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In his comment (Kowalski 2023) on our recent publication (Heiskanen et al. 2022) where we present the Integrated Carbon Observation System (ICOS) research infrastructure, Andrew Kowalski introduces three important and, [...]

The processes responsible for methane (CH4) emissions from boreal wetlands are complex; hence, their model representation is complicated by a large number of parameters and parameter uncertainties. The arctic-enabled dynamic global vegetation model LPJ-GUESS (Lund–Potsdam–Jena General Ecosystem Simulator) is one such model that allows quantification and understanding of the natural wetland CH4 fluxes at various scales, ranging from local to regional and global, but with several uncertainties. The model contains detailed descriptions of the CH4 production, oxidation, and transport controlled by several process parameters. Complexities in the underlying environmental processes, warming-driven alternative paths of meteorological phenomena, and changes in hydrological and vegetation conditions highlight the need for a calibrated and optimised version of LPJ-GUESS. In this study, we formulated the parameter calibration as a Bayesian problem, using knowledge of reasonable parameters values as priors. We then used an adaptive Metropolis–Hastings (MH)-based Markov chain Monte Carlo (MCMC) algorithm to improve predictions of CH4 emission by LPJ-GUESS and to quantify uncertainties. Application of this method on uncertain parameters allows for a greater search of their posterior distribution, leading to a more complete characterisation of the posterior distribution with a reduced risk of the sample impoverishment that can occur when using other optimisation methods. For assimilation, the analysis used flux measurement data gathered during the period from 2005 to 2014 from the Siikaneva wetlands in Southern Finland with an estimation of measurement uncertainties. The data are used to constrain the processes behind the CH4 dynamics, and the posterior covariance structures are used to explain how the parameters and the processes are related. To further support the conclusions, the CH4 flux and the other component fluxes associated with the flux are examined. The results demonstrate the robustness of MCMC methods to quantitatively assess the interrelationship between objective function choices, parameter identifiability, and data support. The experiment using real observations from Siikaneva resulted in a reduction in the root-mean-square error (RMSE), from 0.044 to 0.023 gC m -2 d -1 , and a 93.89 % reduction in the cost function value. As a part of this work, knowledge about how CH4 data can constrain the parameters and processes is derived. Although the optimisation is performed based on a single site's flux data from Siikaneva, the algorithm is useful for larger-scale multi-site studies for a more robust calibration of LPJ-GUESS and similar models, and the results can highlight where model improvements are needed. [ABSTRACT FROM AUTHOR]

In this study, we use a data assimilation framework based on the Adaptive Markov Chain Monte Carlo (MCMC) algorithm to constrain process parameters in LPJ-GUESS using CH4 eddy covariance flux observations from 14 different natural boreal and temperate wetlands. The objective is to derive a single set of calibrated parameter values. These parameters are then used in the model to validate its CH4 flux output against 5 different types of natural wetlands situated in different locations, assessing their generality for simulating CH4 fluxes from different boreal and temperate wetlands. The results show that the MCMC framework has substantially reduced the cost function (measuring the misfit between simulated and observed CH4 fluxes) and facilitated detailed characterisation of the posterior distribution. A reduction of around 95 % in the cost function and approximately 50 % in RMSE were observed. The validation experiment results indicate that four out of 5 sites successfully reduced RMSE, demonstrating the effectiveness of the framework for estimating CH4 emissions from wetlands not included in the study. [ABSTRACT FROM AUTHOR]

Arctic terrestrial greenhouse gas (GHG) fluxes of carbon dioxide (CO 2), methane (CH 4), and nitrous oxide (N 2 O) play an important role in the global GHG budget. However, these GHG fluxes are rarely studied simultaneously, and our understanding of the conditions controlling them across spatial gradients is limited. Here, we explore the magnitudes and drivers of GHG fluxes across fine-scale terrestrial gradients during the peak growing season (July) in sub-Arctic Finland. We measured chamber-derived GHG fluxes and soil temperature, soil moisture, soil organic carbon and nitrogen stocks, soil pH, soil carbon-to-nitrogen (C/N) ratio, soil dissolved organic carbon content, vascular plant biomass, and vegetation type from 101 plots scattered across a heterogeneous tundra landscape (5 km 2). We used these field data together with high-resolution remote sensing data to develop machine learning models for predicting (i.e., upscaling) daytime GHG fluxes across the landscape at 2 m resolution. Our results show that this region was on average a daytime net GHG sink during the growing season. Although our results suggest that this sink was driven by CO 2 uptake, it also revealed small but widespread CH 4 uptake in upland vegetation types, almost surpassing the high wetland CH 4 emissions at the landscape scale. Average N 2 O fluxes were negligible. CO 2 fluxes were controlled primarily by annual average soil temperature and biomass (both increase net sink) and vegetation type, CH 4 fluxes by soil moisture (increases net emissions) and vegetation type, and N 2 O fluxes by soil C/N (lower C/N increases net source). These results demonstrate the potential of high spatial resolution modeling of GHG fluxes in the Arctic. They also reveal the dominant role of CO 2 fluxes across the tundra landscape but suggest that CH 4 uptake in dry upland soils might play a significant role in the regional GHG budget. [ABSTRACT FROM AUTHOR]

