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Controlling factors and spatial distribution of gross N transformation rate of global forest soils.

ZHAO Ting1,2, ZHANG Jun-hui1*, WANG Fang1,2, GENG Shi-cong1,2   

  1. (1Key Laboratory of Forest Ecology and Management, Institute of Applied Ecology, Chinese Academy of Sciences, Shenyang 110016, China; 2University of Chinese Academy of Sciences, Beijing 100049, China).
  • Online:2018-12-10 Published:2018-12-10

Abstract: The total transformation rate of soil N and its relative strength determine N conservation and supply capacity of soils. Studies on the controlling factors of total N transformation rate of forest soils have great significance for understanding productivity, N cycling and environmental change of forest ecosystems. Here we conducted random forest model analysis upon 36 literatures of forest soil gross N transformation. We found that critical factors influencing the gross N mineralization rate were in order of TN> SNDPPT>MAT>WWP, the critical factors influencing the gross nitration rate were in order of TN>TC> SNDPPT>CEC, and the critical factors influencing the dissimilatory nitrate reduction to ammonium (DNRA) rate were in order of CLY>AWC>WWP>CEC. Then, a random forest model of total N transformation rate in forest soils was constructed and the spatial distribution of gross soil N mineralization rate, gross nitrification rate and DNRA rate were delivered. The results showed that the gross N mineralization rate ranged 1.672-64.016 mg N·kg-1·d-1, the gross nitration rate was 0.866-16.984 mg N·kg-1·d-1, and the DNRA rate was 0.030-2.045 mg N·kg-1·d-1. The gross transformation rate of soil N had substantial spatial heterogeneity. Specifically, these three transformation rates were very low in most parts of the world, and the spatial distribution of the maximum transformation rates overlapped in northwestern North America, northwestern Europe, and the Eurasian Continental junction.

Key words: Stellera chamaejasme, soil fungal diversity, geostatistics, high-throughput sequencing, spatial heterogeneity, GIS