Sun Na, Zhang Weiwei, Liao Shangqiang, Li Hong
Institute of Plant Nutrition, Resources and Environment, Beijing Academy of Agriculture and Forestry Sciences, Beijing, China.
Institute of Grassland, Flowers and Ecology, Beijing Academy of Agriculture and Forestry Sciences, Beijing, China.
Front Microbiol. 2023 Feb 24;14:1129042. doi: 10.3389/fmicb.2023.1129042. eCollection 2023.
Rhizosphere bacteria can have wide-ranging effects on their host plants, influencing plant biochemical and structural characteristics, and overall productivity. The implications of plant-microbe interactions provides an opportunity to interfere agriculture ecosystem with exogenous regulation of soil microbial community. Therefore, how to efficiently predict soil bacterial community at low cost is becoming a practical demand. Here, we hypothesize that foliar spectral traits can predict the diversity of bacterial community in orchard ecosystem. We tested this hypothesis by studying the ecological linkages between foliar spectral traits and soil bacterial community in a peach orchard in Yanqing, Beijing in 2020. Foliar spectral indexes were strongly correlated with alpha bacterial diversity and abundant genera that can promote soil nutrient conversion and utilization, such as , and at fruit mature stage. Certain unidentified or relative abundance <1% genera were also associated with foliar spectral traits. We selected specific indicators (photochemical reflectance index, normalized difference vegetable index, greenness index, and optimized soil-adjusted vegetation index) of foliar spectral indexes, alpha and beta diversities of bacterial community, and quantified the relations between foliar spectral traits and belowground bacterial community SEM. The results of this study indicated that foliar spectral traits could powerfully predict belowground bacterial diversity. Characterizing plant attributes with easy-accessed foliar spectral indexes provides a new thinking in untangling the complex plant-microbe relationship, which could better cope with the decreased functional attributes (physiological, ecological, and productive traits) in orchard ecosystem.
根际细菌对其寄主植物可产生广泛影响,影响植物的生化和结构特征以及整体生产力。植物与微生物相互作用的意义为通过外源调控土壤微生物群落来干预农业生态系统提供了契机。因此,如何低成本高效预测土壤细菌群落正成为一项实际需求。在此,我们假设叶片光谱特征能够预测果园生态系统中细菌群落的多样性。我们于2020年在北京延庆的一个桃园中,通过研究叶片光谱特征与土壤细菌群落之间的生态联系来验证这一假设。在果实成熟阶段,叶片光谱指数与细菌α多样性以及能够促进土壤养分转化和利用的优势属(如 、 和 )密切相关。某些未鉴定或相对丰度<1%的属也与叶片光谱特征有关。我们选取了叶片光谱指数的特定指标(光化学反射指数、归一化差值植被指数、绿度指数和优化土壤调节植被指数)、细菌群落的α和β多样性,并通过结构方程模型量化了叶片光谱特征与地下细菌群落之间的关系。本研究结果表明,叶片光谱特征能够有力地预测地下细菌多样性。利用易于获取的叶片光谱指数来表征植物属性,为理清复杂的植物 - 微生物关系提供了新思路,有助于更好地应对果园生态系统中功能属性(生理、生态和生产性状)下降的问题。