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Sampling frequency affects estimates of annual nitrous oxide fluxes
L Barton1, B Wolf2, D Rowlings3
1Soil Biology and Molecular Ecology Group, School of Earth &Environment (M087), UWA Institute of Agriculture, Faculty of Sciences, The University of Western Australia, 35 Stirling Highway, Crawley, Western Australia 6009, Australia.
Scientific Reports
|November 3, 2015
Summary
Daily soil sampling is crucial for accurately measuring annual nitrous oxide (N2O) fluxes, a potent greenhouse gas. Insufficient sampling frequency leads to significant over or underestimations of N2O losses.
Area of Science:
- Environmental Science
- Soil Science
- Climate Change Research
Background:
- Nitrous oxide (N2O) is a potent greenhouse gas with significant soil emissions.
- Accurate quantification of terrestrial N2O losses is vital for understanding global carbon cycles.
- High temporal variability of N2O fluxes complicates accurate annual flux calculations.
Purpose of the Study:
- To determine optimal soil sampling frequencies for calculating annual N2O fluxes.
- To assess the impact of varying measurement frequencies on N2O flux estimations.
- To reduce uncertainty in global terrestrial N2O budgets.
Main Methods:
- Analysis of 28 annual datasets of soil N2O fluxes from Australia, Europe, and Asia.
- Evaluation of daily sampling requirements for achieving a 10% accuracy threshold.
- Comparison of flux estimates with different measurement frequencies, including strategies based on environmental factors.
Main Results:
- Daily soil sampling was largely necessary to achieve annual N2O fluxes within 10% of the best estimate.
- Reduced measurement frequency led to significant under- or overestimations, with overestimations up to 935%.
- Even sampling strategies based on environmental factors required more than weekly measurements.
Conclusions:
- Adequate soil sampling frequencies are essential for reliable annual N2O flux quantification.
- Current global N2O budgets may have significant uncertainties due to inadequate sampling.
- Implementing appropriate measurement frequencies can substantially decrease uncertainty in upscaled terrestrial N2O datasets.
