Iranian Journal of Forest

Iranian Journal of Forest

Allometric equations for biomass and carbon stock of Prunus arabica (Olivier) Meikle and Prunus elaeagrifolia (Spach) Fritsch in the Kareh-bas forest of Chaharmahal and Bakhtiari Province

Document Type : Research Paper

Authors
S. Ghaffari 1
Y. Iranmanesh 2
M.K. Parsapour 3
H.R. Riahi Bakhtiari 4
1 Ph.D. Student, Dept. of Forestry, Faculty of Natural Resources and Earth Sciences, Shahrekord University, Shahrekord, I. R. Iran
2 Associate Prof., Forests and Rangelands Research Dept. Isfahan Agricultural and Natural Resources Research and Education Center (AREEO), Isfahan, I. R. Iran
3 Postdoctoral Researcher., Forests and Rangelands Research Dept. Chaharmahal and Bakhtiari Agricultural and Natural Resources Research and Education Center (AREEO), Shahrekord, I. R. Iran
4 Assistant Prof., Dept. of Forestry, Faculty of Natural Resources and Earth Sciences, Shahrekord University, Shahrekord, I. R. Iran
10.22034/ijf.2025.495245.2027
Abstract
Introduction: Forests play a vital role as ecosystems in combating climate change and reducing greenhouse gases. Due to their high significance in carbon storage and exposure to anthropogenic threats, effective conservation and management of forests are essential. Accurate estimation of biomass and carbon storage, especially in Zagros forests, is crucial for designing management strategies. This study investigates and estimates the biomass and carbon stock of two important forest species, Prunus arabica (Olivier) Meikle and Prunus elaeagrifolia (Spach) Fritsch, and presents suitable allometric models for these species for the first time. The models offer non-destructive and precise estimates using measurable tree characteristics.
Material and Methods: This research was conducted in the natural habitat of the wild almond in Kareh-Bas, Khanmirza County, Chaharmahal and Bakhtiari Province. Thirty sample plots (1000 square meters) were established in the area and 30 individuals (15 individuals of each species) were selected using stratifed random sampling from different crown classes and their quantitative parameters including average crown diameter, diameter of the thickest shoot, number of shoots and total height were measured. The selected shrubs were cut and weighed in the field and sampling was carried out to determine dry weight and carbon percentage. Carbon percentage was measured in the laboratory and by combustion method. Univariate and multivariate models were used to develop allometric equations and their validation was investigated.Results: The results indicated that for Prunus arabica, single-variable (univariate) power models using average crown diameter had the highest coefficient of determination (0.98) and the lowest prediction error (16.4%). Additionally, two-variable models combining average crown diameter with the diameter of the thickest shoot and either height or diameter also yielded similar results, attaining a coefficient of determination of 0.93. For Prunus elaeagrifolia, the best models included univariate power models based on average crown diameter with a coefficient of determination of 0.93 and an error of 16.1%. All multivariate models for this species were also deemed valid, with a coefficient of determination around 0.80 and an approximate error in them is high.
Conclusion: This study emphasizes the importance of biomass as a key indicator in assessing the productivity and health of forest ecosystems and its role in evaluating carbon reserves and management of reduction of greenhouse gases. Allometric models, particularly power equations, are effective for accurately estimating biomass and carbon storage in Prunus arabica and Prunus elaeagrifolia species. Average crown diameter and the diameter of the thickest shoot were identified as the best predictors of biomass. The study also highlights the need for multivariate equations in specific ecosystems, particularly in the Zagros forests, which are influenced by human activities. Overall, the results demonstrate the high potential of allometric models to improve the accuracy of biomass and carbon estimates in forests. The results of this study contribute to a greater scientific understanding of biomass and carbon dynamics, which can inform optimized management and conservation policies, ecosystem valuation, and the minimization of damage from destructive practices.
Keywords
Biomass dynamics
Carbon storage
Climate change
Power equations
Single-variable models

Subjects

 
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Iranian Journal of Forest
Volume 17, Issue 2 - Serial Number 2
Summer 2025
Pages 241-258

  • Receive Date 29 December 2024
  • Revise Date 20 January 2026
  • Accept Date 06 February 2025