Search Results (54)

Hybrid biological–inorganic (HBI) systems that integrate hydrogen-oxidizing bacteria (HOBs) with inorganic water-splitting catalysts have been developed as bioelectrochemical platforms for CO₂ conversion. This study used an HBI system to enrich HOBs under atmospheric air or a high CO₂ concentration. The HBI system operated with two different bioreactor configurations: a high-CO₂ condition, in which the bioreactor was sealed with an air-tight stopper and the headspace gas was replaced with CO₂ (100%), and an atmospheric air condition, in which the bioreactor was sealed with an air-permeable cap, gas exchange was allowed, and contamination was prevented. These bioreactors were inoculated with six rhizosphere soil samples, which were additionally enriched with a conventional gas-fermentation mixture. 16S rRNA gene amplicon sequencing revealed enrichment of the bacterial lineages mostly related to three main families under the high-CO₂ condition. On the contrary, the open-air system facilitated enrichment of aerobic HOBs, potentially occurring through the enrichment of more diverse bacterial lineages. The different enrichment conditions imposed distinct selective pressures on HOBs. The obtained results indicated that HBI systems provide an alternative enrichment platform for expanding the diversity of HOBs applicable to CO₂-based biomanufacturing. Full article

Under the “dual carbon” goals, Taiyuan, a prefecture-level administrative unit and energy-intensive region in Shanxi Province, China, has experienced changes in soil carbon storage and soil carbon flux under rapid urbanization and industrialization. To clarify the spatial patterns of soil carbon storage and flux, 26 field sampling sites, including 78 soil samples, were analyzed using laboratory measurements and an optimized tunable diode laser absorption spectroscopy–geographic information system (TDLAS–GIS) integrated monitoring approach. This study investigated the spatial patterns of soil carbon storage and flux and discussed their potentially associated factors, providing an exploratory workflow for regional carbon monitoring. The results showed clear spatial heterogeneity, with an average soil organic carbon (SOC) content of 10.86 g/kg. High-SOC areas were mainly located in the southern and southwestern plains, while lower SOC levels occurred in urban expansion zones and highly disturbed surfaces. The western mountainous areas were important ecological barriers but were not the highest measured SOC zones. At the site level, arable land and forestland showed higher mean SOC values than grassland, with average SOC contents of 12.47, 12.07, and 8.27 g/kg, respectively, although these land-use-related differences were not statistically significant. Soil carbon flux was relatively higher in some mountainous regions and industrial–ecological transition areas but lower in several urban expansion areas. The results suggest that urbanization and industrial activity may be associated with changes in SOC and soil-atmosphere CO₂ exchange. This study describes the spatial variation characteristics of soil carbon storage and flux, establishes a reproducible TDLAS–GIS workflow for regional carbon monitoring, and provides exploratory support for ecological sustainability, sustainable land management, and the “dual carbon” strategy in northern resource-based cities. Full article

Sequestration of atmospheric CO₂ in the Yatir Mediterranean semi-arid Aleppo Pine Forest (Pinus halepensis) close to the border of the semi-arid timberline was characterized and quantified under field conditions. Measurements of organic and inorganic CO₂ sequestration with gas exchange, stock counting approach, and remote sensing were made in both rainfed control (~12% average annual Soil Moisture) and long-term experiment of irrigation (~10 years with ~24% annual average SM) plots, providing the opportunity to separate the effects of atmospheric water demand from soil water stress on the atmospheric CO₂ sequestration responses. Measurements yield an organic carbon sequestration (OCS) rate of ~550 g CO₂ m⁻² yr⁻¹, 60% in soil and 40% in biomass (standing and removed). In addition, measurements yield an inorganic carbon sequestration (ICS) rate of ~65 g CO₂ m⁻² yr⁻¹ (for half meter soil depth) via calcite (CaCO₃) precipitation in the soil due to root exhalation of CO₂ (25%) and microbial activity (75%). The drip-irrigated plot showed approximately 3 times higher organic CO₂ sequestration than the control plot, divided equally between the soil and the biomass. For the irrigated plot, the inorganic CO₂ sequestration rate was ~1.8 times higher than that of the control plot. These measured values demonstrate the relatively high potential for carbon sequestration in Mediterranean drylands forests under irrigated and non-irrigated conditions. Full article

