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2. |
- Natali, S. M., et al.
(author)
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Large loss of CO2 in winter observed across the northern permafrost region
- 2019
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In: Nature Climate Change. - : Springer Science and Business Media LLC. - 1758-678X .- 1758-6798. ; 9:11, s. 852-857
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Journal article (peer-reviewed)abstract
- Recent warming in the Arctic, which has been amplified during the winter(1-3), greatly enhances microbial decomposition of soil organic matter and subsequent release of carbon dioxide (CO2)(4). However, the amount of CO2 released in winter is not known and has not been well represented by ecosystem models or empirically based estimates(5,6). Here we synthesize regional in situ observations of CO2 flux from Arctic and boreal soils to assess current and future winter carbon losses from the northern permafrost domain. We estimate a contemporary loss of 1,662 TgC per year from the permafrost region during the winter season (October-April). This loss is greater than the average growing season carbon uptake for this region estimated from process models (-1,032 TgC per year). Extending model predictions to warmer conditions up to 2100 indicates that winter CO2 emissions will increase 17% under a moderate mitigation scenario-Representative Concentration Pathway 4.5-and 41% under business-as-usual emissions scenario-Representative Concentration Pathway 8.5. Our results provide a baseline for winter CO2 emissions from northern terrestrial regions and indicate that enhanced soil CO2 loss due to winter warming may offset growing season carbon uptake under future climatic conditions.
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3. |
- Jansen, Joachim, 1989-, et al.
(author)
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Monitoring of carbon-water fluxes at Eurasian meteorological stations using random forest and remote sensing
- 2023
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In: Scientific Data. - : Springer Nature. - 2052-4463. ; 10:1
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Journal article (peer-reviewed)abstract
- Simulating the carbon-water fluxes at more widely distributed meteorological stations based on the sparsely and unevenly distributed eddy covariance flux stations is needed to accurately understand the carbon-water cycle of terrestrial ecosystems. We established a new framework consisting of machine learning, determination coefficient (R2), Euclidean distance, and remote sensing (RS), to simulate the daily net ecosystem carbon dioxide exchange (NEE) and water flux (WF) of the Eurasian meteorological stations using a random forest model or/and RS. The daily NEE and WF datasets with RS-based information (NEE-RS and WF-RS) for 3774 and 4427 meteorological stations during 2002-2020 were produced, respectively. And the daily NEE and WF datasets without RS-based information (NEE-WRS and WF-WRS) for 4667 and 6763 meteorological stations during 1983-2018 were generated, respectively. For each meteorological station, the carbon-water fluxes meet accuracy requirements and have quasi-observational properties. These four carbon-water flux datasets have great potential to improve the assessments of the ecosystem carbon-water dynamics.
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4. |
- Friborg, J, et al.
(author)
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Securing hydropower production using airborne Gpr
- 2022
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Conference paper (peer-reviewed)abstract
- Hydropower is an essential source of renewable energy. To secure power production in cold climates, it is of vital importance to continuously collect information regarding ice build-up around the power plant. The amount of ice, and the quality of the same, can cause significant loss in power production. Ice loads on dam structures are complicated to model and predict without plenty of data points. Traditionally this is performed by foot and using drilling, which is not only a safety issue but usually delivers too few data points to obtain an accurate model of the ice load. With recent developments of airborne GPR equipment, hazardous areas can be investigated safely and efficiently. Furthermore, in comparison to traditional methods airborne GPR collects vast amounts of data points, thus helping create better and more stable models for ice-loads. This paper covers a study from around a hydropower plant in northern Sweden. The study discusses the pros and cons of using air borne GPR equipment for securing hydropower production in cold climate areas.
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6. |
- Oehri, Jacqueline, et al.
