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In March 2020, the first known cases of COVID‐19 occurred in Europe. Subsequently, the pandemic developed a seasonal pattern. The incidence of COVID‐19 comprises spatial heterogeneity and seasonal variations, with lower and/or shorter peaks resulting in lower total incidence and higher and/or longer peaks resulting higher total incidence. The reason behind this phenomena is still unclear. Unraveling factors that explain why certain places have higher versus lower total COVID‐19 incidence can help health decision makers understand and plan for future waves of the pandemic. We test whether differences in the total incidence of COVID‐19 within five European countries (Norway, Sweden, Germany, Italy, and Spain), correlate with two environmental factors: the Köppen‐Geiger climate zones and the Continentality Index, while statistically controlling for crowding. Our results show that during the first 16 months of the pandemic (March 2020 to July 2021), climate zones with larger annual differences in temperature and annually distributed precipitation show a higher total incidence than climate zones with smaller differences in temperature and dry seasons. This coincides with lower continentality values. Total incidence increases with continentality, up to a Continentality Index value of 19, where a peak is reached in the semicontinental zone. Low continentality (high oceanic influence) appears to be a strong suppressing factor for COVID‐19 spread. The incidence in our study area is lowest at open low continentality west coast areas. Plain Language Summary: In March 2020, the first known cases of COVID‐19 occurred in Europe. Over the next 16 months (March 2020 to July 2021) a pattern emerged where some areas had higher versus lower COVID‐19 spread. We studied whether this pattern could be explained by climatological factors in five European countries (Norway, Sweden, Germany, Italy, and Spain). Our results show that areas with larger annual temperature ranges and year‐round rain had higher COVID‐19 spread than areas with smaller annual temperature ranges and dry seasons. We also examined continentality, which measures the influence of the ocean on climate. In Europe, where predominant winds come from the west, we find the highest oceanic influence at open west coasts; in our study area these are represented by north‐west Spain, northernmost Germany, and south‐west Norway. In these areas, COVID‐19 spread was lowest. With decreasing oceanic influence, COVID‐19 spread was higher. For the five countries we studied, we found highest COVID‐19 spread in south‐east Norway, the entire south of Sweden, the south‐eastern part of Germany, northern Italy, and central Spain. Healthcare decision makers in areas that have wide ranges of temperature and rain throughout the year or that have little oceanic influence should expect a higher COVID‐19 spread. Key Points: We study the reason for within country differences of the COVID‐19 pandemic for Norway, Sweden, Germany, Italy, and SpainCOVID‐19 incidence is lower in climate zones with smaller annual temperature ranges and a clear division between wet and dry seasonsIncidence patterns can be explained by continentality; oceanic impact limits COVID‐19 at open west coasts in the European west wind zone [ABSTRACT FROM AUTHOR]

Forest conservation strategies and plans can be unsuccessful if the new habitat conditions determined by climate change are not considered. Our work aims at investigating the likelihood of future suitability, distribution and diversity for some common European forest species under the projected changes in climate, focusing on Southern Europe. We combine an Ensemble Platform for Species Distribution Models ( SDMs) to five Global Circulation Models ( GCMs) driven by two Representative Concentration Pathways ( RCPs), to produce maps of future climate-driven habitat suitability for ten categories of forest species and two time horizons. For each forest category and time horizon, ten maps of future distribution (5 GCMs by 2 RCPs) are thus combined in a single suitability map supplied with information about the 'likelihood' adopting the IPCC terminology based on consensus among projections. Then, the statistical significance of spatially aggregated changes in forest composition at local and regional level is analyzed. Finally, we discuss the importance, among SDMs, that environmental predictors seem to have in influencing forest distribution. Future impacts of climate change appear to be diversified across forest categories. A strong change in forest regional distribution and local diversity is projected to take place, as some forest categories will find more suitable conditions in previously unsuitable locations, while for other categories the same new conditions will become less suited. A decrease in species diversity is projected in most of the area, with Alpine region showing the potentiality to become a refuge for species migration. [ABSTRACT FROM AUTHOR]