Vegetation Structural Complexity Across Tenerife's Zonal Vegetation Types Captured by Terrestrial Laser Scanning

ABSTRACT Questions Vegetation structural complexity, defined as the density and distribution of plants in three‐dimensional (3D) space, is a key ecological property of plant communities, influencing biodiversity and ecosystem functioning. Yet, how vegetation structural complexity varies across contrasting vegetation types, and which factors drive this variation remain poorly understood. This knowledge gap is particularly relevant on oceanic islands, where diverse vegetation types occur across steep environmental gradients and are often highly vulnerable to disturbance. Specifically, we asked (1) how does vegetation structural complexity vary across and within‐vegetation types, (2) by which structural dimensions do the vegetation types most differ, and (3) which climatic factors explain this variation. Location Tenerife, Canary Islands. Methods With 140 scans in 28 plots covering 6 major zonal vegetation types, we derived the Stand Structural Complexity Index (SSCI), which measures the 3D arrangement of vegetation, and other metrics related to vertical stratification, vegetation density and canopy openness, captured by terrestrial laser scanning (TLS) 3D point clouds. For each metric, mean values and coefficient of variation (CV) per plot were analysed with a permutation analysis of variance (ANOVA) and a principal component analysis (PCA). The relationship with long‐term climatic plot data was analysed using robust linear models. Results The SSCI differed significantly across zonal vegetation types (permutation ANOVA, p < 0.001). The SSCI ranged from a high mean value and low variability in laurel forests (mean = 7.00, CV = 10.1%) to the lowest mean value in the summit scrub (mean = 2.65, CV = 65.6%) but highest variability in the tabaibal coastal scrub (mean = 4.93, CV = 91.0%). PCA indicates that vegetation structural complexity in forests was characterised by high vertical stratification and a closed canopy. In contrast, scrub types displayed greater canopy openness and a high variation in 3D vegetation density. Greater annual precipitation was associated with a linear increase in SSCI across zonal vegetation types, positively related to increased vertical stratification and canopy height and negatively related to canopy openness and 3D vegetation density. Conclusions Our results suggest that TLS‐derived metrics of vegetation structural complexity capture within and across vegetation type variation. The SSCI can provide meaningful information beyond forests when interpreted alongside other structural metrics. Our results suggest that differences across vegetation types are associated with climatic gradients. This study provides a basis for future studies and applications of TLS beyond forests that can aid biodiversity monitoring and conservation of environmentally distinct and disturbance‐prone island vegetation.

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Journal
Journal of Vegetation Science
Published
2026-10-30
DOI
https://doi.org/10.1111/jvs.70189
Primary Topic
Remote Sensing and LiDAR Applications
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article
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article

Vegetation Structural Complexity Across Tenerife's Zonal Vegetation Types Captured by Terrestrial Laser Scanning

José María Fernández‐Palacios, Rüdiger Otto, Natalia Sierra Cornejo, Delphine Clara Zemp et al.
Journal of Vegetation Science
Remote Sensing and LiDAR Applications
article

Vegetation Structural Complexity Across Tenerife's Zonal Vegetation Types Captured by Terrestrial Laser Scanning

José María Fernández‐Palacios, Rüdiger Otto, Natalia Sierra Cornejo, Delphine Clara Zemp, Lea de Nascimento, Nathaly R. Guerrero‐Ramírez, Martin Ehbrecht, Samantha Suter, Holger Kreft, Felipe Rodríguez‐Arvelo
article en

Abstract

ABSTRACT Questions Vegetation structural complexity, defined as the density and distribution of plants in three‐dimensional (3D) space, is a key ecological property of plant communities, influencing biodiversity and ecosystem functioning. Yet, how vegetation structural complexity varies across contrasting vegetation types, and which factors drive this variation remain poorly understood. This knowledge gap is particularly relevant on oceanic islands, where diverse vegetation types occur across steep environmental gradients and are often highly vulnerable to disturbance. Specifically, we asked (1) how does vegetation structural complexity vary across and within‐vegetation types, (2) by which structural dimensions do the vegetation types most differ, and (3) which climatic factors explain this variation. Location Tenerife, Canary Islands. Methods With 140 scans in 28 plots covering 6 major zonal vegetation types, we derived the Stand Structural Complexity Index (SSCI), which measures the 3D arrangement of vegetation, and other metrics related to vertical stratification, vegetation density and canopy openness, captured by terrestrial laser scanning (TLS) 3D point clouds. For each metric, mean values and coefficient of variation (CV) per plot were analysed with a permutation analysis of variance (ANOVA) and a principal component analysis (PCA). The relationship with long‐term climatic plot data was analysed using robust linear models. Results The SSCI differed significantly across zonal vegetation types (permutation ANOVA, p < 0.001). The SSCI ranged from a high mean value and low variability in laurel forests (mean = 7.00, CV = 10.1%) to the lowest mean value in the summit scrub (mean = 2.65, CV = 65.6%) but highest variability in the tabaibal coastal scrub (mean = 4.93, CV = 91.0%). PCA indicates that vegetation structural complexity in forests was characterised by high vertical stratification and a closed canopy. In contrast, scrub types displayed greater canopy openness and a high variation in 3D vegetation density. Greater annual precipitation was associated with a linear increase in SSCI across zonal vegetation types, positively related to increased vertical stratification and canopy height and negatively related to canopy openness and 3D vegetation density. Conclusions Our results suggest that TLS‐derived metrics of vegetation structural complexity capture within and across vegetation type variation. The SSCI can provide meaningful information beyond forests when interpreted alongside other structural metrics. Our results suggest that differences across vegetation types are associated with climatic gradients. This study provides a basis for future studies and applications of TLS beyond forests that can aid biodiversity monitoring and conservation of environmentally distinct and disturbance‐prone island vegetation.

Journal of Vegetation ScienceVol. 37(6)
Universidad de La Laguna (ES), University of Neuchâtel (CH), University of Göttingen (DE)
Openalex Percentile: Top 22%
Remote Sensing and LiDAR Applications
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