Permafrost is an important carbon pool for terrestrial ecosystems and a significant source of atmospheric greenhouse gases, but the effects of ground vegetation and snow cover on permafrost greenhouse gas fluxes are still unclear. The soil–atmosphere exchange fluxes of greenhouse gases (mainly carbon dioxide (CO₂), methane (CH₄), and nitrous oxide (N₂O)) occupy key roles during the winter snow and the vegetation growing seasons. Here, a typical Larix gmelinii forest, located in the permafrost region of the Daxing’an Mountains, northeast China, was studied. Using the static chamber-gas chromatograph method, the relationship between soil greenhouse gas emissions, ground vegetation, and snow cover was investigated. We found that the CO₂, CH₄, and N₂O cumulative fluxes from vegetative soils had increased by 19.5%, 37.5%, and 10.7%, compared with fluxes from areas where the ground vegetation had been removed. Snow cover increased soil CO₂ cumulative flux by 53.1% and soil N₂O cumulative flux by 28.6%, and soil CH₄ cumulative flux decreased by 39.3%. Our results show that snow cover and ground vegetation removal reduce CO₂ and N₂O emissions from permafrost soils. Ground vegetation removal also increases the absorption of CH₄ in permafrost soils, while snow cover removal promotes CH₄ emissions. These findings confirm the effects of ground vegetation and snow cover on the transformation processes of greenhouse gases from forest ecosystems in permafrost regions. Therefore, this research provides scientific data support for the improvement of land surface climate models and the mitigation of climate change in cold regions. Full article

Soil respiration, the exchange of gases between soil and the atmosphere (O₂ consumption and CO₂ production), plays a key role in ecosystem functioning and climate regulation. This study investigated the short-term temporal variability of soil CO₂ emissions and O₂ influx and their relationship with tropical climate conditions and soil attributes in the Cerrado region, Selvíria, MS, Brazil. Soil CO₂ emissions were measured using the LI-8100 portable system, while soil O₂ influx was estimated by linear interpolation of O₂ variation inside the chamber using a UV Flux 25% (ultraviolet light) sensor. Soil temperature and moisture were measured simultaneously in three land use types: pasture (~11 years) and reforested areas with native species and eucalyptus (~35 years). Soils were classified as Oxisoils according to Soil Taxonomy. Significant short-term temporal variability was observed in CO₂ emissions (mean 3.2 ± 0.5 µmol m⁻² s⁻¹), O₂ influx (mean 1.8 ± 0.3 mg O₂ m⁻² s⁻¹), soil temperature and moisture across the land use types. Pasture areas exhibited the lowest CO₂ emission rates, associated with improved soil attributes (soil organic matter, sum of bases and pH) due to management practices, while reforested areas showed overlapping soil respiration patterns and higher temporal variability. Principal component analysis revealed strong coupling between O₂ influx and CO₂ emission in reforested soils. These findings highlight the influence of land use on short-term soil respiration dynamics and underscore the importance of sustainable pasture management and reforestation in the Brazilian Cerrado. The results also support public policies aimed at restoring degraded pastures, reducing deforestation and burning, and enhancing soil carbon sequestration to mitigate climate change. Full article

Although accurate quantification of forest soil CO₂ emissions is critical for improving global carbon cycle models, traditional chamber and gradient methods often underestimate fluxes under windy conditions. Based on long-term field observations in a subtropical maple forest, we quantified the interaction between canopy-level winds and soil pore air pressure fluctuations in regulating vertical CO₂ profiles. The results demonstrate that canopy winds, rather than subcanopy airflow, dominate deep soil CO₂ dynamics, with stronger explanatory power for concentration variability. The observed “wind-pumping effect” operates through soil pressure fluctuations rather than direct wind speed, thereby enhancing advective CO₂ transport. Soil pore air pressure accounted for 33%–48% of CO₂ variation, far exceeding the influence of near-surface winds. These findings highlight that, even in dense forests with negligible understory airflow, canopy turbulence significantly alters soil–atmosphere carbon exchange. We conclude that integrating soil pore air pressure into flux calculation models is essential for reducing underestimation bias and improving the accuracy of forest carbon cycle assessments. Full article

