Plant Community Associates with Rare Rather than Abundant Fungal Taxa in Alpine Grassland Soils.

The importance of the rare microbial biosphere in maintaining biodiversity and ecological functions has been highlighted recently. However, the current understanding of the spatial distribution of rare microbial taxa is still limited, with only a few investigations for rare prokaryotes and virtually none for rare fungi. Here, we investigated the spatial patterns of rare and abundant fungal taxa in alpine grassland soils across 2,000 km of the Qinghai-Tibetan plateau. We found that most locally rare fungal taxa remained rare (13.07%) or were absent (82.85%) in other sites, whereas only a small proportion (4.06%) shifted between rare and abundant among sites. Although they differed in terms of diversity levels and compositions, the distance decay relationships of both the rare and the abundant fungal taxa were valid and displayed similar turnover rates. Moreover, the community assemblies of both rare and abundant fungal taxa were predominantly controlled by deterministic rather than stochastic processes. Notably, the community composition of rare rather than abundant fungal taxa associated with the plant community composition. In summary, this study advances our understanding of the biogeographic features of rare fungal taxa in alpine grasslands and highlights the concordance between plant communities and rare fungal subcommunities in soil. IMPORTANCE Our current understanding of the ecology and functions of rare microbial taxa largely relies on research conducted on prokaryotes. Despite the key ecological roles of soil fungi, little is known about the biogeographic patterns and drivers of rare and abundant fungi in soils. In this study, we investigated the spatial patterns of rare and abundant fungal taxa in Qinghai-Tibetan plateau (QTP) alpine grassland soils across 2,000 km, with a special concentration on the importance of the plant communities in shaping rare fungal taxa. We showed that rare fungal taxa generally had a biogeographic pattern that was similar to that of abundant fungal taxa in alpine grassland soils on the QTP. Furthermore, the plant community composition was strongly related to the community composition of rare taxa but not abundant taxa. In summary, this study significantly increases our biogeographic and ecological knowledge of rare fungal taxa in alpine grassland soils.

Machine learning in soil nutrient dynamics of alpine grasslands.

As a terrestrial ecosystem, alpine grasslands feature diverse vegetation types and play key roles in regulating water resources and carbon storage, thus shaping global climate. The dynamics of soil nutrients in this ecosystem, responding to regional climate change, directly impact primary productivity. This review comprehensively explored the effects of climate change on soil nitrogen (N), phosphorus (P), and their balance in the alpine meadows, highlighting the significant roles these nutrients played in plant growth and species diversity. We also shed light on machine learning utilization in soil nutrient evaluation. As global warming continues, alongside shifting precipitation patterns, soil characteristics of grasslands, such as moisture and pH values vary significantly, further altering the availability and composition of soil nutrients. The rising air temperature in alpine regions substantially enhances the activity of soil organisms, accelerating nutrient mineralization and the decomposition of organic materials. Combined with varied nutrient input, such as increased N deposition, plant growth and species composition are changing. With the robust capacity to use and integrate diverse data sources, including satellite imagery, sensor-collected spectral data, camera-captured videos, and common knowledge-based text and audio, machine learning offers rapid and accurate assessments of the changes in soil nutrients and associated determinants, such as soil moisture. When combined with powerful large language models like ChatGPT, these tools provide invaluable insights and strategies for effective grassland management, aiming to foster a sustainable ecosystem that balances high productivity and advanced services with reduced environmental impacts.

Environmental selection overturns the decay relationship of soil prokaryotic community over geographic distance across grassland biotas.

Though being fundamental to global diversity distribution, little is known about the geographic pattern of soil microorganisms across different biotas on a large scale. Here, we investigated soil prokaryotic communities from Chinese northern grasslands on a scale up to 4000 km in both alpine and temperate biotas. Prokaryotic similarities increased over geographic distance after tipping points of 1760-1920 km, generating a significant U-shape pattern. Such pattern was likely due to decreased disparities in environmental heterogeneity over geographic distance when across biotas, supported by three lines of evidences: (1) prokaryotic similarities still decreased with the environmental distance, (2) environmental selection dominated prokaryotic assembly, and (3) short-term environmental heterogeneity followed the U-shape pattern spatially, especially attributed to dissolved nutrients. In sum, these results demonstrate that environmental selection overwhelmed the geographic 'distance' effect when across biotas, overturning the previously well-accepted geographic pattern for microbes on a large scale.