Description Usage Arguments Value Author(s)
Simulation of ecological data structured by single ecological gradient
1 2 3 4 5 6 7 8 | simul.comm(totS = 300, gr.length = 5000, niche.type = "random",
max.niche.breath = gr.length, min.niche.breath = 10,
spec.optima = "random", prop.random.species = 0, seed = NULL,
plotting = F, highlight.species = NULL)
sample.comm(simul.comm = NULL, Np = 300, sample.x = "random",
no.ind = 100, k = 0.2, seed = NULL, pa = FALSE,
based.on = "individuals", standardize.rowsums = TRUE)
|
totS |
total number of species in simulation |
gr.length |
length of the gradient in units |
niche.type |
shape of species response curves ('random', 'normal', 'skewed') |
max.niche.breath |
number, maximum niche breath along the gradient (default = |
min.niche.breath |
number, minimum niche breath along the gradient (default = |
spec.optima |
distribution of species optima along simulated gradient. Either one of |
prop.random.species |
Proportion of random species, i.e. species which are not related to the gradient. Should be real number from [0,1]. These species are generated by randomizing occurrence of given proportion of species among samples. Default = 0. |
seed |
set random seed for reproducing always the same result |
plotting |
should the species response curves along simulated gradient be drawned? Default = |
highlight.species |
vector of species numbers which should be highlighted by color in ploted diagram (if |
simul.comm |
result of simul.comm function with parameters of individual species response curves |
Np |
number of samples |
sample.x |
positions of sampling along the gradient. Default = |
no.ind |
mean number of individuals to be drawn from the species pool (if |
k |
mean proportion of species from species pool to be drawn into local community (if |
pa |
result table will be generated in presence-absence form (default |
based.on |
should the sampling of species from species pool be based on |
standardize.rowsums |
Standardizes the abundances of species in samples so as the sum of species abundances in sample is 100 (standardizes to rowsums equal to 100). Applies only if |
The function simul.comm
returns list
with 10 items, describing the set of parameters used to simulate community of species response curves:
totS
Total number of species in simulation.
gr.length
Length of the gradient.
niche.type
Shape of species response curves.
Ao
Vector of species amplitudes for the simulated gradient (heights of species response curves, corresponding to maximum probability of species to be selected to community in species optima).
m
Vector of species optima along the simulated gradient.
r
Vector of generated species ranges along the simulated gradient (generated niche breaths).
range
Vector of realised species ranges along the simulated gradient, considering the truncation of species response curves by gradient margins (these differ from r
especially at the gradient margins, where the generated species niche may be wide, but since the margin cuts the species occurrences, realised species niche is narrower.)
a, g
Vectors of shape parameters for curves (used in beta function to generate the shape of the species response curve)
A.all
Matrix (dim = gradient length x number of species) with simulated probabilites of individual specie at individual location along the simulated gradient.
The function sample.comm
returns list
of 5 items with parameters of generated community data; the last item contains also all items returned by simul.comm
function:
a.mat
Matrix (sample x species) of species abundances in samples.
p.mat
Matrix (sample x species) of species occurrence probabilities in samples.
sample.x
Vector with positions of samples along the first and second simulated gradient, respectively (environmental variable).
sample.comm
List of 7 items storing initial settings of arguments in sample.comm
(namely arguments Np, based.on, no.ind, k, seed, pa
and standardize.rowsums
).
simul.comm
List of 10 items returned by function simul.comm
.
David Zeleny (zeleny.david@gmail.com) - based on the scripts of Jason Fridley (Fridley et al. 2007, Appendix S2) and David Zeleny (Zeleny 2009, Appendix S1)
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