尾矿
植被(病理学)
植被覆盖
环境科学
封面(代数)
资源(消歧)
地球科学
地质学
生态学
化学
土地利用
工程类
生物
医学
机械工程
计算机网络
物理化学
病理
计算机科学
作者
Wenliang Ju,Jordi Sardans,Haijian Bing,Sheng Wang,Dengke Ma,Yongxing Cui,Chengjiao Duan,Xiankun Li,Qiaohui Fan,Josep Peñuelas,Linchuan Fang
标识
DOI:10.1021/acs.est.4c06081
摘要
Resource demand by soil microorganisms critically influences microbial metabolism and then influences ecosystem resilience and multifunctionality. The ecological remediation of abandoned tailings is a topic of broad interest, yet our understanding of microbial metabolic status in restored soils, particularly at the aggregate scale, remains limited. This study investigated microbial resources within soil aggregates from revegetated tailings and applied a vector model of ecoenzymatic stoichiometry to examine how different vegetation patterns (grassland, forest, or bare land control) impact microbial resource limitation. Five-year vegetation restoration significantly elevated carbon (C) and nitrogen (N) concentrations and their stoichiometric ratios in soil aggregates (approximately 2-fold), although these increases were not translated to in the microbial biomass and its stoichiometry. The activities of C- and phosphorus (P)-acquiring extracellular enzymes in these aggregates increased substantially postvegetation, with the most pronounced escalation in macroaggregates (>0.25 mm). The vector model results indicated soil microbial metabolism was colimited by C and P, most acutely in microaggregates (<0.25 mm). This colimitation was exacerbated by monotypic vegetation cover but mitigated under diversified vegetation cover. Soil nutrient stoichiometric ratios in vegetation restoration controlled microbial resource limitation, overshadowing the impact of heavy metals. Our findings underscore that optimizing resource allocation within soil aggregates through strategic revegetation can enhance microbial metabolism in tailings, which advocates for the implementation of diverse vegetation covers as a viable strategy to improve the ecological development of degraded landscapes.
科研通智能强力驱动
Strongly Powered by AbleSci AI