Ryuichi Takeshige

Summary: Elucidating interspecific variation in growth strategies across environments is critical for understanding tree diversity and distribution. However, a systematic analysis across diverse forests remains scarce due to limited large-tree crown measurements. We analysed 3,814 trees from 107 canopy species in 23 natural forests using forest census data and unmanned aerial vehicle. Relative growth rate (growth rate/biomass) was decomposed into growing space efficiency (growth rate/crown area) and crown area ratio (crown area/biomass). Relative growth rates were similar among functional groups (deciduous broadleaf, evergreen broadleaf, evergreen conifer), but their underlying components differed. Deciduous trees exhibited 34–43% higher crown area ratio but 24–27% lower growing space efficiency than evergreen broadleaf and conifer trees. Across environments, growing space efficiency correlated positively with mean annual temperature, likely from extended growing seasons while crown area ratio correlated negatively, particularly in deciduous species. Snow loading limited crown area ratio in evergreen species, while deciduous achieved higher values through avoiding snow loads. Correlation between crown area ratio and specific leaf area indicated a coordinated strategy between crowns and leaves. Different functional groups achieve comparable growth efficiency either through crown expansion or biomass production, explaining their distinct distribution as well as co-occurrence across broad environments.

Woody canopies regulate exchanges of energy, water and carbon, and their three-dimensional (3D) structure supports much of terrestrial biodiversity. Remote sensing technologies such as airborne laser scanning (ALS) now enable the 3D mapping of entire landscapes. However, we lack the large, harmonized and geographically representative ALS collections needed to build a global picture of woody ecosystem structure. To address this challenge, we developed the Global Canopy Atlas (GCA): 3,458 ALS acquisitions transformed into standardized and analysis-ready maps of canopy height and elevation at 1 m ² resolution. The GCA covers 56,554 km ² across all major biomes. 19% of this area has been scanned multiple times, and 87% of all GCA products are openly available, covering 95% of the total area. To showcase its wide range of applications, we applied the GCA in three case studies. First, we validated three global satellite-derived canopy height maps, finding poor performance at native resolution (1-30 m, R ² < 0.38) and moderate performance at 250 m resolution (R ² < 0.65). Second, analyzing global patterns in canopy gap size frequency we discovered an unexpectedly large variation of power law exponents from branch to stand level (α = 1.52 to 2.38), pointing to a fundamental scale-dependence of forest structure. Third, we developed a framework to standardize forest turnover quantification from multi-source, multi-temporal ALS. In a temperate forest in North America it revealed that 21% of canopy gaps closed within 12 years of opening and would thus be missed by infrequent monitoring. As demonstrated by these case studies, the GCA provides a novel data source for ecologists, foresters, remote sensing scientists and the ecosystem modelling community that substantially advances our ability to understand the structure and dynamics of woody ecosystems at global scales.

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 .

Tropical secondary forests are widespread in the anthropogenically modified landscapes. Because tropical secondary forests were known to show a steady rate of above-ground biomass (AGB) recovery, they were expected to play a crucial role in carbon sequestration. However, in a preliminary survey of logged-over forests in Borneo, some patches covered with ferns and vines do not seem to recover steadily despite the fact that several decades have passed since the last logging. The presence and abundance of fern/vine thickets may affect the AGB recovery, but few studies have investigated the effects of the thickets. We established a total of seventeen 20-m radius circular plots in logged-over forests, Sabah, Malaysia, with a varying degree of fern/vine coverage, and tested the hypothesis that the greater fern/vine coverage would retard the AGB recovery. The net AGB accumulation rate from 2014 to 2019 was lower in the forests with a higher fern/vine coverage. Our lower bound of the accumulation rate was much lower than the previously reported rates elsewhere. The number of newly recruited and small-diameter trees was lower, and the mortality of remnant trees was higher with increasing fern/vine coverage. The growth rate of the extant pioneer trees, which are expected to significantly contribute to the initial build-up phase of the secondary succession, was inhibited when ferns and vines covered the canopy. Our study suggests that the secondary succession is arrested and the recoverability of forest stands is lower than formerly predicted when they are covered by thick ferns and vines.

Forest degradation has been most frequently defined as an anthropogenic reduction in biomass compared with reference biomass in extant forests. However, so-defined “degraded forests” may widely vary in terms of recoverability. A prolonged loss of recoverability, commonly described as a loss of resilience, poses a true threat to global environments. In Bornean logged-over forests, dense thickets of ferns and vines have been observed to cause arrested secondary succession, and their area may indicate the extent of slow biomass recovery. Therefore, we aimed to discriminate the fern thickets and vine-laden forests from those logged-over forests without dense ferns and vines, as well as mapping their distributions, with the aid of Landsat-8 satellite imagery and machine learning modeling. During the process, we tested whether the gray-level co-occurrence matrix (GLCM) textures of Landsat data and Sentinel-1 C-band SAR data were helpful for this classification. Our study sites were Deramakot and Tangkulap Forest Reserves—commercial production forests in Sabah, Malaysian Borneo. First, we flew drones and obtained aerial images that were used as ground truth for the supervised classification. Subsequently, a machine-learning model with a gradient-boosting decision tree was iteratively tested in order to derive the best model for the classification of the vegetation. Finally, the best model was extrapolated to the entire forest reserve and used to map three classes of vegetation (fern thickets, vine-laden forests, and logged-over forests without ferns and vines) and two non-vegetation classes (bare soil and open water). The overall classification accuracy of the best model was 86.6%; however, by combining the fern and vine classes into the same category, the accuracy was improved to 91.5%. The GLCM texture variables were especially effective at separating fern/vine vegetation from the non-degraded forest, but the SAR data showed a limited effect. Our final vegetation map showed that 30.7% of the reserves were occupied by ferns or vines, which may lead to arrested succession. Considering that our study site was once certified as a well-managed forest, the area of degraded forests with a high risk of loss of resilience is expected to be much broader in other Bornean production forests.

Logged-over forests are widespread in SE Asia, and these forests vary greatly in tree-community composition ranging from a near pristine to a greatly modified forest due to repeated high-impact logging. It is a critical concern in terms of forest management and conservation whether modified forests can recover to their original states. However, greatly modified forests may lose the resilience due to the lack of next-generation seedlings. We examined the regeneration potential of Shorea, a dominant genus in pristine forests, in various forests ranging from pristine to degraded forests, and investigated the relationship between the tree-community composition in canopy layer and the regeneration potential in north Borneo. In non-metric multidimensional scaling (nMDS) analysis based on the tree-community composition at genus level, 31 study plots were sorted in the order from pristine to degraded forests along the axis-1 with decreasing the axis-1 scores, and this score was used as a metric of forest intactness. Size distribution of Shorea trees combining all congeneric species showed an inverse-J shape in most plots excluding some degraded forests. The skewness of size distribution was high in pristine forests but remarkably decreased in degraded forests. The skewness reflected the abundance of seedlings in the population of Shorea trees, and it was an important metric indicating regeneration potential. The number of seedlings also decreased abruptly with decreasing forest intactness along the nMDS axis-1. The reduction in these two metrics suggests that regeneration potential is abruptly lost when the forest intactness in terms of tree-community composition is decreasing.