| 1. |
- Harden, Jennifer W., et al.
(author)
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Field information links permafrost carbon to physical vulnerabilities of thawing
- 2012
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In: Geophysical Research Letters. - 0094-8276 .- 1944-8007. ; 39, s. L15704-
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Journal article (peer-reviewed)abstract
- Deep soil profiles containing permafrost (Gelisols) were characterized for organic carbon (C) and total nitrogen (N) stocks to 3 m depths. Using the Community Climate System Model (CCSM4) we calculate cumulative distributions of active layer thickness (ALT) under current and future climates. The difference in cumulative ALT distributions over time was multiplied by C and N contents of soil horizons in Gelisol suborders to calculate newly thawed C and N. Thawing ranged from 147 PgC with 10 PgN by 2050 (representative concentration pathway RCP scenario 4.5) to 436 PgC with 29 PgN by 2100 (RCP 8.5). Organic horizons that thaw are vulnerable to combustion, and all horizon types are vulnerable to shifts in hydrology and decomposition. The rates and extent of such losses are unknown and can be further constrained by linking field and modelling approaches. These changes have the potential for strong additional loading to our atmosphere, water resources, and ecosystems. Citation: Harden, J. W., et al. (2012), Field information links permafrost carbon to physical vulnerabilities of thawing, Geophys. Res. Lett., 39, L15704, doi: 10.1029/2012GL051958.
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| 2. |
- Zona, Donatella, et al.
(author)
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Earlier snowmelt may lead to late season declines in plant productivity and carbon sequestration in Arctic tundra ecosystems
- 2022
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In: Scientific Reports. - : Springer Science and Business Media LLC. - 2045-2322. ; 12:1
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Journal article (peer-reviewed)abstract
- Arctic warming is affecting snow cover and soil hydrology, with consequences for carbon sequestration in tundra ecosystems. The scarcity of observations in the Arctic has limited our understanding of the impact of covarying environmental drivers on the carbon balance of tundra ecosystems. In this study, we address some of these uncertainties through a novel record of 119 site-years of summer data from eddy covariance towers representing dominant tundra vegetation types located on continuous permafrost in the Arctic. Here we found that earlier snowmelt was associated with more tundra net CO2 sequestration and higher gross primary productivity (GPP) only in June and July, but with lower net carbon sequestration and lower GPP in August. Although higher evapotranspiration (ET) can result in soil drying with the progression of the summer, we did not find significantly lower soil moisture with earlier snowmelt, nor evidence that water stress affected GPP in the late growing season. Our results suggest that the expected increased CO2 sequestration arising from Arctic warming and the associated increase in growing season length may not materialize if tundra ecosystems are not able to continue sequestering CO2 later in the season.
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| 3. |
- Andresen, Christian G., et al.
(author)
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Soil moisture and hydrology projections of the permafrost region-a model intercomparison
- 2020
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In: Cryosphere. - : Copernicus GmbH. - 1994-0416. ; 14:2, s. 445-459
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Journal article (peer-reviewed)abstract
- This study investigates and compares soil moisture and hydrology projections of broadly used land models with permafrost processes and highlights the causes and impacts of permafrost zone soil moisture projections. Climate models project warmer temperatures and increases in precipitation (P) which will intensify evapotranspiration (ET) and runoff in land models. However, this study shows that most models project a long-term drying of the surface soil (0-20 cm) for the permafrost region despite increases in the net air-surface water flux (P-ET). Drying is generally explained by infiltration of moisture to deeper soil layers as the active layer deepens or permafrost thaws completely. Although most models agree on drying, the projections vary strongly in magnitude and spatial pattern. Land models tend to agree with decadal runoff trends but underestimate runoff volume when compared to gauge data across the major Arctic river basins, potentially indicating model structural limitations. Coordinated efforts to address the ongoing challenges presented in this study will help reduce uncertainty in our capability to predict the future Arctic hydrological state and associated land-atmosphere biogeochemical processes across spatial and temporal scales.
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| 4. |
- Fisher, Rosie A., et al.
