The Site-Specific Allometric Models for Biomass and Carbon Stocks of Pinus brutia Ten. in Duhok, Iraqi Kurdistan Region

The rise in atmospheric CO₂ driven by human activities is accelerating climate change and threatening ecosystem stability. Forests mitigate this threat by sequestering CO₂ in biomass, making accurate tree biomass estimation critical for carbon accounting and sustainable forest management. This study develops site-specific allometric models for estimating biomass and carbon stocks of Pinus brutia Ten. in three natural forests (Zawita, Atrosh, and Belkef) in the Duhok Governorate, Iraqi Kurdistan Region Field measurements of diameter at breast height (DBH) and total height (H) were collected from 150 trees to construct regression models for aboveground biomass (AGB) and its components (stem, branches, leaves, and litter), as well as total biomass including belowground roots. Linear models using the combined variable D2H, power functions, and exponential equations were evaluated, with the power models consistently outperforming the others, explaining 91–97% of the variation in biomass and showing low prediction errors and minimal bias across sites. Carbon stocks were derived by applying a conversion factor of 0.5 to the biomass estimates. The results highlight marked ecological differences among sites, primarily linked to stand density and annual rainfall, which strongly shape biomass accumulation. The developed site-specific equations provide robust tools for estimating above- and belowground biomass in P. brutia stands, improving carbon accounting, informing reforestation and climate-mitigation planning, and supporting monitoring needs under mechanisms such as REDD+.