scholarly journals Carbon inputs from riparian vegetation limit oxidation of physically-bound organic carbon via biochemical and thermodynamic processes

2017 ◽  
Author(s):  
Emily B. Graham ◽  
Malak Tfaily ◽  
Alex R. Crump ◽  
Amy E. Goldman ◽  
Lisa Bramer ◽  
...  
Keyword(s):  
High Resolution ◽  
Organic Carbon ◽  
Land Cover ◽  
Metabolic Pathways ◽  
Riparian Vegetation ◽  
Columbia River ◽  
Water Soluble ◽  
Future Climate ◽  
River Corridor ◽  
Thermodynamic Processes

In light of increasing terrestrial carbon (C) transport across aquatic boundaries, the mechanisms governing organic carbon (OC) oxidation along terrestrial-aquatic interfaces are crucial to future climate predictions. Here, we investigate the biochemistry, metabolic pathways, and thermodynamics corresponding to OC oxidation in the Columbia River corridor using ultra-high resolution C characterization. We leverage natural vegetative differences to encompass variation in terrestrial C inputs. Our results suggest that decreases in terrestrial C deposition associated with diminished riparian vegetation induce oxidation of physically-bound OC. We also find that contrasting metabolic pathways oxidize OC in the presence and absence of vegetation and -- in direct conflict with the priming concept -- that inputs of water-soluble and thermodynamically favorable terrestrial OC protects bound-OC from oxidation. In both environments, the most thermodynamically favorable compounds appear to be preferentially oxidized regardless of which OC pool microbiomes metabolize. In turn, we suggest that the extent of riparian vegetation causes sediment microbiomes to locally adapt to oxidize a particular pool of OC, but that common thermodynamic principles govern the oxidation of each pool (i.e., water-soluble or physically-bound). Finally, we propose a mechanistic conceptualization of OC oxidation along terrestrial-aquatic interfaces that can be used to model heterogeneous patterns of OC loss under changing land cover distributions.

scholarly journals Molecular Composition and Photochemical Evolution of Water Soluble Organic Carbon (WSOC) Extracted from Field Biomass Burning Aerosols using High Resolution Mass Spectrometry

2019 ◽  
Author(s):  
Jing Cai ◽  
Xiangying Zeng ◽  
Guorui Zhi ◽  
Sasho Gligorovski ◽  
Guoying Sheng ◽  
...  
Keyword(s):  
Mass Spectrometry ◽  
High Resolution ◽  
Organic Carbon ◽  
Biomass Burning ◽  
High Resolution Mass Spectrometry ◽  
Water Soluble ◽  
Oxygenated Compounds ◽  
Water Soluble Organic Carbon ◽  
Soluble Organic Carbon ◽  
Resolution Mass

Abstract. Photochemistry plays an important role in the evolution of atmospheric water soluble organic carbon (WSOC), which dissolves into clouds, fogs and aerosol liquid water. In this study, we examined the molecular composition and evolution of a WSOC mixture extracted from fresh biomass burning aerosols upon photolysis, using direct infusion electrospray ionization high-resolution mass spectrometry (ESI-HRMS) and liquid chromatography coupled with mass spectrometry (LC/ESI-HRMS). For comparison, two typical phenolic compounds (i.e., phenol and guaiacol) emitted from lignin pyrolysis in combination with hydrogen peroxide (H2O2) as a typical OH radical precursor, were exposed to simulated sunlight irradiation. The photochemistry of both, the phenols (photo-oxidation) and WSOC mixture (direct photolysis) can produce a series of highly oxygenated compounds which in turn increases the degree of oxidation of organic composition and acidity of the bulk solution. In particular, the LC/ESI-HRMS technique revealed significant photochemical evolution on the WSOC composition, e.g., the photodegradation of low oxygenated species and the formation of highly oxygenated products. We also tentatively compared the mass spectra of photolytic time-profile extract with each other for a more comprehensive description of the photolytic evolution. The calculated average oxygen-to-carbon (O / C) ratios of oxygenated compounds in bulk extract increases from 0.38 ± 0.02 to 0.44 ± 0.02 (mean±standard deviation) while the intensity (S / N)-weighted average O / C (O / Cw) increases from 0.45 ± 0.03 to 0.53 ± 0.06 as the time of irradiation extends from 0 to 12 h. These findings indicate that the water soluble organic fraction of fresh combustion-derived aerosols have the potential to form more oxidized organic matter, accounting for the highly oxygenated nature of atmospheric organic aerosols.

scholarly journals High-resolution digital mapping of soil organic carbon in permafrost terrain using machine learning: a case study in a sub-Arctic peatland environment

2018 ◽  
Vol 15 (6) ◽  
pp. 1663-1682 ◽  
Author(s):  
Matthias B. Siewert
Keyword(s):  
Machine Learning ◽  
High Resolution ◽  
Random Forest ◽  
Organic Carbon ◽  
Soil Organic Carbon ◽  
Land Cover ◽  
Support Vector ◽  
Small Scale ◽  
Permafrost Degradation ◽  
Discontinuous Permafrost

