Conductive sapwood area prediction from stem and canopy areas - allometric equations of Kalahari trees, Botswana

M.W. Lubczynski*, D.C. Chavarro-Rincon, David Rossiter

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review

6 Citations (Scopus)

Abstract

Conductive sapwood (xylem) area (Ax) of all trees in a given forested area is the main factor contributing to spatial tree transpiration. One hundred ninety-five trees of 9 species in the Kalahari region of Botswana were felled, stained, cut into discs, and measured to develop allometric equations predicting Ax from estimates of stem (As) and canopy (Ac) areas. Stem discs were also subjected to laboratory-based computed tomography, which well detected wood density contrasts but was not diagnostic with regard to delineation of Ax. The staining experiment, along with the help of visual and computed tomography analysis, allowed the definition of 4, tree-species categories of Ax, C1–C4. In C1 (Acacia erioloba, Terminalia sericea, and Burke Africana), the staining and visual delineation of Ax matched the natural color difference between sapwood and heartwood; in C2 (Dichrostachys cinerea and Ochna pulchra), sapwood was divided into external conductive and internal nonconductive annuli; in C3 (Acacia fleckii and Acacia luederitzii), sapwood had sharp staining boundary between external highly conductive and internal low-conductive annuli; and in C4 (Lonchocarpus nelsii and Boscia albitrunca), stems had no heartwood. Per-species 0-intercept linear regression models, Ax = slope.As (slope = 0.392 ÷ 0.794; R2 = 96.7 ÷ 99.8%) and Ax = slope.Ac (slope = 1.477 ÷ 17.044; R2 = 82.1 ÷ 92.2%) yielded excellent to good predictive allometric equations. The first equation is suitable for Ax scaling of small-size Kalahari areas, where the As of all trees can be estimated on the ground, whereas the second, as contribution to automated tree transpiration mapping of large-size Kalahari areas, where the Ac of trees can be derived through remote sensing interpretation of high-resolution images.
Original languageEnglish
Article numbere1856
JournalEcohydrology
Volume10
Issue number6
DOIs
Publication statusPublished - 2017

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