Termites play an essential role in decomposing dead plant material in tropical ecosystems and are thus major sources of gaseous C emissions in many environments. In African savannas, fungus-growing termites are among the ecologically most influential termite species. We studied the gas exchange from mounds of two closely related fungus-growing species (Macrotermes subhyalinus and M. michaelseni, respectively) in two habitats representing different vegetation types (grassland, bushland) together with soil fluxes around the mounds. The fluxes from active termite mounds varied from 120 to 2100 mg CO 2 –C m -2 h -1 for carbon dioxide (CO 2) and from 0.06 to 3.7 mg CH 4 –C m -2 h -1 for methane (CH 4) fluxes. Mound CO 2 fluxes varied seasonally with a 64 % decrease and 41 % increase in the fluxes from the dry to wet season at the grassland and bushland sites, respectively. During the wet season, the CO 2 fluxes were significantly correlated with termite mound volume. The diurnal measurements from two M. michaelseni mounds suggest that the gas fluxes peak during the daytime, possibly reflecting changes in mound internal air circulation. Soil fluxes of both CO 2 and CH 4 were enhanced at up to 2 m distance from the mounds compared to the local soil respiration, indicating that, in addition to mound ventilation structures, a small proportion of the metabolic gases produced also leave the nest via surrounding soils. [ABSTRACT FROM AUTHOR]

The ecosystem–atmosphere flux of biogenic volatile organic compounds (BVOCs) has important impacts on tropospheric oxidative capacity and the formation of secondary organic aerosols, influencing air quality and climate. Here we present within-canopy measurements of a set of dominant BVOCs in a managed spruce- and pine-dominated boreal forest located at the ICOS (Integrated Carbon Observation System) station Norunda in Sweden, collected using proton-transfer-reaction mass spectrometry (PTR-MS) during 2014–2016 and vertical emission profiles derived from these data. Ozone concentrations were simultaneously measured in conjunction with these PTR-MS measurements. The main BVOCs investigated with the PTR-MS were isoprene, monoterpenes, methanol, acetaldehyde, and acetone. The distribution of BVOC sources and sinks in the forest canopy was explored using Lagrangian dispersion matrix methods, in particular continuous near-field theory. The forest canopy was found to contribute ca. 86 % to the total monoterpene emission in summertime, whereas the below-canopy and canopy emissions were comparable (ca. 42 % and 58 %, respectively) during the fall period. This result indicates that boreal forest litter and other below-canopy emitters are a principal source of total forest monoterpene emissions during the fall months. During night, our results for methanol, acetone, and acetaldehyde seasonally present strong sinks in the forest canopy, especially in the fall, likely due to the nighttime formation of dew on vegetation surfaces. [ABSTRACT FROM AUTHOR]

The processes responsible for methane (CH4) emissions from boreal wetlands are complex, and hence their model representation is complicated by a large number of parameters and parameter uncertainties. The arctic-enabled dynamic global vegetation model LPJ-GUESS is one such model that allows quantification and understanding of the natural wetland CH4 fluxes at various scales ranging from local to regional and global, but with several uncertainties. The model contains detailed descriptions of CH4 production, oxidation, and transport controlled by several process parameters. Complexities in the underlying environmental processes, warming-driven alternative paths of meteorological phenomena, and changes in hydrological and vegetation conditions are highlight the need for a calibrated and optimised version of LPJGUESS. In this study we formulated the parameter calibration as a Bayesian problem, using knowledge of reasonable parameters values as priors. We then used an adaptive Metropolis Hastings (MH) based Markov Chain Monte Carlo (MCMC) algorithm to improve predictions of CH4 emission by LPJ-GUESS and to quantify uncertainties. Application of this method on uncertain parameters allows greater search of their posterior distribution, leading to a more complete characterisation of the posterior distribution with reduced risk of sample impoverishment that can occur when using other optimisation methods. For assimilation, the analysis used flux measurement data gathered during the period 2005 to 2014 from the Siikaneva wetlands in southern Finland with an estimation of measurement uncertainties. The data are used to constrain the processes behind the CH4 dynamics, and the posterior covariance structures are used to explain how the parameters and the processes are related. To further support the conclusions, the CH4 flux and the other component fluxes associated with the flux are examined. The results demonstrate the robustness of MCMC methods to quantitatively assess the interrelationship between objective function choices, parameter identifiability, and data support. As a part of this work, knowledge about how the CH4 data can constrain the parameters and processes is derived. Though the optimisation is performed based on a single site's flux data from Siikaneva, the algorithm is useful for larger-scale multi-site studies for more robust calibration of LPJ-GUESS and similar models, and the results can highlight where model improvements are needed. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Arctic terrestrial greenhouse gas (GHG) fluxes of carbon dioxide (CO2), methane (CH4) and nitrous oxide (N2O) play an important role in the global GHG budget. However, these GHG fluxes are rarely studied simultaneously, and our understanding of the conditions controlling them across spatial gradients is limited. Here, we explore the magnitudes and drivers of GHG fluxes across fine-scale terrestrial gradients during the peak growing season (July) in sub-Arctic Finland. We measured chamber-derived GHG fluxes and soil temperature, soil moisture, soil organic carbon and nitrogen stocks, soil pH, soil carbon-to-nitrogen (C/N) ratio, soil dissolved organic carbon content, vascular plant biomass, and vegetation type from 101 plots scattered across a heterogeneous tundra landscape (5 km²). We used these field data together with high-resolution remote sensing data to develop machine learning models to predict (i.e., upscale) daytime GHG fluxes across the landscape at 2-m resolution. Our results show that this region was on average a daytime net GHG sink during the growing season. Although our results suggest that this sink was driven by CO2 uptake, it also revealed small but widespread CH4 uptake in upland vegetation types, shifting this region to an average net CH4 sink at the landscape scale during growing season, despite the presence of high-emitting wetlands. Average N2O fluxes were negligible. CO2 fluxes were controlled primarily by annual average soil temperature and biomass (both increase net sink) and vegetation type, CH4 fluxes by soil moisture (increases net emissions) and vegetation type, and N2O fluxes by soil C/N (lower C/N increases net source). These results demonstrate the potential of high spatial resolution modelling of GHG fluxes in the Arctic. They also reveal the dominant role of CO2 fluxes across the tundra landscape, but suggest that CH4 uptake might play a significant role in the regional GHG budget. [ABSTRACT FROM AUTHOR]