(author)
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Vegetation type is an important predictor of the arctic summer land surface energy budget
- 2022
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In: Nature Communications. - : Springer Nature. - 2041-1723. ; 13
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Journal article (peer-reviewed)abstract
- Despite the importance of high-latitude surface energy budgets (SEBs) for land-climate interactions in the rapidly changing Arctic, uncertainties in their prediction persist. Here, we harmonize SEB observations across a network of vegetated and glaciated sites at circumpolar scale (1994–2021). Our variance-partitioning analysis identifies vegetation type as an important predictor for SEB-components during Arctic summer (June-August), compared to other SEB-drivers including climate, latitude and permafrost characteristics. Differences among vegetation types can be of similar magnitude as between vegetation and glacier surfaces and are especially high for summer sensible and latent heat fluxes. The timing of SEB-flux summer-regimes (when daily mean values exceed 0 Wm−2) relative to snow-free and -onset dates varies substantially depending on vegetation type, implying vegetation controls on snow-cover and SEB-flux seasonality. Our results indicate complex shifts in surface energy fluxes with land-cover transitions and a lengthening summer season, and highlight the potential for improving future Earth system models via a refined representation of Arctic vegetation types.
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7. |
- Chadburn, Sarah E., et al.
(author)
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Modeled Microbial Dynamics Explain the Apparent Temperature Sensitivity of Wetland Methane Emissions
- 2020
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In: Global Biogeochemical Cycles. - 0886-6236 .- 1944-9224. ; 34:11
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Journal article (peer-reviewed)abstract
- Methane emissions from natural wetlands tend to increase with temperature and therefore may lead to a positive feedback under future climate change. However, their temperature response includes confounding factors and appears to differ on different time scales. Observed methane emissions depend strongly on temperature on a seasonal basis, but if the annual mean emissions are compared between sites, there is only a small temperature effect. We hypothesize that microbial dynamics are a major driver of the seasonal cycle and that they can explain this apparent discrepancy. We introduce a relatively simple model of methanogenic growth and dormancy into a wetland methane scheme that is used in an Earth system model. We show that this addition is sufficient to reproduce the observed seasonal dynamics of methane emissions in fully saturated wetland sites, at the same time as reproducing the annual mean emissions. We find that a more complex scheme used in recent Earth system models does not add predictive power. The sites used span a range of climatic conditions, with the majority in high latitudes. The difference in apparent temperature sensitivity seasonally versus spatially cannot be recreated by the non-microbial schemes tested. We therefore conclude that microbial dynamics are a strong candidate to be driving the seasonal cycle of wetland methane emissions. We quantify longer-term temperature sensitivity using this scheme and show that it gives approximately a 12% increase in emissions per degree of warming globally. This is in addition to any hydrological changes, which could also impact future methane emissions.
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9. |
- Petrescu, Ana Maria Roxana, et al.
(author)
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The uncertain climate footprint of wetlands under human pressure
- 2015
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In: Proceedings of the National Academy of Sciences. - : Proceedings of the National Academy of Sciences. - 1091-6490 .- 0027-8424. ; 112:15, s. 4594-4599
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Journal article (peer-reviewed)abstract
- Significant climate risks are associated with a positive carbon-temperature feedback in northern latitude carbon-rich ecosystems, making an accurate analysis of human impacts on the net greenhouse gas balance of wetlands a priority. Here, we provide a coherent assessment of the climate footprint of a network of wetland sites based on simultaneous and quasi-continuous ecosystem observations of CO2 and CH4 fluxes. Experimental areas are located both in natural and in managed wetlands and cover a wide range of climatic regions, ecosystem types, and management practices. Based on direct observations we predict that sustained CH4 emissions in natural ecosystems are in the long term (i.e., several centuries) typically offset by CO2 uptake, although with large spatiotemporal variability. Using a space-for-time analogy across ecological and climatic gradients, we represent the chronosequence from natural to managed conditions to quantify the "cost" of CH4 emissions for the benefit of net carbon sequestration. With a sustained pulse-response radiative forcing model, we found a significant increase in atmospheric forcing due to land management, in particular for wetland converted to cropland. Our results quantify the role of human activities on the climate footprint of northern wetlands and call for development of active mitigation strategies for managed wetlands and new guidelines of the Intergovernmental Panel on Climate Change (IPCC) accounting for both sustained CH4 emissions and cumulative CO2 exchange.
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10. |
- Terzidis, Emmanouil, 1994, et al.
