Can citizen science provide a solution for bat-friendly planning?

Can citizen science provide a solution for bat-friendly planning?

Landscape & Urban Planning, 2022

Citation

Border, J.A., Gillings, S., Reynolds, T., Neeve, G. & Newson, S.E. 2022. Can citizen science provide a solution for bat-friendly planning?. Landscape & Urban Planning 223: doi:10.1016/j.landurbplan.2022.104402

Overview

Can gaps in our knowledge about the occurrence and activity of UK bats be addressed through the use of a citizen science approach? Can we use such an approach to support effective decision-making during the planning process, with opportunity and risk maps that can guide planning decisions and the location of mitigation measures?

In more detail

We are grateful to everyone who has taken part, hosted equipment or helped in other ways to make the project so successful. These analyses were funded by Natural England, as a pilot to look at ways of reforming licensing and planning for bats. We are particularly grateful to Rob Cameron at Natural England for commissioning this work, and his valuable input throughout. We are also grateful to Stephen Rudd, Matt Zeale, Jean Matthews, Katherine Boughey and Ben Payne for their comments on an earlier draft of the paper, and to valuable discussion at meetings of Natural England’s Bat Expert Panel. Thanks also to Sam Neal from Norfolk County Council for providing us with data on Norfolk’s Green Infrastructure corridors for use in these analyses. Thanks to the two anonymous reviewers and the editor for helpful comments and advice.

Abstract

Urban expansion is a severe threat to biodiversity. In the UK, bats are protected meaning new developments need to be surveyed, potential impacts assessed, and appropriate mitigation action taken. However, efforts to minimise effects of urbanisation on bats are hampered by a lack of data for many species making it difficult to implement effective conservation measures. Here we explore whether citizen science data on bat activity via a passive acoustic network can be used to produce maps of high risk areas to bats from urbanisation and areas with the best opportunities for habitat mitigation. We combine the passive acoustic dataset with fine-scale habitat data and use models to quantify the effect of increasing urban areas or increasing suitable habitat (woodland, wetland, or grass heathland). Passive acoustic detection can provide a high volume of data and large area of coverage, which is vital to the success of this modelling approach, but the data quality is dependent on accurate species classification. Therefore, we also assess the effect of identification uncertainty on the accuracy of the risk and opportunity maps. We found agreement between results accounting for species uncertainty and those that did not was high, although approximately 15% of high-risk areas would have been missed, and about 23% of habitat creation opportunities falsely prioritised. This modelling and mapping approach has great potential for use in the planning process to reduce impacts on the most important habitat features in the landscape and enable targeted habitat creation.