README.md

BioCro

BioCro is a model that predicts plant growth over time given climate as input.

It uses models of key physiological and biophysical processes underlying plant growth (Humphries and Long, 1995), and has previously been used for predicting biomass yield and leaf area index of switchgrass and miscanthus (Miguez et al., 2009).

BioCro has also been integrated into a suite of tools that link the model directly with crop trait and yield data, streamlining the entire modeling and data collection workflow (LeBauer et al, 2013). The Predictive Ecosystem Analyzer (PEcAn) couples BioCro to the Biofuel Ecophysiological Traits and Yields database, enabling model parameterization and optimization, targeted data collection optimized to reduce uncertainty in model predictions, and the management of informatics and HPC computing resources.

An example

The BioGro() function accepts initial values, parameters, climate variables, and a set of modules to run. It returns the results in a data frame.

library(BioCro)
data(weather05)
res <- BioGro(weather05)

plot(res)

There are parameters and modules for miscanthus (Miscanthus x giganteus), sorghum (Sorghum bicolor) and willow (Saliceae salix).

Installation

Requirements

The R environment version 3.2.3 or greater.

On Windows, Rtools version 3.3 or higher (3.4 is not recommended as of 2017-09-12 since that version is not frozen), and on Linux, gcc and g++ version 4.9.3 or greater (consult documentation for you distribution for installation instructions).

BioCro installation

Easy method:

library(devtools)
install_github('ebimodeling/biocro')

Alternatives methods:

Clone the BioCro source code from GitHub with git clone https://github.com/ebimodeling/biocro. Or, download the source, unzip the file, and install from the either the command line or from within R using one of the following sets of commands.

These assume that the source files are in a directory named "biocro".

• From the command line

cd path_to_unzipped_directory
R CMD INSTALL biocro

• From within R

setwd('path_to_unzipped_directory')
install.packages('biocro', repos=NULL, type='SOURCE')

Inputs

• Species-specific plant physiological traits
  • Photosynthetic parameters
  • Phenological stages
  • Biomass partitioning
• Soil physical properties
  • Water holding capacity
  • Wilting point
  • Sand
  • Silt
  • Clay
  • Organic matter
  • Rooting depth
• Meteorological data (daily or hourly)
  • Precipitation
  • Solar radiation
  • Wind speed
  • Temperature
  • Humidity

Outputs

• Yield
• Net primary production
• Biomass (leaf, root, storage)
• Evapotranspiration
• Leaf area index
• many more

Software Documentation

• R package
• C library

References

• Humphries S and Long SP (1995) WIMOVAC - a software package for modeling the dynamics of the plant leaf and canopy photosynthesis. Computer Applications in the Bioscience 11(4):361-371.

• Miguez FE, Zhu XG, Humphries S, Bollero GA, Long SP (2009) A semimechanistic model predicting the growth and production of the bioenergy crop Miscanthus × giganteus: description, parameterization and validation. Global Change Biology Bioenergy 1: 282-296.

• Wang D, Jaiswal D, Lebauer DS, Wertin TM, Bollero GA, Leakey ADB, Long SP (2015) A physiological and biophysical model of coppice willow (Salix spp.) production yields for the contiguous USA in current and future climate scenarios. Plant, cell & environment, 38(9), 1850-1865.