Results indicated that models with SDI_C performed best, followed by SDI_S and SDI_R. Remeasured data from 48 plots distributed in Fujian, Jiangxi, Guangxi, and Sichuan provinces were used to develop models for prediction of stand survival and basal area, with SDI_R, site-specific SDI (SDI_S), and climate-sensitive SDI (SDI_C), respectively, incorporated as a predictor variable. For Chinese fir plantations, however, it has been reported that the self-thinning slope varied with site and climate. Reineke’s SDI (SDI_R), based on a constant slope of –1.605 for the self-thinning line, is questionable. Stand density index (SDI) has played an important role in controlling stand stocking and modeling stand development in forest stands. Inclusion of climate-sensitive SDI in growth and survival models can therefore facilitate modeling of the relation between stand density and growth/survival under future climate-change conditions. The control models without SDI received the worst overall rank. Results indicated that models with climate-sensitive SDI (SDI_C) performed best, followed by SDI_S and SDI_R. Also included in the evaluation were growth models based on self-thinning slopes estimated from two groups of sites (SDI_S) or from climate variables (SDI_C).

Remeasured data from 48 plots distributed in Fujian, Jiangxi, Guangxi, and Sichuan provinces were used to develop models for prediction of stand survival and basal area, with SDI_R incorporated as a predictor variable. For Chinese fir plantations, however, it has been reported that the self-thinning slope varied with site and climate, rendering SDI_R questionable. Reineke’s SDI (SDI_R) is based on a constant slope of –1.605 for the self-thinning line.

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