Termites play an essential role in decomposing dead plant material in tropical ecosystems and are thus major sources of gaseous C emissions in many environments. In African savannas, fungus-growing termites are among the ecologically most influential termite species. We studied the gas exchange from mounds of two closely related fungus-growing species (Macrotermes subhyalinus and M. michaelseni, respectively) in shaded and open habitats together with soil fluxes around the mounds. The fluxes from active termite mounds varied from 116 to 2105 mg CO2-C m-2 h-1 for CO2 and from 0.06 to 3.66 mg CH4-C m-2 h-1 for CH4 fluxes. Mound CO2 fluxes varied seasonally with a 64 % decrease and 35 % increase in the fluxes from dry to wet season at the open grassland and shaded bushland sites, respectively. During the wet season, the CO2 fluxes were significantly correlated with termite mound volume. The diurnal measurements from two M. michaelseni mounds suggest that the gas fluxes peak during daytime and midnight supporting the previously presented model of thermally driven air circulation inside the mound and possibly enhanced ventilation during the night by the opening of foraging routes. The stability of the mound gas fluxes over diurnal and annual scales coincides with the constant nature of the nest internal gas and thermal environment that guarantees continuously favorable conditions for the fungal symbiont. Soil fluxes of both CO2 and CH4 were enhanced at up to 2 m distance from the mounds compared to the local soil respiration, indicating that, in addition to mound ventilation structures, a small proportion of the produced metabolic gases leave the nest also via surrounding soils. [ABSTRACT FROM AUTHOR]

The role of precipitation (P) variability with respect to evapotranspiration (ET) and its two components, transpiration (T) and evaporation (E), from savannas continues to draw significant research interest given its relevance to a number of ecohydrological applications. Our study reports on 6 years of measured ET and estimated T and E from a grazed savanna grassland at Welgegund, South Africa. Annual P varied significantly with respect to amount (508 to 672 mm yr -1), with dry years characterized by infrequent early-season rainfall. T was determined using annual water-use efficiency and gross primary production estimates derived from eddy-covariance measurements of latent heat flux and net ecosystem CO2 exchange rates. The computed annual T for the 4 wet years with frequent early wet-season rainfall was nearly constant, 326±19 mm yr -1 (T/ET=0.51), but was lower and more variable between the 2 dry years (255 and 154 mm yr -1 , respectively). Annual T and T/ET were linearly related to the early wet-season storm frequency. The constancy of annual T during wet years is explained by the moderate water stress of C4 grasses as well as trees' ability to use water from deeper layers. During extreme drought, grasses respond to water availability with a dieback–regrowth pattern, reducing leaf area and transpiration and, thus, increasing the proportion of transpiration contributed by trees. The works suggest that the early-season P distribution explains the interannual variability in T , which should be considered when managing grazing and fodder production in these grasslands. [ABSTRACT FROM AUTHOR]

The ecosystem-atmosphere flux of biogenic volatile organic compounds (BVOCs) has important impacts on tropospheric oxidative capacity and the formation of secondary organic aerosols, influencing air quality and climate. Here we present within-canopy measurements of a set of dominant BVOCs in a managed spruce- and pine-dominated boreal forest located at the ICOS station Norunda in Sweden, collected using proton transfer reaction mass spectrometry (PTR-MS) during 2014–2016, and vertical emission profiles derived from these data. Ozone concentrations were simultaneously measured in conjunction with these PTR-MS measurements. The main BVOCs investigated with the PTR-MS were isoprene, monoterpenes, methanol, acetaldehyde, and acetone. The distribution of BVOC sources and sinks in the forest canopy was explored using Lagrangian dispersion matrix methods, in particular continuous near-field theory. The forest canopy was found to contribute ca. 86 % to the total monoterpene emission in summertime, whereas the below-canopy and canopy emission was comparable (ca. 42 % and 58 % respectively) during the autumn period. This result indicates that boreal forest litter and other below-canopy emitters are a principle source for total forest monoterpene emissions during autumn months. During night, our results for methanol, acetone, and acetaldehyde seasonally present strong sinks in the forest canopy, especially in the autumn, likely due to the nighttime formation of dew on vegetation surfaces. [ABSTRACT FROM AUTHOR]

