The UK canal network is a point of vulnerability when it comes to mitigating the spread of invasive non-native species (INNS). There are approximately 2,200 miles (3,500 km) of navigable canals and rivers throughout the United Kingdom, with the highest density present in England. High connectivity of the canal system permits the rapid spread of unwanted aquatic organisms within and between connected rivers. This can lead to the spread of INNS between river catchments, mediated by canals, an often unquantified invasion pathway.
Freshwater environments are highly dynamic and prone to invasion by non-native species. The number of INNS is often associated with high human population density and as canal systems flow through urban areas they pose a high risk in mediating the spread of INNS. INNS are considered the second greatest threat to native wildlife and they cost the UK economy up to £1.7 billion a year (Williams et al, 2010). Every year the Canal and Rivers Trust spend ~ £700,000 treating invasive plant species. However, these direct control costs are likely to represent a small proportion of the wider impact of invasive species. INNS interfere with navigation and water control within the canal network, as well as reducing water quality and habitat availability for native species.
This project aims to assess the impact of canals on the transport of INNS through bulk water movements and leisure and transport craft.
The key objectives are: 1) Determine the extent of invasion by invasive alien plant and invertebrate species across the canal network using generalised linear models to derive a suitability map; 2) Identify a suite of INNS of particular concern, specifically to canals and canalised rivers based on their published traits and extent; 3) Determine the speed of invasion through chronosequence of invasion (a space-for-time substitution, e.g. Hasselquist et al 2015), for a managed section of canal; 4) Develop a network model of the UK canal system; 5) Make predictions on the future extent and speed of invasion using the network model, validated with field data.