欢迎访问《生态学杂志》官方网站,今天是 分享到:

生态学杂志 ›› 2023, Vol. 42 ›› Issue (3): 534-543.doi: 10.13292/j.1000-4890.202303.007

• 研究报告 • 上一篇    下一篇

不同干扰方式下热带雨林土壤微生物群落自然恢复特征和构建机制

于晶晶,丛微,丁易,靳利晓,张于光*   

  1. (中国林业科学研究院森林生态环境与自然保护研究所, 生物多样性保护国家林业和草原局重点实验室, 北京 100091)
  • 出版日期:2023-03-10 发布日期:2023-03-06

Natural restoration characteristics and assembly mechanisms of soil microbial community in tropical rainforest under different  disturbance types.

YU Jingjing, CONG Wei, DING Yi, JIN Lixiao, ZHANG Yuguang*   

  1. (Ecology and Nature Conservation Institute, Chinese Academy of Forestry, Key Laboratory of Biological Conservation of National Forestry and Grassland Administration, Beijing 100091, China).

  • Online:2023-03-10 Published:2023-03-06

摘要: 为探明植被自然恢复过程中的森林土壤微生物群落恢复特征和构建机制,本研究利用Illumina高通量测序技术,选择热带雨林经刀耕火种、皆伐和择伐3种干扰方式后自然恢复40~60年的森林类型以及老龄林为对象,研究森林土壤微生物的群落结构及其相互关系,并利用Null模型定量分析确定性过程和随机性过程在微生物群落构建过程中的相对贡献。结果表明,刀耕火种干扰后,全氮、水解性氮和速效钾等土壤理化性质与老龄林无显著差异,但植物多样性仍显著低于老龄林(P<0.05);土壤细菌的多样性指数与老龄林无显著差异,而土壤真菌的丰富度指数显著低于老龄林(P<0.05)。皆伐和择伐干扰后全氮、有效磷和速效钾等大多数土壤理化性质以及植物多样性显著高于老龄林(P<0.05),但土壤微生物多样性无显著差异。3种不同干扰方式后的土壤微生物群落结构与老龄林存在显著差异(P<0.05)。分子生态网络分析表明,刀耕火种和皆伐降低了土壤微生物网络复杂性,且土壤细菌的网络结构(总节点数、总连接数和模块性)大于真菌;而择伐增加了土壤微生物网络复杂性。Null模型分析表明,不同干扰类型的土壤微生物群落随机性过程相对贡献(细菌为54.76%~66.58%,真菌为87.62%~93.57%)高于确定性过程(细菌为33.42%~45.24%,真菌为6.73%~12.38%)。刀耕火种干扰方式对土壤微生物多样性和群落结构的影响最大,经过较长时间的自然恢复,土壤微生物的多样性得到了较好的恢复,土壤细菌的恢复程度高于真菌,但土壤微生物的群落结构和相互关系仍然存在较大的差异。本研究探讨了不同干扰影响下的森林土壤微生物群落结构及其构建机制,对预测土壤微生物的生态系统功能及其对环境变化的响应具有重要意义。


关键词: 土壤微生物, 群落恢复, 干扰类型, 生态网络, 构建机制

Abstract: Community structure and co-occurrence relationships of soil microorganisms were studied using Illumina high-throughput sequencing technology to better understand restoration characteristics and assembly mechanisms of soil microbial communities during natural restoration of forest. Tropical rainforests with naturally restored for 40-60 years after three types of disturbance (slash and burn, clear cutting, and selective cutting) were compared with old-growth forests. A Null model was used to quantify the relative contributions of deterministic processes and stochastic processes in microbial community assembly. Results showed that soil physicochemical properties (total nitrogen, hydrolysable nitrogen, and available potassium) in the slash and burn forests were not significantly different from that in the old-growth forests. Plant diversity was significantly lower than old-growth forests (P<0.05). Soil bacterial diversity was not significantly different from that of old-growth forests, but soil fungi richness was significantly lower (P<0.05). Most soil physicochemical properties, including total nitrogen, available phosphorus and available potassium, as well as plant diversity, were significantly higher after clear cutting and selective cutting than that in old-growth forests (P<0.05). There was no significant difference in soil microbial diversity. Soil microbial community structure of forests from the three different disturbance types was significantly different from that of old-growth forests (P<0.05). Results of ecological network analysis showed that slash and burn and clear cutting disturbances reduced network complexity of soil microorganisms, while selective cutting increased the complexity. Network structure (total nodes, total links and modularity) of soil bacteria was greater than that of soil fungi. The Null model analysis showed that the relative contribution of stochastic processes (bacteria: 54.76%-66.58%; fungi: 87.62%-93.57%) was higher than deterministic processes (bacteria: 33.42%-45.24%; fungi: 6.73%-12.38%). The slash and burn disturbance had the greatest impact on soil microbial diversity and community structure. After a long-term natural recovery, soil microbial diversity did improve, with greater recovery for bacteria than for fungi, but with large differences in soil microbial community structure and relationships. Our study elucidated microbial community structure and assembly processes in forest soils affected by different disturbances, which is important for predicting ecosystem function of soil microorganisms and their responses to environmental changes.


Key words: soil microorganisms, community recovery, disturbance type, ecological network, assembly mechanism.