assimilation | R Documentation |
This is the main function in siplab for computing assimilation indices. Optionally, it computes also a free-growing index, and/or the assimilation centroid.
assimilation(plants, pixsize = 0.2, resource = 1, influence = gnomon_inf, infpar = NULL, asym = Inf, efficiency = flat_eff, effpar = NULL, plot = TRUE, afree = FALSE, centroid = FALSE) assimilation_pix(plants, pixsize = 0.2, resource = 1, influence = gnomon_inf, infpar = NULL, asym = Inf, efficiency = flat_eff, effpar = NULL, plot = TRUE, afree = FALSE, centroid = FALSE)
plants |
A spatstat point pattern object (class |
pixsize |
Resolution, approximate step size in the pixel grid. Default 0.2. |
resource |
Either a pixel image (class |
influence |
Function for computing influence values. Must take arguments |
infpar |
Parameter(s) for |
asym |
Asymmetry parameter α in the allotment function. Default is |
efficiency |
Efficiency function for weighting the point-wise resource uptake. Must take arguments |
effpar |
Parameter(s) for |
plot |
If |
afree |
If |
centroid |
If |
assimilation()
and assimilation_pix()
are functionally equivalent, but the code in assimilation_pix()
is somewhat clearer and slower. It may be useful for documentation purposes, and as a basis for user modification.
Computation starts with a resource intensity map at a spatial resolution given by pixsize
. Typically the resource distribution is assumed to be uniform (the default). Plants exert competitive pressure depending on size and distance, described by the influence
function. The resource available at each pixel is allotted to plants according to their influence and to an allotment rule parametrized by asym
. Finally, the resource uptake is weighted by the efficiency
function, and is spatially integrated to obtain the plant's assimilation index. Besides size, influence and efficiency functions can include other plant attributes, such as species.
Returns the input point pattern plants
, with the marks replaced by a data frame containing the original marks followed by one or more columns containing the computed results. The additional column are the assimilation indices in column aindex
, and optionally the free-growing index in afree
, and/or the x and y centroid coordinates in cx
and cy
.
Requires the spatstat package.
Oscar García.
https://github.com/ogarciav/siplab.
García, O. (2013) “A generic approach to spatial individual-based modelling and simulation of plant communities”. Mathematical and Computational Forestry and Nat.-Res. Sci. (MCFNS) 6(1), 36-47. 2014.
influence
, efficiency
, edges
a <- assimilation(finpines, infpar=list(a=1, b=4, smark="height"), afree=TRUE) summary(a) system.time(assimilation_pix(finpines)) system.time(assimilation(finpines))
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