Marsh-atmosphere CO2 exchange in a New England salt marsh

Author Posting. © American Geophysical Union, 2015. This article is posted here by permission of American Geophysical Union for personal use, not for redistribution. The definitive version was published in Journal of Geophysical Research: Biogeosciences 120 (2015): 1825–1838, doi:10.1002/2015JG003044.We studied marsh-atmosphere exchange of carbon dioxide in a high marsh dominated salt marsh during the months of May to October in 2012–2014. Tidal inundation at the site occurred only during biweekly spring tides, during which we observed a reduction in fluxes during day and night. We estimated net ecosystem exchange (NEE), gross primary production (GPP), and ecosystem respiration (Reco) using a modified PLIRTLE model, which requires photosynthetically active radiation, temperature, and normalized difference vegetation index (NDVI) as control variables. NDVI decreased during inundation, when the marsh canopy was submerged. Two-time series of NDVI, including and excluding effects of tidal inundation, allowed us to quantify the flux reduction during inundation. The effect of the flux reduction was small (2–4%) at our site, but is likely higher for marshes at a lower elevation. From May to October, GPP averaged −863 g C m−2, Reco averaged 591 g C m−2, and NEE averaged −291 g C m−2. In 2012, which was an exceptionally warm year, we observed an early start of net carbon uptake but higher respiration than in 2013 and 2014 due to higher-air temperature in August. This resulted in the lowest NEE during the study period (−255.9±6.9 g C m−2). The highest seasonal net uptake (−336.5±6.3 g C m−2) was observed in 2013, which was linked to higher rainfall and temperature in July. Mean sea level was very similar during all 3 years which allowed us to isolate the importance of climatic factors.NSF grants OCE-1058747 and OCE-12382122019-03-2

Constraining marsh carbon budgets using long‐term C burial and contemporary atmospheric CO2 fluxes

Author Posting. © American Geophysical Union, 2018. This article is posted here by permission of American Geophysical Union for personal use, not for redistribution. The definitive version was published in Journal of Geophysical Research: Biogeosciences 123 (2018): 867-878, doi:10.1002/2017JG004336.Salt marshes are sinks for atmospheric carbon dioxide that respond to environmental changes related to sea level rise and climate. Here we assess how climatic variations affect marsh‐atmosphere exchange of carbon dioxide in the short term and compare it to long‐term burial rates based on radiometric dating. The 5 years of atmospheric measurements show a strong interannual variation in atmospheric carbon exchange, varying from −104 to −233 g C m−2 a−1 with a mean of −179 ± 32 g C m−2 a−1. Variation in these annual sums was best explained by differences in rainfall early in the growing season. In the two years with below average rainfall in June, both net uptake and Normalized Difference Vegetation Index were less than in the other three years. Measurements in 2016 and 2017 suggest that the mechanism behind this variability may be rainfall decreasing soil salinity which has been shown to strongly control productivity. The net ecosystem carbon balance was determined as burial rate from four sediment cores using radiometric dating and was lower than the net uptake measured by eddy covariance (mean: 110 ± 13 g C m−2 a−1). The difference between these estimates was significant and may be because the atmospheric measurements do not capture lateral carbon fluxes due to tidal exchange. Overall, it was smaller than values reported in the literature for lateral fluxes and highlights the importance of investigating lateral C fluxes in future studies.National Science Foundation Grant Numbers: OCE-1637630, OCE-1238212, 14263082018-08-0

CO2 exchange of a temperate fen during the conversion from moderately rewetting to flooding

