Exploring the branch wood supply potential of an agroforestry system with strategically designed harvesting interventions based on terrestrial LiDAR data
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Exploring the branch wood supply potential of an agroforestry system with strategically designed harvesting interventions based on terrestrial LiDAR data
Reckziegel, Rafael Bohn; Mbongo, Werner; Kunneke, Anton; Morhart, Christopher; Sheppard, Jonathan P.; Chirwa, Paxie W.; Du Toit, Ben; Kahle, Hans-Peter
Agroforestry systems hold potential for wood and tree biomass production without the need
of felling trees. Branch wood harvesting provides access to considerable amounts of lignocellulosic
biomass while leaving the tree standing. Aiming at alternatives for wood provision, we assessed
the actual woody structure of a silvopastoral system in the African Savannah ecoregion, utilising
terrestrial LiDAR technology and quantitative structure models to simulate branch removals and
estimate harvesting yields. In addition, the stand structure and harvested wood were examined for
the provision of four types of assortments meeting local needs, and operational metrics for each
treatment were derived. The stand had large variability in woody structures. Branch harvesting
interventions removed up to 18.2% of total stand volume, yielded 5.9 m3 ha−1 of branch wood, and
delivered 2.54 m3 ha−1 of pole wood quality, retaining on average more than 75% of the original
tree structures. Among the most intense simulations, a mean of 54.7 litres (L) of branch wood was
provided per tree, or approximately 34.2 kg of fresh biomass. The choice of an ideal harvesting
treatment is subject to practitioners’ interests, while the discussion on aspects of the operation,
and stand and tree conditions after treatment, together with outputs, assist decision making. The
partitioning of tree structures and branch removal simulations are tools to support the design of
tending operations aiming for wood and tree biomass harvesting in agroforestry systems while
retaining different functional roles of trees in situ.
Description:
Supplementary File S1. Figure S1: Individual tree point clouds identified
by colours (up), leaf-on mode evidenced by intensity values (middle), and the leaf-off point clouds
(bottom); Figure S2: Stand-level wood assortments available in linear meters for each simulated
harvesting treatment; Figure S3: Boxplots of the absolute branch volume removal in each harvesting
simulation with the red crosses representing treatment means; Table S1: QSM-derived tree parameters
for trees in the stand (n = 66); Table S2: Optimised QSM input parameters for each tree; Table S3:
Summary of available assortments and yields per harvesting treatment.
Supplementary File S2
contains the assessment of assortments on a tree basis for each harvesting simulation.