(author)
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Vegetation demographics in Earth System Models : A review of progress and priorities
- 2018
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In: Global Change Biology. - : Wiley. - 1354-1013 .- 1365-2486. ; 24:1, s. 35-54
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Research review (peer-reviewed)abstract
- Numerous current efforts seek to improve the representation of ecosystem ecology and vegetation demographic processes within Earth System Models (ESMs). These developments are widely viewed as an important step in developing greater realism in predictions of future ecosystem states and fluxes. Increased realism, however, leads to increased model complexity, with new features raising a suite of ecological questions that require empirical constraints. Here, we review the developments that permit the representation of plant demographics in ESMs, and identify issues raised by these developments that highlight important gaps in ecological understanding. These issues inevitably translate into uncertainty in model projections but also allow models to be applied to new processes and questions concerning the dynamics of real-world ecosystems. We argue that stronger and more innovative connections to data, across the range of scales considered, are required to address these gaps in understanding. The development of first-generation land surface models as a unifying framework for ecophysiological understanding stimulated much research into plant physiological traits and gas exchange. Constraining predictions at ecologically relevant spatial and temporal scales will require a similar investment of effort and intensified inter-disciplinary communication.
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| 5. |
- Georgiou, Katerina, et al.
(author)
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Emergent temperature sensitivity of soil organic carbon driven by mineral associations
- 2024
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In: Nature Geoscience. - 1752-0894. ; 17:3, s. 205-212
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Journal article (peer-reviewed)abstract
- Soil organic matter decomposition and its interactions with climate depend on whether the organic matter is associated with soil minerals. However, data limitations have hindered global-scale analyses of mineral-associated and particulate soil organic carbon pools and their benchmarking in Earth system models used to estimate carbon cycle–climate feedbacks. Here we analyse observationally derived global estimates of soil carbon pools to quantify their relative proportions and compute their climatological temperature sensitivities as the decline in carbon with increasing temperature. We find that the climatological temperature sensitivity of particulate carbon is on average 28% higher than that of mineral-associated carbon, and up to 53% higher in cool climates. Moreover, the distribution of carbon between these underlying soil carbon pools drives the emergent climatological temperature sensitivity of bulk soil carbon stocks. However, global models vary widely in their predictions of soil carbon pool distributions. We show that the global proportion of model pools that are conceptually similar to mineral-protected carbon ranges from 16 to 85% across Earth system models from the Coupled Model Intercomparison Project Phase 6 and offline land models, with implications for bulk soil carbon ages and ecosystem responsiveness. To improve projections of carbon cycle–climate feedbacks, it is imperative to assess underlying soil carbon pools to accurately predict the distribution and vulnerability of soil carbon.
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| 6. |
- Kondo, Masayuki, et al.
(author)
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Are Land-Use Change Emissions in Southeast Asia Decreasing or Increasing?
- 2022
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In: Global Biogeochemical Cycles. - 0886-6236. ; 36:1
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Journal article (peer-reviewed)abstract
- Southeast Asia is a region known for active land-use changes (LUC) over the past 60 years; yet, how trends in net CO2 uptake and release resulting from LUC activities (net LUC flux) have changed through past decades remains uncertain. The level of uncertainty in net LUC flux from process-based models is so high that it cannot be concluded that newer estimates are necessarily more reliable than older ones. Here, we examined net LUC flux estimates of Southeast Asia for the 1980s−2010s from older and newer sets of Dynamic Global Vegetation Model simulations (TRENDY v2 and v7, respectively), and forcing data used for running those simulations, along with two book-keeping estimates (H&N and BLUE). These estimates yielded two contrasting historical LUC transitions, such that TRENDY v2 and H&N showed a transition from increased emissions from the 1980s to 1990s to declining emissions in the 2000s, while TRENDY v7 and BLUE showed the opposite transition. We found that these contrasting transitions originated in the update of LUC forcing data, which reduced the loss of forest area during the 1990s. Further evaluation of remote sensing studies, atmospheric inversions, and the history of forestry and environmental policies in Southeast Asia supported the occurrence of peak emissions in the 1990s and declining thereafter. However, whether LUC emissions continue to decline in Southeast Asia remains uncertain as key processes in recent years, such as conversion of peat forest to oil-palm plantation, are yet to be represented in the forcing data, suggesting a need for further revision.
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| 7. |
- Koven, Charles D., et al.
