研究论文

氮沉降下西南山地针叶林根际和非根际土壤微生物养分限制特征差异

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  • 1中国科学院成都生物研究所, 中国科学院山地生态恢复与生物资源利用重点实验室, 生态恢复与生物多样性保育四川省重点实验室, 成都 610041
    2中国科学院大学, 北京 100049
*(wangqt@cib.ac.cn) 汪其同: 0000-0001-9484-3540
ORCID: 张英: 0000-0003-1671-4529

收稿日期: 2021-09-29

  录用日期: 2021-11-20

  网络出版日期: 2022-01-07

基金资助

国家自然科学基金(31872700);国家自然科学基金(32171757);国家自然科学基金(31901131);中科院“西部之光”交叉团队项目(xbzg-zdsys-202112)

Difference of microbial nutrient limiting characteristics in rhizosphere and bulk soil of coniferous forests under nitrogen deposition in southwest mountain, China

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  • 1Chengdu Institute of Biology, Chinese Academy of Sciences, Key Laboratory of Mountain Ecological Restoration and Bioresource Utilization of Chinese Academy of Sciences, and Ecological Restoration and Biodiversity Conservation Key Laboratory of Sichuan Province, Chengdu 610041, China
    2University of Chinese Academy of Sciences, Beijing 100049, China

Received date: 2021-09-29

  Accepted date: 2021-11-20

  Online published: 2022-01-07

Supported by

National Natural Science Foundation of China(31872700);National Natural Science Foundation of China(32171757);National Natural Science Foundation of China(31901131);Chinese Academy of Sciences (CAS) Interdisciplinary Innovation Team(xbzg-zdsys-202112)

摘要

长期氮(N)沉降诱导了土壤养分失衡, 深刻影响着森林生态系统养分循环过程、生态功能及其可持续发展。前期研究发现N沉降下西南森林树木生长受到不同程度的磷(P)限制, 而土壤微生物是否表现出与植物养分限制特征协同的响应仍未明确。基于此, 该研究以西南山地典型人工针叶林——华山松(Pinus armandii)林为对象, 通过野外原位模拟N沉降实验, 测定了土壤有效养分供给、土壤微生物生物量(碳(C)、N、P)含量以及胞外酶活性, 结合生态酶化学计量的3种模型(比值模型、矢量分析模型与阈值元素比率模型)验证森林根际/非根际土壤中微生物是否受P养分限制。结果表明: (1) N添加下两个土壤位置(根际和非根际土壤)酸性磷酸酶(AP)��性分别显著升高52.5%和53.2%, 导致土壤酶活性N:P分别降低7.8%和4.8%; (2)矢量模型分析发现N添加下两个土壤位置的矢量角度均大于45°, 根际土壤和非根际土壤的矢量角度分别为52.2°和49.0°; (3) N添加下两个土壤位置C:P阈值(TERC:P)显著降低, 导致C:P阈值与土壤有效C:P的比值(TERC:P/AvC:P)远小于1, 且根际土壤表现更明显。综上所述, 3个模型均表明N沉降加剧了土壤微生物代谢的P限制, 且根际土壤微生物P限制程度更强, 这与土壤和微生物养分含量及其化学计量特征密切相关。该研究结果可为全球气候变化下森林生态系统的适应性管理提供重要科学依据。

本文引用格式

张英, 张常洪, 汪其同, 朱晓敏, 尹华军 . 氮沉降下西南山地针叶林根际和非根际土壤微生物养分限制特征差异[J]. 植物生态学报, 2022 , 46(4) : 473 -483 . DOI: 10.17521/cjpe.2021.0346

Abstract

Aims Long-term nitrogen (N) deposition induces soil nutrient imbalance and profoundly affects nutrient cycling processes, ecological functions and the sustainable development of forest ecosystems. Although previous studies have found that N deposition increased phosphorus (P) limitation of forest trees in southwest mountainous areas, China, whether soil microorganisms showed synergistic response with plants remains unclear.

Methods In this study, we measured soil available nutrients, soil microbial biomass carbon (C), N, P and extracellular enzyme activities in a typical subalpine coniferous plantation (Pinus armandii) with chronic N addition treatments in southwest China. Furthermore, three models of ecoenzymatic stoichiometry, i.e., enzymatic ratio model, vector analysis model and threshold element ratio model were used to evaluate changes of microbial nutrient limitation under N addition.

Important findings The results showed that: 1) N addition significantly increased the P-acquiring enzyme activities by 52.5% and 53.2% in rhizosphere soil and bulk soil respectively, leading to a decrease of enzymatic N:P ratio by 7.8% and 4.8% compared to the control in rhizosphere soil and bulk soil respectively. 2) Vector model analysis found that vector angles of two soil compartments under N addition exceeded 45°, and the vector angles of rhizosphere soil and bulk soil were 52.2° and 49.0°, respectively. 3) The C:P threshold ratios (TERC:P) of microbes in two soil compartments were significantly reduced by N addition. Consequently, the ratio of TERC:P to available C:P (AvC:P) was much less than 1, and the response of rhizosphere microbes was more significant. Collectively, all three models of ecoenzymatic stoichiometry indicated that N deposition aggravated P-limitation of microbial metabolism, and the extent of P limitation was more intense in the rhizosphere soil, which was closely related to nutrient contents and stoichiometric ratios of soil and microbes. The findings of this study provide an important scientific basis for adaptive management of forest ecosystems under global climate change.

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