Short-term impacts of pruning on crown development and stem growth revealed by dual-temporal terrestrial laser scanning in Larix olgensis plantations

Understanding how pruning regulates the short-term structural development of plantation-grown industrial tree species is essential for improving cultivation practices and enhancing the productivity of forest-based raw materials. Conventional approaches for assessing tree growth rely on repeated field measurements or destructive sampling, which are limited in their ability to capture fine-scale and dynamic changes in crown architecture. Terrestrial laser scanning (TLS) provides a non-destructive, high-resolution alternative for quantifying tree structural attributes and their temporal variation, offering new opportunities to evaluate growth responses to silvicultural interventions. This study investigated short-term structural adjustments following pruning in a Larix olgensis plantation using dual-temporal TLS point cloud data collected in 2021 (T1) and 2024 (T2). Pruning treatments removed 0% (CK), 20% (LP), 30% (MP), or 40% (HP) of the live crown. Tree structural traits were automatically extracted from the TLS data, and increments of crown metrics—crown volume (ΔCV), crown surface area (ΔCSA), crown width (ΔCW), crown projection area (ΔCPA), and height increment (ΔH)—and stem metrics—basal area increment (ΔBA) and stem volume increment (ΔSV)—were quantified. Pruning intensity significantly increased ΔH, ΔCV, and ΔCSA, while ΔBA, ΔSV, ΔCW, and ΔCPA showed no statistically detectable response three years later. Positive relationships were observed between crown and stem growth, though the strength of these associations varied across pruning intensities, indicating treatment-dependent coupling between aboveground structural components. Mixed-effects modeling identified ΔCV and ΔCW as the strongest predictors of stem growth. Accounting for variation among pruning intensities by including random effects improved predictive performance for ΔBA and ΔSV by 8.3% and 4.6%, respectively. Overall, this study demonstrates that time-series TLS can effectively detect subtle, pruning-induced structural dynamics in industrial plantation trees. These findings advance the application of 3D phenotyping technologies in forest cultivation and contribute to improved management strategies for enhancing the growth performance of industrial forest crops. • Multi-temporal TLS reveals pruning-induced short-term crown and stem growth dynamics. • Pruning intensity strongly influences tree height and crown development. • Stem growth closely tracks crown growth, with effects varying by pruning level. • Crown volume and width effectively predict stem growth, aiding forest management decisions.