Abstract. Soil organic carbon (SOC) stored in northern peatlands and permafrost-affected soils are key components in the global carbon cycle. This article quantifies SOC stocks in a sub-Arctic mountainous peatland environment in the discontinuous permafrost zone in Abisko, northern Sweden. Four machine-learning techniques are evaluated for SOC quantification: multiple linear regression, artificial neural networks, support vector machine and random forest. The random forest model performed best and was used to predict SOC for several depth increments at a spatial resolution of 1 m (1×1 m). A high-resolution (1 m) land cover classification generated for this study is the most relevant predictive variable. The landscape mean SOC storage (0–150 cm) is estimated to be 8.3 ± 8.0 kg C m−2 and the SOC stored in the top meter (0–100 cm) to be 7.7 ± 6.2 kg C m−2. The predictive modeling highlights the relative importance of wetland areas and in particular peat plateaus for the landscape's SOC storage. The total SOC was also predicted at reduced spatial resolutions of 2, 10, 30, 100, 250 and 1000 m and shows a significant drop in land cover class detail and a tendency to underestimate the SOC at resolutions  >  30 m. This is associated with the occurrence of many small-scale wetlands forming local hot-spots of SOC storage that are omitted at coarse resolutions. Sharp transitions in SOC storage associated with land cover and permafrost distribution are the most challenging methodological aspect. However, in this study, at local, regional and circum-Arctic scales, the main factor limiting robust SOC mapping efforts is the scarcity of soil pedon data from across the entire environmental space. For the Abisko region, past SOC and permafrost dynamics indicate that most of the SOC is barely 2000 years old and very dynamic. Future research needs to investigate the geomorphic response of permafrost degradation and the fate of SOC across all landscape compartments in post-permafrost landscapes.

scholarly journals Carbon Inputs From Riparian Vegetation Limit Oxidation of Physically Bound Organic Carbon Via Biochemical and Thermodynamic Processes

2017 ◽  
Vol 122 (12) ◽  
pp. 3188-3205 ◽  
Author(s):  
Emily B. Graham ◽  
Malak M. Tfaily ◽  
Alex R. Crump ◽  
Amy E. Goldman ◽  
Lisa M. Bramer ◽  
...  
Keyword(s):  
Organic Carbon ◽  
Riparian Vegetation ◽  
Thermodynamic Processes

scholarly journals High-resolution digital mapping of soil organic carbon in permafrost terrain using machine-learning: A case study in a sub-Arctic peatland environment

2017 ◽  
Author(s):  
Matthias B. Siewert
Keyword(s):  
Machine Learning ◽  
High Resolution ◽  
Random Forest ◽  
Organic Carbon ◽  
Soil Organic Carbon ◽  
Land Cover ◽  
Support Vector ◽  
Small Scale ◽  
Permafrost Degradation ◽  
Discontinuous Permafrost

Abstract. Soil organic carbon (SOC) stored in northern peatlands and permafrost affected soils are key components in the global carbon cycle. I quantify SOC stocks in a sub-arctic mountainous peatland environment in the discontinuous permafrost zone in Abisko, northern Sweden. Four machine-learning techniques are evaluated: multiple linear regression, artificial neural networks, support vector machine and random forest. The random forest approach performed best and was used to predict SOC for several depth increments at a spatial resolution of 2 ×2 m. A high-resolution (1 × 1 m) land cover classification generated for this study is the most relevant predictive variable. The landscape mean SOC storage (0–150 cm) is estimated to 7.9 ± 8.0 kg C m−2 and the SOC stored in the top meter (0–100 cm) to 7.0 ± 6.3 kg C m−2. The predictive modeling highlights the relative importance of wetland areas and in particular peat plateaus for the landscape SOC storage. A surprising large number of small scale wetland areas are mapped forming very local hot-spots of SOC storage. The results show that robust SOC predictions are possible with the available methods and very high-resolution remote sensing data. Strong environmental gradients associated with land cover and permafrost distribution are the most challenging methodological aspect. However, in this study, at local, regional and circum-Arctic scale the main factor limiting robust, high-resolution SOC mapping efforts is the scarcity of soil pedon data from across the entire environmental space. For the Absiko region, past SOC and permafrost dynamics indicate that most of the SOC is barely 2000 years old and very dynamic in wetland areas with permafrost related landforms. Future research needs to investigate the geomorphic response of permafrost degradation and the fate of SOC across all landscape compartments in post-permafrost landscapes.

Exploring the 4D scales of vegetation-morphological interactions along a river corridor using repeat UAV Laser Scanning (ULS), multispectral imagery, and a functional traits framework.

