植物生态学报 ›› 2018, Vol. 42 ›› Issue (3): 382-396.DOI: 10.17521/cjpe.2017.0050

• 研究论文 • 上一篇    下一篇

昭苏山地草甸4种典型土地利用方式下的土壤呼吸特征

王祥1,朱亚琼1,郑伟1,2,*(),关正翾1,盛建东1   

  1. 1 新疆农业大学草业与环境科学学院, 乌鲁木齐 830052
    2 新疆维吾尔自治区草地资源与生态重点实验室, 乌鲁木齐 830052
  • 出版日期:2018-03-20 发布日期:2017-06-16
  • 通讯作者: 郑伟 ORCID:0000-0002-5627-9042
  • 基金资助:
    中国科学院战略性先导科技专项(XDA05050405);国家自然科学基金(31660692);农业部“国家牧草产业技术体系”项目(CARS34)

Soil respiration features of mountain meadows under four typical land use types in Zhaosu Basin

WANG Xiang1,ZHU Ya-Qiong1,ZHENG Wei1,2,*(),GUAN Zheng-Xuan1,SHENG Jian-Dong1   

  1. 1 College of Pratacultural and Environmental Science, Xinjiang Agricultural University, ürümqi 830052, China;
    2 Xinjiang Key Laboratory of Grassland Resources and Ecology, ürümqi 830052, China;
  • Online:2018-03-20 Published:2017-06-16
  • Contact: Wei ZHENG ORCID:0000-0002-5627-9042
  • Supported by:
    Supported by the Strategic Priority Research Program of Chinese Academy of Sciences(XDA05050405);the Natural Science Foundation of China(31660692);the Modern Agroindustry Technology Research System.(CARS34)

摘要:

为探讨不同土地利用方式对新疆昭苏天山北坡山地草甸土壤呼吸速率的影响, 于2015年和2016年的4月底至9月初, 用土壤呼吸测量仪对补播草地(RG)、豆禾混播草地(LG)、围封草地(NG)和农田(CR)的土壤呼吸进行测定, 并分析了影响土壤呼吸速率的土壤生物和水热因子。结果表明: 1)土壤呼吸速率在2015年NG和CR呈现双峰值, RG和LG呈现单峰曲线, 各处理均在8月达到最大值。2016年各处理峰值出现的时间不同, RG和LG在6月底达到最大值, NG和CR在7月底达到最大值; 监测期内平均土壤呼吸速率由大到小依次为: NG > RG > CR > LG。2)各样地土壤呼吸速率与土壤温度呈指数正相关关系; 土壤含水量与土壤呼吸的关系可能由于此地段常年湿润, 土壤含水量较高, 从而抑制土壤呼吸, 土壤呼吸与土壤体积含水量呈线性负相关关系; 土壤呼吸的温度敏感指数(Q10)大小为NG > CR > RG > LG。3)不同处理的土壤微生物以细菌为主, 放线菌次之, 真菌居第三, 各样地总微生物生物量为: NG > RG > CR > LG, 与各样地平均土壤呼吸速率大小一致, 拟合分析显示RG土壤呼吸与放线菌呈显著的线性相关关系, LG土壤呼吸与细菌和放线菌呈显著线性相关关系。不同处理微生物生物量碳平均含量为CR > NG > LG > RG, 拟合分析显示RG与CR的土壤呼吸速率与微生物生物量碳呈显著线性相关关系, 其中CR的土壤呼吸速率与微生物生物量碳极显著相关; 4)各样地酶活性与土壤呼吸的相关关系分析显示, 只有蛋白酶和蔗糖酶与土壤呼吸有相关关系, 而蔗糖酶对土壤呼吸的影响更大。豆禾混播草地和补播草地相对于围封草地和农田, 土壤呼吸速率显著降低, 草地土壤的固碳能力显著提高。

关键词: 土地利用方式, 山地草甸, 土壤呼吸速率, 土壤温度, 土壤含水量, 土壤微生物, 土壤微生物生物量碳, 土壤酶活性

Abstract:

Aims Our objective was to explore the effects of different land use types on soil respiration rates in the mountain meadows of Tianshan Mountain, Zhaosu Racecourse, Xinjiang, China from 2015 to 2016.

Methods Four impermanent plots with different land use types (legume-grass mixture, LG; reseeding grassland, RG; natural grassland, NG; cropland, CR), which were established in 2013, were selected. The soil respiration rates in the growing seasons of two consecutive years (from April to September in 2015 and 2016) were measured using LI-8100A Soil Respiration System. Soil temperatures at 5 cm depth and soil water content at 0-10 cm depth were measured simultaneously. We also investigated soil biological properties including soil microflora structures, soil microbial biomass carbon, and soil enzyme activity. The hydrothermal and soil biological impacts on soil respiration rates were analyzed using the relationship among soil hydrothermal factors, soil microflora factors, and soil enzyme activities.

Important findings We found that: 1) in 2015, the temporal variation of soil respiration showed double peaks in NG and RC plots, but showed a single peak in RG and LG plots, and it reached the maximum in August in all plots. This temporal pattern was different in 2016. Soil respiration reached the maximum at the end of June in RG and LG, and at the end of July in NG and CR. 2) For the whole study period, the average soil respiration rate was in the order of: NG > RG > CR > LG. 3) Soil respiration rate was positively correlated with soil temperature, and negatively correlated with soil volumetric water content. The temperature sensitivity of soil respiration (Q10) was in the order of: NG > CR > RG > LG. 4) Bacteria were dominant among soil microbes in all type of plots, followed by actinomycetes and fungi were the least abundant. The total soil microbial biomass was in the order of: NG > RG > CR > LG, which was consistent with the average soil respiration rate. The fitting analysis showed that soil respiration was positively correlated with the abundance of actinomycetes in RG (p < 0.05), and was positively correlated with the abundances of bacteria and actinomycetes in LG (p < 0.05). 5) The average microbial biomass carbon was in the order of: CR > NG > LG > RG. Fidelity analysis showed that soil respiration rate was significantly positively correlated with microbial biomass carbon in GR and CR (p < 0.05). 6) Among the examined enzymes, only protease and sucrase had a correlation with soil respiration, with sucrase having a greater effect. Changing the degraded mountain meadow to legume-grass mixture and reseeding grassland could decrease soil respiration rates, potentially benefiting carbon sequestration.

Key words: land use type, mountain meadow, soil respiration rate, soil temperature, soil water content, soil microflora, soil microbial carbon, soil enzyme activity