Are variations in heterotrophic soil respiration related to changes in substrate availability and microbial biomass carbon in the subtropical forests?
Are variations in heterotrophic soil respiration related to changes in substrate availability and microbial biomass carbon in the subtropical forests?
复制标题
异养土壤呼吸的变化是否与亚热带森林底物可用性和微生物生物量碳的变化有关？
DOI：
10.1038/srep18370
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发表时间：
2015-12-16
影响因子：
4.6
通讯作者：
Shen W
中科院分区：
文献类型：
--
作者：
Wei H;Chen X;Xiao G;Guenet B;Vicca S;Shen W
土壤温度和水分是公认的异养土壤呼吸(Rh)的控制因素，尽管它们通常只解释了Rh变异性的一部分。其他土壤物理化学和微生物特性如何影响土壤湿度变异性的研究较少。在中国南部的四个亚热带森林中，连续两年对Rh半月和相关土壤性质进行了田间观测，以评估碳有效性和微生物特性对Rh的影响。莱茵针叶林明显低于其他三种阔叶林，并表现出明显的季节变化(P<； )。在这些湿润的亚热带森林中，温度是影响水汽季节变化的主要因素。溶解有机碳(DOC)的含量和可分解性对Rh的变化具有重要意义，但部分壁炉架试验显示DOC含量对Rh的影响与温度的关系不明显。微生物量碳与暖季不同森林间的生物量碳显著相关(P= 0.043)。我们的结果表明，DOC和MBC在某些条件下对Rh的预测可能是重要的，并突出了它们与环境因素对Rh变化的相互影响的复杂性。
Soil temperature and moisture are widely-recognized controlling factors on heterotrophic soil respiration (Rh), although they often explain only a portion of Rhvariability. How other soil physicochemical and microbial properties may contribute to Rhvariability has been less studied. We conducted field measurements on Rhhalf-monthly and associated soil properties monthly for two years in four subtropical forests of southern China to assess influences of carbon availability and microbial properties on Rh. Rhin coniferous forest was significantly lower than that in the other three broadleaf species-dominated forests and exhibited obvious seasonal variations in the four forests (P< 0.05). Temperature was the primary factor influencing the seasonal variability of Rhwhile moisture was not in these humid subtropical forests. The quantity and decomposability of dissolved organic carbon (DOC) were significantly important to Rhvariations, but the effect of DOC content on Rhwas confounded with temperature, as revealed by partial mantel test. Microbial biomass carbon (MBC) was significantly related to Rhvariations across forests during the warm season (P= 0.043). Our results suggest that DOC and MBC may be important when predicting Rhunder some conditions and highlight the complexity by mutual effects of them with environmental factors on Rhvariations.