GapSizeFDist {ForestGapR}

Forest Canopy Gap-size Frequency Distributions

Description

This function quantifies forest canopy gap size-frequency distributions and estimates power-law exponent (λ) from the Zeta distribution.

Usage

GapSizeFDist(gaps_stats,method,...)

Arguments

gaps_stats

A data.frame containing basic statistics of forest gaps. Output of GapStats() function.

method

If method='Asner_2013' the λ is computed following the method described Asner et al. (2013) and if methods='Hanel_2017' the λ is computed following the method described in Hanel et al. (2017)

...

Supplementary parameters for [graphics::plot()).

Value

A log-log plot of gap-size Frequency Distributions and a list containing: i) λ, ii) the gap-size Frequency Distributions and ii) method used. The λ parameter is derived for the Zeta distribution using a maximum likelihood estimator. See details section.

References

Hanel,R., Corominas-Murtra, B., Liu, B., Thurner, S. (2013). Fitting power-laws in empirical data with estimators that work for all exponents, PloS one, vol. 12, no. 2, p. e0170920.https://doi.org/10.1371/journal.pone.0170920

Asner, G.P., Kellner, J.R., Kennedy-Bowdoin, T., Knapp, D.E., Anderson, C. & Martin, R.E. (2013). Forest canopy gap distributions in the Southern Peruvian Amazon. PLoS One, 8, e60875.https://doi.org/10.1371/journal.pone.0060875

White, E.P, Enquist, B.J, Green, J.L. (2008) On estimating the exponent of power law frequency distributions. Ecology 89,905-912. https://doi.org/10.1890/07-1288.1

Examples

# Loading raster library
library(raster)

# ALS-derived CHM over Adolpho Ducke Forest Reserve - Brazilian tropical forest
data(ALS_CHM_DUC)

# set height thresholds (e.g. 10 meters)
threshold <- 10
size <- c(1, 10^4) # m2

# Detecting forest gaps
gaps_duc <- getForestGaps(chm_layer = ALS_CHM_DUC, threshold = threshold, size = size)

# Computing basic statistics of forest gap
gaps_stats <- GapStats(gap_layer = gaps_duc, chm_layer = ALS_CHM_DUC)

# Gap-size Frequency Distributions
GapSizeFDist(
  gaps_stats = gaps_stats, method = "Hanel_2017", col = "forestgreen", pch = 16, cex = 1,
  axes = FALSE, ylab = "Gap Frequency", xlab = as.expression(bquote("Gap Size" ~ (m^2)))
)
axis(1)
axis(2)
grid(4, 4)