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PhD Research

Invasive Species and In-stream Infrastructure

Invasive species and river infrastructure (e.g. dams, weirs and culverts) are widely recognised as key drivers of freshwater biodiversity loss. These stressors are commonly considered in isolation, but a growing body of evidence suggests that river infrastructure can limit the spread of invasive species by acting as a physical barrier to movement. Indeed, some have even suggested that the construction or maintenance of such barriers (i.e. 'exclusion barriers') may be a useful management strategy in cases where eradication is impossible. However, previous studies have typically focused on passage success at individual barriers (i.e., limited spatial scale) over short time periods (i.e., limited temporal scale), meaning little is known about the effectiveness of barriers for long-term, catchment-scale management.

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This project used an individual-based modelling approach to determine the extent to which barriers can limit the spread of invasive species over large spatio-temporal scales, using the American signal crayfish (Pacifastacus leniusculus) as a model species. Fine-scale laboratory experiments were undertaken to determine the influence of personality and population density on crayfish barrier passage, and the results of these studies (alongside existing population dynamics and movement data) were incorporated into an existing individual-based model (IBM) that could accurately predict the spread of signal crayfish through an unbranching virtual river. The existing IBM was then developed and extended to work across real river systems with multiple barriers of different types, and was subsequently applied to the River Glaven (Norfolk, UK). The model was used to predict the impacts of modifying existing barriers to maximise their effectiveness against signal crayfish, and these predictions were combined with estimates of economic costs and impacts on native fish. Working with local river managers, a multi-criteria decision analysis was then conducted to identify the optimal barrier configuration in the catchment. Finally, the model was validated by integrating a variety of large and complex spatial datasets to explore the drivers of crayfish spread at a national scale.

An example of anthropogenic in-stream infrastructure in the River Glaven (Norfolk, UK).

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