Land surface greening suggests vigorous woody regrowth throughout European semi-natural vegetation.

The satellite record has revealed substantial land surface "greening" in the northern hemisphere over recent decades. Process-based Earth system models (ESMs) attribute enhanced vegetation productivity (greening) to CO2 fertilisation. However, the models poorly reproduce observed spatial patterns of greening, suggesting that they ignore crucial processes. Here, we explore whether fine-scale land cover dynamics, as modified by ecological and land-use processes, can explain the discrepancy between models and satellite-based estimates of greening. We used 500 m satellite-derived Leaf Area Index (LAI) to quantify greening. We focus on semi-natural vegetation in Europe, and distinguish between conservation areas and unprotected land. Within these ecological and land-use categories, we then explored the relationships between vegetation change and major climatic gradients. Despite the relatively short time-series (15 years), we found a strong overall increase in LAI (i.e., greening) across all European semi-natural vegetation types. The spatial pattern of vegetation change identifies land-use change, particularly land abandonment, as a major initiator of vegetation change both in- and outside of protected areas. The strongest LAI increases were observed in mild climates, consistent with more vigorous woody regrowth after cessation of intensive management in these environments. Surprisingly, rates of vegetation change within protected areas did not differ significantly from unprotected semi-natural vegetation. Overall, the detected LAI increases are consistent with previous, coarser-scale, studies. The evidence indicates that woody regrowth following land abandonment is an important driver of land surface greening throughout Europe. The results offer an explanation for the large discrepancies between ESM-derived and satellite-derived greening estimates and thus generate new avenues for improving the ESMs on which we rely for crucial climate forecasts.