Contribution of sapwood traits to uncertainty in conifer sap flow as estimated with the heat-ratio method

Nathaniel Looker, Justin Martin, Kelsey Jencso, Jia Hu

Research output: Contribution to journalArticle

8 Citations (Scopus)

Abstract

Inferring whole-tree sap flow rates (Q) with thermometric sap flow sensors requires specification of physiological and structural attributes of trees. Using sap temperature measurements to estimate Q with the heat-ratio method (HRM) requires quantification of the water content (mc), basic density (ρb), and depth (Rs) of sapwood. Values of mc and ρb serve to estimate sapwood thermal diffusivity (k), a necessary variable in the calculation of heat-pulse velocity (Vh) that is often set to a nominal value (k_nom); mc and ρb are also used to convert Vh to sap velocity (Vs). The sapwood area across which Vs is integrated is often estimated on the basis of Rs. Because mc and ρb are correlated and influence Q through estimation of k and the conversion of Vh to Vs, we sought to quantify the potential error introduced when Q is calculated with k_nom rather than with k as estimated from measurements of mc and ρb in five coniferous species. We also examined how variation in mc, ρb, and Rs across sampling scales may contribute to uncertainty in estimated Q. Across the observed range of mc and ρb, the two traits contributed to a net decline in the process of estimating Vs from Vh (with k_nom). This suggests that the use of k_nom rather than a calculated k may result in overestimation of Q when mc and ρb co-vary as they did in our study. Variability in mc and ρb across sampling scales could induce errors greater than 10% in Vs (and hence Q), while within- and among-tree variability in Rs could impart even greater errors (up to 130%). We propose that this uncertainty be represented in the expression of error in whole-tree sap flow estimates and in statistical analyses involving those estimates.

Original languageEnglish (US)
Pages (from-to)60-71
Number of pages12
JournalAgricultural and Forest Meteorology
Volume223
DOIs
StatePublished - Jun 15 2016
Externally publishedYes

Fingerprint

sap flow
sapwood
conifers
coniferous tree
uncertainty
heat
sap
thermal diffusivity
sampling
methodology
diffusivity
water content
sensor
method
temperature

Keywords

  • Basic density
  • Heat-ratio method
  • Sap flow
  • Sapwood area
  • Thermal diffusivity
  • Wood water content

ASJC Scopus subject areas

  • Forestry
  • Global and Planetary Change
  • Agronomy and Crop Science
  • Atmospheric Science

Cite this

Contribution of sapwood traits to uncertainty in conifer sap flow as estimated with the heat-ratio method. / Looker, Nathaniel; Martin, Justin; Jencso, Kelsey; Hu, Jia.

In: Agricultural and Forest Meteorology, Vol. 223, 15.06.2016, p. 60-71.

Research output: Contribution to journalArticle

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abstract = "Inferring whole-tree sap flow rates (Q) with thermometric sap flow sensors requires specification of physiological and structural attributes of trees. Using sap temperature measurements to estimate Q with the heat-ratio method (HRM) requires quantification of the water content (mc), basic density (ρb), and depth (Rs) of sapwood. Values of mc and ρb serve to estimate sapwood thermal diffusivity (k), a necessary variable in the calculation of heat-pulse velocity (Vh) that is often set to a nominal value (k_nom); mc and ρb are also used to convert Vh to sap velocity (Vs). The sapwood area across which Vs is integrated is often estimated on the basis of Rs. Because mc and ρb are correlated and influence Q through estimation of k and the conversion of Vh to Vs, we sought to quantify the potential error introduced when Q is calculated with k_nom rather than with k as estimated from measurements of mc and ρb in five coniferous species. We also examined how variation in mc, ρb, and Rs across sampling scales may contribute to uncertainty in estimated Q. Across the observed range of mc and ρb, the two traits contributed to a net decline in the process of estimating Vs from Vh (with k_nom). This suggests that the use of k_nom rather than a calculated k may result in overestimation of Q when mc and ρb co-vary as they did in our study. Variability in mc and ρb across sampling scales could induce errors greater than 10{\%} in Vs (and hence Q), while within- and among-tree variability in Rs could impart even greater errors (up to 130{\%}). We propose that this uncertainty be represented in the expression of error in whole-tree sap flow estimates and in statistical analyses involving those estimates.",
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