2021 ◽  
Author(s):  
Chris Tomsett ◽  
Julian Leyland
Keyword(s):  
High Resolution ◽  
Functional Traits ◽  
Riparian Vegetation ◽  
Laser Scanning ◽  
Temporal Dynamics ◽  
Spatial Scales ◽  
Morphological Data ◽  
Multispectral Imagery ◽  
Vegetation Diversity ◽  
River Corridor

<p>Interactions between riparian vegetation and river morphology are complex as they are often co-dependent, highly dynamic, and vary across both space and time. Vegetation diversity can be partially attributed to factors such as flood regimes and morphology, whilst simultaneously influencing the flow of water and sediment, ultimately impacting morphology and floodplain connectivity. As such, the importance of vegetation within the river corridor is well recognised and has been the subject of a considerable volume of research. However, within ecogeomorphology, most studies to date have been scale invariant, focusing either on characterisation of fine scale hydraulic roughness (e.g. using Terrestrial Laser Scanning; TLS) or on >reach scale patterns of riparian vegetation (using airborne or satellite imagery). Similarly, less attention has been paid to the temporal dynamics of vegetation beyond some appreciation of seasonality in controlling flow dynamics. This leaves a number of unresolved questions relating to the nested spatial and temporal (i.e. 4-dimensional; 4D) interactions of riparian vegetation and river flow.</p><p>In this study we seek to establish the temporal and spatial scales of riparian vegetation interaction within a river corridor using a traits based framework. Traits based research characterises plants with similar functional traits into guilds (groups) as opposed to by species or types, and as such provides a more useful basis to group vegetation according to the potential geomorphic impact that they exhibit. Traits based research for ecogeomorphic processes is relatively new in fluvial geomorphology, but has shown promise in its applicability, albeit existing applications are yet to investigate the temporal changes in vegetation. The need for extensive ground survey currently limits the application of traits based methods at reach scale and greater, highlighting the requirement for an approach that is able to classify a range of vegetation sizes and types into appropriate guilds.</p><p>Using a novel ULS and multispectral imaging systems, we have collected repeat high resolution (~1000 points per m<sup>3</sup>) surveys over a 1 km reach of the River Teme, UK, which has a wide variety of seasonally dynamic riparian vegetation. For each survey we use the point cloud data and multispectral imagery to classify vegetation into guilds. We use these in conjunction with the morphological data from the survey to create spatially varying surfaces of ecogeomorphic interactions, allowing us to establish links between guild coverage and morphological evolution across the reach throughout the year. The results show that vegetation-morphological co-evolution exists across scales and that high resolution survey methods are highly beneficial for resolving such interactions. The methods are designed to be transferable to other eco-geomorphic domains in any morpho-climatic regions, highlighting the flexibility and potential of a high resolution 4D traits based approach.</p>

scholarly journals Molecular composition and photochemical evolution of water-soluble organic carbon (WSOC) extracted from field biomass burning aerosols using high-resolution mass spectrometry

2020 ◽  
Vol 20 (10) ◽  
pp. 6115-6128
Author(s):  
Jing Cai ◽  
Xiangying Zeng ◽  
Guorui Zhi ◽  
Sasho Gligorovski ◽  
Guoying Sheng ◽  
...  
Keyword(s):  
Mass Spectrometry ◽  
High Resolution ◽  
Organic Carbon ◽  
Biomass Burning ◽  
High Resolution Mass Spectrometry ◽  
Water Soluble ◽  
Oxygenated Compounds ◽  
Water Soluble Organic Carbon ◽  
Soluble Organic Carbon ◽  
Resolution Mass

Abstract. Photochemistry plays an important role in the evolution of atmospheric water-soluble organic carbon (WSOC), which dissolves into clouds, fogs, and aerosol liquid water. In this study, we tentatively examined the molecular composition and evolution of a WSOC mixture extracted from field-collected wheat straw burning aerosol (WSBA) samples upon photolysis, using direct infusion electrospray ionisation (ESI) coupled to high-resolution mass spectrometry (HRMS) and liquid chromatography (LC) coupled with HRMS. For comparison, two typical phenolic compounds (i.e. phenol and guaiacol) emitted from lignin pyrolysis in combination with hydrogen peroxide (H2O2) as a typical OH radical precursor were simultaneously exposed to simulated sunlight irradiation. Their photochemical products such as phenolic dimers (e.g. m∕z 185.0608 for phenol dimer and m∕z 245.0823 for guaiacol dimer) or their isomers, were also observed in field-collected WSBA samples, suggesting that the aqueous-phase reactions might contribute to the formation of emitted biomass burning aerosols. The aqueous photochemistry of both the phenols (photooxidation) and WSBA extracts (direct photolysis) could produce a series of highly oxygenated compounds, which in turn increases the oxidation degree of organic composition and acidity of the bulk solution. In particular, the LC/ESI-HRMS technique revealed significant photochemical evolution of the WSOC composition in WSBA samples, e.g. the photodegradation of low oxygenated species and the formation of highly oxygenated products. We also tentatively compared the mass spectra of photolytic time-profile WSBA extracts with each other for a more comprehensive description of the photolytic evolution. The calculated average oxygen-to-carbon ratio (O∕C) of oxygenated compounds in bulk extract increases from 0.38±0.02 to 0.44±0.02 (mean ± standard deviation), while the intensity (S∕N)-weighted average O∕C (O∕Cw) increases from 0.45±0.03 to 0.53±0.06 as the time of irradiation extends from 0 to 12 h. These findings indicate that the water-soluble organic fraction of combustion-derived aerosols has the potential to form more oxidised organic matter, contributing to the highly oxygenated nature of atmospheric organic aerosols.

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