2023
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Pan-Arctic soil element bioavailability estimations
Peter Stimmler,
Mathias Goeckede,
Bo Elberling,
Susan M. Natali,
Peter Kuhry,
Nia Perron,
Fabrice Lacroix,
Gustaf Hugelius,
Oliver Sonnentag,
Jens Strauß,
C. Minions,
Michael Sommer,
Jörg Schaller
Earth System Science Data, Volume 15, Issue 3
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 (https://doi.org/10.17617/3.8KGQUN, Schaller and Goeckede, 2022).
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Evaluating photosynthetic activity across Arctic-Boreal land cover types using solar-induced fluorescence
Rui Cheng,
Troy S. Magney,
Erica L Orcutt,
Zoe Pierrat,
Philipp Köhler,
David R. Bowling,
M. Syndonia Bret‐Harte,
Eugénie Euskirchen,
Martin Jung,
Hideki Kobayashi,
A. V. Rocha,
Oliver Sonnentag,
J. Stutz,
Sophia Walther,
Donatella Zona,
Christian Frankenberg
Environmental Research Letters, Volume 17, Issue 11
Abstract Photosynthesis of terrestrial ecosystems in the Arctic-Boreal region is a critical part of the global carbon cycle. Solar-induced chlorophyll Fluorescence (SIF), a promising proxy for photosynthesis with physiological insight, has been used to track gross primary production (GPP) at regional scales. Recent studies have constructed empirical relationships between SIF and eddy covariance-derived GPP as a first step to predicting global GPP. However, high latitudes pose two specific challenges: (a) Unique plant species and land cover types in the Arctic–Boreal region are not included in the generalized SIF-GPP relationship from lower latitudes, and (b) the complex terrain and sub-pixel land cover further complicate the interpretation of the SIF-GPP relationship. In this study, we focused on the Arctic-Boreal vulnerability experiment (ABoVE) domain and evaluated the empirical relationships between SIF for high latitudes from the TROPOspheric Monitoring Instrument (TROPOMI) and a state-of-the-art machine learning GPP product (FluxCom). For the first time, we report the regression slope, linear correlation coefficient, and the goodness of the fit of SIF-GPP relationships for Arctic-Boreal land cover types with extensive spatial coverage. We found several potential issues specific to the Arctic-Boreal region that should be considered: (a) unrealistically high FluxCom GPP due to the presence of snow and water at the subpixel scale; (b) changing biomass distribution and SIF-GPP relationship along elevational gradients, and (c) limited perspective and misrepresentation of heterogeneous land cover across spatial resolutions. Taken together, our results will help improve the estimation of GPP using SIF in terrestrial biosphere models and cope with model-data uncertainties in the Arctic-Boreal region.
Abstract Transpiration is a globally important component of evapotranspiration. Careful upscaling of transpiration from point measurements is thus crucial for quantifying water and energy fluxes. In spatially heterogeneous landscapes common across the boreal biome, upscaled transpiration estimates are difficult to determine due to variation in local environmental conditions (e.g., basal area, soil moisture, permafrost). Here, we sought to determine stand‐level attributes that influence transpiration scalars for a forested boreal peatland complex consisting of sparsely treed wetlands and densely treed permafrost plateaus as land cover types. The objectives were to quantify spatial and temporal variability in stand‐level transpiration, and to identify sources of uncertainty when scaling point measurements to the stand‐level. Using heat ratio method sap flow sensors, we determined sap velocity for black spruce and tamarack for 2‐week periods during peak growing season in 2013, 2017 and 2018. We found greater basal area, drier soils, and the presence of permafrost increased daily sap velocity in individual trees, suggesting that local environmental conditions are important in dictating sap velocity. When sap velocity was scaled to stand‐level transpiration using gridded 20 × 20 m resolution data across the ~10 ha Scotty Creek ForestGEO plot, we observed significant differences in daily plot transpiration among years (0.17–0.30 mm), and across land cover types. Daily transpiration was lowest in grid‐cells with sparsely treed wetlands compared to grid‐cells with well‐drained and densely treed permafrost plateaus, where daily transpiration reached 0.80 mm, or 30% of the daily evapotranspiration. When transpiration scalars (i.e., sap velocity) were not specific to the different land cover types (i.e., permafrost plateaus and wetlands), scaled stand‐level transpiration was overestimated by 42%. To quantify the relative contribution of tree transpiration to ecosystem evapotranspiration, we recommend that sampling designs stratify across local environmental conditions to accurately represent variation associated with land cover types, especially with different hydrological functioning as encountered in rapidly thawing boreal peatland complexes.
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Modeled production, oxidation, and transport processes of wetland methane emissions in temperate, boreal, and Arctic regions
Masahito Ueyama,
Sara Knox,
Kyle Delwiche,
Sheel Bansal,
William J. Riley,
Dennis Baldocchi,
Takashi Hirano,
Gavin McNicol,
K. V. Schäfer,
Lisamarie Windham‐Myers,
Benjamin Poulter,
Robert B. Jackson,
Kuang‐Yu Chang,
Jiquen Chen,
Housen Chu,
Ankur R. Desai,
Sébastien Gogo,
Hiroyasu Iwata,
Minseok Kang,
Ivan Mammarella,
Matthias Peichl,
Oliver Sonnentag,
Eeva‐Stiina Tuittila,
Youngryel Ryu,
Eugénie Euskirchen,
Mathias Göckede,
Adrien Jacotot,
Mats Nilsson,
Torsten Sachs
Global Change Biology, Volume 29, Issue 8
Wetlands are the largest natural source of methane (CH4 ) to the atmosphere. The eddy covariance method provides robust measurements of net ecosystem exchange of CH4 , but interpreting its spatiotemporal variations is challenging due to the co-occurrence of CH4 production, oxidation, and transport dynamics. Here, we estimate these three processes using a data-model fusion approach across 25 wetlands in temperate, boreal, and Arctic regions. Our data-constrained model-iPEACE-reasonably reproduced CH4 emissions at 19 of the 25 sites with normalized root mean square error of 0.59, correlation coefficient of 0.82, and normalized standard deviation of 0.87. Among the three processes, CH4 production appeared to be the most important process, followed by oxidation in explaining inter-site variations in CH4 emissions. Based on a sensitivity analysis, CH4 emissions were generally more sensitive to decreased water table than to increased gross primary productivity or soil temperature. For periods with leaf area index (LAI) of ≥20% of its annual peak, plant-mediated transport appeared to be the major pathway for CH4 transport. Contributions from ebullition and diffusion were relatively high during low LAI (<20%) periods. The lag time between CH4 production and CH4 emissions tended to be short in fen sites (3 ± 2 days) and long in bog sites (13 ± 10 days). Based on a principal component analysis, we found that parameters for CH4 production, plant-mediated transport, and diffusion through water explained 77% of the variance in the parameters across the 19 sites, highlighting the importance of these parameters for predicting wetland CH4 emissions across biomes. These processes and associated parameters for CH4 emissions among and within the wetlands provide useful insights for interpreting observed net CH4 fluxes, estimating sensitivities to biophysical variables, and modeling global CH4 fluxes.
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Arctic soil methane sink increases with drier conditions and higher ecosystem respiration
Carolina Voigt,
Anna-Maria Virkkala,
Gabriel Gosselin,
Kathryn A. Bennett,
T. Andrew Black,
Matteo Detto,
Charles Chevrier-Dion,
Georg Guggenberger,
Wasi Hashmi,
Leonie Kohl,
Dan Kou,
Charlotte Marquis,
Philip Marsh,
Maija E. Marushchak,
Zoran Nesic,
Hannu Nykänen,
Taija Saarela,
Leopold Sauheitl,
Branden Walker,
Niels Weiss,
Evan J. Wilcox,
Oliver Sonnentag
Nature Climate Change
Abstract Arctic wetlands are known methane (CH 4 ) emitters but recent studies suggest that the Arctic CH 4 sink strength may be underestimated. Here we explore the capacity of well-drained Arctic soils to consume atmospheric CH 4 using >40,000 hourly flux observations and spatially distributed flux measurements from 4 sites and 14 surface types. While consumption of atmospheric CH 4 occurred at all sites at rates of 0.092 ± 0.011 mgCH 4 m −2 h −1 (mean ± s.e.), CH 4 uptake displayed distinct diel and seasonal patterns reflecting ecosystem respiration. Combining in situ flux data with laboratory investigations and a machine learning approach, we find biotic drivers to be highly important. Soil moisture outweighed temperature as an abiotic control and higher CH 4 uptake was linked to increased availability of labile carbon. Our findings imply that soil drying and enhanced nutrient supply will promote CH 4 uptake by Arctic soils, providing a negative feedback to global climate change.
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Carbon uptake in Eurasian boreal forests dominates the high‐latitude net ecosystem carbon budget
Jennifer D. Watts,
Mary Farina,
J. S. Kimball,
Luke Schiferl,
Zhihua Liu,
Kyle A. Arndt,
Donatella Zona,
Ashley P. Ballantyne,
Eugénie Euskirchen,
Frans-Jan W. Parmentier,
Manuel Helbig,
Oliver Sonnentag,
Torbern Tagesson,
Janne Rinne,
Hiroki Ikawa,
Masahito Ueyama,
Hideki Kobayashi,
Torsten Sachs,
Daniel F. Nadeau,
John Kochendorfer,
Marcin Jackowicz-Korczyński,
Anna‐Maria Virkkala,
Mika Aurela,
R. Commane,
Brendan Byrne,
Leah Birch,
Matthew S. Johnson,
Nima Madani,
Brendan M. Rogers,
Jinyang Du,
Arthur Endsley,
K. E. Savage,
B. Poulter,
Zhen Zhang,
L. Bruhwiler,
Charles E. Miller,
Scott J. Goetz,
Walter C. Oechel
Global Change Biology, Volume 29, Issue 7
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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Pan‐Arctic soil moisture control on tundra carbon sequestration and plant productivity
Donatella Zona,
Peter M. Lafleur,
Koen Hufkens,
Beniamino Gioli,
Barbara Bailey,
George Burba,
Eugénie Euskirchen,
Jennifer D. Watts,
Kyle A. Arndt,
Mary Farina,
J. S. Kimball,
Martin Heimann,
Mathias Goeckede,
Martijn Pallandt,
Torben R. Christensen,
Mikhail Mastepanov,
Efrén López‐Blanco,
A.J. Dolman,
R. Commane,
Charles E. Miller,
Josh Hashemi,
Lars Kutzbach,
David Holl,
Julia Boike,
Christian Wille,
Torsten Sachs,
Aram Kalhori,
Elyn Humphreys,
Oliver Sonnentag,
Gesa Meyer,
Gabriel Gosselin,
Philip Marsh,
Walter C. Oechel
Global Change Biology, Volume 29, Issue 5
Long-term atmospheric CO2 concentration records have suggested a reduction in the positive effect of warming on high-latitude carbon uptake since the 1990s. A variety of mechanisms have been proposed to explain the reduced net carbon sink of northern ecosystems with increased air temperature, including water stress on vegetation and increased respiration over recent decades. However, the lack of consistent long-term carbon flux and in situ soil moisture data has severely limited our ability to identify the mechanisms responsible for the recent reduced carbon sink strength. In this study, we used a record of nearly 100 site-years of eddy covariance data from 11 continuous permafrost tundra sites distributed across the circumpolar Arctic to test the temperature (expressed as growing degree days, GDD) responses of gross primary production (GPP), net ecosystem exchange (NEE), and ecosystem respiration (ER) at different periods of the summer (early, peak, and late summer) including dominant tundra vegetation classes (graminoids and mosses, and shrubs). We further tested GPP, NEE, and ER relationships with soil moisture and vapor pressure deficit to identify potential moisture limitations on plant productivity and net carbon exchange. Our results show a decrease in GPP with rising GDD during the peak summer (July) for both vegetation classes, and a significant relationship between the peak summer GPP and soil moisture after statistically controlling for GDD in a partial correlation analysis. These results suggest that tundra ecosystems might not benefit from increased temperature as much as suggested by several terrestrial biosphere models, if decreased soil moisture limits the peak summer plant productivity, reducing the ability of these ecosystems to sequester carbon during the summer.
Abstract Arctic-boreal regions are experiencing major anthropogenic disturbances in addition to intensifying natural disturbance regimes as a consequence of climate change. Oil and natural gas (OG) activities are extensive in the Arctic-boreal region of western North America, a large portion of which is underlain by permafrost. The total number and distribution of OG wells and their potential fate remain unclear. Consequently, the collective impacts of OG wells on natural and cultural resources, human health and emissions of methane (CH 4 ), are poorly understood. Using public OG well databases, we analysed the distribution of OG wells drilled between 1984 and 2018 across the Core Domain of the NASA Arctic-Boreal Vulnerability Experiment (‘ABoVE domain’). We identified 242 007 OG wells drilled as of 2018 in the ABoVE domain, of which almost two thirds are now inactive or abandoned OG wells. We found that annual drilling has increased from 269 to 8599 OG wells from 1984 to 2014 with around 1000, 700 and 1800 OG wells drilled annually in evergreen forest, deciduous forest and herbaceous land cover types, respectively. 65 588 OG well sites were underlain by permafrost in 2012. Fugitive CH 4 emissions from active and abandoned OG wells drilled in the Canadian portion of the ABoVE domain accounted for approximately 13% of the total anthropogenic CH 4 emissions in Canada in 2018. Our analysis identified OG wells as an anthropogenic disturbance in the ABoVE domain with potentially non-negligible consequences to local populations, ecosystems, and the climate system.
Abstract. The carbon cycle in Arctic-boreal regions (ABR) is an important component of the planetary carbon balance, with growing concerns about the consequences of ABR warming on the global climate system. The greatest uncertainty in annual carbon dioxide (CO2) budgets exists during the non-growing season, primarily due to challenges with data availability and limited spatial coverage in measurements. The goal of this study was to determine the main environmental controls of non-growing season CO2 fluxes in ABR over a latitudinal gradient (45° N to 69° N) featuring four different ecosystem types: closed-crown coniferous boreal forest, open-crown coniferous boreal forest, erect-shrub tundra, and prostrate-shrub tundra. CO2 fluxes calculated using a snowpack diffusion gradient method (n = 560) ranged from 0 to 1.05 gC m2 day-1. To assess the dominant environmental controls governing CO2 fluxes, a Random Forest machine learning approach was used. We identified that soil temperature as the main control of non-growing season CO2 fluxes with 68 % of relative model importance, except when soil liquid water occurred during zero degree Celsius curtain conditions (Tsoil ≈ 0 °C and liquid water coexists with ice in soil pores). Under zero-curtain conditions, liquid water content became the main control of CO2 fluxes with 87 % of relative model importance. We observed exponential regressions between CO2 fluxes and soil temperature (RMSE = 0.024 gC m-2 day-1) in frozen soils, as well as liquid water content (RMSE = 0.137 gC m-2 day-1) in zero-curtain conditions. This study is showing the role of several variables on the spatio-temporal variability of CO2 fluxes in ABR during the non-growing season and highlight that the complex vegetation-snow-soil interactions in northern environments must be considered when studying what drives the spatial variability of soil carbon emission during the non-growing season.
2022
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Range shifts in a foundation sedge potentially induce large Arctic ecosystem carbon losses and gains
Salvatore R. Curasi,
Ned Fetcher,
Rebecca E. Hewitt,
Peter M. Lafleur,
M. M. Loranty,
Michelle C. Mack,
Jeremy L. May,
Isla H. Myers‐Smith,
Susan M. Natali,
Steven F. Oberbauer,
Thomas C. Parker,
Oliver Sonnentag,
S. A. Vargas Zesati,
Stan D. Wullschleger,
A. V. Rocha
Environmental Research Letters, Volume 17, Issue 4
Abstract Foundation species have disproportionately large impacts on ecosystem structure and function. As a result, future changes to their distribution may be important determinants of ecosystem carbon (C) cycling in a warmer world. We assessed the role of a foundation tussock sedge ( Eriophorum vaginatum ) as a climatically vulnerable C stock using field data, a machine learning ecological niche model, and an ensemble of terrestrial biosphere models (TBMs). Field data indicated that tussock density has decreased by ~0.97 tussocks per m2 over the past ~38 years on Alaska’s North Slope from ~1981 to 2019. This declining trend is concerning because tussocks are a large Arctic C stock, which enhances soil organic layer C stocks by 6.9% on average and represents 745 Tg C across our study area. By 2100, we project that changes in tussock density may decrease the tussock C stock by 41% in regions where tussocks are currently abundant (e.g. -0.8 tussocks per m2 and -85 Tg C on the North Slope) and may increase the tussock C stock by 46% in regions where tussocks are currently scarce (e.g. +0.9 tussocks per m2 and +81 Tg C on Victoria Island). These climate-induced changes to the tussock C stock were comparable to, but sometimes opposite in sign, to vegetation C stock changes predicted by an ensemble of TBMs. Our results illustrate the important role of tussocks as a foundation species in determining future Arctic C stocks and highlights the need for better representation of this species in TBMs.
ABSTRACT Simple and robust hydrological modelling is critical for peat studies as water content (θ) and water table depth (d WT) are key controls on many biogeochemical processes. We show that near-surface θ can be a good predictor of θ at any depth and/or d WT in peat. This was achieved by further developing the formulae of an existing model and applying it for Mer Bleue bog (Ontario, Canada) and a permafrost peat plateau at Scotty Creek (Northwest Territories, Canada). Simulated θ dynamics at various depths in hummocks and hollows at both sites matched observations with R2 , Willmott’s index of agreement (d), and normalized Nash-Sutcliffe efficiency coefficient (NNSE), reaching 0.97, 0.95, and 0.86, respectively. Simulated bog WT dynamics matched observations with R2 , d, and NNSE reaching 0.67, 0.87, and 0.72. Our approach circumvents the difficulties of measuring subsurface hydrology and reveals a perspective for large spatial scale estimation of θ and d WT in peat.
