Chang Yuanyuan, Chen Fu, Zhu Yanfeng, You Yunnan, Cheng Yanjun, Ma Jing
School of Public Policy and Management, China University of Mining and Technology, Xuzhou, China.
School of Public Administration, Hohai University, Nanjing, China.
Front Microbiol. 2022 Aug 25;13:992816. doi: 10.3389/fmicb.2022.992816. eCollection 2022.
Vegetation recovery is an important marker of ecosystem health in the mining area. Clarifying the influence of vegetation recovery on the characteristics of soil microbial community and its assembly process can improve our understanding of the ecological resilience and self-maintaining mechanism in the open-pit mining area. For this purpose, we employed MiSeq high-throughput sequencing coupled with null model analysis to determine the composition, molecular ecological network characteristics, key bacterial and fungal clusters, and the assembly mechanism of the soil microbial communities in shrubs (BL), coniferous forest (), broad-leaved forests (BF), mixed forest (MF), and the control plot (CK, the poplar plantation nearby that had been continuously grown for over 30 a without disturbance). The results showed that the vegetation restoration model had a significant influence on the α-diversity of the microbial community ( < 0.05). Compared with CK, Sobs and Shannon index of MF and have increased by 35.29, 3.50, and 25.18%, 1.05%, respectively, whereas there was no significant difference in the α-diversity of fungal community among different vegetation restoration types, , , , and were the dominant phyla. The diversity of the first two phyla was significantly higher than those of CK. However, the diversity of the last two phyla was dramatically lower than those of CK ( < 0.05). and were dominant phyla in the fungal community. The abundance and diversity of were significantly higher than those of CK, while the abundance and diversity of the latter were considerably lower than those of CK ( < 0.05). The stochastic process governed the assembly of the soil microbial community, and the contribution rate to the bacterial community construction of CK, , BF, and MF was 100.0%. Except for MF, where the soil fungal community assembly was governed by the deterministic process, all other fungal communities were governed by the stochastic process. and are key taxa of the bacterial network, while , , and are the key taxa of the fungal network. All these results might provide the theoretical foundation for restoring the fragile ecosystem in the global mining region.
植被恢复是矿区生态系统健康的重要标志。阐明植被恢复对土壤微生物群落特征及其组装过程的影响，有助于我们更好地理解露天矿区的生态恢复力和自我维持机制。为此，我们采用MiSeq高通量测序结合空模型分析，以确定灌木（BL）、针叶林（）、阔叶林（BF）、混交林（MF）以及对照样地（CK，附近连续种植30多年且未受干扰的杨树林）土壤微生物群落的组成、分子生态网络特征、关键细菌和真菌类群以及组装机制。结果表明，植被恢复模式对微生物群落的α多样性有显著影响（<0.05）。与CK相比，MF和的Sobs和香农指数分别增加了35.29%、3.50%和25.18%、1.05%，而不同植被恢复类型间真菌群落的α多样性无显著差异，、、、和为优势门。前两个门的多样性显著高于CK。然而，后两个门的多样性显著低于CK（<0.05）。和是真菌群落中的优势门。前者的丰度和多样性显著高于CK，而后者的丰度和多样性显著低于CK（<0.05）。随机过程主导土壤微生物群落的组装，CK、、BF和MF对细菌群落构建的贡献率为100.0%。除MF的土壤真菌群落组装受确定性过程主导外，其他真菌群落均受随机过程主导。和是细菌网络的关键类群，而、、和是真菌网络的关键类群。所有这些结果可能为恢复全球矿区脆弱生态系统提供理论基础。
