Understanding Of Carbon Cycle Research Articles

Aboveground Carbon Stock Estimation Based on Backpack LiDAR and UAV Multispectral Imagery at the Forest Sample Plot Scale

Aboveground carbon stocks (AGCs) in forests play an important role in understanding carbon cycle processes. The global forestry sector has been working to find fast and accurate methods to estimate forest AGCs and implement dynamic monitoring. The aim of this study was to explore the effects of backpack LiDAR and UAV multispectral imagery on AGC estimation for two tree species (Larix gmelinii and Betula platyphylla) and to emphasize the accuracy of the models used. We estimated the AGC of Larix gmelinii and B. platyphylla forests using multivariate stepwise linear regression and random forest regression models using backpack LiDAR data and multi-source remote sensing data, respectively, and compared them with measured data. This study revealed that (1) the diameter at breast height (DBH) extracted from backpack LiDAR and vegetation indices (RVI and GNDVI) extracted from UAV multispectral imagery proved to be extremely effective in modeling for estimating AGCs, significantly improving the accuracy of the model. (2) Random forest regression models estimated AGCs with higher precision (Xing’an larch R2 = 0.95, RMSE = 3.99; white birch R2 = 0.96, RMSE = 3.45) than multiple linear regression models (Xing’an larch R2 = 0.92, RMSE = 6.15; white birch R2 = 0.96, RMSE = 3.57). (3) After combining backpack LiDAR and UAV multispectral data, the estimation accuracy of AGCs for both tree species (Xing’an larch R2 = 0.95, white birch R2 = 0.96) improved by 2% compared to using backpack LiDAR alone (Xing’an larch R2 = 0.93, white birch R2 = 0.94).

Atmospheric CO2 absorption and counteraction by CH4 emission across contrasting habitats in a large eutrophic lake

Lakes are a crucial component of global carbon cycling and play a key role in the global CO2 and CH4 budgets. Intensified anthropogenic activity contributes to eutrophication, and reduces macrophytes while increasing phytoplankton in shallow lakes. However, the information on how the CO2 and CH4 fluxes at water–air interface temporally varies across habitats dominated by various primary producers in lakes and how CH4 emission counteracts CO2 adsorption is limited. In this study, in situ fluxes of CO2 and CH4 were measured monthly for one year at four sites in Lake Taihu, China. These sites had contrasting habitats dominated by high-density phytoplankton, low-density phytoplankton, floating-leaved macrophytes, and submerged macrophytes. We found that the CO2 fluxes ranged from − 439 ± 385 to − 106 ± 348μmol m−2h−1 and the CH4 fluxes ranged from 1.96 ± 3.79 to 10.7 ± 14.8μmol m−2h−1. The fluxes of CO2 and CH4 were mainly regulated by water pH, phosphorus levels, and sediment organic carbon. All four habitats acted as sinks of atmospheric CO2 and sources of atmospheric CH4, and the habitats with high-density phytoplankton showed the highest CO2 absorption and strongest CH4 emission. Generally, the CH4 emission counteracted 7–69 % of the atmospheric CO2 absorption in the four sites. These results collectively revealed that in a large, shallow eutrophic lake, habitats dominated by various primary producers consistently adsorb atmospheric CO2, even being counteracted by CH4 emission. These findings provide valuable insights for understanding carbon cycling and CO2 and CH4 dynamics across the water–air interface in shallow lakes.

The response of terrestrial vegetation carbon use efficiency to global environmental changes