Author Posting. © American Geophysical Union, 2013. This article is posted here by permission of American Geophysical Union for personal use, not for redistribution. The definitive version was published in Journal of Geophysical Research: Biogeosciences 118 (2013): 940–950, doi:10.1002/jgrg.20069.Year-round flooding provides a common land management practice to reestablish the natural carbon dioxide (CO2) sink function of drained peatlands. Here we present eddy covariance measurements of net CO2 exchange from a temperate fen during three consecutive growing seasons (May–October) that span a period of conversion from moderately rewetting to flooding. When we started our measurements in 2009, the hydrological conditions were representative for the preceding 20 years with a mean growing season water level (MWGL) of 0 cm but considerably lower water levels in summer. Flooding began in 2010 with an MWGL of 36 cm above the surface. The fen was a net CO2 sink throughout all growing seasons (2009: −333.3 ± 12.3, 2010: −294.1 ± 8.4, 2011: −352.4 ± 5.1 g C m−2), but magnitudes of canopy photosynthesis (CP) and ecosystem respiration (Reco) differed distinctively. Rates of CP and Reco were high before flooding, dropped by 46% and 61%, respectively, in 2010, but increased again during the beginning of growing season 2011 until the water level started to rise further due to strong rainfalls during June and July. We assume that flooding decreases not only the CO2 release due to inhibited Reco under anaerobic conditions but also CO2 sequestration rates are constricted due to decreased CP. We conclude that rewetting might act as a disturbance for a plant community that has adapted to drier conditions after decades of drainage. However, if the recent species are still abundant, a rise in CP and autotrophic Reco can be expected after plants have developed plastic response strategies to wetter conditions.F.K. was supported by a scholarship of the Federal State of Mecklenburg-Western Pomerania and by the German Research Foundation (DFG). The German Academic Exchange Service (DAAD) funded the collaboration with I.F.2013-12-2

Shallow ponds are heterogeneous habitats within a temperate salt marsh ecosystem

Author Posting. © American Geophysical Union, 2017. This article is posted here by permission of American Geophysical Union for personal use, not for redistribution. The definitive version was published in Journal of Geophysical Research: Biogeosciences 122 (2017): 1371–1384, doi:10.1002/2017JG003780.Integrating spatial heterogeneity into assessments of salt marsh biogeochemistry is becoming increasingly important because disturbances that reduce plant productivity and soil drainage may contribute to an expansion of shallow ponds. These permanently inundated and sometimes prominent landscape features can exist for decades, yet little is known about pond biogeochemistry or their role in marsh ecosystem functioning. We characterized three ponds in a temperate salt marsh (MA, USA) over alternating periods of tidal isolation and flushing, during summer and fall, by evaluating the composition of plant communities and organic matter pools and measuring surface water oxygen, temperature, and conductivity. The ponds were located in the high marsh and had similar depths, temperatures, and salinities. Despite this, they had different levels of suspended particulate, dissolved, and sediment organic matter and abundances of phytoplankton, macroalgae, and Ruppia maritima. Differences in plant communities were reflected in pond metabolism rates, which ranged from autotrophic to heterotrophic. Integrating ponds into landcover-based estimates of marsh metabolism resulted in slower rates of net production (−8.1 ± 0.3 to −15.7 ± 0.9%) and respiration (−2.9 ± 0.5 to −10.0 ± 0.4%), compared to rates based on emergent grasses alone. Seasonality had a greater effect on pond water chemistry, organic matter pools, and algal abundances than tidal connectivity. Alternating stretches of tidal isolation and flushing did not affect pond salinities or algal communities, suggesting that exchange between ponds and nearby creeks was limited. Overall, we found that ponds are heterogeneous habitats and future expansion could reduce landscape connectivity and the ability of marshes to capture and store carbon.National Science Foundation Grant Number: OCE1233678; PIE-LTER Grant Number: OCE1238212; TIDE Grant Number: OCE13544942017-12-1

Representativeness of Eddy-Covariance flux footprints for areas surrounding AmeriFlux sites

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 103 to 107 m2 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

Methane exchange of a boreal peatland - Integrated measurements and modelling on microform and ecosystem scale at the Salmisuo mire complex, Eastern Finland

