4.8 Article

Analysis on net primary productivity change of forests and its multi-level driving mechanism - A case study in Changbai Mountains in Northeast China

Journal

Publisher

ELSEVIER SCIENCE INC
DOI: 10.1016/j.techfore.2020.119939

Keywords

Net Primary Productivity (NPP); Spatial autocorrelation analysis; Multi-level driving mechanism; Hierarchical Linear Model (HLM); Changbai Mountains in Northeast China

Funding

  1. Key Project of National Key Research and Development Plan [2017YFC050400103]
  2. National Science and Technology Projects [2017ZX07101004, 2017ZX07108002]
  3. Major Research Plan of National Natural Science Foundation of China [41901234, 51909052]
  4. Fundamental Research Funds for the Central Universities [2015ZCQSB03]
  5. Project of the Youth Top Talents Program of Colleges in Hebei Province [BJ2018117]
  6. National Natural Science Foundation of China [71225005]
  7. Beijing Municipal Education Commission through Innovative Transdisciplinary Program Ecological Restoration Engineering

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It is significant to clarify the driving mechanism of the forest ecosystem changes at different scales in Northeast China with serious forest degradation. With Changbai Mountains in Northeast China as the study area, this study integrated multi-source data to explore the spatio-temporal changes of Net Primary Productivity (NPP) and its spatial agglomeration patterns, and probed its multi-level driving mechanism based on the Hierarchical Linear Model (HLM). The results showed the overall NPP in the study area had a gradual declining trend from southeast to northwest from 2001 to 2015. Besides, the ecological risk regions, including Low-Low (L-L) and High-Low (H-L) cluster types, expanded from 27.56% during 2001-2008 to 28.21% during 2008-2015, suggesting the local departments should focus on optimizing these regions and strengthen the construction of complex forests with large age differences to make the ecological environment healthier. In addition, results from the HLM suggested that key driving factors, e.g., the precipitation and vegetation coverage rate, had significant promoting effects on NPP at the grid scale. Whereas the soil organic matter content, distance to the highway, irrigation rate, percentage of the disaster area had significant inhibitory effects (p < 0.01) on ecological environment at the watershed scale. Finally, the increase of the total investment in ecological engineering might directly promote the ecological recovery at the county scale. Those results could provide a reasonable scientific basis for the rational development and utilization of regional forest resources, and sustainable socio-economic development.

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