Literature DB >> 33341471

Estimating the distribution and productivity characters of Larix kaempferi in response to climate change.

Chunyan Wu1, Dongsheng Chen2, Jiapeng Shen3, Xiaomei Sun4, Shougong Zhang5.   

Abstract

Understanding the distribution, net primary productivity (NPP) and environmental constraints of Larix kaempferi is crucial to predict how global climate change will affect its growth and future dynamics. We simulated future changes in the globally suitable distribution patterns and the NPP dynamics under different representative concentration pathways (RCPs) using MaxEnt and Physiological Principles in Predicting Growth (3-PG) models. The results showed that suitable distribution areas for Larix kaempferi were concentrated in Europe and Asia, followed by North America, under current climate conditions. Globally, about 33.75% of the suitable area was in China. Suitable areas decreased and shifted northward in Asia, Europe and China in the RCP scenarios. Larix kaempferi could adapt or move to higher latitudes/altitudes to mitigate the negative impacts of climate change. The NPP of Larix kaempferi in China was 241.85-863.57 g m-2 a-1 simulated by the 3-PG model after local parameterization, which was consistent with the measured NPP. Changes in NPP were predicted in future climates. When the correlations between climate factors and NPP were examined, under the more optimistic scenarios, NPP would increase significantly. The key parameters of the 3-PG model were the optimal temperature for growth, forest age, and the number of days of lost productivity in each frost period. Therefore, climate change has a quantitative and significant impact on the distribution and productivity of L. kaempferi, which was estimated successfully with the two modeling approaches. Our results will contribute to the improved cultivation, environment and management of L. kaempferi and potentially of other deciduous gymnosperms.
Copyright © 2020 Elsevier Ltd. All rights reserved.

Entities:  

Keywords:  3-PG model; MaxEnt model; NPP; RCPs; Sensitivity analysis; Suitable distribution areas

Year:  2020        PMID: 33341471     DOI: 10.1016/j.jenvman.2020.111633

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


  1 in total

1.  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
  1 in total

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