Root respiration is a critical function of root carbon cycling and accounts for a major component of the global carbon budget. However, the insufficient understanding of the global scaling relationships between root traits and respiration rate (R_r) impedes the accurate prediction of carbon effluxes from roots. Here, we analyzed a dataset of 138 species to unravel and quantify the effects of mycorrhizal type, climate, soil, and phylogenetic structure of species on fine root trait-function relationships. Four commonly measured traits were included: root nitrogen content (RNC), specific root length (SRL), root diameter, and root tissue density. We found that mycorrhizal type and climate affected the relationships between fine root traits and R_r. Specifically, the slopes of SRL-R_r and RNC-R_r relationships for ectomycorrhizal (EM) plants were significantly greater than those for arbuscular mycorrhizal (AM) plants, irrespective of the phylogenetic conservatism or plant growth forms. This finding suggested that EM plants consumed more carbon than AM plants for constructing root tissue structures. In a warmer environment, the SRL-R_r relationship was stronger while the RNC-R_r relationship was weaker, possibly because R_r was limited by enzyme activity at low temperature and by substrate supply at high temperature. Our results highlighted the importance of mycorrhizas in influencing the root trait-function relationships. Thus, incorporating mycorrhizal types into trait-based terrestrial biosphere models may help to more accurately predict the future carbon-climate change feedback.

根呼吸是根碳循环的关键功能，是全球碳预算的重要组成部分。然而，对根部性状与呼吸速率（R _r）之间的全局比例关系的了解不足，妨碍了对根部碳排量的准确预测。在这里，我们分析了138个物种的数据集，以阐明和定量菌根类型，气候，土壤和物种的系统发育结构对精细根系性状-功能关系的影响。包括四个通常测量的性状：根氮含量（RNC），比根长（SRL），根直径和根组织密度。我们发现菌根的类型和气候影响了优良根系性状与R _r之间的关系。具体来说，SRL-R的坡度无论系统发育保守性或植物生长形式如何，外生菌根（EM）植物的_r和RNC-R _r关系均显着大于丛枝菌根（AM）植物的_r和RNC-R _r关系。这一发现表明，EM植物比AM植物消耗更多的碳来构建根组织结构。在较热的环境中，SRL-R _r关系更强，而RNC-R _r关系更弱，这可能是因为R _r低温下的酶活性和高温下的底物供应限制了酶的活性。我们的结果突出了菌根在影响根性状-功能关系中的重要性。因此，将菌根类型纳入基于性状的陆地生物圈模型中可能有助于更准确地预测未来的碳气候变化反馈。