Payne, Richard J, Campbell, Claire, Britton, Andrea J, Mitchell, Ruth J, Pakeman, Robin J, Jones, Laurence, Ross, Louise C, Stevens, Carly J, Field, Christopher ORCID: https://orcid.org/0000-0002-8403-2848, Caporn, Simon JM, Carroll, Jacky, Edmondson, Jill L, Carnell, Edward J, Tomlinson, Sam, Dore, Anthony J, 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
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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.
Impact and Reach
Statistics
Additional statistics for this dataset are available via IRStats2.