Abstract
The sustainability of forest species is directly related to the success of stand regeneration. Assuring success is particularly critical in stands where perpetuity relies on natural regeneration, as is often the case with cork oak forests. However, 59% of the stand in Portugal have no natural regeneration, and climate change could further worsen the sustainability of the system. The study summarizes the factors that affect the natural regeneration of cork oak (Quercus suber L.) based on current knowledge and presents a case study on a forest in Northeast Portugal, where the natural regeneration of Quercus suber under the effect of climate change have been monitored and analyzed. The present work focuses on the effect of stand density, i.e., tree cover, on the production of acorns, the establishment and survival of seedlings, and the impact of the summer season on seedling mortality. The monitoring was carried out in February, June, September 2022, and January 2023 in two stands with distinct stand canopy cover, when the region was under extreme drought. Data analysis was performed using the analysis of variance for repeated measures and the Mann-Whitney-Wilcoxon test. The study showed that cork oak regeneration is influenced by stand density, which promoted the establishment success and survival of natural regeneration in a period of reduced precipitation, despite possible competition for water resources. The mean number of seedlings differed significantly between the two stands. However, there were no significant differences in the mean number of seedlings throughout the field measurements. Additionally, the percentage of dead seedlings was low even after the summer season (9.5% of the total seedlings) in the denser stand. These results indicate that high canopy cover can have a protective effect for extreme climatic events and should be considered in forestry management to promote regeneration of the cork oak forests.

Abstract
Wind power is a major source of green energy production. However, the energy generation of wind power is highly affected by uncertainty. Here, we consider the problem of designing the cable network that interconnects the turbines to the substation in wind farms, aiming to minimize both the infrastructure cost and the cost of the energy losses during the wind farm's lifetime. Nonetheless, the energy losses depend on wind direction and speed, which are rarely known with certainty in real situations. Hence, the design of the network should consider these losses as uncertain parameters. We assume that the exact probability distribution of these parameters is unknown but belongs to an ambiguity set and propose a distributionally robust two-stage mixed integer model. The model is solved using a decomposition algorithm. Three enhancements are proposed given the computational difficulty in solving real problem instances. Computational results are reported based on real data.