comTS  R Documentation 
comTS()
is a function used to simulate com
munity T
ime S
eries
based on custom parameters.
comTS(nsp, ny, even, mvs, sync = c("2", "1", "0", "1", "2"))
nsp 
Number of species in the community 
ny 
Length of the time series in years 
even 
Parameter of the geometric rankabundance curve
ranging between 0 and 1 
mvs 
Scaling coefficient of the meanvariance
relationship ranging between 1 and 2 
sync 
Level of synchrony between species

The simulation produces temporal series of abundances of 'nsp'
species for 'ny'
years.
The mean abundance of each species is determined by a geometric series of 'nsp'
values using a constant
'even'
ratio between successive terms. Hence, a high 'even'
value means a community with even species
abundances while a low 'even'
means a strongly dominated community. Species temporal variances are
calculated following Taylorâ€™s power law, using with a 'mvs'
scaling coefficient.
Finally, for each species, the 'ny'
abundance values are sampled from a normal distribution
with the corresponding species parameters, and bounded to positive values. Since each species is simulated independently of others,
the resulting simulation can be used to describe a community where the 'nsp'
species fluctuate independently ('sync'
= "0").
To simulate an overall positive synchrony ('sync'
= "1"), the temporal sequences
of each species are sorted to maximize the number of years with all species
having values above or below their respective median (one random selection among many possible combinations).
A stabilizing negative synchrony ('sync'
= "1") is simulated by sorting the temporal sequences
of each species to maximize the number of years where successively abundant species
have values above and below their respective median (one random selection among many possible combinations).
High positive synchrony ('sync'
= "2") and high negative synchrony ('sync'
= "2") are generated using a similar approach but
sorting values based on four quartiles instead of using the median only.
The simulation uses a simplistic approach where species fluctuations are not related to any underlying environmental factor
nor demographic parameters. Consequently, the temporal order of the simulated abundances for each species cannot be considered realistic.
Nevertheless, this simplification has little influence on the analyses performed in this R
package since none of the indices
calculated depend on the temporal order of individual series, but rather describe the overall variability and temporal coordination of species.
A matrix
of 'ny'
rows and 'nsp'
columns, containing numerical values of species abundances.
The parameters used to compute species values (even, mvs, and sync) are stored as attributes of the matrix.
Jules Segrestin, jsegrestin@gmail.com
require(stats)
comTS(nsp = 10, ny = 30, even = 0.6, mvs = 1.5, sync = "0")
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