Terrestrial vegetation carbon use efficiency (CUE) is a key measure for assessing carbon transfer from the atmosphere to terrestrial biomass, crucial for understanding carbon cycling and allocation in ecosystems. CUE provides valuable insights into how terrestrial ecosystems respond to environmental changes. In this study, we utilized satellite datasets (MODIS and GLASS), MsTMIP models, and TRENDY models to analyze the spatiotemporal distribution characteristics of global vegetation CUE. We found that the average CUE for global land vegetation is 0.44 ± 0.06, with a slight annual increase and significant spatial heterogeneity, characterized by latitude gradients and vegetation types. High-latitude regions demonstrated higher CUE values compared to low-latitude regions. Further employing an integrated attribution approach, we identified the response mechanisms of vegetation CUE to global changes. The comprehensive response of vegetation CUE to climate change, land use change, atmospheric CO2, and nitrogen deposition was found to fluctuate and increase, with a model-averaged CUE increase of approximately 0.01. Land use change was identified as the largest contributor to the annual trend of overall global CUE (48.8%), while climate change was the main factor influencing the interannual variability (IAV) of global CUE (91.7%). Regarding global distribution, the IAV of vegetation CUE is mainly influenced by climate change. CUE annual trends in more regions were influenced by climate change, with 65% and 73% of the ensemble mean of the MsTMIP and TRENDY models, respectively. The results of the MsTMIP and TRENDY models consistently show that, globally, land use change affects about a quarter of the total annual trend of CUE. Land use change affected CUE annual trends to a greater extent than climate change. In addition, the vegetation type most affected by climate change is the deciduous needleleaf forests, and the CUE annual trend of cropland is most affected by land use change. Our findings reveal global patterns and drivers of CUE variability, highlighting the significant impact of climate change and land use change.

High-resolution organic and black carbon records in the South Yellow Sea over the last century

The mud depositional area ("mud area") of the South Yellow Sea serves as a prominent carbon sink within the Eastern Continental Shelf of China, offering crucial insights into human activities and climate fluctuations and its relationship with carbon cycle. This study investigates variations in total organic carbon (TOC) and black carbon (BC) concentrations in South Yellow Sea sediments. By combining 210Pb isotope analysis with grain-size profiling, the study distinguishes organic carbon origins, revealing the complex interplay between human activities and environmental shifts since the Industrial Revolution. The reasons for discrepancies between TOC and BC contents are analyzed, yielding the following results: (1) Sediment core QY-2 predominantly contains terrestrial-sourced organic carbon, primarily derived from the Yellow River and the Yangtze River. (2) Temporal fluctuations of BC in core QY-2 show distinct trends, periodic responses to human activities, particularly peaks in 1937 and 1945, linked to large-scale wars in China. (3) Relaxed carbon emission regulations in China, coupled with industrial growth spurred by the “reform and opening up” policy, led to a continuous rise in BC content from the mid-1960s to the 1980s, peaking in 1980. Subsequently, reduced BC values during the 1990s correlated with emission control policies and the shift from highly polluting domestic coal stoves to cleaner alternatives like liquefied petroleum gas or natural gas stoves. (4) BC content was influenced by the East Asian monsoon and Pacific Decadal Oscillation (PDO), with higher BC accumulation rates occurring in summer and depletion in winter. (5) Interestingly, changes in BC and TOC content exhibited a negative correlation. While grain size and material sources minimally influenced these discrepancies, the primary driver lay in the water's redox environment, impacting other TOC components and thereby causing variations in both TOC and BC content. This study of black carbon sources to sinks in the South Yellow Sea Mud Area holds significant implications for the broader Yellow Sea sedimentary system and provides support for understanding carbon cycle and marine environments.

Enzyme Activity Stoichiometry Suggests That Fertilization, Especially Nitrogen Fertilization, Alleviates Nutrient Limitation of Soil Microorganisms in Moso Bamboo Forests

