| 1. |
- Chang, Kuang Yu, et al.
(author)
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Substantial hysteresis in emergent temperature sensitivity of global wetland CH4 emissions
- 2021
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In: Nature Communications. - : Springer Science and Business Media LLC. - 2041-1723. ; 12:1, s. 2266-2266
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Journal article (peer-reviewed)abstract
- Wetland methane (CH4) emissions ([Formula: see text]) are important in global carbon budgets and climate change assessments. Currently, [Formula: see text] projections rely on prescribed static temperature sensitivity that varies among biogeochemical models. Meta-analyses have proposed a consistent [Formula: see text] temperature dependence across spatial scales for use in models; however, site-level studies demonstrate that [Formula: see text] are often controlled by factors beyond temperature. Here, we evaluate the relationship between [Formula: see text] and temperature using observations from the FLUXNET-CH4 database. Measurements collected across the globe show substantial seasonal hysteresis between [Formula: see text] and temperature, suggesting larger [Formula: see text] sensitivity to temperature later in the frost-free season (about 77% of site-years). Results derived from a machine-learning model and several regression models highlight the importance of representing the large spatial and temporal variability within site-years and ecosystem types. Mechanistic advancements in biogeochemical model parameterization and detailed measurements in factors modulating CH4 production are thus needed to improve global CH4 budget assessments.
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| 2. |
- Knox, Sara H., et al.
(author)
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FLUXNET-CH4 Synthesis Activity : Objectives, Observations, and Future Directions
- 2019
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In: Bulletin of The American Meteorological Society - (BAMS). - 0003-0007 .- 1520-0477. ; 100:12, s. 2607-2632
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Journal article (peer-reviewed)abstract
- This paper describes the formation of, and initial results for, a new FLUXNET coordination network for ecosystem-scale methane (CH4) measurements at 60 sites globally, organized by the Global Carbon Project in partnership with other initiatives and regional flux tower networks. The objectives of the effort are presented along with an overview of the coverage of eddy covariance (EC) CH4 flux measurements globally, initial results comparing CH4 fluxes across the sites, and future research directions and needs. Annual estimates of net CH4 fluxes across sites ranged from -0.2 +/- 0.02 g C m(-2) yr(-1) for an upland forest site to 114.9 +/- 13.4 g C m(-2) yr(-1) for an estuarine freshwater marsh, with fluxes exceeding 40 g C m(-2) yr(-1) at multiple sites. Average annual soil and air temperatures were found to be the strongest predictor of annual CH4 flux across wetland sites globally. Water table position was positively correlated with annual CH4 emissions, although only for wetland sites that were not consistently inundated throughout the year. The ratio of annual CH4 fluxes to ecosystem respiration increased significantly with mean site temperature. Uncertainties in annual CH4 estimates due to gap-filling and random errors were on average +/- 1.6 g C m(-2) yr(-1) at 95% confidence, with the relative error decreasing exponentially with increasing flux magnitude across sites. Through the analysis and synthesis of a growing EC CH4 flux database, the controls on ecosystem CH4 fluxes can be better understood, used to inform and validate Earth system models, and reconcile differences between land surface model- and atmospheric-based estimates of CH4 emissions.
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| 3. |
- Koebsch, Franziska, et al.
