White spruce site index in relation to soil, understory vegetation, and foliar nutrients

Publisher Website
Google Scholar
Abstract
The relationships between site index and measures of soil, understory vegetation, and foliar nutrients were examined using data from 102 white spruce (Piceaglauca (Moench) Voss) stands in the Sub-boreal Spruce zone of British Columbia. Compared with soil physical properties (adjusted.R2 = 0.54), soil nutrient properties (adjusted.R2 = 0.29) were poor predictors of white spruce site index. The best soil model, using depth of major rooting zone, total nitrogen, and slope as predictors, explained 60% of the total variance in site index. The best understory vegetation model, using frequencies of soil-moisture and nitrogen indicator species groups as predictors, explained 53% of the total variance in site index. The best foliar nutrient model, using foliar phosphorus and sulphur as predictors, explained 64% of the total variance in site index. Adding variables from understory vegetation, foliar nutrients, or both into the best soil model significantly improved site index prediction. The resultant models explained up to 83% of the total variance in site index. When stands were stratified according to groundwater influence, regression models developed for three delineated strata were significantly improved compared with unstratified models. Based on practical consideration, four regression models were considered for predicting white spruce site index. Independent testing indicated that the stratified model, which used only soil variables as predictors, predicted white spruce site index with 79% of the estimate errors within 2 m in the study area.

This publication has 0 references indexed in Scilit: