Carbon Dynamics Research Articles

Earthworms in an enhanced weathering mesocosm experiment: Effects on soil carbon sequestration, base cation exchange and soil CO2 efflux

Despite its attractiveness for long-term carbon dioxide removal (CDR), quantifying weathering and CDR rates for enhanced weathering is a significant challenge. Moreover, the role of soil organisms, such as earthworms, in enhancing silicate weathering (both physically and chemically) has been suggested, but there is limited quantitative data on how biota, especially earthworms, contribute to inorganic carbon sequestration. To address these gaps, we conducted a mesocosm experiment with earthworms and basalt.Results indicate increases in clay and cation exchange, causing a weathering rate of over 10−12 mol total alkalinity m2 s−1, in range with other basalt experiments. Basalt amendment increased dissolved inorganic carbon export by only 4 g CO2 m−2. During the 4.5-month experiment, we observed neither a change in organic nor in inorganic carbon content.In soils without earthworms, basalt amendment reduced soil CO₂ efflux by approximately 0.2 kg CO₂ m2, suggesting considerable CDR. This decrease was about two times larger than calculated inorganic CDR equivalents, suggesting changes in soil organic matter dynamics.Interestingly, earthworms reversed the basalt-induced reduction in soil CO₂ efflux. This reversal was partly due to reduced export of dissolved inorganic carbon but mainly driven by increased organic matter decomposition. Our study highlights the importance of including organic carbon dynamics when evaluating the CDR potential of enhanced weathering.

MODELLING THE IMPACT OF SOIL AND METEOROLOGICAL PA-RAMETERS ON CARBON DYNAMICS IN WETLAND ECOSYSTEMS

Wetlands are characterised by distinct hydrological regimes and have significant importance in the global carbon cycle, having the potential to reduce carbon emissions through long-term carbon storage in the soil. In this study, carbon dynamics were simulated using a process-based model DeNitrification-DeComposition (DNDC), for two locations along Dâmbovița River case study area. These scenarios took into consideration the interconnection of soil parameters, hydrology, meteorological conditions and vegetation type. The findings showed that soil CO2 emissions are positively and strongly correlated with air temperature and soil moisture, with changes in the water content of the soil regime having the greatest impact on CO2 fluxes. Also, the model simulations have been validated by statistical analysis of uncertainties with the values of CO2 fluxes measured in situ using the dynamic closed chamber method. By comparing DNDC outputs with field measurements, the performance of the model was evaluated in different environmental conditions and the results were consistent, which increased confidence in its application for assessing wetland ecosystems. These results contribute to a more comprehensive understanding of the carbon cycle in wetlands and an improved estimation of the effects of climate change on the dynamics of carbon in these ecosystems.

Impact of climatic seasons on the dynamics of carbon, nitrogen and mercury in soils of Brazilian biomes affected by gold mining

Land use change, especially mining activities, contributes to anthropic CO2 emissions, leading to decreased carbon (C) storage and loss of biodiversity. Artisanal gold mining associated with the use of mercury (Hg) for amalgamation may change soil organic matter (SOM) contents, and the release of Hg into the environment generates serious environmental problems. Changes in soil biogeochemistry due to C loss and seasonal climate fluctuations affect Hg dynamics and can either increase or decrease its availability. Therefore, our objective was to evaluate the impact of mining on SOM and Hg geochemistry in four Brazilian biomes. We evaluated the dynamics of C and Hg in the dry and rainy seasons of mining and pasture areas by combining spectroscopic, thermogravimetric, and chemical extraction. The critical role of SOM in Hg retention and the influence of climatic seasons on C and nitrogen (N) stocks were highlighted, along with the availability of Hg in solution. Key findings indicated a 50 % reduction in soil C stocks in mined areas, exacerbated during dry seasons, which also saw up to a 70 % increase in bioavailable Hg. SOM played a critical role in Hg retention, with Hg availability closely linked to soil C stability. These results highlight the environmental degradation linked to mining and suggest strategies to mitigate these impacts by increasing SOM and immobilizing Hg. Amalgamation of gold directly into ore, as in the Amazon, has generated great soil Hg stocks, while Hg availability appeared to be governed by soil C stability. This information can serve as a basis for choosing strategies to mitigate environmental degradation caused by changes in land use in mining activities to promote increase in SOM and to immobilize Hg contents.

