Quantifying canopy structural traits in agroforestry systems through Terrestrial Laser Scanning: A case study in cocoa-based agroforestry systems

Abstract

Agroforestry systems might contribute to balance some of the production, environmental and social challenges associated with agricultural intensification in tropical regions. However, the intricate functional dynamics within agroecosystems, combined with their diverse objectives, make it difficult to maximise productivity and identifying factors that constrain crop yields. Canopy structural traits strongly influence light distribution in agroforestry systems, affecting crop variability in light-use efficiency and productivity. Yet, information on 3D vegetation structure in agroforestry systems remains scarce, despite its potential to provide valuable information to better understand the functional complexity of these systems. Our workflow overcome this limitation by incorporating Terrestrial Laser Scanning (TLS) technology and a voxelization approach for light ray tracing (AMAPVox). In this context, this study aims to determine how TLS data, processed using a voxelization approach, can be applied in multi-strata agroforestry systems to quantify the three-dimensional (3D) distribution of Plant Area Density (PAD) across vegetation strata and the total Plant Area Index (PAI). We used detailed multi-scan voxelized data from 28 experimental plots established in Côte d’Ivoire with different species compositions and planting arrangements to quantify the 3D distribution of PAD and key structural traits (PAI, light attenuation and transmittance) at multiple spatial resolutions. Validation with estimates of light measurements based on hemispherical photographs at tree level showed a high level of concordance (R² > 0.42; p-value < 0.05) in estimating plant area index (PAI). Species composition, rather than planting arrangement, notably influenced the vertical distribution of PAD and canopy structural traits. PAI in the plots ranged from 4.94 m² m⁻² to 22.31 m² m⁻². The proposed approach, using TLS data and a voxel-based methodology, enables high-resolution modelling of canopy structural traits in multi-strata agroforestry systems. These results provide highly detailed measurements of key crop yield indicators, allowing decision support to develop management activities that increase crop production while minimising inputs and maintaining ecosystem services.

Plant phenotyping relevance

TLSとボクセル化によるワークフローを用いて、植物群落の3D構造形質（PAD、PAI、光減衰・透過）を定量化し、光学測定で検証しているため、植物フェノタイピング手法が中心である。

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