Plant roots represent about a quarter of global plant biomass and constitute a primary source of soil organic carbon (C). Yet, considerable uncertainty persists regarding root litter decomposition and their responses to global change factors (GCFs). Much of this uncertainty stems from a limited understanding of the multifactorial effects of GCFs and it remains unclear how these effects are mediated by litter quality, soil conditions and microbial functionality. Using complementary field decomposition and laboratory incubation approaches, we assessed the relative controls of GCF-mediated changes in root litter traits and soil and microbial properties on fine-root decomposition under warming, nitrogen (N) enrichment, and precipitation alteration. We found that warming and N enrichment accelerated fine-root decomposition by over 10%, and their combination showed an additive effect, while precipitation reduction suppressed decomposition overall by 12%, with the suppressive effect being most significant under warming-alone and N enrichment-alone conditions. Significantly, changes in litter quality played a dominant role and accelerated fine-root decomposition by 15% ~ 18% under warming and N enrichment, while changes in soil and microbial properties were predominant and reduced decomposition by 7% ~ 10% under precipitation reduction and the combined warming and N enrichment. Examining only the decomposition environment or litter properties in isolation can distort global change effects on root decomposition, underestimating precipitation reduction impacts by 38% and overstating warming and N effects by up to 73%. These findings highlight that the net impact of GCFs on root litter decomposition hinges on the interplay between GCF-modulated root decomposability and decomposition environment, as well as on the synergistic or antagonistic relationships among GCFs themselves. Our study emphasizes that integrating the legacy effects of multiple GCFs on root traits, soil conditions and microbial functionality would improve our prediction of C and nutrient cycling under interactive global change scenarios.
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