The hidden risk: Changes in functional potentials of microbial keystone taxa under global climate change jeopardizing soil carbon storage in alpine grasslands
Climate change is endangering the soil carbon stock of alpine grasslands on the Qinghai-Tibetan Plateau (QTP), but the limited comprehension regarding the mechanisms that sustain carbon storage under hydrothermal changes increases the uncertainty associated with this finding. Here, we examined the r...
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Veröffentlicht in: | Environment international 2024-03, Vol.185, p.108516-108516, Article 108516 |
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Sprache: | eng |
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Zusammenfassung: | Climate change is endangering the soil carbon stock of alpine grasslands on the Qinghai-Tibetan Plateau (QTP), but the limited comprehension regarding the mechanisms that sustain carbon storage under hydrothermal changes increases the uncertainty associated with this finding. Here, we examined the relative abundance of soil microbial keystone taxa and their functional potentials, as well as their influence on soil carbon storage with increased precipitation across alpine grasslands on the QTP, China. The findings indicate that alterations in precipitation significantly decreased the relative abundance of the carbon degradation potentials of keystone taxa, such as chemoheterotrophs. The inclusion of keystone taxa and their internal functional potentials in the two best alternative models explained 70% and 63% of the variance in soil organic carbon (SOC) density, respectively. Moreover, we found that changes in chemoheterotrophs had negative effects on SOC density as indicated by a structural equation model, suggesting that some specialized functional potentials of keystone taxa are not conducive to the accumulation of carbon sink. Our study offers valuable insights into the intricate correlation between precipitation-induced alterations in soil microbial keystone taxa and SOC storage, highlighting a rough categorization is difficult to distinguish the hidden threats and the importance of incorporating functional potentials in SOC storage prediction models in response to changing climate. |
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ISSN: | 0160-4120 1873-6750 |
DOI: | 10.1016/j.envint.2024.108516 |