Summary: There is limited knowledge on how the association of trees with different mycorrhizal types shapes soil microbial communities in the context of changing tree diversity levels. We used arbuscular (AM) and ectomycorrhizal (EcM) tree species as con‐ and heterospecific tree species pairs (TSPs), which were established in plots of three tree diversity levels including monocultures, two‐species mixtures and multi‐tree species mixtures in a tree diversity experiment in subtropical China. We found that the tree mycorrhizal type had a significant effect on fungal but not bacterial alpha diversity. Furthermore, only EcM but not AM TSPs fungal alpha diversity increased with tree diversity, and the differences between AM and EcM TSPs disappeared in multi‐species mixtures. Tree mycorrhizal type, tree diversity and their interaction had significant effects on fungal community composition. Neither fungi nor bacteria showed any significant compositional variation in TSPs located in multi‐species mixtures. Accordingly, the most influential taxa driving the tree mycorrhizal differences at low tree diversity were not significant in multi‐tree species mixtures. Collectively, our results indicate that tree mycorrhizal type is an important factor determining the diversity and community composition of soil microbes, and higher tree diversity levels promote convergence of the soil microbial communities. Significance statement: More than 90% of terrestrial plants have symbiotic associations with mycorrhizal fungi which could influence the coexisting microbiota. Systematic understanding of the individual and interactive effects of tree mycorrhizal type and tree species diversity on the soil microbiota is crucial for the mechanistic comprehension of the role of microbes in forest soil ecological processes. Our tree species pair (TSP) concept coupled with random sampling within and across the plots, allowed us the unbiased assessment of tree mycorrhizal type and tree diversity effects on the tree‐tree interaction zone soil microbiota. Unlike in monocultures and two‐species mixtures, we identified species‐rich and converging fungal and bacterial communities in multi‐tree species mixtures. Consequently, we recommend planting species‐rich mixtures of EcM and AM trees, for afforestation and reforestation regimes. Specifically, our findings highlight the significance of tree mycorrhizal type in studying ‘tree diversity – microbial diversity – ecosystem function’ relationships.

Loss of multifunctional microbial communities can negatively affect ecosystem services, especially forest soil nutrient cycling. Therefore, exploration of the genomic potential of soil microbial communities, particularly their constituting subcommunities and taxa for nutrient cycling, is vital to get an in-depth mechanistic understanding for better management of forest soil ecosystems.

Plants sequester carbon through photosynthesis and provide primary productivity for the ecosystem. However, they also simultaneously consume water through transpiration, leading to a carbon-water balance relationship. Agricultural production can be regarded as a form of carbon sequestration behavior. From the perspective of the natural-social-economic complex ecosystem, excessive water usage in food production will aggravate regional water pressure for both domestic and industrial purposes. Hence, achieving a harmonious equilibrium between carbon and water resources during the food production process is a key scientific challenge for ensuring food security and sustainability. Digital intelligence (DI) and cyber-physical-social systems (CPSS) are emerging as the new research paradigms that are causing a substantial shift in the conventional thinking and methodologies across various scientific fields, including ecological science and sustainability studies. This paper outlines our recent efforts in using advanced technologies such as big data, artificial intelligence (AI), digital twins, metaverses, and parallel intelligence to model, analyze, and manage the intricate dynamics and equilibrium among plants, carbon, and water in arid and semiarid ecosystems. It introduces the concept of the carbon-water balance and explores its management at three levels: the individual plant level, the community level, and the natural-social-economic complex ecosystem level. Additionally, we elucidate the significance of agricultural foundation models as fundamental technologies within this context. A case analysis of water usage shows that, given the limited availability of water resources in the context of the carbon-water balance, regional collaboration and optimized allocation have the potential to enhance the utilization efficiency of water resources in the river basin. A suggested approach is to consider the river basin as a unified entity and coordinate the relationship between the upstream, midstream and downstream areas. Furthermore, establishing mechanisms for water resource transfer and trade among different industries can be instrumental in maximizing the benefits derived from water resources. Finally, we envisage a future of agriculture characterized by the integration of digital, robotic and biological farming techniques. This vision aims to incorporate small tasks, big models, and deep intelligence into the regular ecological practices of intelligent agriculture.