Assessing the of carbon and nitrogen storage potential in Khaya spp. stands in Southeastern Brazil

The objective of this study was to assess the dynamics of carbon and nitrogen in soil, forest floor, and aboveground biomass in 9.5 years-old planted stands of three Khaya spp. (K. grandifoliola, K. ivorensis, and K. senegalensis). The study was conducted at the Reserva Natural Vale (RNV), Brazil. The stands were planted at 5 × 5 m spacing, distributed over rectangular plots of 1250 m2. Soil bulk density at the evaluated depths, as well nitrogen contents, were similar among the species. However, K. ivorensis exhibited higher carbon concentration in the soil. In general, there were no differences in carbon and nitrogen content in soil between the three species; however, the values obtained are comparable to those of the reference area–Native Forest. The carbon stocks in the aboveground biomass for K. grandifoliola, K. ivorensis, and K. senegalensis averaged 37.97, 33.66 and 33.86 Mg ha−1, respectively (p ≤ 0.05). These values collectively represent about 28% of the total carbon stocks across the observed compartments. Notably, the nitrogen content within the aboveground biomass did not differ among these species. Therefore, African mahogany possesses a robust potential to store both carbon and nitrogen.

Greater variation of soil organic carbon in limestone- than shale-based soil along soil depth in a subtropical coniferous forest within a karst faulted basin of China

Lithology strongly influences soil microbial traits and edaphic factors and in turn soil organic carbon (SOC) dynamics. However, the effect of lithology on microbial traits, edaphic factors and resulting SOC physical fractions variation along soil depth remains inadequately understood in karst faulted basin of China. This understanding is critical for improving SOC stability. By separating SOC into labile particulate organic carbon (POC) and stable mineral-associated organic carbon (MAOC) over karst limestone and non-karst shale soil in a subtropical coniferous forest, we aimed to assess potential regulatory mechanisms underlying lithology-associated SOC stability variations across soil depth by integrating soil nutrients, mineralogical characteristics, and microbial traits. We found that SOC and its fractions were higher in limestone than in shale soil, which implying vegetation restoration effects on SOC and its fractions partly depending on lithology. Additionally, we found that the effects of soil depth on SOC and its fractions were greater in limestone soils than shale soils, and the ratios of MAOC to SOC (MAOC:SOC) and MAOC to POC (MAOC:POC) show a opposite trend in response to soil depth between two the lithologies. Variation partitioning and random forest analyses revealed that among multiple factors, the variation of SOC stability assessed via MAOC:SOC was mainly explained by microbial traits than soil nutrients and mineral properties. Contrast to soil depth, structural equation modeling analyses showed that lithology was the primary factor controlling the SOC stability when microbial traits, soil nutrients and mineralogical characteristics were controlled as conditional variables. Overall, these results highlight the crucial role of lithology in regulating the SOC stability along soil depth, which improve our understanding and management of soil carbon (C) pool in karst faulted basin of southwest China.

Large variations of dissolved carbon occurred in small ponds within an agricultural watershed

Dissolved organic carbon (DOC) and dissolved inorganic carbon (DIC) significantly affect the aquatic carbon budget and ecosystem functions. Small ponds are abundant globally and widely distributed especially in agricultural watersheds, however, the variability of DOC and DIC, along with their driving factors, remains poorly understood, which likely hampers the understanding of carbon cycle of inland waters. The presented study was designed to fill the knowledge gap based on a detailed year-long field investigation via examining DOC and DIC concentrations across ponds with differing functionalities (e.g. sewage ponds, irrigation ponds, and natural ponds) of a typical agricultural watershed in eastern China. Our results found a pronounced impact of human activities on pond DOC and DIC, with higher DOC occurring in sewage ponds (10.84 ± 2.83 mg L−1) and irrigation ponds (9.09 ± 2.57 mg L−1) and peak DIC in irrigation ponds (20.36 ± 2.49 mg L−1) compared to that at natural ponds (DOC: 7.54 ± 2.55 mg L−1; DIC: 11.16 ± 3.85 mg L−1) with less human activity. The positive correlations between DOC/DIC and key environmental variables (e.g. nutrients and chlorophyll-a) further demonstrated that human activity can either directly increase the carbon concentrations via pollutant discharge, or indirectly increase DOC concentration via stimulating primary production. Meanwhile, field measurements found precipitation and temperature play roles in determining the carbon variability. Specifically, precipitation increased the DOC of these ponds via enhancing land-based carbon inputs, and decrease the DIC of irrigation ponds via diluting. Temperature can influence the carbon dynamics through increasing primary productivity and metabolism. Our study underscores the roles of human and natural influences in determining the large variations of DOC and DIC in small ponds, which should be considered to better understand the carbon dynamic variability of human-impacted small aquatic systems.

