Diversity and composition of beetle assemblages attracted to dung in cloud forests under active and passive restoration practices.

Ecosystem loss and degradation has become a worldwide concern. The implementation of ecological restoration plans has been proposed to facilitate the recovery of ecosystems. It is imperative that once restoration strategies have been implemented, the effects of these actions in the medium and long term be evaluated, particularly the structure and functioning of the ecosystem. Diversity (α- and ß-diversity) of beetles attracted to dung was assessed and compared in 3 habitat conditions (conserved forest, passive restoration, and active restoration) at 2 different seasons during the year (dry vs. rainy season) in cloud forest in San Luis Potosí (central Mexico). We found that the dry season was slightly richer than the rainy season, but the latter was significantly more diverse. Species diversity and composition in active restoration were more similar to passive restoration, and both differed greatly from the conserved forest. In contrast, conserved and passive restoration conditions exhibited similar patterns in ß-diversity of insects likely because they maintain more species associated with the original vegetation of the cloud forest. Beetle assemblages could be of more habitat generalists, as they actively distribute across the restoration sites. Beetles attracted to dung provide an overview of the effect of restoration in early faunal recovery, even though we monitored this entomofauna for a short period (31 months after the restoration plots were established). These beetles can be a useful indicator for exploring the main forces driving species diversity for the management and conservation status of cloud forests, a threatened ecosystem.

Selecting tree species to restore forest under climate change conditions: Complementing species distribution models with field experimentation.

The long-term success of forest restoration programs can be improved using climate-based species distribution models (SDMs) to predict which tree species will tolerate climate change. However, as SDMs cannot estimate if species will recruit at these habitats, determining whether their predictions apply to early life-cycle stages of trees is critical to support such a usage. For this, we propose sowing seeds of the focal tree species under the current climate and simulated climate change conditions in target restoration sites. Thus, using of SDMs to design climate-adaptive forest restoration programs would be supported if the differences in habitat occupancy probabilities of species they predict between the current and future climate concurs with the observed differences in recruitment rates of species when sowed under the current climate and simulated climate change conditions. To test this hypothesis, we calibrated SDMs for Vachellia pennatula and Prosopis laevigata, two pioneer tree species widely recommended to restore human-degraded drylands in Mexico, and transferred them to climate change scenarios. After that, we applied the experimental approach proposed above to validate the predictions of SDMs. These models predicted that V. pennatula will decrease its habitat occupancy probabilities across Mexico, while P. laevigata was predicted to keep out their current habitat occupancy probabilities, or even increase them, in climate change scenarios. The results of the field experiment supported these predictions, as recruitment rates of V. pennatula were lower under simulated climate change than under the current climate, while no differences were found for the recruitment rates of P. laevigata between these environmental conditions. These findings demonstrate that SDMs provide meaningful insights for designing climate-adaptive forest restoration programs but, before applying this methodology, predictions of these models must be validated with field experiments to determine whether the focal tree species will recruit under climate change conditions. Moreover, as the pioneer trees used to test our proposal seem to be differentially sensitive to climate change, this approach also allows establishing what species must be prescribed to restore forests with a view to the future and what species must be avoided in these practices.