Aim: The first comprehensive checklist of European phytosociological alliances, orders and classes (EuroVegChecklist) was published by Mucina et al. (2016, Applied Vegetation Science, 19 (Suppl. 1), 3–264). However, this checklist did not contain detailed information on the distribution of individual vegetation types. Here we provide the first maps of all alliances in Europe.Location: Europe, Greenland, Canary Islands, Madeira, Azores, Cyprus and the Caucasus countries.Methods: We collected data on the occurrence of phytosociological alliances in European countries and regions from literature and vegetation‐plot databases. We interpreted and complemented these data using the expert knowledge of an international team of vegetation scientists and matched all the previously reported alliance names and concepts with those of the EuroVegChecklist. We then mapped the occurrence of the EuroVegChecklist alliances in 82 territorial units corresponding to countries, large islands, archipelagos and peninsulas. We subdivided the mainland parts of large or biogeographically heterogeneous countries based on the European biogeographical regions. Specialized alliances of coastal habitats were mapped only for the coastal section of each territorial unit.Results: Distribution maps were prepared for 1,105 alliances of vascular‐plant dominated vegetation reported in the EuroVegChecklist. For each territorial unit, three levels of occurrence probability were plotted on the maps: (a) verified occurrence; (b) uncertain occurrence; and (c) absence. The maps of individual alliances were complemented by summary maps of the number of alliances and the alliance–area relationship. Distribution data are also provided in a spreadsheet.Conclusions: The new map series represents the first attempt to characterize the distribution of all vegetation types at the alliance level across Europe. There are still many knowledge gaps, partly due to a lack of data for some regions and partly due to uncertainties in the definition of some alliances. The maps presented here provide a basis for future research aimed at filling these gaps.

We present a bioclimatological diagnosis of mainland Portugal, namely the thermotype and ombrotype maps following Rivas‐Martínez's worldwide bioclimatic classification system. In order to obtain this diagnosis, we produced maps of bioclimatological indices using, as base data, geostatistical interpolations of air temperature and precipitation. We performed uncertainty propagation obtaining uncertainty measures for the produced maps: mean absolute errors and root mean squared errors. For the non‐linear indices, besides the usual approximation using Taylor expansion, we devised error formulae, for which we showed that the propagated uncertainties are upper bounds on the true uncertainty measures. We compared the obtained uncertainty measures to those reported on a previously published work, which used a different methodological framework to obtain the same diagnosis. Although the approach we used here implies a great number of interpolations and subsequent calculation steps, it permitted the use of a large amount of data relative to precipitation. An F‐test showed that the estimated mean squared errors for the maps of ombrothermic indices were significantly lower than those produced by the former methodological framework.

The first comprehensive phytosociological classification of all vegetation types in Europe (EuroVegChecklist; Applied Vegetation Science, 2016, 19, 3–264) contained brief descriptions of each type. However, these descriptions were not standardized and mentioned only the most distinct features of each vegetation type. The practical application of the vegetation classification system could be enhanced if users had the option to select sets of vegetation types based on various combinations of structural, ecological, and biogeographical attributes. Based on a literature review and expert knowledge, we created a new database that assigns standardized categorical attributes of 12 variables to each of the 1106 alliances dominated by vascular plants defined in EuroVegChecklist. These variables include dominant life form, phenological optimum, substrate moisture, substrate reaction, salinity, nutrient status, soil organic matter, vegetation region, elevational vegetation belt, azonality, successional status and naturalness. The new database has the potential to enhance the usefulness of phytosociological classification for researchers and practitioners and to help understand this classification to non‐specialists.

Persistence of native forests is a global concern. We aimed at unveiling the main factors affecting tree recruitment in Portuguese native forests, modelling sapling data collected during the 5th Portuguese Forest Inventory, for five main Quercus taxa. Zero-inflated count data models allowed us to examine simultaneously (i) the absence of tree recruitment and (ii) the density of tree recruitment. Using Akaike weights, we obtained importance values for 15 relevant explanatory variables. Results showed that seed availability and climatic variables were determinant to understand regional absence of regeneration for all taxa. Seed availability was also an important driver of sapling density, except for Quercus suber. Other variables impacted on regeneration density: grazing hindered Q. suber regeneration; regeneration of Q. rotundifolia and Q. suber was lower in flat areas; recurrent fire hampered the regeneration of Q. robur and Q. pyrenaica; Q. broteroi and Q. pyrenaica showed depressed regeneration in regions where forest plantations abound, while Q. robur and Q. suber seemed selectively protected. We conclude that caution is warranted when analysing pooled data for Quercus spp. regeneration, as different variables affected Quercus taxa differently. Finally, we suggest dedicated management actions to enhance the establishment of new native forests.