Space-time Analysis of the Longitudinal Variation in Wood Specific Gravity of Teak and Its Effect on Tree Growth and Development

Authors

  • Jerry Oppong Adutwum Graduate School of Bioresource and Bioenvironmental Sciences, Faculty of Agriculture, Kyushu University
  • Hiroki Sakagami Laboratory of Wood Materials Technology, Faculty of Agriculture, Kyushu University
  • Shinya Koga Laboratory of Forest Resources Management, Faculty of Agriculture, Kyushu University
  • Junji Matsumura Laboratory of Wood Science, Faculty of Agriculture, Kyushu University

Keywords:

Juvenility, Kronecker product, Maturation, Mixed-effects model, Space-time dynamics, Stochastic processes, Teak, Tree growth, Wood specific gravity

Abstract

The space-time structure of a teak wood specific gravity (SG) dataset was analyzed using a mixed-effects model. Spatial correlation increased in space, a phenomenon attributable to the maturation of apical meristems, while the temporal correlation of vascular meristems decreased over time. The decay of temporal correlation over time was attributed to the diminishing crown effect on the later formed wood further away from the pith, morphogen gradient, and probably changing microenvironmental conditions. The Kronecker product was used to collect spatiotemporal data on the intricate dynamic process of the evolution of the apical and lateral meristems. The results showed that height and relative radial distance (RRD) (i.e., the flow of time with wood formation) were statistically significant factors, with their interaction showing no significance. The results confirm the usefulness of using the space-time approach to elucidate the interaction between the apical and lateral meristems, two major inherent biological systems that control tree growth and wood formation dynamics. To understand the origins of patterns that vary both temporally and spatially in the tree, future work should describe the variation of SG within the tree due to increasing height (space) and diameter (age) as a matrix; then the correlation function can be modelled.

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Published

2023-02-08

Issue

Section

Research Article or Brief Communication