View source: R/indicator_plrange.R
indicator_plrange | R Documentation |
Compute the power-law range of a matrix
indicator_plrange(mat, merge = FALSE, xmin_bounds = NULL)
mat |
A logical matrix, or a list of logical matrices |
merge |
Controls whether the patch-size distributions of the input
matrices are merged together before computing the power-law range. Setting
this value to |
xmin_bounds |
A vector of two integer values, defining a range in which to search for the best xmin (see 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 (x_{min}
) and the one with the lowest Kolmogorov-Smirnov
distance to the empirical distribution is retained. PLR is then computed
using this best-fitting x_{min}
as:
\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.
A data.frame
with columns minsize
, maxsize
which are the
observed minimum and maximum patch sizes, the estimated x_{min}
as column
xmin
and the value of the power-law range as plrange
. If multiple
matrices were provided, then a list of data.frames is returned
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.
patchdistr_sews
forestgap.plr <- indicator_plrange(forestgap)
do.call(rbind, forestgap.plr) # convert results to data.frame
# Restrict to small xmins
forestgap.plr2 <- indicator_plrange(forestgap, xmin_bounds = c(1, 10))
do.call(rbind, forestgap.plr2)
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