scholarly journals Methane emissions from floodplains in the Amazon Basin: challenges in developing a process-based model for global applications

2014 ◽  
Vol 11 (6) ◽  
pp. 1519-1558 ◽  
Author(s):  
B. Ringeval ◽  
S. Houweling ◽  
P. M. van Bodegom ◽  
R. Spahni ◽  
R. van Beek ◽  
...  

Abstract. Tropical wetlands are estimated to represent about 50% of the natural wetland methane (CH4) emissions and explain a large fraction of the observed CH4 variability on timescales ranging from glacial–interglacial cycles to the currently observed year-to-year variability. Despite their importance, however, tropical wetlands are poorly represented in global models aiming to predict global CH4 emissions. This publication documents a first step in the development of a process-based model of CH4 emissions from tropical floodplains for global applications. For this purpose, the LPX-Bern Dynamic Global Vegetation Model (LPX hereafter) was slightly modified to represent floodplain hydrology, vegetation and associated CH4 emissions. The extent of tropical floodplains was prescribed using output from the spatially explicit hydrology model PCR-GLOBWB. We introduced new plant functional types (PFTs) that explicitly represent floodplain vegetation. The PFT parameterizations were evaluated against available remote-sensing data sets (GLC2000 land cover and MODIS Net Primary Productivity). Simulated CH4 flux densities were evaluated against field observations and regional flux inventories. Simulated CH4 emissions at Amazon Basin scale were compared to model simulations performed in the WETCHIMP intercomparison project. We found that LPX reproduces the average magnitude of observed net CH4 flux densities for the Amazon Basin. However, the model does not reproduce the variability between sites or between years within a site. Unfortunately, site information is too limited to attest or disprove some model features. At the Amazon Basin scale, our results underline the large uncertainty in the magnitude of wetland CH4 emissions. Sensitivity analyses gave insights into the main drivers of floodplain CH4 emission and their associated uncertainties. In particular, uncertainties in floodplain extent (i.e., difference between GLC2000 and PCR-GLOBWB output) modulate the simulated emissions by a factor of about 2. Our best estimates, using PCR-GLOBWB in combination with GLC2000, lead to simulated Amazon-integrated emissions of 44.4 ± 4.8 Tg yr−1. Additionally, the LPX emissions are highly sensitive to vegetation distribution. Two simulations with the same mean PFT cover, but different spatial distributions of grasslands within the basin, modulated emissions by about 20%. Correcting the LPX-simulated NPP using MODIS reduces the Amazon emissions by 11.3%. Finally, due to an intrinsic limitation of LPX to account for seasonality in floodplain extent, the model failed to reproduce the full dynamics in CH4 emissions but we proposed solutions to this issue. The interannual variability (IAV) of the emissions increases by 90% if the IAV in floodplain extent is accounted for, but still remains lower than in most of the WETCHIMP models. While our model includes more mechanisms specific to tropical floodplains, we were unable to reduce the uncertainty in the magnitude of wetland CH4 emissions of the Amazon Basin. Our results helped identify and prioritize directions towards more accurate estimates of tropical CH4 emissions, and they stress the need for more research to constrain floodplain CH4 emissions and their temporal variability, even before including other fundamental mechanisms such as floating macrophytes or lateral water fluxes.

2013 ◽  
Vol 10 (10) ◽  
pp. 16713-16803 ◽  
Author(s):  
B. Ringeval ◽  
S. Houweling ◽  
P. M. van Bodegom ◽  
R. Spahni ◽  
R. van Beek ◽  
...  

