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Inferring nitrogen deposition from plant community composition

Research output: Contribution to journalArticle

Published copy (DOI)

Author(s)

  • Richard J. Payne
  • Simon J. M. Caporn
  • Carly J. Stevens
  • Jacky A. Carroll
  • Jill L. Edmondson
  • David J. Gowing
  • Nancy B. Dise

Department/unit(s)

Publication details

JournalEcological Indicators
DateE-pub ahead of print - 14 Nov 2012
DatePublished (current) - Mar 2013
Volume26
Number of pages4
Pages (from-to)1-4
Early online date14/11/12
Original languageEnglish

Abstract

Chronically elevated reactive nitrogen deposition has a severe impact on many ecosystems, and there is widespread interest in the possibility of using plant community composition to estimate the level of nitrogen deposition and consequent impacts. Existing approaches use a variety of simple measures including functional type ratios, Ellenberg numbers, and diversity indices. We propose an alternative approach in which species–environment models are constructed using national datasets designed to capture broad-scale deposition patterns. We construct models using partial least squares, weighted average, and maximum likelihood Gaussian logit regression for two British semi-natural habitats, and test how well they predict N deposition by cross-validation. We find that performance is good with R2 values up to 0.7, and suggest that such models could be a useful addition to the bioindication toolbox.

    Research areas

  • Nitrogen, Bioindication, Pollution, Ellenberg indices, Transfer functions, Biodiversity

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