气候变化领域集成服务门户(CCPortal): Growth and yield drivers of loblolly pine in the southeastern U.S.: A meta-analysis

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DOI	10.1016/j.foreco.2018.12.007
	Growth and yield drivers of loblolly pine in the southeastern U.S.: A meta-analysis
	Restrepo H.I.; Bullock B.P.; Montes C.R.
发表日期	2019
ISSN	0378-1127
起始页码	205
结束页码	218
卷号	435
英文摘要	An abundant amount of information has been accumulated over the past century on loblolly pine. However, few studies have been aimed at assembling this information. Three possible approaches can be used to synthesize available information on loblolly pine: a review paper in the form of a narrative discussion, systematic review compiling data in tables, and meta-analysis to statistically summarize data. The purpose of this research is to statistically synthesize suitable loblolly pine yield data in the southeastern United States using meta-analysis. There were 18 studies selected out of approximately 500 peer-reviewed papers, and three high-quality studies (one proceeding, one M.S. thesis, and one Ph.D. dissertation) evaluated, from which a database was compiled. Since forest growth has several drivers (i.e. age, site quality, genetics, density, and management) the use of meta-regression, a meta-analysis technique to account for variability associated with covariates, was used. Thus, meta-regression linear mixed effects yield models using the log-transformed Schumacher form, at the whole-stand level, were estimated as a function of the mentioned forest growth factors for diameter at breast height (DBH), height (Ht), basal area (BA), and volume (V). Overall, the estimated models suggest that these forest growth factors successfully explain yield variability. The Raudenbush's pseudo-R 2 , which measures the amount of variation explained by the covariates, were 97, 94, 97, and 91%, for DBH, Ht, BA, and V models, respectively. However, the 95% confidence intervals (CI) of yield curves associated with some growth factor levels overlapped their corresponding reference level, suggesting no statistical differences at certain ages. In this sense, the CI's width is driven mainly by the number of studies, and their number of replicates, available for factor levels. Thus, the lack of information of factor levels, and their combinations, was identified and suggested to be investigated in future research in order to achieve narrower CIs. Meta-analysis and meta-regression are promising techniques to be applied in forestry research to give insight into the effect of growth factors on forest yield. © 2018
英文关键词	Genetically improved trees; Pinus taeda L.; Schumacher model; Silvicultural regimes; Site quality; Spatially explicit models
语种	英语
scopus关键词	Forestry; Regression analysis; Genetically improved trees; Pinus taeda L; Silvicultural regimes; Site quality; Spatially explicit models; Quality control; basal area; confidence interval; coniferous tree; database; genetically modified organism; growth; meta-analysis; model; regression analysis; silviculture; yield; Forestry; Growth; Pinus Taeda; Quality Control; Regression Analysis; Site Index; Yield; United States; Pinus taeda
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/156180
作者单位	Warnell School of Forestry and Natural Resources, University of Georgia, Athens, GA, United States
推荐引用方式 GB/T 7714	Restrepo H.I.,Bullock B.P.,Montes C.R.. Growth and yield drivers of loblolly pine in the southeastern U.S.: A meta-analysis[J],2019,435.
APA	Restrepo H.I.,Bullock B.P.,&Montes C.R..(2019).Growth and yield drivers of loblolly pine in the southeastern U.S.: A meta-analysis.Forest Ecology and Management,435.
MLA	Restrepo H.I.,et al."Growth and yield drivers of loblolly pine in the southeastern U.S.: A meta-analysis".Forest Ecology and Management 435(2019).