2018 ESA Annual Meeting (August 5 -- 10)

COS 117-6 - A spatially-explicit empirical model of structural development processes in natural forests based on climate and topography

Thursday, August 9, 2018: 3:20 PM
253, New Orleans Ernest N. Morial Convention Center
Yuichi Yamaura1,2, David Lindenmayer2, Yusuke Yamada3, Hao Gong3, Toshiya Matsuura3, Yasushi Mitsuda4 and Takashi Masaki5, (1)Department of Forest Vegetation, Forestry and Forest Products Research Institute, Tsukuba, Japan, (2)Fenner School of Environment and Society, Australian National University, Canberra, Australia, (3)Department of Forest Management, Forestry and Forest Products Research Institute, Tsukuba, Japan, (4)Faculty of Agriculture, University of Miyazaki, Miyazaki, Japan, (5)Forestry and Forest Products Research Institute, Tsukuba, Japan
Background/Question/Methods

Stand structure develops with stand age, and old-growth forests with well-developed stand structure support myriads of species. However, development rates after disturbance of some elements of stand structure may vary with climate and topography. Here we modeled structural development processes in four key stand variables and a composite old-growth index (which has values ranging from 0 to 1 and comprises key stand variables), as functions of climatic and topographic covariates. We used a hierarchical Bayesian method for the analysis of snap-shot extensive national forest inventory (NFI) data in Japan (n = 5,506 plots) to account for different stand age of the plots.

Results/Conclusions

We found that development rates of structural variables and the old-growth index exhibited nonlinear responses to environmental covariates. Flat sites were characterized by high rates of structural development. Old natural forests (>150 years old) occurred primarily in cool locations subject to deep snow. Approximately 150-200 years would generally be required to attain high values (~0.8) of the old-growth index; however, the predicted age to achieve these values varied depending on values for the environmental covariates. Spatial prediction highlighted regional variation in potential structural development rates; for example, there was >100 post-harvest year difference required to attain a medium value (0.5) of the old-growth index between sites even in the same catchment. Sites with high development rates often supported plantations rather than natural forests. Remnant natural forests, especially old stands, on productive flat sites have high conservation value due to their likely fast development rates and sufficient structural development.