1. Soil carbon stocks in plantations and natural forests of the sub-tropics
- Author
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Zhang Yanjie, Xu Yan, Lu ShunBao, and Fu Xiangping
- Subjects
Soil test ,Natural forest ,04 agricultural and veterinary sciences ,General Medicine ,Soil carbon ,Mineralization (soil science) ,Subtropics ,Vegetation ,010501 environmental sciences ,01 natural sciences ,Agronomy ,Soil pH ,040103 agronomy & agriculture ,0401 agriculture, forestry, and fisheries ,Environmental science ,Water content ,0105 earth and related environmental sciences - Abstract
Purpose Soil carbon (C) storage plays an important role in the mitigation of atmospheric CO2 emission. Soil C pools under different vegetation are distinct and need to be investigated. However, there are still large quantities of data shortages, which should be remedied by field and systematic studies. Materials and methods Soil was collected at 0–10 cm depth from subtropical natural vegetation and plantations both in southeast China and southeast Queensland, Australia, respectively. Soil samples were assayed for soil organic C; organic N and inorganic N; and mineralization of SOC; total C, N, and P; and pH. Results and discussion Our results suggested soil C concentrations in natural vegetation ranged from 6.25% to 9.20%, whereas soil C concentrations in plantations ranged from 1.08% to 2.69%. No significant differences were found among vegetation along altitudinal gradients, whereas plantations with different tree species had different soil C concentrations, being higher in broadleaf-species plantations than in coniferous-species plantations. But there were no differences in soil C between single-species plantations and mixed-species plantations. Soil C concentrations in plantations were correlated with soil moisture, soil pH and dissolved organic C concentrations; Whereas soil C concentrations in natural vegetation were significantly correlated with soil moisture, soil pH and NO3− concentrations. Conclusions These results can contribute to the remedy of data shortages and provide the data necessary for model projections and informed decisions in the future.
- Published
- 2019