data frame of the table of relative metrics, importance values, and ranking.

plot.indices()

This function allows you to calculate the Holdridge Complexity Index (Holdridge 1967) and Mean Stand Diameter (Cintrón and Schaeffer Novelli 1984) using fixed-area sampling (plot). Height is required for the Holdridge Complexity Index.

circle.method()

This function allows you to estimate mangrove forest structure based on fixed-radius plots. Outputs a data frame of the table of relative metrics, importance values, and ranking.

circle.indices()

This function allows you to calculate the Holdridge Complexity Index (Holdridge 1967) and Mean Stand Diameter (Cintrón and Schaeffer Novelli 1984) using fixed-radius plots. Height is required for the Holdridge Complexity Index.

iv.plot()

This function allows you to create a importance value plot using a data object created from either pcqm.method() or plot.method(), based on radarchart() from the 'fmsb' package.

Use examples

Load the necessary libraries

Note: the RCurl library is to allow for downloading of csv files from the github server, which are pulled for the examples below.

library(mangroveStructure)
library(RCurl)

Compute structure for point-centered transects (PCQM)

pcqm_data <- read.csv(text=getURL("https://raw.githubusercontent.com/gshideler/mangroveStructure/master/testdata/pcqm_data.csv"), header=TRUE)

r1 <- pcqm.method(pcqm_data)
iv.plot(r1)
pcqm.indices(pcqm_data, sizebin=TRUE)
canopy.profile(pcqm_data)

If your column names are different from the defaults, you can specify them using the appropriate argument. See package help files for more information and for all defaults. This applies to all functions in the package.

Example:

pcqm.method(pcqm_data, samplingpoint = "Sampling_Point", dbh = "Diameter")

Compute structure for fixed-area sampling plots

plot_data <- read.csv(text=getURL("https://raw.githubusercontent.com/gshideler/mangroveStructure/master/testdata/plot_data.csv"), header=TRUE)

r2 <- plot.method(plot_data)
iv.plot(r2, colors = c("black", "gray", "firebrick1"))
plot.indices(plot_data, sizebin=TRUE)

Compute structure for fixed-radius sampling plots ####

circleplot_data <- read.csv(text=getURL("https://raw.githubusercontent.com/gshideler/mangroveStructure/master/testdata/circleplot_data.csv"), header=TRUE)

r3 <- circle.method(circleplot_data, plot.radius = 5.65)
iv.plot(r3, colors = c("black", "forestgreen", "lightblue", "firebrick1"))
circle.indices(circleplot_data, sizebin=TRUE)

License

Use of mangroveStructure is covered under the open source "MIT License".

See License page for more details.

References

Cintrón G, Shaeffer Novelli Y. 1984. Methods for studying mangrove structure. In: Snedaker SC, Snedaker JG. (eds.) The mangrove ecosystem: research methods. Unesco. 251 p.

Cottam G, Curtis JT. 1956. The use of distance measures in phytosociological sampling. Ecology. 37:451–460.

Holdridge LR. 1967. Life zone ecology. Tropical Science Center. San José, Costa Rica. 206 p.

gshideler/mangroveStructure documentation built on Oct. 31, 2021, 4:37 a.m.