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Effects of stand age on soil respiration in Pinus massoniana plantations in the hilly red soil region of Southern China

Author:
Yu, Kunyong, Yao, Xiong, Deng, Yangbo, Lai, Zhuangjie, Lin, Lingchen, Liu, Jian
Source:
Catena 2019 v.178 pp. 313-321
ISSN:
0341-8162
Subject:
Pinus massoniana, afforestation, carbon dioxide, carbon sequestration, chronosequences, climate change, global carbon budget, microclimate, plantations, prediction, regression analysis, seasonal variation, soil erosion, soil organic carbon, soil respiration, soil temperature, stand age, summer, winter, China
Abstract:
It is of great importance to assess the effect of stand age on soil respiration (SR) to understand the potential carbon sequestration capacity of afforestation. In this study, we investigated the changes in SR and microclimate variables in a chronosequence of four different aged stands (8-, 17-, 27-, and 36-year-old) in a Pinus massoniana plantation in the soil erosion area of southern China. SR was found to have obvious seasonal dynamics among the four aged stands, and the highest and lowest value in summer and winter, respectively. We also found that SR increased with increasing stand age, and the mean SRs for the 8-, 17-, 27-, and 36-year-old stands were 1.45, 1.83, 2.03, and 2.32 μmol CO2 m−2 s−1, respectively. Furthermore, all stands showed that SR increased exponentially with increasing soil temperature and that the temperature sensitivity of SR (Q10) was 2.08, 2.09, 2.23, and 2.19 for 8-, 17-, 27-, and 36-year-old stands, respectively. Moreover, the Q10 values for the 27- and 36-year-old stands were significantly higher than those of the other two stands (p < 0.05). Stepwise multiple regression analysis indicated that soil temperature had a greater effect on SR than soil organic carbon. This study provides insights for estimating SR in P. massoniana plantations in the eroded area of southern China and highlights the need to consider the effect of stand age and seasonal patterns when predicting the carbon budget under different future climate change scenarios.
Agid:
6351561