(author)
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Higher climatological temperature sensitivity of soil carbon in cold than warm climates
- 2017
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In: Nature Climate Change. - 1758-678X .- 1758-6798. ; 7:11, s. 817-822
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Journal article (peer-reviewed)abstract
- The projected loss of soil carbon to the atmosphere resulting from climate change is a potentially large but highly uncertain feedback to warming. The magnitude of this feedback is poorly constrained by observations and theory, and is disparately represented in Earth system models (ESMs)(1-3). To assess the climatological temperature sensitivity of soil carbon, we calculate apparent soil carbon turnover times(4) that reflect long-term and broad-scale rates of decomposition. Here, we show that the climatological temperature control on carbon turnover in the top metre of global soils is more sensitive in cold climates than in warm climates and argue that it is critical to capture this emergent ecosystem property in global-scale models. We present a simplified model that explains the observed high cold-climate sensitivity using only the physical scaling of soil freeze-thaw state across climate gradients. Current ESMs fail to capture this pattern, except in anESMthat explicitly resolves vertical gradients in soil climate and carbon turnover. An observed weak tropical temperature sensitivity emerges in a different model that explicitly resolves mineralogical control on decomposition. These results support projections of strong carbon- climate feedbacks from northern soils(5,6) and demonstrate a method for ESMs to capture this emergent behaviour.
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| 8. |
- Li, Wei, et al.
(author)
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Land-use and land-cover change carbon emissions between 1901 and 2012 constrained by biomass observations
- 2017
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In: Biogeosciences. - : Copernicus GmbH. - 1726-4170 .- 1726-4189. ; 14:22, s. 5053-5067
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Journal article (peer-reviewed)abstract
- The use of dynamic global vegetation models (DGVMs) to estimate CO2 emissions from land-use and land-cover change (LULCC) offers a new window to account for spatial and temporal details of emissions and for ecosystem processes affected by LULCC. One drawback of LULCC emissions from DGVMs, however, is lack of observation constraint. Here, we propose a new method of using satellite-and inventory-based biomass observations to constrain historical cumulative LULCC emissions (E-LUC(c)) from an ensemble of nine DGVMs based on emerging relationships between simulated vegetation biomass and E-LUC(c). This method is applicable on the global and regional scale. The original DGVM estimates of E-LUC(c) range from 94 to 273 PgC during 1901-2012. After constraining by current biomass observations, we derive a best estimate of 155 +/- 50 PgC (1 sigma Gaussian error). The constrained LULCC emissions are higher than prior DGVM values in tropical regions but significantly lower in North America. Our emergent constraint approach independently verifies the median model estimate by biomass observations, giving support to the use of this estimate in carbon budget assessments. The uncertainty in the constrained Ec LUC is still relatively large because of the uncertainty in the biomass observations, and thus reduced uncertainty in addition to increased accuracy in biomass observations in the future will help improve the constraint. This constraint method can also be applied to evaluate the impact of land-based mitigation activities.
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| 9. |
- Li, Zhao, et al.
(author)
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Non-uniform seasonal warming regulates vegetation greening and atmospheric CO2 amplification over northern lands
- 2018
-
In: Environmental Research Letters. - : IOP Publishing. - 1748-9326. ; 13:12
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Journal article (peer-reviewed)abstract
- The enhanced vegetation growth by climate warming plays a pivotal role in amplifying the seasonal cycle of atmospheric CO2 at northern lands (>50° N) since 1960s. However, the correlation between vegetation growth, temperature and seasonal amplitude of atmospheric CO2 concentration have become elusive with the slowed increasing trend of vegetation growth and weakened temperature control on CO2 uptake since late 1990s. Here, based on in situ atmospheric CO2 concentration records from the Barrow observatory site, we found a slowdown in the increasing trend of the atmospheric CO2 amplitude from 1990s to mid-2000s. This phenomenon was associated with the paused decrease in the minimum CO2 concentration ([CO2]min), which was significantly correlated with the slowdown of vegetation greening and growing-season length extension. We then showed that both the vegetation greenness and growing-season length were positively correlated with spring but not autumn temperature over the northern lands. Furthermore, such asymmetric dependences of vegetation growth upon spring and autumn temperature cannot be captured by the state-of-art terrestrial biosphere models. These findings indicate that the responses of vegetation growth to spring and autumn warming are asymmetric, and highlight the need of improving autumn phenology in the models for predicting seasonal cycle of atmospheric CO2 concentration.