Variation patterns in foliar δ13C and δ15N among plant life types along an altitudinal gradient on the Tibetan Plateau

Understanding how foliar δ13C and δ15N vary with the environment is crucial for elucidating the carbon and nitrogen cycle dynamics within ecosystems. Yet, there is limited knowledge about these variations among different plant life types along altitudinal gradients, particularly in subtropical forest ecosystems found in the southeastern Tibetan Plateau. Therefore, we collected leaves from 67 species, including 20 trees, 24 shrubs, and 23 herbs along an altitudinal gradient of 834 m to 3105 m in the subtropical forest of Medog, and investigated their patterns of variation along the altitudinal gradient. Our findings revealed a positive relationship between foliar δ13C and altitude, as well as a negative relationship between foliar δ13C and soil temperature. There was no significant correlation between foliar δ15N and altitude, but a hump-shaped relationship was observed between foliar δ15N and soil moisture. Among the different plant functional groups, the δ13C of shrubs is more sensitive and representative of environmental changes. In addition, we discovered no difference in the δ13C (δ15N) values of leaves among trees, shrubs, and herbs in this study. Still, there were significant differences when compared to the δ13C (δ15N) values of leaves in other typical climatic zones, indicating that climatic zones influenced the δ13C and δ15N values of leaves more than plant functional groups. In conclusion, our results provide new insights into the climatic drivers of the changes in δ13C and δ15N of the different plant life types along the altitudinal gradient in the southeastern Tibetan Plateau.

Temporal and spatial dynamics of carbon and water use efficiency on the Qinghai-Tibet plateau and their ecosystem responses

Research on the carbon and water use efficiency (CUE, WUE) in the Qinghai-Tibet Plateau (QTP) holds significant importance due to its implications in understanding and addressing global environmental challenges, particularly climate change. This study comprehensively explored the spatiotemporal distribution patterns and trends of WUE and CUE on the plateau from 2001 to 2018 using linear regression analysis and geostatistical methods. The results revealed a gradual decrease in WUE from southeast to northwest, showing a non-linear variation trend during the study period. CUE exhibited relatively minor spatial variations but demonstrated a significant decrease trend in the eastern regions. The results from the Random Forest algorithm and path analysis indicated that ecosystem respiration (Re) was the predominant controlling factor for WUE and CUE in the cold alpine (PA) region. In the temperate, warm temperate (Te&WT) region, temperature emerged as the primary determinant for WUE, while Leaf Area Index (LAI) served as the absolute dominant factor for CUE. Additionally, LAI also played a crucial role in determining WUE and CUE in the tropical and subtropical (Tr&S) region. Partial correlation analysis highlighted the heterogeneity in the responses of WUE and CUE to environmental changes across different regional climates and vegetation types. The findings emphasized the significant impact of biological factors on terrestrial carbon and water cycling processes (WUE and CUE) within the context of global climate change. Furthermore, the study identified a potential linkage between WUE and CUE, with their relationship to vegetation dynamics showing significant variations across various ecosystems. WUE and CUE showed a positive correlation in the western regions, particularly in high-altitude areas, while a negative correlation was observed in eastern regions with high SOC. In the Te&WT and the Tr&S region, the increase of NDVI (Normalized difference vegetation index) suppressed the rise of both WUE and CUE, establishing a negative correlation between them. Conversely, in the PA region, a significant positive correlation trend between WUE and CUE was observed, indicating a positive response to the decrease in NDVI. These findings are of significant importance for advancing the understanding of and effectively addressing climate change, maintaining ecosystem stability, and promoting sustainable socio-economic development.

