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

Payne, Richard J and Campbell, Claire and Britton, Andrea J and Mitchell, Ruth J and Pakeman, Robin J and Jones, Laurence and Ross, Louise C and Stevens, Carly J and Field, Christopher and Caporn, Simon JM and Carroll, Jacky and Edmondson, Jill L and Carnell, Edward J and Tomlinson, Sam and Dore, Anthony J and Dise, Nancy and Dragosits, Ulrike (2019) What is the most ecologically-meaningful metric of nitrogen deposition? Environmental Pollution, 247. pp. 319-331. ISSN 0269-7491

Restricted to Repository staff only until 19 January 2020.
Available under License Creative Commons Attribution Non-commercial No Derivatives.

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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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