Emissions of biogenic volatile organic compounds (BVOCs) are a crucial component of biosphere-atmosphere interactions. In northern latitudes, climate change is amplified by feedback processes in which BVOCs have a recognized, yet poorly quantified role, mainly due to a lack of measurements and concomitant modeling gaps. Hence, current Earth system models mostly rely on temperature responses measured on vegetation from lower latitudes, rendering their predictions highly uncertain. Here, we show how tundra isoprene emissions respond vigorously to temperature increases, compared to model results. Our unique dataset of direct eddy covariance ecosystem-level isoprene measurements in two contrasting ecosystems exhibited Q10 (the factor by which the emission rate increases with a 10 °C rise in temperature) temperature coefficients of up to 20.8, that is, 3.5 times the Q10 of 5.9 derived from the equivalent model calculations. Crude estimates using the observed temperature responses indicate that tundra vegetation could enhance their isoprene emissions by up to 41% (87%)--that is, 46% (55%) more than estimated by models--with a 2 °C (4 °C) warming. Our results demonstrate that tundra vegetation possesses the potential to substantially boost its isoprene emissions in response to future rising temperatures, at rates that exceed the current Earth system model predictions. [ABSTRACT FROM AUTHOR]

The reasons for spatial and temporal variation of methane emission from mire ecosystems are not fully understood. Stable isotope signatures of the emitted methane can offer cues to the causes of these variations. We measured the methane emission and 13C-signature of emitted methane by automated chambers at a temperate mire for two growing seasons. In addition, we used ambient methane mixing ratios and δ13C-CH4 to calculate a mire-scale 13C signature using a nocturnal boundary-layer accumulation approach. Microbial methanogenic and methanotrophic communities were determined by a captured metagenomics analysis. The chamber measurements showed large and systematic spatial variations in δ13C-CH4 of up to 15 ‰ but smaller and less systematic temporal variation. The trophic status of methanogenesis was the dominant factor explaining the spatial variation. Genetic analysis indicated that methanogenic communities at all sample locations were able to utilize both hydrogenotrophic and acetoclastic pathways and could thus adapt to trophic status. The temporal variation of methane emission and δ13C-CH4 over the growing seasons showed hysteresis-like behavior, indicative of time-lagged responses to temperature and trophic status. The up-scaled chamber measurements and nocturnal boundary-layer accumulation measurements showed similar average δ13C-CH4 values of -81.3 ‰ and -79.3 ‰, respectively, lending confidence to the use of mire scale isotopic signatures to be used in e.g. atmospheric inversion modelling of methane sources. The results obtained can constrain our theories on the variability of methane emission from mire ecosystems and be useful in development of numerical models of mire biogeochemistry. [ABSTRACT FROM AUTHOR]

Recent climate change mitigation strategies rely on the reduction of methane (CH4) emissions. δ13CCH4 and δ²HCH4 measurements can be used to distinguish sources and thus to understand the CH4 budget better. The CH4 emission estimates by models are sensitive to the isotopic signatures assigned to each source category, so it is important to provide representative estimates of the different CH4 source isotopic signatures worldwide. We present new measurements of isotope signatures of various, mainly anthropogenic, CH4 sources in Europe, which represent a substantial contribution to the global dataset of source isotopic measurements from the literature, especially for δ²HCH4. They improve the definition of δ13CCH4 from waste sources, and demonstrate the use of δ²HCH4 for fossil fuel source attribution. Results from previous studies were combined in a common database that we updated with our new measurements, as well as with additional literature. We found that microbial sources are generally well characterised. The large variability in fossil fuels isotopic compositions requires particular care in the choice of weighting criteria for the calculation of a representative global value. The global dataset could be further improved by measurements from African, South American and Asian countries, as well as more measurements from pyrogenic sources. The final version of the European methane isotope database coupled with a global inventory of fossil and non-fossil δ13CCH4 and δ²HCH4 source signature measurements, is available at: https://doi.org/10.24416/UU01-4PO56T (Menoud et al., 2021a). [ABSTRACT FROM AUTHOR]