(author)
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Tumor volume definitions in head and neck squamous cell carcinoma - Comparing PET/MRI and histopathology
- 2023
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In: Radiotherapy and Oncology. - : Elsevier BV. - 0167-8140. ; 180
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Journal article (peer-reviewed)abstract
- Background and purpose: In cancer treatment precise definition of the tumor volume is essential, but despite development in imaging modalities, this remains a challenge. Here, pathological tumor volumes from the surgical specimens were obtained and compared to tumor volumes defined from modern PET/ MRI hybrid imaging. The purpose is to evaluate mismatch between the volumes defined from imaging and pathology was estimated and potential clinical impact.Methods and Materials: Twenty-five patients with head and neck squamous cell carcinoma were scanned on an integrated PET/MRI system prior to surgery. Three gross tumor volumes (GTVs) from the primary tumor site were delineated defined from MRI (GTVMRI), PET (GTVPET) and one by utilizing both anatomical images and clinical information (GTVONCO). Twenty-five primary tumor specimens were extracted en bloc, scanned with PET/MRI and co-registered to the patient images. Each specimen was sectioned in blocks, sliced and stained with haematoxylin and eosin. All slices were digitalized and tumor delineated by a head and neck pathologist. The pathological tumor areas in all slices were interpolated yielding a pathological 3D tumor volume (GTVPATO). GTVPATO was compared with the imaging GTV's and potential mismatch was estimated.Results: Thirteen patients were included. The mean volume of GTVONCO was larger than the GTV's defined from PET or MRI. The mean mismatch of the GTVPATO compared to the GTVPET, GTVMRI and GTVONCO was 31.9 %, 54.5 % and 27.9 % respectively, and the entire GTVPATO was only fully encompassed in GTVONCO in 1 of 13 patients. However, after the addition of a clinical 5 mm margin the GTVPATO was fully encompassed in GTVONCO in 11 out of 13 patients.Conclusions: Despite modern hybrid imaging modalities, a mismatch between imaging and pathological defined tumor volumes was observed in all patients. A 5 mm clinical margin was sufficient to ensure inclusion of the entire pathological volume in 11 out of 13 patients.(c) 2023 The Authors. Published by Elsevier B.V. Radiotherapy and Oncology 180 (2023) 1-8 This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
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11. |
- Yuan, Kunxiaojia, et al.
(author)
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Causality guided machine learning model on wetland CH4 emissions across global wetlands
- 2022
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In: Agricultural and Forest Meteorology. - : Elsevier. - 0168-1923 .- 1873-2240. ; 324
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Journal article (peer-reviewed)abstract
- Wetland CH4 emissions are among the most uncertain components of the global CH4 budget. The complex nature of wetland CH4 processes makes it challenging to identify causal relationships for improving our understanding and predictability of CH4 emissions. In this study, we used the flux measurements of CH4 from eddy covariance towers (30 sites from 4 wetlands types: bog, fen, marsh, and wet tundra) to construct a causality-constrained machine learning (ML) framework to explain the regulative factors and to capture CH4 emissions at sub -seasonal scale. We found that soil temperature is the dominant factor for CH4 emissions in all studied wetland types. Ecosystem respiration (CO2) and gross primary productivity exert controls at bog, fen, and marsh sites with lagged responses of days to weeks. Integrating these asynchronous environmental and biological causal relationships in predictive models significantly improved model performance. More importantly, modeled CH4 emissions differed by up to a factor of 4 under a +1C warming scenario when causality constraints were considered. These results highlight the significant role of causality in modeling wetland CH(4 )emissions especially under future warming conditions, while traditional data-driven ML models may reproduce observations for the wrong reasons. Our proposed causality-guided model could benefit predictive modeling, large-scale upscaling, data gap-filling, and surrogate modeling of wetland CH4 emissions within earth system land models.
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12. |
- Chadburn, Sarah E., et al.
