首页> 中文期刊> 《林业研究:英文版》 >Allometric relationships between primary size measures and sapwood area for six common tree species in snow-dependent ecosystems in the Southwest United States

Allometric relationships between primary size measures and sapwood area for six common tree species in snow-dependent ecosystems in the Southwest United States

         

摘要

High-elevation,snow-dependent,semiarid ecosystems across southwestern United States are expected to be vulnerable to climate change,including drought and fi re,with implications for various aspects of the water cycle.To that end,much less is known about the dynamics of transpiration,an important component of the water cycle across this region.At the individual-tree scale,transpiration is estimated by scaling mean sap fl ux density by the hydroactive sapwood area(SA).SA also remains a key factor in eff ectively scaling individual tree water-use to stand level.SA across large spatial scales is normally established by relating SA of a few trees to primary size measures,e.g.,diameter at breast height(DBH),tree height(H),or canopy diameter(CD).Considering the importance of SA in scaling transpiration,the primary objective of this study was therefore to establish six species-specifi c(aspen,maple,white fi r,ponderosa pine,Douglas fi r,Englemann spruce)allometric relationships between SA and three primary size measures(DBH,CD,or H)across two high-elevation,snow-dependent,semiarid ecosystems in New Mexico and Arizona.Based on multiple statistical criteria(coeffi cient of determination,index of agreement,Nash–Sutcliff e effi-ciency)and ease of measurement in the forest,we identifi ed DBH as the primary independent variable for estimating SA across all sites.Based on group regression analysis,we found allometric relationships to be signifi cantly(p<0.05)diff erent for the same species(ponderosa pine,Douglas-fi r)across diff erent sites.Overall,our allometric relationships provide a valuable database for estimating transpiration at diff erent spatial scales from sap fl ow data in some of our most vulnerable ecosystems.

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