Microbial communities of methane (CH4) producing methanogens and consuming methanotrophs play an important role for Earth's atmospheric CH4 budget. Despite their global significance, knowledge on how much they control the spatial variation in CH4 fluxes from peatlands is poorly understood. We studied variation in CH4 producing and consuming communities in a natural peatland dominated by Eriophorum vaginatum, via a metagenomics approach using custom designed hybridization-based oligonucleotide probes to focus on taxa and functions associated with methane cycling. We hypothesized that sites with different magnitudes of methane flux are occupied by structurally and functionally different microbial communities, despite the dominance of a single vascular plant species. To investigate this, nine plant-peat mesocosms dominated by the sedge Eriophorum vaginatum, with varying vegetation coverage, were collected from a temperate natural wetland and subjected to a simulated growing season. During the simulated growing season, measurements of CH4 emission, carbon dioxide (CO2) exchange and δ13C signature of emitted CH4 were made. Mesocosms 1 through 9 were classified into three categories according to the magnitude of CH4 flux. Gross primary production and ecosystem respiration followed the same pattern as CH4 fluxes, but this trend was not observed in net ecosystem exchange. We observed that genetic functional potential was of minor importance in explaining spatial variability of CH4 fluxes with only small shifts in taxonomic community and functional genes. In addition, a higher β-diversity was observed in samples with high CH4 emission. Among methanogens, Methanoregula, made up over 50% of the community composition. This, in combination with the remaining hydrogenotrophic methanogens matched the δ13C isotopic signature of emitted CH4. However, the presence of acetoclastic and methylotrophic taxa and type I, II and Verrucomicrobia methanotrophs indicates that the microbial community holds the ability to produce and consume CH4 in multiple ways. This is important in terms of future climate scenarios, where peatlands are expected to alter in nutrient status, hydrology, and peat biochemistry. Due to the high functional potential, we expect the community to be highly adaptive to future climate scenarios. [ABSTRACT FROM AUTHOR]

The role of precipitation (P) variability on evapotranspiration (ET) and its two components, transpiration (T) and evaporation (E) from savannas, continues to draw significant research interest given its relevance to a number of eco-hydrological applications. Our study reports on six years of measured ET and estimated T and E from a grazed savanna grassland in Welgegund, South Africa. Annual P varied significantly in amount (508 to 672 mm yr-1), with dry years characterized by infrequent early-season rainfall. T was determined using annual water-use efficiency and gross primary production estimates derived from eddy covariance measurements of latent heat flux and net ecosystem CO2 exchange rates. The computed annual T was nearly constant, 331 ± 11 mm yr-1 (T/ET=0.52), for the four wet years with frequent early wet-season rainfall, whereas annual T was 268 and 175 mm yr-1 during the dry years. Annual T/ET was linearly related to the early wet-season storm frequency. The constancy of annual T during wet years is explained by the moderate water stress of C4 grass and constant annual tree transpiration covering 15% of the landscape. However, grass transpiration declines during dry spells. Moreover, grasses respond to water availability with a dieback-regrowth pattern, reducing leaf area and transpiration during drought. These changes lead to an anomalous monthly T/ET relation to leaf-area index (LAI). The results highlight the role of the C4 grass layer in the hydrological balance and suggest that the grass response to dry spells and drought is reasonably described by precipitation timing. [ABSTRACT FROM AUTHOR]

Ecosystems exchange climate-relevant trace gases with the atmosphere, including volatile organic compounds (VOCs) that are a small but highly reactive part of the carbon cycle. VOCs have important ecological functions and implications for atmospheric chemistry and climate. We measured the ecosystem-level surface–atmosphere VOC fluxes using the eddy covariance technique at a shallow subarctic lake and an adjacent graminoid-dominated fen in northern Sweden during two contrasting periods: the peak growing season (mid-July) and the senescent period post-growing season (September–October). In July, the fen was a net source of methanol, acetaldehyde, acetone, dimethyl sulfide, isoprene, and monoterpenes. All of these VOCs showed a diel cycle of emission with maxima around noon and isoprene dominated the fluxes (93±22 µ mol m -2 d -1 , mean ± SE). Isoprene emission was strongly stimulated by temperature and presented a steeper response to temperature (Q10=14.5) than that typically assumed in biogenic emission models, supporting the high temperature sensitivity of arctic vegetation. In September, net emissions of methanol and isoprene were drastically reduced, while acetaldehyde and acetone were deposited to the fen, with rates of up to -6.7±2.8 µ mol m -2 d -1 for acetaldehyde. Remarkably, the lake was a sink for acetaldehyde and acetone during both periods, with average fluxes up to -19±1.3 µ mol m -2 d -1 of acetone in July and up to -8.5±2.3 µ mol m -2 d -1 of acetaldehyde in September. The deposition of both carbonyl compounds correlated with their atmospheric mixing ratios, with deposition velocities of -0.23±0.01 and -0.68±0.03 cm s -1 for acetone and acetaldehyde, respectively. Even though these VOC fluxes represented less than 0.5 % and less than 5 % of the CO 2 and CH 4 net carbon ecosystem exchange, respectively, VOCs alter the oxidation capacity of the atmosphere. Thus, understanding the response of their emissions to climate change is important for accurate prediction of the future climatic conditions in this rapidly warming area of the planet. [ABSTRACT FROM AUTHOR]