Peatlands cover only about 3% of the terrestrial surface but are significant players in the global carbon (C) cycle and the climate system, since they store roughly one quarter of the global soil carbon (C) and are among the largest natural sources of methane (CH4). Since the resulting feedbacks on the climate system are uncertain, research efforts aim at identifying key processes and quantifying the C exchange from ecosystem to regional and global scales. To identify peatland ecosystem dynamics requires analysis of yet different scales. The key scale for their C dynamics is the microform scale, which is the smallest entity of the system. To estimate ecosystem dynamics, up-scaling from the microform scale is needed. Up-scaling demands (1) a correct estimation of the spatial heterogeneity and (2) the correct aggregation. In this thesis, the traditional spatial weighting of microform fluxes by the microform distribution is evaluated by (1) analyzing the flux calculation procedure, (2) investigating the effect of the resolution of the landcover maps on the up-scaling and by (3) cross-evaluating the up-scaling result with the directly measured ecosystem flux. Eventually, it is evaluated how these dynamics are considered in a mechanistic ecosystem model (LPJ-WHyMe). CH4 fluxes were measured on the microform scale with the closed chamber technique and on the ecosystem scale with the eddy covariance (EC) technique. The quantification of microform fluxes relies on the correct flux calculation. Since only few gas samples are taken during the closure period, traditionally the linear regression is applied when calculating CH4 fluxes from chamber measurements. Still, the chamber itself affects the diffusion gradient between peat and chamber atmosphere resulting in a theoretically non-linear concentration increase in the chamber. Using data with six data points per measurement from different microform types it is tested whether the linear or exponential regression fits the data better. In the majority of cases, the linear regression fits best. However, the exponential concentration change might still not be detectable resulting in an underestimation of the ’real‘ flux and the test of different techniqes to estimate the slope of a non-linear function with small sample amounts is recommended. To define the spatial heterogeneity of the peatland surface, the application of remote sensing techniques offer the advantage of supplying area-wide information with less uncertainty when compared to vegetation mapping along transects. However, the required resolution to resolve the microform distribution is <1m which in this study was derived from near-aerial photography. Besides for up-scaling, the resulting high-resolution landcover map was used in combination with a footprint model to analyze (1) the effect of landcover on the directly measured ecosystem flux and (2) its spatial representativeness. It was shown that fluctuations of the measured ecosystem flux over periods of several days could be explained by changes of the landcover composition in the source area of the EC measurements. The estimated budget was slightly biased towards the higher emissions from lawns which could be corrected. Still, the seasonal ecosystem CH4 budget was higher than the estimate derived from the up-scaling of microform fluxes. This is most likely due to an underestimation of microform fluxes by the chamber technique. Generally, the budget estimate derived from EC measurements was more accurate, i.e., characterized by less uncertainty than the up-scaled estimate. The developed approach depends on (1) identification and accurate measurements of all relevant microform types and (2) on spatial information which should be smaller than the footprint size of the EC measurements and available on the scale relevant for the studied process, i.e., the microform scale. The demonstrated effect of microform dynamics on the ecosystem flux highlights the importance of dealing with spatial heterogeneity of ecosystems in mechanistic modelling. For example, in LPJ-WHyMe, the ecosystem flux is simulated with mean input variables as water table level. To investigate its model performance, flux data from the rather homogeneous peatland margin and the more heterogeneous peatland centre were compared with the model output. At the homogeneous peatland margin, the ecosystem flux was clearly dominated (with a contribution of 91%) by one microform flux. In this case, one water table level as input variable could be used to estimate the ecosystem flux. However, for a heterogeneous site such as the peatland centre in this study, only one mean water table would simulate a mean microform flux but not the ecosystem flux. Consequently, it is recommended to incorporate at least one high-emitting and one low-emitting microform type in the model to increase the model performance.Moore