Abstract. Tropical wetlands are estimated to represent about 50% of the natural wetland emissions and explain a large fraction of the observed CH4 variability on time scales ranging from glacial-interglacial cycles to the currently observed year-to-year variability. Despite their importance, however, tropical wetlands are poorly represented in global models aiming to predict global CH4 emissions. This study documents the first regional-scale, process-based model of CH4 emissions from tropical floodplains. The LPX-Bern Dynamic Global Vegetation Model (LPX hereafter) was modified to represent floodplain hydrology, vegetation and associated CH4 emissions. The extent of tropical floodplains was prescribed using output from the spatially-explicit hydrology model PCR-GLOBWB. We introduced new Plant Functional Types (PFTs) that explicitly represent floodplain vegetation. The PFT parameterizations were evaluated against available remote sensing datasets (GLC2000 land cover and MODIS Net Primary Productivity). Simulated CH4 flux densities were evaluated against field observations and regional flux inventories. Simulated CH4 emissions at Amazon Basin scale were compared to model simulations performed in the WETCHIMP intercomparison project. We found that LPX simulated CH4 flux densities are in reasonable agreement with observations at the field scale but with a~tendency to overestimate the flux observed at specific sites. In addition, the model did not reproduce between-site variations or between-year variations within a site. Unfortunately, site informations are too limited to attest or disprove some model features. At the Amazon Basin scale, our results underline the large uncertainty in the magnitude of wetland CH4 emissions. In particular, uncertainties in floodplain extent (i.e., difference between GLC2000 and PCR-GLOBWB output) modulate the simulated emissions by a factor of about 2. Our best estimates, using PCR-GLOBWB in combination with GLC2000, lead to simulated Amazon-integrated emissions of 44.4 ± 4.8 Tg yr−1. Additionally, the LPX emissions are highly sensitive to vegetation distribution. Two simulations with the same mean PFT cover, but different spatial distributions of grasslands within the basin modulated emissions by about 20%. Correcting the LPX simulated NPP using MODIS reduces the Amazon emissions by 11.3%. Finally, due to an intrinsic limitation of LPX to account for seasonality in floodplain extent, the model failed to reproduce the seasonality in CH4 emissions. The Inter Annual Variability (IAV) of the emissions increases by 90% if the IAV in floodplain extent is account for, but still remains lower than in most of WETCHIMP models. While our model includes more mechanisms specific to tropical floodplains, we were unable to reduce the uncertainty in the magnitude of wetland CH4 emissions of the Amazon Basin. Our results stress the need for more research to constrain floodplain CH4 emissions and their temporal variability.


2017 ◽  
Author(s):  
Eduardo Eiji Maeda ◽  
Xuanlong Ma ◽  
Fabien Wagner ◽  
Hyungjun Kim ◽  
Taikan Oki ◽  
...  

Abstract. Evapotranspiration (ET) of Amazon forests is a main driver of regional climate patterns and an important indicator of ecosystem functioning. Despite its importance, the seasonal variability of ET over Amazon forests, and its relationship with environmental drivers, is still poorly understood. In this study, we carry out a water balance approach to analyse seasonal patterns in ET and their relationships with water and energy drivers over five sub-basins across the Amazon basin. We used in-situ measurements of river discharge, and remotely sensed estimates of terrestrial water storage, rainfall, and solar radiation. We show that the characteristics of ET seasonality in all sub-basins differ in timing and magnitude. The highest mean annual ET was found in the northern Rio Negro basin (~ 1497 mm year−1) and the lowest values in the Solimões River basin (~ 986 mm year−1). For the first time in a basin-scale study, using observational data, we show that factors limiting ET vary across climatic gradients in the Amazon, confirming local-scale eddy covariance studies. Both annual mean and seasonality in ET are driven by a combination of energy and water availability, as neither rainfall nor radiation alone could explain patterns in ET. In southern basins, despite seasonal rainfall deficits, deep root water uptake allows increasing rates of ET during the dry season, when radiation is usually higher than in the wet season. We demonstrate contrasting ET seasonality with satellite greenness across Amazon forests, with strong asynchronous relationships in ever-wet watersheds, and positive correlations observed in seasonally dry watersheds. Finally, we compared our results with estimates obtained by two ET models, and we conclude that neither of the two tested models could provide a consistent representation of ET seasonal patterns across the Amazon.


