Abstract
Forests are major components of global carbon (C) cycling, and hence, it is crucial to explore the drivers of forest functions related to C sequestration. Here, using the multiple linear regression models (MLMs) and structural equation models (SEMs), we evaluated how abiotic (i.e., soil nutrients and topography) and biotic [i.e., functional trait diversity (FTD) and functional trait identity (FTI)] factors regulate aboveground C (AGC) and topsoil (0–30 cm) organic C (SOC) stocks across 104 plots in temperate forests of Northern Iran. The optimal MLMs showed that the community‐weighted mean (CWM) of wood density and functional divergence increased, but functional evenness decreased AGC stock, where FTI values contributed much (i.e., 74.40%) to the explained variance in AGC stock as compared to FTD indices (12.86%) and abiotic factors (12.74%). On contrary, SOC stock was mainly promoted by soil‐available phosphorus, where abiotic factors contributed much (92.62%) to the explained variance as compared to FTD indices (6.73%) and FTI values (0.65%). The final best‐fitted SEMs showed that AGC stock was strongly controlled (β = 0.64) by FTI values (i.e., a latent variable of CWM of wood density and plant maximum height), whereas SOC stock was strongly controlled (β = 0.74) by abiotic factors (i.e., a latent variable of soil‐available phosphorus and total nitrogen). We argue that suitable functional strategies in combination with soil nutrients should be taken into priority during the forestland management and policy plans for the improvement of C stocks in above‐ and belowground compartments of forest ecosystems.