Divergent response of seasonally dry tropical vegetation to climatic variations in dry and wet seasons

Abstract Interannual variations of photosynthesis in tropical seasonally dry vegetation are one of the dominant drivers to interannual variations of atmospheric CO 2 growth rate. Yet, the seasonal differences in the response of photosynthesis to climate variations in these ecosystems remain poorly understood. Here using Normalized Difference Vegetation Index ( NDVI ), we explored the response of photosynthesis of seasonally dry tropical vegetation to climatic variations in the dry and the wet seasons during the past three decades. We found significant ( p < 0.01) differences between dry and wet seasons in the interannual response of photosynthesis to temperature ( γ int ) and to precipitation ( δ int ). γ int is ~1% °C −1 more negative and δ int is ~8% 100 mm −1 more positive in the dry season than in the wet season. Further analyses show that the seasonal difference in γ int can be explained by background moisture and temperature conditions. Positive γ int occurred in wet season where mean temperature is lower than 27°C and precipitation is at least 60 mm larger than potential evapotranspiration. Two widely used Gross Primary Productivity ( GPP ) estimates (empirical modeling by machine‐learning algorithm applied to flux tower measurements, and nine process‐based carbon cycle models) were examined for the GPP –climate relationship over wet and dry seasons. The GPP derived from empirical modeling can partly reproduce the divergence of γ int , while most process models cannot. The overestimate by process models on negative impacts by warmer temperature during the wet season highlights the shortcomings of current carbon cycle models in representing interactive impacts of temperature and moisture on photosynthesis. Improving representations on soil water uptake, leaf temperature, nitrogen cycling, and soil moisture may help improve modeling skills in reproducing seasonal differences of photosynthesis–climate relationship and thus the projection for impacts of climate change on tropical carbon cycle.