Simulating long-term drought-driven forest stand dynamics in East Texas using the Forest Vegetation Simulator

Drought is a major climatic disturbance affecting forest productivity, mortality, and long-term stand development. We used the Forest Vegetation Simulator (FVS) to explore potential long-term drought effects on selected major forest types in East Texas. Forest Inventory and Analysis (FIA)/FVS-ready stand data were projected from 2001 to 2151 (150-year period) under three scenarios: control; simplified, parameterized drought-mortality; and drought plus hypothetical growth-enhancement. Simulated responses varied among the forest types. Pine-dominated and oak–pine mixed stands generally showed lower tree density, basal area, and merchantable volume under drought-mortality than under the control scenario. The largest decline in tree density occurred in mixed stands, whereas the largest reduction in merchantable volume occurred in pine-dominated stands. In contrast, hardwood-dominated stands showed small simulated increases in these attributes under drought-mortality. This counterintuitive response is interpreted cautiously as a model-derived outcome potentially influenced by initial stand structure, species composition, competition dynamics, regeneration assumptions, and drought parameterization. The hypothetical growth-enhancement scenario partially offset drought-related reductions in pine and oak–pine mixed stands, particularly in merchantable volume, but had limited effects in hardwood stands. This scenario represents a user-defined diameter-growth modification rather than an explicit silvicultural treatment. Overall, the simulations suggest that drought-related stand responses may differ among forest types and that enhanced residual growth could partially offset some negative drought effects under simplified assumptions. Because the analysis used selected representative stands, parameterized drought assumptions, and unvalidated long-term projections, the results should be interpreted as exploratory scenario-based comparisons rather than definitive forecasts.