Modeling the long-term natural regeneration potential of woodlands in semi-arid regions to guide restoration efforts

Understanding forest regeneration at sites previously used for agriculture underlies the establishment of science-based woodlands management policies. This is especially relevant in semi-arid areas, where the tree cover is critical in ameliorating the effects of aridity and in preventing desertification and land degradation. Natural regeneration in semi-arid areas occurs very slowly, which in part explains why it has hardly been studied. In the present work, we sought to devise a method to predict the natural regeneration potential of woodlands in semi-arid areas, to be used in guiding restoration efforts. Specifically, we evaluated holm oak coverage at a long-term ecological research site and then designed and validated a model to predict the natural regeneration of holm oak based on a few environmental variables. Unlike available studies, we obtained long-term information on tree regeneration (making use of >60 years of aerial photography) and climate (using long-term climate and microclimate data). We found that microclimate, measured using the potential solar radiation as a proxy, was a key driver of natural regeneration: after 60 years of agricultural abandonment, less sun-exposed areas attained a tree cover >90 %, whereas in more sun-exposed areas it remained below 20 %. We then used the model to map the natural regeneration potential, first in the study area and then in an area where holm oak plantations had been unsuccessfully introduced. In the latter case, the model successfully predicted the failure of this reforestation effort. Our results support the use of this model by decision makers to optimize management practices, as it will encourage the concentration of efforts in areas more prone to successful reforestation and allow the identification of areas more likely to benefit from natural regeneration processes.