<i>pnetr</i> : An R package for the <scp>PnET</scp> family of forest ecosystem models
Abstract Ecosystem models offer a rigorous way to formalize scientific theories and are critical to evaluating complex interactions among ecological and biogeochemical processes. In addition to simulation and prediction, ecosystem models are a valuable tool for testing hypotheses about mechanisms and empirical findings because they reveal critical internal processes that are difficult to observe directly. However, many ecosystem models are difficult to manage and apply by scientists because of complex model structures, lack of consistent documentation, and low‐level programming implementation. Here, we present the ‘ pnetr ’ R package, which is designed to provide an easy‐to‐manage ecosystem modelling framework and detailed documentation in both model structure and programming. The framework implements a family of widely used PnET (net photosynthesis, evapotranspiration) ecosystem models, which are relatively parsimonious but capture essential biogeochemical cycles of water, carbon and nitrogen. We chose the R programming language because it is familiar to many ecologists and has abundant statistical modelling resources. We showcase examples of model simulations and test the effects of phenology on carbon assimilation and wood production using data measured by the Environmental Measurement Station (EMS) eddy‐covariance flux tower at Harvard Forest, MA. We hope ‘ pnetr ’ can facilitate further development of ecological theory and increase the accessibility of ecosystem modelling and ecological forecasting.
Authors
- Xiaojie Gao (ORCID: https://orcid.org/0000-0002-0607-7768)
- Jonathan Robert Thompson (ORCID: https://orcid.org/0000-0003-0512-1226)
- Zaixing Zhou (ORCID: https://orcid.org/0000-0003-1895-0891)
- Jaclyn Hatala Matthes
- Scott V. Ollinger (ORCID: https://orcid.org/0000-0001-6226-1431)
- Wenzhe Jiao (ORCID: https://orcid.org/0000-0002-2173-4041)
Institutions
- Harvard University (US)
- University of New Hampshire (US)
- Dana-Farber/Harvard Cancer Center (US)
- Texas A&M University (US)
Publication Details
- Journal
- Methods in Ecology and Evolution
- Published
- 2025-06-09
- DOI
- https://doi.org/10.1111/2041-210x.70076
- Citations
- 1
- Primary Topic
- Forest ecology and management
- Type
- article
- Field-Weighted Citation Impact
- 2.31
Funders
- National Science Foundation
- Office of Integrative Activities
- Division of Environmental Biology
- New Hampshire Agricultural Experiment Station