bedecken nur ca. 3% der terrestrischen Erdoberfläche, spielen aber eine bedeutende Rolle im globalen Kohlenstoffkreislauf und Klimasystem. Sie speichern rund ein Viertel des globalen Kohlenstoffs im Boden-Pool und sind mit anderen Feuchtgebieten die bedeutendste natürliche Quelle für Methan (CH4). Die daraus entstehenden Rückkopplungen mit dem globalen Klima sind noch Gegenstand der Forschung. Die entscheidenden Prozesse innerhalb des Moor-Ökosystems zu identifizieren, setzt Messungen und Modellierungen auf mehreren räumlichen Skalen voraus. Haupteinheit dabei ist die Skala von Mikrostandorten, die die kleinste Einheit des Systems repräsentieren. Um Eigenschaften des Ökosystems daraus abzuleiten werden Informationen auf diese Ebene hochskaliert. Hochskalieren setzt (1) eine genaue Abschätzung der räumlichen Heterogenität voraus und (2) ihre korrekte Aggregierung. In dieser Arbeit wird der klassische Ansatz, die gemessenen Flüsse der Mikrostandorte mit ihrer räumlichen Verteilung zu gewichten, evaluiert. Es werden (1) die Flussberechnung analysiert, (2) der Effekt der Auflösung der räumlichen Daten auf das Skalieren untersucht und (3) der geschätzte Ökosystemfluss mit einem direkt gemessenen Fluss auf dieser Skala verglichen. Darauf aufbauend wird untersucht in wie weit diese Dynamik in einem mechanistischen Ökosystem-Modell (LPJ-WHyMe) berücksichtigt wird. Die CH4 Emissionsraten wurden mit der Haubenmethode für die einzelnen Mikrostandorte ermittelt und auf der Ökosystemebene mittels der Eddy-Kovarianz-Methode. Die Quantifizierung der Emissionen von Mikrostandorten hängt von der adäquaten Flussberechnung ab. Da die Haube selbst die Diffusion zwischen Boden und Haubenatmosphäre beeinflusst, ist theoretisch von einer nichtlinearen Konzentrationsänderung in der Haube auszugehen. Mit einem Datensatz aller Mikrostandorte mit sechs Datenpunkten pro Messung wird hier untersucht, ob eine lineare oder eine exponentielle Funktion die Konzentrationsänderung in der Haube besser beschreibt. In der Mehrheit passt die lineare Regression besser. Es kann aber durchaus sein, dass ein nicht-linearer Konzentrationsanstieg mit sechs Punkten noch nicht identifiziert werden kann und daher mit der linearen Regression der Fluss unterschätzt wird. Um die räumliche Heterogenität der Mooroberfläche zu definieren, bieten Fernerkundungsdaten den Vorteil, dass sie flächendeckende Informationen liefern, die zudem genauer sind. Die notwendige hohe Auflösung (<1m) wurde in dieser Arbeit mittels near-aerial photography erreicht. Die resultierende Klassifikation der Oberfläche wird neben dem Hochskalieren zusammen mit einem Footprint Modell dafür eingesetzt, den Effekt der unterschiedlichen Oberflächen auf den direkt gemessenen Ökosystemfluss und (2) dessen räumliche Repräsentativität zu untersuchen. Es konnte gezeigt werden, dass Schwankungen des Ökosystemflusses über den Zeitraum von einem bis mehreren Tagen mit Änderungen der Oberfläche im Footprint der Eddy-Kovarianz-Messung erklärt werden konnte. Die resultierende Bilanz war geringfügig mehr beeinflusst durch die höheren Emissionen der Lawn Mikrostandorte, was korrigiert werden konnte. Die Bilanz war danach immer noch höher als die der hochskalierten Flüsse der Mikrostandorte. Dies ist wahrscheinlich auf eine Unterschätzung dieser Flüsse durch die Haubenmethode zurückzuführen. Generell ist die Abschätzung der Bilanz basierend auf Eddy-Kovarianz-Messungen genauer, d.h. mit einer geringeren Unsicherheit belegt, als die hochskalierten Flüsse. Der entwickelte Ansatz basiert auf (1) der Identifizierung und Beprobung aller relevanter Mikrostandorte sowie (2) vorhandener räumlicher Information auf der prozess-relevanten Skala, d.h. Skala der Mikrostandorte, die kleiner sein sollte als die Ausdehnung des Footprint der Eddy-Kovarianz-Messung. Der beschriebene Effekt der Zusammensetzung der Mikrostandorte auf den Ökosystemfluss zeigt die Notwendigkeit, räumliche Heterogenität von Ökosystemen in mechanistischen Modellen zu berücksichtigen. In LPJ-WHyMe z.B. wird der Ökosystemfluss mit mittleren Eingangsvariablen wie dem Wasserstand modelliert. Um die Funktionsweise des Modells zu evaluieren, wurden Messdaten vom eher homogenen Moorrand und vom heterogenen Moorzentrum mit dem Modellergebnis verglichen. Am homogenen Moorrand war der Ökosystemfluss klar dominiert von einem einzigen Mikrostandort (mit einem Beitrag von 91%). In diesem Fall kann ein Wasserstand als Eingangsvariable zur Simulierung des Ökosystemflusses verwendet werden. Für heterogene Systeme, wie dem Moorzentrum in dieser Arbeit, würde ein einzelner Wasserstand auch nur einen Fluss für einen mittleren Mikrostandort modellieren aber nicht den Ökosystemfluss. Es wird daher argumentiert, dass mindestens ein viel-emittierender und ein wenig-emittierender Mikrostandort in das Modell inkorporiert werden sollte, um die Funktionsweise zu verbessern

