| 1. |
- Kattge, Jens, et al.
(författare)
-
TRY plant trait database - enhanced coverage and open access
- 2020
-
Ingår i: Global Change Biology. - : Wiley-Blackwell. - 1354-1013 .- 1365-2486. ; 26:1, s. 119-188
-
Tidskriftsartikel (refereegranskat)abstract
- Plant traits-the morphological, anatomical, physiological, biochemical and phenological characteristics of plants-determine how plants respond to environmental factors, affect other trophic levels, and influence ecosystem properties and their benefits and detriments to people. Plant trait data thus represent the basis for a vast area of research spanning from evolutionary biology, community and functional ecology, to biodiversity conservation, ecosystem and landscape management, restoration, biogeography and earth system modelling. Since its foundation in 2007, the TRY database of plant traits has grown continuously. It now provides unprecedented data coverage under an open access data policy and is the main plant trait database used by the research community worldwide. Increasingly, the TRY database also supports new frontiers of trait-based plant research, including the identification of data gaps and the subsequent mobilization or measurement of new data. To support this development, in this article we evaluate the extent of the trait data compiled in TRY and analyse emerging patterns of data coverage and representativeness. Best species coverage is achieved for categorical traits-almost complete coverage for 'plant growth form'. However, most traits relevant for ecology and vegetation modelling are characterized by continuous intraspecific variation and trait-environmental relationships. These traits have to be measured on individual plants in their respective environment. Despite unprecedented data coverage, we observe a humbling lack of completeness and representativeness of these continuous traits in many aspects. We, therefore, conclude that reducing data gaps and biases in the TRY database remains a key challenge and requires a coordinated approach to data mobilization and trait measurements. This can only be achieved in collaboration with other initiatives.
|
|
| 2. |
- Flannick, Jason, et al.
(författare)
-
Data Descriptor : Sequence data and association statistics from 12,940 type 2 diabetes cases and controls
- 2017
-
Ingår i: Scientific Data. - : Springer Science and Business Media LLC. - 2052-4463. ; 4
-
Tidskriftsartikel (refereegranskat)abstract
- To investigate the genetic basis of type 2 diabetes (T2D) to high resolution, the GoT2D and T2D-GENES consortia catalogued variation from whole-genome sequencing of 2,657 European individuals and exome sequencing of 12,940 individuals of multiple ancestries. Over 27M SNPs, indels, and structural variants were identified, including 99% of low-frequency (minor allele frequency [MAF] 0.1-5%) non-coding variants in the whole-genome sequenced individuals and 99.7% of low-frequency coding variants in the whole-exome sequenced individuals. Each variant was tested for association with T2D in the sequenced individuals, and, to increase power, most were tested in larger numbers of individuals (> 80% of low-frequency coding variants in similar to ~82 K Europeans via the exome chip, and similar to ~90% of low-frequency non-coding variants in similar to ~44 K Europeans via genotype imputation). The variants, genotypes, and association statistics from these analyses provide the largest reference to date of human genetic information relevant to T2D, for use in activities such as T2D-focused genotype imputation, functional characterization of variants or genes, and other novel analyses to detect associations between sequence variation and T2D.
|
|
| 3. |
- Kaiser, Sonja, et al.
(författare)
-
Process-based modelling of the methane balance in periglacial landscapes (JSBACH-methane)
- 2017
-
Ingår i: Geoscientific Model Development. - : Copernicus GmbH. - 1991-959X .- 1991-9603. ; 10:1, s. 333-358
-
Tidskriftsartikel (refereegranskat)abstract
- A detailed process-based methane module for a global land surface scheme has been developed which is general enough to be applied in permafrost regions as well as wetlands outside permafrost areas. Methane production, oxidation and transport by ebullition, diffusion and plants are represented. In this model, oxygen has been explicitly incorporated into diffusion, transport by plants and two oxidation processes, of which one uses soil oxygen, while the other uses oxygen that is available via roots. Permafrost and wetland soils show special behaviour, such as variable soil pore space due to freezing and thawing or water table depths due to changing soil water content. This has been integrated directly into the methane-related processes. A detailed application at the Samoylov polygonal tundra site, Lena River Delta, Russia, is used for evaluation purposes. The application at Samoylov also shows differences in the importance of the several transport processes and in the methane dynamics under varying soil moisture, ice and temperature conditions during different seasons and on different microsites. These microsites are the elevated moist polygonal rim and the depressed wet polygonal centre. The evaluation shows sufficiently good agreement with field observations despite the fact that the module has not been specifically calibrated to these data. This methane module is designed such that the advanced land surface scheme is able to model recent and future methane fluxes from periglacial landscapes across scales. In addition, the methane contribution to carbon cycle-climate feedback mechanisms can be quantified when running coupled to an atmospheric model.
