Spatial distribution of soil carbon and nitrogen storage and forest productivity in a watershed planted to Japanese cedar (Cryptomeria japonica D. Don)

Abstract

Digital terrain modeling was used to evaluate landscape-level spatial variation of soil C and N storage and site productivity in Japanese cedar (Cryptomeria japonica D. Don) stands. Soil C and N storage were measured in samples from surface soils (0-25 cm depth) of 29 Japanese cedar stands in the 205-ha Myougodani watershed, Toyama Prefecture. The site index (C. japonica tree height at age 40 years) was used as a measure of forest productivity. Seven terrain attributes (elevation, slope gradient, aspect, profile curvature, plan curvature, openness, and wetness index) were calculated from a digital elevation model. Soil C and N storage were negatively correlated with slope gradient and positively correlated with openness. Variation in the site index was closely related to the wetness index. The prediction models using terrain attributes as explanatory variables explained 50% of the variability in soil C storage, 53% of the variability in soil N storage, and 75% of the variability in site index. This result demonstrated that this technique is useful for estimating the spatial distribution of soil properties and productivity in forest landscapes. On the other hand, there was no correlation between site index and soil C and N storage. Use of the prediction models in a geographic information system revealed that the spatial distribution of forest productivity differed considerably from those of soil C and N storage.

Regional estimation of Japanese cedar (Cryptomeria japonica D. Don) productivity by use of digital terrain analysis

“…The author's previous study (Zushi 2006) revealed that a linear regression model using wetness index and openness derived from digital terrain analysis as explanatory variables could explain reasonably well the spatial variation in productivity of Japanese cedar forests within a 205 ha watershed in Himi city. In particular, wetness index, which represents the redistribution of soil water within a landscape by lateral flow, explained 58% of the total variation in cedar productivity.…”

“…In a previous study (Zushi 2006) the author discovered strong correlations between environmental factors derived from digital terrain analysis and site productivity of Japanese cedar (Cryptomeria japonica D. Don) in a relatively small watershed (205 ha). These correlations proved to have good predictive utility.…”

“…Terrain analysis shows promise as a tool for interpreting the role of environmental factors in determining the spatial distribution of forest productivity (Mitsuda et al 2001;Zushi 2006). In a previous study (Zushi 2006) the author discovered strong correlations between environmental factors derived from digital terrain analysis and site productivity of Japanese cedar (Cryptomeria japonica D. Don) in a relatively small watershed (205 ha).…”

Effects of nutrition spatial heterogeneity on root traits and carbon usage by roots of Cercis chinensis seedlings in split root rooms

“…In natural ecosystems, nutrition levels showed great spatial heterogeneity at a range of scales, from meters to centimeters (Jackson and Caldwell, 1993;Boerner et al, 2000;Jonson et al, 2001;Rietkerk et al, 2002;Schreiner, 2005;Zushi, 2006;Knyazhneva et al, 2006). Roots manifest high plasticity in response to the nutrition spatial heterogeneity because of their chemotaxis, resulting in great changes in root traits and root system architecture (Ahlström et al, 1988;Fitter and Stickland, 1991;Robinson, 1994), and meanwhile the changes in the spatial heterogeneity affected fine root longevity and turnover (Majdi and Andersson, 2005).…”

Stem productivity in relation to nitrogen concentration and carbon isotopic composition (δ13C) in leaves of hinoki cypress (Chamaecyparis obtusa Endlicher) plantations in Shikoku district, Japan

“…Previous studies have shown that stem productivity or height growth (site index) in Japanese forests is related to topography (Enoki et al 1996;Tateno and Takeda 2003;Zushi 2006) and soil type (Inoue et al 1973;Mashimo 1960). These studies suggest that soil water and nitrogen availability are the primary factors that determine stem productivity.…”