raw_plrange {spatialwarnings} | R Documentation |
Power-law range indicator
Description
Compute the power-law range of a matrix
Usage
raw_plrange(mat, xmin_bounds = NULL)
Arguments
mat |
A logical matrix, or a list of logical matrices |
xmin_bounds |
A vector of two integer values, defining a range in which to search for the best xmin (see Details). |
Details
Some ecosystems show typical changes in their patch-size
distribution as they become more and more degraded. In particular, an
increase in the truncation of the patch-size distribution (PSD) is expected
to occur. The power-law range (PLR) measures the truncation of the PSD
in a single value (see also patchdistr_sews
for more details).
To compute the PLR, power-laws are fitted with a variable minimum patch size (xmin) and the one with the lowest Kolmogorov-Smirnov distance to the empirical distribution is retained. PLR is then computed using this best-fitting xmin:
\frac{log(x_{max}) - log(x_{min})}{log(x_{max}) - log(x_{smallest})}
where x_{max}
is the maximum observed patch size, and
x_{smallest}
is the minimum observed patch size.
Value
A named vector containing the power-law range value
References
Clauset, A., Shalizi, C. R., & Newman, M. E. (2009). Power-law distributions in empirical data. SIAM review, 51(4), 661-703.
Berdugo, M., Kefi, S., Soliveres, S. & Maestre, F.T. (2017). Plant spatial patterns identify alternative ecosystem multifunctionality states in global drylands. Nature in Ecology and Evolution.
See Also
Examples
## Not run:
forestgap.plr <- raw_plrange(forestgap[[2]])
# Restrict to small xmins
forestgap.plr2 <- indicator_plrange(forestgap[[2]], xmin_bounds = c(1, 10))
## End(Not run)