Assessment of the distribution of phyto invasive species from the european list in the territory of Ukraine based on open data from GBIF, iNaturalist, and UkrBIN

The objective of this study is to investigate and evaluate the spatial distribution of invasive alien plant species (IAPS) listed in the European Union’s (EU) official register of invasive alien species of Union concern, within the national territory of Ukraine. The research utilizes occurrence records derived from three major open-access biodiversity data repositories: the Global Biodiversity Information Facility (GBIF), iNaturalist, and the Ukrainian Biodiversity Information Network (UkrBIN). In the broader context of Ukraine’s ongoing integration into the EU, aligning national environmental monitoring systems with EU biodiversity policies has become increasingly essential. Ensuring effective monitoring, early detection, and control of these high-risk biological invaders is not only a key element of environmental compliance but also a strategic necessity for safeguarding biodiversity, ecological stability, and food security. The study involves a critical assessment of data quality, completeness, and spatial reliability across the three platforms and includes a comparative evaluation of their usability for generating accurate phyto invasion distribution maps. Invasive alien species (IAS) are widely recognized as one of the primary threats to global biodiversity and ecological balance. Their uncontrolled proliferation can displace native flora, disrupt local ecosystems, alter habitat structures, lead to crop failures, and even trigger negative health outcomes for humans. As of now, Ukraine lacks a nationally adopted list of invasive alien species; therefore, the research adopts the EU List of Union Concern as the reference framework. This list, first established in 2016 and periodically updated (in 2017, 2019, and 2022), currently includes 88 species, of which 41 are vascular plants. An additional amendment proposed in 2025 is expected to include 8 new taxa. The methodological approach of the study is grounded in geospatial data analysis and geoinformation technologies (GIS), with an emphasis on spatial modeling, visualization, and cross-referencing between different data sets. Through the application of spatial analysis tools, the study identifies both confirmed areas of IAPS presence and data-deficient zones, thus providing insight into distribution gaps and monitoring needs. By integrating multiple sources and controlling for reporting biases, the methodology increases the accuracy of detection and minimizes false positives. The resulting distribution maps and geospatial models generated by this research may serve as a foundational resource for developing targeted IAS surveillance strategies, policymaking, habitat restoration plans, and adaptive management measures at both the national and cross-border levels.