(author)
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Refining the role of phenology in regulating gross ecosystem productivity across European peatlands
- 2020
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In: Global Change Biology. - : Wiley. - 1354-1013 .- 1365-2486. ; 26:2, s. 876-887
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Journal article (peer-reviewed)abstract
- The role of plant phenology as a regulator for gross ecosystem productivity (GEP) in peatlands is empirically not well constrained. This is because proxies to track vegetation development with daily coverage at the ecosystem scale have only recently become available and the lack of such data has hampered the disentangling of biotic and abiotic effects. This study aimed at unraveling the mechanisms that regulate the seasonal variation in GEP across a network of eight European peatlands. Therefore, we described phenology with canopy greenness derived from digital repeat photography and disentangled the effects of radiation, temperature and phenology on GEP with commonality analysis and structural equation modeling. The resulting relational network could not only delineate direct effects but also accounted for possible effect combinations such as interdependencies (mediation) and interactions (moderation). We found that peatland GEP was controlled by the same mechanisms across all sites: phenology constituted a key predictor for the seasonal variation in GEP and further acted as a distinct mediator for temperature and radiation effects on GEP. In particular, the effect of air temperature on GEP was fully mediated through phenology, implying that direct temperature effects representing the thermoregulation of photosynthesis were negligible. The tight coupling between temperature, phenology and GEP applied especially to high latitude and high altitude peatlands and during phenological transition phases. Our study highlights the importance of phenological effects when evaluating the future response of peatland GEP to climate change. Climate change will affect peatland GEP especially through changing temperature patterns during plant phenologically sensitive phases in high latitude and high altitude regions.
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| 4. |
- Kropp, Heather, et al.
(author)
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Shallow soils are warmer under trees and tall shrubs across Arctic and Boreal ecosystems
- 2021
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In: Environmental Research Letters. - : IOP Publishing. - 1748-9326. ; 16:1
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Journal article (peer-reviewed)abstract
- Soils are warming as air temperatures rise across the Arctic and Boreal region concurrent with the expansion of tall-statured shrubs and trees in the tundra. Changes in vegetation structure and function are expected to alter soil thermal regimes, thereby modifying climate feedbacks related to permafrost thaw and carbon cycling. However, current understanding of vegetation impacts on soil temperature is limited to local or regional scales and lacks the generality necessary to predict soil warming and permafrost stability on a pan-Arctic scale. Here we synthesize shallow soil and air temperature observations with broad spatial and temporal coverage collected across 106 sites representing nine different vegetation types in the permafrost region. We showed ecosystems with tall-statured shrubs and trees (>40 cm) have warmer shallow soils than those with short-statured tundra vegetation when normalized to a constant air temperature. In tree and tall shrub vegetation types, cooler temperatures in the warm season do not lead to cooler mean annual soil temperature indicating that ground thermal regimes in the cold-season rather than the warm-season are most critical for predicting soil warming in ecosystems underlain by permafrost. Our results suggest that the expansion of tall shrubs and trees into tundra regions can amplify shallow soil warming, and could increase the potential for increased seasonal thaw depth and increase soil carbon cycling rates and lead to increased carbon dioxide loss and further permafrost thaw.
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| 5. |
- Kross, Angela, et al.
(author)
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Estimating carbon dioxide exchange rates at contrasting northern peatlands using MODIS satellite data
- 2013
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In: Remote Sensing of Environment. - : Elsevier BV. - 0034-4257. ; 137, s. 234-243
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Journal article (peer-reviewed)abstract
- Northern hemisphere peatlands play an important role in the global carbon (C) cycle, accounting for about 30% of global soil C and similar to 10-25% of global natural methane (CH4) emissions. Satellite remote sensing has the potential for extracting continuous information related to C exchange rates at regional and global extents, yet, few studies have focused on peatlands. In this study we examined the potential of moderate resolution imaging spectroradiometer (MODIS) vegetation indices (normalized difference vegetation index, NDVI and simple ratio, SR), MODIS light use efficiency (LUE) based gross primary production (GPP) and a MODIS derived phenological index (annual peak photosynthetic rate) for the estimation of eddy covariance (EC) flux-derived GPP and net ecosystem production (NEP) at four contrasting northern peatlands. At the four sites of this study MODIS NDVI and SR explained between 39% and 71%, and between 42% and 69% of the variation in EC-derived GPP, respectively; and between 25% and 53%, and between 29% and 39% of the variation in EC-derived NEP, respectively. The relationships were mostly consistent across sites and within sites, suggesting that data may be pooled across years and sites, which could simplify the prediction of gross and net C dioxide (CO2) uptake over large areas dominated by northern peatlands based on MODIS data. MODIS GPP explained between 68% and 89% of the variation in EC-derived GPP at the four study sites. The root mean square errors ranged between 0.62 and 1.16 g C m(-2) d(-1) and were similar to errors from ecosystem process model estimates reported in the literature. Annual peak MODIS GPP, NDVI and SR rates explained up to 50% of the variations in annual cumulative EC-derived GPP and NEP at two of the study sites. Our results show the potentials and limitations of MODIS data to monitor the C dynamics of northern peatlands; among the three studied approaches the MODIS LUE-based GPP approach showed better performance as a predictor of GPP and NEP. The other approaches (VIs and phenology) can provide important input data for LUE models. (c) 2013 Elsevier Inc. All rights reserved.
