Allometric equations for biomass estimations in Cameroon and pan moist tropical equations including biomass data from Africa
Allometric equations for biomass estimations in Cameroon and pan moist tropical equations including biomass data from Africa
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DOI：
10.1016/j.foreco.2010.08.034
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发表时间：
2010-10-15
影响因子：
3.7
通讯作者：
Gravenhorst, Gode
中科院分区：
文献类型：
--
作者：
Djomo, Adrien N.;Ibrahima, Adamou;Gravenhorst, Gode
非洲和其他地方潮湿的热带森林储存了大量的碳，需要准确的异速生长回归来进行估计。在非洲，由于缺乏特定物种或混合物种的异速生长方程，导致广泛使用泛湿热带方程来估计树木生物量。这种信息的缺乏引起了对这些数据的准确性的许多讨论，因为方程是从非洲以外收集的生物量，混合物种回归方程与71个样本树使用不同的输入变量，如直径，直径和高度，产品的直径和高度，木材密度，估计总地上生物量和生物量的树叶和树枝为喀麦隆森林。我们的生物量数据被添加到372个生物量数据收集在亚洲和南美洲不同的潮湿热带森林开发新的泛潮湿热带异速生长回归。用3833株树木建立了种属和混合种的树高直径回归模型，混合种回归模型仅以直径为输入变量，估算了研究地的地上生物量，平均误差为7.4%。增加高度或木材密度并没有显着改善的估计。将三个变量结合使用，提高了精度，平均误差为3.4%。一般异速生长方程树高是一个很好的预测变量。最佳的泛湿热带方程是将三个变量加在一起，然后是一个包括直径和高度。本研究提供了31个树种的高径关系和木材密度。Chave等人（2005年）开发的泛湿热带方程估计了不同地点的总地上生物量，平均误差为20.3%，而本研究开发的方程平均误差为29.5%。(C)出版社：Elsevier B.V.
Moist tropical forests in Africa and elsewhere store large amounts of carbon and need accurate allometric regressions for their estimation. In Africa the absence of species-specific or mixed-species allometric equations has lead to broad use of pan moist tropical equations to estimate tree biomass. This lack of information has raised many discussions on the accuracy of these data, since equations were derived from biomass collected outside Africa.Mixed-species regression equations with 71 sample trees using different input variables such as diameter, diameter and height, product of diameter and height, and wood density were developed to estimate total aboveground biomass and biomass of leaves and branches for a Cameroon forest. Our biomass data was added to 372 biomass data collected across different moist tropical forests in Asia and South America to develop new pan moist tropical allometric regressions. Species-specific and mixed-species height diameter regression models were also developed to estimate heights using 3833 trees.Using only diameter as input variable, the mixed-species regression model estimates the aboveground biomass of the study site with an average error of 7.4%. Adding height or wood density did not improve significantly the estimations. Using the three variables together improved the precision with an average error of 3.4%. For general allometric equations tree height was a good predictor variable. The best pan moist tropical equation was obtained when the three variables were added together followed by the one which includes diameter and height. This study provides height diameter relationships and wood density of 31 species. The pan moist tropical equation developed by Chave et al. (2005), estimates total aboveground biomass across different sites with an average error of 20.3% followed by equations developed in the present study with an average error of 29.5%. (C) 2010 Published by Elsevier B.V.