Potential of individual-scale phenological measurements for improving wood productivity and maintaining genetic diversity in forest management
Abstract
Early budburst can improve tree growth by extending the photosynthetic period. However, studies linking budburst timing to biomass accumulation have focused on seedlings or saplings, rather than mature trees because of observer limitations and throughput. Cameras are more suited to landscape-scale than tree-scale applications. In this study, we developed an innovative method for quantifying budburst timing in mature trees at the individual-tree scale by combining remote sensing techniques, specifically laser scanning, unmanned aerial vehicles, multispectral cameras, and data analysis. To assess the long-term implications of phenological variation, we investigated the relationship between current phenological traits and lifetime growth in an even-aged population of mature Larix trees. We analyzed 134 trees (aged 60 years) to examine the correlations among spring leaf-out timing, leaf-out duration, autumn leaf coloring timing, leaf coloring duration, current tree height, breast height diameter, and early growth records. The trees that leafed earlier or had a longer leaf-out duration were taller, suggesting a cumulative effect of early budburst on growth. Genetic factors weakly influenced the relationship between early budburst and growth, suggesting that factors other than genetic factors may be crucial. These results do not contradict the hypothesis that earlier budbursts, potentially induced by long-term climate change, contribute to increased biomass accumulation. In contrast to budburst phenology, our results showed high heritability for autumn leaf coloring phenology. Our findings suggest that individual-scale phenological measurements in forest management could support both higher wood productivity and conservation of genetic diversity under changing climatic conditions.
Fields of Study & Subjects
Wood Treatment and Properties
Plant Water Relations and Carbon Dynamics
Remote Sensing and LiDAR Applications
Publication details
- Journal / source
- Forest Ecology and Management
- Volume
- 615
- Pages
- 123814–123814
- Publication date
- 6 May 2026
- Language
- EN