comm.simul {comsimitv}

Framework for community assembly simulation

Description

Flexible framework of individual-based simulation of community assembly following framework proposed by Botta-Dukat & Czucz (2016), but allowing intraspecific trait variation (ITV)

Usage

comm.simul(
  x = vector(),
  S = 200,
  n.traits = 3,
  J = 300,
  rand.seed = NULL,
  sim.length = 1,
  fSpecPool = "Gener.species.pool",
  competition.kernel = "Gaussian.competition.kernel",
  fSurvive = "Gaussian.tolerance",
  fSeedProduction = "SeedProduction",
  fDispersal = "MetaCom.Dispersal",
  fITV = "randomITV",
  verbose = FALSE,
  ...
)

Arguments

x

Vector of environmental values in communities. If not given, 40 communities are created, with environmental variable equally spacing from 0.11 to 0.89

S

Species pool size

n.traits

Number of traits

J

Number of individuals in each community

rand.seed

Random seed number. Setting the same value allows repeating the same simulation

sim.length

Length of simulation. sim.length*S cycle (disturbance-seed production-dispersal-establishment) will happen.

fSpecPool

Name of (the user defined) function that generates the species pool. See Gener.species.pool

competition.kernel

Name of the (user defined) function for calculating pairwise competition coefficients. See more details in available functions and specification of your own function in competition.kernel

fSurvive

Name of the (user defined) function for calculating survival probability of seeds. See more details in available functions and specification of your own function in tolerance

fSeedProduction

Name of the user defined function for calculating number of produced seeds See SeedProduction

fDispersal

Name of the user defined function for dispersal of produced seeds among local communities. See more details in available functions and specification of your own function in fDispersal

fITV

Name of the function that define seeds trait values, possibly considering mother's trait and mothers environment. If "noITV", there is no intraspecific trait variation. See more details in available functions and specification of your own function in fITV

verbose

Runing may take long time. If verbose set to TRUE, it writes messages into the screen indicating the progress.

...

Additional parameters of functions called by the framework.

Details

This function is a framework for simulation of assembly in a meta-community. The simulation consists of a community initialization followed by an iterative simulation of a "disturbance–regeneration" cycle. During initialization a species pool is created defining each species by its trait values. Each locality is characterized by an environmental variable. Initial composition of local communities is a random selection from the species pool: species identity is selected independently for each individal with probability of seedling survival (that depends on local environment and trait value).

The "disturbance-regeneration" cycle consists of the following steps:

1. disturbance event: some randomly selected individuals die in each community

2. survivors produce seeds. Seed production depends on fertility of the locality and competition among coexisting individuals

3. seeds are dispersed among localities

4. all seeds germinate and seedlings struggle for survival. The number of adults in local communities is fixed, thus number of seedlings that can survive and grow up equals to the number of individulas died in the disturbance event (in the recent version one individual dies, but planed development is introducing a disturbance severity/number of deaths parameter)

It is a flexible framework that calls funcions for:

• generating species pool (Gener.species.pool)

• calculating pairwise competition coefficients (competition.kernel)

• calculating seedling's survival probabilities (tolerance)

• calculating number of produced seeds (SeedProduction)

• calculating trait values of offsprings (fITV)

• seed dispersal among localities (fDispersal)

Functions available in the package can be easily replaced by user-defined functions.

Value

A list with two elements:

$final.community a dataframe containing data on individuals in the final meta-community. Each individual represented by a row; columns are: sub-community, species identity, trait values.

$parameters list of simulation parameters (including parameters of functions called by the framework function)

References

Botta-Dukat Z, Czucz B (2016) Testing the ability of functional diversity indices to detect trait convergence and divergence using individual-based simulation. Methods in Ecology and Evolution 7(1): 114-126. doi: 10.1111/2041-210X.12450

Examples

w<-comm.simul(S=20, J=30)
str(w)

set.seed(1)
w<-comm.simul(S=20, J=30, fITV=NULL)$final.community
w[w[,2]==1,] # Each individuals belonging to Species1 has the same trait values