This study evaluated the seasonal variability of soil–atmosphere greenhouse gas (GHG) fluxes—carbon dioxide (CO₂), methane (CH₄), and nitrous oxide (N₂O)—across a land-use gradient in the Andean–Amazon transition zone of Colombia. The gradient included five land-use types incorporating at least one innovative climate-smart practice—improved pasture (IP), cacao agroforestry system (CaAS), copoazu agroforestry system (CoAS), secondary forest with agroforestry enrichment (SFAE), and moriche palm swamp ecosystem (MPSE)—alongside the dominant regional land uses, old-growth forest (OF) and degraded pasture (DP). Soil GHG fluxes varied markedly among land-use types and between seasons. CO₂ fluxes were consistently higher during the dry season, whereas CH₄ and N₂O fluxes peaked in the rainy season. Agroecological and restoration systems exhibited substantially lower CO₂ emissions (7.34–9.74 Mg CO₂-C ha⁻¹ yr⁻¹) compared with DP (18.85 Mg CO₂-C ha⁻¹ yr⁻¹) during the rainy season, and lower N₂O fluxes (0.21–1.04 Mg CO₂-C ha⁻¹ yr⁻¹) during the dry season. In contrast, the MPSE presented high CH₄ emissions in the rainy season (300.45 kg CH₄-C ha⁻¹ yr⁻¹). Across all land uses, CO₂ was the dominant contributor to the total GWP (>95% of emissions). The highest global warming potential (GWP) occurred in DP, whereas CaAS, CoAS and MPSE exhibited the lowest values. Soil temperature, pH, exchangeable acidity, texture, and bulk density play a decisive role in regulating GHG fluxes, whereas climatic factors, such as air temperature and relative humidity, influence fluxes indirectly by modulating soil conditions. These findings underscore the role of diversified agroforestry and restoration systems in mitigating GHG emissions and the need to integrate soil and climate drivers into regional climate models. Full article

Desert steppe ecosystems, characterized by water limitation and high sensitivity to global climate change and anthropogenic disturbance drivers, experience profound alterations in carbon (C) cycling processes driven by the multiplicative interactions among grassland grazing, altered precipitation regimes, and elevated atmospheric nitrogen deposition. However, how historical grazing legacies modulate ecosystem responses to concurrent changes in nitrogen deposition and precipitation regimes remains poorly resolved. To address this, we conducted a field experiment manipulating water and nitrogen addition across grazing intensities (no grazing, light grazing, moderate grazing, heavy grazing) in a Stipa breviflora desert steppe. Over three consecutive growing seasons (2015–2017), we continuously monitored net ecosystem CO₂ exchange (NEE), ecosystem respiration (ER), and gross ecosystem production (GEP) to quantify ecosystem CO₂ fluxes under these interacting global change drivers. Results revealed that water and nitrogen addition did not alter seasonal CO₂ flux dynamics across grazing intensities. Light grazing enhanced ecosystem C sink capacity, whereas heavy grazing reduced NEE and GEP, diminishing C sink strength. Water addition significantly increased CO₂ fluxes, strongly correlated with soil moisture. Nitrogen addition exerted a weak C source effect in a water-deficient year but enhanced the C sink in a water-rich year. Nitrogen plus water addition significantly boosted C sink potential, though this effect diminished along the grazing pressure gradient. Our findings demonstrate that the impacts of climate change on soil C fluxes in desert steppes are mediated by historical grazing intensity. Future manipulative experiments should explicitly incorporate grazing legacy effects, and integrate this factor into C models to generate reliable predictions of grassland C dynamics under global change scenarios. Full article

Reclaiming coastal wetlands for agricultural purposes has led to intensified farming activities, which are anticipated to affect greenhouse gas (GHG) flux processes within coastal wetland ecosystems. However, how greenhouse gas exchanges respond to variations in agricultural reclamation activities across different years remains uncertain. To address this knowledge gap, this study characterized dynamic exchanges within the soil–plant–atmosphere continuum by employing continuous monitoring across four representative coastal wetland soil–vegetation systems in Jiangsu, China. The results show the carbon dioxide (CO₂) and nitrous oxide (N₂O) flux exchanges between the system and the atmosphere and soil–vegetation carbon pools, which revealed the drivers of carbon dynamics in the coastal wetland system. The four study sites, converted from coastal wetlands to agricultural lands at different times (years), generally act as CO₂ sinks and N₂O sources. Higher levels of CO₂ sequestration occur as the age of reclamation rises. In terms of time scale, crops lands were found to be CO₂ sinks during the growing period but became CO₂ sources during the crop fallow period. Although the temporal trend of the N₂O flux was generally smooth, reclaimed farmlands acted as net sources of N₂O, particularly during the crop-growing period. The RDA and PLS-PM models illustrate that soil salinity, acidity, and hydrothermal conditions were the key drivers affecting the magnitude of the GHG flux exchanges under reclamation. This study demonstrates that GHG emissions from reclaimed wetlands can be effectively regulated through science-based land management, calling for prioritized attention to post-development practices rather than blanket restrictions on coastal exploitation. Full article