(author)
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Carbon stocks and fluxes in the high latitudes : using site-level data to evaluate Earth system models
- 2017
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In: Biogeosciences. - : Copernicus GmbH. - 1726-4170 .- 1726-4189. ; 14:22, s. 5143-5169
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Journal article (peer-reviewed)abstract
- It is important that climate models can accurately simulate the terrestrial carbon cycle in the Arctic due to the large and potentially labile carbon stocks found in permafrost-affected environments, which can lead to a positive climate feedback, along with the possibility of future carbon sinks from northward expansion of vegetation under climate warming. Here we evaluate the simulation of tundra carbon stocks and fluxes in three land surface schemes that each form part of major Earth system models (JSBACH, Germany; JULES, UK; ORCHIDEE, France). We use a site-level approach in which comprehensive, high-frequency datasets allow us to disentangle the importance of different processes. The models have improved physical permafrost processes and there is a reasonable correspondence between the simulated and measured physical variables, including soil temperature, soil moisture and snow. We show that if the models simulate the correct leaf area index (LAI), the standard C3 photosynthesis schemes produce the correct order of magnitude of carbon fluxes. Therefore, simulating the correct LAI is one of the first priorities. LAI depends quite strongly on climatic variables alone, as we see by the fact that the dynamic vegetation model can simulate most of the differences in LAI between sites, based almost entirely on climate inputs. However, we also identify an influence from nutrient limitation as the LAI becomes too large at some of the more nutrient-limited sites. We conclude that including moss as well as vascular plants is of primary importance to the carbon budget, as moss contributes a large fraction to the seasonal CO2 flux in nutrient-limited conditions. Moss photosynthetic activity can be strongly influenced by the moisture content of moss, and the carbon uptake can be significantly different from vascular plants with a similar LAI. The soil carbon stocks depend strongly on the rate of input of carbon from the vegetation to the soil, and our analysis suggests that an improved simulation of photosynthesis would also lead to an improved simulation of soil carbon stocks. However, the stocks are also influenced by soil carbon burial (e.g. through cryoturbation) and the rate of heterotrophic respiration, which depends on the soil physical state. More detailed below-ground measurements are needed to fully evaluate biological and physical soil processes. Furthermore, even if these processes are well modelled, the soil carbon profiles cannot resemble peat layers as peat accumulation processes are not represented in the models. Thus, we identify three priority areas for model development: (1) dynamic vegetation including (a) climate and (b) nutrient limitation effects; (2) adding moss as a plant functional type; and an (3) improved vertical profile of soil carbon including peat processes.
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13. |
- Chang, Kuang Yu, et al.
(author)
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Substantial hysteresis in emergent temperature sensitivity of global wetland CH4 emissions
- 2021
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In: Nature Communications. - : Springer Science and Business Media LLC. - 2041-1723. ; 12:1, s. 2266-2266
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Journal article (peer-reviewed)abstract
- Wetland methane (CH4) emissions ([Formula: see text]) are important in global carbon budgets and climate change assessments. Currently, [Formula: see text] projections rely on prescribed static temperature sensitivity that varies among biogeochemical models. Meta-analyses have proposed a consistent [Formula: see text] temperature dependence across spatial scales for use in models; however, site-level studies demonstrate that [Formula: see text] are often controlled by factors beyond temperature. Here, we evaluate the relationship between [Formula: see text] and temperature using observations from the FLUXNET-CH4 database. Measurements collected across the globe show substantial seasonal hysteresis between [Formula: see text] and temperature, suggesting larger [Formula: see text] sensitivity to temperature later in the frost-free season (about 77% of site-years). Results derived from a machine-learning model and several regression models highlight the importance of representing the large spatial and temporal variability within site-years and ecosystem types. Mechanistic advancements in biogeochemical model parameterization and detailed measurements in factors modulating CH4 production are thus needed to improve global CH4 budget assessments.
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15. |
- Christensen, Torben, et al.
(author)
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Trace gas exchange in a high-arctic valley 1. Variations in CO2 and CH4 flux between tundra vegetation types
- 2000
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In: Global Biogeochemical Cycles. - 0886-6236. ; 14:3, s. 701-714
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Journal article (peer-reviewed)abstract
- Ecosystem exchanges of CO2 and CH4 were studied by chamber techniques in five different vegetation types in a high arctic valley at Zackenberg, NE Greenland. The vegetation types were categorized as Cassiope heath, hummocky fen, continuous fen, grass land and Salix arctica snowbed. Integrated daytime fluxes for the different vegetation types of the valley showed that the fen areas and the grassland, were significant sources of CH4 with a mean efflux of 6.3 mg CH4 m(-2) h(-1) and sinks for CO2, with almost -170 mg CO2 m(-2) hr(-1). The heath and snowbed areas had much lower carbon sequestration rates of about -25 mg CO2 m(-2) hr(-1) and were also sinks for CH4. Methane emissions from the valley dominated in the hummocky fens. Computation of area integrated mean daytime flux values across all vegetation types of the entire valley bottom revealed that it was a sink of CO2 in the order of -96+/-33 mg CO2 m-2 hr-1 and a source of 1.9+/-0.7 m(-2) CH4 m(-2) hr(-1). These values were in accordance with eddy correlation measurements reported elsewhere in this issue and reflect a high-carbon exchange despite the high arctic location. In the fens, where the water table was at or above the soil surface, methane emissions increased with net ecosystem CO2 flux. In places with the water table below the soil surface, such as particularly in the hummocky parts of the fen, oxidation tended to become the dominant controlling factor on methane efflux.
