High-Resolution LiDAR Reveals Scale-Dependent Links Between Forest Structure and Understory Plant Diversity Across Successional Stages

Forest structural heterogeneity is widely recognized as a key driver of biodiversity, yet its effects on different components of understory diversity across spatial scales remain insufficiently understood, particularly when assessed using high-resolution remote sensing techniques. In this study, we examined the relationship between forest structure and understory plant diversity along secondary forest succession using high-density uncrewed laser scanning (ULS) data. We derived a suite of LiDAR-based structural metrics describing canopy height, vertical heterogeneity and canopy openness, and evaluated their association with both taxonomic and functional diversity at alpha- and beta-scales, through linear mixed models and distance-based redundancy analysis. Structural metrics showed a limited explanatory power for local (alpha) diversity, with generally weak relationships across taxonomic and functional indices. In contrast, forest structure consistently explained variation in beta diversity, with canopy openness and vertical heterogeneity emerging as the strongest predictors of community dissimilarity. These findings suggest that forest structure plays a greater role in shaping differences in species composition among stands than in determining within-stand diversity. Overall, our findings highlight the potential of ULS-derived structural metrics to capture spatial patterns of understory diversity, while underscoring the importance of accounting for multiple environmental drivers and scale-dependent processes.

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Publication Details

Journal
Remote Sensing
Published
2026-06-29
DOI
https://doi.org/10.3390/rs18132099
Primary Topic
Remote Sensing and LiDAR Applications
Type
article
Field-Weighted Citation Impact
0.00

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article

High-Resolution LiDAR Reveals Scale-Dependent Links Between Forest Structure and Understory Plant Diversity Across Successional Stages

Valentino Casolo, Filip Kratoš, Giacomo Trotta, Miha Živec et al.
Remote Sensing
Remote Sensing and LiDAR Applications
article

High-Resolution LiDAR Reveals Scale-Dependent Links Between Forest Structure and Understory Plant Diversity Across Successional Stages

Valentino Casolo, Filip Kratoš, Giacomo Trotta, Miha Živec, Antonio Tomao, Martin Krůček, Kamil Král, Giorgio Alberti, Paolo Cingano, Lorenzo Orzan
article en

Abstract

Forest structural heterogeneity is widely recognized as a key driver of biodiversity, yet its effects on different components of understory diversity across spatial scales remain insufficiently understood, particularly when assessed using high-resolution remote sensing techniques. In this study, we examined the relationship between forest structure and understory plant diversity along secondary forest succession using high-density uncrewed laser scanning (ULS) data. We derived a suite of LiDAR-based structural metrics describing canopy height, vertical heterogeneity and canopy openness, and evaluated their association with both taxonomic and functional diversity at alpha- and beta-scales, through linear mixed models and distance-based redundancy analysis. Structural metrics showed a limited explanatory power for local (alpha) diversity, with generally weak relationships across taxonomic and functional indices. In contrast, forest structure consistently explained variation in beta diversity, with canopy openness and vertical heterogeneity emerging as the strongest predictors of community dissimilarity. These findings suggest that forest structure plays a greater role in shaping differences in species composition among stands than in determining within-stand diversity. Overall, our findings highlight the potential of ULS-derived structural metrics to capture spatial patterns of understory diversity, while underscoring the importance of accounting for multiple environmental drivers and scale-dependent processes.

Remote SensingVol. 18(13)
University of Udine (IT), University of Trieste (IT), Gobierno del Principado de Asturias (ES), Biodiversity Research Institute (US), Institute of Landscape Ecology of the Slovak Academy of Sciences (SK)
European Commission
Life in Land
Openalex Percentile: Top 11%
Remote Sensing and LiDAR Applications
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