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CR 45:163-176 (2010)  -  DOI:

Impacts of pollution and climate change on ombrotrophic Sphagnum species in the UK: analysis of uncertainties in two empirical niche models

S. M. Smart1,*, P. A. Henrys1, W. A. Scott1, J. R. Hall2, C. D. Evans2, A. Crowe1, E. C. Rowe2, U. Dragosits3, T. Page4, J. D. Whyatt4, A. Sowerby2, J. M. Clark5,6,7

1NERC Centre for Ecology and Hydrology, Library Avenue, Bailrigg, Lancaster LA1 4AP, UK
2NERC Centre for Ecology and Hydrology, Environment Centre Wales, Deiniol Road, Bangor, Gwynedd LL57 2UW, UK
3NERC Centre for Ecology and Hydrology, Bush estate, Penicuik, Midlothian EH26 0QB, UK
4Lancaster Environment Centre, Lancaster University, Bailrigg, Lancaster LA1 4AP, UK
5Wolfson Carbon Capture Laboratory, School of Biological Sciences, Bangor University, Deiniol Road, Bangor, Gwynedd LL57 2UW, UK
6Grantham Institute for Climate Change Fellow, and Environmental Engineering, Imperial College London, South Kensington, London SW7 2AZ, UK
7Present address: Walker Institute for Climate Systems Research and Soils Research Centre, Geography and Environmental Science, School of Human and Environmental Sciences, University of Reading, Whiteknights Reading RG6 6DW, UK

ABSTRACT: A significant challenge in the prediction of climate change impacts on ecosystems and biodiversity is quantifying the sources of uncertainty that emerge within and between different models. Statistical species niche models have grown in popularity, yet no single best technique has been identified reflecting differing performance in different situations. Our aim was to quantify uncertainties associated with the application of 2 complimentary modelling techniques. Generalised linear mixed models (GLMM) and generalised additive mixed models (GAMM) were used to model the realised niche of ombrotrophic Sphagnum species in British peatlands. These models were then used to predict changes in Sphagnum cover between 2020 and 2050 based on projections of climate change and atmospheric deposition of nitrogen and sulphur. Over 90% of the variation in the GLMM predictions was due to niche model parameter uncertainty, dropping to 14% for the GAMM. After having covaried out other factors, average variation in predicted values of Sphagnum cover across UK peatlands was the next largest source of variation (8% for the GLMM and 86% for the GAMM). The better performance of the GAMM needs to be weighed against its tendency to overfit the training data. While our niche models are only a first approximation, we used them to undertake a preliminary evaluation of the relative importance of climate change and nitrogen and sulphur deposition and the geographic locations of the largest expected changes in Sphagnum cover. Predicted changes in cover were all small (generally <1% in an average 4 m2 unit area) but also highly uncertain. Peatlands expected to be most affected by climate change in combination with atmospheric pollution were Dartmoor, Brecon Beacons and the western Lake District.

KEY WORDS: Nitrogen · Sulphur · Generalised linear model · Generalised additive model · Uncertainty · Large scale · Peatlands · UKCP09 · UKCIP02

Supplementary material 
Cite this article as: Smart SM, Henrys PA, Scott WA, Hall JR and others (2010) Impacts of pollution and climate change on ombrotrophic Sphagnum species in the UK: analysis of uncertainties in two empirical niche models. Clim Res 45:163-176.

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