Long-term prediction of wound closure in residual damaged trees using Markov chain analysis

Abstract

Understanding the wound healing dynamics in damaged residual trees along skid trail margins is important for maintaining stand health and minimizing financial losses during final harvesting. This study deployed a Markov chain decision process to model wound healing times, integrating complex treatments of trail design factors (traffic intensity, decommissioning age) and wound characteristics (severity) to inform postharvest management strategies, including retaining or early thinning interventions before residual trees exceed their biological longevity. Data on wound size and healing rates were collected from standing residual trees along four abandoned skid trails in mixed hardwood forests subjected to ground-based skidding operations in northern Iran. Healing times varied significantly, ranging from 39 years for trees on recently decommissioned trails (<5 yrs) to 54 years for those on older trails (>15 yrs), influenced by wound severity and traffic levels. Light-bark wounds healed within 20 years, while severe wounds influencing the phloem or fibre required up to 60 years. Increased traffic intensity was associated with more severe damage and extended healing times, with trees adjacent to lightly trafficked trails recovered within 50 years, compared to up to 70 years for those near heavily trafficked trails. This study validates the utility of Markov chain models in predicting wound healing durations and informing postharvest management decisions. Given the extended healing times (50–70 yrs) and the risk of infection spread, strategic skid trail planning, employment of skilled operators, and periodic thinning interventions are recommended to maintain the health and economic value of damaged residual trees.