Soil autotrophic and heterotrophic respiration respond differently to land-use change and variations in environmental factors
Soil autotrophic and heterotrophic respiration respond differently to land-use change and variations in environmental factors
复制标题
土壤自养和异养呼吸对土地利用变化和环境因素变化的反应不同
DOI:
10.1016/j.agrformet.2018.01.003
复制
发表时间:
2018-03-15
影响因子:
6.2
通讯作者:
Lin, Ziwen
中科院分区:
文献类型:
--
作者:
Hu, Shuaidong;Li, Yongfu;Lin, Ziwen
Converting natural forests to intensively managed plantations markedly alters soil carbon (C) dynamics. However, the impact of such land-use change on soil respiration (R-S) components remains unclear. The objective of this study was to examine the effect on R-S, autotrophic respiration (R-A) and heterotrophic respiration (R-H) of converting a natural evergreen broadleaf forest to an intensively managed Moso bamboo (Phyllostachys edulis) plantation. A two-year field study was carried out to assess the seasonal dynamics of R-S, R-A and R-H in three broadleaf forest-bamboo plantation pairs, using a portable soil CO2 flux measurement system. Results showed that converting the evergreen broadleaf forest to the bamboo plantation increased the annual cumulative R-S and R-H by 18.8% and 20.9%, respectively, but did not change the annual cumulative R-A. Soil temperature alone explained 48% and 79% of seasonal variations in R-A and R-H, respectively, in the evergreen broadleaf forest, and 68% and 79%, respectively, in the bamboo plantation. The land-use change increased the apparent temperature sensitivity (Q(10)) of R-A, but did not affect that of R-H. Regardless of the land-use type, both R-A and R-H were positively correlated with soil water soluble organic C, but not with soil moisture content. The R-H was positively correlated to soil microbial biomass C (MBC) in the evergreen broadleaf forest, but not in the bamboo plantation. The R-A was not correlated with soil MBC, regardless of the land-use type. Therefore, soil R-A and R-H responded differently to land-use change and variations in environmental factors, suggesting that partitioning of R-S to different components is essential to elucidate mechanisms associated with changes in R-S induced by land-use change and to predict R-S under different climate change scenarios.