Seasonal dynamics of carbon, nitrogen, and phosphorus stoichiometric traits in an extensive green roof in Nanjing, China

Green roofs (GRs) are vital for shaping the material cycles of urban ecosystems as a form of distributed green infrastructure. However, current studies have predominantly focused on the material exchange between GRs and the urban environment, neglecting the internal distribution and equilibrium of constituent elements. By monitoring carbon (C), nitrogen (N), and phosphorus (P) in Sedum lineare Thunb and four substrates throughout the seasons, this study analyzes the ecological stoichiometric characteristics of an extensive GR in Nanjing, China. Intra-annual ratios of C:N (46.02, 13.38, 15.40), C:P (252.41, 57.85, 47.22), and N:P (5.75, 4.23, 3.84) were identified in the plant, substrate, and substrate microbial biomass, respectively. The intra-annual ratios of plant to substrate C, N, and P were roughly 9:1, 7:3, and 6:4, respectively. The use of different substrates resulted in significant variations in plant C, N, and P levels and their quantitative ratios, leading to distribution differences of these elements. Furthermore, substrate C, N, and P levels exhibit a generalized threshold effect on microbial biomass and plant C, N, and P concentrations. Notably, the substrate demonstrates an organic C sink potential of 7.11 g/kg/season, surpassing that of plants in unit mass. These findings contribute to understanding the distribution and dynamics of C, N, and P elements within extensive GRs.

Examining the Ecosystem-Scale GHG Exchange Following the Acrotelm Harvesting Method (ACM) in Eastern Quebec

Traditional horticultural peat production involves the removal of vegetation and drainage of peatlands, resulting in significant ecological disturbances and greenhouse gas (GHG) emissions. The Acrotelm Harvesting Method (ACM) was developed as a more sustainable alternative, designed to reduce these impacts by allowing peat extraction without large-scale ecosystem alterations. However, the ACM still necessitates the passage of machinery over the peat, potentially disturbing surface vegetation and altering the carbon dynamics. My project, based at a field site near Baie-Comeau, QC, represents the first comprehensive assessment of the ACM’s impact on net ecosystem exchanges of main GHGs. I focused on evaluating the ecosystem-scale effects by analyzing data collected from paired eddy covariance towers installed at both the control (unharvested) and harvested sites. These towers provide temporally continuous, spatially integrated flux measurements. Preliminary findings indicate that the site subjected to ACM exhibits altered surface topography, leading to overall wetter conditions, compaction of hummocks, and vegetation damage. These changes have resulted in reduced carbon dioxide uptake and increased methane emissions at the harvested site. Through the analysis and interpretation of this data, my research contributes to a better understanding of the ACM’s environmental impact and its potential as a sustainable peatland management strategy. This research was conducted under the supervision of Dr. Ian Strachan in the Atmospheric Environmental Research (AER) lab.

Extreme precipitation reduces the recent photosynthetic carbon isotope signal detected in ecosystem respiration in an old-growth temperate forest.

The successful utilization of stable carbon isotope approaches in investigating forest carbon dynamics has relied on the assumption that the carbon isotope compositions (δ13C) therein have detectable temporal variations. However, interpreting the δ13C signal transfer can be challenging, given the complexities involved in disentangling the effect of a single environmental factor, the isotopic dilution effect from background CO2 and the lack of high-resolution δ13C measurements. In this study, we conducted continuous in situ monitoring of atmospheric CO2 (δ13Ca) across a canopy profile in an old-growth temperate forest in northeast China during the normal year 2020 and the wet year 2021. Both years exhibited similar temperature conditions in terms of both seasonal variations and annual averages. We tracked the natural carbon isotope composition from δ13Ca to photosynthate (δ13Cp) and to ecosystem respiration (δ13CReco). We observed significant differences in δ13Ca between the two years. Contrary to in 2020, in 2021 there was a δ13Ca valley in the middle of the growing season, attributed to surges in soil CO2 efflux induced by precipitation, while in 2020 values peaked during that period. Despite substantial and similar seasonal variations in canopy photosynthetic discrimination (Δ13Ccanopy) in the two years, the variability of δ13Cp in 2021 was significantly lower than in 2020, due to corresponding differences in δ13Ca. Furthermore, unlike in 2020, we found almost no changes in δ13CReco in 2021, which we ascribed to the imprint of the δ13Cp signal on above-ground respiration and, more importantly, to the contribution of stable δ13C signals from soil heterotrophic respired CO2. Our findings suggest that extreme precipitation can impede the detectability of recent photosynthetic δ13C signals in ecosystem respiration in forests, thus complicating the interpretation of above- and below-ground carbon linkage using δ13CReco. This study provides new insights for unravelling precipitation-related variations in forest carbon dynamics using stable isotope techniques.

