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分析已确定的非本地物种报告背后的因素。

Analysing factors underlying the reporting of established non-native species.

作者信息

Haubrock Phillip J, Soto Ismael, Cuthbert Ross N, Kurtul Irmak, Briski Elizabeta

机构信息

Department of River Ecology and Conservation, Senckenberg Research Institute and Natural History Museum Frankfurt, Gelnhausen, Germany.

Faculty of Fisheries and Protection of Waters, University of South Bohemia in České Budějovice, South Bohemian Research Centre of Aquaculture and Biodiversity of Hydrocenoses, Zátiší 728/II, Vodňany, 389 25, Czech Republic.

出版信息

Sci Rep. 2025 Apr 10;15(1):12337. doi: 10.1038/s41598-025-96133-0.

Abstract

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.

摘要

自然变量和人类变量相互关联,共同影响着那些威胁全球生物多样性和生态稳定性的外来物种的入侵态势。然而,相关因素之间的相对重要性及其相互作用尚未得到全面探讨。为了识别相关自然和人类驱动因素中的空间差异及潜在联系,我们利用一个新整理的外来物种数据库,分析了欧洲各国已建立的外来物种数量。我们采用了一系列广泛的国家预测指标,分为“研究”、“经济”、“环境与文化”以及“土地利用”,以预测外来物种的成功定殖。我们的零模型假设外来物种的分布反映了每个预测指标的分布,该模型准确地预测了欧洲各国的外来物种数量。然而,一些国家被确定为异常值,根据调整后的拟泊松分布分位数,这些国家的外来物种数量显著高于或低于预期。对外来物种组成的网络分析表明,这些地区是中心枢纽(如德国、法国和瑞士),但也凸显了欧洲各国之间独特的空间相似性。“经济”、“研究”和“环境与文化”这几个预测指标的组合,解释了欧洲各国已建立的外来物种数量差异及其随时间变化的报告率的最大份额。单一的驱动因素不足以完全解释各国之间的差异,而相互作用的驱动因素类别最终解释了最大的方差份额。该分析展示了介导成功定殖的预测指标的广度,尤其突出了被忽视的历史文化因素对生物入侵的影响。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/37a3/11985998/91d6060c13b0/41598_2025_96133_Fig1_HTML.jpg

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