|
|
| 4. |
- Beer, Christian, et al.
(författare)
-
Terrestrial Gross Carbon Dioxide Uptake: Global Distribution and Covariation with Climate
- 2010
-
Ingår i: Science. - : American Association for the Advancement of Science (AAAS). - 1095-9203 .- 0036-8075. ; 329:5993, s. 834-838
-
Tidskriftsartikel (refereegranskat)abstract
- Terrestrial gross primary production (GPP) is the largest global CO2 flux driving several ecosystem functions. We provide an observation-based estimate of this flux at 123 +/- 8 petagrams of carbon per year (Pg C year(-1)) using eddy covariance flux data and various diagnostic models. Tropical forests and savannahs account for 60%. GPP over 40% of the vegetated land is associated with precipitation. State-of-the-art process-oriented biosphere models used for climate predictions exhibit a large between-model variation of GPP's latitudinal patterns and show higher spatial correlations between GPP and precipitation, suggesting the existence of missing processes or feedback mechanisms which attenuate the vegetation response to climate. Our estimates of spatially distributed GPP and its covariation with climate can help improve coupled climate-carbon cycle process models.
|
|
| 5. |
- Beer, Christian, et al.
(författare)
-
Vertical pattern of organic matter decomposability in cryoturbated permafrost-affected soils
- 2022
-
Ingår i: Environmental Research Letters. - : IOP Publishing. - 1748-9326. ; 17:10
-
Tidskriftsartikel (refereegranskat)abstract
- Permafrost thaw will release additional carbon dioxide into the atmosphere resulting in a positive feedback to climate change. However, the mineralization dynamics of organic matter (OM) stored in permafrost-affected soils remain unclear. We used physical soil fractionation, radiocarbon measurements, incubation experiments, and a dynamic decomposition model to identify distinct vertical pattern in OM decomposability. The observed differences reflect the type of OM input to the subsoil, either by cryoturbation or otherwise, e.g. by advective water-borne transport of dissolved OM. In non-cryoturbated subsoil horizons, most OM is stabilized at mineral surfaces or by occlusion in aggregates. In contrast, pockets of OM-rich cryoturbated soil contain sufficient free particulate OM for microbial decomposition. After thaw, OM turnover is as fast as in the upper active layer. Since cryoturbated soils store ca. 450 Pg carbon, identifying differences in decomposability according to such translocation processes has large implications for the future global carbon cycle and climate, and directs further process model development.
|
|
| 6. |
- Guanter, Luis, et al.
(författare)
-
Global and time-resolved monitoring of crop photosynthesis with chlorophyll fluorescence
- 2014
-
Ingår i: Proceedings of the National Academy of Sciences of the United States of America. - : Proceedings of the National Academy of Sciences. - 0027-8424 .- 1091-6490. ; 111:14, s. E1327-E1333
-
Tidskriftsartikel (refereegranskat)abstract
- Photosynthesis is the process by which plants harvest sunlight to produce sugars from carbon dioxide and water. It is the primary source of energy for all life on Earth; hence it is important to understand how this process responds to climate change and human impact. However, model-based estimates of gross primary production (GPP, output from photosynthesis) are highly uncertain, in particular over heavily managed agricultural areas. Recent advances in spectroscopy enable the space-based monitoring of sun-induced chlorophyll fluorescence (SIF) from terrestrial plants. Here we demonstrate that spaceborne SIF retrievals provide a direct measure of the GPP of cropland and grassland ecosystems. Such a strong link with crop photosynthesis is not evident for traditional remotely sensed vegetation indices, nor for more complex carbon cycle models. We use SIF observations to provide a global perspective on agricultural productivity. Our SIF-based crop GPP estimates are 50-75% higher than results from state-of-the-art carbon cycle models over, for example, the US Corn Belt and the Indo-Gangetic Plain, implying that current models severely underestimate the role of management. Our results indicate that SIF data can help us improve our global models for more accurate projections of agricultural productivity and climate impact on crop yields. Extension of our approach to other ecosystems, along with increased observational capabilities for SIF in the near future, holds the prospect of reducing uncertainties in the modeling of the current and future carbon cycle.