Impact of Land Use and Land Cover (LULC) Changes on Carbon Stocks and Economic Implications in Calabria Using Google Earth Engine (GEE).

Terrestrial ecosystems play a crucial role in global carbon cycling by sequestering carbon from the atmosphere and storing it primarily in living biomass and soil. Monitoring terrestrial carbon stocks is essential for understanding the impacts of changes in land use on carbon sequestration. This study investigates the potential of remote sensing techniques and the Google Earth Engine to map and monitor changes in the forests of Calabria (Italy) over the past two decades. Using satellite-sourced Corine land cover datasets and the InVEST model, changes in Land Use Land Cover (LULC), and carbon concentrations are analyzed, providing insights into the carbon dynamics of the region. Furthermore, cellular automata and Markov chain techniques are used to simulate the future spatial and temporal dynamics of LULC. The results reveal notable fluctuations in LULC; specifically, settlement and bare land have expanded at the expense of forested and grassland areas. These land use and land cover changes significantly declined the overall carbon stocks in Calabria between 2000 and 2024, resulting in notable economic impacts. The region experienced periods of both decline and growth in carbon concentration, with overall losses resulting in economic impacts up to EUR 357.57 million and carbon losses equivalent to 6,558,069.68 Mg of CO 2 emissions during periods of decline. Conversely, during periods of carbon gain, the economic benefit reached EUR 41.26 million, with sequestered carbon equivalent to 756,919.47 Mg of CO 2 emissions. This research aims to highlight the critical role of satellite data in enhancing our understanding and development of comprehensive strategies for managing carbon stocks in terrestrial ecosystems.

Potential for nutrients reuse, carbon sequestration, and CO2 emissions reduction in the practice of domestic and industrial wastewater recycling into agricultural soils: A review

This review assesses the feasibility of reusing treated wastewater for irrigation in agricultural soils as a strategy for nutrients recycling and mitigation of CO2 emissions. Through a literature review, it was examined wastewater sources enriched with carbon and nutrients, including municipal wastewater and associated sludge, vinasse, swine wastewater, as well as wastewater from the food industry and paper and pulp production. The review also explores the dynamics of organic matter within the soil, discussing the aspects related to its potential conversion to CO2 or long-term storage. It was found that industrial wastewaters, owing to their higher organic matter and recalcitrance, exhibit greater potential for carbon storage. However, the presence of pollutants in wastewater necessitates careful consideration, particularly concerning their impact on soil quality. Toxic metals, microplastics, and organic compounds emerged as significant contaminants that could accumulate in the soil, posing risks to ecosystem health. To mitigate the environmental impacts, it was evaluated various wastewater treatment technologies and their associated carbon emissions. While advanced treatments may effectively reduce the contaminant load and mitigate soil impacts, their adoption is often associated with an increase in CO2 emissions. Membrane bioreactors, microfiltration, ultrafiltration, and up-flow anaerobic sludge blanket reactors were identified as promising technologies with lower carbon footprints. Looking ahead, future research should aim to enhance the understanding of carbon dynamics in soil and validate the environmental impacts of treated wastewater disposal. Despite remaining uncertainties, the literature indicates a positive outlook for wastewater recycling in soil, offering a viable strategy for carbon storage and mitigation of greenhouse gas emissions.

Progressing beyond colonization strategies to understand arbuscular mycorrhizal fungal life history.

Knowledge of differential life-history strategies in arbuscular mycorrhizal (AM) fungi is relevant for understanding the ecology of this group and its potential role in sustainable agriculture and carbon sequestration. At present, AM fungal life-history theories often focus on differential investment into intra- vs extraradical structures among AM fungal taxa, and its implications for plant benefits. With this Viewpoint we aim to expand these theories by integrating a mycocentric economics- and resource-based life-history framework. As in plants, AM fungal carbon and nutrient demands are stoichiometrically coupled, though uptake of these elements is spatially decoupled. Consequently, investment in morphological structures for carbon vs nutrient uptake is not in competition. We argue that understanding the ecology and evolution of AM fungal life-history trade-offs requires increased focus on variation among structures foraging for the same element, that is within intra- or extraradical structures (in our view a 'horizontal' axis), not just between them ('vertical' axis). Here, we elaborate on this argument and propose a range of plausible life-history trade-offs that could lead to the evolution of strategies in AM fungi, providing testable hypotheses and creating opportunities to explain AM fungal co-existence, and the context-dependent effects of AM fungi on plant growth and soil carbon dynamics.

