Estimation of Aboveground Oil Palm Biomass in a Mature Plantation in the Congo Basin
Estimation of Aboveground Oil Palm Biomass in a Mature Plantation in the Congo Basin
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DOI：
10.3390/f11050544
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发表时间：
2020-05-01
期刊：
影响因子：
2.9
通讯作者：
Biyogo, Andreana Paola Mekui
中科院分区：
文献类型：
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作者：
Migolet, Pierre;Goita, Kalifa;Biyogo, Andreana Paola Mekui
在刚果盆地（西赤道非洲），主要是出于经济原因，越来越多地建立了农工业油棕榈种植园。要了解油棕榈固碳的能力，就需要对生物量进行估计。本研究实施了当地和区域的方法，估计棕榈生物量在成熟的种植园，使用破坏性采样。18个35岁的油棕榈树与胸高直径（DBH）之间的48和58厘米被砍伐和切片在位于Makouke，加蓬中部的种植园。现场和实验室测量确定了不同的树木隔间（水果，小叶，叶柄，轴，茎）的生物量。果实和小叶平均占地上生物量的6%，其中叶柄占8%，轴占13%，茎占73%。以胸径（2）×干高为复合变量，以组织亚密度为权重，建立了估算干生物量的最佳异速生长方程。对于叶生物量（果实+小叶+叶柄+轴），方程具有类似的形式，但包括叶数而不是亚密度。将茎和叶生物量相结合的异速生长模型得到了油棕地上总生物量的最佳估计值（决定系数（r（2））= 0.972，p < 0.0001，相对均方根误差（RMSE）= 5%）。然而，由于叶数等变量的可用性有限，该模型难以在实践中实施。用胸径（2）×干高，以密度内加权，估算出的地上生物量具有可比性（r（2）= 0.961，p < 0.0001，相对RMSE（%RMSE）= 5.7%）。排除亚密度的更简单的模型没有严重损害结果（R-2= 0.939，p < 0.0003，%RMSE = 8.2%）。我们还研究了现有的异速生长模型，建立在世界其他地方，估计地上油棕榈生物量在我们的研究领域。这些模型表现出最好的本地异速生长方程，开发性能较差。
Agro-industrial oil palm plantations are becoming increasingly established in the Congo Basin (West Equatorial Africa) for mainly economic reasons. Knowledge of oil palm capacity to sequester carbon requires biomass estimates. This study implemented local and regional methods for estimating palm biomass in a mature plantation, using destructive sampling. Eighteen 35-year-old oil palms with breast height diameters (DBH) between 48 and 58 cm were felled and sectioned in a plantation located in Makouke, central Gabon. Field and laboratory measurements determined the biomasses of different tree compartments (fruits, leaflets, petioles, rachises, stems). Fruits and leaflets contributed an average of 6% to total aboveground palm biomass, which petioles accounted for 8%, rachises for 13% and the stem, 73%. The best allometric equation for estimating stem biomass was obtained with a composite variable, formulated as DBH(2)x stem height, weighted by tissue infra-density. For leaf biomass (fruits + leaflets + petioles + rachises), the equation was of a similar form, but included the leaf number instead of infra-density. The allometric model combining the stem and leaf biomass yielded the best estimates of the total aboveground oil palm biomass (coefficient of determination (r(2)) = 0.972,p< 0.0001, relative root mean square error (RMSE) = 5%). Yet, the model was difficult to implement in practice, given the limited availability of variables such as the leaf number. The total aboveground biomass could be estimated with comparable results using DBH(2)x stem height, weighted by the infra-density (r(2)= 0.961,p< 0.0001, relative RMSE (%RMSE) = 5.7%). A simpler model excluding infra-density did not severely compromise results (R-2= 0.939,p< 0.0003, %RMSE = 8.2%). We also examined existing allometric models, established elsewhere in the world, for estimating aboveground oil palm biomass in our study area. These models exhibited performances inferior to the best local allometric equations that were developed.