Topic: Spatial

Topic Description:

Functions for calculating Ripley's K from CTFS R Analytical Tables, many routines for quadrat-based calculations. and calculations of wavelet variance.



File: spatial/block.analysis.r

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Function: wavelet.allsp

Function Description: wavelet.allsp

Function to calculate the wavelet variance curves for all species in one plot using quadrat indexation from CTFS package. Author: Matteo Detto and Tania Brenes
Output is a matrix with:
scale: vector with scale of the analysis in meters;
variance: matrix with the normalized variance at each scale (columns) for each species (rows);
density: matrix with the density per area and abundance for each species in the plot;
plotdim: plot dimentions parameter used;
gridsize: grid size parameter used;
UCL: vector with the upper confidence limit for the null hypothesis;
LCL: vector with the lower confidence limit for the null hypothesis.

Function Arguments:

ArgumentDefault Value
censdata
plotdimc(1000,500)
gridsize2.5
mindbhNULL

Arguments Description:

censdata (): census data for the plot containing the variables gx, gy, dbh, status, and sp code;
plotdim c(1000,500): vector with two numbers indicating the plot size;
gridsize (2.5): gives the size of the quadrats for the rasterization mindbh (NULL): if analysis is to be done at different size classes


Sample Usage:

load("bci.full1.rdata")
wavelet.variances = wavelet.allsp(censdata, plotdim=c(1000,500))


Function Source:

#
#
# wavelet.allsp
#


#

# Function to calculate the wavelet variance curves for all species in one plot using quadrat indexa
        tion from CTFS package. #
# Author: Matteo Detto and Tania Brenes

#
# Output is a matrix with:

# scale: vector with scale of the analysis in meters;


# variance: matrix with the normalized variance at each scale (columns) for each species (rows);

         # density: matrix with the density per area and abundance for each species in the plot;

# plotdim: plot dimentions parameter used;

# gridsize: grid size parameter used;

# UCL: vector with the upper confidence limit for the null hypothesis;

# LCL: vector with the lower confidence limit for the null hypothesis.