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Warming response of peatland CO2 sink is sensitive to seasonality in warming trends
Manuel Helbig,
T. Živković,
Pavel Alekseychik,
Mika Aurela,
Tarek S. El-Madany,
Eugénie Euskirchen,
Lawrence B. Flanagan,
T. J. Griffis,
Paul J. Hanson,
J. Hattakka,
Carole Helfter,
Takashi Hirano,
Elyn Humphreys,
Gérard Kiely,
Randall K. Kolka,
Tuomas Laurila,
Paul Leahy,
Annalea Lohila,
Ivan Mammarella,
Mats Nilsson,
А. В. Панов,
Frans‐Jan W. Parmentier,
Matthias Peichl,
Janne Rinne,
Daniel T. Roman,
Oliver Sonnentag,
Eeva‐Stiina Tuittila,
Masahito Ueyama,
Timo Vesala,
Patrik Vestin,
Simon Weldon,
Per Weslien,
Sönke Zaehle
Nature Climate Change, Volume 12, Issue 8
Peatlands have acted as net CO2 sinks over millennia, exerting a global climate cooling effect. Rapid warming at northern latitudes, where peatlands are abundant, can disturb their CO2 sink function. Here we show that sensitivity of peatland net CO2 exchange to warming changes in sign and magnitude across seasons, resulting in complex net CO2 sink responses. We use multiannual net CO2 exchange observations from 20 northern peatlands to show that warmer early summers are linked to increased net CO2 uptake, while warmer late summers lead to decreased net CO2 uptake. Thus, net CO2 sinks of peatlands in regions experiencing early summer warming, such as central Siberia, are more likely to persist under warmer climate conditions than are those in other regions. Our results will be useful to improve the design of future warming experiments and to better interpret large-scale trends in peatland net CO2 uptake over the coming few decades.
Adapting to climate change as a consequence of increasing greenhouse gas (GHG) emissions is of paramount importance in the near future. Therefore, recognition of spatial and temporal variations of atmospheric carbon dioxide (CO 2 ) concentration both globally and regionally is critical. The goal of this study was to analyze spatio-temporal patterns of atmospheric CO 2 concentration (XCO 2 ) for Iran over the period from 2003 to 2020 to shed light on the role of various biotic and abiotic controls. First, by using atmospheric XCO 2 data obtained from the SCIAMACHY and GOSAT satellite instruments, a series of spatio-temporal XCO 2 distribution maps were developed. Second, to understand of the potential causes underlying the spatio-temporal distributions in XCO 2 , the correlations between monthly XCO 2 and vegetation abundance, air temperature, precipitation, and fossil fuel CO 2 emissions were examined. The spatio-temporal patterns in XCO 2 indicated an increasing gradient of XCO 2 from north to south and from west to east in Iran, with the highest XCO 2 in the central, southern and southeastern parts of the country. The findings revealed that XCO 2 was negatively correlated with vegetation abundance and precipitation, and positively correlated with air temperature in different months from 2003 to 2020. Among the different explanatory variables, vegetation abundance explained most of the spatial variation in XCO 2 . Furthermore, in spring (April and May), which has the highest amount of vegetation abundance and precipitation, biotic controls had a substantial impact on the diffusion and absorption of XCO 2 in the northern and northwestern parts of Iran. Our results suggest that CO 2 is moved from the center of Iran to the outer parts of the country in summer (July–September) and vice-versa in winter (January–March). Our findings provide policy- and decision makers with crucial information regarding the spatio-temporal dynamics in XCO 2 to reduce and, ultimately, halt its increase. • Over the spatial distribution of XCO 2 , biotic controls such as vegetation abundance were found to be the primary controlling factor especially in spring. • The results revealed a significant positive correlation between XCO 2 and CO 2 emissions only in temporal correlation but not in the spatial correlation. • The spatio-temporal distribution maps show the maximum XCO 2 in south and southeast of Iran, while the highest net increase of XCO 2 appeared in the west and north of Iran which are densely populated.
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Snowmelt Water Use at Transpiration Onset: Phenology, Isotope Tracing, and Tree Water Transit Time
Magali F. Nehemy,
Jason Maillet,
Nia Perron,
Christoforos Pappas,
Oliver Sonnentag,
Jennifer L. Baltzer,
Colin P. Laroque,
Jeffrey J. McDonnell,
Magali F. Nehemy,
Jason Maillet,
Nia Perron,
Christoforos Pappas,
Oliver Sonnentag,
Jennifer L. Baltzer,
Colin P. Laroque,
Jeffrey J. McDonnell
Water Resources Research, Volume 58, Issue 9
Studies of tree water source partitioning have primarily focused on the growing season. However, little is yet known about the source of transpiration before, during, and after snowmelt when trees rehydrate and recommence transpiration in the spring. This study investigates tree water use during spring snowmelt following tree's winter stem shrinkage. We document the source of transpiration of three boreal forest tree species—Pinus banksiana, Picea mariana, and Larix laricina—by combining observations of weekly isotopic signatures (δ18O and δ2H) of xylem, soil water, rainfall and snowmelt with measurements of soil moisture dynamics, snow depth and high-resolution temporal measurements of stem radius changes and sap flow. Our data shows that the onset of stem rehydration and transpiration overlaps with snowmelt for evergreens. During rehydration and transpiration onset, xylem water at the canopy reflected a constant pre-melt isotopic signature likely showing late fall conditions. As snowmelt infiltrates the soil and recharges the soil matrix, soil water shows a rapid isotopic shift to depleted-snowmelt water values. While there was an overlap between snowmelt and transpiration timing, xylem and soil water isotopic values did not overlap during transpiration onset. Our data showed 1–2-week delay in the shift in xylem water from pre-melt to clear snowmelt-depleted water signatures in evergreen species. This delay appears to be controlled by tree water transit time that was in the order of 9–18 days. Our study shows that snowmelt is a key source for stem rehydration and transpiration in the boreal forest during spring onset.
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Snowmelt Water Use at Transpiration Onset: Phenology, Isotope Tracing, and Tree Water Transit Time
Magali F. Nehemy,
Jason Maillet,
Nia Perron,
Christoforos Pappas,
Oliver Sonnentag,
Jennifer L. Baltzer,
Colin P. Laroque,
Jeffrey J. McDonnell,
Magali F. Nehemy,
Jason Maillet,
Nia Perron,
Christoforos Pappas,
Oliver Sonnentag,
Jennifer L. Baltzer,
Colin P. Laroque,
Jeffrey J. McDonnell
Water Resources Research, Volume 58, Issue 9
Studies of tree water source partitioning have primarily focused on the growing season. However, little is yet known about the source of transpiration before, during, and after snowmelt when trees rehydrate and recommence transpiration in the spring. This study investigates tree water use during spring snowmelt following tree's winter stem shrinkage. We document the source of transpiration of three boreal forest tree species—Pinus banksiana, Picea mariana, and Larix laricina—by combining observations of weekly isotopic signatures (δ18O and δ2H) of xylem, soil water, rainfall and snowmelt with measurements of soil moisture dynamics, snow depth and high-resolution temporal measurements of stem radius changes and sap flow. Our data shows that the onset of stem rehydration and transpiration overlaps with snowmelt for evergreens. During rehydration and transpiration onset, xylem water at the canopy reflected a constant pre-melt isotopic signature likely showing late fall conditions. As snowmelt infiltrates the soil and recharges the soil matrix, soil water shows a rapid isotopic shift to depleted-snowmelt water values. While there was an overlap between snowmelt and transpiration timing, xylem and soil water isotopic values did not overlap during transpiration onset. Our data showed 1–2-week delay in the shift in xylem water from pre-melt to clear snowmelt-depleted water signatures in evergreen species. This delay appears to be controlled by tree water transit time that was in the order of 9–18 days. Our study shows that snowmelt is a key source for stem rehydration and transpiration in the boreal forest during spring onset.
At the edge of alpine and Arctic ecosystems all over the world, a transition zone exists beyond which it is either infeasible or unfavorable for trees to exist, colloquially identified as the treeline. We explore the possibility of a thermodynamic basis behind this demarcation in vegetation by considering ecosystems as open systems driven by thermodynamic advantage-defined by vegetation's ability to dissipate heat from the earth's surface to the air above the canopy. To deduce whether forests would be more thermodynamically advantageous than existing ecosystems beyond treelines, we construct and examine counterfactual scenarios in which trees exist beyond a treeline instead of the existing alpine meadow or Arctic tundra. Meteorological data from the Italian Alps, United States Rocky Mountains, and Western Canadian Taiga-Tundra are used as forcing for model computation of ecosystem work and temperature gradients at sites on both sides of each treeline with and without trees. Model results indicate that the alpine sites do not support trees beyond the treeline, as their presence would result in excessive CO[Formula: see text] loss and extended periods of snowpack due to temperature inversions (i.e., positive temperature gradient from the earth surface to the atmosphere). Further, both Arctic and alpine sites exhibit negative work resulting in positive feedback between vegetation heat dissipation and temperature gradient, thereby extending the duration of temperature inversions. These conditions demonstrate thermodynamic infeasibility associated with the counterfactual scenario of trees existing beyond a treeline. Thus, we conclude that, in addition to resource constraints, a treeline is an outcome of an ecosystem's ability to self-organize towards the most advantageous vegetation structure facilitated by thermodynamic feasibility.
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Earlier snowmelt may lead to late season declines in plant productivity and carbon sequestration in Arctic tundra ecosystems
Donatella Zona,
Peter M. Lafleur,
Koen Hufkens,
Barbara Bailey,
Beniamino Gioli,
George Burba,
Jordan P. Goodrich,
A. K. Liljedahl,
Eugénie Euskirchen,
Jennifer D. Watts,
Mary Farina,
J. S. Kimball,
Martin Heimann,
Mathias Göckede,
Martijn Pallandt,
Torben R. Christensen,
Mikhail Mastepanov,
Efrén López‐Blanco,
Marcin Jackowicz-Korczyński,
A. J. Dolman,
Luca Belelli Marchesini,
R. Commane,
Steven C. Wofsy,
Charles E. Miller,
David A. Lipson,
Josh Hashemi,
Kyle A. Arndt,
Lars Kutzbach,
David Holl,
Julia Boike,
Christian Wille,
Torsten Sachs,
Aram Kalhori,
Xingyu Song,
Xiaofeng Xu,
Elyn Humphreys,
C. Koven,
Oliver Sonnentag,
Gesa Meyer,
Gabriel Gosselin,
Philip Marsh,
Walter C. Oechel
Scientific Reports, Volume 12, Issue 1
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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The ABCflux database: Arctic–boreal CO<sub>2</sub> flux observations and ancillary information aggregated to monthly time steps across terrestrial ecosystems
Anna-Maria Virkkala,
Susan M. Natali,
Brendan M. Rogers,
Jennifer D. Watts,
K. E. Savage,
Sara June Connon,
Marguerite Mauritz,
Edward A. G. Schuur,
D. L. Peter,
C. Minions,
Julia Nojeim,
R. Commane,
Craig A. Emmerton,
Mathias Goeckede,
Manuel Helbig,
David Holl,
Hiroyasu Iwata,
Hideki Kobayashi,
Pasi Kolari,
Efrén López‐Blanco,
Maija E. Marushchak,
Mikhail Mastepanov,
Lutz Merbold,
Frans‐Jan W. Parmentier,
Matthias Peichl,
Torsten Sachs,
Oliver Sonnentag,
Masahito Ueyama,
Carolina Voigt,
Mika Aurela,
Julia Boike,
Gerardo Celis,
Namyi Chae,
Torben R. Christensen,
M. Syndonia Bret‐Harte,
Sigrid Dengel,
A. J. Dolman,
C. Edgar,
Bo Elberling,
Eugénie Euskirchen,
Achim Grelle,
Juha Hatakka,
Elyn Humphreys,
Järvi Järveoja,
Ayumi Kotani,
Lars Kutzbach,
Tuomas Laurila,
Annalea Lohila,
Ivan Mammarella,
Yukiko Matsuura,
Gesa Meyer,
Mats Nilsson,
Steven F. Oberbauer,
Sang Jong Park,
Roman E. Petrov,
А. С. Прокушкин,
Christopher Schulze,
Vincent L. St. Louis,
Eeva‐Stiina Tuittila,
Juha‐Pekka Tuovinen,
William L. Quinton,
Andrej Varlagin,
Donatella Zona,
Viacheslav I. Zyryanov
Earth System Science Data, Volume 14, Issue 1
Abstract. Past efforts to synthesize and quantify the magnitude and change in carbon dioxide (CO2) fluxes in terrestrial ecosystems across the rapidly warming Arctic–boreal zone (ABZ) have provided valuable information but were limited in their geographical and temporal coverage. Furthermore, these efforts have been based on data aggregated over varying time periods, often with only minimal site ancillary data, thus limiting their potential to be used in large-scale carbon budget assessments. To bridge these gaps, we developed a standardized monthly database of Arctic–boreal CO2 fluxes (ABCflux) that aggregates in situ measurements of terrestrial net ecosystem CO2 exchange and its derived partitioned component fluxes: gross primary productivity and ecosystem respiration. The data span from 1989 to 2020 with over 70 supporting variables that describe key site conditions (e.g., vegetation and disturbance type), micrometeorological and environmental measurements (e.g., air and soil temperatures), and flux measurement techniques. Here, we describe these variables, the spatial and temporal distribution of observations, the main strengths and limitations of the database, and the potential research opportunities it enables. In total, ABCflux includes 244 sites and 6309 monthly observations; 136 sites and 2217 monthly observations represent tundra, and 108 sites and 4092 observations represent the boreal biome. The database includes fluxes estimated with chamber (19 % of the monthly observations), snow diffusion (3 %) and eddy covariance (78 %) techniques. The largest number of observations were collected during the climatological summer (June–August; 32 %), and fewer observations were available for autumn (September–October; 25 %), winter (December–February; 18 %), and spring (March–May; 25 %). ABCflux can be used in a wide array of empirical, remote sensing and modeling studies to improve understanding of the regional and temporal variability in CO2 fluxes and to better estimate the terrestrial ABZ CO2 budget. ABCflux is openly and freely available online (Virkkala et al., 2021b, https://doi.org/10.3334/ORNLDAAC/1934).
Future warming of the Arctic not only threatens to destabilize the enormous pool of organic carbon accumulated in permafrost soils but may also mobilize elements such as calcium (Ca) or silicon (Si). While for Greenlandic soils, it was recently shown that both elements may have a strong effect on carbon dioxide (CO 2 ) production with Ca strongly decreasing and Si increasing CO 2 production, little is known about the effects of Si and Ca on carbon cycle processes in soils from Siberia, the Canadian Shield, or Alaska. In this study, we incubated five different soils (rich organic soil from the Canadian Shield and from Siberia (one from the top and one from the deeper soil layer) and one acidic and one non-acidic soil from Alaska) for 6 months under both drained and waterlogged conditions and at different Ca and amorphous Si (ASi) concentrations. Our results show a strong decrease in soil CO 2 production for all soils under both drained and waterlogged conditions with increasing Ca concentrations. The ASi effect was not clear across the different soils used, with soil CO 2 production increasing, decreasing, or not being significantly affected depending on the soil type and if the soils were initially drained or waterlogged. We found no methane production in any of the soils regardless of treatment. Taking into account the predicted change in Si and Ca availability under a future warmer Arctic climate, the associated fertilization effects would imply potentially lower greenhouse gas production from Siberia and slightly increased greenhouse gas emissions from the Canadian Shield. Including Ca as a controlling factor for Arctic soil CO 2 production rates may, therefore, reduces uncertainties in modeling future scenarios on how Arctic regions may respond to climate change.
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What explains the year-to-year variation in growing season timing of boreal black spruce forests?
Mariam El-Amine,
Alexandre Roy,
Franziska Koebsch,
Jennifer L. Baltzer,
Alan Barr,
Andrew Black,
Hiroki Ikawa,
Hiroyasu Iwata,
Hideki Kobayashi,
Masahito Ueyama,
Oliver Sonnentag
Agricultural and Forest Meteorology, Volume 324
Amplified climate warming in high latitudes is expected to affect growing season timing of the vast boreal biome. It is unclear whether the presence of permafrost (perennially frozen ground) might have an influence on changes in growing season timing. This study examined how different environmental variables explained, either directly or indirectly, the variation in growing season timing of boreal forest stands with and without permafrost. We expected that environmental variables explaining the variation in growing season timing differed or had different explanatory power depending on permafrost presence or absence. The growing season was delineated from daily gross primary productivity (GPP) time series derived from 40 site-year data of net ecosystem carbon dioxide exchange measured with eddy covariance techniques over five black spruce (Picea mariana [Mill.])-dominated boreal forest stands in North America. In permafrost-free forest stands, a combination of start in canopy ‘green-up’ in spring and the timing of air and soil temperature increasing above freezing explained the start-of-season (SOSGPP). Results from commonality analysis and structural equation modeling suggest that canopy ‘green-up’ and air temperature directly affected SOSGPP in permafrost-free forest stands. In addition, soil temperature acted as mediator for an indirect effect of air temperature on SOSGPP. In contrast, none of the environmental variables, or their combination, explained the variation in SOSGPP in forest stands with permafrost. The explanatory power of environmental variables was more consistent regarding the end-of-season (EOSGPP). In both, forest stands with and without permafrost, EOSGPP was directly explained by mean soil water content in the fall and the first day of continuous snowpack formation. A better understanding how environmental variables control SOSGPP and EOSGPP in forest stands with and without permafrost will help to refine parameterizations of the boreal biome in Earth system models.
