气候变化领域集成服务门户(CCPortal): Using climatic and biophysical attributes to model the presence and severity of root disease across the U.S. Northern Rocky Mountains

CCPortal

DOI	10.1016/j.foreco.2020.118355
	Using climatic and biophysical attributes to model the presence and severity of root disease across the U.S. Northern Rocky Mountains
	Holden Z.A.; Swanson A.; Lockman B.; Egan J.; Cleaver C.M.; McKeever K.; Bush R.; Landguth E.L.
发表日期	2020
ISSN	0378-1127
卷号	474
英文摘要	Root disease fungi are native, soil-borne pathogens that impact forest stand dynamics and productivity through direct tree mortality or reduced yield. Despite being a major contributor of mortality in forests of western North America, particularly in the northern Rocky Mountains in the United States, little is known about the underlying factors that influence root disease occurrence and severity at landscape and broader scales. We used a database with >15,000 geographically-distributed, spatially-referenced root disease assessments from United States Department of Agriculture (USDA) Forest Service Forest Inventory and Analysis (FIA) plots from across the US Northern Rocky mountains and high resolution (30 m) climate and soil-water balance grids to examine climatic and biophysical factors associated with presence and severity of root disease. We used a two-stage modeling approach that combined boosted regression-tree models and residual kriging to predict the probability of occurrence and severity of root disease across the area of analysis. A best-fit model explained root disease occurrence moderately well (AUC = 0.77) and included average annual dewpoint temperature, evapotranspiration and climatic water deficit. Root disease occurrence was associated with moist, humid sites subject to low or moderate climatic water deficits. Root disease severity was not well explained by climatic and biophysical factors alone (R2 = 0.19). Residual kriging only marginally improved model fit (R2 = 0.20). We used the fitted models to produce 30 m resolution gridded root disease occurrence and severity maps across the US Forest Service Northern Region for use in broad-scale planning and analysis. Weak spatial autocorrelation at distances beyond 5 km and relatively low accuracy of the severity model suggests that the FIA plot distribution is not suited to predict spatial patterns of root disease severity. Additional factors related to root disease severity, such as vegetation type and site-specific disturbance histories, are likely needed for fine-scale severity predictions. © 2020 Elsevier B.V.
关键词	Agricultural robots Biophysics Distributed database systems Forecasting Interpolation Landforms Plants (botany)Soil moisture Boosted regression trees Broad-scale planning Dewpoint temperature Forest inventory and analysis Northern Rocky Mountains Probability of occurrence Spatial autocorrelations United states department of agricultures Forestry Fungi
语种	英语
来源机构	Forest Ecology and Management
文献类型	期刊论文
条目标识符	http://gcip.llas.ac.cn/handle/2XKMVOVA/132616
推荐引用方式 GB/T 7714	Holden Z.A.,Swanson A.,Lockman B.,et al. Using climatic and biophysical attributes to model the presence and severity of root disease across the U.S. Northern Rocky Mountains[J]. Forest Ecology and Management,2020,474.
APA	Holden Z.A..,Swanson A..,Lockman B..,Egan J..,Cleaver C.M..,...&Landguth E.L..(2020).Using climatic and biophysical attributes to model the presence and severity of root disease across the U.S. Northern Rocky Mountains.,474.
MLA	Holden Z.A.,et al."Using climatic and biophysical attributes to model the presence and severity of root disease across the U.S. Northern Rocky Mountains".474(2020).