干旱区生态环境知识资源中心(Arid): Application of a Bayesian approach to adjust biomass equations of Prosopis laevigata in Northern Mexico

Arid

DOI	10.21829/myb.2021.2742424
	Application of a Bayesian approach to adjust biomass equations of Prosopis laevigata in Northern Mexico
	Salas-Aguilar, Victor; Paz-Pellat, Fernando; Mendez-Gonzalez, Jorge; Abel Najera-Luna, Juan
通讯作者	Salas-Aguilar, V (corresponding author), Univ Autonoma Ciudad Juarez, Geoinformat, Cuauhtemoc, Chihuahua, Mexico.
来源期刊	MADERA Y BOSQUES
ISSN	2448-7597
出版年	2021
卷号	27 期号:4
英文摘要	One of the biggest problems in the estimation of aboveground biomass at the global level is the choice of a correct allometric model. In Mexico, there is a need to quantify the biomass of species in arid zones. For this reason, the objectives of this work were to adjust allometric equations for estimating biomass of Prosopis using a bayesian approach (EB) and to quantify the error in the adjustment of the models: EB, Ordinary Least Squares (OLS) and one get from a research published in 2012. The Bayesian model was developed on the basis of probability distributions of parameters (a and b) a priori, collected from seven experimentation sites in which we estimated the biomass (B) through basal diameter (Db) using power equations. We compared the approaches in five sizes of samples (TM) (10, 30, 60, 90 and 120); in each of them, 1000 repetitions without replacement were carried out. The 144 trees measured in the sampling sites were used to validate the setting for each sub-sample. The results showed that the EB presented the lowest error variability in the different TM. The MCO adjusted similar to EB, however its variability and the presence of outliers grew to decrease TM. The adjustment with the parameters of that research made in 2012 presented the greatest variability and demonstrated the high degree of uncertainty when estimating the biomass with fixed parameters. It is recommended the application of EB for the estimation of biomass in other species of interest and their application in national inventories.
英文关键词	bayesian calibration forest inventories allometric models arid zones
类型	Article
语种	其他
开放获取类型	gold
收录类别	SCI-E
WOS记录号	WOS:000731078300002
WOS关键词	FOREST BIOMASS ; MODELS ; LAWS
WOS类目	Forestry
WOS研究方向	Forestry
资源类型	期刊论文
条目标识符	http://119.78.100.177/qdio/handle/2XILL650/373976
作者单位	[Salas-Aguilar, Victor] Univ Autonoma Ciudad Juarez, Geoinformat, Cuauhtemoc, Chihuahua, Mexico; [Paz-Pellat, Fernando] GRENASER SA CV, Mexico City, DF, Mexico; [Paz-Pellat, Fernando] Colegio Postgrad, Campus Montecillo, Montecillo, Estado De Mexic, Mexico; [Mendez-Gonzalez, Jorge] Univ Autonoma Agr Antonio Narro, Dept Forestal, Saltillo, Coahuila, Mexico; [Abel Najera-Luna, Juan] Inst Tecnol & Salto, Div Estudios Posgrad & Invest, Durango, Mexico
推荐引用方式 GB/T 7714	Salas-Aguilar, Victor,Paz-Pellat, Fernando,Mendez-Gonzalez, Jorge,et al. Application of a Bayesian approach to adjust biomass equations of Prosopis laevigata in Northern Mexico[J],2021,27(4).
APA	Salas-Aguilar, Victor,Paz-Pellat, Fernando,Mendez-Gonzalez, Jorge,&Abel Najera-Luna, Juan.(2021).Application of a Bayesian approach to adjust biomass equations of Prosopis laevigata in Northern Mexico.MADERA Y BOSQUES,27(4).
MLA	Salas-Aguilar, Victor,et al."Application of a Bayesian approach to adjust biomass equations of Prosopis laevigata in Northern Mexico".MADERA Y BOSQUES 27.4(2021).