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16. |
- Elberling, Bo, et al.
(author)
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Arctic vegetation damage by winter-generated coal mining pollution released upon thawing
- 2007
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In: Environmental Science and Technology. - : American Chemical Society (ACS). - 0013-936X .- 1520-5851. ; 41:7, s. 2407-2413
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Journal article (peer-reviewed)abstract
- Acid mine drainage (known as AMD) is a well-known environmental problem resulting from the oxidation of sulfidic mine waste. In cold regions, AMD is often considered limited by low temperatures most of the year and observed environmental impact is related to pollution generated during the warm summer period. Here we show that heat generation within an oxidizing, sulfidic, coal-mining waste-rock pile in Svalbard (78 degrees N) is high enough to keep the pile warm (roughly 5 degrees C throughout the year) despite mean annual air temperatures below -5 degrees C. Consequently, weathering processes continue year-round within the waste-rock pile. During the winter, weathering products accumulate within the pile because of a frozen outer layer on the pile and are released as a flush within 2 weeks of soil thawing in the spring. Consequently, spring runoff water contains elevated concentrations of metals. Several of these metals are taken up and accumulated in plants where they reach phytotoxic levels, including aluminum and manganese. Laboratory experiments document that uptake of Al and Mn in native plant species is highly correlated with dissolved concentrations. Therefore, future remedial actions to control the adverse environmental impacts of cold region coal-mining need to pay more attention to winter processes including AMD generation and accumulation of weathering products.
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19. |
- Jesper, Kristiansen, et al.
(author)
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The Danish version of the Karolinska Exhaustion Disorder Scale (KEDS)
- 2016
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Conference paper (peer-reviewed)abstract
- Jesper Kristiansen1, Maria Kristine Friborg1, Lars Brandt2, Nanna Eller3, David Glasscock4, Anders Daldorph Nielsen2, Roger Persson5, Aniella Besèr6, Marie Åsberg6
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23. |
- Knox, Sara H., et al.
(author)
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FLUXNET-CH4 Synthesis Activity : Objectives, Observations, and Future Directions
- 2019
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In: Bulletin of The American Meteorological Society - (BAMS). - 0003-0007 .- 1520-0477. ; 100:12, s. 2607-2632
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Journal article (peer-reviewed)abstract
- This paper describes the formation of, and initial results for, a new FLUXNET coordination network for ecosystem-scale methane (CH4) measurements at 60 sites globally, organized by the Global Carbon Project in partnership with other initiatives and regional flux tower networks. The objectives of the effort are presented along with an overview of the coverage of eddy covariance (EC) CH4 flux measurements globally, initial results comparing CH4 fluxes across the sites, and future research directions and needs. Annual estimates of net CH4 fluxes across sites ranged from -0.2 +/- 0.02 g C m(-2) yr(-1) for an upland forest site to 114.9 +/- 13.4 g C m(-2) yr(-1) for an estuarine freshwater marsh, with fluxes exceeding 40 g C m(-2) yr(-1) at multiple sites. Average annual soil and air temperatures were found to be the strongest predictor of annual CH4 flux across wetland sites globally. Water table position was positively correlated with annual CH4 emissions, although only for wetland sites that were not consistently inundated throughout the year. The ratio of annual CH4 fluxes to ecosystem respiration increased significantly with mean site temperature. Uncertainties in annual CH4 estimates due to gap-filling and random errors were on average +/- 1.6 g C m(-2) yr(-1) at 95% confidence, with the relative error decreasing exponentially with increasing flux magnitude across sites. Through the analysis and synthesis of a growing EC CH4 flux database, the controls on ecosystem CH4 fluxes can be better understood, used to inform and validate Earth system models, and reconcile differences between land surface model- and atmospheric-based estimates of CH4 emissions.