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| 6. |
- Kuhn, McKenzie A., et al.
(author)
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Controls on Stable Methane Isotope Values in Northern Peatlands and Potential Shifts in Values Under Permafrost Thaw Scenarios
- 2024
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In: Journal of Geophysical Research - Biogeosciences. - : American Geophysical Union (AGU). - 2169-8953 .- 2169-8961. ; 129:7
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Journal article (peer-reviewed)abstract
- Northern peatlands are a globally significant source of methane (CH4), and emissions are projected to increase due to warming and permafrost loss. Understanding the microbial mechanisms behind patterns in CH4 production in peatlands will be key to predicting annual emissions changes, with stable carbon isotopes (δ13C-CH4) being a powerful tool for characterizing these drivers. Given that δ13C-CH4 is used in top-down atmospheric inversion models to partition sources, our ability to model CH4 production pathways and associated δ13C-CH4 values is critical. We sought to characterize the role of environmental conditions, including hydrologic and vegetation patterns associated with permafrost thaw, on δ13C-CH4 values from high-latitude peatlands. We measured porewater and emitted CH4 stable isotopes, pH, and vegetation composition from five boreal-Arctic peatlands. Porewater δ13C-CH4 was strongly associated with peatland type, with δ13C enriched values obtained from more minerotrophic fens (−61.2 ± 9.1‰) compared to permafrost-free bogs (−74.1 ± 9.4‰) and raised permafrost bogs (−81.6 ± 11.5‰). Variation in porewater δ13C-CH4 was best explained by sedge cover, CH4 concentration, and the interactive effect of peatland type and pH (r2 = 0.50, p < 0.001). Emitted δ13C-CH4 varied greatly but was positively correlated with porewater δ13C-CH4. We calculated a mixed atmospheric δ13C-CH4 value for northern peatlands of −65.3 ± 7‰ and show that this value is more sensitive to landscape drying than wetting under permafrost thaw scenarios. Our results suggest northern peatland δ13C-CH4 values are likely to shift in the future which has important implications for source partitioning in atmospheric inversion models.
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| 7. |
- Loranty, Michael M., et al.
(author)
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Reviews and syntheses : Changing ecosystem influences on soil thermal regimes in northern high-latitude permafrost regions
- 2018
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In: Biogeosciences. - : Copernicus GmbH. - 1726-4170 .- 1726-4189. ; 15:17, s. 5287-5313
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Research review (peer-reviewed)abstract
- Soils in Arctic and boreal ecosystems store twice as much carbon as the atmosphere, a portion of which may be released as high-latitude soils warm. Some of the uncertainty in the timing and magnitude of the permafrost-climate feedback stems from complex interactions between ecosystem properties and soil thermal dynamics. Terrestrial ecosystems fundamentally regulate the response of permafrost to climate change by influencing surface energy partitioning and the thermal properties of soil itself. Here we review how Arctic and boreal ecosystem processes influence thermal dynamics in permafrost soil and how these linkages may evolve in response to climate change. While many of the ecosystem characteristics and processes affecting soil thermal dynamics have been examined individually (e.g., vegetation, soil moisture, and soil structure), interactions among these processes are less understood. Changes in ecosystem type and vegetation characteristics will alter spatial patterns of interactions between climate and permafrost. In addition to shrub expansion, other vegetation responses to changes in climate and rapidly changing disturbance regimes will affect ecosystem surface energy partitioning in ways that are important for permafrost. Lastly, changes in vegetation and ecosystem distribution will lead to regional and global biophysical and biogeochemical climate feedbacks that may compound or offset local impacts on permafrost soils. Consequently, accurate prediction of the permafrost carbon climate feedback will require detailed understanding of changes in terrestrial ecosystem distribution and function, which depend on the net effects of multiple feedback processes operating across scales in space and time.