Rational application of N fertilizer is essential for maintaining the long-term productivity of Moso bamboo forests. Microbial activity is a crucial indicator of soil quality. Changes in soil nutrient resources due to N addition can lead to microbial nutrient limitations, thereby impeding the maintenance of soil quality. Currently, there is limited research on the effects of N application on microbial nutrient limitations in Moso bamboo forest soils. To examine the changes in extracellular enzyme activity and microbial nutrient limitations in Moso bamboo forest soils following N application, we conducted an N application experiment in northern Guizhou. The findings revealed that the N3 treatment (726 kg·N·hm−2·yr−1) significantly reduced β-glucosidase (BG) activity by 27.61% compared to the control group (no fertilization). The N1 (242 kg·N·hm−2·yr−1), N2 (484 kg·N·hm−2·yr−1), and N3 treatments notably increased the activities of leucine aminopeptidase (LAP) and N-acetyl-β-D-glucosidase (NAG) by 11.45% to 15.79%. Acid phosphatase (ACP) activity remained unaffected by fertilization. N application treatments significantly decreased the C:Ne and C:Pe ratios, while the N:Pe ratio was less influenced by N fertilizer application. Scatter plots and vector characteristics of enzyme activity stoichiometry suggested that microorganisms in the study area were limited by C and N, and N fertilizer application reduced the vector length and increased the vector angle, indicating that N application alleviated the C and N limitation of microorganisms in Moso bamboo forests. Redundancy Analysis (RDA) demonstrated that microbial biomass phosphorus (MBP) was the most critical factor affecting extracellular enzyme activity and stoichiometry. Furthermore, Random Forest Regression analysis identified MBP and the N:Pm ratio as the most significant factors influencing microbial C and N limitation, respectively. The study demonstrated that N application modulates the microbial nutrient acquisition strategy by altering soil nutrient resources in Moso bamboo forests. Formulating fertilizer application strategies based on microbial nutrient requirements is more beneficial for maintaining soil quality and sustainably managing Moso bamboo forests. Additionally, our study offers a theoretical reference for understanding carbon cycling in bamboo forest ecosystems in the context of substantial N inputs.

A stacking ensemble model for predicting soil organic carbon content based on visible and near-infrared spectroscopy

The content of soil organic carbon (SOC) plays an important role in maintaining ecosystem functions, protecting soil biodiversity, and understanding carbon cycling processes. The combination of visible and near-infrared spectroscopy (VIS–NIRS) and machine learning can achieve rapid prediction of SOC content. However, it is still relatively unknown how to integrate the characteristics of various machine learning models to improve the performance of SOC prediction models. In this study, a new model for predicting SOC content based on stacking ensemble learning was proposed by using VIS–NIRS. The prediction performances of six different models including Support Vector Regression (SVR), Extreme Gradient Boosting (XGBoost), Random Forest (RF), Light Gradient Boosting Machine (LightGBM), PartialLeast-square (PLS) and Extreme Learning Machine (ELM) on SOC content under different spectral preprocessing methods were compared. The results indicated that SVR, XGBoost, and LightGBM models provide better prediction performance after first-order derivative preprocessing. After comparing the performance of various combinations of base models applied to the first layer of a stacking ensemble model, the results showed that both the combination of XGBoost, LightGBM, and SVR models and the combination of SVR, ELM, and LightGBM models achieve the best performance. The coefficient of determination (R2) of the stacking ensemble model on the test set reaches 0.84, which improves the accuracy of the model compared with the traditional single model. The stability of the stacking ensemble model was verified by applying it to datasets of different sizes, which can replace traditional machine learning models in predicting SOC content.

The Response of Soil Respiration to Temperature and Humidity in the Thermokarst Depression Zone of the Headwater Wetlands of Qinghai Lake.

As the climate warms, the thickening of the active layer of permafrost has led to permafrost melting and surface collapse, forming thermokarst landforms. These changes significantly impact regional vegetation, soil physicochemical properties, and hydrological processes, thereby exacerbating regional carbon cycling. This study analyzed the relationship between soil respiration rate (Rs), soil temperature (T), and volumetric water content (VWC) in the thermokarst depression zone of the headwater wetlands of Qinghai Lake, revealing their influence on these soil parameters. Results showed a significant positive correlation between soil temperature and Rs (p < 0.001), and a significant negative correlation between VWC and Rs (p < 0.001). The inhibitory effect of VWC on Rs in the thermokarst depression zone was stronger than under natural conditions (p < 0.05). Single-factor models indicated that the temperature-driven model had higher explanatory power for Rs variation in both the thermokarst depression zone (R2 = 0.509) and under natural conditions (R2 = 0.414), while the humidity-driven model had lower explanatory power. Dual-factor models further improved explanatory power, slightly more so in the thermokarst depression zone. This indicates that temperature and humidity jointly drive Rs. Additionally, during the daytime, temperature had a more significant impact on Rs under natural conditions, while increased VWC inhibited Rs. At night, the positive correlation between Rs and temperature in the thermokarst depression zone increased significantly. The temperature sensitivity (Q10) values of Rs were 3.32 and 1.80 for the thermokarst depression zone and natural conditions, respectively, indicating higher sensitivity to temperature changes at night in the thermokarst depression zone. This study highlights the complexity of soil respiration responses to temperature and humidity in the thermokarst depression zone of Qinghai Lake's headwater wetlands, contributing to understanding carbon cycling in wetland ecosystems and predicting wetland carbon emissions under climate change.