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| 10. |
- McGuire, A. David, et al.
(author)
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Variability in the sensitivity among model simulations of permafrost and carbon dynamics in the permafrost region between 1960 and 2009
- 2016
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In: Global Biogeochemical Cycles. - 0886-6236 .- 1944-9224. ; 30:7, s. 1015-1037
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Journal article (peer-reviewed)abstract
- A significant portion of the large amount of carbon (C) currently stored in soils of the permafrost region in the Northern Hemisphere has the potential to be emitted as the greenhouse gases CO2 and CH4 under a warmer climate. In this study we evaluated the variability in the sensitivity of permafrost and C in recent decades among land surface model simulations over the permafrost region between 1960 and 2009. The 15 model simulations all predict a loss of near-surface permafrost (within 3m) area over the region, but there are large differences in the magnitude of the simulated rates of loss among the models (0.2 to 58.8x10(3)km(2)yr(-1)). Sensitivity simulations indicated that changes in air temperature largely explained changes in permafrost area, although interactions among changes in other environmental variables also played a role. All of the models indicate that both vegetation and soil C storage together have increased by 156 to 954TgCyr(-1) between 1960 and 2009 over the permafrost region even though model analyses indicate that warming alone would decrease soil C storage. Increases in gross primary production (GPP) largely explain the simulated increases in vegetation and soil C. The sensitivity of GPP to increases in atmospheric CO2 was the dominant cause of increases in GPP across the models, but comparison of simulated GPP trends across the 1982-2009 period with that of a global GPP data set indicates that all of the models overestimate the trend in GPP. Disturbance also appears to be an important factor affecting C storage, as models that consider disturbance had lower increases in C storage than models that did not consider disturbance. To improve the modeling of C in the permafrost region, there is the need for the modeling community to standardize structural representation of permafrost and carbon dynamics among models that are used to evaluate the permafrost C feedback and for the modeling and observational communities to jointly develop data sets and methodologies to more effectively benchmark models.
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| 11. |
- Mishra, Umakant, et al.
(author)
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Spatial heterogeneity and environmental predictors of permafrost region soil organic carbon stocks
- 2021
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In: Science Advances. - : American Association for the Advancement of Science (AAAS). - 2375-2548. ; 7:9
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Journal article (peer-reviewed)abstract
- Large stocks of soil organic carbon (SOC) have accumulated in the Northern Hemisphere permafrost region, but their current amounts and future fate remain uncertain. By analyzing dataset combining >2700 soil profiles with environmental variables in a geospatial framework, we generated spatially explicit estimates of permafrost-region SOC stocks, quantified spatial heterogeneity, and identified key environmental predictors. We estimated that Pg C are stored in the top 3 m of permafrost region soils. The greatest uncertainties occurred in circumpolar toe-slope positions and in flat areas of the Tibetan region. We found that soil wetness index and elevation are the dominant topographic controllers and surface air temperature (circumpolar region) and precipitation (Tibetan region) are significant climatic controllers of SOC stocks. Our results provide first high-resolution geospatial assessment of permafrost region SOC stocks and their relationships with environmental factors, which are crucial for modeling the response of permafrost affected soils to changing climate.
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| 12. |
- Muster, Sina, et al.
