樹木の日陰耐性を測定する新たな定量モデルを開発(Scientists Develop New Quantitative Model to Measure Tree Shade Tolerance)

2025-09-15 中国科学院（CAS）

中国科学院応用生態研究所の朱教君院士率いるチームは、樹木の耐陰性を定量化する新モデルを開発しました。耐陰性は森林の種構成や遷移、植林樹種選定に不可欠ですが、従来の分類は定性的で精度が不十分でした。研究者らは地上型レーザースキャニング（TLS）を用い、23種の広葉樹の葉傾斜角（LIA）を高精度に測定。クラスタ解析により5段階の耐陰性カテゴリーを設定しました。さらに「相対耐陰性指数（RSTI）」を提案し、0～1の連続値で種の耐陰性を表現。61種で検証したところ、予測精度は83.6％に達しました。RSTIは森林構造データの精度向上と樹種管理に役立ち、実務応用性の高い指標を提供します。成果はForest Ecology and Management誌に掲載されました。

＜関連情報＞

広葉樹種の葉傾斜角と温帯林における樹木の日陰耐性推定への応用（中国東北部） Leaf inclination angle of broadleaved tree species and its application on estimating tree shade tolerance in temperate forests, Northeast China

Qingda Chen, Jiaojun Zhu, Tian Gao, Jingcheng Luo, Jinxin Zhang, Shuangtian Li
Forest Ecology and Management Available online: 16 August 2025
DOI:https://doi.org/10.1016/j.foreco.2025.123076

Highlights

Terrestrial laser scanning on towers enabled comprehensive crown data collection.
Leaf inclination angle (LIA) of 23 species were quantified based on point cloud data.
A novel method was proposed to quantitatively classify shade tolerance based on LIA.
We create relative shade tolerance index to predict tree shade tolerance continuously.

Abstract

Tree shade tolerance, the minimum light requirement for tree survival, is crucial for understanding forest community dynamics, affecting species composition, forest structure, and succession processes. However, current methods for estimating shade tolerance are qualitative, which may produce unreliable results. Therefore, it is imperative to propose a quantitative classification method. Leaf inclination angle (LIA) has been recognized as a feasible parameter for indicating trees’ strategies for optimizing light interception and is closely linked to shade tolerance. However, adequate measurement of LIA has been challenged due to limited access to complete canopy leaf data. Here, we determined the LIA of 23 broadleaved tree species in temperate forests using the point cloud data that was obtained along canopy heights via terrestrial laser scanning (TLS) system with the towers-platforms. Then, we quantified their shade tolerance based on LIA characteristics. The LIA estimation demonstrated a high level of accuracy compared to manual calibration (R²=0.92, rRMSE=6.83 %). The 23 tree species were classified into five categories (strong shade-intolerant, shade-intolerant, intermediate shade-tolerant, shade-tolerant, and strong shade-tolerant) through hierarchical clustering analysis based on their LIA values and vertical distribution patterns. To further universalize and quantify shade tolerance, we proposed “relative shade tolerance index (RSTI)” based on LIA range of 18°-87° (RSTI as 1 when LIA=18°, as 0 when LIA=87°) and developed a model (RSTI=14.58 ×LIA^−0.84, R²=0.97, rRMSE=2.36 % and AIC=-195.87) to quantify the shade tolerance with a continuous function by using the 23 tree species in our study (LIA range 30°-50°). Model validation with published LIA data from 61 temperate broadleaved species (9 species with LIA=18°-29°, 35 species with LIA=30°-50°, and 17 species with LIA=51°-87°) yielded a robust prediction accuracy (83.61 %). The study provides an insightful method for quantifying tree shade tolerance, which can be applied in identifying the shade tolerance of tree species in temperate forests.