Microbial polyphenol metabolism is part of the thawing permafrost carbon cycle

With rising global temperatures, permafrost carbon stores are vulnerable to microbial degradation. The enzyme latch theory states that polyphenols should accumulate in saturated peatlands due to diminished phenol oxidase activity, inhibiting resident microbes and promoting carbon stabilization. Pairing microbiome and geochemical measurements along a permafrost thaw-induced saturation gradient in Stordalen Mire, a model Arctic peatland, we confirmed a negative relationship between phenol oxidase expression and saturation but failed to support other trends predicted by the enzyme latch. To inventory alternative polyphenol removal strategies, we built CAMPER, a gene annotation tool leveraging polyphenol enzyme knowledge gleaned across microbial ecosystems. Applying CAMPER to genome-resolved metatranscriptomes, we identified genes for diverse polyphenol-active enzymes expressed by various microbial lineages under a range of redox conditions. This shifts the paradigm that polyphenols stabilize carbon in saturated soils and highlights the need to consider both oxic and anoxic polyphenol metabolisms to understand carbon cycling in changing ecosystems.

Light grazing reduces the abundance of carbon cycling functional genes by decreasing oligotrophs microbes in desert steppe

Understanding the functional genes of microorganisms involved in carbon cycling processes can link microbial community structure to potential ecological functions. However, the effects of grazing on the relationship between carbon cycling functional genes and soil environment need to be further investigated as a global land use activity. A replicated sheep grazing platform was established in Northern China in 2004 with four different stocking rates: no grazing (0 sheep ha−1 month−1), light grazing (0.15 sheep ha−1 month−1), moderate grazing (0.30 sheep ha−1 month−1), and heavy grazing (0.45 sheep ha−1 month−1). To examine the effects of biotic and abiotic factors on microbial species and functional gene abundance, we collected soil samples after 17 years of grazing analyzed for the abundance of microbial communities, the abundance of carbon function genes, plant carbon input and soil environmental factors. We found that light grazing reduced carbon cycling functional genes compared to no grazing (fencing). With increasing grazing intensity, the absolute abundance of functional genes increased. Changes in microbial species abundance were mainly responsible for the changes in the structure of carbon cycling functional genes. Our results emphasize that elucidating how grazing affects the carbon cycling functional genes through the effects of plant carbon inputs and the environment, and the interactions between them, will provide important information for understanding carbon cycling processes in grassland ecosystems.

Nitrate nitrogen enhances the efficiency of photoprotection in Leymus chinensis under drought stress.

Global climate change exerts a significant impact on the nitrogen supply and photosynthesis ability in land-based plants. The photosynthetic capacity of dominant grassland species is important if we are to understand carbon cycling under climate change. Drought stress is one of the major factors limiting plant photosynthesis, and nitrogen (N) is an essential nutrient involved in the photosynthetic activity of leaves. The regulatory mechanisms responsible for the effects of ammonium (NH4 +) and nitrate (NO3 -) on the drought-induced photoinhibition of photosystem II (PSII) in plants have yet to be fully elucidated. Therefore, there is a significant need to gain a better understanding of the role of electron transport in the photoinhibition of PSII. In the present study, we conducted experiments with normal watering (LD), severe drought (MD), and extreme drought (HD) treatments, along with no nitrogen (N0), ammonium (NH4), nitrate (NO3), and mixed nitrogen (NH4NO3) treatments. We analyzed pigment accumulation, reactive oxygen species (ROS) accumulation, photosynthetic enzyme activity, photosystem activity, electron transport, and O-J-I-P kinetics. Analysis showed that increased nitrate application significantly increased the leaf chlorophyll content per unit area (Chlarea) and nitrogen content per unit area (Narea) (p< 0.05). Under HD treatment, ROS levels were lower in NO3-treated plants than in N0 plants, and there was no significant difference in photosynthetic enzyme activity between plants treated with NO3 and NH4NO3. Under drought stress, the maximum photochemical efficiency of PSII (Fv/Fm), PSII electron transport rate (ETR), and effective quantum yield of PSII (φPSII) were significant higher in NO3-treated plants (p< 0.05). Importantly, the K-band and G-band were higher in NO3-treated plants. These results suggest that drought stress hindered the formation of NADPH and ATP in N0 and NH4-treated L. chinensis plants, thus damaging the donor side of the PSII oxygen-evolving complex (OEC). After applying nitrate, higher photosynthetic enzyme and antioxidant enzyme activity not only protected PSII from photodamage under drought stress but also reduced the rate of damage in PSII during the growth of L. chinensis growth under drought stress.