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| 8. |
- Oehri, Jacqueline, et al.
(author)
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Vegetation type is an important predictor of the arctic summer land surface energy budget
- 2022
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In: Nature Communications. - : Springer Nature. - 2041-1723. ; 13
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Journal article (peer-reviewed)abstract
- Despite the importance of high-latitude surface energy budgets (SEBs) for land-climate interactions in the rapidly changing Arctic, uncertainties in their prediction persist. Here, we harmonize SEB observations across a network of vegetated and glaciated sites at circumpolar scale (1994–2021). Our variance-partitioning analysis identifies vegetation type as an important predictor for SEB-components during Arctic summer (June-August), compared to other SEB-drivers including climate, latitude and permafrost characteristics. Differences among vegetation types can be of similar magnitude as between vegetation and glacier surfaces and are especially high for summer sensible and latent heat fluxes. The timing of SEB-flux summer-regimes (when daily mean values exceed 0 Wm−2) relative to snow-free and -onset dates varies substantially depending on vegetation type, implying vegetation controls on snow-cover and SEB-flux seasonality. Our results indicate complex shifts in surface energy fluxes with land-cover transitions and a lengthening summer season, and highlight the potential for improving future Earth system models via a refined representation of Arctic vegetation types.
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| 9. |
- Olefeldt, David, et al.
(author)
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The Boreal-Arctic Wetland and Lake Dataset (BAWLD)
- 2021
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In: Earth System Science Data. - : Copernicus Gesellschaft MBH. - 1866-3508 .- 1866-3516. ; 13:11, s. 5127-5149
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Journal article (peer-reviewed)abstract
- Methane emissions from boreal and arctic wetlands, lakes, and rivers are expected to increase in response to warming and associated permafrost thaw. However, the lack of appropriate land cover datasets for scaling field-measured methane emissions to circumpolar scales has contributed to a large uncertainty for our understanding of present-day and future methane emissions. Here we present the BorealArctic Wetland and Lake Dataset (BAWLD), a land cover dataset based on an expert assessment, extrapolated using random forest modelling from available spatial datasets of climate, topography, soils, permafrost conditions, vegetation, wetlands, and surface water extents and dynamics. In BAWLD, we estimate the fractional coverage of five wetland, seven lake, and three river classes within 0.5 x 0.5 degrees grid cells that cover the northern boreal and tundra biomes (17 % of the global land surface). Land cover classes were defined using criteria that ensured distinct methane emissions among classes, as indicated by a co-developed comprehensive dataset of methane flux observations. In BAWLD, wetlands occupied 3.2 x 10(6) km(2) (14 % of domain) with a 95 % confidence interval between 2.8 and 3.8 x 10(6) km(2). Bog, fen, and permafrost bog were the most abundant wetland classes, covering similar to 28 % each of the total wetland area, while the highest-methane-emitting marsh and tundra wetland classes occupied 5 % and 12 %, respectively. Lakes, defined to include all lentic open-water ecosystems regardless of size, covered 1.4 x 10(6) km(2) (6 % of domain). Low-methane-emitting large lakes (>10 km(2)) and glacial lakes jointly represented 78 % of the total lake area, while high-emitting peatland and yedoma lakes covered 18 % and 4 %, respectively. Small (<0.1 km(2)) glacial, peatland, and yedoma lakes combined covered 17 % of the total lake area but contributed disproportionally to the overall spatial uncertainty in lake area with a 95 % confidence interval between 0.15 and 0.38 x 10(6) km(2). Rivers and streams were estimated to cover 0.12 x 10(6) km(2) (0.5 % of domain), of which 8 % was associated with high-methane-emitting headwaters that drain organic-rich landscapes. Distinct combinations of spatially co-occurring wetland and lake classes were identified across the BAWLD domain, allowing for the mapping of "wetscapes" that have characteristic methane emission magnitudes and sensitivities to climate change at regional scales. With BAWLD, we provide a dataset which avoids double-accounting of wetland, lake, and river extents and which includes confidence intervals for each land cover class. As such, BAWLD will be suitable for many hydrological and biogeochemical modelling and upscaling efforts for the northern boreal and arctic region, in particular those aimed at improving assessments of current and future methane emissions.
