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

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Impacts of pollution and climate change on ombrotrophic Sphagnum species in the UK: analysis of uncertainties in two empirical niche models. / Smart, Simon; Henrys, P.A; Scott, W.A et al.
In: Climate Research, Vol. 45, No. CR Special 24, 2010, p. 163-177.

Research output: Contribution to Journal/MagazineJournal articlepeer-review

Harvard

Smart, S, Henrys, PA, Scott, WA, Hall, J, Evans, C, Rowe, E, Page, T, Whyatt, D, Sowerby, A & Clark, J 2010, 'Impacts of pollution and climate change on ombrotrophic Sphagnum species in the UK: analysis of uncertainties in two empirical niche models', Climate Research, vol. 45, no. CR Special 24, pp. 163-177. https://doi.org/10.3354/cr00969

APA

Smart, S., Henrys, P. A., Scott, W. A., Hall, J., Evans, C., Rowe, E., Page, T., Whyatt, D., Sowerby, A., & Clark, J. (2010). Impacts of pollution and climate change on ombrotrophic Sphagnum species in the UK: analysis of uncertainties in two empirical niche models. Climate Research, 45(CR Special 24), 163-177. https://doi.org/10.3354/cr00969

Vancouver

Smart S, Henrys PA, Scott WA, Hall J, Evans C, Rowe E et al. Impacts of pollution and climate change on ombrotrophic Sphagnum species in the UK: analysis of uncertainties in two empirical niche models. Climate Research. 2010;45(CR Special 24):163-177. doi: 10.3354/cr00969

Author

Smart, Simon ; Henrys, P.A ; Scott, W.A et al. / Impacts of pollution and climate change on ombrotrophic Sphagnum species in the UK: analysis of uncertainties in two empirical niche models. In: Climate Research. 2010 ; Vol. 45, No. CR Special 24. pp. 163-177.

Bibtex

@article{23f74f027d21453bb1c20a5a5380d9ad,
title = "Impacts of pollution and climate change on ombrotrophic Sphagnum species in the UK: analysis of uncertainties in two empirical niche models",
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.",
keywords = "Nitrogen, Sulphur, Generalised linear model , Generalised additive model, Uncertainty , Large scale , Peatlands, UKCP09 , UKCIP02",
author = "Simon Smart and P.A Henrys and W.A Scott and Jane Hall and Chris Evans and Ed Rowe and Trevor Page and Duncan Whyatt and A Sowerby and Joanne Clark",
year = "2010",
doi = "10.3354/cr00969",
language = "English",
volume = "45",
pages = "163--177",
journal = "Climate Research",
issn = "0936-577X",
publisher = "Inter-Research",
number = "CR Special 24",

}

RIS

TY - JOUR

T1 - Impacts of pollution and climate change on ombrotrophic Sphagnum species in the UK: analysis of uncertainties in two empirical niche models

AU - Smart, Simon

AU - Henrys, P.A

AU - Scott, W.A

AU - Hall, Jane

AU - Evans, Chris

AU - Rowe, Ed

AU - Page, Trevor

AU - Whyatt, Duncan

AU - Sowerby, A

AU - Clark, Joanne

PY - 2010

Y1 - 2010

N2 - 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.

AB - 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.

KW - Nitrogen

KW - Sulphur

KW - Generalised linear model

KW - Generalised additive model

KW - Uncertainty

KW - Large scale

KW - Peatlands

KW - UKCP09

KW - UKCIP02

U2 - 10.3354/cr00969

DO - 10.3354/cr00969

M3 - Journal article

VL - 45

SP - 163

EP - 177

JO - Climate Research

JF - Climate Research

SN - 0936-577X

IS - CR Special 24

ER -