AIM: Hotspots of human activity are focal points for ecosystem disturbance and non‐native introduction, from which invading populations disperse and spread. As such, connectivity to locations used by humans may influence the likelihood of invasion. Moreover, connectivity in freshwater ecosystems may follow the hydrological network. Here we tested whether multiple forms of connectivity to human recreational activities promotes biological invasion of freshwater ecosystems. LOCATION: England, UK. TIME PERIOD: 1990–2018. MAJOR TAXA STUDIED: One hundred and twenty‐six non‐native freshwater birds, crustaceans, fish, molluscs and plants. METHODS: Machine learning was used to predict spatial gradients in human recreation and two high risk activities for invasion (fishing and water sports). Connectivity indices were developed for each activity, in which human influence decayed from activity hotspots according to Euclidean distance (spatial connectivity) or hydrological network distance (downstream, upstream and along‐channel connectivity). Generalized linear mixed models identified the connectivity type most associated to invasive species richness of each group, while controlling for other anthropogenic and environmental drivers. RESULTS: Connectivity to humans generally had stronger positive effects on invasion than all other drivers except recording effort. Recreation had stronger influence than urban land cover, and for most groups high risk activities had stronger effects than general recreation. Downstream human connectivity was most important for invasion by most of the groups, potentially reflecting predominantly hydrological dispersal. An exception was birds, for which spatial connectivity was most important, possibly because of overland dispersal capacity. MAIN CONCLUSIONS: These findings support the hypothesis that freshwater invasion is partly determined by an interaction between human activity and species dispersal in the hydrological network. By comparing alternative connectivity types for different human activities, our approach could enable robust inference of specific pathways and spread mechanisms associated with particular taxa. This would provide evidence to support better prioritization of surveillance and management for invasive non‐native species.

中文翻译：

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与人类活动热点的网络连接促进了淡水生态系统的入侵

目的：人类活动的热点是生态系统干扰和非本地引入的焦点，入侵种群由此分散和扩散。因此，与人类使用的位置的连接性可能会影响入侵的可能性。此外，淡水生态系统的连通性可能遵循水文网络。在这里，我们测试了与人类娱乐活动的多种形式的连接是否会促进淡水生态系统的生物入侵。地点：英国，英国。时间段：1990-2018。研究的主要类群：126 种非本地淡水鸟类、甲壳类动物、鱼类、软体动物和植物。方法：机器学习用于预测人类娱乐和两项高风险入侵活动（钓鱼和水上运动）的空间梯度。为每项活动制定了连通性指数，其中人类影响根据欧几里德距离（空间连通性）或水文网络距离（下游、上游和沿河道连通性）从活动热点衰减。广义线性混合模型确定了与每个组的入侵物种丰富度最相关的连接类型，同时控制了其他人为和环境驱动因素。结果：与人类的连接通常比所有其他驱动因素对入侵具有更强的积极影响，除了记录努力。娱乐比城市土地覆盖的影响更大，对大多数群体来说，高风险活动的影响比一般娱乐更强。下游人类连通性对于大多数群体的入侵最为重要，这可能主要反映了水文扩散。一个例外是鸟类，其中空间连通性最重要，可能是因为陆上传播能力。主要结论：这些发现支持淡水入侵部分由人类活动与水文网络中物种扩散之间的相互作用决定的假设。通过比较不同人类活动的替代连接类型，我们的方法可以对与特定分类群相关的特定途径和传播机制进行稳健推断。这将为支持更好地优先考虑对入侵的非本地物种进行监测和管理提供证据。这些发现支持了以下假设：淡水入侵部分是由人类活动与水文网络中物种扩散之间的相互作用决定的。通过比较不同人类活动的替代连接类型，我们的方法可以对与特定分类群相关的特定途径和传播机制进行稳健推断。这将为支持更好地优先考虑对入侵的非本地物种进行监测和管理提供证据。这些发现支持了以下假设：淡水入侵部分是由人类活动与水文网络中物种扩散之间的相互作用决定的。通过比较不同人类活动的替代连接类型，我们的方法可以对与特定分类群相关的特定途径和传播机制进行稳健推断。这将为支持更好地优先考虑对入侵的非本地物种进行监测和管理提供证据。