Work

High-resolution Automatic Dendrometer-based Time Series Data for Three Temperate Tree Species in Mt. Jeombong, Korea in 2024

Year: 2025

Type: article

Abstract: Long-term ecological research (LTER) provides an essential foundation for understanding ecosystem responses to climate change and environmental disturbances. Traditional dendrometry, based on one or two manual diameter breast height measurements per year, cannot capture short-term or seasonal growth fluctuations, highlighting the need for automated high-frequency monitoring. In Korea, however, high-resolution stem growth data for dominant temperate tree species remain scarce at the national scale. To address this gap, systematic high-resolution stem growth monitoring has been carried out at Mt. Jeombong since 2024, a core site of the “National Long-Term Ecological Research in Korea” program. This dataset presents high-resolution stem radial growth measurements for three representative temperate tree species (Quercus mongolica, Acer pseudosieboldianum, and Carpinus laxiflora) in the deciduous oak forest near the ecological observation tower in Mt. Jeombong. Automatic point dendrometers generated stem radial displacement and temperature measurements at 10-minute intervals for the entire year of 2024. From the raw measurements, hourly values were extracted and subsequently averaged to generate daily mean time series for visualization and interpretation. Analysis of the 2024 dataset showed that the three species exhibited broadly similar seasonal patterns of growth initiation, stabilization, and cessation, although some interspecific and individual-level differences were observed. Integrating these measurements with climate and other environmental variables is expected to yield deeper insights into the physiological drivers of these growth dynamics. Furthermore, the continuous radial growth data serve as valuable input for estimating stem carbon accumulation and improving assessments of forest net primary productivity. Long-term accumulation of comparable datasets will contribute to detecting climate-driven shifts in growth timing and carbon dynamics in Korean temperate forests.

Source: GEO DATA

DOI: 10.22761/gd.2025.0080

Author: Jaeyeon Lee

Institution: National Institute of Ecology

Language: English

Topic: Forest ecology and management

Subfield: Nature and Landscape Conservation

Field: Environmental Science

Domain: Physical Sciences

SDG: Life on land

Open Access status: diamond

Funder: National Institute of Ecology