Molecular mechanisms of microbiome modulation by the eukaryotic secondary metabolite azelaic acid.

Photosynthetic eukaryotes, such as microalgae and plants, foster fundamentally important relationships with their microbiome based on the reciprocal exchange of chemical currencies. Among these, the dicarboxylate metabolite azelaic acid (Aze) appears to play an important, but heterogeneous, role in modulating these microbiomes, as it is used as a carbon source for some heterotrophs but is toxic to others. However, the ability of Aze to promote or inhibit growth, as well as its uptake and assimilation mechanisms into bacterial cells are mostly unknown. Here, we use transcriptomics, transcriptional factor coexpression networks, uptake experiments, and metabolomics to unravel the uptake, catabolism, and toxicity of Aze on two microalgal-associated bacteria, Phycobacter and Alteromonas, whose growth is promoted or inhibited by Aze, respectively. We identify the first putative Aze transporter in bacteria, a 'C4-TRAP transporter', and show that Aze is assimilated through fatty acid degradation, with further catabolism occurring through the glyoxylate and butanoate metabolism pathways when used as a carbon source. Phycobacter took up Aze at an initial uptake rate of 3.8×10-9 nmol/cell/hr and utilized it as a carbon source in concentrations ranging from 10 μM to 1 mM, suggesting a broad range of acclimation to Aze availability. For growth-impeded bacteria, we infer that Aze inhibits the ribosome and/or protein synthesis and that a suite of efflux pumps is utilized to shuttle Aze outside the cytoplasm. We demonstrate that seawater amended with Aze becomes enriched in bacterial families that can catabolize Aze, which appears to be a different mechanism from that in soil, where modulation by the host plant is required. This study enhances our understanding of carbon cycling in the oceans and how microscale chemical interactions can structure marine microbial populations. In addition, our findings unravel the role of a key chemical currency in the modulation of eukaryote-microbiome interactions across diverse ecosystems.

Molecular mechanisms of microbiome modulation by the eukaryotic secondary metabolite azelaic acid

Photosynthetic eukaryotes, such as microalgae and plants, foster fundamentally important relationships with their microbiome based on the reciprocal exchange of chemical currencies. Among these, the dicarboxylate metabolite azelaic acid (Aze) appears to play an important, but heterogeneous, role in modulating these microbiomes, as it is used as a carbon source for some heterotrophs but is toxic to others. However, the ability of Aze to promote or inhibit growth, as well as its uptake and assimilation mechanisms into bacterial cells are mostly unknown. Here, we use transcriptomics, transcriptional factor coexpression networks, uptake experiments, and metabolomics to unravel the uptake, catabolism, and toxicity of Aze on two microalgal-associated bacteria, Phycobacter and Alteromonas, whose growth is promoted or inhibited by Aze, respectively. We identify the first putative Aze transporter in bacteria, a ‘C4-TRAP transporter’, and show that Aze is assimilated through fatty acid degradation, with further catabolism occurring through the glyoxylate and butanoate metabolism pathways when used as a carbon source. Phycobacter took up Aze at an initial uptake rate of 3.8×10–9 nmol/cell/hr and utilized it as a carbon source in concentrations ranging from 10 μM to 1 mM, suggesting a broad range of acclimation to Aze availability. For growth-impeded bacteria, we infer that Aze inhibits the ribosome and/or protein synthesis and that a suite of efflux pumps is utilized to shuttle Aze outside the cytoplasm. We demonstrate that seawater amended with Aze becomes enriched in bacterial families that can catabolize Aze, which appears to be a different mechanism from that in soil, where modulation by the host plant is required. This study enhances our understanding of carbon cycling in the oceans and how microscale chemical interactions can structure marine microbial populations. In addition, our findings unravel the role of a key chemical currency in the modulation of eukaryote-microbiome interactions across diverse ecosystems.