|
|
| 7. |
- Knoblauch, Christian, et al.
(författare)
-
Methane production as key to the greenhouse gas budget of thawing permafrost
- 2018
-
Ingår i: Nature Climate Change. - : Springer Science and Business Media LLC. - 1758-678X .- 1758-6798. ; 8:4, s. 309-312
-
Tidskriftsartikel (refereegranskat)abstract
- Permafrost thaw liberates frozen organic carbon, which is decomposed into carbon dioxide (CO2) and methane (CH4). The release of these greenhouse gases (GHGs) forms a positive feedback to atmospheric CO2 and CH4 concentrations and accelerates climate change(1,2). Current studies report a minor importance of CH4 production in water-saturated (anoxic) permafrost soils(3-6) and a stronger permafrost carbon-climate feedback from drained (oxic) soils(1,7). Here we show through seven-year laboratory incubations that equal amounts of CO2 and CH4 are formed in thawing permafrost under anoxic conditions after stable CH4-producing microbial communities have established. Less permafrost carbon was mineralized under anoxic conditions but more CO2-carbon equivalents (CO2Ce) were formed than under oxic conditions when the higher global warming potential (GWP) of CH4 is taken into account(8). A model of organic carbon decomposition, calibrated with the observed decomposition data, predicts a higher loss of permafrost carbon under oxic conditions (113 +/- 58 g CO2-C kgC(-1) (kgC, kilograms of carbon)) by 2100, but a twice as high production of CO2-Ce (241 +/- 138 g CO2-Ce kgC(-1)) under anoxic conditions. These findings challenge the view of a stronger permafrost carbon-climate feedback from drained soils1,7 and emphasize the importance of CH4 production in thawing permafrost on climate-relevant timescales.
|
|
| 8. |
|
|
| 9. |
- von Deimling, Thomas Schneider, et al.
(författare)
-
Long-term deglacial permafrost carbon dynamics in MPI-ESM
- 2018
-
Ingår i: Climate of the Past. - : Copernicus GmbH. - 1814-9324 .- 1814-9332. ; 14:12, s. 2011-2036
-
Tidskriftsartikel (refereegranskat)abstract
- We have developed a new module to calculate soil organic carbon (SOC) accumulation in perennially frozen ground in the land surface model JSBACH. Running this offline version of MPI-ESM we have modelled long-term permafrost carbon accumulation and release from the Last Glacial Maximum (LGM) to the pre-industrial (PI) age. Our simulated near-surface PI permafrost extent of 16.9 x 10(6) km(2) is close to observational estimates. Glacial boundary conditions, especially ice sheet coverage, result in profoundly different spatial patterns of glacial permafrost extent. Deglacial warming leads to large-scale changes in soil temperatures, manifested in permafrost disappearance in southerly regions, and permafrost aggregation in formerly glaciated grid cells. In contrast to the large spatial shift in simulated permafrost occurrence, we infer an only moderate increase in total LGM permafrost area (18.3 x 10(6) km(2)) - together with pronounced changes in the depth of seasonal thaw. Earlier empirical reconstructions suggest a larger spread of permafrost towards more southerly regions under glacial conditions, but with a highly uncertain extent of non-continuous permafrost. Compared to a control simulation without describing the transport of SOC into perennially frozen ground, the implementation of our newly developed module for simulating permafrost SOC accumulation leads to a doubling of simulated LGM permafrost SOC storage (amounting to a total of similar to 150 PgC). Despite LGM temperatures favouring a larger permafrost extent, simulated cold glacial temperatures - together with low precipitation and low CO2 levels - limit vegetation productivity and therefore prevent a larger glacial SOC build-up in our model. Changes in physical and biogeochemical boundary conditions during deglacial warming lead to an increase in mineral SOC storage towards the Holocene (168 PgC at PI), which is below observational estimates (575 PgC in continuous and discontinuous permafrost). Additional model experiments clarified the sensitivity of simulated SOC storage to model parameters, affecting long-term soil carbon respiration rates and simulated ALDs. Rather than a steady increase in carbon release from the LGM to PI as a consequence of deglacial permafrost degradation, our results suggest alternating phases of soil carbon accumulation and loss as an effect of dynamic changes in permafrost extent, ALDs, soil litter input, and heterotrophic respiration.
