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: 126 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). Generalised 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 prioritisation of surveillance and management for invasive non-native species.

Raster files showing estimated relative spatial gradients in the intensity of all recreation, fishing and watersports in England are contained within files:

• fishing.tif
• recreation.tif
• watersports.tif 

These gradients were produced by modelling destinations of visits to freshwater ecosystems (lakes, rivers and canals) in the Monitor of Engagement with the Natural Environment survey data (Natural England 2017). Visit locations within this dataset were modelled using machine learning to generate gradients in relative visit intensity. The files are in geoTIFF format 1x1 km rasters with OSGB 1936 British National Grid projection (EPSG:27700).

In addition, indices of connectivity to these human activity gradients are contained in the other raster files. The file name indicates:

• the human activity (recreation, fishing, watersports)
• the form of connectivity (sp2d = spatial, down = downstream, up = upstream, along = along-channel)
• the distance decay in connectivity (x_km)  

Reference

Natural England (2017) Monitor of Engagement with the Natural Environment: The National Survey on People and the Natural Environment. Technical Report to the 2009-16 surveys, Natural England, Peterborough, UK