Modeling the growth and yield of natural hardwood stands in the southern United States using the Forest Inventory and Analysis data
Growth and yield models (GYMs) are essential for sustainable forest management and silvicultural decisions. However, most stand-level models rely on age and related variables like site index, which are often unavailable for natural hardwood stands. To address this, we developed GYMs for natural hardwood stands independent of age, using differential equations that relate the rate of change in ingrowth, mortality, and survivor growth to the initial stand conditions. Data from 1540 permanent plots in the Forest Inventory Analysis (FIA) program across the southern United States were used to develop the systems of differential equations (SDE) for some important forest types. The numerical solution of these SDEs provided predictions of stand attributes over time, which were used to obtain diameter distributions. We evaluated the SDE using an independent FIA dataset from Tennessee, and the results showed strong consistency, with predicted stand attributes such as basal area, density, sum of diameters, and volume aligning closely with observed values. Stand development after two prescribed cuttings produced patterns expected of a natural stand. Further application of the SDE to even-aged thinned stands produced reliable estimates comparable to those from an existing simulator. The SDE can be implemented in both mixed-age and even-aged stands. • Developed age-independent growth and yield models for natural hardwood stands. • The predicted stand attributes from the models were consistent with those observed. • Stand growth after prescribed cuts followed the expected pattern of a natural stand. • The models apply to mixed-age and even-aged stands in the southern United States.
Authors
- Philip J. Radtke (ORCID: https://orcid.org/0000-0002-8921-8406)
- P. Corey Green
- Friday Nwabueze Ogana (ORCID: https://orcid.org/0000-0002-8388-204X)
Institutions
- Virginia Tech (US)
Publication Details
- Journal
- Forest Ecology and Management
- Published
- 2025-04-17
- DOI
- https://doi.org/10.1016/j.foreco.2025.122722
- Citations
- 4
- Primary Topic
- Forest ecology and management
- Type
- article
- Field-Weighted Citation Impact
- 9.25