The main source of soil moisture variability in savanna ecosystems is pulsed rainfall. Rainfall pulsing impacts water‐stress durations, soil moisture switching between wet‐to‐dry and dry‐to‐wet states, and soil moisture spectra as well as derived measures from it such as soil moisture memory. Rainfall pulsing is also responsible for rapid changes in grassland leaf area and concomitant changes in evapotranspirational (ET) losses, which then impact soil moisture variability. With the use of a hierarchy of models and soil moisture measurements, temporal variability in root‐zone soil moisture and water‐stress periods are analysed at four African sites ranging from grass to miombo savannas. The normalized difference vegetation index (NDVI) and potential ET (PET)‐adjusted ET model predict memory timescale and dry persistence in agreement with measurements. The model comparisons demonstrate that dry persistence and mean annual dry periods must account for seasonal and interannual changes in maximum ET represented by NDVI and to a lesser extent PET. Interestingly, the precipitation intensity and soil moisture memory were linearly related across three savannas with ET/infiltration ∼ 1.0. This relation and the variability of length and timing of dry periods are also discussed. [ABSTRACT FROM AUTHOR]

Field measurement data on greenhouse gas (GHG) emissions are still scarce for many land-use types in Africa, causing a high level of uncertainty in GHG budgets. To address this gap, we present in situ measurements of carbon dioxide (CO2), nitrous oxide (N2O), and methane (CH4) emissions from the lowlands of southern Kenya. We conducted eight chamber measurement campaigns on gas exchange from four dominant land-use types (LUTs) comprising (1) cropland, (2) bushland, (3) grazing land, and (4) conservation land between 29 November 2017 and 3 November 2018, accounting for regional seasonality (wet and dry seasons and transitions periods). Mean CO2 emissions for the whole observation period were the highest by a significant margin (p value < 0.05) in the conservation land (75±6 mg CO2 -C m -2 h -1) compared to the three other sites, which ranged from 45±4 mg CO2 -C m -2 h -1 (bushland) to 50±5 mg CO2 -C m -2 h -1 (grazing land). Furthermore, CO2 emissions varied between seasons, with significantly higher emissions in the wet season than the dry season. Mean N2O emissions were highest in cropland (2.7±0.6 µ g N2O -N m -2 h -1) and lowest in bushland (1.2±0.4 µ g N2O -N m -2 h -1) but did not vary with season. In fact, N2O emissions were very low both in the wet and dry seasons, with slightly elevated values during the early days of the wet seasons in all LUTs. On the other hand, CH4 emissions did not show any significant differences across LUTs and seasons. Most CH4 fluxes were below the limit of detection (LOD, ±0.03 mg CH4 -C m -2 h -1). We attributed the difference in soil CO2 emissions between the four sites to soil C content, which differed between the sites and was highest in the conservation land. In addition, CO2 and N2O emissions positively correlated with soil moisture, thus an increase in soil moisture led to an increase in emissions. Furthermore, vegetation cover explained the seasonal variation in soil CO2 emissions as depicted by a strong positive correlation between the normalized difference vegetation index (NDVI) and CO2 emissions, most likely because, with more green (active) vegetation cover, higher CO2 emissions occur due to enhanced root respiration compared to drier periods. Soil temperature did not show a clear correlation with either CO2 or N2O emissions, which is likely due to the low variability in soil temperature between seasons and sites. Based on our results, soil C, active vegetation cover, and soil moisture are key drivers of soil GHG emissions in all the tested LUTs in southern Kenya. Our results are within the range of previous GHG flux measurements from soils from various LUTs in other parts of Kenya and contribute to more accurate baseline GHG emission estimates from Africa, which are key to reducing uncertainties in global GHG budgets as well as for informing policymakers when discussing low-emission development strategies. [ABSTRACT FROM AUTHOR]

The role of precipitation (P) variability on evapotranspiration (ET) and its two components transpiration (T) and evaporation (E) rates from savannas continues to draw significant research interest given its relevance to a number of eco-hydrological applications. The work here reports on six years of measured ET and energy flux components, and estimated T from a grazed savanna grassland collected at a research site situated in Welgegund, South Africa. During this period, annual P varied considerably in amount (421 mm to 614 mm), rainy season length and precipitation intensity. T was estimated using annual water use efficiency and gross primary production determined from eddy-covariance measurements of net ecosystem CO2 exchange rates. The computed annual T was highly constrained to 352 ± 8 mm (T/ET = 0.55) for four wet years when rainfall was near or above the long-term mean. This is explained by the near constant annual tree transpiration and moderate water stress of C4 grasses during these years. In a drought year with intermittent rainfall, the annual ecosystem T was reduced due to grass dieback-regrowth that alters the temporal dynamics of bare soil cover and infiltration, and complicates monthly T/ET relation to leaf-area index (LAI). However, annual ET remains approximately equal to annual precipitation (P) even during the drought year due to increased soil evaporation. Indeed, at annual scales, ET ≈ P and annual T is conservative despite variation in amount and timing in rainfall, due to constant water use of mature trees, and the ability of C4 grasses to maintain transpiration at moderate water stress and effectively use pulsed rainfall. [ABSTRACT FROM AUTHOR]