|
|
| 10. |
|
|
| 11. |
|
|
| 12. |
|
|
| 13. |
- Ammanath, Aparna Viswanathan, et al.
(författare)
-
From an Hsp90 - binding protein to a peptide drug.
- 2022
-
Ingår i: microLife. - : Oxford University Press (OUP). - 2633-6693. ; 4
-
Tidskriftsartikel (refereegranskat)abstract
- The Lpl proteins represent a class of lipoproteins that was first described in the opportunistic bacterial pathogen Staphylococcus aureus, where they contribute to pathogenicity by enhancing F-actin levels of host epithelial cells and thereby increasing S. aureus internalization. The model Lpl protein, Lpl1 was shown to interact with the human heat shock proteins Hsp90α and Hsp90ß, suggesting that this interaction may trigger all observed activities. Here we synthesized Lpl1-derived peptides of different lengths and identified two overlapping peptides, namely, L13 and L15, which interacted with Hsp90α. Unlike Lpl1, the two peptides not only decreased F-actin levels and S. aureus internalization in epithelial cells but they also decreased phagocytosis by human CD14+ monocytes. The well-known Hsp90 inhibitor, geldanamycin, showed a similar effect. The peptides not only interacted directly with Hsp90α, but also with the mother protein Lpl1. While L15 and L13 significantly decreased lethality of S. aureus bacteremia in an insect model, geldanamycin did not. In a mouse bacteremia model L15 was found to significantly decreased weight loss and lethality. Although the molecular bases of the L15 effect is still elusive, in vitro data indicate that simultaneous treatment of host immune cells with L15 or L13 and S. aureus significantly increase IL-6 production. L15 and L13 represent not antibiotics but they cause a significant reduction in virulence of multidrug-resistant S. aureus strains in in vivo models. In this capacity, they can be an important drug alone or additive with other agents.
|
|
| 14. |
- Anav, Alessandro, et al.
(författare)
-
Spatiotemporal patterns of terrestrial gross primary production : A review
- 2015
-
Ingår i: Reviews of geophysics. - 8755-1209 .- 1944-9208. ; 53:3, s. 785-818
-
Forskningsöversikt (refereegranskat)abstract
- Great advances have been made in the last decade in quantifying and understanding the spatiotemporal patterns of terrestrial gross primary production (GPP) with ground, atmospheric, and space observations. However, although global GPP estimates exist, each data set relies upon assumptions and none of the available data are based only on measurements. Consequently, there is no consensus on the global total GPP and large uncertainties exist in its benchmarking. The objective of this review is to assess how the different available data sets predict the spatiotemporal patterns of GPP, identify the differences among data sets, and highlight the main advantages/disadvantages of each data set. We compare GPP estimates for the historical period (1990-2009) from two observation-based data sets (Model Tree Ensemble and Moderate Resolution Imaging Spectroradiometer) to coupled carbon-climate models and terrestrial carbon cycle models from the Fifth Climate Model Intercomparison Project and TRENDY projects and to a new hybrid data set (CARBONES). Results show a large range in the mean global GPP estimates. The different data sets broadly agree on GPP seasonal cycle in terms of phasing, while there is still discrepancy on the amplitude. For interannual variability (IAV) and trends, there is a clear separation between the observation-based data that show little IAV and trend, while the process-based models have large GPP variability and significant trends. These results suggest that there is an urgent need to improve observation-based data sets and develop carbon cycle modeling with processes that are currently treated either very simplistically to correctly estimate present GPP and better quantify the future uptake of carbon dioxide by the world's vegetation.
|
|
| 15. |
- Barredo, José I., et al.