2012 ◽  
Vol 12 (13) ◽  
pp. 6041-6065 ◽  
Author(s):  
M. O. Andreae ◽  
P. Artaxo ◽  
V. Beck ◽  
M. Bela ◽  
S. Freitas ◽  
...  

Abstract. We present the results of airborne measurements of carbon monoxide (CO) and aerosol particle number concentration (CN) made during the Balanço Atmosférico Regional de Carbono na Amazônia (BARCA) program. The primary goal of BARCA is to address the question of basin-scale sources and sinks of CO2 and other atmospheric carbon species, a central issue of the Large-scale Biosphere-Atmosphere (LBA) program. The experiment consisted of two aircraft campaigns during November–December 2008 (BARCA-A) and May–June 2009 (BARCA-B), which covered the altitude range from the surface up to about 4500 m, and spanned most of the Amazon Basin. Based on meteorological analysis and measurements of the tracer, SF6, we found that airmasses over the Amazon Basin during the late dry season (BARCA-A, November 2008) originated predominantly from the Southern Hemisphere, while during the late wet season (BARCA-B, May 2009) low-level airmasses were dominated by northern-hemispheric inflow and mid-tropospheric airmasses were of mixed origin. In BARCA-A we found strong influence of biomass burning emissions on the composition of the atmosphere over much of the Amazon Basin, with CO enhancements up to 300 ppb and CN concentrations approaching 10 000 cm−3; the highest values were in the southern part of the Basin at altitudes of 1–3 km. The ΔCN/ΔCO ratios were diagnostic for biomass burning emissions, and were lower in aged than in fresh smoke. Fresh emissions indicated CO/CO2 and CN/CO emission ratios in good agreement with previous work, but our results also highlight the need to consider the residual smoldering combustion that takes place after the active flaming phase of deforestation fires. During the late wet season, in contrast, there was little evidence for a significant presence of biomass smoke. Low CN concentrations (300–500 cm−3) prevailed basinwide, and CO mixing ratios were enhanced by only ~10 ppb above the mixing line between Northern and Southern Hemisphere air. There was no detectable trend in CO with distance from the coast, but there was a small enhancement of CO in the boundary layer suggesting diffuse biogenic sources from photochemical degradation of biogenic volatile organic compounds or direct biological emission. Simulations of CO distributions during BARCA-A using a range of models yielded general agreement in spatial distribution and confirm the important contribution from biomass burning emissions, but the models evidence some systematic quantitative differences compared to observed CO concentrations. These mismatches appear to be related to problems with the accuracy of the global background fields, the role of vertical transport and biomass smoke injection height, the choice of model resolution, and reliability and temporal resolution of the emissions data base.


2016 ◽  
Vol 20 (8) ◽  
pp. 3077-3098 ◽  
Author(s):  
Carlos Rocha ◽  
Cristina Veiga-Pires ◽  
Jan Scholten ◽  
Kay Knoeller ◽  
Darren R. Gröcke ◽  
...  

Abstract. Natural radioactive tracer-based assessments of basin-scale submarine groundwater discharge (SGD) are well developed. However, SGD takes place in different modes and the flow and discharge mechanisms involved occur over a wide range of spatial and temporal scales. Quantifying SGD while discriminating its source functions therefore remains a major challenge. However, correctly identifying both the fluid source and composition is critical. When multiple sources of the tracer of interest are present, failure to adequately discriminate between them leads to inaccurate attribution and the resulting uncertainties will affect the reliability of SGD solute loading estimates. This lack of reliability then extends to the closure of local biogeochemical budgets, confusing measures aiming to mitigate pollution.Here, we report a multi-tracer study to identify the sources of SGD, distinguish its component parts and elucidate the mechanisms of their dispersion throughout the Ria Formosa – a seasonally hypersaline lagoon in Portugal. We combine radon budgets that determine the total SGD (meteoric + recirculated seawater) in the system with stable isotopes in water (δ2H, δ18O), to specifically identify SGD source functions and characterize active hydrological pathways in the catchment. Using this approach, SGD in the Ria Formosa could be separated into two modes, a net meteoric water input and another involving no net water transfer, i.e., originating in lagoon water re-circulated through permeable sediments. The former SGD mode is present occasionally on a multi-annual timescale, while the latter is a dominant feature of the system. In the absence of meteoric SGD inputs, seawater recirculation through beach sediments occurs at a rate of  ∼  1.4  ×  106 m3 day−1. This implies that the entire tidal-averaged volume of the lagoon is filtered through local sandy sediments within 100 days ( ∼  3.5 times a year), driving an estimated nitrogen (N) load of  ∼  350 Ton N yr−1 into the system as NO3−. Land-borne SGD could add a further  ∼  61 Ton N yr−1 to the lagoon. The former source is autochthonous, continuous and responsible for a large fraction (59 %) of the estimated total N inputs into the system via non-point sources, while the latter is an occasional allochthonous source capable of driving new production in the system.