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Causality guided machine learning model on wetland CH4 emissions across global wetlands
Kunxiaojia Yuan,
Qing Zhu,
Fa Li,
William J. Riley,
M. S. Torn,
Housen Chu,
Gavin McNicol,
Min Chen,
Sara Knox,
Kyle Delwiche,
Huayi Wu,
Dennis Baldocchi,
Hengbo Ma,
Ankur R. Desai,
Jiquan Chen,
Torsten Sachs,
Masahito Ueyama,
Oliver Sonnentag,
Manuel Helbig,
Eeva‐Stiina Tuittila,
Gerald Jurasinski,
Franziska Koebsch,
David I. Campbell,
Hans Peter Schmid,
Annalea Lohila,
Mathias Goeckede,
Mats Nilsson,
Thomas Friborg,
Joachim Jansen,
Donatella Zona,
Eugénie Euskirchen,
Eric J. Ward,
Gil Bohrer,
Zhenong Jin,
Licheng Liu,
Hiroyasu Iwata,
Jordan P. Goodrich,
Robert B. Jackson
Agricultural and Forest Meteorology, Volume 324
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 +1°C warming scenario when causality constraints were considered. These results highlight the significant role of causality in modeling wetland CH4 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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Permafrost Landscape History Shapes Fluvial Chemistry, Ecosystem Carbon Balance, and Potential Trajectories of Future Change
Scott Zolkos,
Suzanne E. Tank,
Steven V. Kokelj,
Robert G. Striegl,
Sarah Shakil,
Carolina Voigt,
Oliver Sonnentag,
William L. Quinton,
Edward A. G. Schuur,
Donatella Zona,
Peter M. Lafleur,
Ryan C. Sullivan,
Masahito Ueyama,
David P. Billesbach,
David Cook,
Elyn Humphreys,
Philip Marsh
Global Biogeochemical Cycles, Volume 36, Issue 9
Abstract Intensifying permafrost thaw alters carbon cycling by mobilizing large amounts of terrestrial substrate into aquatic ecosystems. Yet, few studies have measured aquatic carbon fluxes and constrained drivers of ecosystem carbon balance across heterogeneous Arctic landscapes. Here, we characterized hydrochemical and landscape controls on fluvial carbon cycling, quantified fluvial carbon fluxes, and estimated fluvial contributions to ecosystem carbon balance across 33 watersheds in four ecoregions in the continuous permafrost zone of the western Canadian Arctic: unglaciated uplands, ice‐rich moraine, and organic‐rich lowlands and till plains. Major ions, stable isotopes, and carbon speciation and fluxes revealed patterns in carbon cycling across ecoregions defined by terrain relief and accumulation of organics. In previously unglaciated mountainous watersheds, bicarbonate dominated carbon export (70% of total) due to chemical weathering of bedrock. In lowland watersheds, where soil organic carbon stores were largest, lateral transport of dissolved organic carbon (50%) and efflux of biotic CO 2 (25%) dominated. In watersheds affected by thaw‐induced mass wasting, erosion of ice‐rich tills enhanced chemical weathering and increased particulate carbon fluxes by two orders of magnitude. From an ecosystem carbon balance perspective, fluvial carbon export in watersheds not affected by thaw‐induced wasting was, on average, equivalent to 6%–16% of estimated net ecosystem exchange (NEE). In watersheds affected by thaw‐induced wasting, fluvial carbon export approached 60% of NEE. Because future intensification of thermokarst activity will amplify fluvial carbon export, determining the fate of carbon across diverse northern landscapes is a priority for constraining trajectories of permafrost region ecosystem carbon balance.
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Vegetation type is an important predictor of the arctic summer land surface energy budget
Jacqueline Oehri,
Gabriela Schaepman‐Strub,
Jin‐Soo Kim,
Raleigh Grysko,
Heather Kropp,
Inge Grünberg,
Vitalii Zemlianskii,
Oliver Sonnentag,
Eugénie Euskirchen,
Merin Reji Chacko,
Giovanni Muscari,
Peter D. Blanken,
Joshua Dean,
Alcide di Sarra,
R. J. Harding,
Ireneusz Sobota,
Lars Kutzbach,
Elena Plekhanova,
Aku Riihelä,
Julia Boike,
Nathaniel B. Miller,
Jason Beringer,
Efrén López‐Blanco,
Paul C. Stoy,
Ryan C. Sullivan,
Marek Kejna,
Frans‐Jan W. Parmentier,
John A. Gamon,
Mikhail Mastepanov,
Christian Wille,
Marcin Jackowicz-Korczyński,
Dirk Nikolaus Karger,
William L. Quinton,
Jaakko Putkonen,
Dirk van As,
Torben R. Christensen,
Maria Z. Hakuba,
Robert S. Stone,
Stefan Metzger,
Baptiste Vandecrux,
G. V. Frost,
Martin Wild,
Birger Ulf Hansen,
Daniela Meloni,
Florent Dominé,
Mariska te Beest,
Torsten Sachs,
Aram Kalhori,
A. V. Rocha,
Scott Williamson,
S. Crepinsek,
A. L. Atchley,
Richard Essery,
Benjamin R. K. Runkle,
David Holl,
Laura D. Riihimaki,
Hiroyasu Iwata,
Edward A. G. Schuur,
Christopher Cox,
A. A. Grachev,
J. P. McFadden,
Robert S. Fausto,
Mathias Goeckede,
Masahito Ueyama,
Norbert Pirk,
Gijs de Boer,
M. Syndonia Bret‐Harte,
Matti Leppäranta,
Konrad Steffen,
Thomas Friborg,
Atsumu Ohmura,
C. Edgar,
Johan Olofsson,
Scott D. Chambers
Nature Communications, Volume 13, Issue 1
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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Disturbances in North American boreal forest and Arctic tundra: impacts, interactions, and responses
Adrianna C. Foster,
Jonathan Wang,
G. V. Frost,
Scott J. Davidson,
Elizabeth Hoy,
Kevin W. Turner,
Oliver Sonnentag,
Howard E. Epstein,
L. T. Berner,
A. H. Armstrong,
Mary Kang,
Brendan M. Rogers,
Elizabeth M. Campbell,
Kimberley Miner,
Kathleen M. Orndahl,
Laura Bourgeau‐Chavez,
David A. Lutz,
Nancy H. F. French,
Dong Chen,
Jinyang Du,
Tatiana A. Shestakova,
J. K. Shuman,
Ken D. Tape,
Anna-Maria Virkkala,
Christopher Potter,
Scott J. Goetz
Environmental Research Letters, Volume 17, Issue 11
Abstract Ecosystems in the North American Arctic-Boreal Zone (ABZ) experience a diverse set of disturbances associated with wildfire, permafrost dynamics, geomorphic processes, insect outbreaks and pathogens, extreme weather events, and human activity. Climate warming in the ABZ is occurring at over twice the rate of the global average, and as a result the extent, frequency, and severity of these disturbances are increasing rapidly. Disturbances in the ABZ span a wide gradient of spatiotemporal scales and have varying impacts on ecosystem properties and function. However, many ABZ disturbances are relatively understudied and have different sensitivities to climate and trajectories of recovery, resulting in considerable uncertainty in the impacts of climate warming and human land use on ABZ vegetation dynamics and in the interactions between disturbance types. Here we review the current knowledge of ABZ disturbances and their precursors, ecosystem impacts, temporal frequencies, spatial extents, and severity. We also summarize current knowledge of interactions and feedbacks among ABZ disturbances and characterize typical trajectories of vegetation loss and recovery in response to ecosystem disturbance using satellite time-series. We conclude with a summary of critical data and knowledge gaps and identify priorities for future study.
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Impact of measured and simulated tundra snowpack properties on heat transfer
Victoria R. Dutch,
Nick Rutter,
Leanne Wake,
Melody Sandells,
Chris Derksen,
Branden Walker,
Gabriel Gosselin,
Oliver Sonnentag,
Richard Essery,
Richard Kelly,
Phillip Marsh,
Joshua King,
Julia Boike
The Cryosphere, Volume 16, Issue 10
Abstract. Snowpack microstructure controls the transfer of heat to, as well as the temperature of, the underlying soils. In situ measurements of snow and soil properties from four field campaigns during two winters (March and November 2018, January and March 2019) were compared to an ensemble of CLM5.0 (Community Land Model) simulations, at Trail Valley Creek, Northwest Territories, Canada. Snow micropenetrometer profiles allowed for snowpack density and thermal conductivity to be derived at higher vertical resolution (1.25 mm) and a larger sample size (n=1050) compared to traditional snowpit observations (3 cm vertical resolution; n=115). Comparing measurements with simulations shows CLM overestimated snow thermal conductivity by a factor of 3, leading to a cold bias in wintertime soil temperatures (RMSE=5.8 ∘C). Two different approaches were taken to reduce this bias: alternative parameterisations of snow thermal conductivity and the application of a correction factor. All the evaluated parameterisations of snow thermal conductivity improved simulations of wintertime soil temperatures, with that of Sturm et al. (1997) having the greatest impact (RMSE=2.5 ∘C). The required correction factor is strongly related to snow depth (R2=0.77,RMSE=0.066) and thus differs between the two snow seasons, limiting the applicability of such an approach. Improving simulated snow properties and the corresponding heat flux is important, as wintertime soil temperatures are an important control on subnivean soil respiration and hence impact Arctic winter carbon fluxes and budgets.
2021
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Impact of measured and simulated tundra snowpack properties on heat transfer
Victoria R. Dutch,
Nick Rutter,
Leanne Wake,
Melody Sandells,
Chris Derksen,
Branden Walker,
Gabriel Gosselin,
Oliver Sonnentag,
Richard Essery,
Richard Kelly,
Philip Marsh,
Joshua King
Abstract. Snowpack microstructure controls the transfer of heat to, and the temperature of, the underlying soils. In situ measurements of snow and soil properties from four field campaigns during two different winters (March and November 2018, January and March 2019) were compared to an ensemble of CLM5.0 (Community Land Model) simulations, at Trail Valley Creek, Northwest Territories, Canada. Snow MicroPenetrometer profiles allowed snowpack density and thermal conductivity to be derived at higher vertical resolution (1.25 mm) and a larger sample size (n = 1050) compared to traditional snowpit observations (3 cm vertical resolution; n = 115). Comparing measurements with simulations shows CLM overestimated snow thermal conductivity by a factor of 3, leading to a cold bias in wintertime soil temperatures (RMSE = 5.8 °C). Bias-correction of the simulated thermal conductivity (relative to field measurements) improved simulated soil temperatures (RMSE = 2.1 °C). Multiple linear regression shows the required correction factor is strongly related to snow depth (R2 = 0.77, RMSE = 0.066) particularly early in the winter. Furthermore, CLM simulations did not adequately represent the observed high proportions of depth hoar. Addressing uncertainty in simulated snow properties and the corresponding heat flux is important, as wintertime soil temperatures act as a control on subnivean soil respiration, and hence impact Arctic winter carbon fluxes and budgets.
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The Boreal-Arctic Wetland and Lake Dataset (BAWLD)
David Olefeldt,
Mikael Hovemyr,
McKenzie A. Kuhn,
David Bastviken,
Theodore J. Bohn,
John Connolly,
Patrick Crill,
Eugénie Euskirchen,
S. A. Finkelstein,
Hélène Genet,
Guido Grosse,
Lorna I. Harris,
Liam Heffernan,
Manuel Helbig,
Gustaf Hugelius,
Ryan H. S. Hutchins,
Sari Juutinen,
Mark J. Lara,
Avni Malhotra,
Kristen L. Manies,
A. David McGuire,
Susan M. Natali,
J. A. O’Donnell,
Frans‐Jan W. Parmentier,
Aleksi Räsänen,
Christina Schädel,
Oliver Sonnentag,
Maria Strack,
Suzanne E. Tank,
Claire C. Treat,
R. K. Varner,
Tarmo Virtanen,
Rebecca K. Warren,
Jennifer D. Watts
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 Boreal-Arctic 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 × 0.5° 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 × 106 km2 (14 % of domain) with a 95 % confidence interval between 2.8 and 3.8 × 106 km2. Bog, fen, and permafrost bog were the most abundant wetland classes, covering ~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 × 106 km2 (6 % of domain). Low methane-emitting large lakes (> 10 km2) 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 km2) glacial, peatland, and yedoma lakes combined covered 17 % of the total lake area, but contributed disproportionally to the overall spatial uncertainty of lake area with a 95 % confidence interval between 0.15 and 0.38 × 106 km2. Rivers and streams were estimated to cover 0.12 × 106 km2 (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 will 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. Data is freely available at https://doi.org/10.18739/A2C824F9X (Olefeldt et al., 2021).
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FLUXNET-CH<sub>4</sub>: a global, multi-ecosystem dataset and analysis of methane seasonality from freshwater wetlands
Kyle Delwiche,
Sara Knox,
Avni Malhotra,
Etienne Fluet‐Chouinard,
Gavin McNicol,
Sarah Féron,
Zutao Ouyang,
Dario Papale,
Carlo Trotta,
E. Canfora,
You Wei Cheah,
Danielle Christianson,
Ma. Carmelita R. Alberto,
Pavel Alekseychik,
Mika Aurela,
Dennis Baldocchi,
Sheel Bansal,
David P. Billesbach,
Gil Bohrer,
Rosvel Bracho,
Nina Buchmann,
David I. Campbell,
Gerardo Celis,
Jiquan Chen,
Weinan Chen,
Housen Chu,
Higo J. Dalmagro,
Sigrid Dengel,
Ankur R. Desai,
Matteo Detto,
A. J. Dolman,
Elke Eichelmann,
Eugénie Euskirchen,
D. Famulari,
Kathrin Fuchs,
Mathias Goeckede,
Sébastien Gogo,
Mangaliso J. Gondwe,
Jordan P. Goodrich,
Pia Gottschalk,
Scott L. Graham,
Martin Heimann,
Manuel Helbig,
Carole Helfter,
Kyle S. Hemes,
Takashi Hirano,
David Y. Hollinger,
Lukas Hörtnagl,
Hiroyasu Iwata,
Adrien Jacotot,
Gerald Jurasinski,
Minseok Kang,
Kuno Kasak,
John S. King,
Janina Klatt,
Franziska Koebsch,
Ken W. Krauss,
Derrick Y.F. Lai,
Annalea Lohila,
Ivan Mammarella,
Luca Belelli Marchesini,
Giovanni Manca,
Jaclyn Hatala Matthes,
Trofim C. Maximov,
Lutz Merbold,
Bhaskar Mitra,
Timothy H. Morin,
Eiko Nemitz,
Mats Nilsson,
Shuli Niu,
Walter C. Oechel,
Patricia Y. Oikawa,
Kaori Ono,
Matthias Peichl,
Olli Peltola,
M. L. Reba,
Andrew D. Richardson,
William J. Riley,
Benjamin R. K. Runkle,
Youngryel Ryu,
Torsten Sachs,
Ayaka Sakabe,
Camilo Rey‐Sánchez,
Edward A. G. Schuur,
Karina V. R. Schäfer,
Oliver Sonnentag,
Jed P. Sparks,
Ellen Stuart-Haëntjens,
Cove Sturtevant,
Ryan C. Sullivan,
Daphne Szutu,
Jonathan E. Thom,
M. S. Torn,
Eeva‐Stiina Tuittila,
J. Turner,
Masahito Ueyama,
Alex Valach,
Rodrigo Vargas,
Andrej Varlagin,
Alma Vázquez‐Lule,
Joseph Verfaillie,
Timo Vesala,
George L. Vourlitis,
Eric J. Ward,
Christian Wille,
Georg Wohlfahrt,
Guan Xhuan Wong,
Zhen Zhang,
Donatella Zona,
Lisamarie Windham‐Myers,
Benjamin Poulter,
Robert B. Jackson
Earth System Science Data, Volume 13, Issue 7
Abstract. Methane (CH4) emissions from natural landscapes constitute roughly half of global CH4 contributions to the atmosphere, yet large uncertainties remain in the absolute magnitude and the seasonality of emission quantities and drivers. Eddy covariance (EC) measurements of CH4 flux are ideal for constraining ecosystem-scale CH4 emissions due to quasi-continuous and high-temporal-resolution CH4 flux measurements, coincident carbon dioxide, water, and energy flux measurements, lack of ecosystem disturbance, and increased availability of datasets over the last decade. Here, we (1) describe the newly published dataset, FLUXNET-CH4 Version 1.0, the first open-source global dataset of CH4 EC measurements (available at https://fluxnet.org/data/fluxnet-ch4-community-product/, last access: 7 April 2021). FLUXNET-CH4 includes half-hourly and daily gap-filled and non-gap-filled aggregated CH4 fluxes and meteorological data from 79 sites globally: 42 freshwater wetlands, 6 brackish and saline wetlands, 7 formerly drained ecosystems, 7 rice paddy sites, 2 lakes, and 15 uplands. Then, we (2) evaluate FLUXNET-CH4 representativeness for freshwater wetland coverage globally because the majority of sites in FLUXNET-CH4 Version 1.0 are freshwater wetlands which are a substantial source of total atmospheric CH4 emissions; and (3) we provide the first global estimates of the seasonal variability and seasonality predictors of freshwater wetland CH4 fluxes. Our representativeness analysis suggests that the freshwater wetland sites in the dataset cover global wetland bioclimatic attributes (encompassing energy, moisture, and vegetation-related parameters) in arctic, boreal, and temperate regions but only sparsely cover humid tropical regions. Seasonality metrics of wetland CH4 emissions vary considerably across latitudinal bands. In freshwater wetlands (except those between 20∘ S to 20∘ N) the spring onset of elevated CH4 emissions starts 3 d earlier, and the CH4 emission season lasts 4 d longer, for each degree Celsius increase in mean annual air temperature. On average, the spring onset of increasing CH4 emissions lags behind soil warming by 1 month, with very few sites experiencing increased CH4 emissions prior to the onset of soil warming. In contrast, roughly half of these sites experience the spring onset of rising CH4 emissions prior to the spring increase in gross primary productivity (GPP). The timing of peak summer CH4 emissions does not correlate with the timing for either peak summer temperature or peak GPP. Our results provide seasonality parameters for CH4 modeling and highlight seasonality metrics that cannot be predicted by temperature or GPP (i.e., seasonality of CH4 peak). FLUXNET-CH4 is a powerful new resource for diagnosing and understanding the role of terrestrial ecosystems and climate drivers in the global CH4 cycle, and future additions of sites in tropical ecosystems and site years of data collection will provide added value to this database. All seasonality parameters are available at https://doi.org/10.5281/zenodo.4672601 (Delwiche et al., 2021). Additionally, raw FLUXNET-CH4 data used to extract seasonality parameters can be downloaded from https://fluxnet.org/data/fluxnet-ch4-community-product/ (last access: 7 April 2021), and a complete list of the 79 individual site data DOIs is provided in Table 2 of this paper.