Decade-long effects of integrated farming systems on soil aggregation and carbon dynamics in sub-tropical Eastern Indo-Gangetic plains

Integrated farming system (IFS) aims to diversify the agricultural landscapes by incorporating different components to meet the multifarious needs of the burgeoning population. The present study was undertaken to understand the impact of different cropping systems on soil organic carbon (SOC) stock, aggregate distribution, and aggregate associated organic carbon (AAOC) in 2-IFS models of varying sizes (0.4 and 0.8 ha) established during 2008–2009. After 10 years of the study, the fodder system registered the greatest TOC and carbon stocks across IFS models, with surface soil (0–15 cm) accumulating 17 and 13% higher TOC and C stock, respectively, in 0.4 and 0.8 ha models. In 0–15 cm, macroaggregates (Ma) represented the highest proportion (75–76%) in both models. Among cropping systems, the fodder system recorded the highest large macroaggregates in both IFS models. Within 0–30 cm depth, small macroaggregates are mostly found in the perennial system (fodder, guava+turmeric, and lemon intercropping system), indicating the potential to improve the aggregate stability over the seasonal (shorter duration) system. In general, micro aggregate (Mi) fraction was pre-dominant in sub-surface soil (17.35%). The maximum AAOC was found in Ma compared to Mi fractions, with approximately 67 and 63% of total carbon associated with Ma in 0.4 and 0.8 ha IFS models, respectively. Interestingly, the 0.8 ha IFS model had higher TOC (~11%) and carbon stock (~12%) than the 0.4 ha model, but AAOC did not show a similar result, indicating the influence of cropping systems on AAOC. The study indicated that the fodder-based production system had better performance in terms of soil physical health and increased aggregate stability and content of soil carbon. This is indicative of the advantages of perennial-based systems over seasonal- or annual-based cropping systems for soil sustainability in Eastern Indo-Gangetic Plains.

Assessment of coral reef connectivity in improved organic carbon storage of seagrass ecosystems in Palk Bay, India

The increase in climate-related extreme events and ecosystem degradation demands consistent and sustainable climate mitigation efforts. Seagrass playing a key role in nature-based carbon sequestration mitigation strategy. Here, we investigated the role of coral reef connectivity in blue carbon dynamics with seagrass meadows with coral reef connectivity (SC areas) and without coral reef connectivity (SG areas) in Palk Bay, India. The high sediment organic carbon was recorded in SC areas (90.26 ± 25.68 Mg org.C/ha) and lower in SG areas (66.96 ± 12.6 Mg org.C/ha). The maximum above-ground biomass (AGB) was recorded in Syringodium isoetifolium (35.43 ± 8.50) in SC areas and the minimum in Halophila ovalis (7.59 ± 0.90) in SG areas, with a similar trend observed in below-ground biomass (BGB). Our findings highlight the importance of coral reefs in enhancing the blue carbon potential of seagrass ecosystems and underscore the need for integrated conservation and restoration strategies for coral reefs and seagrasses.

Influences of wildfire on the soil dissolved organic matter characteristics and its electron-donating capacity

