Global changes can alter plant inputs from both above-and belowground, which, thus, may differently affect soil carbon and microbial communities. However, the general patterns of how plant input changes affect them in forests remain unclear. By conducting a meta-analysis of 3193 observations from 166 experiments worldwide, we found that alterations in aboveground litter and/or root inputs had profound effects on soil carbon and microbial communities in forest ecosystems. Litter addition stimulated soil organic carbon (SOC) pools and microbial biomass, whereas removal of litter, roots or both (no inputs) decreased them. The increased SOC under litter addition suggested that aboveground litter inputs benefit SOC sequestration despite accelerated decomposition. Unlike root removal, litter alterations and no inputs altered particulate organic carbon, whereas all detrital treatments did not significantly change mineral-associated organic carbon. In addition, detrital treatments contrastingly altered soil microbial community, with litter addition or removal shifting it toward fungi, whereas root removal shifting it toward bacteria. Furthermore, the responses of soil carbon and microbial biomass to litter alterations positively correlated with litter input rate and total litter input, suggesting that litter input quantity is a critical controller of belowground processes. Taken together, these findings provide critical insights into understanding how altered plant productivity and allocation affects soil carbon cycling, microbial communities and functioning of forest ecosystems under global changes. Future studies can take full advantage of the existing plant detritus experiments and should focus on the relative roles of litter and roots in forming SOC and its fractions.

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So far, no research has used the partial order algorithm for the mining of hospital medical technology. This paper proposed a novel knowledge discovery method of hospital medical technology based on partial ordered structure diagrams, constructed attribute partial ordered structure diagram and object partial ordered structure diagram for the formal context constructed by hospital set and medical technology set, and finally analyzed them using the knowledge discovery method. The experiments show that the partial ordered structure diagram can effectively visualize the structural relationships between hospital sets and medical technology sets, and the distribution characteristics of medical technology sets in hospital sets and the rules of medical technology sets owned by hospital sets can be obtained based on the node, branch, and group structure relationships of the partial ordered structure diagram.