The plant package for R is an extensible framework for modelling size- and trait-structured demography, ecology and evolution in simulated forests. At its core, plant is an individual-based model where plant physiology and demography are mediated by traits. Individual plants from multiple species can be grown in isolation, in patches of competing plants or in metapopulations under a disturbance regime. These dynamics can be integrated into metapopulation-level estimates of invasion fitness and vegetation structure. Accessed from R, the core routines in plant are written in C++. The package provides for alternative physiologies and for capturing trade-offs among parameters. A detailed test suite is provided to ensure correct behaviour of the code.

## Citation

Falster DS, FitzJohn RG, Brännström Å, Dieckmann U, Westoby M (2016) plant: A package for modelling forest trait ecology & evolution. Methods in Ecology and Evolution 7: 136-146. doi: 10.1111/2041-210X.12525

## Documentation

An overview of the plant package is given by the above publication. Further background on the default FF16 growth model is available in Falster et al 2011 (10.1111/j.1365-2745.2010.01735.x) and Falster et al 2017 (10.1101/083451).

plant comes with a lot of documentation, available at https://traitecoevo.github.io/plant/. Initial versions for some of the material there was also included as supplementary material with the publication about plant, which can be accessed here.

## Package structure

Plant is a complex package, using C++11 behind the scenes for speed with R6 classes (via the Rcpp and RcppR6 packages). In this blog post, Rich FitzJohn and I describe the key technologies used to build the plant package.

If you are interested in developing plant you should read the Developer Notes.

## Installation

You must be using R 3.3.0 or newer. At this stage the package is not on CRAN. You’re options for installing are described below.

Installation requires a C++11 compatible C compiler (OSX >= 10.10/Yosemite satisfies this, as do standard linux Ubuntu 12.04 and 14.04). On Windows machines you will need to install Rtools. When I tried this in Rstudio, the program automagically sensed the absence of a compiler and asked if I wanted to install Rtools. Click Yes!

Option 1, using devtools::install_github

(install devtools with install.packages("devtools"))

The plant package can be installed direct from github using the devtools package. plant also requires the packages loggr and RcppR6 packages. Install those with

devtools::install_github("smbache/loggr", dependencies=TRUE)
devtools::install_github("richfitz/RcppR6", dependencies=TRUE)

Then install plant:

devtools::install_github("traitecoevo/plant", dependencies=TRUE)

If installing locally you will still need to install the loggr and RcppR6 packages. Install using devtools::install_github as above, or alternatively do as follows.

Additionally install other dependencies from CRAN:

install.packages(c("Rcpp", "R6", "crayon", "nleqslv", "BB" ,"BH"))

Then download a zip file from github of the dependencies RcppR6 and loggr (if needed), plus plant.

Unzip these archives and then for each package run the command

install.packages("path_to_package", repos = NULL, type="source")

where path_to_package is the folder for each package, e.g. ~/Downloads/plant-master

Installing different versions

To install a specific (older) release, decide for the version number that you want to install in https://github.com/traitecoevo/plant/releases e.g.

devtools::install_github("traitecoevo/plant", ref = "v1.0.0", dependencies=TRUE)

with "v1.0.0" replaced by the appropriate version number.

## Usage

Plant has been used in the following publications:

• Falster DS, FitzJohn RG, Brännström Å, Dieckmann U, Westoby M (2016) plant: A package for modelling forest trait ecology & evolution. Methods in Ecology and Evolution 7: 136-146. doi: 10.1111/2041-210X.12525  code: github
• Falster DS, Duursma RA, FitzJohn RG (2016) Trajectories: how functional traits influence plant growth and shade tolerance across the life-cycle. bioRxiv: 083451. doi: 10.1101/083451  code: github