ACGCA: An R package for simulating tree growth and mortality based on functional traits

Michael Fell, Jarrett Barber, Kiona Ogle

Research output: Contribution to journalArticlepeer-review


The Allometrically Constrained Growth and Carbon Allocation (ACGCA) model is an individual-based model of tree growth and mortality, and it is a unique tool for investigating how tree functional traits influence growth and mortality. Several studies have used the ACGCA model to investigate tree traits, but the model is not readily accessible to the wider scientific community. Thus, we developed an R package that provides a greatly simplified interface to the ACGCA model. The package contains a single function, runacgca, with the capability of simulating tree growth under constant light conditions, variable light, or within a simple forest gap dynamics scenario. The ACGCA package can accommodate temporally varying parameters (tree traits), and its modular structure allows for users to swap out the current carbon gain (photosynthesis) algorithm for alternative versions that may incorporate more physiological detail. We provide examples demonstrating how the package can be used to investigate the effects of tree traits on growth and survival under constant light and under different gap dynamic scenarios. Though not explicitly shown, this model can be easily adapted to include more mechanistic detail or integrated into larger modeling frameworks.

Original languageEnglish (US)
Article number101605
JournalEcological Informatics
StatePublished - Jul 2022


  • Individual-based model
  • Plant functional traits
  • R package
  • Trait trade-offs
  • Tree growth model

ASJC Scopus subject areas

  • Ecology, Evolution, Behavior and Systematics
  • Ecology
  • Modeling and Simulation
  • Ecological Modeling
  • Computer Science Applications
  • Computational Theory and Mathematics
  • Applied Mathematics


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