Influence of Cambial Age and Axial Height on the Spatial Patterns of Xylem Traits in Catalpa bungei, a Ring-Porous Tree Species Native to China

Abstract

Studying how cambial age and axial height affects wood anatomical traits may improve our understanding of xylem hydraulics, heartwood formation and axial growth. Radial strips were collected from six different heights (0–11.3 m) along the main trunk of three Manchurian catalpa (Catalpa bungei) trees, yielding 88 samples. In total, thirteen wood anatomical vessel and fiber traits were observed usinglight microscopy (LM) and scanning electron microscopy (SEM), and linear models were used to analyse the combined effect of axial height, cambial age and their interaction. Vessel diameter differed by about one order of magnitude between early- and latewood, and increased significantly with both cambial age and axial height in latewood, while it was positively affected by cambial age and independent of height in earlywood. Vertical position further had a positive effect on earlywood vessel density, and negative effects on fibre wall thickness, wall thickness to diameter ratio and length. Cambial age had positive effects on the pit membrane diameter and vessel element length, while the annual diameter growth decreased with both cambial age and axial position. In contrast, early- and latewood fiber diameter were unaffected by both cambial age and axial height. We further observed an increasing amount of tyloses from sapwood to heartwood, accompanied by an increase of warty layers and amorphous deposits on cell walls, bordered pit membranes and pit apertures. This study highlights the significant effects of cambial age and vertical position on xylem anatomical traits, and confirms earlier work that cautions to take into account xylem spatial position when interpreting wood anatomical structures, and thus, xylem hydraulic functioning.

Investigating Effects of Bordered Pit Membrane Morphology and Properties on Plant Xylem Hydraulic Functions—A Case Study from 3D Reconstruction and Microflow Modelling of Pit Membranes in Angiosperm Xylem

“…For instance, pit membrane thickness was found not to be affected by cambial age and axial sampling position in mangrove stem sapwood [29]. However, pit membrane thickness appeared to be thicker in the heartwood compared with sapwood of Catalpa bungei [30], while older growth rings tend to have shrunken and slightly thinner pit membranes in Acer pseduoplatnus [31]. Given that a strong positive correlation exists between xylem embolism resistance and pit membrane thickness [4], if larger vessels are more vulnerable to xylem embolism, one would expect larger vessels should have thinner pit membranes.…”

“…Given that a strong positive correlation exists between xylem embolism resistance and pit membrane thickness [4], if larger vessels are more vulnerable to xylem embolism, one would expect larger vessels should have thinner pit membranes. Although there is convergent vessel widening from tree top to tree base [32,33], and vessel diameter tends to increase radially from the pith to the bark [30], no general agreement has been achieved on whether larger or smaller conduits are more vulnerable to xylem embolism [34], which might yield conflicting findings on pit membrane thickness from different studied tree species as mentioned above. Therefore, multiple tree species are needed to further explore the axial and radial variation of pit membrane thickness.…”

“…Additional pit traits such as pit membrane diameter are positively affected by cambial age, suggesting that larger pit membrane diameter in sapwood might improve hydraulic efficiency while smaller pit membrane diameter might be involved to effectively protect fungi invasion in heartwood [30]. The pit area hypothesis, i.e., larger pit area per vessel, was negatively correlated with xylem embolism resistance in many angiosperm species [76][77][78], however, not supported by [16,34,79], which again showed complexity in interpreting pit membrane traits due to diversity of studied tree species.…”

Machine Learning Models with Quantitative Wood Anatomy Data Can Discriminate between Swietenia macrophylla and Swietenia mahagoni

“…In traditional wood identification, species-level resolution is often impossible because intra-species variation is as large as inter-species variation within a genus [54][55][56]. All characters showed overlap in intra-and inter-species variation for the three Swietenia species, and, therefore, no single character was sufficient to separate them.…”

“…The high wood anatomical variability within S. macrophylla encompasses much of the variability in the other two species, and even machine learning methods did not suffice to provide full forensic certainty [22,60] but did greatly exceed prior reported accuracy [10]. When separating similar species using quantitative wood anatomy data, it is recommended that a sufficiently large number of specimens be studied to ensure that the full range of variation across the species is incorporated [56].…”