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| 10. |
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| 11. |
- Peltola, Olli, et al.
(author)
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Monthly gridded data product of northern wetland methane emissions based on upscaling eddy covariance observations
- 2019
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In: Earth System Science Data. - : Copernicus GmbH. - 1866-3508 .- 1866-3516. ; 11:3, s. 1263-1289
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Journal article (peer-reviewed)abstract
- Natural wetlands constitute the largest and most uncertain source of methane (CH4) to the atmosphere and a large fraction of them are found in the northern latitudes. These emissions are typically estimated using process ("bottom-up") or inversion ("top-down") models. However, estimates from these two types of models are not independent of each other since the top-down estimates usually rely on the a priori estimation of these emissions obtained with process models. Hence, independent spatially explicit validation data are needed. Here we utilize a random forest (RF) machine-learning technique to upscale CH4 eddy covariance flux measurements from 25 sites to estimate CH4 wetland emissions from the northern latitudes (north of 45° N). Eddy covariance data from 2005 to 2016 are used for model development. The model is then used to predict emissions during 2013 and 2014. The predictive performance of the RF model is evaluated using a leave-one-site-out cross-validation scheme. The performance (Nash-Sutcliffe model efficiency D 0:47) is comparable to previous studies upscaling net ecosystem exchange of carbon dioxide and studies comparing process model output against site-level CH4 emission data. The global distribution of wetlands is one major source of uncertainty for upscaling CH4. Thus, three wetland distribution maps are utilized in the upscaling. Depending on the wetland distribution map, the annual emissions for the northern wetlands yield 32 (22.3-41.2, 95 % confidence interval calculated from a RF model ensemble), 31 (21.4-39.9) or 38 (25.9-49.5) Tg(CH4) yr-1. To further evaluate the uncertainties of the upscaled CH4 flux data products we also compared them against output from two process models (LPX-Bern and WetCHARTs), and methodological issues related to CH4 flux upscaling are discussed. The monthly upscaled CH4 flux data products are available at https://doi.org/10.5281/zenodo.2560163 (Peltola et al., 2019).
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| 12. |
- Pulliainen, Jouni, et al.
