Abstract
Fine roots (≤2 mm in diameter) play a more significant role in regulating the biogeochemical cycles of forest ecosystems, but our current knowledge of fine root stoichiometry and its driving factors is extremely limited. In this study, fine root biomass (FRB) and their carbon (C), nitrogen (N) and phosphorus (P) concentrations were measured from dominant forests along environmental gradients in Northwestern China. The results showed that forest type (coniferous vs. broadleaved, and plantation vs. secondary forest) and climatic factors had no effects on FRB. FRB was only correlated with soil P, C:P and N:P in coniferous forests and N:P in secondary forests. Thus, forest type, soil C:N:P stoichiometry and climatic factors were less important to FRB. The fine root C and C:N and C:P were higher, and N and P were lower in coniferous than in broadleaved forests. Only fine root N concentration was higher in plantations than in secondary forests. The fine root C was positively correlated with soil C, N and C:N, C:P and N:P except in coniferous forests. The fine root N was negatively correlated soil C:N, C:P and N:P in plantations and C:N in broadleaved forests, but positively correlated with soil C, N, C:P and N:P in secondary forests. The fine root P was positively correlated with soil P in plantations and in coniferous forests, but negatively correlated with soil C:N, C:P and N:P in all forest types. The fine root C in broadleaved and in secondary forests was positively correlated with mean annual precipitation (MAP) and fine root N and N:P in plantations were negatively correlated with MAP. Only the fine root P and C:P in broadleaved forests were correlated with mean annual temperature (MAT). Collectively, forest type, soil C:N:P stoichiometry and climatic factors explained 29, 13 and 12% of the variation in the fine root C, N and P, and their most important explanatory variables were leaf form, soil C:N and soil C:P, respectively. These results advance our knowledge about the regional fine root stoichiometry and its driving factors and provide basic data for improving the key below-ground parameters for biogeochemical models.