Dataset DOI: 10.5061/dryad.mw6m9067x

Description of the data and file structure

This dataset contains code and simulated data from a study on the effect of propagule pressure and native community characteristics on the success of a virtual invasive species. Invasion of ecological communities by introduced species depends on the introduced species’ traits, biotic resistance, and propagule pressure. Each of these factors has been studied individually, but the interactions between them need further attention. For example, propagule pressure is considered an important predictor of invader success, but its effect is likely mediated by native composition and invader traits. Similarly, biotic resistance arises through the effects of local community assembly processes on native-exotic interactions, but is generally studied using native diversity alone. Therefore, here we examined interactions between propagule pressure and native community assembly processes in determining exotic species abundance, using spatially-explicit community assembly simulations. All data in this dataset is simulated.

Files and variables

File types

Simulation code files - .R files with names beginning with a number, contain code used for simulations.

Data files - .csv files, contain simulated data generated used the simulation code files.

Analysis code files - .R files with names beginning with 'Analysis', contain code used for plotting and analyzing simulated data.

Other files - .rds files, used in the simulations.

Common abbreviations in file names

Assembly scenario

• Nuet - Neutral scenario
• LimSim1 - Limiting similarity sub-scenario with classic limiting similarity and character displacement
• LimSim2 - Limiting similarity sub-scenario with modified limiting similarity and character displacement
• LimSim3 - Limiting similarity sub-scenario with limiting similarity only
• SelAss - Self-assembly scenario

Independent variable

• numvar - Number of propagules per introduction event was varied, while frequency of introduction events and initial native species richness kept constant (introduction frequency equal to once every time step during the introduction period, native richness equal to 10 unless otherwise mentioned).
• richvar - Initial native species richness was varied. Number of propagules per introduction event also varied in a full factorial manner. Frequency of introduction events kept constant (equal to once every time step during the introduction period).
• burnin - Native community dynamics during burn-in period. No propagule pressure. Initial native richness equal to 10 unless otherwise specified.

Simulation code files

File names begin with 3 digits in the format x.y.z, where:

• x = assembly scenario
  • 1 - neutral (e.g. 1.0.1Neut_numvar.R, 1.0.2Neut_richvar.R)
  • 2 - limiting similarity
  • 3 - self assembly (e.g. 3.0.0SelAss_burnin.R, 3.0.1SelAss_numvar.R)
• y = sub-scenario (in limiting similarity scenario only)
  • 1 - classic limiting similarity with character displacement (e.g. 2.1.0LimSim1_burnin.R, 2.1.1LimSim1_numvar.R, 2.1.2LimSim1_richvar.R)
  • 2 - modified limiting similarity with character displacement (e.g. 2.2.0LimSim2_burnin.R, 2.2.1LimSim2_numvar.R, 2.2.2LimSim2_richvar.R)
  • 3 - limiting similarity only (e.g. 2.3.0LimSim3_burnin.R, 2.3.1LimSim3_numvar.R, 2.3.2LimSim3_richvar.R)
  • 0 - no sub-scenario (in neutral and self-assembly scenarios)
• z = independent variable varied
  • 1 - propagule pressure/number of propagules per introduction event (e.g. e.g. 1.0.1Neut_numvar.R)
  • 2 - initial native species richness (e.g. 1.0.2Neut_richvar.R)
  • 0 - only burn-in period simulated, no propagule pressure and no variation in native richness (e.g. 2.1.0LimSim1_burnin.R)

Note: All simulation code files other than 0.0.0Env_Grid_Neighbours.R are meant to be run on a high performance computing cluster. Running them on a personal computer may require excessive computational time, unless the number of replicates and/or number of time steps is reduced.** **Each code file in its current form requires 96 cores for parallel processing. Users can adjust the number of cores using the 'ncores' variable.

Note 2: All simulation code files other than 0.0.0Env_Grid_Neighbours.R will generate temporary .txt files while running, for keeping track of simulation progress. Users may wish to create folders for storing these .txt files, and will need to specify the appropriate file path inside the clusterEvalQ function.

File: 0.0.0Env_Grid_Neighbours.R

Code for generating the landscape grid, a list of neighbours of each grid cell (neighbours.rds), and the environment (env.rds). Output from this file is needed for running all other simulation files.

All other simulation code files

File names start with the three digit code explained above, which describes what each file does. There is no burn-in only code for the neutral scenario as there was no burn-in period in this scenario (i.e. there is no file with name beginning with 1.0.0). Additionally, the effect of varying initial native richness was not explored in the self-assembly scenario, hence there is no code file whose name begins with 3.0.2.

Data files

Data files containing community composition data are named according to the following format: CommunComp_scenario*_***var.csv, where

• CommunComp - indicates that the file contains community composition data
• scenario - abbreviated scenario name (see "Common abbreviations in file names" section)
• var - abbreviation describing the independent variable that was varied (see "Common abbreviations in file names" section)

In these files, each row contains data from a single simulated community at a single time step. The code files used for generating each of these data files can be identified using the scenario and independent variable abbreviations in the file names.

