气候变化领域集成服务门户(CCPortal): A Bayesian analysis of topographic influences on the presence and severity of beech bark disease

CCPortal

DOI	10.1016/j.foreco.2020.118198
	A Bayesian analysis of topographic influences on the presence and severity of beech bark disease
	Mulder O.; Sleith R.; Mulder K.; Coe N.R.
发表日期	2020
ISSN	0378-1127
卷号	472
英文摘要	Forests of the Eastern United States and North Eastern Canada have been devastated by the onslaught of beech bark disease (BBD). The cultivation and management of resistant trees is an important conservation issue. Disease resistance is an interplay between tree genetics and environmental factors. To further understand resistance to BBD, this study investigates the contribution of topographic factors to both the occurrence and the severity of beech bark disease through the examination of small-scale patterns of disease. Approximately two hundred trees of the species Fagus grandifolia (American beech) located on an eighty-five-acre plot in southwestern Vermont were monitored over five years for the presence and severity of BBD. Trees were examined yearly, during which time diameter at breast height (DBH) was recorded as well as a measure of disease severity. Topographical factors (aspect, slope, curvature, elevation, and aspect • slope) were assessed as potential predictors of disease presence and severity. Two distance measures of disease presence in nearby trees were also included to control for the spatial spread of the disease. Akaike's Information Criterion (AIC) was used to determine which subset of parameters yielded the best binary and ordinal logistic models of disease presence and rank. Bayesian analysis was used to determine the joint posterior distribution for model parameters. Slope was a both significant factors in determining disease presence. Slope • aspect was significant in determining both the presence and disease severity. DBH, time, and weighted distance to diseased trees were strong indicators of both disease presence and severity. Curvature and elevation were not significant factors. Predictive models based on identified local topographical parameters can identify environmental factors conducive to resistance which can be utilized to inform and designate regional beech restoration sites. Such models can also identify potential candidate trees for resistance screening and genetic profiling. With the more recent availability of higher resolution USGS topographic maps for the northeastern United States, it is easier to determine and evaluate ideal resistant beech habitat. From these maps we can predict regions with healthier beech trees and suggest potential ecologically favorable restoration sites only using slope and aspect. © 2020 Elsevier B.V.
英文关键词	Bayesian analysis; Beech bark disease; Disease ecology; Fagus grandifolia; Forest ecology; Restoration; Topographic factors
语种	英语
scopus关键词	Diagnosis; Forestry; Maps; Restoration; Akaike's information criterions; Diameter-at-breast heights; Disease resistance; Environmental factors; Posterior distributions; Predictive models; Slope and aspects; Weighted distance; Disease control; Bayesian analysis; cultivation; deciduous tree; disease resistance; disease severity; disease spread; environmental factor; genetic analysis; topography; Diagnosis; Fagus; Forestry; Maps; Resistance; Restoration; Slope; Trees; Canada; United States; Vermont; Fagus; Fagus grandifolia
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/155206
作者单位	Biology, Green Mountain College, 1 Brennan Circle, Poultney, VT 05764, United States; Biology, Smith College, 44 College Lane, Northampton, MA 01063, United States; Mathematics, Long Trail School, 1045 Kirby Hollow Rd, Dorset, VT 05251, United States; Chemistry, Long Trail School, 1045 Kirby Hollow Rd, Dorset, VT 05251, United States
推荐引用方式 GB/T 7714	Mulder O.,Sleith R.,Mulder K.,et al. A Bayesian analysis of topographic influences on the presence and severity of beech bark disease[J],2020,472.
APA	Mulder O.,Sleith R.,Mulder K.,&Coe N.R..(2020).A Bayesian analysis of topographic influences on the presence and severity of beech bark disease.Forest Ecology and Management,472.
MLA	Mulder O.,et al."A Bayesian analysis of topographic influences on the presence and severity of beech bark disease".Forest Ecology and Management 472(2020).