Estimating dendrometric variables, volume and carbon from stump diameter for Pinus arizonica Engelm. in northern Mexico

• Published in: Notulae scientia biologicae Vol. 15; no. 4; p. 11704
• Main Authors: VARGAS-FLORES, Karen A., RASCÓN-SOLANO, Joel, HERNÁNDEZ-SALAS, Javier, POMPA-GARCÍA, Marín
• Format: Journal Article
• Language: English
• Published: Society of Land Measurements and Cadastre from Transylvania (SMTCT) 21.12.2023
• Subjects: dendrometric variables; linear models; mathematical models; Microsoft Excel; Pinus arizonica Engelm; prediction models
• ISSN: 2067-3264; 2067-3264
• DOI: 10.55779/nsb15411704

It is noteworthy that in the last decade, there has been an increase in the number of studies predicting normal diameter, total height, and stem volume based on stump dimensions. Therefore, the objectives were: a) to determine the mathematical model that best estimates normal diameter, total height, stem volume, and captured carbon as a function of stump diameter for Pinus arizonica Engelm. in northern Mexico; and b) to generate mathematical models through data processing in the Microsoft Excel program. Using a targeted sampling design, we selected 264 Pinus arizonica Engelm. trees to generate the database. The development of prediction models for normal diameter, total height, total tree volume, and captured carbon as a function of stump diameter was carried out using the Microsoft Excel database management package. The fit's adequacy was analyzed based on residuals and statistics such as the root mean square error, the adjusted coefficient of determination, and the coefficient of variation. Model fits indicate a linear trend for the normal diameter variable, while for total height, the model turned out to be logarithmic. As for total tree volume and captured carbon, the relationship is exponential in relation to stump diameter. The R2adj fits were highly reliable for estimating normal diameter, total tree volume, and captured carbon, with values exceeding 95%. The development of prediction models using Microsoft Excel is viable according to the results presented here. The tested techniques can be replicated by forestry technicians, environmental inspectors, and forest landowners who do not have specialized knowledge in the generation prediction models.