Integrating 3D Canopy Reconstruction to Assess Photosynthetic and Carbon Sequestration Responses of Larch Plantations to Drought Stress

Forest phenotypic responses are significantly influenced by extreme climate conditions, particularly canopy structure and photosynthetic traits. However, the underlying mechanisms driving these responses, especially in conifer species, remain poorly understood. This study employs advanced phenotyping technologies, combining three-dimensional (3D) canopy reconstruction with high-resolution physiological trait analysis, quantifying changes in key physiological traits that light interception, gas exchange parameters stomatal conductance, and chlorophyll content. Developing 3D reconstruction algorithms tailored to conifer canopies is essential for simulating forest ecosystem responses under varying canopy densities. We investigate the following questions: (1) How does thinning affect canopy light penetration and photosynthetic efficiency? Thinning significantly increased light penetration from 15 ​% (CK) to 22 ​%, enhancing photosynthetic efficiency, resulting in an 18 ​% increase in carbon absorption under drought conditions. (2) How does reduced-rainfall affect photosynthetically active radiation (PAR) and stomatal conductance? Reduced-rainfall caused a 12 ​% decrease in PAR, a 20 ​% reduction in stomatal conductance, and an 8 ​% decrease in chlorophyll content. (3) What are the synergistic effects of thinning and reduced-rainfall in carbon absorption? Thinning under reduced-rainfall increased carbon absorption by 25 ​%. This study reveals a significant correlation between chlorophyll content, leaf nitrogen content, and canopy structural dynamics under drought and elevated temperature conditions, offering new insights into the adaptive mechanisms plants employ to adjust their photosynthetic processes. In conclusion, the development of 3D reconstruction algorithms tailored for conifer canopies, in regulating photosynthetic traits, is crucial for improving forest adaptation, contributing to functional trait-based forest management and ecosystem modeling.