Small Diameter and Decreased Radial Growth Control Pinus palustris Tropical Cyclone Damage in Georgia, USA
Year: 2026
Type: article
Abstract: Traditional correlative analyses often struggle to parse the confounding drivers of storm damage in forested systems. To address this limitation, this study utilized a causal inference framework to separate broad observational trends from underlying biological mechanisms. We applied a non-parametric causal forest algorithm to evaluate how diameter at breast height (DBH) and DBH growth rates influenced tree-level damage probabilities in even-aged longleaf pine ( Pinus palustris Mill.) plantations following Hurricane Helene (2024). The data were from two contrasting sites, an old-field and a cutover plantation, in Berrien County, Georgia, USA, ranging from 5 to 24 cm DBH. Pre-tropical cyclone correlative analysis showed that the old-field site possessed greater aboveground productivity, like increased DBH, height, volume, and basal area. Post-cyclone analysis revealed that while aboveground trends remained, the old-field site suffered a 17% reduction in stand density. While a simple correlative assessment would likely attribute this decline entirely to the vulnerability of larger trees, the causal forest model parsed a more nuanced storm damage response. Specifically, smaller trees (< 12 cm DBH; 1.69 to 8.06 m height) demonstrated high sensitivity to moderate stem damage, while larger, slower-growing individuals (> 12 cm DBH; 10.09 to 12.17 m height) were more susceptible to severe stem failure. These results highlight proactive density management - specifically tailored to maintain increased individual tree growth rates - as a critical tool for building wind resilience in southern pine plantations. Additionally, causal inference applied to site-intensive inventory data provided a precise, data-centered understanding of storm-induced mortality dynamics.
Source: Forest Science
Language: English
Subfield: Forestry
Domain: Life Sciences
Open Access status: hybrid
Estimated APC paid: $2,690
OpenAlex ID: W7225778619