Global increases in the intensity and frequency of wildfires are driving major changes in soil organic matter (SOM) characteristics, including soil dissolved organic matter (DOM). As the most crucial component of SOM, soil DOM plays a pivotal role in the carbon cycle and regulates the environmental fate of contaminants through its versatile reactivities, including electron-donating capacity (EDC). However, it is still being determined how wildfire influences key characteristics of soil DOM and subsequent effects on EDC in forest soils. Thus, we conducted our study to fill this gap with the forest soils of Jinyun Mountain Nature Reserve of China, which experienced an unprecedented wildfire event in 2022. The results from optical characterization, high-performance size-exclusion chromatography (HPSEC), and Fourier transform ion cyclotron resonance mass spectrometry (FT-ICR-MS) showed decreasing molecular weight but elevating nitrogen-containing molecular formulas of soil DOM in the burned soils. This could be attributed to the Maillard reaction and microbial re-colonies. Additionally, wildfires increased the condensed aromatics and lignin components in soil DOM. In the burned soils, we observed increasing EDC of soil DOM, which accounts for an increase in lignin-derived phenolic components. Overall, the findings of this study demonstrate that eco-disturbances, such as wildfires, induce alterations in the properties of DOM, leading to variations in its reactivity and potentially influencing the fate of environmental pollutants beyond carbon dynamics alone. Thus, incorporating the dynamic properties of soil DOM, particularly in the context of climate change, can enhance the assessment of risks associated with contaminants in soil and water, providing valuable insights.

Effect of Vegetation Restoration on Soil Iron‐Associated Carbon Dynamics: Insights From Different Soil Textures

AbstractSoil iron (Fe)‐associated carbon (C) (Fe‐OC) plays a vital role in the soil C cycle due to its high stability, but vegetation restoration might alter the composition and quantity of Fe‐OC by introducing a large amount of plant‐derived C and affecting soil properties. However, how vegetation restoration affects soil Fe‐OC remains unclear. Herein, plant and topsoil samples from grasslands, shrublands, and forestlands across three soil types (loam, loess, and sandy soil) since cropland conversions were collected to address this issue. The results showed soil Fe‐OC content decreased in loam soil but increased in loess and sandy soil following vegetation restoration. Additionally, the Fe‐OC accumulation efficiency induced by vegetation restoration increased with the coarser soil texture. Vegetation restoration promoted the accumulation of Fe‐OC by increasing soil microbial biomass C, dissolved organic C, aromatic‐C, and citric acid, but also disrupted the combination of Fe oxides and C by introducing oxalic acid, reducing Fe oxide content and iron trivalent (Fe(III)). There were two‐sided effects of vegetation restoration on Fe‐OC, but the overall effect depends on the soil types. Moreover, isotopic evidence indicated that microbial source C is the main source of Fe‐OC, but Fe oxides preferentially adsorbed dissolved organic matter (DOM) and root deposits from plants rather than microbial residues and metabolites following vegetation restoration. In addition, Fe oxides preferentially adsorbed aromatic‐C compared to other functional group components. These findings indicated that vegetation restoration in coarser‐texture soils, coupled with selecting species that increase soil microbial biomass, produce more root deposits, and enhance DOM, contribute to the accumulation of soil Fe‐OC.

Soil carbon dynamics in perennial biomass crops on marginally productive cropland in southern Canada

Predicting changes in soil organic carbon (SOC) in perennial biomass crops using process-based models provides a greater understanding of land management impacts on climate mitigation through long-term soil carbon sequestration. The objective of this study was to predict long-term SOC dynamics in different perennial biomass crops [miscanthus (Miscanthus giganteus L.), switchgrass (Panicum virgatum L.), willow (Salix miyabeana L.)] as compared to secondary regrowth vegetation (successional site) and a row crop system. The Century model accurately predicted SOC when simulated values were compared to measured field data. Average SOC stocks over the 162-year simulation period to 20 cm, were highest in miscanthus (8521 g C m−2), followed by the successional site (6877 g C m−2), switchgrass (6480 g C m−2), willow (5448 g C m−2) and lowest in the row crop system (3995 g C m−2). Higher SOC stocks in the miscanthus than the successional site indicates that, despite frequent biomass harvest, perennial biomass crops can accumulate higher carbon in soil than when a marginally productive cropland is left to undergo secondary regrowth. However, this depends on the crop species, since the miscanthus was the only biomass crop that reached pre-cultivation (1911) SOC stock of 8288 g C m−2. Moreover, the perennial biomass crops enhanced SOC in the slow fraction, whereas row crops depleted SOC in this fraction. This indicates the vital contribution of perennial biomass crops in long-term SOC sequestration and their role in climate change mitigation, especially when grown on marginally productive croplands.

Regional prediction of soil organic carbon dynamics for intensive farmland in the hot arid climate of India using the machine learning model

Regional prediction of soil organic carbon dynamics for intensive farmland in the hot arid climate of India using the machine learning model