(författare)
-
Mapping and assessment of forest ecosystems and their services : Applications and guidance for decision making in the framework of MAES
- 2015
-
Rapport (övrigt vetenskapligt/konstnärligt)abstract
- The aim of this report is to illustrate by means of a series of case studies the implementation of mapping and assessment of forest ecosystem services in different contexts and geographical levels. Methodological aspects, data issues, approaches, limitations, gaps and further steps for improvement are analysed for providing good practices and decision making guidance. The EU initiative on Mappingand Assessment of Ecosystems and their Services (MAES), with the support of all Member States, contributes to improve the knowledge on ecosystem services. MAES is one of the building-block initiatives supporting the EU Biodiversity Strategy to 2020.
|
|
| 16. |
- Bayer, Tina K., et al.
(författare)
-
Future Carbon Emission From Boreal and Permafrost Lakes Are Sensitive to Catchment Organic Carbon Loads
- 2019
-
Ingår i: Journal of Geophysical Research - Biogeosciences. - 2169-8953 .- 2169-8961. ; 124:7, s. 1827-1848
-
Tidskriftsartikel (refereegranskat)abstract
- Carbon storage, processing, and transport in freshwater systems are important components of the global carbon cycle and sensitive to global change. However, in large-scale modeling this part of the boundless carbon cycle is often lacking or represented in a very simplified way. A new process-oriented lake biogeochemical model is used for investigating impacts of changes in atmospheric CO2 concentrations and organic carbon loading from the catchment on future greenhouse gas emissions from lakes across two boreal to subarctic regions (Northern Sweden and Alaska). Aquatic processes represented include carbon, oxygen, phytoplankton, and nutrient dynamics leading to CO2 and CH4 exchanges with the atmosphere. The model is running inside a macroscale hydrological model and may be easily implemented into a land surface scheme. Model evaluation demonstrates the validity in terms of average concentration of nutrients, algal biomass, and organic and inorganic carbon. Cumulative annual emissions of CH4 and CO2, as well as pathways of CH4 emissions, also compare well to observations. Model calculations imply that lake emissions of CH4 may increase by up to 45% under the Representative Concentration Pathway 8.5 scenario until 2100, and CO2 emissions may increase by up to 80% in Alaska. Increasing organic carbon loading to the lakes resulted in a linear response in CO2 and CH4 emissions across both regions, but increases in CO2 emissions from subarctic lakes in Sweden were lower than for southern boreal lakes, probably due to the higher importance of imported vegetation-generated inorganic carbon for CO2 emission from subarctic lakes.
|
|
| 17. |
- Beer, Christian, et al.
(författare)
-
Effects of short-term variability of meteorological variables on soil temperature in permafrost regions
- 2018
-
Ingår i: The Cryosphere. - : Copernicus GmbH. - 1994-0416 .- 1994-0424. ; 12:2, s. 741-757
-
Tidskriftsartikel (refereegranskat)abstract
- Effects of the short-term temporal variability of meteorological variables on soil temperature in northern high-latitude regions have been investigated. For this, a process-oriented land surface model has been driven using an artificially manipulated climate dataset. Short-term climate variability mainly impacts snow depth, and the thermal diffusivity of lichens and bryophytes. These impacts of climate variability on insulating surface layers together substantially alter the heat exchange between atmosphere and soil. As a result, soil temperature is 0.1 to 0.8 degrees C higher when climate variability is reduced. Earth system models project warming of the Arctic region but also increasing variability of meteorological variables and more often extreme meteorological events. Therefore, our results show that projected future increases in permafrost temperature and active-layer thickness in response to climate change will be lower (i) when taking into account future changes in short-term variability of meteorological variables and (ii) when representing dynamic snow and lichen and bryophyte functions in land surface models.
|
|
| 18. |
- Beer, Christian, et al.