Investigations of CO₂ emissions in the context of different tillage systems are relevant not only for studying the effects of climate change but also for evaluating the sustainability of soil management. To better understand the influence of soil physico-chemical properties on CO₂ emissions, an experiment was conducted to measure the direct and indirect effects of these soil properties on CO₂ efflux. Soil CO₂ efflux is measured using a closed chamber method (LI-COR LI-8100A) under various tillage in two soil textures. Our research revealed that soil temperature, water content, soil organic carbon, total nitrogen, available phosphorus and pH significantly affected the soil–atmosphere CO₂ exchange rate. Soil CO₂, volumetric water content and soil temperature were higher in loam soil than in sandy loam soil. Soil CO₂ efflux was 8.6% lower in conventional tillage than under reduced and no tillage. Total nitrogen and soil organic carbon contents are dependent on tillage and decreased from no tillage to conventional tillage. Soil agrochemical properties such as SOC, total nitrogen, available phosphorus, available potassium and soil pH were higher evaluated in loam soil than in sandy loam soil. The results of this research are valuable contributions to knowledge on soil management in relation to CO₂ emissions on morainic loamy soil. Full article

Background and Methods: We assessed the prokaryotic and eukaryotic diversity present in non-vegetated and vegetated soils on King George Island, Maritime Antarctic, in combination with measurements of carbon dioxide fluxes. Results: For prokaryotes, 381 amplicon sequence variants (ASVs) were assigned, dominated by the phyla Actinobacteriota, Acidobacteriota, Pseudomonadota, Chloroflexota, and Verrucomicrobiota. A total of 432 eukaryotic ASVs were assigned, including representatives from seven kingdoms and 21 phyla. Fungi dominated the eukaryotic communities, followed by Viridiplantae. Non-vegetated soils had higher diversity indices compared with vegetated soils. The dominant prokaryotic ASV in non-vegetated soils was Pyrinomonadaceae sp., while Pseudarthrobacter sp. dominated vegetated soils. Mortierella antarctica (Fungi) and Meyerella sp. (Viridiplantae) were dominant eukaryotic taxa in the non-vegetated soils, while Lachnum sp. (Fungi) and Polytrichaceae sp. (Viridiplantae) were dominant in the vegetated soils. Measured CO₂ fluxes indicated that the net ecosystem exchange values measured in vegetated soils were lower than ecosystem respiration in non-vegetated soils. However, the total flux values indicated that the region displayed positive ecosystem respiration values, suggesting that the soils may represent a source of CO₂ in the atmosphere. Conclusions: Our study revealed the presence of rich and complex communities of prokaryotic and eukaryotic organisms in both soil types. Although non-vegetated soils demonstrated the highest levels of diversity, they had lower CO₂ fluxes than vegetated soils, likely reflecting the significant biomass of photosynthetically active plants (mainly dense moss carpets) and their resident organisms. The greater diversity detected in exposed soils may influence future changes in CO₂ flux in the studied region, for which comparisons of non-vegetated and vegetated soils with different microbial diversities are needed. This reinforces the necessity for studies to monitor the impact of resident biota on CO₂ flux in different areas of Maritime Antarctica, a region strongly impacted by climatic changes. Full article

Soil moisture is a key factor affecting the exchange of heat and water between the land and the atmosphere. Land data assimilation (LDA) methods that leverage the strengths of both models and observations can generate more accurate initial conditions. However, soil moisture exhibits significant spatial heterogeneity, implying strong local characteristics for both observational and background errors. To elucidate the impact of error localization on LDA, we constructed a land data assimilation system (LDAS) suitable for the Common Land Model (CoLM), based on the simplified extended Kalman filter (SEKF) method. Through practical assimilation experiments using soil moisture retrieval products from the Soil Moisture Active Passive (SMAP) and Fenyun-3D (FY3D) satellites, we investigated the influence of spatial static and dynamic observational and background errors on LDA. The results indicate that by incorporating dynamic errors that account for the spatial heterogeneity of soil, LDAS can adaptively absorb observational information, thereby significantly enhancing assimilation impact and subsequent model forecast accuracy. Compared to experiments applying static errors, dynamic errors increased the spatial correlation coefficients by 17.4% and reduced the root mean square error (RMSE) by 11.2%. The results clearly demonstrate that for soil variable assimilation studies with strong spatial heterogeneity, progressively refined dynamic error estimation is a crucial direction for improving land surface assimilation performance. Full article