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Substantial hysteresis in emergent temperature sensitivity of global wetland CH4 emissions
Kuang‐Yu Chang,
William J. Riley,
Sara Knox,
Robert B. Jackson,
Gavin McNicol,
Benjamin Poulter,
Mika Aurela,
Dennis Baldocchi,
Sheel Bansal,
Gil Bohrer,
David I. Campbell,
Alessandro Cescatti,
Housen Chu,
Kyle Delwiche,
Ankur R. Desai,
Eugénie Euskirchen,
Thomas Friborg,
Mathias Goeckede,
Manuel Helbig,
Kyle S. Hemes,
Takashi Hirano,
Hiroyasu Iwata,
Minseok Kang,
Trevor F. Keenan,
Ken W. Krauss,
Annalea Lohila,
Ivan Mammarella,
Bhaskar Mitra,
Akira Miyata,
Mats Nilsson,
Asko Noormets,
Walter C. Oechel,
Dario Papale,
Matthias Peichl,
M. L. Reba,
Janne Rinne,
Benjamin R. K. Runkle,
Youngryel Ryu,
Torsten Sachs,
Karina V. R. Schäfer,
Hans Peter Schmid,
Narasinha Shurpali,
Oliver Sonnentag,
Angela C. I. Tang,
M. S. Torn,
Carlo Trotta,
Eeva‐Stiina Tuittila,
Masahito Ueyama,
Rodrigo Vargas,
Timo Vesala,
Lisamarie Windham‐Myers,
Zhen Zhang,
Donatella Zona
Nature Communications, Volume 12, Issue 1
Abstract Wetland methane (CH 4 ) emissions ( $${F}_{{{CH}}_{4}}$$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:msub> <mml:mrow> <mml:mi>F</mml:mi> </mml:mrow> <mml:mrow> <mml:msub> <mml:mrow> <mml:mi>C</mml:mi> <mml:mi>H</mml:mi> </mml:mrow> <mml:mrow> <mml:mn>4</mml:mn> </mml:mrow> </mml:msub> </mml:mrow> </mml:msub> </mml:math> ) are important in global carbon budgets and climate change assessments. Currently, $${F}_{{{CH}}_{4}}$$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:msub> <mml:mrow> <mml:mi>F</mml:mi> </mml:mrow> <mml:mrow> <mml:msub> <mml:mrow> <mml:mi>C</mml:mi> <mml:mi>H</mml:mi> </mml:mrow> <mml:mrow> <mml:mn>4</mml:mn> </mml:mrow> </mml:msub> </mml:mrow> </mml:msub> </mml:math> projections rely on prescribed static temperature sensitivity that varies among biogeochemical models. Meta-analyses have proposed a consistent $${F}_{{{CH}}_{4}}$$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:msub> <mml:mrow> <mml:mi>F</mml:mi> </mml:mrow> <mml:mrow> <mml:msub> <mml:mrow> <mml:mi>C</mml:mi> <mml:mi>H</mml:mi> </mml:mrow> <mml:mrow> <mml:mn>4</mml:mn> </mml:mrow> </mml:msub> </mml:mrow> </mml:msub> </mml:math> temperature dependence across spatial scales for use in models; however, site-level studies demonstrate that $${F}_{{{CH}}_{4}}$$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:msub> <mml:mrow> <mml:mi>F</mml:mi> </mml:mrow> <mml:mrow> <mml:msub> <mml:mrow> <mml:mi>C</mml:mi> <mml:mi>H</mml:mi> </mml:mrow> <mml:mrow> <mml:mn>4</mml:mn> </mml:mrow> </mml:msub> </mml:mrow> </mml:msub> </mml:math> are often controlled by factors beyond temperature. Here, we evaluate the relationship between $${F}_{{{CH}}_{4}}$$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:msub> <mml:mrow> <mml:mi>F</mml:mi> </mml:mrow> <mml:mrow> <mml:msub> <mml:mrow> <mml:mi>C</mml:mi> <mml:mi>H</mml:mi> </mml:mrow> <mml:mrow> <mml:mn>4</mml:mn> </mml:mrow> </mml:msub> </mml:mrow> </mml:msub> </mml:math> and temperature using observations from the FLUXNET-CH 4 database. Measurements collected across the globe show substantial seasonal hysteresis between $${F}_{{{CH}}_{4}}$$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:msub> <mml:mrow> <mml:mi>F</mml:mi> </mml:mrow> <mml:mrow> <mml:msub> <mml:mrow> <mml:mi>C</mml:mi> <mml:mi>H</mml:mi> </mml:mrow> <mml:mrow> <mml:mn>4</mml:mn> </mml:mrow> </mml:msub> </mml:mrow> </mml:msub> </mml:math> and temperature, suggesting larger $${F}_{{{CH}}_{4}}$$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:msub> <mml:mrow> <mml:mi>F</mml:mi> </mml:mrow> <mml:mrow> <mml:msub> <mml:mrow> <mml:mi>C</mml:mi> <mml:mi>H</mml:mi> </mml:mrow> <mml:mrow> <mml:mn>4</mml:mn> </mml:mrow> </mml:msub> </mml:mrow> </mml:msub> </mml:math> 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 CH 4 production are thus needed to improve global CH 4 budget assessments.
In the discontinuous permafrost zone of the Northwest Territories (NWT), Canada, snow covers the ground surface for half the year. Snowmelt constitutes a primary source of moisture supply for the short growing season and strongly influences stream hydrographs. Permafrost thaw has changed the landscape by increasing the proportional coverage of permafrost-free wetlands at the expense of permafrost-cored peat plateau forests. The biophysical characteristics of each feature affect snow water equivalent (SWE) accumulation and melt rates. In headwater streams in the southern Dehcho region of the NWT, snowmelt runoff has significantly increased over the past 50 years, despite no significant change in annual SWE. At the Fort Simpson A climate station, we found that SWE measurements made by Environment and Climate Change Canada using a Nipher precipitation gauge were more accurate than the Adjusted and Homogenized Canadian Climate Dataset which was derived from snow depth measurements. Here, we: (a) provide 13 years of snow survey data to demonstrate differences in end-of-season SWE between wetlands and plateau forests; (b) provide ablation stake and radiation measurements to document differences in snow melt patterns among wetlands, plateau forests, and upland forests; and (c) evaluate the potential impact of permafrost-thaw induced wetland expansion on SWE accumulation, melt, and runoff. We found that plateaus retain significantly (p < 0.01) more SWE than wetlands. However, the differences are too small (123 mm and 111 mm, respectively) to cause any substantial change in basin SWE. During the snowmelt period in 2015, wetlands were the first feature to become snow-free in mid-April, followed by plateau forests (7 days after wetlands) and upland forests (18 days after wetlands). A transition to a higher percentage cover of wetlands may lead to more rapid snowmelt and provide a more hydrologically-connected landscape, a plausible mechanism driving the observed increase in spring freshet runoff.
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L-band vegetation optical depth as an indicator of plant water potential in a temperate deciduous forest stand
Nataniel M. Holtzman,
Leander D. L. Anderegg,
Simon Kraatz,
Alex Mavrovic,
Oliver Sonnentag,
Christoforos Pappas,
Michael H. Cosh,
Alexandre Langlois,
Tarendra Lakhankar,
Derek Tesser,
N. Steiner,
Andreas Colliander,
Alexandre Roy,
Alexandra G. Konings
Biogeosciences, Volume 18, Issue 2
Abstract. Vegetation optical depth (VOD) retrieved from microwave radiometry correlates with the total amount of water in vegetation, based on theoretical and empirical evidence. Because the total amount of water in vegetation varies with relative water content (as well as with biomass), this correlation further suggests a possible relationship between VOD and plant water potential, a quantity that drives plant hydraulic behavior. Previous studies have found evidence for that relationship on the scale of satellite pixels tens of kilometers across, but these comparisons suffer from significant scaling error. Here we used small-scale remote sensing to test the link between remotely sensed VOD and plant water potential. We placed an L-band radiometer on a tower above the canopy looking down at red oak forest stand during the 2019 growing season in central Massachusetts, United States. We measured stem xylem and leaf water potentials of trees within the stand and retrieved VOD with a single-channel algorithm based on continuous radiometer measurements and measured soil moisture. VOD exhibited a diurnal cycle similar to that of leaf and stem water potential, with a peak at approximately 05:00 eastern daylight time (UTC−4). VOD was also positively correlated with both the measured dielectric constant and water potentials of stem xylem over the growing season. The presence of moisture on the leaves did not affect the observed relationship between VOD and stem water potential. We used our observed VOD–water-potential relationship to estimate stand-level values for a radiative transfer parameter and a plant hydraulic parameter, which compared well with the published literature. Our findings support the use of VOD for plant hydraulic studies in temperate forests.
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Gap-filling eddy covariance methane fluxes: Comparison of machine learning model predictions and uncertainties at FLUXNET-CH4 wetlands
Jeremy Irvin,
Sharon Zhou,
Gavin McNicol,
Fred Lu,
Vincent Liu,
Etienne Fluet‐Chouinard,
Zutao Ouyang,
Sara Knox,
Antje Lucas-Moffat,
Carlo Trotta,
Dario Papale,
Domenico Vitale,
Ivan Mammarella,
Pavel Alekseychik,
Mika Aurela,
Anand Avati,
Dennis Baldocchi,
Sheel Bansal,
Gil Bohrer,
David I. Campbell,
Jiquan Chen,
Housen Chu,
Higo J. Dalmagro,
Kyle Delwiche,
Ankur R. Desai,
Eugénie Euskirchen,
Sarah Féron,
Mathias Goeckede,
Martin Heimann,
Manuel Helbig,
Carole Helfter,
Kyle S. Hemes,
Takashi Hirano,
Hiroyasu Iwata,
Gerald Jurasinski,
Aram Kalhori,
Andrew Kondrich,
Derrick Y.F. Lai,
Annalea Lohila,
Avni Malhotra,
Lutz Merbold,
Bhaskar Mitra,
Andrew Y. Ng,
Mats Nilsson,
Asko Noormets,
Matthias Peichl,
Camilo Rey‐Sánchez,
Andrew D. Richardson,
Benjamin R. K. Runkle,
Karina V. R. Schäfer,
Oliver Sonnentag,
Ellen Stuart-Haëntjens,
Cove Sturtevant,
Masahito Ueyama,
Alex Valach,
Rodrigo Vargas,
George L. Vourlitis,
Eric J. Ward,
Guan Xhuan Wong,
Donatella Zona,
Ma. Carmelita R. Alberto,
David P. Billesbach,
Gerardo Celis,
A. J. Dolman,
Thomas Friborg,
Kathrin Fuchs,
Sébastien Gogo,
Mangaliso J. Gondwe,
Jordan P. Goodrich,
Pia Gottschalk,
Lukas Hörtnagl,
Adrien Jacotot,
Franziska Koebsch,
Kuno Kasak,
Regine Maier,
Timothy H. Morin,
Eiko Nemitz,
Walter C. Oechel,
Patricia Y. Oikawa,
Kaori Ono,
Torsten Sachs,
Ayaka Sakabe,
Edward A. G. Schuur,
Robert Shortt,
Ryan C. Sullivan,
Daphne Szutu,
Eeva‐Stiina Tuittila,
Andrej Varlagin,
Joeseph G. Verfaillie,
Christian Wille,
Lisamarie Windham‐Myers,
Benjamin Poulter,
Robert B. Jackson
Agricultural and Forest Meteorology, Volume 308-309
• We evaluate methane flux gap-filling methods across 17 boreal-to-tropical wetlands • New methods for generating realistic artificial gaps and uncertainties are proposed • Decision tree algorithms perform slightly better than neural networks on average • Soil temperature and generic seasonality are the most important predictors • Open-source code is released for gap-filling steps and uncertainty evaluation Time series of wetland methane fluxes measured by eddy covariance require gap-filling to estimate daily, seasonal, and annual emissions. Gap-filling methane fluxes is challenging because of high variability and complex responses to multiple drivers. To date, there is no widely established gap-filling standard for wetland methane fluxes, with regards both to the best model algorithms and predictors. This study synthesizes results of different gap-filling methods systematically applied at 17 wetland sites spanning boreal to tropical regions and including all major wetland classes and two rice paddies. Procedures are proposed for: 1) creating realistic artificial gap scenarios, 2) training and evaluating gap-filling models without overstating performance, and 3) predicting half-hourly methane fluxes and annual emissions with realistic uncertainty estimates. Performance is compared between a conventional method (marginal distribution sampling) and four machine learning algorithms. The conventional method achieved similar median performance as the machine learning models but was worse than the best machine learning models and relatively insensitive to predictor choices. Of the machine learning models, decision tree algorithms performed the best in cross-validation experiments, even with a baseline predictor set, and artificial neural networks showed comparable performance when using all predictors. Soil temperature was frequently the most important predictor whilst water table depth was important at sites with substantial water table fluctuations, highlighting the value of data on wetland soil conditions. Raw gap-filling uncertainties from the machine learning models were underestimated and we propose a method to calibrate uncertainties to observations. The python code for model development, evaluation, and uncertainty estimation is publicly available. This study outlines a modular and robust machine learning workflow and makes recommendations for, and evaluates an improved baseline of, methane gap-filling models that can be implemented in multi-site syntheses or standardized products from regional and global flux networks (e.g., FLUXNET).
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Identifying dominant environmental predictors of freshwater wetland methane fluxes across diurnal to seasonal time scales
Sara Knox,
Sheel Bansal,
Gavin McNicol,
Karina V. R. Schäfer,
Cove Sturtevant,
Masahito Ueyama,
Alex Valach,
Dennis Baldocchi,
Kyle Delwiche,
Ankur R. Desai,
Eugénie Euskirchen,
Jinxun Liu,
Annalea Lohila,
Avni Malhotra,
Lulie Melling,
William J. Riley,
Benjamin R. K. Runkle,
J. Turner,
Rodrigo Vargas,
Qing Zhu,
Tuula Alto,
Etienne Fluet‐Chouinard,
Mathias Goeckede,
Joe R. Melton,
Oliver Sonnentag,
Timo Vesala,
Eric J. Ward,
Zhen Zhang,
Sarah Féron,
Zutao Ouyang,
Pavel Alekseychik,
Mika Aurela,
Gil Bohrer,
David I. Campbell,
Jiquan Chen,
Housen Chu,
Higo J. Dalmagro,
Jordan P. Goodrich,
Pia Gottschalk,
Takashi Hirano,
Hiroyasu Iwata,
Gerald Jurasinski,
Minseok Kang,
Franziska Koebsch,
Ivan Mammarella,
Mats Nilsson,
Kaori Ono,
Matthias Peichl,
Olli Peltola,
Youngryel Ryu,
Torsten Sachs,
Ayaka Sakabe,
Jed P. Sparks,
Eeva‐Stiina Tuittila,
George L. Vourlitis,
Guan Xhuan Wong,
Lisamarie Windham‐Myers,
B. Poulter,
Robert B. Jackson
Global Change Biology, Volume 27, Issue 15
While wetlands are the largest natural source of methane (CH4) to the atmosphere, they represent a large source of uncertainty in the global CH4 budget due to the complex biogeochemical controls on CH4 dynamics. Here we present, to our knowledge, the first multi-site synthesis of how predictors of CH4 fluxes (FCH4) in freshwater wetlands vary across wetland types at diel, multiday (synoptic), and seasonal time scales. We used several statistical approaches (correlation analysis, generalized additive modeling, mutual information, and random forests) in a wavelet-based multi-resolution framework to assess the importance of environmental predictors, nonlinearities and lags on FCH4 across 23 eddy covariance sites. Seasonally, soil and air temperature were dominant predictors of FCH4 at sites with smaller seasonal variation in water table depth (WTD). In contrast, WTD was the dominant predictor for wetlands with smaller variations in temperature (e.g., seasonal tropical/subtropical wetlands). Changes in seasonal FCH4 lagged fluctuations in WTD by ~17 ± 11 days, and lagged air and soil temperature by median values of 8 ± 16 and 5 ± 15 days, respectively. Temperature and WTD were also dominant predictors at the multiday scale. Atmospheric pressure (PA) was another important multiday scale predictor for peat-dominated sites, with drops in PA coinciding with synchronous releases of CH4. At the diel scale, synchronous relationships with latent heat flux and vapor pressure deficit suggest that physical processes controlling evaporation and boundary layer mixing exert similar controls on CH4 volatilization, and suggest the influence of pressurized ventilation in aerenchymatous vegetation. In addition, 1- to 4-h lagged relationships with ecosystem photosynthesis indicate recent carbon substrates, such as root exudates, may also control FCH4. By addressing issues of scale, asynchrony, and nonlinearity, this work improves understanding of the predictors and timing of wetland FCH4 that can inform future studies and models, and help constrain wetland CH4 emissions.
