1. |
- Franz, D, et al.
(author)
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Towards long-term standardised carbon and greenhouse gas observations for monitoring Europe´s terrestrial ecosystems: a review
- 2018
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In: International Agrophysics. - : Walter de Gruyter GmbH. - 0236-8722 .- 2300-8725. ; 32, s. 439-455
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Journal article (peer-reviewed)abstract
- 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.
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2. |
- 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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3. |
- Berner, Logan T., et al.
(author)
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The Arctic plant aboveground biomass synthesis dataset
- 2024
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In: Scientific Data. - : Springer Nature. - 2052-4463. ; 11:1
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Journal article (peer-reviewed)abstract
- Plant biomass is a fundamental ecosystem attribute that is sensitive to rapid climatic changes occurring in the Arctic. Nevertheless, measuring plant biomass in the Arctic is logistically challenging and resource intensive. Lack of accessible field data hinders efforts to understand the amount, composition, distribution, and changes in plant biomass in these northern ecosystems. Here, we present The Arctic plant aboveground biomass synthesis dataset, which includes field measurements of lichen, bryophyte, herb, shrub, and/or tree aboveground biomass (g m−2) on 2,327 sample plots from 636 field sites in seven countries. We created the synthesis dataset by assembling and harmonizing 32 individual datasets. Aboveground biomass was primarily quantified by harvesting sample plots during mid- to late-summer, though tree and often tall shrub biomass were quantified using surveys and allometric models. Each biomass measurement is associated with metadata including sample date, location, method, data source, and other information. This unique dataset can be leveraged to monitor, map, and model plant biomass across the rapidly warming Arctic.
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4. |
- Abdalla, M., et al.
(author)
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Simulation of CO2 and Attribution Analysis at Six European Peatland Sites Using the ECOSSE Model
- 2014
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In: Water, Air and Soil Pollution. - : Springer Science and Business Media LLC. - 1573-2932 .- 0049-6979. ; 225:11, s. 2182-2182
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Journal article (peer-reviewed)abstract
- In this study, we simulated heterotrophic CO2 (Rh) fluxes at six European peatland sites using the ECOSSE model and compared them to estimates of Rh made from eddy covariance (EC) measurements. The sites are spread over four countries with different climates, vegetation and management. Annual Rh from the different sites ranged from 110 to 540 g C m(-2). The maximum annual Rh occurred when the water table (WT) level was between -10 and -25 cm and the air temperature was above 6.2 degrees C. The model successfully simulated seasonal trends for the majority of the sites. Regression relationships (r(2)) between the EC-derived and simulated Rh ranged from 0.28 to 0.76, and the root mean square error and relative error were small, revealing an acceptable fit. The overall relative deviation value between annual EC-derived and simulated Rh was small (-1 %) and model efficiency ranges across sites from -0.25 to +0.41. Sensitivity analysis highlighted that increasing temperature, decreasing precipitation and lowering WT depth could significantly increase Rh from soils. Thus, management which lowers the WT could significantly increase anthropogenic CO2, so from a carbon emissions perspective, it should be avoided. The results presented here demonstrate a robust basis for further application of the ECOSSE model to assess the impacts of future land management interventions on peatland carbon emissions and to help guide best practice land management decisions.
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5. |
- Martínez, B., et al.
(author)
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Retrieval of daily gross primary production over Europe and Africa from an ensemble of SEVIRI/MSG products
- 2018
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In: International Journal of Applied Earth Observation and Geoinformation. - : Elsevier BV. - 1569-8432. ; 65, s. 124-136
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Journal article (peer-reviewed)abstract
- The main goal of this paper is to derive a method for a daily gross primary production (GPP) product over Europe and Africa taking the full advantage of the SEVIRI/MSG satellite products from the European Organization for the Exploitation of Meteorological Satellites (EUMETSAT) sensors delivered from the Satellite Application Facility for Land Surface Analysis (LSA SAF) system. Special attention is paid to model the daily GPP response from an optimized Montheith's light use efficiency model under dry conditions by controlling water shortage limitations from the actual evapotranspiration and the potential evapotranspiration (PET). The PET was parameterized using the mean daily air temperature at 2 m (Ta) from ERA-Interim data. The GPP product (MSG GPP) was produced for 2012 and assessed by direct site-level comparison with GPP from eddy covariance data (EC GPP). MSG GPP presents relative bias errors lower than 40% for the most forest vegetation types with a high agreement (r > 0.7) when compared with EC GPP. For drylands, MSG GPP reproduces the seasonal variations related to water limitation in a good agreement with site level GPP estimates (RMSE = 2.11 g m−2 day−1; MBE = −0.63 g m−2 day−1), especially for the dry season. A consistency analysis against other GPP satellite products (MOD17A2 and FLUXCOM) reveals a high consistency among products (RMSD < 1.5 g m−2 day−1) over Europe, North and South Africa. The major GPP disagreement arises over moist biomes in central Africa (RMSD > 3.0 g m−2 day−1) and over dry biomes with MSG GPP estimates lower than FLUXCOM (MBD up to −3.0 g m−2 day−1). This newly derived product has the potential for analysing spatial patterns and temporal dynamics of GPP at the MSG spatial resolutions on a daily basis allowing to better capture the GPP dynamics and magnitude.