(författare)
-
Harmonized European Long-Term Climate Data for Assessing the Effect of Changing Temporal Variability on Land-Atmosphere CO2 Fluxes
- 2014
-
Ingår i: Journal of Climate. - 0894-8755 .- 1520-0442. ; 27:13, s. 4815-4834
-
Tidskriftsartikel (refereegranskat)abstract
- Temporal variability of meteorological variables and extreme weather events is projected to increase in many regions of the world during the next century. Artificial experiments using process-oriented terrestrial ecosystem models make it possible to isolate effects of temporal variability from effects of gradual climate change on terrestrial ecosystem functions and the system state. Such factorial experiments require two long-term climate datasets: 1) a control dataset that represents observed and projected climate and 2) a dataset with the same long-term mean as the control dataset but with altered short-term variability. Using a bias correction method, various climate datasets spanning different periods are harmonized and then combined with the control dataset with consistent time series for Europe during 1901-2100. Then, parameters of a distribution transformation function are estimated for individual meteorological variables to derive the second climate dataset, which has similar long-term means but reduced temporal variability. The transformation conserves the number of rainy days within a month and the shape of the daily meteorological data distributions, which is important to ensure that, for example, drought duration does not modify the suitability of localized vegetation type to precipitation regimes. The median absolute difference between daily data of both datasets is 5% to 20%. On average, decadal extreme values are reduced by 2% to 35%. Driving a terrestrial ecosystem model with both climate datasets shows a general higher gross primary production under reduced temporal climate variability. This effect of climate variability on productivity demonstrates the potential of the climate datasets for studying various effects of temporal variability on ecosystem state and functions over large domains.
|
|
| 19. |
- Beer, Christian
(författare)
-
Permafrost Sub-grid Heterogeneity of Soil Properties Key for 3-D Soil Processes and Future Climate Projections
- 2016
-
Ingår i: Frontiers in Earth Science. - : Frontiers Media SA. - 2296-6463. ; 4
-
Tidskriftsartikel (refereegranskat)abstract
- There are massive carbon stocks stored in permafrost-affected soils due to the 3-D soil movement process called cryoturbation. For a reliable projection of the past, recent and future Arctic carbon balance, and hence climate, a reliable concept for representing cryoturbation in a land surface model (LSM) is required. The basis of the underlying transport processes is pedon-scale heterogeneity of soil hydrological and thermal properties as well as insulating layers, such as snow and vegetation. Today we still lack a concept of how to reliably represent pedon-scale properties and processes in a LSM. One possibility could be a statistical approach. This perspective paper demonstrates the importance of sub-grid heterogeneity in permafrost soils as a pre-requisite to implement any lateral transport parametrization. Representing such heterogeneity at the sub-pixel size of a LSM is the next logical step of model advancements. As a result of a theoretical experiment, heterogeneity of thermal and hydrological soil properties alone lead to a remarkable initial sub-grid range of subsoil temperature of 2C, and active-layer thickness of 150 cm in East Siberia. These results show the way forward in representing combined lateral and vertical transport of water and soil in LSMs.
|
|
| 20. |
- Beer, Christian, et al.
(författare)
-
Protection of Permafrost Soils from Thawing by Increasing Herbivore Density
- 2020
-
Ingår i: Scientific Reports. - : Nature Publishing Group. - 2045-2322. ; 10:1
-
Tidskriftsartikel (refereegranskat)abstract
- Climate change will cause a substantial future greenhouse gas release from warming and thawing permafrost-affected soils to the atmosphere enabling a positive feedback mechanism. Increasing the population density of big herbivores in northern high-latitude ecosystems will increase snow density and hence decrease the insulation strength of snow during winter. As a consequence, theoretically 80% of current permafrost-affected soils (<10 m) is projected to remain until 2100 even when assuming a strong warming using the Representative Concentration Pathway 8.5. Importantly, permafrost temperature is estimated to remain below -4C on average after increasing herbivore population density. Such ecosystem management practices would be therefore theoretically an important additional climate change mitigation strategy. Our results also highlight the importance of new field experiments and observations, and the integration of fauna dynamics into complex Earth System models, in order to reliably project future ecosystem functions and climate.
|
|
| 21. |
- Braakhekke, Maarten C., et al.
