Towards an objective assessment of tree vitality: a case study based on 3D laser scanning

Abstract

Key message Analyzing fine branch length characteristics in beech trees using single-tree QSMs derived from laser scanning reveals insights into drought-induced changes in vitality, which include branch shedding and reduced shoot growth. Abstract Climate change causes increasing temperatures and precipitation anomalies, which result in deteriorations of tree health and declines in ecosystem services of forests. It is therefore crucial to monitor tree vitality to preserve forests and their functions. However, methods describing tree vitality in situ are lacking reproducibility or are too laborious. Thus, we tested a laser-scanning based approach, assuming that an objective measurement of a tree’s outer shape should reveal changes according to tree vitality. QSMs of similarly sized beech trees from stands with varying degrees of drought damage were used. Absolute and relative fine branch lengths, their ratio to lower order branches’ lengths and their progressions over relative height were targeted to identify fine branch dieback and reduced growth. The absolute fine branch length was significantly lower for less vital beech trees, especially within the upper crown, leading to a less top-heavy vertical distribution of fine branches and a reduced fine-to-base order branch length ratio. Hence, height-dependent characteristics of fine branch lengths differed between vitalities. We conclude that using fine branch length characteristics derived from QSMs can be helpful in vitality assessments of beech trees. Still, uncertainties with regard to the plotwise assessment and problems with QSM quality are present.

Plant phenotyping relevance

3DレーザースキャンとQSMから枝長形質を抽出し、樹木活力を客観評価する手法が研究の中心であるため。

Code and data availability

The paper's Data availability statement explicitly deposits the datasets generated and analyzed (QSM-derived fine branch length measurements of beech trees) in the GRO.data repository with a public DOI, making it a paper-specific, publicly actionable phenotype dataset.