Time-Scale Dependent Relations Between Earth Observation Based Proxies of Vegetation Productivity

Abstract

Abstract Much uncertainty remains in measuring the inter-annual and longer-term dynamics of vegetation gross and net primary productivity (GPP, NPP) and the connected land carbon sink. Potential for better GPP estimation lies in newer satellite products representing different processes or vegetation states, but how they capture interannual GPP dynamics remains to be explored. Here, we differentiate shorter- and longer-term vegetation dynamics and their drivers for several Earth-observation-based vegetation proxies and a GPP estimate using time series decomposition. We find that relations between proxies can significantly differ between time scales, along land cover and climate gradients. For GPP estimated at FLUXNET sites, seasonal and multiannual slopes differ by at least 25% for half of the cases investigated, indicating considerable mismatch if multiannual relations were derived from seasonal slopes. Considering time-scale-specific sensitivities between proxies of vegetation productivity may improve estimates of interannual variability in vegetation productivity. , Plain Language Summary How ecosystems will develop in the future is still difficult to predict, in part because the factors that influence ecosystems over several years or decades may differ from those influencing them in the course of a day or a year. Several satellites monitor vegetation growth on Earth and report, for example, leaf greenness or fluorescence. Fluorescence is often superior in tracking seasonal vegetation dynamics, but when it comes to understanding the long-term imprint of climate, it remains to be clarified how different data products relate to each other. In this study, we compare how much changes in interannual and longer vegetation activity are captured by different satellite products. We find that the relationship between satellite proxies for vegetation differs between monthly, yearly and long-term scales. These findings may help to better understand and predict vegetation growth and carbon uptake from the atmosphere in the future. , Key Points Contrary to seasonal time scales, it is poorly understood how different vegetation productivity proxies relate at interannual time scales Interannual relations between vegetation proxies need to be considered: Seasonal relations do not generally hold at multiannual scale Time-scale-specific slopes between vegetation proxies vary along gradients of tree cover, vegetation type, climate, and across FLUXNET sites