(author)
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PeRL : a circum-Arctic Permafrost Region Pond and Lake database
- 2017
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In: Earth System Science Data. - : Copernicus GmbH. - 1866-3508 .- 1866-3516. ; 9:1, s. 317-348
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Journal article (peer-reviewed)abstract
- Ponds and lakes are abundant in Arctic permafrost lowlands. They play an important role in Arctic wetland ecosystems by regulating carbon, water, and energy fluxes and providing freshwater habitats. However, ponds, i. e., waterbodies with surface areas smaller than 1.0 x 10(4) m(2), have not been inventoried on global and regional scales. The Permafrost Region Pond and Lake (PeRL) database presents the results of a circum-Arctic effort to map ponds and lakes from modern (2002-2013) high-resolution aerial and satellite imagery with a resolution of 5m or better. The database also includes historical imagery from 1948 to 1965 with a resolution of 6m or better. PeRL includes 69 maps covering a wide range of environmental conditions from tundra to boreal regions and from continuous to discontinuous permafrost zones. Waterbody maps are linked to regional permafrost landscape maps which provide information on permafrost extent, ground ice volume, geology, and lithology. This paper describes waterbody classification and accuracy, and presents statistics of waterbody distribution for each site. Maps of permafrost landscapes in Alaska, Canada, and Russia are used to extrapolate waterbody statistics from the site level to regional landscape units. PeRL presents pond and lake estimates for a total area of 1.4 x 10(6) km(2) across the Arctic, about 17% of the Arctic lowland (<300ma. s.l.) land surface area. PeRL waterbodies with sizes of 1.0 x 10(6) m(2) down to 1.0 x 10(2) m(2) contributed up to 21% to the total water fraction. Waterbody density ranged from 1.0 x 10 to 9.4 x 10(1) km(-2). Ponds are the dominant waterbody type by number in all landscapes representing 45-99% of the total waterbody number. The implementation of PeRL size distributions in land surface models will greatly improve the investigation and projection of surface inundation and carbon fluxes in permafrost lowlands. Waterbody maps, study area boundaries, and maps of regional permafrost landscapes including detailed metadata are available at https://doi.pangaea.de/10.1594/PANGAEA.868349.
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| 13. |
- Needham, Jessica F., et al.
(author)
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Demographic composition, not demographic diversity, predicts biomass and turnover across temperate and tropical forests
- 2022
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In: Global Change Biology. - : Wiley. - 1354-1013 .- 1365-2486. ; 28, s. 2895-2909
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Journal article (peer-reviewed)abstract
- The growth and survival of individual trees determine the physical structure of a forest with important consequences for forest function. However, given the diversity of tree species and forest biomes, quantifying the multitude of demographic strategies within and across forests and the way that they translate into forest structure and function remains a significant challenge. Here, we quantify the demographic rates of 1961 tree species from temperate and tropical forests and evaluate how demographic diversity (DD) and demographic composition (DC) differ across forests, and how these differences in demography relate to species richness, aboveground biomass (AGB), and carbon residence time. We find wide variation in DD and DC across forest plots, patterns that are not explained by species richness or climate variables alone. There is no evidence that DD has an effect on either AGB or carbon residence time. Rather, the DC of forests, specifically the relative abundance of large statured species, predicted both biomass and carbon residence time. Our results demonstrate the distinct DCs of globally distributed forests, reflecting biogeography, recent history, and current plot conditions. Linking the DC of forests to resilience or vulnerability to climate change, will improve the precision and accuracy of predictions of future forest composition, structure, and function.
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| 14. |
- Turetsky, Merritt R., et al.
(author)
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Carbon release through abrupt permafrost thaw
- 2020
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In: Nature Geoscience. - : Springer Science and Business Media LLC. - 1752-0894 .- 1752-0908. ; 13:2, s. 138-
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Journal article (peer-reviewed)abstract
- The permafrost zone is expected to be a substantial carbon source to the atmosphere, yet large-scale models currently only simulate gradual changes in seasonally thawed soil. Abrupt thaw will probably occur in <20% of the permafrost zone but could affect half of permafrost carbon through collapsing ground, rapid erosion and landslides. Here, we synthesize the best available information and develop inventory models to simulate abrupt thaw impacts on permafrost carbon balance. Emissions across 2.5 million km(2) of abrupt thaw could provide a similar climate feedback as gradual thaw emissions from the entire 18 million km(2) permafrost region under the warming projection of Representative Concentration Pathway 8.5. While models forecast that gradual thaw may lead to net ecosystem carbon uptake under projections of Representative Concentration Pathway 4.5, abrupt thaw emissions are likely to offset this potential carbon sink. Active hillslope erosional features will occupy 3% of abrupt thaw terrain by 2300 but emit one-third of abrupt thaw carbon losses. Thaw lakes and wetlands are methane hot spots but their carbon release is partially offset by slowly regrowing vegetation. After considering abrupt thaw stabilization, lake drainage and soil carbon uptake by vegetation regrowth, we conclude that models considering only gradual permafrost thaw are substantially underestimating carbon emissions from thawing permafrost.
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| 15. |
- Varney, Rebecca M., et al.
