Intra-specific differences in allometric equations for aboveground biomass of eastern Mediterranean Pinus brutia

Abstract

& Context Biomass prediction is important when dealing for instance with carbon sequestration, wildfire modeling, or bioenergy supply. Although allometric models based on destructive sampling provide accurate estimates, alternative speciesspecific equations often yield considerably different biomass predictions. An important source of intra-specific variability remains unexplained.• Aims The aims of the study were to inspect and assess intraspecific differences in aboveground biomass of Pinus brutia Ten. and to fill the gap in knowledge on biomass prediction for this species.• Methods Two hundred one trees between 2.3 and 55.8 cm in diameter at breast height were sampled throughout the easternand southernmost natural distribution area of P. brutia, in Middle East, where it forms different stand structures.Allometric equations were fitted separately for two countries. The differences in biomass prediction at tree, stand, and forest level were analyzed. The effect of stand structure and past forest management was discussed.• Results Between-country differences in total aboveground biomass were not large. However, differences in biomass stock were large when tree components were analyzed separately. Trees had higher stem biomass and lower crown biomass in dense even-aged stands than in more uneven-aged and sparse stands.• Conclusion Biomass and carbon predictions could be improved by taking into account stand structure in biomass models.

Modeling Crown Biomass for Four Pine Species in China

“…In fact, it is very common that shorter trees with the same D typically have a larger crown while taller trees have a smaller crown. This did agree with the regression estimation results in this paper and previous findings [5,14,15,20]. If the crown biomass models such as Equation (1) analysis of these three groups of combined variables, one could find that the sum of all power values in each situation was 3, indicating that crown biomass is related to a three-dimensional space.…”

“…Among the four main variables affecting crown biomass (D, H, crown width, and crown length), D was the most important, which was consistent with the conclusions of related literature [4,5,9,20,36]. Crown width was the next most important variable affecting crown biomass, consistent with the conclusion of Hoffmann et al (2002) [6].…”

“…According to the review by Henry et al (2014), significant variations have been observed in forest biomass estimation between different ecological zones, tree species, ages, management types and sites [5]. From the results, we found that P. tabulaeformis growing in the northern region had the largest crown biomass, followed by P. elliottii and P. massoniana growing in the southern region, while P. yunnanensis growing in the southwestern region had the smallest crown biomass.…”

“…Previous studies have reported significant variations in forest biomass estimation between different ecological zones, tree species, ages, density and management types [4,5]. Particularly, crown biomass estimates, which include branch and foliage biomass, vary widely between species.…”

“…Particularly, crown biomass estimates, which include branch and foliage biomass, vary widely between species. Many studies related to crown biomass have been reported worldwide [5][6][7][8][9][10][11][12][13][14][15][16][17]. For example, Yu et al (2010) established individual tree crown, branch and foliage biomass equations for Larix gmelinii forests using stem diameter, tree height, crown width, and crown length [18].…”