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Land degradation neutrality: testing the indicator in a temperate agricultural landscape

Thomas, Amy ORCID: https://orcid.org/0000-0002-4929-7285; Bentley, Laura ORCID: https://orcid.org/0000-0001-5055-7673; Feeney, Chris ORCID: https://orcid.org/0000-0003-2175-1842; Lofts, Stephen ORCID: https://orcid.org/0000-0002-3627-851X; Robb, Ciaran ORCID: https://orcid.org/0000-0002-2314-4985; Rowe, Ed C. ORCID: https://orcid.org/0000-0003-4784-7236; Thomson, Amanda ORCID: https://orcid.org/0000-0002-7306-4545; Warren-Thomas, Eleanor ORCID: https://orcid.org/0000-0001-5746-1738; Emmett, Bridget ORCID: https://orcid.org/0000-0002-2713-4389. 2023 Land degradation neutrality: testing the indicator in a temperate agricultural landscape. Journal of Environmental Management, 346, 118884. 12, pp. 10.1016/j.jenvman.2023.118884

Abstract
Land degradation directly affects around 25% of land globally, undermining progress on most of the UN Sustainable Development Goals (SDG), particularly target 15.3. To assess land degradation, SDG indicator 15.3.1 combines sub-indicators of productivity, soil carbon and land cover. Over 100 countries have set Land Degradation Neutrality (LDN) targets. Here, we demonstrate application of the indicator for a well-established agricultural landscape using the case study of Great Britain. We explore detection of degradation in such landscapes by: 1) transparently evaluating land cover transitions; 2) comparing assessments using global and national data; 3) identifying misleading trends; and 4) including extra sub-indicators for additional forms of degradation. Our results demonstrate significant impacts on the indicator both from the land cover transition evaluation and choice or availability of data. Critically, we identify a misleading improvement trend due to a trade-off between improvement detected by the productivity sub-indicator, and 30-year soil carbon loss trends in croplands (11% from 1978 to 2007). This carbon loss trend would not be identified without additional data from Countryside Survey (CS). Thus, without incorporating field survey data we risk overlooking the degradation of regulating and supporting ecosystem services (linked to soil carbon), in favour of signals from improving provisioning services (productivity sub-indicator). Relative importance of these services will vary between socioeconomic contexts. Including extra sub-indicators for erosion or critical load exceedance, as additional forms of degradation, produced a switch from net area improving (9%) to net area degraded (58%). CS data also identified additional degradation for soil health, including 44% arable soils exceeding bulk density thresholds and 35% of CS squares exceeding contamination thresholds for metals.
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