干旱区生态环境知识资源中心(Arid): Improving wood volume predictions in dry tropical forest in the semi-arid Brazil

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DOI	10.1007/s40333-020-0082-x
	Improving wood volume predictions in dry tropical forest in the semi-arid Brazil
	de Lima, Robson B.; Barreto-Garcia, Patricia A. B.; de Paula, Alessandro; Pereira, Jhuly E. S.; de Carvalho, Flavia F.; Gomes, Silvio H. M.
通讯作者	de Lima, RB (corresponding author), State Univ Amapa, Dept Forest Engn, BR-68900070 Macapa, Brazil.
来源期刊	JOURNAL OF ARID LAND
ISSN	1674-6767
EISSN	2194-7783
出版年	2020
卷号	12 期号:6 页码:1046-1055
英文摘要	The volumetric variability of dry tropical forests in Brazil and the scarcity of studies on the subject show the need for the development of techniques that make it possible to obtain adequate and accurate wood volume estimates. In this study, we analyzed a database of thinning trees from a forest management plan in the Contendas de Sincora National Forest, southwestern Bahia State, Brazil. The data set included a total of 300 trees with a trunk diameter ranging from 5 to 52 cm. Adjustments, validation and statistical selection of four volumetric models were performed. Due to the difference in height values for the same diameter and the low correlation between both variables, we do not suggest models which only use the diameter at breast height (DBH) variable as a predictor because they accommodate the largest estimation errors. In comparing the best single entry model (Hohenald-Krenn) with the Spurr model (best fit model), it is noted that the exclusion of height as a predictor causes the values of 136.44 and 0.93 for Akaike information criterion (AIC) and adjusted determination coefficient (Radj(2)), which are poorer than the second best model (Schumacher-Hall). Regarding the minimum sample size, errors in estimation (root mean square error (RMSE) and bias) of the best model decrease as the sample size increases, especially when a larger number of trees with DBH >= 5.0 cm are randomly sampled. Stratified sampling by diameter class produces smaller volume prediction errors than random sampling, especially when considering all trees. In summary, the Spurr and Schumacher-Hall models perform better. These models suggest that the total variance explained in the estimates is not less than 95%, producing reliable forecasts of the total volume with shell. Our estimates indicate that the bias around the average is not greater than 7%. Our results support the decision to use regression methods to build models and estimate their parameters, seeking stratification strategies in diameter classes for the sample trees. Volume estimates with valid confidence intervals can be obtained using the Spurr model for the studied dry forest. Stratified sampling of the data set for model adjustment and selection is necessary, since we find significant results with mean error square root values and bias of up to 70% of the total database.
英文关键词	volume modeling minimal sample size Caatinga Spurr model forest management
类型	Article
语种	英语
开放获取类型	Bronze
收录类别	SCI-E
WOS记录号	WOS:000603535500001
WOS关键词	ABOVEGROUND BIOMASS ; ALLOMETRIC MODELS ; TREE VOLUME ; VEGETATION ; EQUATIONS ; AREA ; STEM
WOS类目	Environmental Sciences
WOS研究方向	Environmental Sciences & Ecology
资源类型	期刊论文
条目标识符	http://119.78.100.177/qdio/handle/2XILL650/369266
作者单位	[de Lima, Robson B.] State Univ Amapa, Dept Forest Engn, BR-68900070 Macapa, Brazil; [Barreto-Garcia, Patricia A. B.; de Paula, Alessandro; de Carvalho, Flavia F.] State Univ Southwest Bahia, Dept Forest Sci, BR-45083900 Vitoria Da Conquista, Brazil; [Pereira, Jhuly E. S.] Univ Fed Lavras, BR-37200900 Lavras, Brazil; [Gomes, Silvio H. M.] Univ Sao Paulo, BR-13418900 Piracicaba, Brazil
推荐引用方式 GB/T 7714	de Lima, Robson B.,Barreto-Garcia, Patricia A. B.,de Paula, Alessandro,et al. Improving wood volume predictions in dry tropical forest in the semi-arid Brazil[J],2020,12(6):1046-1055.
APA	de Lima, Robson B.,Barreto-Garcia, Patricia A. B.,de Paula, Alessandro,Pereira, Jhuly E. S.,de Carvalho, Flavia F.,&Gomes, Silvio H. M..(2020).Improving wood volume predictions in dry tropical forest in the semi-arid Brazil.JOURNAL OF ARID LAND,12(6),1046-1055.
MLA	de Lima, Robson B.,et al."Improving wood volume predictions in dry tropical forest in the semi-arid Brazil".JOURNAL OF ARID LAND 12.6(2020):1046-1055.