(author)
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Increase in gross primary production of boreal forests balanced out by increase in ecosystem respiration
- 2024
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In: Remote Sensing of Environment. - 0034-4257. ; 313, s. 114376-114376
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Journal article (peer-reviewed)abstract
- Changes in the net carbon sink of boreal forests constitute a major source of uncertainty in the future global carbon budget and, hence, climate change projections. The annual net ecosystem exchange of carbon dioxide (CO2) controlling the terrestrial carbon stock results from the small difference between respiratory CO2 release and the photosynthetic CO2 uptake by vegetation. The boreal forest, and the boreal biome in general, is regarded as a persistent and even increasing net carbon sink. However, decreases in photosynthetic CO2 uptake and/or concurrent increases in respiratory CO2 release under a changing climate may turn boreal forests from a net sink to a net source of CO2. Here, we assessed the interannual variability of the boreal forest net CO2 sink-source strength and its two component fluxes from 1981 to 2018. Our remote sensing approach - trained by net CO2 flux observations at eddy covariance sites across the circumpolar boreal forests - employs satellite-derived retrievals of snowmelt timing, landscape freeze-thaw status, and yearly maximum estimates of the normalized difference vegetation index as a proxy for peak vegetation productivity. Our results suggest that for the period 2000–2018, the mean annual evergreen boreal forest CO2 photosynthetic uptake (gross primary productivity) was 0.2 Pg C y−1 (0.1 Pg C y−1 for Eurasia and 0.1 Pg C y−1 for North America). In contrast to earlier studies results obtained here do not indicate a clear increasing trend in the circumpolar evergreen boreal forest CO2 sink. The increase in photosynthetic CO2 uptake is compensated by increasing respiratory releases with both component fluxes showing considerable interannual variabilities.
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| 13. |
- Stimmler, Peter, et al.
(author)
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Pan-Arctic soil element bioavailability estimations
- 2023
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In: Earth System Science Data. - : Copernicus GmbH. - 1866-3508 .- 1866-3516. ; 15:3, s. 1059-1075
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Journal article (peer-reviewed)abstract
- Arctic soils store large amounts of organic carbon and other elements, such as amorphous silicon, silicon, calcium, iron, aluminum, and phosphorous. Global warming is projected to be most pronounced in the Arctic, leading to thawing permafrost which, in turn, changes the soil element availability. To project how biogeochemical cycling in Arctic ecosystems will be affected by climate change, there is a need for data on element availability. Here, we analyzed the amorphous silicon (ASi) content as a solid fraction of the soils as well as Mehlich III extractions for the bioavailability of silicon (Si), calcium (Ca), iron (Fe), phosphorus (P), and aluminum (Al) from 574 soil samples from the circumpolar Arctic region. We show large differences in the ASi fraction and in Si, Ca, Fe, Al, and P availability among different lithologies and Arctic regions. We summarize these data in pan-Arctic maps of the ASi fraction and available Si, Ca, Fe, P, and Al concentrations, focusing on the top 100 cm of Arctic soil. Furthermore, we provide element availability values for the organic and mineral layers of the seasonally thawing active layer as well as for the uppermost permafrost layer. Our spatially explicit data on differences in the availability of elements between the different lithological classes and regions now and in the future will improve Arctic Earth system models for estimating current and future carbon and nutrient feedbacks under climate change (, Schaller and Goeckede, 2022).
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| 14. |
- Treat, Claire C., et al.
(author)
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Permafrost Carbon : Progress on Understanding Stocks and Fluxes Across Northern Terrestrial Ecosystems
- 2024
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In: Journal of Geophysical Research - Biogeosciences. - : American Geophysical Union (AGU). - 2169-8953 .- 2169-8961. ; 129:3
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Journal article (peer-reviewed)abstract
- Significant progress in permafrost carbon science made over the past decades include the identification of vast permafrost carbon stocks, the development of new pan-Arctic permafrost maps, an increase in terrestrial measurement sites for CO2 and methane fluxes, and important factors affecting carbon cycling, including vegetation changes, periods of soil freezing and thawing, wildfire, and other disturbance events. Process-based modeling studies now include key elements of permafrost carbon cycling and advances in statistical modeling and inverse modeling enhance understanding of permafrost region C budgets. By combining existing data syntheses and model outputs, the permafrost region is likely a wetland methane source and small terrestrial ecosystem CO2 sink with lower net CO2 uptake toward higher latitudes, excluding wildfire emissions. For 2002–2014, the strongest CO2 sink was located in western Canada (median: −52 g C m−2 y−1) and smallest sinks in Alaska, Canadian tundra, and Siberian tundra (medians: −5 to −9 g C m−2 y−1). Eurasian regions had the largest median wetland methane fluxes (16–18 g CH4 m−2 y−1). Quantifying the regional scale carbon balance remains challenging because of high spatial and temporal variability and relatively low density of observations. More accurate permafrost region carbon fluxes require: (a) the development of better maps characterizing wetlands and dynamics of vegetation and disturbances, including abrupt permafrost thaw; (b) the establishment of new year-round CO2 and methane flux sites in underrepresented areas; and (c) improved models that better represent important permafrost carbon cycle dynamics, including non-growing season emissions and disturbance effects.