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Tower‐Based Remote Sensing Reveals Mechanisms Behind a Two‐phased Spring Transition in a Mixed‐Species Boreal Forest
Zoe Pierrat,
Magali F. Nehemy,
Alexandre Roy,
Troy S. Magney,
Nicholas C. Parazoo,
Colin P. Laroque,
Christoforos Pappas,
Oliver Sonnentag,
Katja Großmann,
David R. Bowling,
Ulli Seibt,
Alexandra Ramirez,
Bruce Johnson,
Warren Helgason,
Alan Barr,
J. Stutz
Journal of Geophysical Research: Biogeosciences, Volume 126, Issue 5
The boreal forest is a major contributor to the global climate system, therefore, reducing uncertainties in how the forest will respond to a changing climate is critical. One source of uncertainty is the timing and drivers of the spring transition. Remote sensing can provide important information on this transition, but persistent foliage greenness, seasonal snow cover, and a high prevalence of mixed forest stands (both deciduous and evergreen species) complicate interpretation of these signals. We collected tower-based remotely sensed data (reflectance-based vegetation indices and Solar-Induced Chlorophyll Fluorescence [SIF]), stem radius measurements, gross primary productivity, and environmental conditions in a boreal mixed forest stand. Evaluation of this data set shows a two-phased spring transition. The first phase is the reactivation of photosynthesis and transpiration in evergreens, marked by an increase in relative SIF, and is triggered by thawed stems, warm air temperatures, and increased available soil moisture. The second phase is a reduction in bulk photoprotective pigments in evergreens, marked by an increase in the Chlorophyll-Carotenoid Index. Deciduous leaf-out occurs during this phase, marked by an increase in all remotely sensed metrics. The second phase is controlled by soil thaw. Our results demonstrate that remote sensing metrics can be used to detect specific physiological changes in boreal tree species during the spring transition. The two-phased transition explains inconsistencies in remote sensing estimates of the timing and drivers of spring recovery. Our results imply that satellite-based observations will improve by using a combination of vegetation indices and SIF, along with species distribution information.
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Statistical upscaling of ecosystem CO <sub>2</sub> fluxes across the terrestrial tundra and boreal domain: Regional patterns and uncertainties
Anna‐Maria Virkkala,
Juha Aalto,
Brendan M. Rogers,
Torbern Tagesson,
Claire C. Treat,
Susan M. Natali,
Jennifer D. Watts,
Stefano Potter,
Aleksi Lehtonen,
Marguerite Mauritz,
Edward A. G. Schuur,
John Kochendorfer,
Donatella Zona,
Walter C. Oechel,
Hideki Kobayashi,
Elyn Humphreys,
Mathias Goeckede,
Hiroyasu Iwata,
Peter M. Lafleur,
Eugénie Euskirchen,
Stef Bokhorst,
Maija E. Marushchak,
Pertti J. Martikainen,
Bo Elberling,
Carolina Voigt,
Christina Biasi,
Oliver Sonnentag,
Frans‐Jan W. Parmentier,
Masahito Ueyama,
Gerardo Celis,
Vincent L. St. Louis,
Craig A. Emmerton,
Matthias Peichl,
Jinshu Chi,
Järvi Järveoja,
Mats Nilsson,
Steven F. Oberbauer,
M. S. Torn,
Sang Jong Park,
A. J. Dolman,
Ivan Mammarella,
Namyi Chae,
Rafael Poyatos,
Efrén López‐Blanco,
Torben R. Christensen,
Mi Hye Kwon,
Torsten Sachs,
David Holl,
Miska Luoto
Global Change Biology, Volume 27, Issue 17
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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Soil respiration strongly offsets carbon uptake in Alaska and Northwest Canada
Jennifer D. Watts,
Susan M. Natali,
C. Minions,
D. A. Risk,
Kyle A. Arndt,
Donatella Zona,
Eugénie Euskirchen,
A. V. Rocha,
Oliver Sonnentag,
Manuel Helbig,
Aram Kalhori,
W. C. Oechel,
Hiroki Ikawa,
Masahito Ueyama,
Rikie Suzuki,
Hideki Kobayashi,
Gerardo Celis,
Edward A. G. Schuur,
Elyn Humphreys,
Yongwon Kim,
Bang-Yong Lee,
Scott J. Goetz,
Nima Madani,
Luke Schiferl,
R. Commane,
J. S. Kimball,
Zhihua Liu,
M. S. Torn,
Stefano Potter,
Jonathan Wang,
M. Torre Jorgenson,
Jingfeng Xiao,
Xing Li,
C. Edgar
Environmental Research Letters, Volume 16, Issue 8
Abstract Soil respiration (i.e. from soils and roots) provides one of the largest global fluxes of carbon dioxide (CO 2 ) to the atmosphere and is likely to increase with warming, yet the magnitude of soil respiration from rapidly thawing Arctic-boreal regions is not well understood. To address this knowledge gap, we first compiled a new CO 2 flux database for permafrost-affected tundra and boreal ecosystems in Alaska and Northwest Canada. We then used the CO 2 database, multi-sensor satellite imagery, and random forest models to assess the regional magnitude of soil respiration. The flux database includes a new Soil Respiration Station network of chamber-based fluxes, and fluxes from eddy covariance towers. Our site-level data, spanning September 2016 to August 2017, revealed that the largest soil respiration emissions occurred during the summer (June–August) and that summer fluxes were higher in boreal sites (1.87 ± 0.67 g CO 2 –C m −2 d −1 ) relative to tundra (0.94 ± 0.4 g CO 2 –C m −2 d −1 ). We also observed considerable emissions (boreal: 0.24 ± 0.2 g CO 2 –C m −2 d −1 ; tundra: 0.18 ± 0.16 g CO 2 –C m −2 d −1 ) from soils during the winter (November–March) despite frozen surface conditions. Our model estimates indicated an annual region-wide loss from soil respiration of 591 ± 120 Tg CO 2 –C during the 2016–2017 period. Summer months contributed to 58% of the regional soil respiration, winter months contributed to 15%, and the shoulder months contributed to 27%. In total, soil respiration offset 54% of annual gross primary productivity (GPP) across the study domain. We also found that in tundra environments, transitional tundra/boreal ecotones, and in landscapes recently affected by fire, soil respiration often exceeded GPP, resulting in a net annual source of CO 2 to the atmosphere. As this region continues to warm, soil respiration may increasingly offset GPP, further amplifying global climate change.
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Widespread decline in winds delayed autumn foliar senescence over high latitudes
Chaoyang Wu,
Jian Wang,
Philippe Ciais,
Josep Peñuelas,
Xiaoyang Zhang,
Oliver Sonnentag,
Feng Tian,
Xiaoyue Wang,
Huanjiong Wang,
Ronggao Liu,
Yulan Fu,
Quansheng Ge
Proceedings of the National Academy of Sciences, Volume 118, Issue 16
The high northern latitudes (>50°) experienced a pronounced surface stilling (i.e., decline in winds) with climate change. As a drying factor, the influences of changes in winds on the date of autumn foliar senescence (DFS) remain largely unknown and are potentially important as a mechanism explaining the interannual variability of autumn phenology. Using 183,448 phenological observations at 2,405 sites, long-term site-scale water vapor and carbon dioxide flux measurements, and 34 y of satellite greenness data, here we show that the decline in winds is significantly associated with extended DFS and could have a relative importance comparable with temperature and precipitation effects in contributing to the DFS trends. We further demonstrate that decline in winds reduces evapotranspiration, which results in less soil water losses and consequently more favorable growth conditions in late autumn. In addition, declining winds also lead to less leaf abscission damage which could delay leaf senescence and to a decreased cooling effect and therefore less frost damage. Our results are potentially useful for carbon flux modeling because an improved algorithm based on these findings projected overall widespread earlier DFS than currently expected by the end of this century, contributing potentially to a positive feedback to climate.
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Representativeness of Eddy-Covariance flux footprints for areas surrounding AmeriFlux sites
Housen Chu,
Xiangzhong Luo,
Zutao Ouyang,
Chan Sc,
Sigrid Dengel,
S. Biraud,
M. S. Torn,
Stefan Metzger,
Jitendra Kumar,
M. Altaf Arain,
T. J. Arkebauer,
Dennis Baldocchi,
Carl J. Bernacchi,
D. P. Billesbach,
T. Andrew Black,
Peter D. Blanken,
Gil Bohrer,
Rosvel Bracho,
Scott Brown,
Nathaniel A. Brunsell,
Jiquan Chen,
Xingyuan Chen,
Kenneth L. Clark,
Ankur R. Desai,
Tomer Duman,
David Durden,
Silvano Fares,
Inke Forbrich,
John A. Gamon,
Christopher M. Gough,
Timothy J. Griffis,
Manuel Helbig,
David Y. Hollinger,
Elyn Humphreys,
Hiroki Ikawa,
Hiroyasu Iwata,
Yang Ju,
John F. Knowles,
Sara Knox,
Hideki Kobayashi,
Thomas E. Kolb,
Beverly E. Law,
Xuhui Lee,
M. E. Litvak,
Heping Li,
J. William Munger,
Asko Noormets,
Kim Novick,
Steven F. Oberbauer,
Walter C. Oechel,
Patricia Y. Oikawa,
S. A. Papuga,
Elise Pendall,
Prajaya Prajapati,
John H. Prueger,
William L. Quinton,
Andrew D. Richardson,
Eric S. Russell,
Russell L. Scott,
Gregory Starr,
R. M. Staebler,
Paul C. Stoy,
Ellen Stuart-Haëntjens,
Oliver Sonnentag,
Ryan C. Sullivan,
Andy Suyker,
Masahito Ueyama,
Rodrigo Vargas,
J. D. Wood,
Donatella Zona
Agricultural and Forest Meteorology, Volume 301-302
• Large-scale eddy-covariance flux datasets need to be used with footprint-awareness • Using a fixed-extent target area across sites can bias model-data integration • Most sites do not represent the dominant land-cover type at a larger spatial extent • A representativeness index provides general guidance for site selection and data use Large datasets of greenhouse gas and energy surface-atmosphere fluxes measured with the eddy-covariance technique (e.g., FLUXNET2015, AmeriFlux BASE) are widely used to benchmark models and remote-sensing products. This study addresses one of the major challenges facing model-data integration: To what spatial extent do flux measurements taken at individual eddy-covariance sites reflect model- or satellite-based grid cells? We evaluate flux footprints—the temporally dynamic source areas that contribute to measured fluxes—and the representativeness of these footprints for target areas (e.g., within 250–3000 m radii around flux towers) that are often used in flux-data synthesis and modeling studies. We examine the land-cover composition and vegetation characteristics, represented here by the Enhanced Vegetation Index (EVI), in the flux footprints and target areas across 214 AmeriFlux sites, and evaluate potential biases as a consequence of the footprint-to-target-area mismatch. Monthly 80% footprint climatologies vary across sites and through time ranging four orders of magnitude from 10 3 to 10 7 m 2 due to the measurement heights, underlying vegetation- and ground-surface characteristics, wind directions, and turbulent state of the atmosphere. Few eddy-covariance sites are located in a truly homogeneous landscape. Thus, the common model-data integration approaches that use a fixed-extent target area across sites introduce biases on the order of 4%–20% for EVI and 6%–20% for the dominant land cover percentage. These biases are site-specific functions of measurement heights, target area extents, and land-surface characteristics. We advocate that flux datasets need to be used with footprint awareness, especially in research and applications that benchmark against models and data products with explicit spatial information. We propose a simple representativeness index based on our evaluations that can be used as a guide to identify site-periods suitable for specific applications and to provide general guidance for data use.
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The Boreal–Arctic Wetland and Lake Dataset (BAWLD)
David Olefeldt,
Mikael Hovemyr,
McKenzie A. Kuhn,
David Bastviken,
Theodore J. Bohn,
John Connolly,
Patrick Crill,
Eugénie Euskirchen,
S. A. Finkelstein,
Hélène Genet,
Guido Grosse,
Lorna I. Harris,
Liam Heffernan,
Manuel Helbig,
Gustaf Hugelius,
Ryan H. S. Hutchins,
Sari Juutinen,
Mark J. Lara,
Avni Malhotra,
Kristen L. Manies,
A. David McGuire,
Susan M. Natali,
J. A. O’Donnell,
Frans-Jan W. Parmentier,
Aleksi Räsänen,
Christina Schädel,
Oliver Sonnentag,
Maria Strack,
Suzanne E. Tank,
Claire C. Treat,
Ruth K. Varner,
Tarmo Virtanen,
Rebecca K. Warren,
Jennifer D. Watts
Earth System Science Data, Volume 13, Issue 11
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 Boreal–Arctic 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 × 0.5∘ 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 × 106 km2 (14 % of domain) with a 95 % confidence interval between 2.8 and 3.8 × 106 km2. Bog, fen, and permafrost bog were the most abundant wetland classes, covering ∼ 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 × 106 km2 (6 % of domain). Low-methane-emitting large lakes (>10 km2) 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 km2) 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 × 106 km2. Rivers and streams were estimated to cover 0.12 × 106 km2 (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. Data are freely available at https://doi.org/10.18739/A2C824F9X (Olefeldt et al., 2021).
2020
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Shallow soils are warmer under trees and tall shrubs across Arctic and Boreal ecosystems
Heather Kropp,
M. M. Loranty,
Susan M. Natali,
Alexander Kholodov,
A. V. Rocha,
Isla H. Myers‐Smith,
Benjamin W Abbot,
Jakob Abermann,
E. Blanc‐Betes,
Daan Blok,
Gesche Blume‐Werry,
Julia Boike,
A. L. Breen,
Sean M. P. Cahoon,
Casper T. Christiansen,
Thomas A. Douglas,
Howard E. Epstein,
G. V. Frost,
Mathias Goeckede,
Toke T. Høye,
Steven D. Mamet,
J. A. O’Donnell,
David Olefeldt,
Gareth K. Phoenix,
V. G. Salmon,
A. Britta K. Sannel,
Sharon L. Smith,
Oliver Sonnentag,
Lydia Smith Vaughn,
Mathew Williams,
Bo Elberling,
Laura Gough,
Jan Hjort,
Peter M. Lafleur,
Eugénie Euskirchen,
M.M.P.D. Heijmans,
Elyn Humphreys,
Hiroyasu Iwata,
Benjamin M. Jones,
M. Torre Jorgenson,
Inge Grünberg,
Yongwon Kim,
James A. Laundre,
Marguerite Mauritz,
Anders Michelsen,
Gabriela Schaepman‐Strub,
Ken D. Tape,
Masahito Ueyama,
Bang-Yong Lee,
Kirsty Langley,
Magnus Lund
Environmental Research Letters, Volume 16, Issue 1
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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Expert assessment of future vulnerability of the global peatland carbon sink
Julie Loisel,
Angela Gallego‐Sala,
Matthew J. Amesbury,
Gabriel Magnan,
Gusti Z. Anshari,
David W. Beilman,
Juan C. Benavides,
Jerome Blewett,
Philip Camill,
Dan J. Charman,
Sakonvan Chawchai,
A. Hedgpeth,
Thomas Kleinen,
Atte Korhola,
David J. Large,
Claudia A Mansilla,
Jurek Müller,
Simon van Bellen,
Jason B. West,
Zicheng Yu,
Jill L. Bubier,
Michelle Garneau,
Tim R. Moore,
A. Britta K. Sannel,
Susan Page,
Minna Vӓliranta,
Michel Bechtold,
Victor Brovkin,
Lydia E.S. Cole,
Jeffrey P. Chanton,
Torben R. Christensen,
Marissa A. Davies,
François De Vleeschouwer,
Sarah A. Finkelstein,
Steve Frolking,
Mariusz Gałka,
Laure Gandois,
Nicholas T. Girkin,
Lorna I. Harris,
Andreas Heinemeyer,
Alison M. Hoyt,
Miriam C. Jones,
Fortunat Joos,
Sari Juutinen,
Karl Kaiser,
Terri Lacourse,
Mariusz Lamentowicz,
Tuula Larmola,
Jens Leifeld,
Annalea Lohila,
Alice M. Milner,
Kari Minkkinen,
Patrick Moss,
B. David A. Naafs,
J. E. Nichols,
J. A. O’Donnell,
Richard J. Payne,
Michael Philben,
Sanna Piilo,
Anne Quillet,
Amila Sandaruwan Ratnayake,
Thomas P. Roland,
Sofie Sjögersten,
Oliver Sonnentag,
Graeme T. Swindles,
Ward Swinnen,
Julie Talbot,
Claire C. Treat,
Amy Valach,
Jiequn Wu
Nature Climate Change, Volume 11, Issue 1
The carbon balance of peatlands is predicted to shift from a sink to a source this century. However, peatland ecosystems are still omitted from the main Earth system models that are used for future climate change projections, and they are not considered in integrated assessment models that are used in impact and mitigation studies. By using evidence synthesized from the literature and an expert elicitation, we define and quantify the leading drivers of change that have impacted peatland carbon stocks during the Holocene and predict their effect during this century and in the far future. We also identify uncertainties and knowledge gaps in the scientific community and provide insight towards better integration of peatlands into modelling frameworks. Given the importance of the contribution by peatlands to the global carbon cycle, this study shows that peatland science is a critical research area and that we still have a long way to go to fully understand the peatland–carbon–climate nexus. Peatlands are impacted by climate and land-use changes, with feedback to warming by acting as either sources or sinks of carbon. Expert elicitation combined with literature review reveals key drivers of change that alter peatland carbon dynamics, with implications for improving models.