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6. |
- Mbufong, H. N., et al.
(author)
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Assessing the spatial variability in peak season CO2 exchange characteristics across the Arctic tundra using a light response curve parameterization
- 2014
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In: Biogeosciences. - : Copernicus GmbH. - 1726-4189. ; 11:17, s. 4897-4912
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Journal article (peer-reviewed)abstract
- This paper aims to assess the spatial variability in the response of CO2 exchange to irradiance across the Arctic tundra during peak season using light response curve (LRC) parameters. This investigation allows us to better understand the future response of Arctic tundra under climatic change. Peak season data were collected during different years (between 1998 and 2010) using the micrometeorological eddy covariance technique from 12 circumpolar Arctic tundra sites, in the range of 64-74 degrees N. The LRCs were generated for 14 days with peak net ecosystem exchange (NEE) using an NEE-irradiance model. Parameters from LRCs represent site-specific traits and characteristics describing the following: (a) NEE at light saturation (F-csat), (b) dark respiration (Rd), (c) light use efficiency (alpha), (d) NEE when light is at 1000 mu molm(-2) s(-1) (F-c1000), (e) potential photosynthesis at light saturation (P-sat) and (f) the light compensation point (LCP). Parameterization of LRCs was successful in predicting CO2 flux dynamics across the Arctic tundra. We did not find any trends in LRC parameters across the whole Arctic tundra but there were indications for temperature and latitudinal differences within sub-regions like Russia and Greenland. Together, leaf area index (LAI) and July temperature had a high explanatory power of the variance in assimilation parameters (F-csat, F-c1000 and P-sat), thus illustrating the potential for upscaling CO2 exchange for the whole Arctic tundra. Dark respiration was more variable and less correlated to environmental drivers than were assimilation parameters. This indicates the inherent need to include other parameters such as nutrient availability, substrate quantity and quality in flux monitoring activities.
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7. |
- Sarneel, Judith M., et al.
(author)
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Reading tea leaves worldwide: Decoupled drivers of initial litter decomposition mass-loss rate and stabilization
- 2024
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In: ECOLOGY LETTERS. - : John Wiley & Sons. - 1461-023X .- 1461-0248. ; 27:5
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Journal article (peer-reviewed)abstract
- The breakdown of plant material fuels soil functioning and biodiversity. Currently, process understanding of global decomposition patterns and the drivers of such patterns are hampered by the lack of coherent large-scale datasets. We buried 36,000 individual litterbags (tea bags) worldwide and found an overall negative correlation between initial mass-loss rates and stabilization factors of plant-derived carbon, using the Tea Bag Index (TBI). The stabilization factor quantifies the degree to which easy-to-degrade components accumulate during early-stage decomposition (e.g. by environmental limitations). However, agriculture and an interaction between moisture and temperature led to a decoupling between initial mass-loss rates and stabilization, notably in colder locations. Using TBI improved mass-loss estimates of natural litter compared to models that ignored stabilization. Ignoring the transformation of dead plant material to more recalcitrant substances during early-stage decomposition, and the environmental control of this transformation, could overestimate carbon losses during early decomposition in carbon cycle models.
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8. |
- Duursma, R. A., et al.
