Abstract. Drained peatlands often act as carbon dioxide (CO 2 ) hotspots. Raising the groundwater table is expected to reduce their CO 2 contribution to the atmosphere and revitalise their function as carbon (C) sink in the long term. Without strict water management rewetting often results in partial flooding and the formation of spatially heterogeneous, nutrient-rich shallow lakes. Uncertainties remain as to when the intended effect of rewetting is achieved, as this specific ecosystem type has hardly been investigated in terms of greenhouse gas (GHG) exchange. In most cases of rewetting, methane (CH 4 ) emissions increase under anoxic conditions due to a higher water table and in terms of global warming potential (GWP) outperform the shift towards CO 2 uptake, at least in the short term.Based on eddy covariance measurements we studied the ecosystem-atmosphere exchange of CH 4 and CO 2 at a shallow lake situated on a former fen grassland in northeastern Germany. The lake evolved shortly after flooding, 9 years previous to our investigation period. The ecosystem consists of two main surface types: open water (inhabited by submerged and floating vegetation) and emergent vegetation (particularly including the eulittoral zone of the lake, dominated by Typha latifolia). To determine the individual contribution of the two main surface types to the net CO 2 and CH 4 exchange of the whole lake ecosystem, we combined footprint analysis with CH 4 modelling and net ecosystem exchange partitioning.The CH 4 and CO 2 dynamics were strikingly different between open water and emergent vegetation. Net CH 4 emissions from the open water area were around 4-fold higher than from emergent vegetation stands, accounting for 53 and 13 g CH 4 m −2 a −1 respectively. In addition, both surface types were net CO 2 sources with 158 and 750 g CO 2 m −2 a −1 respectively. Unusual meteorological conditions in terms of a warm and dry summer and a mild winter might have facilitated high respiration rates. In sum, even after 9 years of rewetting the lake ecosystem exhibited a considerable C loss and global warming impact, the latter mainly driven by high CH 4 emissions. We assume the eutrophic conditions in combination with permanent high inundation as major reasons for the unfavourable GHG balance.
Research infrastructures play a key role in launching a new generation of integrated long-term, geographically distributed observation programmes designed to monitor climate change, better understand its impacts on global ecosystems, and evaluate possible mitigation and adaptation strategies. The pan-European Integrated Carbon Observation System combines carbon and greenhouse gas (GHG; CO2, CH4, N2O, H2O) observations within the atmosphere, terrestrial ecosystems and oceans. High-precision measurements are obtained using standardised methodologies, are centrally processed and openly available in a traceable and verifiable fashion in combination with detailed metadata. The Integrated Carbon Observation System ecosystem station network aims to sample climate and land-cover variability across Europe. In addition to GHG flux measurements, a large set of complementary data (including management practices, vegetation and soil characteristics) is collected to support the interpretation, spatial upscaling and modelling of observed ecosystem carbon and GHG dynamics. The applied sampling design was developed and formulated in protocols by the scientific community, representing a trade-off between an ideal dataset and practical feasibility. The use of open-access, high-quality and multi-level data products by different user communities is crucial for the Integrated Carbon Observation System in order to achieve its scientific potential and societal value.
The Integrated Carbon Observation System Research Infrastructure aims to provide long-term, continuous observations of sources and sinks of greenhouse gases such as carbon dioxide, methane, nitrous oxide, and water vapour. At ICOS ecosystem stations, the principal technique for measurements of ecosystem-atmosphere exchange of GHGs is the eddy-covariance technique. The establishment and setup of an eddy-covariance tower have to be carefully reasoned to ensure high quality flux measurements being representative of the investigated ecosystem and comparable to measurements at other stations. To fulfill the requirements needed for flux determination with the eddy-covariance technique, variations in GHG concentrations have to be measured at high frequency, simultaneously with the wind velocity, in order to fully capture turbulent fluctuations. This requires the use of high-frequency gas analysers and ultrasonic anemometers. In addition, to analyse flux data with respect to environmental conditions but also to enable corrections in the post-processing procedures, it is necessary to measure additional abiotic variables in close vicinity to the flux measurements. Here we describe the standards the ICOS ecosystem station network has adopted for GHG flux measurements with respect to the setup of instrumentation on towers to maximize measurement precision and accuracy while allowing for flexibility in order to observe specific ecosystem features.
We conducted eddy covariance measurements from April to August 2014 on a Siberian thermokarst lake. The study site is located in the Lena River Delta and characterized as a floating ice lake. Heat fluxes differed in magnitudes, directions and temporal patterns depending on the lake surface conditions (“frozen” ice cover, ice cover melt, and open water). Significant heat release during frozen ice cover conditions highlighted the importance of lakes for the landscape heat budget and water balance. The energy balance was nearly closed during the open water period and highlighted the impact of melting energy on its closure during the ice cover period. Sensible and latent heat dynamics were driven by temperature and water vapor gradients scaled by wind speed, respectively. We calculated bulk aerodynamics transfer coefficients and evaluated the performance of the derived in situ and three independent heat flux parameterization schemes. We found that bulk transfer models perform moderately to poorly for the different lake surface conditions. During the open water period small‐scale temporal variability could not be represented by the models, particularly in case of latent heat flux. The model results were less sensitive to the specific model type than to the accuracy of the surface water temperature measurement, which is dependent on a well‐thought‐out measurement design. Our study stresses considerations that are crucial for similar campaigns in the future, in order to face the measurement challenges encountered on arctic lakes especially during the ice cover period.
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