• Energy Research

Surface-atmosphere energy exchange is strongly ecosystem-specific. At the same time, as the energy balance constitutes responses of an ecosystem to environmental stressors including precipitation, humidity and solar radiation, it results in feedbacks of potential importance for the regional climate. Northern peatlands represent a diverse class of ecosystems that cover nearly 6 x 10(6) km(2) in the Boreal region, which makes the inter-comparison of their energy balances an important objective. With this in mind we studied energy exchange across a broad spectrum of peatlands from pristine fens and bogs to forested and agriculturally managed peatlands, which represent a large fraction of the landscape in Finland and Sweden. The effects of management activities on the energy balance were extensively examined from the micrometeorological point of view, using eddy covariance data from eight sites in these two countries (56 degrees 12'-62 degrees 11' N, 13 degrees 03'-30 degrees 05' E). It appears that the surface energy balance varies widely amongst the different peatland types. Generally, energy exchange features including the Bowen ratio, surface conductance, coupling to the atmosphere, responses to water table fluctuations and vapour pressure deficit could be associated directly with the peatland type. The relative constancy of the Bowen ratio in natural open mires contrasted with its variation in tree-covered and agricultural peatlands. We conclude that the impacts of management and the consequences of land-use change in peatlands for the local and regional climate might be substantial. Peer reviewed

AbstractThe FLUXNET2015 dataset provides ecosystem-scale data on CO2, water, and energy exchange between the biosphere and the atmosphere, and other meteorological and biological measurements, from 212 sites around the globe (over 1500 site-years, up to and including year 2014). These sites, independently managed and operated, voluntarily contributed their data to create global datasets. Data were quality controlled and processed using uniform methods, to improve consistency and intercomparability across sites. The dataset is already being used in a number of applications, including ecophysiology studies, remote sensing studies, and development of ecosystem and Earth system models. FLUXNET2015 includes derived-data products, such as gap-filled time series, ecosystem respiration and photosynthetic uptake estimates, estimation of uncertainties, and metadata about the measurements, presented for the first time in this paper. In addition, 206 of these sites are for the first time distributed under a Creative Commons (CC-BY 4.0) license. This paper details this enhanced dataset and the processing methods, now made available as open-source codes, making the dataset more accessible, transparent, and reproducible.

AbstractThe regional variability in tundra and boreal carbon dioxide (CO2) fluxes can be high, complicating efforts to quantify sink‐source patterns across the entire region. Statistical models are increasingly used to predict (i.e., upscale) CO2 fluxes across large spatial domains, but the reliability of different modeling techniques, each with different specifications and assumptions, has not been assessed in detail. Here, we compile eddy covariance and chamber measurements of annual and growing season CO2 fluxes of gross primary productivity (GPP), ecosystem respiration (ER), and net ecosystem exchange (NEE) during 1990–2015 from 148 terrestrial high‐latitude (i.e., tundra and boreal) sites to analyze the spatial patterns and drivers of CO2 fluxes and test the accuracy and uncertainty of different statistical models. CO2 fluxes were upscaled at relatively high spatial resolution (1 km2) across the high‐latitude region using five commonly used statistical models and their ensemble, that is, the median of all five models, using climatic, vegetation, and soil predictors. We found the performance of machine learning and ensemble predictions to outperform traditional regression methods. We also found the predictive performance of NEE‐focused models to be low, relative to models predicting GPP and ER. Our data compilation and ensemble predictions showed that CO2 sink strength was larger in the boreal biome (observed and predicted average annual NEE −46 and −29 g C m−2 yr−1, respectively) compared to tundra (average annual NEE +10 and −2 g C m−2 yr−1). This pattern was associated with large spatial variability, reflecting local heterogeneity in soil organic carbon stocks, climate, and vegetation productivity. The terrestrial ecosystem CO2 budget, estimated using the annual NEE ensemble prediction, suggests the high‐latitude region was on average an annual CO2 sink during 1990–2015, although uncertainty remains high.