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| 15. |
- Virkkala, Anna Maria, et al.
(author)
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Statistical upscaling of ecosystem CO2 fluxes across the terrestrial tundra and boreal domain : Regional patterns and uncertainties
- 2021
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In: Global Change Biology. - : Wiley. - 1354-1013 .- 1365-2486. ; 27:17, s. 4040-4059
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Journal article (peer-reviewed)abstract
- The regional variability in tundra and boreal carbon dioxide (CO2) fluxes can be high, complicating efforts to quantify sink-source patterns across the entire region. Statistical models are increasingly used to predict (i.e., upscale) CO2 fluxes across large spatial domains, but the reliability of different modeling techniques, each with different specifications and assumptions, has not been assessed in detail. Here, we compile eddy covariance and chamber measurements of annual and growing season CO2 fluxes of gross primary productivity (GPP), ecosystem respiration (ER), and net ecosystem exchange (NEE) during 1990–2015 from 148 terrestrial high-latitude (i.e., tundra and boreal) sites to analyze the spatial patterns and drivers of CO2 fluxes and test the accuracy and uncertainty of different statistical models. CO2 fluxes were upscaled at relatively high spatial resolution (1 km2) across the high-latitude region using five commonly used statistical models and their ensemble, that is, the median of all five models, using climatic, vegetation, and soil predictors. We found the performance of machine learning and ensemble predictions to outperform traditional regression methods. We also found the predictive performance of NEE-focused models to be low, relative to models predicting GPP and ER. Our data compilation and ensemble predictions showed that CO2 sink strength was larger in the boreal biome (observed and predicted average annual NEE −46 and −29 g C m−2 yr−1, respectively) compared to tundra (average annual NEE +10 and −2 g C m−2 yr−1). This pattern was associated with large spatial variability, reflecting local heterogeneity in soil organic carbon stocks, climate, and vegetation productivity. The terrestrial ecosystem CO2 budget, estimated using the annual NEE ensemble prediction, suggests the high-latitude region was on average an annual CO2 sink during 1990–2015, although uncertainty remains high.
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| 16. |
- Watts, Jennifer D., et al.
(author)
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Carbon uptake in Eurasian boreal forests dominates the high-latitude net ecosystem carbon budget
- 2023
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In: Global Change Biology. - : Wiley. - 1354-1013 .- 1365-2486. ; 29:7, s. 1870-1889
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Journal article (peer-reviewed)abstract
- Arctic-boreal landscapes are experiencing profound warming, along with changes in ecosystem moisture status and disturbance from fire. This region is of global importance in terms of carbon feedbacks to climate, yet the sign (sink or source) and magnitude of the Arctic-boreal carbon budget within recent years remains highly uncertain. Here, we provide new estimates of recent (2003–2015) vegetation gross primary productivity (GPP), ecosystem respiration (Reco), net ecosystem CO2 exchange (NEE; Reco − GPP), and terrestrial methane (CH4) emissions for the Arctic-boreal zone using a satellite data-driven process-model for northern ecosystems (TCFM-Arctic), calibrated and evaluated using measurements from >60 tower eddy covariance (EC) sites. We used TCFM-Arctic to obtain daily 1-km2 flux estimates and annual carbon budgets for the pan-Arctic-boreal region. Across the domain, the model indicated an overall average NEE sink of −850 Tg CO2-C year−1. Eurasian boreal zones, especially those in Siberia, contributed to a majority of the net sink. In contrast, the tundra biome was relatively carbon neutral (ranging from small sink to source). Regional CH4 emissions from tundra and boreal wetlands (not accounting for aquatic CH4) were estimated at 35 Tg CH4-C year−1. Accounting for additional emissions from open water aquatic bodies and from fire, using available estimates from the literature, reduced the total regional NEE sink by 21% and shifted many far northern tundra landscapes, and some boreal forests, to a net carbon source. This assessment, based on in situ observations and models, improves our understanding of the high-latitude carbon status and also indicates a continued need for integrated site-to-regional assessments to monitor the vulnerability of these ecosystems to climate change.