(författare)
-
The use of radiocarbon to constrain current and future soil organic matter turnover and transport in a temperate forest
- 2014
-
Ingår i: Journal of Geophysical Research: Biogeosciences. - 2169-8953. ; 119:3, s. 372-391
-
Tidskriftsartikel (refereegranskat)abstract
- We investigated the merits of radiocarbon measurements for estimating soil organic matter (SOM) turnover and vertical transport for a temperate deciduous forest in Germany. Eleven parameters, defining decomposition and transport in the soil carbon model SOMPROF, were estimated using a Bayesian approach based on organic carbon measurements and radiocarbon concentration of SOM and heterotrophic respiration. The addition of radiocarbon data had strong effects on the parameters, most importantly a reduction of the decomposition and production rate of the slowest SOM pool by an order of magnitude, and a similar reduction in advective SOM transport. The modified parameters further led to changes in the partitioning of SOM over the different model pools. The calibration results were subsequently used to perform transient soil carbon projections for the period 1901-2100. These simulations were run with parameter sets from calibrations both with and without radiocarbon. The results show an increase over time of topsoil carbon and a decrease in the subsoil, adding to a net gain overall. Near the end of the 21st century, total carbon stocks stabilize andfor the radiocarbon-constrained modelstart to decrease. However, the changes are small compared to the total stocks. The model results for the calibrations with and without radiocarbon are in general quite similar, but the latter shows notably higher heterotrophic respiration fluxes. Constraining the model with radiocarbon yielded only a small reduction of uncertainty for the total carbon stocks, while for the individual depth compartments, the uncertainty wasincreased. Key Points SOM turnover and transport was estimated using Bayesian calibration Radiocarbon data strongly improved constraint of turnover rate of slow pool Predictive simulation showed small increase of soil C stocks in 21st century
|
|
| 22. |
- Buddenkotte, Thomas, et al.
(författare)
-
Deep learning-based segmentation of multisite disease in ovarian cancer
- 2023
-
Ingår i: EUROPEAN RADIOLOGY EXPERIMENTAL. - : Springer Nature. - 2509-9280. ; 7:1
-
Tidskriftsartikel (refereegranskat)abstract
- Purpose: To determine if pelvic/ovarian and omental lesions of ovarian cancer can be reliably segmented on computed tomography (CT) using fully automated deep learning-based methods.Methods: A deep learning model for the two most common disease sites of high-grade serous ovarian cancer lesions (pelvis/ovaries and omentum) was developed and compared against the well-established “no-new-Net” framework and unrevised trainee radiologist segmentations. A total of 451 CT scans collected from four different institutions were used for training (n = 276), evaluation (n = 104) and testing (n = 71) of the methods. The performance was evaluated using the Dice similarity coefficient (DSC) and compared using a Wilcoxon test.Results: Our model outperformed no-new-Net for the pelvic/ovarian lesions in cross-validation, on the evaluation and test set by a significant margin (p values being 4 × 10–7, 3 × 10–4, 4 × 10–2, respectively), and for the omental lesions on the evaluation set (p = 1 × 10–3). Our model did not perform significantly differently in segmenting pelvic/ovarian lesions (p = 0.371) compared to a trainee radiologist. On an independent test set, the model achieved a DSC performance of 71 ± 20 (mean ± standard deviation) for pelvic/ovarian and 61 ± 24 for omental lesions.Conclusion: Automated ovarian cancer segmentation on CT scans using deep neural networks is feasible and achieves performance close to a trainee-level radiologist for pelvic/ovarian lesions.Relevance statement: Automated segmentation of ovarian cancer may be used by clinicians for CT-based volumetric assessments and researchers for building complex analysis pipelines.Key points:The first automated approach for pelvic/ovarian and omental ovarian cancer lesion segmentation on CT images has been presented.Automated segmentation of ovarian cancer lesions can be comparable with manual segmentation of trainee radiologists.Careful hyperparameter tuning can provide models significantly outperforming strong state-of-the-art baselines. Graphical Abstract: [Figure not available: see fulltext.]
|
|
| 23. |
- Carvalhais, Nuno, et al.
