Scale-dependent variations in photosynthetic processes mediate net primary productivity in temperate forests

Abstract

The net primary productivity (NPP) of forest ecosystems plays a crucial role in regulating the terrestrial carbon cycle under global climate change. While the temporal effect driven by ecosystem processes on NPP variations is well-documented, spatial variations (from local to regional scales) remain inadequately understood. To evaluate the scale-dependent effects of productivity, predictions from the Biome-BGC model were compared with moderate-resolution imaging spectroradiometer (MODIS) and biometric NPP data in a large temperate forest region at both local and regional levels. Linear mixed-effect models and variance partitioning analysis were used to quantify the effects of environmental heterogeneity and trait variation on simulated NPP at varying spatial scales. Results show that NPP had considerable predictability at the local scale, with a coefficient of determination (R²) of 0.37, but this predictability declined significantly to 0.02 ​at the regional scale. Environmental heterogeneity and photosynthetic traits collectively explained 94.8% of the local variation in NPP, which decreased to 86.7% regionally due to the reduced common effects among these variables. Locally, the leaf area index (LAI) predominated (34.6%), while at regional scales, the stomatal conductance and maximum carboxylation rate were more influential (41.1%). Our study suggests that environmental heterogeneity drives the photosynthetic processes that mediate NPP variations across spatial scales. Incorporating heterogeneous local conditions and trait variations into analyses could enhance future research on the relationship between climate and carbon cycles at larger scales.