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the GiGLer

The newsletter of Greenspace Information of Greater London CIC

Modelling Risk

Karen Harper, London Invasive Species Initiative Manager

Recently, GiGL and LISI produced a range of predictive risk model layers for London for various invasive non-native species. Risk modelling is only as good as the data behind it, which is what made this project so innovative. We were able to use local data to create the model on a local scale, down to 100m² as well as a standard 1km² scale; making it more relevant to local partners and useful for informing local action. Exciting, yes?

The modelling was based on some simple ecological principles, such as suitable habitat, areas of environmental importance and existing invasive species records. These were ranked relative to each other to show comparative risk across Greater London.

From this, we have created a range of maps that show areas of higher risk (darker areas) compared to the areas of lower risk (lighter areas). We are able to see some unique features that you would expect to be high risk. For example aquatic species show rivers and water bodies to be at higher risk than terrestrial habitats.

Other risk areas are not immediately obvious and are worthy of investigation. The maps allow us to compare a range of factors not just to look at one simple qualifier like habitat suitability. They also give us a way to show something partially intangible to people who might not understand elements of evaluating ecological risk; and a simple way for people to pinpoint areas of the highest risk and allocate resources accordingly. There is a wide range of ways this type of modelling can help, including allowing managers to target monitoring of the potential spread of these species.

The next step is to continue working with the model to refine it for more species as needed. Please do let us know of the different ways you have been able to use this modelling as feedback is greatly appreciated.

As Manager of LISI, Karen knows that prevention and early treatment is the best way to manage invasive non-native species. She believes this style of modelling has allowed LISI to target areas where species of concern are likely to arrive or spread. “For me it has been great to see that this kind of modelling is not only possible but accurate with GiGL’s existing data. I hope people find it as useful, and exciting, as I have.”

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