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| 17. |
- Yuan, Kunxiaojia, et al.
(author)
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Causality guided machine learning model on wetland CH4 emissions across global wetlands
- 2022
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In: Agricultural and Forest Meteorology. - : Elsevier. - 0168-1923 .- 1873-2240. ; 324
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Journal article (peer-reviewed)abstract
- Wetland CH4 emissions are among the most uncertain components of the global CH4 budget. The complex nature of wetland CH4 processes makes it challenging to identify causal relationships for improving our understanding and predictability of CH4 emissions. In this study, we used the flux measurements of CH4 from eddy covariance towers (30 sites from 4 wetlands types: bog, fen, marsh, and wet tundra) to construct a causality-constrained machine learning (ML) framework to explain the regulative factors and to capture CH4 emissions at sub -seasonal scale. We found that soil temperature is the dominant factor for CH4 emissions in all studied wetland types. Ecosystem respiration (CO2) and gross primary productivity exert controls at bog, fen, and marsh sites with lagged responses of days to weeks. Integrating these asynchronous environmental and biological causal relationships in predictive models significantly improved model performance. More importantly, modeled CH4 emissions differed by up to a factor of 4 under a +1C warming scenario when causality constraints were considered. These results highlight the significant role of causality in modeling wetland CH(4 )emissions especially under future warming conditions, while traditional data-driven ML models may reproduce observations for the wrong reasons. Our proposed causality-guided model could benefit predictive modeling, large-scale upscaling, data gap-filling, and surrogate modeling of wetland CH4 emissions within earth system land models.
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| 18. |
- Zhang, Zhen, et al.
(author)
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Characterizing Performance of Freshwater Wetland Methane Models Across Time Scales at FLUXNET-CH4 Sites Using Wavelet Analyses
- 2023
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In: Journal of Geophysical Research: Biogeosciences. - 2169-8953. ; 128:11
-
Journal article (peer-reviewed)abstract
- Process-based land surface models are important tools for estimating global wetland methane (CH4) emissions and projecting their behavior across space and time. So far there are no performance assessments of model responses to drivers at multiple time scales. In this study, we apply wavelet analysis to identify the dominant time scales contributing to model uncertainty in the frequency domain. We evaluate seven wetland models at 23 eddy covariance tower sites. Our study first characterizes site-level patterns of freshwater wetland CH4 fluxes (FCH4) at different time scales. A Monte Carlo approach was developed to incorporate flux observation error to avoid misidentification of the time scales that dominate model error. Our results suggest that (a) significant model-observation disagreements are mainly at multi-day time scales (<15 days); (b) most of the models can capture the CH4 variability at monthly and seasonal time scales (>32 days) for the boreal and Arctic tundra wetland sites but have significant bias in variability at seasonal time scales for temperate and tropical/subtropical sites; (c) model errors exhibit increasing power spectrum as time scale increases, indicating that biases at time scales <5 days could contribute to persistent systematic biases on longer time scales; and (d) differences in error pattern are related to model structure (e.g., proxy of CH4 production). Our evaluation suggests the need to accurately replicate FCH4 variability, especially at short time scales, in future wetland CH4 model developments.
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| 19. |
- 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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