(författare)
-
Global covariation of carbon turnover times with climate in terrestrial ecosystems
- 2014
-
Ingår i: Nature. - : Springer Science and Business Media LLC. - 0028-0836 .- 1476-4687. ; 514:7521, s. 213-
-
Tidskriftsartikel (refereegranskat)abstract
- The response of the terrestrial carbon cycle to climate change is among the largest uncertainties affecting future climate change projections(1,2). The feedback between the terrestrial carbon cycle and climate is partly determined by changes in the turnover time of carbon in land ecosystems, which in turn is an ecosystem property that emerges from the interplay between climate, soil and vegetation type(3-6). Here we present a global, spatially explicit and observation-based assessment of whole-ecosystem carbon turnover times that combines new estimates of vegetation and soil organic carbon stocks and fluxes. We find that the overall mean global carbon turnover time is 23(4)(+7) years (95 per cent confidence interval). Onaverage, carbon resides in the vegetation and soil near the Equator for a shorter time than at latitudes north of 75 degrees north (mean turnover times of 15 and 255 years, respectively). We identify a clear dependence of the turnover time on temperature, as expected from our present understanding of temperature controls on ecosystem dynamics. Surprisingly, our analysis also reveals a similarly strong association between turnover time and precipitation. Moreover, we find that the ecosystem carbon turnover times simulated by state-of-the-art coupled climate/carbon-cycle models vary widely and that numerical simulations, on average, tend to underestimate the global carbon turnover time by 36 per cent. The models show stronger spatial relationships with temperature than do observation-based estimates, but generally do not reproduce the strong relationships with precipitation and predict faster carbon turnover in many semiarid regions. Our findings suggest that future climate/carbon-cycle feedbacks may depend more strongly on changes in the hydrological cycle than is expected at present and is considered in Earth system models.
|
|
| 24. |
- Castro-Morales, Karel, et al.
(författare)
-
Year-round simulated methane emissions from a permafrost ecosystem in Northeast Siberia
- 2018
-
Ingår i: Biogeosciences. - : Copernicus GmbH. - 1726-4170 .- 1726-4189. ; 15:9, s. 2691-2722
-
Tidskriftsartikel (refereegranskat)abstract
- Wetlands of northern high latitudes are ecosystems highly vulnerable to climate change. Some degradation effects include soil hydrologic changes due to permafrost thaw, formation of deeper active layers, and rising topsoil temperatures that accelerate the degradation of permafrost carbon and increase in CO2 and CH4 emissions. In this work we present 2 years of modeled year-round CH4 emissions into the atmosphere from a Northeast Siberian region in the Russian Far East. We use a revisited version of the process-based JSBACH-methane model that includes four CH4 transport pathways: plant-mediated transport, ebullition and molecular diffusion in the presence or absence of snow. The gas is emitted through wetlands represented by grid cell inundated areas simulated with a TOPMODEL approach. The magnitude of the summertime modeled CH4 emissions is comparable to ground-based CH4 fluxes measured with the eddy covariance technique and flux chambers in the same area of study, whereas wintertime modeled values are underestimated by 1 order of magnitude. In an annual balance, the most important mechanism for transport of methane into the atmosphere is through plants (61 %). This is followed by ebullition (similar to 35 %), while summertime molecular diffusion is negligible (0.02 %) compared to the diffusion through the snow during winter (similar to 4 %). We investigate the relationship between temporal changes in the CH4 fluxes, soil temperature, and soil moisture content. Our results highlight the heterogeneity in CH4 emissions at landscape scale and suggest that further improvements to the representation of large-scale hydrological conditions in the model will facilitate a more process-oriented land surface scheme and better simulate CH4 emissions under climate change. This is especially necessary at regional scales in Arctic ecosystems influenced by permafrost thaw.
|
|
| 25. |
- Chadburn, Sarah E., et al.
(författare)
-
Carbon stocks and fluxes in the high latitudes : using site-level data to evaluate Earth system models
- 2017
-
Ingår i: Biogeosciences. - : Copernicus GmbH. - 1726-4170 .- 1726-4189. ; 14:22, s. 5143-5169
-
Tidskriftsartikel (refereegranskat)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.
|
|
