考虑空心树影响的异速生长方程:以沙捞越热带泥炭沼泽森林为例

IF 1 Q4 ECOLOGY
Tropics Pub Date : 2015-01-01 DOI:10.3759/TROPICS.24.11
Yukako Monda, Y. Kiyono, L. Melling, Christopher Damian, Auldry Chaddy
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引用次数: 14

摘要

热带泥炭沼泽森林的生物量估计相当复杂,因为经常发现空心树,因为没有空心大小的数据,而且关于生物量精确测量的数据有限。在马来西亚沙捞越的一个被砍伐的泥炭沼泽森林中,对剩余树木的地上(AGB)和地下生物量(BGB)以及空心大小进行了破坏性采样。随后,考虑到热带泥炭沼泽森林地上和地下生物量的空穴的异速生长方程也正在开发中。结果表明,在杉树和圆圆杉树中,树胸径大于40 cm;沙捞越的泥炭沼泽森林中均有优势种或共优势种。中空体积在0.23 ~ 1.08 m之间,平均占茎体积的42.3%。以前异速生长模型产生的较大生物量部分是由于空洞的存在。在此基础上,建立了包括1个(仅胸径)、2个(胸径加高度[H]或木材密度[WD])或3个(胸径、胸径和胸径)预测变量的AGB和BGB估算模型,并添加了[ln(DBH)]作为预测变量,表示空洞形成造成的生物量损失。三个预测变量的AGB模型和一个预测变量的BGB模型表现最好,其中;校正决定系数最高,Furnival指数和赤池信息标准(Akaike information criterion, AIC)最低。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Allometric equations considering the influence of hollow trees: A case study for tropical peat swamp forest in Sarawak
Biomass estimations in tropical peat swamp forests are quite complex when hollow trees are frequently found due to the unavailability of data on hollow size and the limited data on accurate measures of biomass. Destructive samplings were done for both above(AGB) and belowground biomass (BGB) and hollow sizes of remained trees at a logged-over peat swamp forest in Sarawak, Malaysia. Subsequently, allometric equations taking hollows into account for both the aboveand belowground biomass of tropical peat swamp forests were also being developed. It was observed that these were hollows in Shorea albida and Combretocarpus rotundatus trees with diameters at breast height (DBH) exceeding 40 cm; S. albida is a dominant or co-dominant species, and C. rotundatus grows in peat swamp forests throughout Sarawak. The hollow volumes ranged from 0.23 to 1.08 m, and occupied 42.3% of stem volume on average. The larger biomass produced by previous allometric models were partially due to the presence of hollows. Thus, new models for estimating both AGB and BGB were developed that included one (only DBH), two (DBH and height [H] or wood density [WD]), or three (DBH, H, and WD) predictor variables, and [ln(DBH)] was added as predictor variable indicating the biomass loss by cavity formation. AGB model with three predictor variables and BGB model with one predictor variable performed the best where; they had the highest adjusted coefficients of determination and lowest Furnival index and Akaike information criterion (AIC).
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来源期刊
Tropics
Tropics ECOLOGY-
CiteScore
1.40
自引率
0.00%
发文量
7
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