Models of knot and stem development in black spruce trees indicate a shift in allocation priority to branches when growth is limited

Abstract

The branch autonomy principle, which states that the growth of individual branches can be predicted from their morphology and position in the forest canopy irrespective of the characteristics of the tree, has been used to simplify models of branch growth in trees. However, observed changes in allocation priority within trees towards branches growing in light-favoured conditions, referred to as ‘Milton’s Law of resource availability and allocation’, have raised questions about the applicability of the branch autonomy principle. We present models linking knot ontogeny to the secondary growth of the main stem in black spruce (Picea mariana (Mill.) B.S.P.), which were used to assess the patterns of assimilate allocation over time, both within and between trees. Data describing the annual radial growth of 445 stem rings and the three-dimensional shape of 5377 knots were extracted from optical scans and X-ray computed tomography images taken along the stems of 10 trees. Total knot to stem area increment ratios (KSR) were calculated for each year of growth, and statistical models were developed to describe the annual development of knot diameter and curvature as a function of stem radial increment, total tree height, stem diameter, and the position of knots along an annual growth unit. KSR varied as a function of tree age and of the height to diameter ratio of the stem, a variable indicative of the competitive status of the tree. Simulations of the development of an individual knot showed that an increase in the stem radial growth rate was associated with an increase in the initial growth of the knot, but also with a shorter lifespan. Our results provide support for ‘Milton’s Law’, since they indicate that allocation priority is given to locations where the potential return is the highest. The developed models provided realistic simulations of knot morphology within trees, which could be integrated into a functional-structural model of tree growth and above-ground resource partitioning.

How tree morphology reflects ring properties in Norway spruce?

“…The growth of the branches is naturally connected with the overall growth of a stand: Mäkinen and Hein (2006) found that as the growing space increased, the diameter of the branches of the butt log also increased in synchrony with the stem volume growth in Norway spruce. Duchateau, et al (2015) modelled the development of the knot shape within Black spruce stems (Picea mariana Mill. B.S.P.…”

Assessing wood properties in standing timber with laser scanning

“…The tight interdependencies between primary and secondary growth are due to the wood formation responding to intrinsic (increasing size) and extrinsic (climate and competition) factors as described in the Introduction. With detailed inputs from TLS point clouds accompanied by wood property references, any of the above-mentioned models could be utilized in translating allometric growth responses into vertical and radial gradients of wood properties such as knottiness, wood density, or fiber properties (Duchateau et al 2013;Eberhardt et al 2019;Ikonen et al 2003;Mäkelä et al 2010;Mäkinen et al 2020;Moberg 2006;Osborne and Maguire 2016) (Figures 1 and 4).…”

“…Establishing databases that combine detailed morphological tree traits from standing timber, bucking data from harvesters, and wood quality data from sawmills would enable reconstructions of virtual sawlogs that are used to optimize the secondary log breakdown, or sawing. Using stem taper, branching, and knot shape models, comprehensive reconstructions of interior knot structures were previously demonstrated (Duchateau et al 2013;Osborne and Maguire 2016). TLS provides an excellent instrument for obtaining the calibration data from standing timber (Figure 4).…”

From inside to outside: CT scanning as a tool to link internal knot structure and external branch diameter as a prerequisite for quality assessment

“…Growth models have covered part of the solution for an integration between forest and timber products, by exploring the causal effect of silvicultural treatments on external branch diameter (Väisänen et al 1989;Hein et al 2008b;Garber and Maguire 2005;Grace et al 2015) or directly on saw timber properties (Rais et al 2014;Högberg et al 2010), as well as relating branch development to tree measurements (Duchateau et al 2015) and stand structural data (Mäkinen and Colin 1998). Ultimately, the incorporation of such models into growth simulators (Yue et al 2013;Dufour-Kowalski et al 2012) led to its output being linked to product recovery models (Houllier et al 1995).…”