Data files that do not contain community composition data:

env.csv - environment variable used in the limiting similarity and self-assembly simulations. Each row corresponds to a grid cell in the simulated landscape. Generated using the code file 0.0.0Env_Grid_Neighbours.R

SpNiche_SelAss.csv - environmental niche and demographic rates of each species in each species pool, used in the self-assembly scenario simulations. Each row corresponds to a single species in a given species pool. Generated using the code file 3.0.0SelAss_burnin.R

Description of variable names in each data file

File: env.csv

Variables

• x - x coordinates of the given grid cell
• y - y coordinates of the given grid cell
• env - value of the environmental variable in the given grid cell (unit-less)

File: SpNiche**_SelAss**.csv

Variables

• PoolNum: A unique number for each simulated species pool
• Sp: A unique number for each simulated species in each species pool. Each pool contains 101 species (Sp101 corresponds to the introduced species, rest are native species). Note that species with the same ID number from different pools are unrelated to each other.
• EnvOpt: Environmental niche optimum of the given species
• EnvWidth: Environmental niche width of the given species
• Fecund: Fecundity of the given species
• SurvivalTradeoff: Maximum survival rate of adults of the given species in their optimal environment
• Survival2Tradeoff: Maximum survival rate of propagules of the given species in their optimal environment

Files with names ending in "numvar.csv"

(i.e. CommunComp_Neut_numvar.csv, CommunComp_LimSim1_numvar.csv , CommunComp_LimSim2_numvar.csv, CommunComp_LimSim3_numvar.csv, CommunComp_SelAss_numvar.csv)

Variables

• Rep: A unique number for each simulated community
• Time: Time step (may not start at zero because burn-in period is not saved)
• SpRich: Species richness (number of species present in the landscape) at the given time step
• PropNum: Propagule pressure (number of invader propagules introduced per introduction event, relative to the fecundity of a native individual)
• Column names beginning with 'Sp' or 'sp' (sp1-sp11 or Sp1-Sp101): Abundance of each species at the given time step. Abundance refers to the number of landscape cells occupied by a given species. Column name with the highest number corresponds to the introduced species (sp11 in the neutral and limiting similarity scenarios, Sp101 in the self-assembly scenario).

The file for the self-assembly scenario contains the additional column:

• PoolNum: Species pool that the given community belongs to

Files with names ending in "richvar.csv"

(i.e. CommunComp_Neut_richvar.csv, CommunComp_LimSim1_richvar.csv , CommunComp_LimSim2_richvar.csv, CommunComp_LimSim3_richvar.csv)

Variables

• Rep: A unique number for each simulated community
• Time: Time step (may not start at zero because burn-in period is not saved)
• NumSp: Initial native species richness (including the introduced species)
• PropNum: Propagule pressure (number of invader propagules introduced per introduction event, relative to the fecundity of a native individual)
• NumSpRemain: Species richness at the given time step
• MeanNAbund: Mean native species abundance at the given time step
• MaxNAbund: Maximum native species abundance at the given time step (i.e. abundance of the most common native species)
• SdNAbund: Standard deviation of native species abundance at the given time step
• InvAbund: Abundance of introduced species at the given time step

Files with names ending in "burnin.csv"

(i.e. CommunComp_LimSim1_burnin.csv , CommunComp_LimSim2_burnin.csv, CommunComp_LimSim3_burnin.csv, CommunComp_SelAss_burnin.csv)

Variables

Same as for files with names ending in 'numvar.csv', except that the Time variable starts at zero, and there is no introduced species (column 'sp11' or 'Sp101' if present, is always zero).

Analysis code files

File: Analysis_burnin.R

Description: For plotting and analyzing community composition trends during the burn-in period, in the self-assembly and limiting similarity scenarios.

File: Analysis_richvar.R

Description: For plotting and analyzing results of simulations where of varying native richness on introduced species abundance, and the effect of the introduced species on native diversity.

File: Analysis_numvar.R

Description: For plotting and analyzing the results of simulations where propagule pressure (number of propagules per introduction event) was varied.

File: Analysis_SelAss_nativeniches.R

Description: For plotting and analyzing the changes in native niche distributions during the burn-in period in the self-assembly scenario.

File: Analysis_SelAss_randomforest.R

Description: For the random forest analysis on the role of propagule pressure and native community characteristics in determining invader abundance, in the self-assembly scenario

Other files

env.rds - file containing the environment value associated with grid cell of the landscape. Generated using the code in 0.0.0Env_Grid_Neighbours.R and was used in the simulations. Contains the same information as the env.csv file.

neighbours.rds - file containing the list of neighbours of each grid cell. Generated using the code in 0.0.0Env_Grid_Neighbours.R and in the simulations.

Code/software

All code was written in R version 4.2.0

Access information

Other publicly accessible locations of the data:

• None

Data was derived from the following sources:

• None