文献类型：期刊文献

英文题名：Use of Modified Reineke's Stand Density Index in Predicting Growth and Survival of Chinese Fir Plantations

作者：Zhang, Xiongqing[1,2] Cao, Quang V.[3] Lu, Lele[4] Wang, Hanchen[4] Duan, Aiguo[4] Zhang, Jianguo[1,2]

第一作者：张雄清;Zhang, Xiongqing

通信作者：Zhang, XQ[1];Zhang, XQ[2]

机构：[1]Chinese Acad Forestry, Res Inst Forestry, State Key Lab Tree Genet & Breeding, Key Lab Tree Breeding & Cultivat State Forestry A, Beijing, Peoples R China;[2]Nanjing Forestry Univ, Collaborat Innovat Ctr Sustainable Forestry South, Nanjing, Jiangsu, Peoples R China;[3]Louisiana State Univ, Sch Renewable Nat Resources, Baton Rouge, LA 70803 USA;[4]Chinese Acad Forestry, Res Inst Forestry, Key Lab Tree Breeding & Cultivat State Forestry A, Beijing, Peoples R China

年份：2019

卷号：65

期号：6

起止页码：776-783

外文期刊名：FOREST SCIENCE

收录：;EI(收录号：20200308030168);Scopus(收录号：2-s2.0-85077737608);WOS:【SCI-EXPANDED(收录号:WOS:000500564100014)】；

基金：The study was supported by the National Natural Science Foundation of China (31670634), the Young Elite Scientists Sponsorship Program by CAST (2017QNRC001), and National Key Research Program of China (2016YFD0600302). Partial support for data analysis was received from the National Institute of Food and Agriculture, USDA, McIntire-Stennis project LAB94223.

语种：英文

外文关键词：site-specific SDI; climate-sensitive SDI; growth; survival

摘要：Stand density index (SDI) has played an important role in controlling stand stocking and modeling stand development in forest stands. Reineke's SDI (SDI_R) is based on a constant slope of -1.605 for the self-thinning line. For Chinese fir plantations, however, it has been reported that the self-thinning slope varied with site and climate, rendering SDI_R questionable. 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. 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). Results indicated that models with climate-sensitive SDI (SDI_C) performed best, followed by SDI_S and SDI_R. The control models without SDI received the worst overall rank. 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.