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Agricultural Management and Climatic Change Are the Major Drivers of Biodiversity Change in the UK

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posted on 2023-07-26, 14:30 authored by Kyle A. Young, Fiona Burns, Mark A. Eaton, Kate E. Barlow, Björn C. Beckmann, Tom Brereton, David R. Brooks, Peter M. J. Brown, Nida Al Fulaij, Tony Gent, Ian Henderson, David G. Noble, Mark Parsons, Gary D. Powney, Helen E. Roy, Peter A. Stroh, Kevin Walker, John W. Wilkinson, Simon R. Wotton, Richard D. Gregory
Action to reduce anthropogenic impact on the environment and species within it will be most effective when targeted towards activities that have the greatest impact on biodiversity. To do this effectively we need to better understand the relative importance of different activities and how they drive changes in species’ populations. Here, we present a novel, flexible framework that reviews evidence for the relative importance of these drivers of change and uses it to explain recent alterations in species’ populations. We review drivers of change across four hundred species sampled from a broad range of taxonomic groups in the UK. We found that species’ population change (~1970–2012) has been most strongly impacted by intensive management of agricultural land and by climatic change. The impact of the former was primarily deleterious, whereas the impact of climatic change to date has been more mixed. Findings were similar across the three major taxonomic groups assessed (insects, vascular plants and vertebrates). In general, the way a habitat was managed had a greater impact than changes in its extent, which accords with the relatively small changes in the areas occupied by different habitats during our study period, compared to substantial changes in habitat management. Of the drivers classified as conservation measures, low-intensity management of agricultural land and habitat creation had the greatest impact. Our framework could be used to assess the relative importance of drivers at a range of scales to better inform our policy and management decisions. Furthermore, by scoring the quality of evidence, this framework helps us identify research gaps and needs.



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