2019 ◽  
Author(s):  
Richard Coppell ◽  
Emanuel Gloor ◽  
Joseph Holden

Abstract. Peatlands are important carbon stores and Sphagnum moss represents a critical peatland genus contributing to carbon exchange and storage. However, gas fluxes in Sphagnum-dominated systems are poorly represented in Dynamic Global Vegetation Models (DGVMs) which simulate, via incorporation of Plant Functional Types (PFTs), biogeochemical and energy fluxes between vegetation, the land surface and the atmosphere. Mechanisms characterised by PFTs within DGVMs include photosynthesis, respiration and competition and, in more recent DGVMs, sub-daily gas-exchange processes regulated by leaf 10 stomata. However, Sphagnum, like all mosses, are non-vascular plants and do not exhibit stomatal regulation. In order to achieve a level of process detail consistent with existing vascular vegetation PFTs within DGVMs, this paper describes a new process-based non-vascular-PFT model that is implemented within the TRIFFID DGVM used by the JULES land surface model. The new PFT model was tested against extant published field and laboratory studies of peat assemblage-net primary productivity, assemblage-gross primary productivity, assemblage respiration, water-table position, incoming 15 photosynthetically active radiation, temperature, and canopy dark respiration. The PFT model’s parameters were roughly tuned and the PFT model easily produced curves of the correct shape for peat assemblage-net primary productivity against water-table position, incoming photosynthetically active radiation and temperature, suggesting that it replicates the internal productivity mechanism of Sphagnum for the first time. Minor modifications should also allow it to be used across a range of other bryophytes enabling this non-vascular PFT model to have enhanced functionality.


2012 ◽  
Vol 9 (12) ◽  
pp. 5199-5215 ◽  
Author(s):  
T. Li ◽  
Y. Huang ◽  
W. Zhang ◽  
Y.-Q. Yu

Abstract. Wetland loss and climate change are known to alter regional and global methane (CH4) budgets. Over the last six decades, an extensive area of marshland has been converted to cropland on the Sanjiang Plain in northeast China, and a significant increase in air temperature has also been observed there, while the impacts on regional CH4 budgets remain uncertain. Through model simulation, we estimated the changes in CH4 emissions associated with the conversion of marshland to cropland and climate change in this area. Model simulations indicated a significant reduction of 1.1 Tg yr−1 (0.7–1.8 Tg yr−1) from the 1950s to the 2000s in regional CH4 emissions. The cumulative reduction of CH4 from 1960 to 2009 was estimated to be ~36 Tg (24–57 Tg) relative to the 1950s, and marshland conversion and the climate contributed 86% and 14% of this change, respectively. Interannual variation in precipitation (linear trend with P > 0.2) contributed to yearly fluctuations in CH4 emissions, but the relatively lower amount of precipitation over the period 1960–2009 (47 mm yr−1 lower on average than in the 1950s) contributed ~91% of the reduction in the area-weighted CH4 flux. Global warming at a rate of 0.3 ° per decade (P < 0.001) has increased CH4 emissions significantly since the 1990s. Relative to the mean of the 1950s, the warming-induced increase in the CH4 flux has averaged 19 kg ha−1 yr−1 over the last two decades. In the RCP (Representative Concentration Pathway) 2.6, RCP 4.5, RCP 6.0 and RCP 8.5 scenarios of the fifth IPCC assessment report (AR5), the CH4 fluxes are predicted to increase by 36%, 52%, 78% and 95%, respectively, by the 2080s compared to 1961–1990 in response to climate warming and wetting.


