Linking leaf traits to the temporal stability of above- and belowground productivity under global change and land use scenarios in a semi-arid grassland of Inner Mongolia

The biotic drivers for the temporal stability of aboveground net productivity (ANPP) in natural ecosystems are well understood. However, knowledge gaps still exist regarding the relative importance of biotic and abiotic drivers regulating the temporal stability of aboveground productivity (ANPP), belowground net productivity (BNPP), and community net productivity (NPP) under global change and land use scenarios. Thus, in this study, we aimed to study the effects of increased water and nitrogen availability on temporal stability of ANPP, BNPP, and NPP and underlying mechanisms at sites with different long-term grazing histories in typical grasslands of the Inner Mongolia. The results suggested that resource addition affected the ANPP stability, but it did not change the stability of BNPP and NPP, which were all mediated by grazing histories. Most importantly, our study further indicated that species asynchrony, primarily contributed to the stability of ANPP and NPP by weakening their variation, and species asynchrony was regulated directly by plant diversity-related variables and indirectly by soil variables which were affected by resource addition and grazing history. In addition, an increase of ANPP stimulated under resource addition was a secondary contributor to ANPP stability. Specifically, the community-weighted mean of specific leaf area (CWM SLA) regulated the ANPP stability indirectly by promoting species asynchrony, while functional diversity of leaf area and SLA both directly controlled the BNPP stability. Findings of our study demonstrate that different mechanisms drove temporal stability of above- and belowground productivity. Our study has important implications for maintaining the temporal stability of community productivity and for establishing sustainable management practices of semi-arid grasslands under global change and land use scenarios.