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24. |
- Peltola, Olli, et al.
(author)
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Monthly gridded data product of northern wetland methane emissions based on upscaling eddy covariance observations
- 2019
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In: Earth System Science Data. - : Copernicus GmbH. - 1866-3508 .- 1866-3516. ; 11:3, s. 1263-1289
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Journal article (peer-reviewed)abstract
- Natural wetlands constitute the largest and most uncertain source of methane (CH4) to the atmosphere and a large fraction of them are found in the northern latitudes. These emissions are typically estimated using process ("bottom-up") or inversion ("top-down") models. However, estimates from these two types of models are not independent of each other since the top-down estimates usually rely on the a priori estimation of these emissions obtained with process models. Hence, independent spatially explicit validation data are needed. Here we utilize a random forest (RF) machine-learning technique to upscale CH4 eddy covariance flux measurements from 25 sites to estimate CH4 wetland emissions from the northern latitudes (north of 45° N). Eddy covariance data from 2005 to 2016 are used for model development. The model is then used to predict emissions during 2013 and 2014. The predictive performance of the RF model is evaluated using a leave-one-site-out cross-validation scheme. The performance (Nash-Sutcliffe model efficiency D 0:47) is comparable to previous studies upscaling net ecosystem exchange of carbon dioxide and studies comparing process model output against site-level CH4 emission data. The global distribution of wetlands is one major source of uncertainty for upscaling CH4. Thus, three wetland distribution maps are utilized in the upscaling. Depending on the wetland distribution map, the annual emissions for the northern wetlands yield 32 (22.3-41.2, 95 % confidence interval calculated from a RF model ensemble), 31 (21.4-39.9) or 38 (25.9-49.5) Tg(CH4) yr-1. To further evaluate the uncertainties of the upscaled CH4 flux data products we also compared them against output from two process models (LPX-Bern and WetCHARTs), and methodological issues related to CH4 flux upscaling are discussed. The monthly upscaled CH4 flux data products are available at https://doi.org/10.5281/zenodo.2560163 (Peltola et al., 2019).
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25. |
- Wohlfahrt, Georg, et al.
(author)
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Biotic, Abiotic, and Management Controls on the Net Ecosystem CO2 Exchange of European Mountain Grassland Ecosystems
- 2008
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In: Ecosystems. - : Springer Science and Business Media LLC. - 1432-9840 .- 1435-0629. ; 11:8, s. 1338-1351
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Journal article (peer-reviewed)abstract
- was spring and autumn for the sites characterized by summer droughts (southern sites) and (peak) summer for the Alpine and northern study sites. This general pattern was interrupted by grassland management practices, that is, mowing and grazing, when the variability in NEE explained by PPFD decreased in concert with the amount of aboveground biomass (BMag). Temperature was the abiotic influence factor that explained most of the variability in ecosystem respiration at the Alpine and northern study sites, but not at the southern sites characterized by a pronouncedThe net ecosystem carbon dioxide (CO2) exchange (NEE) of nine European mountain grassland ecosystems was measured during 2002-2004 using the eddy covariance method. Overall, the availability of photosynthetically active radiation (PPFD) was the single most important abiotic influence factor for NEE. Its role changed markedly during the course of the season, PPFD being a better predictor for NEE during periods favorable for CO2 uptake, which summer drought, where soil water availability and the amount of aboveground biomass were more or equally important. The amount of assimilating plant area was the single most important biotic variable determining the maximum ecosystem carbon uptake potential, that is, the NEE at saturating PPFD. Good correspondence, in terms of the magnitude of NEE, was observed with many (semi-) natural grasslands around the world, but not with grasslands sown on fertile soils in lowland locations, which exhibited higher maximum carbon gains at lower respiratory costs. It is concluded that, through triggering rapid changes in the amount and area of the aboveground plant matter, the timing and frequency of land management practices is crucial for the short-term sensitivity of the NEE of the investigated mountain grassland ecosystems to climatic drivers.
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