Monitoring greenhouse gas fluxes in an array of Dutch natural peatlands and fen meadows using mobile Eddy covariance. 

Abstract

<p>Natural peatlands and fen meadows have the potential to sequester CO<sub>2</sub> from the atmosphere but can also <br>form a major source of CH<sub>4</sub> emissions. However, their flux dynamics, showing the diurnal and annual <br>variation of GHG exchange depend on site characteristics such as soil/peat type, water dynamics and<br>management practices. It is thus essential, that carbon fluxes of different locations are individually <br>quantified in order to assess if, from a climate perspective, CO<sub>2</sub> uptake outweighs CH<sub>4</sub> emission for these <br>areas.</p><p>We deployed five movable eddy covariance measurement stations to chart dynamics of CO<sub>2</sub> and CH<sub>4</sub> fluxes <br>in an array of peat soil sites. The fluxes are measured directly, alternating every few weeks between the <br>different sites. One aim of the study is to examine the feasibility of these moveable stations, as they may <br>reduce the relatively high investment costs of EC measurements per site. We show that moveable stations <br>are feasible from a practical point of view, as the stations can be relocated relatively easily within the time <br>span of a few hour.</p><p>The resulting carbon budgets provide insight into an array of site specific GHG exchanges over typically <br>small temporal and spatial scales. Meteorological observations are permanently performed at all selected <br>locations as well, along with other supportive measurements such as soil/water temperature, moisture and <br>water level.</p><p>Since the measurement stations alternate between locations, robust gap filling methods are needed to <br>obtain a complete picture of the variability of the flux dynamics over the entire year for each location. The <br>main objective of this study is to identify most suitable and robust gap filling methods. As such<br>measurements from the permanent meteorological stations serve to force several gap-filling methods such <br>as interpolation based on observed ecosystem responses, the look up table approach and more established <br>methods. We also investigate in the use of more process-based empirical models as the gaps between <br>measurement periods are longer. Results show that the mobile eddy covariance approach does allow<br>identification of significant differences in GHG flux between sites as well as meaningful aggregation to <br>annual budgets.</p><p>Ultimately, enabling the monitoring at more locations than with static systems may serve as a basis for <br>policy makers and land managers to shape nature conservation or agricultural practices that achieve a net <br>mitigation of greenhouse warming potential.</p>