Production and preservation of organic carbon in sub-seafloor tephra layers

The deposition of volcanic ash into the ocean initiates a range of chemical and biological reactions. During diagenesis, these reactions may enhance the preservation of organic carbon (OC) in marine sediments, which ultimately promotes CO2 sequestration from the ocean-atmosphere system. However, this interpretation is reliant on a small number of studies that make a link between tephra and OC burial. Here, we compare organic and inorganic geochemical data from tephra-bearing marine sediments from three sites that differ widely in their location, age, and composition. We show that OC is buried in, and proximal to, tephra layers, in proportions higher than would be expected via simple admixture of surrounding sediment. Our data indicate that this OC is preserved primarily through interactions with reactive iron phases, which act to physically protect the carbon from oxidation. Analysis of the composition of the OC associated with reactive iron indicates it is isotopically (consistently more negative δ13C than sediment) and chemically (comprised of compounds not found in the sediment) distinct from OC in the background sediments. We interpret this signal as indicating a microbial source of OC, with autochthonous OC production resulting from autotrophic microbial exploitation of nutrients supplied from tephra. This finding has implications for our understanding of carbon cycling on Earth, and possibly for the emergence of life in terrestrial and perhaps even extra-terrestrial environments.

Estimation of ecosystem respiration and photosynthesis in supersaturated stream water downstream of a hydropower plant

The estimation of whole stream metabolism, as determined by photosynthesis and respiration, is critical to our understanding of carbon cycling and carbon subsidies to aquatic food-webs. The mass development of aquatic plants is a worldwide problem for human activities and often occurs in regulated rivers, altering biodiversity and ecosystem functions. Hydropower plants supersaturate water with gases and prevent the use of common whole stream metabolism models to estimate ecosystem respiration. Here we used the inert noble gas argon to parse out biological from physical processes in stream metabolism calculations. We coupled the O2:Ar ratio determined by gas chromatography in grab samples with in-situ oxygen concentrations measured by an optode to estimate aquatic plant photosynthesis and ecosystem respiration during supersaturation events through a parsimonious approach. The results compared well with a more complicated two-station model based on O2 mass balances in non-supersatured water, and with associated changes in dissolved CO2 (or dissolved inorganic carbon). This new method provides an independent approach to evaluate alternative corrections of dissolved oxygen data (e.g. through the use of total dissolved gases) in long term studies. The use of photosynthesis-irradiance models allows the determination of light parameters such as the onset of light saturation or low light use efficiency, which could be used for inverse modelling. The use of the O2:Ar approach to correct for oversaturation may become more applicable with the emergence of portable mass inlet mass spectrometers (MIMS). Photosynthesis was modest (2.9-5.8 g O2 m2 day−1) compared to other rivers with submerged vegetation, likely indicating nutrient co-limitations (CO2, inorganic N and P). Respiration was very low (-2.1 to -3.9 g O2 m2 day−1) likely due to a lack of allochthonous carbon supply and sandy sediment.