Globally, ecosystem respiration of carbon dioxide (CO2) is the second largest terrestrial carbon (C) flux after photosynthesis (Mahecha et al., 2010). Soil respiration is the main contributor to ecosystem respiration (e.g. c. 70% in temperate forests; reviewed in Ryan & Law, 2005). Plants shunt tremendous quantities of newly photosynthesized C belowground for storage in their roots but also to support rootmetabolism, root exudate production, and resource trading with root symbionts, most notably mycorrhizas (Raich & Nadelhoffer, 1989). These latter C end-points result in newly-fixed C being respired by roots or their symbionts or becoming substrate for use by free-living soil microorganisms. The respiration of this new photosynthetic C can occur within a few days to a month or two after fixation and can contribute to > 50% of the soil respiration (H€ogberg et al., 2001). Plants allocate photosynthetic C differentially aboveground and belowground depending on resource limitation and the demands of the mutualists with whom they collaborate, suggesting that this contribution to soil respiration may vary. As such, both belowground and aboveground vegetation composition, structure, function, and mutualistic partnerships are quite important for determining soil and thus ecosystem respiration. A new paper by Parker et al. (2020; pp. 1818–1830), in this issue of New Phytologist advances our understanding of the contributions of canopy-forming species to soil respiration at the boreal forest–tundra ecotone (FTE), the world’s largest vegetation transition zone spanning rapidly warming high-latitude regions.
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Increasing contribution of peatlands to boreal evapotranspiration in a warming climate
Manuel Helbig,
J. M. Waddington,
Pavel Alekseychik,
B.D. Amiro,
Mika Aurela,
Alan G. Barr,
T. Andrew Black,
Peter D. Blanken,
Sean K. Carey,
Jiquan Chen,
Jinshu Chi,
Ankur R. Desai,
Allison L. Dunn,
Eugénie Euskirchen,
Lawrence B. Flanagan,
Inke Forbrich,
Thomas Friborg,
Achim Grelle,
Silvie Harder,
Michal Heliasz,
Elyn Humphreys,
Hiroki Ikawa,
Pierre‐Érik Isabelle,
Hiroyasu Iwata,
Rachhpal S. Jassal,
Mika Korkiakoski,
Juliya Kurbatova,
Lars Kutzbach,
Anders Lindroth,
Mikaell Ottosson Löfvenius,
Annalea Lohila,
Ivan Mammarella,
Philip Marsh,
Trofim C. Maximov,
Joe R. Melton,
Paul A. Moore,
Daniel F. Nadeau,
Erin M. Nicholls,
Mats Nilsson,
Takeshi Ohta,
Matthias Peichl,
Richard M. Petrone,
Roman E. Petrov,
Anatoly Prokushkin,
William L. Quinton,
David E. Reed,
Nigel T. Roulet,
Benjamin R. K. Runkle,
Oliver Sonnentag,
I. B. Strachan,
Pierre Taillardat,
Eeva‐Stiina Tuittila,
Juha‐Pekka Tuovinen,
J. Turner,
Masahito Ueyama,
Andrej Varlagin,
Martin Wilmking,
Steven C. Wofsy,
Vyacheslav Zyrianov
Nature Climate Change, Volume 10, Issue 6
The response of evapotranspiration (ET) to warming is of critical importance to the water and carbon cycle of the boreal biome, a mosaic of land cover types dominated by forests and peatlands. The effect of warming-induced vapour pressure deficit (VPD) increases on boreal ET remains poorly understood because peatlands are not specifically represented as plant functional types in Earth system models. Here we show that peatland ET increases more than forest ET with increasing VPD using observations from 95 eddy covariance tower sites. At high VPD of more than 2 kPa, peatland ET exceeds forest ET by up to 30%. Future (2091–2100) mid-growing season peatland ET is estimated to exceed forest ET by over 20% in about one-third of the boreal biome for RCP4.5 and about two-thirds for RCP8.5. Peatland-specific ET responses to VPD should therefore be included in Earth system models to avoid biases in water and carbon cycle projections.
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Aboveground tree growth is a minor and decoupled fraction of boreal forest carbon input
Christoforos Pappas,
Jason Maillet,
Sharon Rakowski,
Jennifer L. Baltzer,
Alan G. Barr,
T. Andrew Black,
Simone Fatichi,
Colin P. Laroque,
Ashley M. Matheny,
Alexandre Roy,
Oliver Sonnentag,
Tianshan Zha
Agricultural and Forest Meteorology, Volume 290
• We reconstructed time series of boreal tree growth with a biometric approach. • Aboveground tree growth was a minor and decoupled fraction of carbon input. • Partitioned estimates of tree carbon sink are valuable observational constraints. • Such observational constraints can be used for model validation and policy making. The boreal biome accounts for approximately one third of the terrestrial carbon (C) sink. However, estimates of its individual C pools remain uncertain. Here, focusing on the southern boreal forest, we quantified the magnitude and temporal dynamics of C allocation to aboveground tree growth at a mature black spruce ( Picea mariana )-dominated forest stand in Saskatchewan, Canada. We reconstructed aboveground tree biomass increments (AGBi) using a biometric approach, i.e., species-specific allometry combined with forest stand characteristics and tree ring widths collected with a C-oriented sampling design. We explored the links between boreal tree growth and ecosystem C input by comparing AGBi with eddy-covariance-derived ecosystem C fluxes from 1999 to 2015 and we synthesized our findings with a refined meta-analysis of published values of boreal forest C use efficiency (CUE). Mean AGBi at the study site was decoupled from ecosystem C input and equal to 71 ± 7 g C m –2 (1999–2015), which is only a minor fraction of gross ecosystem production (GEP; i.e., AGBi / GEP ≈ 9 %). Moreover, C allocation to AGBi remained stable over time (AGBi / GEP; –0.0001 yr –1 ; p -value=0.775), contrary to significant trends in GEP (+5.72 g C m –2 yr –2 ; p -value=0.02) and CUE (–0.0041 yr –1 , p -value=0.007). CUE was estimated as 0.50 ± 0.03 at the study area and 0.41 ± 0.12 across the reviewed boreal forests. These findings highlight the importance of belowground tree C investments, together with the substantial contribution of understory, ground cover and soil to the boreal forest C balance. Our quantitative insights into the dynamics of aboveground boreal tree C allocation offer additional observational constraints for terrestrial ecosystem models that are often biased in converting C input to biomass, and can guide forest-management strategies for mitigating carbon dioxide emissions.
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The biophysical climate mitigation potential of boreal peatlands during the growing season
Manuel Helbig,
J. M. Waddington,
Pavel Alekseychik,
B.D. Amiro,
Mika Aurela,
Alan G. Barr,
T. Andrew Black,
Sean K. Carey,
Jiquan Chen,
Jinshu Chi,
Ankur R. Desai,
Allison L. Dunn,
Eugénie Euskirchen,
Lawrence B. Flanagan,
Thomas Friborg,
Michelle Garneau,
Achim Grelle,
Silvie Harder,
Michal Heliasz,
Elyn Humphreys,
Hiroki Ikawa,
Pierre‐Érik Isabelle,
Hiroyasu Iwata,
Rachhpal S. Jassal,
Mika Korkiakoski,
Juliya Kurbatova,
Lars Kutzbach,
Е. Д. Лапшина,
Anders Lindroth,
Mikaell Ottosson Löfvenius,
Annalea Lohila,
Ivan Mammarella,
Philip Marsh,
Paul A. Moore,
Trofim C. Maximov,
Daniel F. Nadeau,
Erin M. Nicholls,
Mats Nilsson,
Takeshi Ohta,
Matthias Peichl,
Richard M. Petrone,
Anatoly Prokushkin,
William L. Quinton,
Nigel T. Roulet,
Benjamin R. K. Runkle,
Oliver Sonnentag,
I. B. Strachan,
Pierre Taillardat,
Eeva‐Stiina Tuittila,
Juha‐Pekka Tuovinen,
J. Turner,
Masahito Ueyama,
Andrej Varlagin,
Timo Vesala,
Martin Wilmking,
Vyacheslav Zyrianov,
Christopher Schulze
Environmental Research Letters, Volume 15, Issue 10
Peatlands and forests cover large areas of the boreal biome and are critical for global climate regulation. They also regulate regional climate through heat and water vapour exchange with the atmosphere. Understanding how land-atmosphere interactions in peatlands differ from forests may therefore be crucial for modelling boreal climate system dynamics and for assessing climate benefits of peatland conservation and restoration. To assess the biophysical impacts of peatlands and forests on peak growing season air temperature and humidity, we analysed surface energy fluxes and albedo from 35 peatlands and 37 evergreen needleleaf forests - the dominant boreal forest type - and simulated air temperature and vapour pressure deficit (VPD) over hypothetical homogeneous peatland and forest landscapes. We ran an evapotranspiration model using land surface parameters derived from energy flux observations and coupled an analytical solution for the surface energy balance to an atmospheric boundary layer (ABL) model. We found that peatlands, compared to forests, are characterized by higher growing season albedo, lower aerodynamic conductance, and higher surface conductance for an equivalent VPD. This combination of peatland surface properties results in a ∼20% decrease in afternoon ABL height, a cooling (from 1.7 to 2.5 °C) in afternoon air temperatures, and a decrease in afternoon VPD (from 0.4 to 0.7 kPa) for peatland landscapes compared to forest landscapes. These biophysical climate impacts of peatlands are most pronounced at lower latitudes (∼45°N) and decrease toward the northern limit of the boreal biome (∼70°N). Thus, boreal peatlands have the potential to mitigate the effect of regional climate warming during the growing season. The biophysical climate mitigation potential of peatlands needs to be accounted for when projecting the future climate of the boreal biome, when assessing the climate benefits of conserving pristine boreal peatlands, and when restoring peatlands that have experienced peatland drainage and mining. © 2020 The Author(s). Published by IOP Publishing Ltd. (Less)
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L-Band response to freeze/thaw in a boreal forest stand from ground- and tower-based radiometer observations
Alexandre Roy,
Peter Toose,
Alex Mavrovic,
Christoforos Pappas,
A. Royer,
Chris Derksen,
Aaron Berg,
Tracy Rowlandson,
Mariam El-Amine,
Alan G. Barr,
Andrew Black,
Alexandre Langlois,
Oliver Sonnentag
Remote Sensing of Environment, Volume 237
Abstract The extent, timing and duration of seasonal freeze/thaw (FT) state exerts dominant control on boreal forest carbon, water and energy cycle processes. Recent and on-going L-Band (≈1.4 GHz) spaceborne missions have the potential to provide enhanced information on FT state over large geographic regions with rapid revisit time. However, the low spatial resolution of these spaceborne observations (≈45 km) makes it difficult to isolate the primary contributions (soil, vegetation, snow) to the FT signal in boreal forest. To better quantify these controls, two L-Band radiometers were deployed (September 2016 to July 2017) at a black spruce (Picea mariana) dominated boreal forest site; one unit above and one unit on the ground surface below the canopy to disentangle the microwave contributions of overstory canopy, and the ground surface on the FT brightness temperature (TB) signal. Bi-weekly multi-angular measurements from both units were combined in order to estimate effective scattering albedo (ω) and the microwave vegetative optical depth (τ), using the τ-ω microwave vegetation radiative transfer model. Soil moisture probes were inserted in the trunk of two black spruce and one larch (Larix laricina) trunks located in the footprint of the above-canopy radiometer to measure tree trunk relative dielectric constant (RDCtree). Results showed a strong relationship between RDCtree and tree skin temperature (Ttree) under freezing temperature conditions, which led to a gradual decrease of τ in winter. During the spring thawing period in April and May, τ remained relatively stable. In contrast, it increased substantially in June, most likely in relation to the growing season onset. Overall, τ was related to the seasonal RDCtree cycle (r = 0.76). Regarding ω, a value of 0.086 (±0.029) was obtained, but no dependency on Ttree or RDCtree was observed. Despite the observed impact of FT on vegetation L-Band signals, results from continuous TB observations spanning from 14 September 2016 to 25 May 2017, indicated that the main contribution to the observed L-Band TB freeze-up signal in the fall originated from the ground surface. The above-canopy unit showed some sensitivity to overstory canopy FT, yet the sensitivity was lower compared to the signal induced by the ground FT. In April and May, L-Band radiometer FT retrieval agreed closely to the melt onset detection using RDCtree but it was likely related to the coincident presence of liquid water in the snow. Our findings have important applications to L-Band spaceborne FT algorithm development and validation across the boreal forest. More specifically, our findings allow better quantification of the potential effect of frozen ground on various biogeophysical and biogeochemical processes in boreal forests.
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Climate‐change refugia in boreal North America: what, where, and for how long?
Diana Stralberg,
Dominique Arseneault,
Jennifer L. Baltzer,
Quinn E. Barber,
Erin M. Bayne,
Yan Boulanger,
Clifford M. Brown,
Hilary A. Cooke,
K. J. Devito,
Jason E. Edwards,
César A. Estevo,
Nadele Flynn,
Lee E. Frelich,
Edward H. Hogg,
Mark Johnston,
Travis Logan,
Steven M. Matsuoka,
Paul A. Moore,
Toni Lyn Morelli,
Jacques Morissette,
Elizabeth A. Nelson,
Hedvig K. Nenzén,
Scott E. Nielsen,
Marc André Parisien,
John H. Pedlar,
David T. Price,
Fiona K. A. Schmiegelow,
Stuart M. Slattery,
Oliver Sonnentag,
Daniel K. Thompson,
Ellen Whitman
Frontiers in Ecology and the Environment, Volume 18, Issue 5
H latitude regions around the world are experiencing particularly rapid climate change. These regions include the 625 million ha North American boreal region, which contains 16% of the world’s forests and plays a major role in the global carbon cycle (Brandt et al. 2013). Boreal ecosystems are particularly susceptible to rapid climatedriven vegetation change initiated by standreplacing natural disturbances (notably fires), which have increased in number, extent, and frequency (Kasischke and Turetsky 2006; Hanes et al. 2018) and are expected to continue under future climate change (Boulanger et al. 2014). Such disturbances will increasingly complicate species persistence, and it will therefore be critical to identify locations of possible climatechange refugia (areas “relatively buffered from contemporary climate change”) (Morelli et al. 2016). These “slow lanes” for biodiversity will be especially important for conservation and management of boreal species and ecosystems (Morelli et al. 2020). Practically speaking, the refugia concept can translate into specific sites or regions that are expected to be more resistant to the influence of climate change than other areas (“in situ refugia”; Ashcroft 2010). Refugia may also encompass sites or regions to which species may more readily retreat as climate conditions change (“ex situ refugia”; Ashcroft 2010; Keppel et al. 2012), as well as temporary “stepping stones” (Hannah et al. 2014) linking current and future habitats. In addition to areas that are climatically buffered, fire refugia – “places that are disturbed less frequently or less severely by wildfire” (Krawchuk et al. 2016) – may also play key roles in promoting ecosystem persistence under changing conditions (Meddens et al. 2018). Previous examinations of climatechange refugia have primarily emphasized external, terrainmediated mechanisms. Factors such as topographic shading and temperature inverClimatechange refugia in boreal North America: what, where, and for how long?
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Nitrous oxide emissions from permafrost-affected soils
Carolina Voigt,
Maija E. Marushchak,
Benjamin W. Abbott,
Christina Biasi,
Bo Elberling,
Steven D. Siciliano,
Oliver Sonnentag,
Katherine Stewart,
Yuanhe Yang,
Pertti J. Martikainen
Nature Reviews Earth & Environment, Volume 1, Issue 8
Soils are sources of the potent greenhouse gas nitrous oxide (N2O) globally, but emissions from permafrost-affected soils have been considered negligible owing to nitrogen (N) limitation. Recent measurements of N2O emissions have challenged this view, showing that vegetated soils in permafrost regions are often small but evident sources of N2O during the growing season (~30 μg N2O–N m−2 day−1). Moreover, barren or sparsely vegetated soils, common in harsh climates, can serve as substantial sources of N2O (~455 μg N2O–N m−2 day−1), demonstrating the importance of permafrost-affected soils in Earth’s N2O budget. In this Review, we discuss N2O fluxes from subarctic, Arctic, Antarctic and alpine permafrost regions, including areas that likely serve as sources (such as peatlands) and as sinks (wetlands, dry upland soils), and estimate global permafrost-affected soil N2O emissions from previously published fluxes. We outline the below-ground N cycle in permafrost regions and examine the environmental conditions influencing N2O dynamics. Climate-change-related impacts on permafrost ecosystems and how these impacts could alter N2O fluxes are reviewed, and an outlook on the major questions and research needs to better constrain the global impact of permafrost N2O emissions is provided.