2013 ◽  
Vol 10 (4) ◽  
pp. 2255-2272 ◽  
Author(s):  
A. D. A. Castanho ◽  
M. T. Coe ◽  
M. H. Costa ◽  
Y. Malhi ◽  
D. Galbraith ◽  
...  

Abstract. Dynamic vegetation models forced with spatially homogeneous biophysical parameters are capable of producing average productivity and biomass values for the Amazon basin forest biome that are close to the observed estimates, but these models are unable to reproduce observed spatial variability. Recent observational studies have shown substantial regional spatial variability of above-ground productivity and biomass across the Amazon basin, which is believed to be primarily driven by a combination of soil physical and chemical properties. In this study, spatial heterogeneity of vegetation properties is added to the Integrated Biosphere Simulator (IBIS) land surface model, and the simulated productivity and biomass of the Amazon basin are compared to observations from undisturbed forest. The maximum RuBiCo carboxylation capacity (Vcmax) and the woody biomass residence time (τw) were found to be the most important properties determining the modeled spatial variation of above-ground woody net primary productivity and biomass, respectively. Spatial heterogeneity of these properties may lead to simulated spatial variability of 1.8 times in the woody net primary productivity (NPPw) and 2.8 times in the woody above-ground biomass (AGBw). The coefficient of correlation between the modeled and observed woody productivity improved from 0.10 with homogeneous parameters to 0.73 with spatially heterogeneous parameters, while the coefficient of correlation between the simulated and observed woody above-ground biomass improved from 0.33 to 0.88. The results from our analyses with the IBIS dynamic vegetation model demonstrated that using single values for key ecological parameters in the tropical forest biome severely limits simulation accuracy. Clearer understanding of the biophysical mechanisms that drive the spatial variability of carbon allocation, τw and Vcmax is necessary to achieve further improvements to simulation accuracy.


2020 ◽  
Vol 13 (1) ◽  
pp. 153-164 ◽  
Author(s):  
Nina Löbs ◽  
Cybelli G. G. Barbosa ◽  
Sebastian Brill ◽  
David Walter ◽  
Florian Ditas ◽  
...  

Abstract. Bioaerosols are considered to play a relevant role in atmospheric processes, but their sources, properties, and spatiotemporal distribution in the atmosphere are not yet well characterized. In the Amazon Basin, primary biological aerosol particles (PBAPs) account for a large fraction of coarse particulate matter, and fungal spores are among the most abundant PBAPs in this area as well as in other vegetated continental regions. Furthermore, PBAPs could also be important ice nuclei in Amazonia. Measurement data on the release of fungal spores under natural conditions, however, are sparse. Here we present an experimental approach to analyze and quantify the spore release from fungi and other spore-producing organisms under natural and laboratory conditions. For measurements under natural conditions, the samples were kept in their natural environment and a setup was developed to estimate the spore release numbers and sizes as well as the microclimatic factors temperature and air humidity in parallel to the mesoclimatic parameters net radiation, rain, and fog occurrence. For experiments in the laboratory, we developed a cuvette to assess the particle size and number of newly released fungal spores under controlled conditions, simultaneously measuring temperature and relative humidity inside the cuvette. Both approaches were combined with bioaerosol sampling techniques to characterize the released particles using microscopic methods. For fruiting bodies of the basidiomycetous species, Rigidoporus microporus, the model species for which these techniques were tested, the highest frequency of spore release occurred in the range from 62 % to 96 % relative humidity. The results obtained for this model species reveal characteristic spore release patterns linked to environmental or experimental conditions, indicating that the moisture status of the sample may be a regulating factor, whereas temperature and light seem to play a minor role for this species. The presented approach enables systematic studies aimed at the quantification and validation of spore emission rates and inventories, which can be applied to a regional mapping of cryptogamic organisms under given environmental conditions.


