Quantification of leaf area index (LAI) is essential for understanding forest productivity and the atmosphere–vegetation interface, where the majority of gas and energy exchange occurs. LAI is one of the most difficult plant variables to adequately quantify, owing to large spatial and temporal variability, and few studies have examined the horizontal and vertical distribution of LAI in forest ecosystems. In this study, we demonstrated the LAI distribution in each layer from the understory to canopy using multiple-point measurements (121 points) and examined the relationships among layers in a cool-temperate deciduous forest. LAI at each point, and the spatial distribution of LAI in each layer, varied within the forest. The spatial distribution of LAI in the upper layer was more heterogeneous than that of LAI at the scale of the entire forest. Significant negative correlations were observed between the upper- and lower-layer LAI. Our results indicate that the understory compensates for gaps in LAI in the upper layer; thus, the LAI of the entire forest tends to remain spatially homogeneous even in a mature forest ecosystem.

Understory trees occupy a spatially heterogeneous light environment owing to light interception by patchily distributed canopy leaves. We examined the spatial distribution of canopy leaves and the spatial structure of the understory tree community (height < 5 m) and their relationships in a beech forest in Nagano, Japan. We measured the canopy leaf area index (LAI) at 10 m intervals (n = 81) in a permanent research plot (1 ha). We established a circular subplot centered on each LAI measurement point, and determined the species composition and the aboveground net primary production of wood (ANPPW) of the understory tree community by using tree size data from an open database in the Monitoring Sites 1000 project. There was a significant negative correlation between canopy LAI and the ANPPW of understory trees and a significant positive correlation between the ANPPW of understory and understory tree density. The dominant species of understory trees differed between subplots with high and low LAI values. Our results suggest that niche differentiation allows trees in the understory community to make use of various light conditions, thereby enhancing the primary productivity of the entire community.

Recent developments in Unmanned Aerial Vehicles (UAVs) and Light Detection and Ranging (LiDAR) technology have enhanced the ability to capture precise three‐dimensional forest information at a lower cost. This article reports four types of high‐resolution digital datasets derived from UAV‐LiDAR measurements and associated fieldwork. The dataset includes 5 cm resolution Digital Terrain Models (DTMs) and Canopy Height Models (CHMs), ortho‐mosaic photos with sub‐2.7 cm resolution, and 4328 tree crown polygons with information on 151 species, stem girth at breast height, and canopy height. Data were collected from 22 approximately 1‐ha long‐term monitoring plots across Japan, spanning major climate zones from subtropical to subarctic. These plots encompass evergreen conifer, broadleaf and conifer mixed, deciduous broadleaf, and evergreen broadleaf forests. UAV surveys were conducted from May 2022 to October 2023. Based on these data, we also report basic profiles of these natural forests: a median slope of 22.2° (ranging from 2.5° to 35.0° across sites), median canopy height of 19.2 m (10.5–25.2 m), median maximum canopy height of 29.4 m (17.6–39.8 m), median gap ratios of 1.7% (0–10.7%) and 7.7% (0–28.9%) depending on gap definitions, and median crown area of 42.9 m ² (10.7–80.2 m ² ) for canopy trees. This dataset is the first publicly available collection of forest structure and individual tree crown information for Japanese natural forests. We hope this dataset will be useful for a wide range of studies and analyses, from site‐specific case studies to global‐scale meta‐analyses. The metadata is available in MetaCat in JaLTER at https://jalter.diasjp.net/data/ERDP-2025-04 .