The growth of past, present, and future forests was, is and will be affected by climate variability. This multifaceted relationship has been assessed in several regional studies, but spatially resolved, large-scale analyses are largely missing so far. Here we estimate recent changes in growth of 5800 beech trees (Fagus sylvatica L.) from 324 sites, representing the full geographic and climatic range of species. Future growth trends were predicted considering state-of-the-art climate scenarios. The validated models indicate growth declines across large region of the distribution in recent decades, and project severe future growth declines ranging from −20% to more than −50% by 2090, depending on the region and climate change scenario (i.e. CMIP6 SSP1-2.6 and SSP5-8.5). Forecasted forest productivity losses are most striking towards the southern distribution limit of Fagus sylvatica, in regions where persisting atmospheric high-pressure systems are expected to increase drought severity. The projected 21^st century growth changes across Europe indicate serious ecological and economic consequences that require immediate forest adaptation.

An analysis was made of the Precipitation Concentration Index using the new MOPREDAS database of monthly precipitation in Spain (Monthly Precipitation Data base of Spain). The database was compiled after exhaustive quality control of the complete digitalized Spanish Meterological Agency (AEMet) archives and contains a total set of 2670 complete and homogeneous monthly precipitation series from 1946 to 2005. Thus, MOPREDAS currently holds the densest information available for the 1946–2005 period for Spain and ensures a high resolution of results. The Precipitation Concentration Index (PCI) is a powerful indicator of the temporal distribution of precipitation, traditionally applied at annual scales; as the value increases, the more concentrated the precipitation. Furthermore PCI is a part of the well-known Fournier index, with a long tradition on natural system analyses, as for example soil erosion. In this paper, the mean values of annual, seasonal and wet and dry periods of PCI in the conterminous Spain and for two normal periods (1946–1975 and 1976–2005) were studied. Precipitation in Spain follows a general NW-SE spatial pattern during the wet (months) period due to the Atlantic storm track, while during the dry (months) period, it follows a predominantly N-S spatial pattern. As a result, the annual values of PCI combine the two patterns and show a SW-NE PCI gradient. The analyses of the two sub-periods show significant changes in the precipitation occurred in conterminous Spain from 1946 to 2005, and precipitation concentration increased across most of the IP. At an annual scale, PCI increases mostly due to an increase in precipitation concentration during the wet season. At a seasonal scale significant changes were detected between 1945–1975 and 1976–2005, particularly in autumn (increase of PCI values), while changes in winter, spring and summer were mostly localized and not generalized (both increase and decrease). Changes in PCI seem to be complex and appear to be related to global atmospheric features and synoptic and local factors affecting precipitation trends. We discuss the possible explanation linked to the atmospheric pattern and monthly trends and their implications.

Significance: Forest trees can live for hundreds to thousands of years, and they play a critical role in mitigating global warming by fixing approximately 15% of anthropogenic CO ₂ emissions annually by wood formation. However, the environmental factors triggering wood formation onset in springtime and the cellular mechanisms underlying this onset remain poorly understood, since wood forms beneath the bark and is difficult to monitor. We report that the onset of wood formation in Northern Hemisphere conifers is driven primarily by photoperiod and mean annual temperature. Understanding the unique relationships between exogenous factors and wood formation could aid in predicting how forest ecosystems respond and adapt to climate warming, while improving the assessment of long-term and high-resolution observations of global biogeochemical cycles.