• PhenoCam data at 13 sites were used to analyze its potential of phenology modeling. • GCC and RCC performed well in capturing GPP-based SOS and EOS at DBF sites. • RCC showed unrecognized importance than GCC for phenology modeling at ENF sites. Vegetation phenology has received increasing attention in climate change research. Near-surface sensing using digital repeat photography has proven to be useful for ecosystem-scale monitoring of vegetation phenology. However, our understanding of the link between phenological metrics derived from digital repeat photography and the phenology of forest canopy photosynthesis is still incomplete, especially for evergreen plant species. Using 49 site-years of digital images from the PhenoCam Network from eight evergreen needleleaf forest (ENF) and six deciduous broadleaf forest (DBF) sites in North America, we explored the potential of the green chromatic (GCC) and red chromatic coordinates (RCC) in tracking forest canopy photosynthesis by comparing camera-derived start- and end-of-growing season (SOS and EOS, respectively) with corresponding estimates derived from eddy covariance-derived daily gross primary productivity (GPP). We found that for DBF sites, both GCC and RCC performed comparable in capturing SOS and EOS. However, similar to earlier studies, GCC had limited potential in capturing GPP-based SOS or EOS for ENF sites. In contrast, we found RCC was a better predictor of both GPP-based SOS and EOS for ENF sites. Environmental and ecological explanations were both provided that phenological transitions derived from RCC were highly correlated with spring and autumn meteorological conditions, as well as having overall higher correlations with phenology based on LAI, a critical variable for describing canopy development. Our results demonstrate that RCC is an underappreciated metric for tracking vegetation phenology, especially for ENF sites where GCC failed to provide reliable estimates for GPP-based SOS or EOS. Our results improve confidence in using digital repeat photography to characterize the phenology of canopy photosynthesis across forest types.
2019
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Proximal remote sensing of tree physiology at northern treeline: Do late-season changes in the photochemical reflectance index (PRI) respond to climate or photoperiod?
Jan U. H. Eitel,
Andrew J. Maguire,
Natalie T. Boelman,
Lee A. Vierling,
Kevin L. Griffin,
Johanna Jensen,
Troy S. Magney,
Peter J. Mahoney,
Arjan J. H. Meddens,
Carlos Alberto Silva,
Oliver Sonnentag
Remote Sensing of Environment, Volume 221
Abstract Relatively little is known of how the world's largest vegetation transition zone – the Forest Tundra Ecotone (FTE) – is responding to climate change. Newly available, satellite-derived time-series of the photochemical reflectance index (PRI) across North America and Europe could provide new insights into the physiological response of evergreen trees to climate change by tracking changes in foliar pigment pools that have been linked to photosynthetic phenology. However, before implementing these data for such purpose at these evergreen dominated systems, it is important to increase our understanding of the fine scale mechanisms driving the connection between PRI and environmental conditions. The goal of this study is thus to gain a more mechanistic understanding of which environmental factors drive changes in PRI during late-season phenological transitions at the FTE – including factors that are susceptible to climate change (i.e., air- and soil-temperatures), and those that are not (photoperiod). We hypothesized that late-season phenological changes in foliar pigment pools captured by PRI are largely driven by photoperiod as opposed to less predictable drivers such as air temperature, complicating the utility of PRI time-series for understanding climate change effects on the FTE. Ground-based, time-series of PRI were acquired from individual trees in combination with meteorological variables and photoperiod information at six FTE sites in Alaska. A linear mixed-effects modeling approach was used to determine the significance (α = 0.001) and effect size (i.e., standardized slope b*) of environmental factors on late-seasonal changes in the PRI signal. Our results indicate that photoperiod had the strongest, significant effect on late-season changes in PRI (b* = 0.08, p
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Increased high‐latitude photosynthetic carbon gain offset by respiration carbon loss during an anomalous warm winter to spring transition
Zhi Hua Liu,
J. S. Kimball,
Nicholas C. Parazoo,
Ashley P. Ballantyne,
Wen J. Wang,
Nima Madani,
Caleb G. Pan,
Jennifer D. Watts,
Rolf H. Reichle,
Oliver Sonnentag,
Philip Marsh,
Miriam Hurkuck,
Manuel Helbig,
William L. Quinton,
Donatella Zona,
Masahito Ueyama,
Hideki Kobayashi,
Eugénie Euskirchen
Global Change Biology, Volume 26, Issue 2
Arctic and boreal ecosystems play an important role in the global carbon (C) budget, and whether they act as a future net C sink or source depends on climate and environmental change. Here, we used complementary in situ measurements, model simulations, and satellite observations to investigate the net carbon dioxide (CO2 ) seasonal cycle and its climatic and environmental controls across Alaska and northwestern Canada during the anomalously warm winter to spring conditions of 2015 and 2016 (relative to 2010-2014). In the warm spring, we found that photosynthesis was enhanced more than respiration, leading to greater CO2 uptake. However, photosynthetic enhancement from spring warming was partially offset by greater ecosystem respiration during the preceding anomalously warm winter, resulting in nearly neutral effects on the annual net CO2 balance. Eddy covariance CO2 flux measurements showed that air temperature has a primary influence on net CO2 exchange in winter and spring, while soil moisture has a primary control on net CO2 exchange in the fall. The net CO2 exchange was generally more moisture limited in the boreal region than in the Arctic tundra. Our analysis indicates complex seasonal interactions of underlying C cycle processes in response to changing climate and hydrology that may not manifest in changes in net annual CO2 exchange. Therefore, a better understanding of the seasonal response of C cycle processes may provide important insights for predicting future carbon-climate feedbacks and their consequences on atmospheric CO2 dynamics in the northern high latitudes.
A multitude of disturbance agents, such as wildfires, land use, and climate-driven expansion of woody shrubs, is transforming the distribution of plant functional types across Arctic–Boreal ecosystems, which has significant implications for interactions and feedbacks between terrestrial ecosystems and climate in the northern high-latitude. However, because the spatial resolution of existing land cover datasets is too coarse, large-scale land cover changes in the Arctic–Boreal region (ABR) have been poorly characterized. Here, we use 31 years (1984–2014) of moderate spatial resolution (30 m) satellite imagery over a region spanning 4.7 × 106 km2 in Alaska and northwestern Canada to characterize regional-scale ABR land cover changes. We find that 13.6 ± 1.3% of the domain has changed, primarily via two major modes of transformation: (a) simultaneous disturbance-driven decreases in Evergreen Forest area (−14.7 ± 3.0% relative to 1984) and increases in Deciduous Forest area (+14.8 ± 5.2%) in the Boreal biome; and (b) climate-driven expansion of Herbaceous and Shrub vegetation (+7.4 ± 2.0%) in the Arctic biome. By using time series of 30 m imagery, we characterize dynamics in forest and shrub cover occurring at relatively short spatial scales (hundreds of meters) due to fires, harvest, and climate-induced growth that are not observable in coarse spatial resolution (e.g., 500 m or greater pixel size) imagery. Wildfires caused most of Evergreen Forest Loss and Evergreen Forest Gain and substantial areas of Deciduous Forest Gain. Extensive shifts in the distribution of plant functional types at multiple spatial scales are consistent with observations of increased atmospheric CO2 seasonality and ecosystem productivity at northern high-latitudes and signal continental-scale shifts in the structure and function of northern high-latitude ecosystems in response to climate change.
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Refining the role of phenology in regulating gross ecosystem productivity across European peatlands
Franziska Koebsch,
Oliver Sonnentag,
Järvi Järveoja,
Mikko Peltoniemi,
Pavel Alekseychik,
Mika Aurela,
Ali Arslan,
Kerry J. Dinsmore,
Damiano Gianelle,
Carole Helfter,
Marcin Jackowicz-Korczyński,
Aino Korrensalo,
Fraser Leith,
Maiju Linkosalmi,
Annalea Lohila,
Magnus Lund,
Martin Maddison,
Ivan Mammarella,
Ülo Mander,
Kari Minkkinen,
Amy Pickard,
Johannes Wilhelmus Maria Pullens,
Eeva‐Stiina Tuittila,
Mats Nilsson,
Matthias Peichl
Global Change Biology, Volume 26, Issue 2
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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Large loss of CO2 in winter observed across the northern permafrost region
Susan M. Natali,
Jennifer D. Watts,
Brendan M. Rogers,
Stefano Potter,
S. Ludwig,
A. K. Selbmann,
Patrick F. Sullivan,
Benjamin W. Abbott,
Kyle A. Arndt,
Leah Birch,
Mats Björkman,
A. Anthony Bloom,
Gerardo Celis,
Torben R. Christensen,
Casper T. Christiansen,
R. Commane,
Elisabeth J. Cooper,
Patrick Crill,
C. I. Czimczik,
S. P. Davydov,
Jinyang Du,
Jocelyn Egan,
Bo Elberling,
Eugénie Euskirchen,
Thomas Friborg,
Hélène Genet,
Mathias Göckede,
Jordan P. Goodrich,
Paul Grogan,
Manuel Helbig,
Elchin Jafarov,
Julie D. Jastrow,
Aram Kalhori,
Yongwon Kim,
J. S. Kimball,
Lars Kutzbach,
Mark J. Lara,
Klaus Steenberg Larsen,
Bang Yong Lee,
Zhihua Liu,
M. M. Loranty,
Magnus Lund,
Massimo Lupascu,
Nima Madani,
Avni Malhotra,
Roser Matamala,
J. W. Mcfarland,
A. David McGuire,
Anders Michelsen,
C. Minions,
Walter C. Oechel,
David Olefeldt,
Frans‐Jan W. Parmentier,
Norbert Pirk,
Benjamin Poulter,
William L. Quinton,
Fereidoun Rezanezhad,
David Risk,
Torsten Sachs,
Kevin Schaefer,
Niels Martin Schmidt,
Edward A. G. Schuur,
Philipp Semenchuk,
Gaius R. Shaver,
Oliver Sonnentag,
Gregory Starr,
Claire C. Treat,
Mark P. Waldrop,
Yihui Wang,
Jeffrey M. Welker,
Christian Wille,
Xiaofeng Xu,
Zhen Zhang,
Qianlai Zhuang,
Donatella Zona
Nature Climate Change, Volume 9, Issue 11
Recent warming in the Arctic, which has been amplified during the winter1-3, greatly enhances microbial decomposition of soil organic matter and subsequent release of carbon dioxide (CO2)4. However, the amount of CO2 released in winter is highly uncertain and has not been well represented by ecosystem models or by empirically-based estimates5,6. Here we synthesize regional in situ observations of CO2 flux from arctic and boreal soils to assess current and future winter carbon losses from the northern permafrost domain. We estimate a contemporary loss of 1662 Tg C yr-1 from the permafrost region during the winter season (October through April). This loss is greater than the average growing season carbon uptake for this region estimated from process models (-1032 Tg C yr-1). Extending model predictions to warmer conditions in 2100 indicates that winter CO2 emissions will increase 17% under a moderate mitigation scenario-Representative Concentration Pathway (RCP) 4.5-and 41% under business-as-usual emissions scenario-RCP 8.5. Our results provide a new baseline for winter CO2 emissions from northern terrestrial regions and indicate that enhanced soil CO2 loss due to winter warming may offset growing season carbon uptake under future climatic conditions.
Thawing permafrost could release large amounts of carbon into the atmosphere, but finding out how much requires better collection and curation of data.
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Monthly gridded data product of northern wetland methane emissions based on upscaling eddy covariance observations
Olli Peltola,
Timo Vesala,
Yao Gao,
Olle Räty,
Pavel Alekseychik,
Mika Aurela,
Bogdan H. Chojnicki,
Ankur R. Desai,
A. J. Dolman,
Eugénie Euskirchen,
Thomas Friborg,
Mathias Göckede,
Manuel Helbig,
Elyn Humphreys,
Robert B. Jackson,
Georg Jocher,
Fortunat Joos,
Janina Klatt,
Sara Knox,
Natalia Kowalska,
Lars Kutzbach,
Sebastian Lienert,
Annalea Lohila,
Ivan Mammarella,
Daniel F. Nadeau,
Mats Nilsson,
Walter C. Oechel,
Matthias Peichl,
Thomas G. Pypker,
William L. Quinton,
Janne Rinne,
Torsten Sachs,
Mateusz Samson,
Hans Peter Schmid,
Oliver Sonnentag,
Christian Wille,
Donatella Zona,
Tuula Aalto
Earth System Science Data, Volume 11, Issue 3
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 =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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A synthesis of three decades of hydrological research at Scotty Creek, NWT, Canada
William L. Quinton,
Aaron Berg,
Michael Braverman,
Olivia Carpino,
L. Chasmer,
Ryan F. Connon,
James R. Craig,
Élise Devoie,
Masaki Hayashi,
Kristine M. Haynes,
David Olefeldt,
Alain Pietroniro,
Fereidoun Rezanezhad,
Robert A. Schincariol,
Oliver Sonnentag
Hydrology and Earth System Sciences, Volume 23, Issue 4
Abstract. Scotty Creek, Northwest Territories (NWT), Canada, has been the focus of hydrological research for nearly three decades. Over this period, field and modelling studies have generated new insights into the thermal and physical mechanisms governing the flux and storage of water in the wetland-dominated regions of discontinuous permafrost that characterises much of the Canadian and circumpolar subarctic. Research at Scotty Creek has coincided with a period of unprecedented climate warming, permafrost thaw, and resulting land cover transformations including the expansion of wetland areas and loss of forests. This paper (1) synthesises field and modelling studies at Scotty Creek, (2) highlights the key insights of these studies on the major water flux and storage processes operating within and between the major land cover types, and (3) provides insights into the rate and pattern of the permafrost-thaw-induced land cover change and how such changes will affect the hydrology and water resources of the study region.
Permafrost degradation in the peat‐rich southern fringe of the discontinuous permafrost zone is catalysing substantial changes to land cover with expansion of permafrost‐free wetlands (bogs and fens) and shrinkage of forest‐dominated permafrost peat plateaux. Predicting discharge from headwater basins in this region depends upon understanding and numerically representing the interactions between storage and discharge within and between the major land cover types and how these interactions are changing. To better understand the implications of advanced permafrost thaw‐induced land cover change on wetland discharge, with all landscape features capable of contributing to drainage networks, the hydrological behaviour of a channel fen sub‐basin in the headwaters of Scotty Creek, Northwest Territories, Canada, dominated by peat plateau–bog complexes, was modelled using the Cold Regions Hydrological Modelling platform for the period of 2009 to 2015. The model construction was based on field water balance observations, and performance was deemed adequate when evaluated against measured water balance components. A sensitivity analysis was conducted to assess the impact of progressive permafrost loss on discharge from the sub‐basin, in which all units of the sub‐basin have the potential to contribute to the drainage network, by incrementally reducing the ratio of wetland to plateau in the modelled sub‐basin. Simulated reductions in permafrost extent decreased total annual discharge from the channel fen by 2.5% for every 10% decrease in permafrost area due to increased surface storage capacity, reduced run‐off efficiency, and increased landscape evapotranspiration. Runoff ratios for the fen hydrological response unit dropped from 0.54 to 0.48 after the simulated 50% permafrost area loss with a substantial reduction of 0.47 to 0.31 during the snowmelt season. The reduction in peat plateau area resulted in decreased seasonal variability in discharge due to changes in the flow path routing, with amplified low flows associated with small increases in subsurface discharge, and decreased peak discharge with large reductions in surface run‐off.
The overall spatial and temporal influence of shrub expansion on permafrost is largely unknown due to uncertainty in estimating the magnitude of many counteracting processes. For example, shrubs shade the ground during the snow-free season, which can reduce active layer thickness. At the same time, shrubs advance the timing of snowmelt when they protrude through the snow surface, thereby exposing the active layer to thawing earlier in spring. Here, we compare 3056 in situ frost table depth measurements split between mineral earth hummocks and organic inter-hummock zones across four dominant shrub–tundra vegetation types. Snow-free date, snow depth, hummock development, topography, and vegetation cover were compared to frost table depth measurements using a structural equation modeling approach that quantifies the direct and combined interacting influence of these variables. Areas of birch shrubs became snow free earlier regardless of snow depth or hillslope aspect because they protruded through the snow surface, leading to deeper hummock frost table depths. Projected increases in shrub height and extent combined with projected decreases in snowfall would lead to increased shrub protrusion across the Arctic, potentially deepening the active layer in areas where shrub protrusion advances the snow-free date.
2018
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Application of Photon Recollision Probability Theory for Compatibility Check Between Foliage Clumping and Leaf Area Index Products Obtained from Earth Observation Data
Jan Písek,
Henning Buddenbaum,
Fernando Camacho,
Joachim Hill,
Jennifer Jensen,
Holger Lange,
Zhili Liu,
Arndt Piayda,
Yonghua Qu,
Olivier Roupsard,
Shawn P. Serbin,
Svein Solberg,
Oliver Sonnentag,
Anne Thimonier,
Francesco Vuolo
IGARSS 2018 - 2018 IEEE International Geoscience and Remote Sensing Symposium
Clumping index (CI) is a measure of foliage aggregation relative to a random distribution of leaves in space. The CI can help with estimating fractions of sunlit and shaded leaves for a given value of leaf area index (LAI). Both the CI and LAI can be obtained from global Earth Observing (EO) systems such as the Moderate Resolution Imaging Spectrometer (MODIS). Here, the compatibility between CI and LAI products derived from EO data is examined independently using the theory of spectral invariants, also referred to as photon recollision probability theory (i.e. ‘ $p$ -theory’), along with raw LAI-2000/2200 Plant Canopy Analyzer data from 75 sites distributed across a range of plant functional types (PFTs). The $p$ -theory describes the probability (p-value) that a photon, having intercepted an element in the canopy, will recollide with another canopy element rather than escape the canopy. Our results indicate that the integration of empirically-based CI maps with the MODIS LAI product is feasible, providing a potential means to improve the accuracy of LAI EO data products. Given the strong results for the large range of PFTs explored here, we demonstrate the capacity to obtain p-values for any location solely from EO data. This is relevant for future applications of the photon recollision probability concept for global and local monitoring of vegetation using EO data.
