Analysing factors underlying the reporting of established non-native species

. 2025 Apr 10 ; 15 (1) : 12337. [epub] 20250410

Jazyk angličtina Země Anglie, Velká Británie Médium electronic

Typ dokumentu časopisecké články

Perzistentní odkaz   https://www.medvik.cz/link/pmid40210947
Odkazy

PubMed 40210947
PubMed Central PMC11985998
DOI 10.1038/s41598-025-96133-0
PII: 10.1038/s41598-025-96133-0
Knihovny.cz E-zdroje

A nexus of natural and human variables mediate the success of non-native species that threaten global biodiversity and ecological stability. However, the relative importance and interplays among relevant factors has not been holistically approached. To identify spatial differences and potential connections in relevant natural and human drivers, we analyzed the number of non-native species established in European countries using a newly collated database of established non-native species. We employ a series of broadscale national predictors classified into 'research', 'economy', 'environment & culture', and 'land-use' to predict successful establishment. Our null models, which assume the distribution of non-native species mirrors that of each predictor, accurately predicted non-native species numbers across European countries. However, a few countries were identified as outliers, having significantly over- or underrepresented non-native species numbers based on adjusted quasi-Poisson distribution quantiles. A network analysis of non-native species compositions identified these regions to be central hubs (e.g. Germany, France, and Switzerland), but also highlighted distinct spatial similarities across European countries. Combinations of the predictors 'economy', 'research', and 'environment & culture' explained the largest shares of differences in the number of established non-native species among European countries as well as their reporting rates over time. Individual drivers alone were insufficient to wholly explain national differences, whereas interacting driver categories ultimately accounted for the largest shares of variance. This analysis demonstrates the breadth of predictors that mediate successful establishment, and particularly highlights the relevance of overlooked historical-cultural facets affecting biological invasions.

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