For effective climate change mitigation strategies, adequate data on greenhouse gas (GHG) emissions from a wide range of land-use and land cover types area prerequisite. However, GHG field measurement data are still scarce for many land-use types in Africa, causing a high uncertainty in GHG budgets. To address this knowledge gap, we present in situ measurements of carbon dioxide (CO2), nitrous oxide (N2O), and methane (CH4) emissions in the lowland part of southern Kenya. We conducted chamber measurements on gas exchange from four dominant land-use types (LUTs) and included (1) cropland, (2) grazed savanna, (3) bushland, and (4) conservation land. Between 29 November 2017 to 3 November 2018, eight measurement campaigns were conducted accounting for regional seasonality (including wet and dry seasons and transitions periods) in each LUT. Mean CO2 emissions for the whole observation period were significantly higher (p-value < 0.05) in the conservation land (75 ± 6 mg CO2-C m-2 h-1) compared to the three other sites, which ranged from 45 ± 4 mg CO2-C m-2 h-1 (bushland) to 50 ± 5 mg CO2-C m-2 h-1 (grazing land). Furthermore, CO2 emissions varied between seasons, with significantly higher emissions during the wet season than the dry season. In contrast, mean N2O emissions were not different between the four sites, ranging from 1.2 ± 0.4 µg N2O-N m-2 h-1 (in bushland) to 2.7 ± 0.6 µg N2O-N m-2 h-1 (in cropland). However, N2O emissions were slightly elevated during the early days of the wet season. CH4 emissions did not show any significant differences between LUTs and seasons, and most values were below the limit of detection (LOD, 0.03 mg CH4-C m-2 h-1). We attributed the difference in soil CO2 emissions between the four sites to soil C content, which differed between the sites and was highest in the conservation land. CO2 and N2O emissions positively correlated to soil moisture, thus an increase in soil moisture led to an increase in emissions. Soil temperature did not show a clear correlation with either, most likely due to the low annual variation in soil temperature. We found a strong positive correlation between soil CO2 and the normalized difference vegetation index (NDVI), but we observed no correlation with soil N2O emissions. We conclude that soil moisture is a key factor in soil GHG emissions in these tropical savanna LUTs. In addition, including vegetation indices in the model greatly improved the results, thus showing the importance of vegetation cover in predicting soil emissions. Our results are within the range of previous GHG flux measurements from soils from various land-use types in other parts of Kenya and contribute to more accurate baseline GHG emission estimates from Africa, which are key for informing policymakers when discussing low-emission development strategies. [ABSTRACT FROM AUTHOR]

Abstract: We have analyzed decade‐long methane flux data set from a boreal fen, Siikaneva, together with data on environmental parameters and carbon dioxide exchange. The methane flux showed seasonal cycle but no systematic diel cycle. The highest fluxes were observed in July–August with average value of 73 nmol m−2 s−1. Wintertime fluxes were small but positive, with January–March average of 6.7 nmol m−2 s−1. Daily average methane emission correlated best with peat temperatures at 20–35 cm depths. The second highest correlation was with gross primary production (GPP). The best correspondence between emission algorithm and measured fluxes was found for a variable‐slope generalized linear model (r2 = 0.89) with peat temperature at 35 cm depth and GPP as explanatory variables, slopes varying between years. The homogeneity of slope approach indicated that seasonal variation explained 79% of the sum of squares variation of daily average methane emission, the interannual variation in explanatory factors 7.0%, functional change 5.3%, and random variation 9.1%. Significant correlation between interannual variability of growing season methane emission and that of GPP indicates that on interannual time scales GPP controls methane emission variability, crucially for development of process‐based methane emission models. Annual methane emission ranged from 6.0 to 14 gC m−2 and was 2.7 ± 0.4% of annual GPP. Over 10‐year period methane emission was 18% of net ecosystem exchange as carbon. The weak relation of methane emission to water table position indicates that space‐to‐time analogy, used to extrapolate spatial chamber data in time, may not be applicable in seasonal time scales. [ABSTRACT FROM AUTHOR]

The Arctic tundra plays an important role in the carbon cycle as it stores 50% of global soil organic carbon reservoirs. The processes (fluxes) regulating these stocks are predicted to change due to direct and indirect effects of climate change. Understanding the current and future carbon balance calls for a summary of the level of knowledge regarding chamber-derived carbon dioxide (CO2) flux studies. Here, we describe progress from recently (2000–2016) published studies of growing-season CO2 flux chamber measurements, namely GPP (gross primary production), ER (ecosystem respiration), and NEE (net ecosystem exchange), in the tundra region. We review the study areas and designs along with the explanatory environmental drivers used. Most of the studies were conducted in Alaska and Fennoscandia, and we stress the need for measuring fluxes in other tundra regions, particularly in more extreme climatic, productivity, and soil conditions. Soil respiration and other greenhouse gas measurements were seldom included in the studies. Although most of the environmental drivers of CO2 fluxes have been relatively well investigated (such as the effect of vegetation type and soil microclimate on fluxes), soil nutrients, other greenhouse gases and disturbance regimes require more research as they might define the future carbon balance. Particular attention should be paid to the effects of shrubification, geomorphology, and other disturbance effects such as fire events, and disease and herbivore outbreaks. An improved conceptual framework and understanding of underlying processes of biosphere–atmosphere CO2 exchange will provide more information on carbon cycling in the tundra. [ABSTRACT FROM AUTHOR]