Solute fluxes in the Kidisjoki catchment, subarctic Finnish Lapland

Le bilan hydrique, la chimie des eaux et les transferts en solution ont été étudiés dans le bassin versant de Kidisjoki (18 km2 ; 75 à 365 m d’altitude ; 69º47’N et 27º05’E) en Laponie finlandaise. L’aire d’étude fait partie du Bouclier baltique, d’âge précambrien et composé essentiellement de gneiss et de granulites. Nous estimons que la dénudation chimique dans le bassin versant est de l’ordre de 2,9 t.km2.a-1. La variabilité spatio-temporelle de la charge en solution dans le bassin versant semble être influencée par des variations spatiales de la persistance du gélisol hivernal et de l’épaisseur du régolithe. En dépit de la faible intensité de l’altération chimique et de la faible concentration des solutions dans les eaux superficielles, l’altération chimique semble être plus importante que l’érosion fluviale et pourrait être le principal processus de dénudation de cet environnement subarctique.Water balance, water chemistry, and solute fluxes have been investigated in the Kidisjoki catchment (18 km2 ; 75 to 365 m a.s.l. ; 69°47’N, 27°05’E) in subarctic Finnish Lapland. The study area is part of the Precambrian Baltic Shield and is composed lithologically of gneisses and granulites. It is estimated that chemical denudation in the catchment is on the order of 2.9 t.km2.yr-1. Spatio-temporal variability of solute yields within the catchment seems to be influenced by spatial variations of winter ground frost duration and regolith thickness. In spite of the low intensity of chemical weathering and the low solute concentrations in the surface water, chemical denudation seems to be more important than mechanical fluvial erosion, and so might be the most important denudational process in this subarctic environment

Integrating Tide‐Driven Wetland Soil Redox and Biogeochemical Interactions Into a Land Surface Model

Redox processes, aqueous and solid-phase chemistry, and pH dynamics are key drivers of subsurface biogeochemical cycling and methanogenesis in terrestrial and wetland ecosystems but are typically not included in terrestrial carbon cycle models. These omissions may introduce errors when simulating systems where redox interactions and pH fluctuations are important, such as wetlands where saturation of soils can produce anoxic conditions and coastal systems where sulfate inputs from seawater can influence biogeochemistry. Integrating cycling of redox-sensitive elements could therefore allow models to better represent key elements of carbon cycling and greenhouse gas production. We describe a model framework that couples the Energy Exascale Earth System Model (E3SM) Land Model (ELM) with PFLOTRAN biogeochemistry, allowing geochemical processes and redox interactions to be integrated with land surface model simulations. We implemented a reaction network including aerobic decomposition, fermentation, sulfate reduction, sulfide oxidation, methanogenesis, and methanotrophy as well as pH dynamics along with iron oxide and iron sulfide mineral precipitation and dissolution. We simulated biogeochemical cycling in tidal wetlands subject to either saltwater or freshwater inputs driven by tidal hydrological dynamics. In simulations with saltwater tidal inputs, sulfate reduction led to accumulation of sulfide, higher dissolved inorganic carbon concentrations, lower dissolved organic carbon concentrations, and lower methane emissions than simulations with freshwater tidal inputs. Model simulations compared well with measured porewater concentrations and surface gas emissions from coastal wetlands in the Northeastern United States. These results demonstrate how simulating geochemical reaction networks can improve land surface model simulations of subsurface biogeochemistry and carbon cycling

Coastal vegetation and estuaries are collectively a greenhouse gas sink

Coastal ecosystems release or absorb carbon dioxide (CO2), methane (CH4) and nitrous oxide (N2O), but the net effects of these ecosystems on the radiative balance remain unknown. We compiled a dataset of observations from 738 sites from studies published between 1975 and 2020 to quantify CO2, CH4 and N2O fluxes in estuaries and coastal vegetation in ten global regions. We show that the CO2-equivalent (CO(2)e) uptake by coastal vegetation is decreased by 23-27% due to estuarine CO(2)e outgassing, resulting in a global median net sink of 391 or 444 TgCO(2)e yr(-1) using the 20- or 100-year global warming potentials, respectively. Globally, total coastal CH4 and N2O emissions decrease the coastal CO2 sink by 9-20%. Southeast Asia, North America and Africa are critical regional hotspots of GHG sinks. Understanding these hotspots can guide our efforts to strengthen coastal CO2 uptake while effectively reducing CH4 and N2O emissions. The authors show that estuarine and coastal vegetation are collectively a greenhouse gas (GHG) sink for the atmosphere, but methane and nitrous oxide emissions counteract the carbon dioxide uptake. Critical coastal GHG sink hotspots are identified in Southeast Asia, North America and Africa