parametersDataframe: Generates a template dataframe to contain simulation...

In virtualPollen: Simulating Pollen Curves from Virtual Taxa with Different Life and Niche Traits

Generates a template dataframe to contain simulation parameters.

Description

Generates the dataframe structure needed to contain the parameters used as input for the simulatePopulation function.

Usage

parametersDataframe(rows=1)

Arguments

rows	integer, number of rows in the output dataframe.

Details

The resulting dataframe can either be filled manually through vectors, as shown in the example (but this requires to use the function fixParametersTypes once the dataframe is completed), or can be edited manually in Rstudio by installing the editData package.

Value

A dataframe filled with NA values and the columns:

• label: to store names (character string) of the virtual taxa.

• maximum.age: integer, maximum possible age of the individuals in years.

• reproductive.age: integer, age of sexual maturity in years.

• fecundity: integer, number of maximum viable seeds produced by a mature individual under fully suitable conditions.

• growth.rate: numeric, parameter of the logistic growth function.

• pollen.control: numeric in the interval [0, 1]. If 0, pollen productivity depends on environmental suitability only. The larger the number, biomass takes over environmental suitability in determining pollen productivity.

• maximum.biomass: integer, maximum biomass of the individuals.

• carrying.capacity: integer, maximum sum of biomass of the individuals. Very large carrying capacities plus a low maximum.biomass generates too many individuals for the simulation to remain efficient. Try to set carrying.capacity and maximum.biomass to carrying.capacity divided by biomass returns a number lower than 1000 (and even better if it is closer to 100).

• driver.A.weight: numeric in the interval [0, 1], represents the relative influence of the driver on environmental suitability.

• driver.B.weight: numeric in the interval [0, 1], represents the relative influence of the driver on environmental suitability. The sum of weights of drivers A and B should be 1.

• niche.A.mean: numeric, in the same units as driver A. It is the mean of the normal function defining the response of the virtual taxa to driver A.

• niche.A.sd: numeric, in the same units as driver A. It is the standard deviation of the normal function defining the response of the virtual taxa to driver A.

• niche.B.mean: as above, but for driver B.

• niche.B.sd: as above, but for driver B.

• autocorrelation.length.A: numeric, only useful if several drivers generated with different autocorrelation lengths are available (and identified by the column autocorrelation.length) in the drivers argument provided to the simulatePopulation function.

• autocorrelation.length.B: same as above.

Author(s)

Blas M. Benito <[e-mail]>

See Also

simulatePopulation, fixParametersTypes

Examples

#generating the template
parameters <- parametersDataframe(rows=1)

#filling it with a vector
parameters[1,] <- c("Species 1", 50, 20, 2, 0.2, 0, 100, 1000, 1, 0, 50, 10, 0, 0, 600, 600)

virtualPollen documentation built on March 18, 2022, 6:16 p.m.