Climate-driven changes to the long-range fluctuations in vegetation production: Consequences for the global carbon cycle

Climate plays a vital role in the carbon (C) uptake through vegetation productivity (Gross Primary Production; GPP) that is crucial to the persistence of the land as a carbon sink, thereby resulting in negative land-climate feedbacks. Large uncertainties persist in understanding the role of climate variability on this C flux, which influence future projections using Earth System Models (ESMs). One important source of uncertainty arises from the temporal variability in the carbon influx, and this includes effects of autocorrelation—i.e., similarity in observations with time-lag due to temporal structuring (“memory”) in the underlying dynamics. Evidence of the presence of memory in C uptake through GPP arises from field-based measurements through eddy covariance flux towers, but these lack widespread spatial distribution across environmental conditions and ecosystems. Therefore, estimating memory in the C cycle and its drivers on the global scale is important to our understanding of the global C cycle. For this, we used remotely sensed long-term GPP data from MODIS over the past two decades (2001-2021), to estimate long-term memory in C cycling through C-uptake by vegetation. Additionally, we also examined how the climate variables – temperature and precipitation- that are known to drive C influx, influenced the memory in C-uptake. We find that memory occurs in satellite-based estimates of GPP, corroborating field-based measurements. Interestingly, the memory in the C cycle was not limited to either short- or long-term but consisted of both these characteristics across different timescales. Climate variability through temperature and precipitation influenced memory and their effects are heterogeneous across ecosystems. With climate variability predicted to increase in the near future, our results suggest that these effects are likely to be consequential for the memory in C-uptake and, ultimately on the dynamics of the global C cycle. Therefore, estimating the memory in C cycle and its variation, is crucial for understanding as well as predicting the C-influx, under present and future climate change scenarios.