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What is the most ecologically-meaningful metric of nitrogen deposition?

Payne, Richard J.; Campbell, Claire; Britton, Andrea J.; Mitchell, Ruth J.; Pakeman, Robin J.; Jones, Laurence ORCID: https://orcid.org/0000-0002-4379-9006; Ross, Louise C.; Stevens, Carly J.; Field, Christopher; Caporn, Simon J.M.; Carroll, Jacky; Edmondson, Jill L.; Carnell, Edward J. ORCID: https://orcid.org/0000-0003-0870-1955; Tomlinson, Sam ORCID: https://orcid.org/0000-0002-3237-7596; Dore, Anthony J.; Dise, Nancy ORCID: https://orcid.org/0000-0003-0463-6885; Dragosits, Ulrike ORCID: https://orcid.org/0000-0002-9283-6467. 2019 What is the most ecologically-meaningful metric of nitrogen deposition? Environmental Pollution, 247. 319-331. 10.1016/j.envpol.2019.01.059

Abstract
Nitrogen (N) deposition poses a severe risk to global terrestrial ecosystems, and managing this threat is an important focus for air pollution science and policy. To understand and manage the impacts of N deposition, we need metrics which accurately reflect N deposition pressure on the environment, and are responsive to changes in both N deposition and its impacts over time. In the UK, the metric typically used is a measure of total N deposition over 1–3 years, despite evidence that N accumulates in many ecosystems and impacts from low-level exposure can take considerable time to develop. Improvements in N deposition modelling now allow the development of metrics which incorporate the long-term history of pollution, as well as current exposure. Here we test the potential of alternative N deposition metrics to explain vegetation compositional variability in British semi-natural habitats. We assembled 36 individual datasets representing 48,332 occurrence records in 5479 quadrats from 1683 sites, and used redundancy analyses to test the explanatory power of 33 alternative N metrics based on national pollutant deposition models. We find convincing evidence for N deposition impacts across datasets and habitats, even when accounting for other large-scale drivers of vegetation change. Metrics that incorporate long-term N deposition trajectories consistently explain greater compositional variance than 1–3 year N deposition. There is considerable variability in results across habitats and between similar metrics, but overall we propose that a thirty-year moving window of cumulative deposition is optimal to represent impacts on plant communities for application in science, policy and management.
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Programmes:
UKCEH and CEH Science Areas 2017-24 (Lead Area only) > Atmospheric Chemistry and Effects
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