A vegetative index of stand productivity based on tree inventory for predicting oak site index in the Central Hardwood Region

Abstract

Models for prediction of site index (SI) typically include only abiotic causal variables (e.g., soil) and lack biotic response variables  (e.g.,  vegetation), which could exhibit greater sensitivity to important environmental factors affecting tree height growth. Our study objective was to evaluate Whittaker’s moisture condition index (MCI) (R.H. Whittaker. 1956. Ecol. Monogr. 26: 1–80) as a potential biotic variable for inclusion with conventional abiotic variables in oak (Quercus L.) SI prediction models. The MCI is the sum of relative abundances of inventoried plot tree species weighted by their moisture affinity classification. We compared regression parameters of conventional base models including only abiotic variables with exploratory models configured with abiotic variables and MCI for explaining variation of SI. The best abiotic model included only aspect. When MCI was included  in the  abiotic  model,  aspect  became  insignificant, resulting in a single-variable  biotic  model  that  accounted  for increased SI variation. The MCI biotic model remained significant when tested with independent data from a distant location. The MCI is easily
calculated using plot inventory data, and with further evaluation, it may be confirmed as a useful biotic variable in combination with abiotic soil and topographic variables for prediction of oak SI.

  • Citation: McNab, W. Henry; Keyser, Tara L. 2020. A vegetative index of stand productivity based on tree inventory for predicting oak site index in the Central Hardwood Region. Canadian Journal of Forest Research. 50(8): 760-773. https://doi.org/10.1139/cjfr-2019-0412.
  • Keywords: moisture af nity, moisture condition index, productivity, Quercus, site index.
  • Posted Date: September 4, 2020
  • Modified Date: September 10, 2020
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