Plant Ecology

, Volume 217, Issue 9, pp 1105–1114 | Cite as

Canopy foliation and area as predictors of mortality risk from episodic drought for individual trees of Ashe juniper

  • H. Wayne PolleyEmail author
  • Daniel M. Johnson
  • Robert B. Jackson


Drought is killing an increasing number of trees globally, yet mortality risk remains difficult to predict at fine spatial scales. We sought to identify metrics of living individuals that could be used to estimate mortality risk of Ashe juniper (Juniperus ashei) trees and eventually to estimate the fraction of juniper populations at risk from drought. Ashe juniper is a keystone species in the Edwards Plateau region in central Texas, USA. We analyzed tree rings from both living and dead trees to determine growth rate prior to an historic drought in 2011 and measured morphological, physiological, and stand-level variables hypothesized to link growth rate and mortality risk. Slowly growing trees were disproportionately vulnerable to mortality. Fractional mortality of sampled trees was correlated to the difference between the mean predrought basal area increment (BAI) per tree and the predrought BAI of minimally stressed trees growing on deep soil (=BAI90 − BAI). Slowly growing trees had sparsely foliated canopies. BAI90 − BAI was positively correlated to the difference between: (1) leaf area per unit of projected canopy area per tree (LA) and the LA of minimally stressed trees and (2) projected canopy area (CA) and the CA of comparably sized trees. By contrast, there was no correlation between growth of living trees and light interception by neighboring trees, soil depth, or two functional metrics, the stem–leaf Ψ gradient and leaf light use efficiency. Mortality risk in Ashe juniper populations can be estimated from nondestructive measurements of leaf and canopy area of individual trees using relationships among risk, growth, and leaf and canopy area.


Basal area increment Canopy area Climate change Leaf area Growth rate Woodland 



Basal area (cm2)


Basal area increment (cm2)


BAI estimated from a quantile regression (0.90 quantile) model fit to the BAI-canopy area relationship (cm2)


Projected canopy area per tree (m2)


Leaf area per tree (m2)


LA estimated from a quantile regression (0.90 quantile) model fit to the LA–CA relationship (m2)


Leaf area index


Photosynthetically active radiation


Photochemical reflectance index



Field and laboratory assistance from Chris Kolodziejczyk, Katherine Jones, and Corey Courchane was critical. We are indebted to Texas Parks and Wildlife staff at Colorado Bend State Park for their gracious cooperation. This project was funded under a Grant from USDA-AFRI (#2012-00857). Mention of trade names or commercial products does not imply endorsement by the US Department of Agriculture. USDA is an equal opportunity provider and employer.

Supplementary material

11258_2016_636_MOESM1_ESM.docx (40 kb)
Supplementary material 1 (DOCX 40 kb)


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Copyright information

© Springer Science+Business Media Dordrecht (outside the USA) 2016

Authors and Affiliations

  • H. Wayne Polley
    • 1
    Email author
  • Daniel M. Johnson
    • 2
  • Robert B. Jackson
    • 3
  1. 1.Grassland, Soil & Water Research LaboratoryUSDA–Agricultural Research ServiceTempleUSA
  2. 2.Department of Forest, Rangeland and Fire SciencesUniversity of IdahoMoscowUSA
  3. 3.School of Earth SciencesStanford UniversityStanfordUSA

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