The spatiotemporal variations in ecosystem photosynthetic quantum yield and their drivers

Abstract

The quantum yield (α) of photosynthesis represents the maximum light use efficiency (LUE) as indicated by the initial slope of photosynthetic light response curves. α is an important variable in LUE-based models which are widely used to simulate gross primary productivity (GPP) from regional to global scales. However, the spatiotemporal variations in α at the ecosystem scale remain elusive despite its importance. Here, we leveraged long-term eddy-covariance observations from 90 sites globally and examined the spatiotemporal variations in α and their drivers, using statistical and machine learning approaches. We found significant spatial variability in α across and within biomes, primarily driven by atmospheric vapor pressure deficit (VPD) and soil moisture variations. Meanwhile, the temporal changes in α are primarily driven by the negative effect of VPD, which weakens the positive effects of elevated CO₂ and leaf area index (LAI). Our results highlight the dominant role of VPD in controlling the spatiotemporal variations of α and the unneglectable impacts of soil moisture, CO₂, and LAI on α. These new results provide insights for improving the representation of α in LUE-based models for GPP simulations.