Forest Regeneration in Earth System Models

Are Earth system models representing forest regeneration well enough?

Figure of forest regeneration processes.

Forest regeneration is a series of environmentally sensitive processes that culminate in tree recruitment. Environmental variables act as filters (depicted as varying sieve mesh sizes) that impose constraints on each process.

[Reprinted with permission from Hanbury-Brown, A.R., et al. "Forest Regeneration Within Earth System Models: Current Process Representations and Ways Forward." New Phytologist 235(1), 20–40 (2022). DOI:10.1111/nph.18131. © 2023 John Wiley & Sons Ltd.]

The Science

Forest regeneration processes are generally not well represented in models ecologists use to predict future forests. A team of researchers critically reviewed how regeneration processes are represented within models that strive to predict forest demography in Earth system models. The researchers found a need to improve parameter values and algorithms for reproductive allocation, dispersal, environmental filtering in the seedling layer, and tree regeneration strategies adapted to wind, fire, and anthropogenic disturbance regimes.

The Impact

Vegetation demographic models represent forest dynamics in the Earth system, providing the opportunity to integrate ecological understanding into predictions of future climate and ecosystems. In this study, researchers identify critical areas where models are not prepared to capture future forest responses to global change variables like changing precipitation and disturbance. This review helps modelers identify necessary improvements and field ecologists understand what data best supports model improvement. Improving models will advance our ability to predict the role that forests will play in sequestering and storing carbon, providing habitat for biodiversity, and provisioning critical natural resources for people.

Summary

Earth system models must predict forest responses to global change in order to simulate future global climate, hydrology, and ecosystem dynamics. These models are increasingly adopting vegetation demographic approaches that explicitly represent tree growth, mortality, and recruitment, enabling advances in the projection of forest vulnerability and resilience, as well as evaluation with field data. To date, simulation of regeneration processes has received far less attention than simulation of processes that affect growth and mortality despite its critical role in maintaining forest structure, facilitating turnover in forest composition over space and time, enabling recovery from disturbance, and regulating climate-driven range shifts. This critical review of regeneration process representations within current Earth system vegetation demographic models reveals the need to improve parameter values and algorithms for reproductive allocation, dispersal, seed survival and germination, environmental filtering in the seedling layer, and tree regeneration strategies adapted to wind, fire, and anthropogenic disturbance regimes. These improvements require synthesis of existing data, specific field data collection protocols, and novel model algorithms compatible with global scale simulations. Vegetation demographic models offer the opportunity to integrate ecological understanding more fully into Earth system prediction, including a critical focus on regeneration processes.

Principal Investigator

Adam Hanbury-Brown
University of California, Berkeley
[email protected]

Program Manager

Brian Benscoter
U.S. Department of Energy, Biological and Environmental Research (SC-33)
Environmental System Science
[email protected]

Funding

This research was supported as part of the Next-Generation Ecosystem Experiments-Tropics (NGEE-Tropics) and was funded by the Biological and Environmental Research (BER) Program within the U.S. Department of Energy’s (DOE) Office of Science. The lead author also received support from the National Science Foundation and NASA during this research.

References

Hanbury-Brown, A.R., et al. "Forest Regeneration Within Earth System Models: Current Process Representations and Ways Forward." New Phytologist 235 (1), 20-40  (2022). https://doi.org/10.1111/nph.18131.