The introduction of non-native aquatic species has fundamentally transformed aquatic assemblages, primarily due to human activities, such as aquaculture, fisheries enhancement, aquarium trade, the creation of artificial corridors, and deliberate and accidental releases. Despite growing concern for biological invasions, there is no overall global appraisal of successful non-native fishes. This study compiled a comprehensive dataset from several global sources to examine the taxonomic diversity, geographical distribution, introduction pathways, and ecological impacts of non-native freshwater and marine fishes. Our dataset includes 1535 established non-native fish species in 193 countries (82% of the global coverage), with Leuciscidae, Cichlidae, Salmonidae, and Cyprinidae being the most represented families. Although the incline in first reportings appears almost linear, annual reporting has been declining for decades, suggesting fish introduction rates are decreasing. The main introduction pathways are aquarium trade, aquaculture, fishery augmentation, and the creation of artificial corridors. The importance of introduction pathways substantially differed between freshwater species (primarily the aquarium trade and aquaculture) and marine species (corridors). While extensive records exist for hundreds of non-native fish species, information on their impact types and impact mechanisms remains available only for a third of these species, highlighting broad knowledge deficiencies. Available impact information indicates that non-native fish species may threaten native biodiversity through primarily competition and predation as dominant mechanisms. The magnitude of highest-risk invasions suggests remediation is possible through urgent proactive policy and management interventions. This comprehensive global evaluation of established fish species and their ecological effects thus addresses critical data deficiencies, strengthens risk assessment frameworks, and supports the development of targeted biosecurity policies on priority pathways, approaches essential for helping mitigate the environmental and economic impacts of non-native fish introductions.

• Klíčová slova
• aquatic ecosystem, aquatic habitat, biological invasion, freshwater ecosystem, introduction pathways, invasive species,
• MeSH
• biodiverzita * MeSH
• rybářství MeSH
• ryby * fyziologie   klasifikace   MeSH
• vodní hospodářství MeSH
• zachování přírodních zdrojů * MeSH
• zavlečené druhy * MeSH
• zvířata MeSH
• Check Tag
• zvířata MeSH
• Publikační typ
• časopisecké články MeSH

Invasive alien species are a major driver of global change, impacting biodiversity, ecosystem services, and human livelihoods. To document these impacts, we present the Global Impacts Dataset of Invasive Alien Species (GIDIAS), a dataset on the positive, negative and neutral impacts of invasive alien species on nature, nature's contributions to people, and good quality of life. This dataset arises from the Intergovernmental Science-Policy Platform on Biodiversity and Ecosystem Services' (IPBES) thematic assessment report of this topic. Data were compiled from published sources, including grey literature, reporting a direct observation of an invasive alien species' impact. All impact records contain up to 52 fields of contextual information and attempt to link impacts to the global standard "environmental impact classification for alien taxa" (EICAT) and "socio-economic impact classification for alien taxa" (SEICAT). GIDIAS includes more than 22000 records of impacts caused by 3353 invasive alien species (plants, vertebrates, invertebrates, microorganisms) from all continents and realms (terrestrial, freshwater, marine), extracted from over 6700 sources. We intend GIDIAS to be a global resource for investigating and managing the variety of impacts of invasive alien species across taxa and regions.

• MeSH
• biodiverzita * MeSH
• ekosystém MeSH
• lidé MeSH
• zachování přírodních zdrojů MeSH
• zavlečené druhy * MeSH
• zvířata MeSH
• Check Tag
• lidé MeSH
• zvířata MeSH
• Publikační typ
• časopisecké články MeSH
• dataset MeSH