气候变化领域集成服务门户(CCPortal): Aboveground tree biomass prediction options for the Dry Afromontane forests in south-central Ethiopia

CCPortal

DOI	10.1016/j.foreco.2020.118335
	Aboveground tree biomass prediction options for the Dry Afromontane forests in south-central Ethiopia
	Asrat Z.; Eid T.; Gobakken T.; Negash M.
发表日期	2020
ISSN	0378-1127
卷号	473
英文摘要	Biomass of trees may be predicted either directly applying allometric models or indirectly from volume and biomass expansion factors (BEFs). For the Dry Afromontane forests, the second largest biomass pool in Ethiopia, such methods are not devised and properly documented. The main objective of this study was to explore different aboveground tree biomass prediction options based on destructively sampled tree biomass data. We explored the direct method by means of 1) new mixed-species general biomass models developed in the present study, and 2) some previously developed models including the pan-tropical models, and the indirect method by means of 3) volume and BEFs. From two sites in south-central Ethiopia, based on information from systematic sample plot inventories, 63 trees from 30 different species that contributed about 87% to the total forest basal area, were destructively sampled. Weighted nonlinear regression was applied to fit new models and their performance was assessed using root mean squared error (RMSE, %), mean prediction error (MPE, %) and pseudo-R2 based on leave-one-out-cross-validation. Previously developed models and the indirect method were also evaluated by means of RMSE and MPE. The new general total biomass models performed well with pseudo-R2 ranging between 0.87 and 0.96 and are presented along with covariance matrices for the parameter estimates enabling error propagation in biomass estimation. Most previously developed models resulted in significant MPEs up to 78%, while the best pan-tropical model performed much better with an MPE of about 7%. The indirect method also showed poor performance with MPEs ranging between 5% and 30%. Generally, the new models are accurate and flexible, thus, preferred over all previously developed models and the indirect method for application. However, their application to Dry Afromontane forests outside the study sites should be made only after thoroughly evaluating growing conditions and species composition. The results are step forward to enhance decisions made towards sustainable forest management including the REDD+ implementation for Dry Afromontane forests in Ethiopia. © 2020 Elsevier B.V.
英文关键词	Aboveground biomass; Allometric models; Biomass expansion factors; Dry Afromontane forest
语种	英语
scopus关键词	Biomass; Covariance matrix; Errors; Forecasting; Mean square error; Tropics; Aboveground tree biomass; Covariance matrices; Dry afromontane forests; Leave-one-out cross validations; Non-linear regression; Root mean squared errors; Species composition; Sustainable forest management; Forestry; aboveground biomass; decision making; forest inventory; forest management; model validation; montane forest; prediction; sampling; tropical forest; Biomass; Errors; Forecasts; Forestry; Sustainable Forest Management; Tropics; Ethiopia
来源期刊	Forest Ecology and Management
文献类型	期刊论文
条目标识符	http://gcip.llas.ac.cn/handle/2XKMVOVA/155129
作者单位	Norwegian University of Life Sciences, Faculty of Environmental Sciences and Natural Resource Management, P.O. Box 50031432Ås, Norway; Wondo Genet College of Forestry and Natural Resources, P.O. Box 128, Shashemene, Ethiopia
推荐引用方式 GB/T 7714	Asrat Z.,Eid T.,Gobakken T.,et al. Aboveground tree biomass prediction options for the Dry Afromontane forests in south-central Ethiopia[J],2020,473.
APA	Asrat Z.,Eid T.,Gobakken T.,&Negash M..(2020).Aboveground tree biomass prediction options for the Dry Afromontane forests in south-central Ethiopia.Forest Ecology and Management,473.
MLA	Asrat Z.,et al."Aboveground tree biomass prediction options for the Dry Afromontane forests in south-central Ethiopia".Forest Ecology and Management 473(2020).