Evapotranspiration (ET) is a key component of the water cycle, whereby accurate partitioning of ET into evaporation and transpiration provides important information about the intrinsically coupled carbon, water, and energy fluxes. Currently, global estimates of partitioned evaporative and transpiration fluxes remain highly uncertain, especially for high‐latitude ecosystems where measurements are scarce. Forested peat plateaus underlain by permafrost and surrounded by permafrost‐free wetlands characterize approximately 60% (7.0 × 107 km2) of Canadian peatlands. In this study, 22 Picea mariana (black spruce) individuals, the most common tree species of the North American boreal forest, were instrumented with sap flow sensors within the footprint of an eddy covariance tower measuring ET from a forest–wetland mosaic landscape. Sap flux density (JS), together with remote sensing data and in situ measurements of canopy structure, was used to upscale tree‐level JS to overstorey transpiration (TBS). Black spruce trees growing in nutrient‐poor permafrost peat soils were found to have lower mean JS than those growing in mineral soils. Overall, TBS contributed less than 1% to landscape ET. Climate‐change‐induced forest loss and the expansion of wetlands may further minimize the contributions of TBS to ET and increase the contribution of standing water.
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Missing pieces to modeling the Arctic-Boreal puzzle
Joshua B. Fisher,
D. J. Hayes,
Christopher R. Schwalm,
D. N. Huntzinger,
Eric Stofferahn,
Kevin Schaefer,
Yiqi Luo,
Stan D. Wullschleger,
Scott J. Goetz,
Charles E. Miller,
P. C. Griffith,
Sarah Chadburn,
Abhishek Chatterjee,
Philippe Ciais,
Thomas A. Douglas,
Hélène Genet,
Akihiko Ito,
C. S. R. Neigh,
Benjamin Poulter,
Brendan M. Rogers,
Oliver Sonnentag,
Hanqin Tian,
Weile Wang,
Yongkang Xue,
Zong‐Liang Yang,
Ning Zeng,
Zhen Zhang
Environmental Research Letters, Volume 13, Issue 2
Author(s): Fisher, JB; Hayes, DJ; Schwalm, CR; Huntzinger, DN; Stofferahn, E; Schaefer, K; Luo, Y; Wullschleger, SD; Goetz, S; Miller, CE; Griffith, P; Chadburn, S; Chatterjee, A; Ciais, P; Douglas, TA; Genet, H; Ito, A; Neigh, CSR; Poulter, B; Rogers, BM; Sonnentag, O; Tian, H; Wang, W; Xue, Y; Yang, ZL; Zeng, N; Zhang, Z | Abstract: NASA has launched the decade-long Arctic-Boreal Vulnerability Experiment (ABoVE). While the initial phases focus on field and airborne data collection, early integration with modeling activities is important to benefit future modeling syntheses. We compiled feedback from ecosystem modeling teams on key data needs, which encompass carbon biogeochemistry, vegetation, permafrost, hydrology, and disturbance dynamics. A suite of variables was identified as part of this activity with a critical requirement that they are collected concurrently and representatively over space and time. Individual projects in ABoVE may not capture all these needs, and thus there is both demand and opportunity for the augmentation of field observations, and synthesis of the observations that are collected, to ensure that science questions and integrated modeling activities are successfully implemented.
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Data synergy between leaf area index and clumping index Earth Observation products using photon recollision probability theory
Jan Písek,
Henning Buddenbaum,
Fernando Camacho,
Joachim Hill,
Jennifer Jensen,
Holger Lange,
Zhili Liu,
Arndt Piayda,
Yonghua Qu,
Olivier Roupsard,
Shawn P. Serbin,
Svein Solberg,
Oliver Sonnentag,
Anne Thimonier,
Francesco Vuolo
Remote Sensing of Environment, Volume 215
Abstract Clumping index (CI) is a measure of foliage aggregation relative to a random distribution of leaves in space. The CI can help with estimating fractions of sunlit and shaded leaves for a given leaf area index (LAI) value. Both the CI and LAI can be obtained from global Earth Observation data from sensors such as the Moderate Resolution Imaging Spectrometer (MODIS). Here, the synergy between a MODIS-based CI and a MODIS LAI product is examined using the theory of spectral invariants, also referred to as photon recollision probability (‘p-theory’), along with raw LAI-2000/2200 Plant Canopy Analyzer data from 75 sites distributed across a range of plant functional types. The p-theory describes the probability (p-value) that a photon, having intercepted an element in the canopy, will recollide with another canopy element rather than escape the canopy. We show that empirically-based CI maps can be integrated with the MODIS LAI product. Our results indicate that it is feasible to derive approximate p-values for any location solely from Earth Observation data. This approximation is relevant for future applications of the photon recollision probability concept for global and local monitoring of vegetation using Earth Observation data.
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Reviews and syntheses: Changing ecosystem influences on soil thermal regimes in northern high-latitude permafrost regions
M. M. Loranty,
Benjamin W. Abbott,
Daan Blok,
Thomas A. Douglas,
Howard E. Epstein,
Bruce C. Forbes,
Benjamin M. Jones,
Alexander Kholodov,
Heather Kropp,
Avni Malhotra,
Steven D. Mamet,
Isla H. Myers‐Smith,
Susan M. Natali,
J. A. O’Donnell,
Gareth K. Phoenix,
A. V. Rocha,
Oliver Sonnentag,
Ken D. Tape,
Donald A. Walker
Biogeosciences, Volume 15, Issue 17
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.
Abstract. Decoupling the integrated microwave signal originating from soil and vegetation remains a challenge for all microwave remote sensing applications. To improve satellite and airborne microwave data products in forest environments, a precise and reliable estimation of the relative permittivity (ε=ε′-iε′′) of trees is required. We developed an open-ended coaxial probe suitable for in situ permittivity measurements of tree trunks at L-band frequencies (1–2 GHz). The probe is characterized by uncertainty ratios under 3.3 % for a broad range of relative permittivities (unitless), [2–40] for ε′ and [0.1–20] for ε′′. We quantified the complex number describing the permittivity of seven different tree species in both frozen and thawed states: black spruce, larch, red spruce, balsam fir, red pine, aspen and black cherry. Permittivity variability is substantial and can range up to 300 % for certain species. Our results show that the permittivity of wood is linked to the freeze–thaw state of vegetation and that even short winter thaw events can lead to an increase in vegetation permittivity. The open-ended coaxial probe proved to be precise enough to capture the diurnal cycle of water storage inside the trunk for the length of the growing season.
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Boreal tree hydrodynamics: asynchronous, diverging, yet complementary
Christoforos Pappas,
Ashley M. Matheny,
Jennifer L. Baltzer,
Alan G. Barr,
T. Andrew Black,
Gil Bohrer,
Matteo Detto,
Jason Maillet,
Alexandre Roy,
Oliver Sonnentag,
Jilmarie Stephens
Tree Physiology, Volume 38, Issue 7
Water stress has been identified as a key mechanism of the contemporary increase in tree mortality rates in northwestern North America. However, a detailed analysis of boreal tree hydrodynamics and their interspecific differences is still lacking. Here we examine the hydraulic behaviour of co-occurring larch (Larix laricina) and black spruce (Picea mariana), two characteristic boreal tree species, near the southern limit of the boreal ecozone in central Canada. Sap flux density (Js), concurrently recorded stem radius fluctuations and meteorological conditions are used to quantify tree hydraulic functioning and to scrutinize tree water-use strategies. Our analysis revealed asynchrony in the diel hydrodynamics of the two species with the initial rise in Js occurring 2 h earlier in larch than in black spruce. Interspecific differences in larch and black spruce crown architecture explained the observed asynchrony in their hydraulic functioning. Furthermore, the two species exhibited diverging stomatal regulation strategies with larch and black spruce employing relatively isohydric and anisohydric behaviour, respectively. Such asynchronous and diverging tree-level hydrodynamics provide new insights into the ecosystem-level complementarity in tree form and function, with implications for understanding boreal forests' water and carbon dynamics and their resilience to environmental stress.
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Quantification of uncertainties in conifer sap flow measured with the thermal dissipation method
Richard L. Peters,
Patrick Fonti,
David Frank,
Rafael Poyatos,
Christoforos Pappas,
Ansgar Kahmen,
Vinicio Carraro,
Angela Luisa Prendin,
Lea Schneider,
Jennifer L. Baltzer,
Greg A. Baron‐Gafford,
Lars Dietrich,
Ingo Heinrich,
R. L. Minor,
Oliver Sonnentag,
Ashley M. Matheny,
Maxwell G. Wightman,
Kathy Steppe
New Phytologist, Volume 219, Issue 4
Trees play a key role in the global hydrological cycle and measurements performed with the thermal dissipation method (TDM) have been crucial in providing whole-tree water-use estimates. Yet, different data processing to calculate whole-tree water use encapsulates uncertainties that have not been systematically assessed. We quantified uncertainties in conifer sap flux density (Fd ) and stand water use caused by commonly applied methods for deriving zero-flow conditions, dampening and sensor calibration. Their contribution has been assessed using a stem segment calibration experiment and 4 yr of TDM measurements in Picea abies and Larix decidua growing in contrasting environments. Uncertainties were then projected on TDM data from different conifers across the northern hemisphere. Commonly applied methods mostly underestimated absolute Fd . Lacking a site- and species-specific calibrations reduced our stand water-use measurements by 37% and induced uncertainty in northern hemisphere Fd . Additionally, although the interdaily variability was maintained, disregarding dampening and/or applying zero-flow conditions that ignored night-time water use reduced the correlation between environment and Fd . The presented ensemble of calibration curves and proposed dampening correction, together with the systematic quantification of data-processing uncertainties, provide crucial steps in improving whole-tree water-use estimates across spatial and temporal scales.
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Towards long-term standardised carbon and greenhouse gas observations for monitoring Europe’s terrestrial ecosystems: a review
Daniela Franz,
Manuel Acosta,
Núria Altimir,
Nicola Arriga,
Dominique Arrouays,
Marc Aubinet,
Mika Aurela,
Edward Ayres,
Ana López‐Ballesteros,
Mireille Barbaste,
Daniel Berveiller,
S. Biraud,
Hakima Boukir,
Thomas S. Brown,
Christian Brümmer,
Nina Buchmann,
George Burba,
Arnaud Carrara,
A. Cescatti,
Éric Ceschia,
Robert Clement,
Edoardo Cremonese,
Patrick Crill,
Eva Dařenová,
Sigrid Dengel,
Petra D’Odorico,
Gianluca Filippa,
Stefan Fleck,
Gerardo Fratini,
Roland Fuß,
Bert Gielen,
Sébastien Gogo,
J. Grace,
Alexander Graf,
Achim Grelle,
Patrick Gross,
Thomas Grünwald,
Sami Haapanala,
Markus Hehn,
Bernard Heinesch,
Jouni Heiskanen,
Mathias Herbst,
Christine Herschlein,
Lukas Hörtnagl,
Koen Hufkens,
Andreas Ibrom,
Claudy Jolivet,
Lilian Joly,
Michael B. Jones,
Ralf Kiese,
Leif Klemedtsson,
Natascha Kljun,
Katja Klumpp,
Pasi Kolari,
Olaf Kolle,
Andrew S. Kowalski,
Werner L. Kutsch,
Tuomas Laurila,
Anne De Ligne,
Sune Linder,
Anders Lindroth,
Annalea Lohila,
Bernhard Longdoz,
Ivan Mammarella,
Tanguy Manise,
Sara Marañón-Jiménez,
Giorgio Matteucci,
Matthias Mauder,
Philip Meier,
Lutz Merbold,
Simone Mereu,
Stefan Metzger,
Mirco Migliavacca,
Meelis Mölder,
Leonardo Montagnani,
Christine Moureaux,
David D. Nelson,
Eiko Nemitz,
Giacomo Nicolini,
Mats Nilsson,
Maarten Op de Beeck,
Bruce Osborne,
Mikaell Ottosson Löfvenius,
Marián Pavelka,
Matthias Peichl,
Olli Peltola,
Mari Pihlatie,
Andrea Pitacco,
Radek Pokorný,
Jukka Pumpanen,
Céline Ratié,
Corinna Rebmann,
Marilyn Roland,
Simone Sabbatini,
Nicolas Saby,
Matthew Saunders,
Hans Peter Schmid,
Marion Schrumpf,
Pavel Sedlák,
Penélope Serrano-Ortiz,
Lukas Siebicke,
Ladislav Šigut,
Hanna Silvennoinen,
Guillaume Simioni,
U. Skiba,
Oliver Sonnentag,
Kamel Soudani,
Patrice Soulé,
R. Steinbrecher,
Tiphaine Tallec,
Anne Thimonier,
Eeva‐Stiina Tuittila,
Juha‐Pekka Tuovinen,
Patrik Vestin,
Gaëlle Vincent,
Caroline Vincke,
Domenico Vitale,
Peter Waldner,
Per Weslien,
Lisa Wingate,
Georg Wohlfahrt,
M. S. Zahniser,
Timo Vesala
International Agrophysics, Volume 32, Issue 4
Abstract Research infrastructures play a key role in launching a new generation of integrated long-term, geographically distributed observation programmes designed to monitor climate change, better understand its impacts on global ecosystems, and evaluate possible mitigation and adaptation strategies. The pan-European Integrated Carbon Observation System combines carbon and greenhouse gas (GHG; CO 2 , CH 4 , N 2 O, H 2 O) observations within the atmosphere, terrestrial ecosystems and oceans. High-precision measurements are obtained using standardised methodologies, are centrally processed and openly available in a traceable and verifiable fashion in combination with detailed metadata. The Integrated Carbon Observation System ecosystem station network aims to sample climate and land-cover variability across Europe. In addition to GHG flux measurements, a large set of complementary data (including management practices, vegetation and soil characteristics) is collected to support the interpretation, spatial upscaling and modelling of observed ecosystem carbon and GHG dynamics. The applied sampling design was developed and formulated in protocols by the scientific community, representing a trade-off between an ideal dataset and practical feasibility. The use of open-access, high-quality and multi-level data products by different user communities is crucial for the Integrated Carbon Observation System in order to achieve its scientific potential and societal value.
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Ancillary vegetation measurements at ICOS ecosystem stations
Bert Gielen,
Manuel Acosta,
Núria Altimir,
Nina Buchmann,
A. Cescatti,
Éric Ceschia,
Stefan Fleck,
Lukas Hörtnagl,
Katja Klumpp,
Pasi Kolari,
Annalea Lohila,
Denis Loustau,
Sara Marañón-Jiménez,
Tanguy Manise,
Giorgio Matteucci,
Lutz Merbold,
Christine Metzger,
Christine Moureaux,
Leonardo Montagnani,
Mats Nilsson,
Bruce Osborne,
Dario Papale,
Marián Pavelka,
Matthew Saunders,
Guillaume Simioni,
Kamel Soudani,
Oliver Sonnentag,
Tiphaine Tallec,
Eeva‐Stiina Tuittila,
Matthias Peichl,
Radek Pokorný,
Caroline Vincke,
Georg Wohlfahrt
International Agrophysics, Volume 32, Issue 4
Abstract The Integrated Carbon Observation System is a Pan-European distributed research infrastructure that has as its main goal to monitor the greenhouse gas balance of Europe. The ecosystem component of Integrated Carbon Observation System consists of a multitude of stations where the net greenhouse gas exchange is monitored continuously by eddy covariance measurements while, in addition many other measurements are carried out that are a key to an understanding of the greenhouse gas balance. Amongst them are the continuous meteorological measurements and a set of non-continuous measurements related to vegetation. The latter include Green Area Index, aboveground biomass and litter biomass. The standardized methodology that is used at the Integrated Carbon Observation System ecosystem stations to monitor these vegetation related variables differs between the ecosystem types that are represented within the network, whereby in this paper we focus on forests, grasslands, croplands and mires. For each of the variables and ecosystems a spatial and temporal sampling design was developed so that the variables can be monitored in a consistent way within the ICOS network. The standardisation of the methodology to collect Green Area Index, above ground biomass and litter biomass and the methods to evaluate the quality of the collected data ensures that all stations within the ICOS ecosystem network produce data sets with small and similar errors, which allows for inter-comparison comparisons across the Integrated Carbon Observation System ecosystem network.
2017
About a fifth of the global wetland methane emissions originate from boreal peatlands, which represent an important land cover type in boreal landscapes in the sporadic permafrost zone. There, rising air temperatures could lead to warmer spring and longer growing seasons, changing landscape methane emissions. To quantify the effect of warmer spring conditions on methane emissions of a boreal peat landscape in the sporadic permafrost zone of northwestern Canada, we analyzed four years (2013 – 2016) of methane fluxes measured with the eddy covariance technique and long-term (1951-2016) meteorological observations from a nearby climate station. In May, after snowmelt was complete, mean air temperatures were more than 2 °C warmer in 2013, 2015, and 2016 than in 2014. Mean growing season (May-August) air temperatures, in contrast, differed by less than 1 °C over the four years. Warmer May air temperatures caused earlier wetland soil warming, with temperatures rising from ~0 °C to g12 °C 25 to 40 days earlier and leading to ~6 °C warmer mean soil temperatures between May and June. However, from July to August, soil temperatures were similar among years. Mean May to August and annual methane emissions (6.4 g CH4 m-2 and 9.4 g CH4 m-2, respectively) of years with warmer spring (i.e., May) temperatures exceeded emissions during the cooler year by 20-30 % (4.5 g CH4 m-2 and 7.2 g CH4 m-2, respectively). Among years with warmer springs, growing season methane emissions varied little (0.5 g CH4 m-2). The observed interannual differences are most likely caused by a strong soil temperature control on methane fluxes and large soil temperature differences during the spring. Thus, in a warming climate, methane emissions from waterlogged boreal peat landscapes at the southern limit of permafrost are likely to increase in response to more frequent occurrences of warm springs.