Fate of carbon influenced by the in-situ growth of phototrophic biofilms at the soil–water interface of paddy soil

Phototrophic biofilms (PBs) are commonly found in the sediment/soil–water interface of paddy soils and have a significant impact on carbon cycles. However, the specific carbon fate influenced by the in-situ growth of PBs in paddy soil remains unclear. In this study, we investigated the effect of in situ PBs growth on methane and carbon dioxide emissions, as well as dissolved organic matter (DOM) transformation. Our findings demonstrated a negative correlation between PBs growth and methane and carbon dioxide emissions, while showing a positive correlation with DOM composition. The in-situ growth of PBs reduced methane emissions by approximately 79 % and carbon dioxide emissions by approximately 33 % in the daytime, and also slowed down the degradation rate of dissolved organic matter from over 30.4 % to <16 %. Microsensor measurements revealed that these changes were attributed to the increased concentration and penetration depth of oxygen, as well as variations in pH caused by the growth of in situ PBs. Co-occurrence analysis indicated a robust correlation between DOM transformation and the significantly suppressed methanogenesis by methanogens such as Methanosaeta, Methanomassiliicoccus and Methanosarcina, and also the notably enhanced methane oxidation by methanotrophs including Methylobacterium, Methyloversatilis and Methylomonas, in response to the growth of PBs. These findings shed light on the impact of in situ PBs on methane and carbon dioxide emissions and DOM transformation, providing new insights for understanding carbon cycling in paddy soils.

Shear and Scholte wave measurements on surficial intertidal mudflat sediments using medical sonoelastography techniques

In low-energy environments, the water–sediment interface often contains a dynamic fluffy transition layer (FTL) of suspended organic and inorganic matter, which is transformed by complex physical, biological, and chemical processes. The FTL mechanical properties are important for understanding carbon cycle dynamics and for robust sediment acoustic characterization, but erodibility and size make it difficult to study non-invasively and at sufficient resolution. In medical ultrasound sonoelastography, shear waves are excited within the body either using the acoustic radiation force (ARF) or via external vibration at the skin surface. Sub-micrometer displacements are measured remotely by subsequent ultrasound imaging at up to 10 kHz frame rate with approximately 0.5 μm spatial resolution. In this study, sediment cores were extracted from the intertidal mudflats from the Great Bay Estuary, USA. Compressional wave speed and attenuation measurements were performed using a core logger. Shear and Scholte waves were excited in the FTL using ARF- and external-vibration-based techniques and the motion detected with clinical ultrasound imaging arrays. Upward refraction of the shear wave was observed, and shear and Scholte wave speed and attenuation were measured. Finally, scanning electron microscopy was used to image the microstructure. Comparison between wave properties and microstructure will be discussed.

A dataset of soil carbon flux in Xishuangbanna tropical rainforest ecosystem from 2003 to 2008

Long-term and large-scale carbon flux data supports research on key processes of the global carbon and water cycle. Soil is the largest carbon pool in the terrestrial ecosystem. Small variations in soil carbon can significantly impact the carbon budgets of terrestrial ecosystems. Tropical forest is a crucial carbon sink in the world. However, there have been some reports indicating a decrease in soli carbon levels, potentially approaching neutrality, as a result of soil carbon degradation caused by global changing. Thus, the long-term and continuous observation of soil carbon flux is of great significance for evaluating the role of soil carbon in the tropical carbon cycle. ChinaFLUX Observation and Research Network (ChinaFLUX) has not only conducted the observation and research on carbon flux by using vorticity correlation technology, but also carried out the long-term observation and research on surface CO2 flux by using the box method. In this dataset, we collected and sorted out the soil CO2 emission flux data and conventional meteorological data of Xishuangbanna tropical rain forest ecosystem from January 2003 to August 2008 according to the static box observation method and data quality control management of greenhouse gas emissions. The dataset consists of three types of files at daily, monthly and yearly scales, covering surface CO2 flux, pressure, atmospheric temperature, soil temperature (5 cm) and soil water content (5 cm). It is expected to provide essential data for estimating carbon balance and understanding carbon cycle processes at both tropical and global scales.

