气候变化领域集成服务门户(CCPortal): Improving the knowledge base for tropical dry forest management in southern Africa: Regional volume models for Pterocarpus angolensis

CCPortal

DOI	10.1016/j.foreco.2020.118485
	Improving the knowledge base for tropical dry forest management in southern Africa: Regional volume models for Pterocarpus angolensis
	De Cauwer V.; Beeckman H.; Kleinn C.; Moses M.; Nott A.; Seifert T.; Muys B.
发表日期	2020
ISSN	0378-1127
卷号	477
英文摘要	The development of site-specific allometric models for tree species of natural tropical forests is hampered by limited resources while there is little quality control of the models developed. This study compares site- and species-specific models with generic and regional or pantropical models for Pterocarpus angolensis, the most widely exploited timber tree of southern Africa. We developed regional models with diameter at breast height (DBH) and tree height for the total and merchantable wood volume of P. angolensis with a dataset of 415 trees collected by destructive and non-destructive methods at 14 different sites in the Baikiaea – Pterocarpus woodlands of Namibia and southern Angola. Sources of data heterogeneity, such as site, collector and method, were investigated using mixed models and climate variables as model predictors. The study compared the ability of the new models with ten other site and species-specific volume models and nine generic volume and biomass models to estimate wood volume at tree and stand level. Stand data of 129 sample plots, representing a rainfall gradient from 480 mm to 750 mm, were used. Results showed that the three best performing models with DBH as single predictor (error 28% − 30%), including our new model, were developed for Namibia and Zambia. Adding tree height as predictor to our model removed the heterogeneity caused by site and reduced the error to 22%. One regional generic and one pantropical generic model, both with tree height, performed as well and outperformed other Pterocarpus specific models. Our models showed that the mean portion of merchantable wood was 35% of the total wood volume, of which 58% was heartwood. Although addition of climate variables improved our models, they did not perform well at stand level. Estimated merchantable volume of P. angolensis at stand level varied from 1.9 to 2.7 m3 ha−1, depending on the models employed. Total growing stock is estimated between 36 and 52 m3 ha−1 in our study area, depending on the model, with the contribution of P. angolensis approximately 13%. Our results suggest that site-specificity of models is needed when they only include DBH. The use of pantropical and regional DBH-height based models that are adapted to site conditions through the collection of accurate height and wood density data for biomass conversion factors, is advised rather than developing site-specific DBH based allometric models. © 2020 Elsevier B.V.
英文关键词	Allometric relationship; Baikiaea – Pterocarpus woodlands; Generic model; Kiaat; Muninga; Specific model; Tree volume model; Umbila
语种	英语
scopus关键词	Bioconversion; Data handling; Forestry; Knowledge based systems; Nondestructive examination; Tropics; Wood; Allometric models; Biomass conversion; Climate variables; Data heterogeneity; Diameter-at-breast heights; Nondestructive methods; Species specifics; Tropical dry forest; Climate models; climate change; dry forest; ecological modeling; forest management; rainfall; timber; tree; tropical forest; woodland; Data Processing; Forestry; Models; Pterocarpus Angolensis; Tree Dimensions; Tropics; Volume; Wood; Angola; Namibia; Zambia; Baikiaea; Pterocarpus; Pterocarpus angolensis
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/154976
作者单位	Namibia University of Science and Technology, Faculty of Natural Resources & Spatial Sciences, Private Bag 13388, Windhoek, Namibia; KU Leuven, Division Forest, Nature and Landscape, Celestijnenlaan 200E-2411, Leuven, 3001, Belgium; Royal Museum for Central Africa, Service of Wood Biology, Leuvensesteenweg 13, Tervuren, 3080, Belgium; University of Göttingen, Forest Inventory and Remote Sensing, Faculty of Forest Sciences and Forest Ecology, Büsgenweg 5, Göttingen, 37077, Germany; Directorate of Forestry, PO Box 13088, Eenhana, Namibia; Stellenbosch University, Department of Forest and Wood Science, Private Bag X1, Matieland, 7602, South Africa; Albert-Ludwigs-University Freiburg, Chair of Forest Growth and Dendroecology, Tennenbacher-Str. 4, Freiburg, 89106, Germany
推荐引用方式 GB/T 7714	De Cauwer V.,Beeckman H.,Kleinn C.,et al. Improving the knowledge base for tropical dry forest management in southern Africa: Regional volume models for Pterocarpus angolensis[J],2020,477.
APA	De Cauwer V..,Beeckman H..,Kleinn C..,Moses M..,Nott A..,...&Muys B..(2020).Improving the knowledge base for tropical dry forest management in southern Africa: Regional volume models for Pterocarpus angolensis.Forest Ecology and Management,477.
MLA	De Cauwer V.,et al."Improving the knowledge base for tropical dry forest management in southern Africa: Regional volume models for Pterocarpus angolensis".Forest Ecology and Management 477(2020).