(author)
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Contributions of climate, leaf area index and leaf physiology to variation in gross primary production of six coniferous forests across Europe: a model-based analysis
- 2009
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In: Tree Physiology. - : Oxford University Press (OUP). - 1758-4469 .- 0829-318X. ; 29:5, s. 621-639
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Journal article (peer-reviewed)abstract
- Gross primary production (GPP) is the primary source of all carbon fluxes in the ecosystem. Understanding, variation in this flux is vital to understanding variation in the carbon sink of forest ecosystems, and this would serve as input to forest production models. Using GPP derived from eddy-covariance (EC) Measurements, it is now possible to determine the most important factor to scale GPP across sites. We use long-term EC measurements for six coniferous forest stands in Europe, for a total of 25 site-years, located oil a gradient between Southern France and northern Finland. Eddy-derived GPP varied threefold across the six sites, peak ecosystem leaf area index (LAI) (all-sided) varied from 4 to 22 m(2) m(-2) and mean annual temperature varied from - 1 to 13 degrees C. A process-based model operating at a half-hourly time-step was parameterized with available information for each site, and explained 71-96% in variation between daily totals of GPP within site-years and 62% of annual total GPP across site-years. Using the parameterized model, we performed two simulation experiments: weather datasets were interchanged between sites, so that the model was used to predict GPP at some site using data from either a different year or a different site. The resulting bias in GPP prediction was related to several aggregated weather variables and was found to be closely related to the change in the effective temperature sum or mean annual temperature. High R(2)s resulted even when using weather datasets from unrelated sites, providing a cautionary note on the interpretation of R-2 ill model comparisons. A second experiment interchanged stand-structure information between sites. and the resulting bias was strongly related to the difference in LAI, or the difference in integrated absorbed light. Across the six sites. variation in mean annual temperature had more effect on simulated GPP than the variation in LAI. but both were important determinants of GPP. A sensitivity analysis of leaf physiology parameters showed that the quantum yield was the most influential parameter on annual GPP, followed by a parameter controlling the seasonality of photosynthesis and photosynthetic capacity. Overall, the results are promising for the development of a parsimonious model of GPP.
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9. |
- Helbig, M., et al.
(author)
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Warming response of peatland CO2 sink is sensitive to seasonality in warming trends
- 2022
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In: Nature Climate Change. - : Springer Science and Business Media LLC. - 1758-6798 .- 1758-678X. ; 12:8, s. 743-749
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Journal article (peer-reviewed)abstract
- Peatlands have acted as net CO2 sinks over millennia, exerting a global climate cooling effect. Rapid warming at northern latitudes, where peatlands are abundant, can disturb their CO2 sink function. Here we show that sensitivity of peatland net CO2 exchange to warming changes in sign and magnitude across seasons, resulting in complex net CO2 sink responses. We use multiannual net CO2 exchange observations from 20 northern peatlands to show that warmer early summers are linked to increased net CO2 uptake, while warmer late summers lead to decreased net CO2 uptake. Thus, net CO2 sinks of peatlands in regions experiencing early summer warming, such as central Siberia, are more likely to persist under warmer climate conditions than are those in other regions. Our results will be useful to improve the design of future warming experiments and to better interpret large-scale trends in peatland net CO2 uptake over the coming few decades.
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10. |
- Nemitz, E, et al.
(author)
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Standardisation of eddy-covariance flux measurements of methane and nitrous oxide
- 2018
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In: International Agrophysics. - : Walter de Gruyter GmbH. - 0236-8722 .- 2300-8725. ; 32, s. 517-549
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Journal article (peer-reviewed)abstract
- Commercially available fast-response analysers for methane (CH4) and nitrous oxide (N2O) have recently become more sensitive, more robust and easier to operate. This has made their application for long-term flux measurements with the eddycovariance method more feasible. Unlike for carbon dioxide (CO2) and water vapour (H2O), there have so far been no guidelines on how to optimise and standardise the measurements. This paper reviews the state-of-the-art of the various steps of the measurements and discusses aspects such as instrument selection, setup and maintenance, data processing as well as the additional measurements needed to aid interpretation and gap-filling. It presents the methodological protocol for eddy covariance measurements of CH4 and N2O fluxes as agreed for the ecosystem station network of the pan-European Research Infrastructure Integrated Carbon Observation System and provides a first international standard that is suggested to be adopted more widely. Fluxes can be episodic and the processes controlling the fluxes are complex, preventing simple mechanistic gap-filling strategies. Fluxes are often near or below the detection limit, requiring additional care during data processing. The protocol sets out the best practice for these conditions to avoid biasing the results and long-term budgets. It summarises the current approach to gap-filling.
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