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Robinia pseudoacacia L. (commonly known as black locust) is an economically and environmentally important plant, native to the eastern USA, and introduced into several European countries, including Hungary. An early successional leguminous tree, the black locust is characterized by tolerance to degraded sites, rapid growth rate, dense and rot-resistant wood, and heavy flowering. Due to its economic potential and environmental impact, the historic Hungarian breeding strategy targeted not only increased wood production but also in wood and honey-production quality. However, because many important features of the species are under polygenic control, genome-wide genetic data provided by high-throughput sequencing technology could make possible the identification of gene variants with identifiable functional effects on complex traits. Furthermore, the evaluation of the breeding efforts carried out so far would be also achievable, by comparing bred/selected genotypes with those from the original habitat. This paper provides a genomic dataset with highly variable SNP markers from native American and Hungarian Robinia pseudoacacia L. individuals. These SNP loci can be used to assess genetic differentiation, and to detect signatures of polygenic determination of economically important traits, providing a basis for further research into this species.

For non-native tree species with an origin outside of Europe a detailed compilation of enemy species including the severity of their attack is lacking up to now. We collected information on native and non-native species attacking non-native trees, i.e. type, extent and time of first observation of damage for 23 important non-native trees in 27 European countries. Our database includes about 2300 synthesised attack records (synthesised per biotic threat, tree and country) from over 800 species. Insects (49%) and fungi (45%) are the main observed biotic threats, but also arachnids, bacteria including phytoplasmas, mammals, nematodes, plants and viruses have been recorded. This information will be valuable to identify patterns and drivers of attacks, and trees with a lower current health risk to be considered for planting. In addition, our database will provide a baseline to which future impacts on non-native tree species could be compared with and thus will allow to analyse temporal trends of impacts.