Non‐native tree (NNT) species have been transported worldwide to create or enhance services that are fundamental for human well‐being, such as timber provision, erosion control or ornamental value; yet NNTs can also produce undesired effects, such as fire proneness or pollen allergenicity. Despite the variety of effects that NNTs have on multiple ecosystem services, a global quantitative assessment of their costs and benefits is still lacking. Such information is critical for decision‐making, management and sustainable exploitation of NNTs. We present here a global assessment of NNT effects on the three main categories of ecosystem services, including regulating (RES), provisioning (PES) and cultural services (CES), and on an ecosystem disservice (EDS), i.e. pollen allergenicity. By searching the scientific literature, country forestry reports, and social media, we compiled a global data set of 1683 case studies from over 125 NNT species, covering 44 countries, all continents but Antarctica, and seven biomes. Using different meta‐analysis techniques, we found that, while NNTs increase most RES (e.g. climate regulation, soil erosion control, fertility and formation), they decrease PES (e.g. NNTs contribute less than native trees to global timber provision). Also, they have different effects on CES (e.g. increase aesthetic values but decrease scientific interest), and no effect on the EDS considered. NNT effects on each ecosystem (dis)service showed a strong context dependency, varying across NNT types, biomes and socio‐economic conditions. For instance, some RES are increased more by NNTs able to fix atmospheric nitrogen, and when the ecosystem is located in low‐latitude biomes; some CES are increased more by NNTs in less‐wealthy countries or in countries with higher gross domestic products. The effects of NNTs on several ecosystem (dis)services exhibited some synergies (e.g. among soil fertility, soil formation and climate regulation or between aesthetic values and pollen allergenicity), but also trade‐offs (e.g. between fire regulation and soil erosion control). Our analyses provide a quantitative understanding of the complex synergies, trade‐offs and context dependencies involved for the effects of NNTs that is essential for attaining a sustained provision of ecosystem services.

Patterns of wildfire occurrence at the landscape level were characterised during the period 1990–94 in Portugal. Based on land-cover information within 5591 burned patches (larger than 5 ha) and in the surrounding landscape, selection ratio functions were used to measure fire preference or avoidance for different land-cover types in 12 regions of the country. Shrublands were the most fire-prone land cover, whereas annual crops, permanent crops and agro-forestry systems were the most avoided by fire. In terms of forest types, conifer plantations were more susceptible to fire than eucalyptus, and broadleaved forests were the least fire-prone. There were regional variations in land-cover susceptibility to fire, which may be explained by differences in climate, management, ignition patterns, firefighting strategies, and regional availability. A cluster analysis of regional variations in selection ratios for all land covers allowed the identification of three main geographical areas with similar fire selection patterns. These results can be used for planning landscape-scale fuel management in order to create landscapes with a lower fire hazard.

In the context of global change, the integration of non-native tree (NNT) species into European forestry is increasingly being discussed. The ecological consequences of increasing use or spread of NNTs in European forests are highly uncertain, as the scientific evidence is either constraint to results from case studies with limited spatial extent, or concerns global assessments that lack focus on European NNTs. For either case, generalisations on European NNTs are challenging to draw. Here we compile data on the impacts of seven important NNTs (Acacia dealbata, Ailanthus altissima, Eucalyptus globulus, Prunus serotina, Pseudotsuga menziesii, Quercus rubra, Robinia pseudoacacia) on physical and chemical soil properties and diversity attributes in Europe, and summarise commonalities and differences. From a total of 103 publications considered, studies on diversity attributes were overall more frequent than studies on soil properties. The effects on soil properties varied greatly among tree species and depended on the respective soil property. Overall, increasing (45%) and decreasing (45%) impacts on soil occurred with similar frequency. In contrast, decreasing impacts on biodiversity were much more frequent (66%) than increasing ones (24%). Species phylogenetically distant from European tree species, such as Acacia dealbata, Eucalyptus globulus and Ailanthus altissima, showed the strongest decreasing impacts on biodiversity. Our results suggest that forest managers should be cautious in using NNTs, as a majority of NNT stands host fewer species when compared with native tree species or ecosystems, likely reflected in changes in biotic interactions and ecosystem functions. The high variability of impacts suggests that individual NNTs should be assessed separately, but NNTs that lack European relatives should be used with particular caution.

We have assessed the fire proneness of the main forest types in Portugal classified according to the main species, using three different approaches: the use of resource selection ratios applied to burned patches, the proportion of randomly located plots that were burned and the proportion of burned National Forest Inventory plots. The results allowed ranking fire proneness according to the following decreasing order: maritime pine forests, eucalyptus forests, unspecified broadleaf forests, unspecified conifer forests, cork oak forests, chestnut forests, holm oak forests and stone pine forests. In order to understand the obtained results we have assessed the structure of the different forest types using the percent cover of seven vegetation layers (C1–C7), a Tree Dominance Index, a Height Index and a Cover Index (IC). Structural variables and stand composition were used to predict fire probability according to binary logistic modelling. Only four structural variables and stand composition provided significant results, the latter being the most important variable for explaining fire probability. These models were used to predict fire probability for different stand types as a function of IC.