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Above-ground biomass models for dominant trees species in cacao agroforestry systems in Talamanca, Costa Rica
Agroforestry Systems ( IF 2.0 ) Pub Date : 2022-03-30 , DOI: 10.1007/s10457-022-00741-y
Hernán J. Andrade 1 , Milena Segura 1 , Eduardo Somarriba 2
Affiliation  

Tree biomass allometric models are essential to estimate biomass, carbon sequestration and nutrient cycling in cacao agroforestry systems and other land uses with woody perennial species. A total of 34 trees of Cordia alliodora, 74 trees of Theobroma cacao and 38 trees of eight fruit species (Inga spp., Citrus aurantifolia, C. sinensis, Spondias mombin, Nephelium lappaceum, Persea americana, Mammea americana, Mangifera indica and Syzigium malaccensis) were harvested to gravimetrically estimate aboveground biomass (total, stem, branches, and foliage). Additionally, a database with total stem volume of 208 trees of C. alliodora was used to estimate above-ground biomass using a biomass expansion factor (BEF) and wood specific gravity estimations from this study. The well-known generic allometric models were fitted to the data using ordinary least squares, and the best ones were selected based on determination coefficient (R2), adjusted R2, root of mean square error, Akaike Information Criterion, Bayesian information criterion, and residual analyses. Selected models were compared with published models for the same species or group of species. Tree BEF were estimated for C. alliodora and fruit trees. The best fit models explained 93–96% of total above-ground biomass, and 54–95% of biomass by components. BEF differed significantly between timber and fruit trees. These models represent an advance in monitoring of carbon projects.



中文翻译:

哥斯达黎加塔拉曼卡可可农林系统中优势树种的地上生物量模型

树木生物量异速生长模型对于估计可可农林系统和其他多年生木本植物的土地利用中的生物量、碳固存和养分循环至关重要。共有34棵Cordia alliodora树、74棵可可树和8种果树(Inga spp.、Citrus aurantifolia、C. sinensis、Spondias mombin、Nephelium lappaceum、Persea americanaMammea americana、Mangifera indicaSyzigium malaccensis )的8个果树。 ) 被收获以通过重量法估计地上生物量(总、茎、枝和树叶)。此外,一个总茎量为 208 棵C. alliodora树的数据库用于使用本研究中的生物量膨胀因子 (BEF) 和木材比重估计来估计地上生物量。众所周知的通用异速生长模型使用普通最小二乘法拟合数据,并根据决定系数(R 2)、调整后的 R 2、均方误差根、Akaike 信息准则、贝叶斯信息准则、和残差分析。将选定的模型与同一物种或物种组的已发表模型进行比较。估计C. alliodora的树 BEF和果树。最佳拟合模型解释了 93-96% 的地上总生物量和 54-95% 的生物量(按成分)。木材和果树的 BEF 差异显着。这些模型代表了碳项目监测方面的进步。

更新日期:2022-03-30
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