(author)
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A spatial emergent constraint on the sensitivity of soil carbon turnover to global warming
- 2020
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In: Nature Communications. - : Springer Science and Business Media LLC. - 2041-1723. ; 11:1
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Journal article (peer-reviewed)abstract
- Carbon cycle feedbacks represent large uncertainties in climate change projections, and the response of soil carbon to climate change contributes the greatest uncertainty to this. Future changes in soil carbon depend on changes in litter and root inputs from plants and especially on reductions in the turnover time of soil carbon (tau(s)) with warming. An approximation to the latter term for the top one metre of soil (Delta C-s,C-tau) can be diagnosed from projections made with the CMIP6 and CMIP5 Earth System Models (ESMs), and is found to span a large range even at 2 degrees C of global warming (-196 +/- 117 PgC). Here, we present a constraint on Delta C-s,C-tau, which makes use of current heterotrophic respiration and the spatial variability of tau(s) inferred from observations. This spatial emergent constraint allows us to halve the uncertainty in Delta C-s,C-tau at 2 degrees C to -232 +/- 52 PgC.
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| 16. |
- Wang, Wenli, et al.
(author)
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Evaluation of air-soil temperature relationships simulated by land surface models during winter across the permafrost region
- 2016
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In: Cryosphere. - : Copernicus GmbH. - 1994-0416. ; 10:4, s. 1721-1737
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Journal article (peer-reviewed)abstract
- A realistic simulation of snow cover and its thermal properties are important for accurate modelling of permafrost. We analyse simulated relationships between air and near-surface (20 cm) soil temperatures in the Northern Hemisphere permafrost region during winter, with a particular focus on snow insulation effects in nine land surface models, and compare them with observations from 268 Russian stations. There are large cross-model differences in the simulated differences between near-surface soil and air temperatures (ΔT; 3 to 14 °C), in the sensitivity of soil-to-air temperature (0.13 to 0.96 °C °C-1), and in the relationship between ΔT and snow depth. The observed relationship between ΔT and snow depth can be used as a metric to evaluate the effects of each model's representation of snow insulation, hence guide improvements to the model's conceptual structure and process parameterisations. Models with better performance apply multilayer snow schemes and consider complex snow processes. Some models show poor performance in representing snow insulation due to underestimation of snow depth and/or overestimation of snow conductivity. Generally, models identified as most acceptable with respect to snow insulation simulate reasonable areas of near-surface permafrost (13.19 to 15.77 million km2). However, there is not a simple relationship between the sophistication of the snow insulation in the acceptable models and the simulated area of Northern Hemisphere near-surface permafrost, because several other factors, such as soil depth used in the models, the treatment of soil organic matter content, hydrology and vegetation cover, also affect the simulated permafrost distribution.
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| 17. |
- Xia, Jianyang, et al.
(author)
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Terrestrial ecosystem model performance in simulating productivity and its vulnerability to climate change in the northern permafrost region
- 2017
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In: Journal of Geophysical Research - Biogeosciences. - 2169-8953. ; 122:2, s. 430-446
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Journal article (peer-reviewed)abstract
- Realistic projection of future climate-carbon (C) cycle feedbacks requires better understanding and an improved representation of the C cycle in permafrost regions in the current generation of Earth system models. Here we evaluated 10 terrestrial ecosystem models for their estimates of net primary productivity (NPP) and responses to historical climate change in permafrost regions in the Northern Hemisphere. In comparison with the satellite estimate from the Moderate Resolution Imaging Spectroradiometer (MODIS; 246±6gCm-2yr-1), most models produced higher NPP (309±12gCm-2yr-1) over the permafrost region during 2000-2009. By comparing the simulated gross primary productivity (GPP) with a flux tower-based database, we found that although mean GPP among the models was only overestimated by 10% over 1982-2009, there was a twofold discrepancy among models (380 to 800gCm-2yr-1), which mainly resulted from differences in simulated maximum monthly GPP (GPPmax). Most models overestimated C use efficiency (CUE) as compared to observations at both regional and site levels. Further analysis shows that model variability of GPP and CUE are nonlinearly correlated to variability in specific leaf area and the maximum rate of carboxylation by the enzyme Rubisco at 25°C (Vcmax_25), respectively. The models also varied in their sensitivities of NPP, GPP, and CUE to historical changes in climate and atmospheric CO2 concentration. These results indicate that model predictive ability of the C cycle in permafrost regions can be improved by better representation of the processes controlling CUE and GPPmax as well as their sensitivity to climate change.
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