Philosophical Transactions of the Royal Society B: Biological Sciences
Restricted accessResearch article

Pan-Arctic modelling of net ecosystem exchange of CO2

G. R. Shaver

G. R. Shaver

Ecosystems Center, Marine Biological Laboratory, Woods Hole, MA, USA

[email protected]

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E. B. Rastetter

E. B. Rastetter

Ecosystems Center, Marine Biological Laboratory, Woods Hole, MA, USA

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,
V. Salmon

V. Salmon

Ecosystems Center, Marine Biological Laboratory, Woods Hole, MA, USA

Department of Biology, University of Florida, Gainesville, FL, USA

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L. E. Street

L. E. Street

Ecosystems Center, Marine Biological Laboratory, Woods Hole, MA, USA

Department of Geography, University of Sheffield, Sheffield, UK

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M. J. van de Weg

M. J. van de Weg

Ecosystems Center, Marine Biological Laboratory, Woods Hole, MA, USA

Amsterdam Global Change Institute, Vrije Universiteit, Amsterdam, The Netherlands

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A. Rocha

A. Rocha

Ecosystems Center, Marine Biological Laboratory, Woods Hole, MA, USA

Department of Biological Sciences, University of Notre Dame, Notre Dame, IN, USA

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M. T. van Wijk

M. T. van Wijk

School of Geosciences, University of Edinburgh, Edinburgh, UK

Plant Sciences, Wageningen Agricultural University, Wageningen, The Netherlands

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M. Williams

M. Williams

Plant Sciences, Wageningen Agricultural University, Wageningen, The Netherlands

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    Net ecosystem exchange (NEE) of C varies greatly among Arctic ecosystems. Here, we show that approximately 75 per cent of this variation can be accounted for in a single regression model that predicts NEE as a function of leaf area index (LAI), air temperature and photosynthetically active radiation (PAR). The model was developed in concert with a survey of the light response of NEE in Arctic and subarctic tundras in Alaska, Greenland, Svalbard and Sweden. Model parametrizations based on data collected in one part of the Arctic can be used to predict NEE in other parts of the Arctic with accuracy similar to that of predictions based on data collected in the same site where NEE is predicted. The principal requirement for the dataset is that it should contain a sufficiently wide range of measurements of NEE at both high and low values of LAI, air temperature and PAR, to properly constrain the estimates of model parameters. Canopy N content can also be substituted for leaf area in predicting NEE, with equal or greater accuracy, but substitution of soil temperature for air temperature does not improve predictions. Overall, the results suggest a remarkable convergence in regulation of NEE in diverse ecosystem types throughout the Arctic.

    Footnotes

    One contribution of 11 to a Theme Issue ‘Long-term changes in Arctic tundra ecosystems’.

    References