A national-scale model of linear features improves predictions of farmland biodiversity

Sullivan, Martin J.P.; Pearce-Higgins, James W.; Newson, Stuart E.; Scholefield, Paul ORCID: https://orcid.org/0000-0003-2974-6431; Brereton, Tom; Oliver, Tom H.. 2017 A national-scale model of linear features improves predictions of farmland biodiversity. Journal of Applied Ecology, 54 (6). 1776-1784. https://doi.org/10.1111/1365-2664.12912

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Abstract/Summary

1. Modelling species distribution and abundance is important for many conservation applications, but it is typically performed using relatively coarse-scale environmental variables such as the area of broad land-cover types. Fine-scale environmental data capturing the most biologically-relevant variables have the potential to improve these models. For example, field studies have demonstrated the importance of linear features, such as hedgerows, for multiple taxa, but the absence of large-scale datasets of their extent prevents their inclusion in large-scale modelling studies. 2. We assessed whether a novel spatial dataset mapping linear and woody linear features across the UK improves the performance of abundance models of 18 bird and 24 butterfly species across 3723 and 1547 UK monitoring sites respectively. 3. Although improvements in explanatory power were small, the inclusion of linear features data significantly improved model predictive performance for many species. For some species, the importance of linear features depended on landscape context, with greater importance in agricultural areas. 4. Synthesis and applications. This study demonstrates that a national-scale model of the extent and distribution of linear features improves predictions of farmland biodiversity. The ability to model spatial variability in the role of linear features such as hedgerows will be important in targeting agri-environment schemes to maximally deliver biodiversity benefits. Although this study focuses on farmland, data on the extent of different linear features are likely to improve species distribution and abundance models in a wide range of systems, and also can potentially be used to assess habitat connectivity.

Item Type:	Publication - Article
Digital Object Identifier (DOI):	https://doi.org/10.1111/1365-2664.12912
UKCEH and CEH Sections/Science Areas:	UKCEH Fellows Parr
ISSN:	0021-8901
Additional Information. Not used in RCUK Gateway to Research.:	Open Access paper - full text available via Official URL link.
Additional Keywords:	abundance model, agriculture, bird, butterfly, GIS, hedgerow, remote sensing, species distribution model
NORA Subject Terms:	Ecology and Environment
Date made live:	30 Mar 2017 11:13 +0 (UTC)
URI:	https://nora.nerc.ac.uk/id/eprint/516447

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