We measured methane fluxes of a patterned bog situated in Siikaneva in southern Finland from six different plant community types in three growing seasons (2012-2014) using the static chamber method with chamber exposure of 35 min. A mixed-effects model was applied to quantify the effect of the controlling factors on the methane flux. The plant community types differed from each other in their water level, species composition, total leaf area (LAITOT/and leaf area of aerenchymatous plant species (LAIAER/. Methane emissions ranged from -309 to 1254 mgm-2 d-1. Although methane fluxes increased with increasing peat temperature, LAITOT and LAIAER, they had no correlation with water table or with plant community type. The only exception was higher fluxes from hummocks and high lawns than from high hummocks and bare peat surfaces in 2013 and from bare peat surfaces than from high hummocks in 2014. Chamber fluxes upscaled to ecosystem level for the peak season were of the same magnitude as the fluxes measured with the eddy covariance (EC) technique. In 2012 and in August 2014 there was a good agreement between the two methods; in 2013 and in July 2014, the chamber fluxes were higher than the EC fluxes. Net fluxes to soil, indicating higher methane oxidation than production, were detected every year and in all community types. Our results underline the importance of both LAIAER and LAITOT in controlling methane fluxes and indicate the need for automatized chambers to reliably capture localized events to support the more robust EC method. [ABSTRACT FROM AUTHOR]

Wetlands are one of the most significant natural sources of methane (CH4/to the atmosphere. They emit CH4 because decomposition of soil organic matter in waterlogged anoxic conditions produces CH4, in addition to carbon dioxide (CO2/. Production of CH4 and how much of it escapes to the atmosphere depend on a multitude of environmental drivers. Models simulating the processes leading to CH4 emissions are thus needed for upscaling observations to estimate present CH4 emissions and for producing scenarios of future atmospheric CH4 concentrations. Aiming at a CH4 model that can be added to models describing peatland carbon cycling, we composed a model called HIMMELI that describes CH4 build-up in and emissions from peatland soils. It is not a full peatland carbon cycle model but it requires the rate of anoxic soil respiration as input. Driven by soil temperature, leaf area index (LAI) of aerenchymatous peatland vegetation, and water table depth (WTD), it simulates the concentrations and transport of CH4, CO2, and oxygen (O2/in a layered one-dimensional peat column. Here, we present the HIMMELI model structure and results of tests on the model sensitivity to the input data and to the description of the peat column (peat depth and layer thickness), and demonstrate that HIMMELI outputs realistic fluxes by comparing modeled and measured fluxes at two peatland sites. As HIMMELI describes only the CH4-related processes, not the full carbon cycle, our analysis revealed mechanisms and dependencies that may remain hidden when testing CH4 models connected to complete peatland carbon models, which is usually the case. Our results indicated that (1) the model is flexible and robust and thus suitable for different environments; (2) the simulated CH4 emissions largely depend on the prescribed rate of anoxic respiration; (3) the sensitivity of the total CH4 emission to other input variables is mainly mediated via the concentrations of dissolved gases, in particular, the O2 concentrations that affect the CH4 production and oxidation rates; (4) with given input respiration, the peat column description does not significantly affect the simulated CH4 emissions in this model version. [ABSTRACT FROM AUTHOR]

We measured methane fluxes of a patterned bog from six different plant community types in three growing seasons 2012-2014 using the static chamber method. A mixed effects model was applied for quantifying the effect of the controlling factors on the methane flux. The plant community types differed from each other in their water level, total leaf area (LAITOT) and leaf area of aerenchymatous plant species (LAIAER). Excluding the highest 2.5 % of all fluxes, methane emissions ranged from -309 to 556 mg m-2 d-1. Although methane fluxes increased with increasing peat temperature, LAITOT and LAIAER, they had no correlation with water table or with plant community type. The only exception were higher fluxes from hummocks than from other plant community types in 2013. Chamber fluxes upscaled to ecosystem level for the peak season were of the same magnitude as the fluxes measured with the eddy covariance (EC) technique. In 2012 and in August 2014 there was a good agreement between the two methods, in 2013 and in July 2014, the chamber fluxes were higher than the EC fluxes. Net fluxes to soil, indicating higher methane oxidation than production, were detected every year and on all community types. Exceptionally high methane emissions up to 17 000 mg m-2 d-1 were measured sporadically in 2013 and 2014. These extreme emissions not detected in EC measurements we were not able to exclude as measurement errors and they did not correlate with any measured variables. Our results underline the importance of both LAIAER and LAITOT in controlling methane fluxes and indicate need for automatized chambers to reliably capture localized events to support more robust EC method. [ABSTRACT FROM AUTHOR]