Exploring carbon sequestration in broad-leaved Korean pine forests: Insights into photosynthetic and respiratory processes

A comprehensive understanding of carbon assimilation and sequestration in broad-leaved Korean pine forests is crucial for accurately estimating this significant aspect of temperate forests at a regional scale. In this study, we introduced a high-temporal resolution model designed for carbon assimilation insights at the plot scale, focusing on specific parameters such as leaf area dynamics, vertical leaf distribution, photosynthetically active radiation (PAR) fluctuations, and the photosynthetic traits of tree species. The findings reveal that most tree species in broad-leaved Korean pine forests exhibit an inverted U-shaped pattern in leaf area dynamics, with shorter leaf drop periods than leaf expansion events. Leaf distribution varies significantly among different canopy heights, with approximately 80 % of the leaves above 15 m. PAR decreases as canopy height decreases, with PAR at 25 m accounting for about 60 % of the PAR above the canopy. Our framework incorporates a leaf-scale light-response curve and empirical photosynthesis-temperature relationships to estimate forest carbon assimilation on daily and hourly scales accurately. Using the model, we assess the gross primary productivity (GPP), leaf net photosynthetic assimilation (LNPA), and carbon increment (ΔC) of broad-leaved Korean pine forests from 2017 to 2020. The results demonstrate GPP, LNPA, and ΔC values of 21.4 t·ha−1·a−1, 17.4 t·ha−1·a−1, and 4.0 t·ha−1·a−1, respectively. Regarding efficiency, GPP, LNPA, and ΔC per square meter of leaf per year are 179 g, 146 g, and 33 g, respectively. Notably, tree species in the canopy layer of the forest exhibit significantly higher efficiency than those in the understory layer. This research significantly contributes to our understanding of carbon cycling and the responses of forest ecosystems to climate change. Moreover, it provides a practical tool for forest management and the development of carbon sequestration strategies.

Carbon dioxide reduction by photosynthesis undetectable even during phytoplankton blooms in two lakes

Lakes located in the boreal region are generally supersaturated with carbon dioxide (CO2), which emerges from inflowing inorganic carbon from the surrounding watershed and from mineralization of allochthonous organic carbon. While these CO2 sources gained a lot of attention, processes that reduce the amount of CO2 have been less studied. We therefore examined the CO2 reduction capacity during times of phytoplankton blooms. We investigated partial pressure of CO2 (pCO2) in two lakes at times of blooms dominated by the cyanobacterium Gloeotrichia echinulata (Erken, Sweden) or by the nuisance alga Gonyostomum semen (Erssjön, Sweden) during two years. Our results showed that pCO2 and phytoplankton densities remained unrelated in the two lakes even during blooms. We suggest that physical factors, such as wind-induced water column mixing and import of inorganic carbon via inflowing waters suppressed the phytoplankton signal on pCO2. These results advance our understanding of carbon cycling in lakes and highlight the importance of detailed lake studies for more precise estimates of local, regional and global carbon budgets.

Quantifying land carbon cycle feedbacks under negative CO2emissions

Abstract. Land and ocean carbon sinks play a major role in regulating atmospheric CO2 concentration and climate. However, their future efficiency depends on feedbacks in response to changes in atmospheric CO2 concentration and climate, namely the concentration–carbon and climate–carbon feedbacks. Since carbon dioxide removal (CDR) is a key mitigation measure in emission scenarios consistent with global temperature goals in the Paris Agreement, understanding carbon cycle feedbacks under negative CO2 emissions is essential. This study investigates land carbon cycle feedbacks under positive and negative CO2 emissions using an Earth system model of intermediate complexity (EMIC) driven with an idealized scenario of symmetric atmospheric CO2 concentration increase (ramp-up) and decrease (ramp-down), run in three modes. Our results show that the magnitudes of carbon cycle feedbacks are generally smaller in the atmospheric CO2 ramp-down phase than in the ramp-up phase, except for the ocean climate–carbon feedback, which is larger in the ramp-down phase. This is largely due to carbon cycle inertia: the carbon cycle response in the ramp-down phase is a combination of the committed response to the prior atmospheric CO2 increase and the response to decreasing atmospheric CO2. To isolate carbon cycle feedbacks under decreasing atmospheric CO2 and quantify these feedbacks more accurately, we propose a novel approach that uses zero emission simulations to quantify the committed carbon cycle response. We find that the magnitudes of the concentration–carbon and climate–carbon feedbacks under decreasing atmospheric CO2 are larger in our novel approach than in the standard approach. Accurately quantifying carbon cycle feedbacks in scenarios with negative emissions is essential for determining the effectiveness of carbon dioxide removal in drawing down atmospheric CO2 and mitigating warming.