Vegetation is a fundamental component of terrestrial ecosystems, and accurately assessing the effects of seasonal climate variations, extreme weather events, and land use changes on vegetation dynamics is crucial. The Ganjiang River Basin (GRB), a key region for water conservation and recharge in southeastern China, has experienced significant land use changes and variable climate in the past. However, comprehensive evaluations of how these changes have impacted vegetation remain limited. To address this gap, we used machine learning models (random forest and XGBoost) to assess the impact of seasonal and extreme climate variables, land cover, topography, soil properties, atmospheric CO₂, and night-time light intensity on vegetation dynamics. We found that the annual mean NDVI showed a slight increase from 1990 to 1999 but has decreased significantly over the last 8 years. XGBoost was better than the RF model in simulating the NDVI when using all five types of data source (R² = 0.85; RMSE = 0.04). The most critical factors influencing the NDVI were forest and cropland ratio, followed by soil organic carbon content, elevation, cation exchange capacity, night-time light intensity, and CO₂ concentration. Spring minimum temperature was the most important seasonal climate variable. Both linear and nonlinear relationships were identified between these variables and the NDVI, with most variables exhibiting threshold effects. These findings underscore the need to develop and implement effective land management strategies to enhance vegetation health and promote ecological balance in the region. Full article

Opposite to atmospheric CO₂ concentrations, which reach a minimum during the vegetation season (e.g., June–August in the Northern Hemisphere), soil CO₂ reaches a maximum in the same period due to the root respiration. In karst areas, characterized by high rock porosity, this excess CO₂ seeps inside caves, locally increasing pCO₂ values above 1%. To better understand the role of karst areas in the carbon cycle, it is essential to understand the mechanisms of CO₂ dynamics in such regions. In this study, we present and discuss the spatial and temporal variability of air temperature and CO₂ concentrations in Samograd Cave, Croatia, based on three years of monthly spot measurements. The cave consists of a single descending passage, resulting in a characteristic bimodal climate, with stable conditions during summer (i.e., stagnant air inside the cave) and a strong convective cell bringing in cold air during winter. This bimodality is reflected in both CO₂ concentrations and air temperatures. In summer, the exchange of air through the cave’s main entrance is negligible, allowing the temperature and CO₂ concentration to equilibrate with the surrounding rocks, resulting in high in-cave CO₂ concentrations, sourced from enhanced root respiration. During cold periods, CO₂ concentrations are low due to frequent intrusions of fresh external air, which effectively flush out CO₂ from the cave. Both parameters show distinct spatial variability, highlighting the role of cave morphology in their dynamics. The CO₂ concentrations and temperatures have increased over the observation period, in line with external changes. Our results highlight the role of caves in transferring large amounts of CO₂ from soil to the atmosphere via caves, a process that could have a large impact on the global atmospheric CO₂ budget, and thus, call for a more in-depth study of these mechanisms. Full article

Plant stomata regulate transpiration (T) and CO₂ assimilation, essential for the water–carbon cycle. Quantifying how environmental factors influence stomatal conductance will provide a scientific basis for understanding the vegetation–atmosphere water–carbon exchange process and water use strategies. Based on eddy covariance and hydro-metrological observations from FLUXNET sites with four plant functional types and using three widely applied methods to estimate ecosystem T from eddy covariance data, namely uWUE, Perez-Priego, and TEA, we quantified the regulation effect of environmental factors on canopy stomatal conductance (G_s). The environmental factors considered here include radiation (net radiation and solar radiation), water (soil moisture, relative air humidity, and vapor pressure deficit), temperature (air temperature), and atmospheric conditions (CO₂ concentration and wind speed). Our findings reveal variation in the influence of these factors on G_s across biomes, with air temperature, relative humidity, soil water content, and net radiation being consistently significant. Wind speed had the least influence. Incorporating the leaf area index into a Random Forest model to account for vegetation phenology significantly improved model accuracy (R² increased from 0.663 to 0.799). These insights enhance our understanding of the primary factors influencing stomatal conductance, contributing to a broader knowledge of vegetation physiology and ecosystem functioning. Full article