2019 ◽  
Vol 19 (6) ◽  
pp. 4041-4059 ◽  
Author(s):  
Carsten Schaller ◽  
Fanny Kittler ◽  
Thomas Foken ◽  
Mathias Göckede

Abstract. Methane (CH4) emissions from biogenic sources, such as Arctic permafrost wetlands, are associated with large uncertainties because of the high variability of fluxes in both space and time. This variability poses a challenge to monitoring CH4 fluxes with the eddy covariance (EC) technique, because this approach requires stationary signals from spatially homogeneous sources. Episodic outbursts of CH4 emissions, i.e. triggered by spontaneous outgassing of bubbles or venting of methane-rich air from lower levels due to shifts in atmospheric conditions, are particularly challenging to quantify. Such events typically last for only a few minutes, which is much shorter than the common averaging interval for EC (30 min). The steady-state assumption is jeopardised, which potentially leads to a non-negligible bias in the CH4 flux. Based on data from Chersky, NE Siberia, we tested and evaluated a flux calculation method based on wavelet analysis, which, in contrast to regular EC data processing, does not require steady-state conditions and is allowed to obtain fluxes over averaging periods as short as 1 min. Statistics on meteorological conditions before, during, and after the detected events revealed that it is atmospheric mixing that triggered such events rather than CH4 emission from the soil. By investigating individual events in more detail, we identified a potential influence of various mesoscale processes like gravity waves, low-level jets, weather fronts passing the site, and cold-air advection from a nearby mountain ridge as the dominating processes. The occurrence of extreme CH4 flux events over the summer season followed a seasonal course with a maximum in early August, which is strongly correlated with the maximum soil temperature. Overall, our findings demonstrate that wavelet analysis is a powerful method for resolving highly variable flux events on the order of minutes, and can therefore support the evaluation of EC flux data quality under non-steady-state conditions.


2017 ◽  
Vol 8 (2) ◽  
pp. 439-454 ◽  
Author(s):  
Eduardo Eiji Maeda ◽  
Xuanlong Ma ◽  
Fabien Hubert Wagner ◽  
Hyungjun Kim ◽  
Taikan Oki ◽  
...  

Abstract. Evapotranspiration (ET) of Amazon forests is a main driver of regional climate patterns and an important indicator of ecosystem functioning. Despite its importance, the seasonal variability of ET over Amazon forests, and its relationship with environmental drivers, is still poorly understood. In this study, we carry out a water balance approach to analyse seasonal patterns in ET and their relationships with water and energy drivers over five sub-basins across the Amazon Basin. We used in situ measurements of river discharge, and remotely sensed estimates of terrestrial water storage, rainfall, and solar radiation. We show that the characteristics of ET seasonality in all sub-basins differ in timing and magnitude. The highest mean annual ET was found in the northern Rio Negro basin (∼ 1497 mm year−1) and the lowest values in the Solimões River basin (∼ 986 mm year−1). For the first time in a basin-scale study, using observational data, we show that factors limiting ET vary across climatic gradients in the Amazon, confirming local-scale eddy covariance studies. Both annual mean and seasonality in ET are driven by a combination of energy and water availability, as neither rainfall nor radiation alone could explain patterns in ET. In southern basins, despite seasonal rainfall deficits, deep root water uptake allows increasing rates of ET during the dry season, when radiation is usually higher than in the wet season. We demonstrate contrasting ET seasonality with satellite greenness across Amazon forests, with strong asynchronous relationships in ever-wet watersheds, and positive correlations observed in seasonally dry watersheds. Finally, we compared our results with estimates obtained by two ET models, and we conclude that neither of the two tested models could provide a consistent representation of ET seasonal patterns across the Amazon.


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