Literature DB >> 32148315

Simulation of climate change and thinning effects on productivity of Larix olgensis plantations in northeast China using 3-PGmix model.

Yalin Xie1, Haiyan Wang2, Xiangdong Lei3.   

Abstract

Understanding the effects of thinning on forest productivity under climate change is vital to adaptive forest management. In the present study, the 3-PGmix model was applied to simulate the thinning effects on productivity of Larix olgensis plantations under climate change using 164 sample plots collected from the 6th, 7th and 8th National Forest Inventories in Jilin Province, northeast China. Climate scenarios of RCP 4.5 and RCP 8.5 were adopted from 2011 to 2100 with corresponding reference years (1981-2010). We simulated four cutting intensities: no-thinning, NT; low intensity thinning with 10% stem removal, LT; moderate thinning with 20% stem removal, MT and heavy thinning with 30% stem removal, HT for three times with 5- and 10-year thinning intervals. The results indicated that the mean net primary productivity (NPP) during the simulated 90 years was increased under RCP 4.5 and RCP 8.5. The LT and MT had positive but HT had negative effects on the mean NPP for the same climate scenario. Increased thinning intensity facilitated the positive effects of climate change on NPP but without a significant interaction effect. During the simulation, LT had the highest NPP value and HT had the biggest NPP increase under future climate change. We also discussed the management of larch plantations under climate change and advocated low intensity thinning with 10-year thinning interval to gain maximum NPP for mitigating climate change.
Copyright © 2020 Elsevier Ltd. All rights reserved.

Entities:  

Keywords:  3-PG(mix) model; Climate change; Larix olgensis plantation; NPP; Thinning

Year:  2020        PMID: 32148315     DOI: 10.1016/j.jenvman.2020.110249

Source DB:  PubMed          Journal:  J Environ Manage        ISSN: 0301-4797            Impact factor:   6.789


  2 in total

1.  Assessing scale-dependent effects on Forest biomass productivity based on machine learning.

Authors:  Jingyuan He; Chunyu Fan; Yan Geng; Chunyu Zhang; Xiuhai Zhao; Klaus von Gadow
Journal:  Ecol Evol       Date:  2022-07-13       Impact factor: 3.167

2.  Stand carbon storage and net primary production in China's subtropical secondary forests are predicted to increase by 2060.

Authors:  Jia Jin; Wenhua Xiang; Yelin Zeng; Shuai Ouyang; Xiaolu Zhou; Yanting Hu; Zhonghui Zhao; Liang Chen; Pifeng Lei; Xiangwen Deng; Hui Wang; Shirong Liu; Changhui Peng
Journal:  Carbon Balance Manag       Date:  2022-05-26
  2 in total

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