Terrestrial Carbon Research Articles

Terrestrial Carbon Sink and Clean Air Co‐Benefits From China's Carbon Neutrality Policy

AbstractAs the world's largest carbon emitter, China has been confronting the dual challenge of climate change and air pollution. China's quest for reducing carbon emissions will promisingly benefit the air quality, yet its impact on carbon sinks remains unclear. Here, we assess the effect of China's clean air actions and carbon neutrality policy on air quality and its associated co‐benefits for terrestrial carbon sinks by integrating multiple observations and numerical modeling. We find a quadratic response of plant photosynthesis to aerosol loading due to trade‐offs between diffuse fertilization effect and light limitations. The estimations show that China's air pollution suppresses terrestrial carbon uptake through aerosol‐induced light limitations, leading to a 7.3% decrease in plant productivity in the 2010s. In the context of carbon neutrality pledge, the associated aerosol reductions tend to alleviate the suppression and produce an additional CO2 removal of 0.39 GtCO2 year−1. Our results uncover the enhanced terrestrial carbon sinks by aerosol mitigation, highlighting the synergy between carbon neutrality and clean air.

A 30-m gross primary production dataset from 2016 to 2020 in China

Estimating gross primary production (GPP) of terrestrial ecosystems is important for understanding the terrestrial carbon cycle. However, existed nationwide GPP datasets are primarily driven by coarse spatial resolutions (≥500 m) remotely sensed data, which fails to capture the spatial heterogeneity of GPP across different ecosystem types at land surface. This paper introduces a new GPP dataset, Hi-GLASS GPP v1, with a fine spatial resolution (30-m) and monthly temporal resolution from 2016 to 2020 in China. The Hi-GLASS GPP v1 dataset is generated from 30-m Landsat data using a process based light use efficiency model. The Hi-GLASS GPP v1 model integrates a detailed map of maize plantations, a crucial C4 crop in China known for its higher photosynthetic efficiency compared to C3 crops. This inclusion helps correct the underestimation of GPP that typically occurs when all croplands are categorized as C3. The Hi-GLASS GPP v1 dataset demonstrates a robust correlation with GPP data derived from eddy covariance towers, thereby enabling a more accurate assessment of terrestrial carbon sequestration across China.

Research on on-orbit relative radiometric calibration method based on solar diffuse reflector hyperspectral camera

Abstract In the original image data obtained by optical remote sensing satellite sensors, there is stripe noise caused by inconsistent probe response, which will seriously affect the application effect and accuracy of the image. The importance of relative radiometric calibration is that it can eliminate the stripe noise in the image, thus improving the quality and clarity of the image. In this paper, a relative radiometric calibration method based on the data of a solar diffuse reflector downloaded from the satellite is proposed. The relative radiation calibration coefficient is calculated by using the least square method by obtaining the calibration image of the on-board diffuse reflector covering all the detectors. To verify the method proposed in this paper, the on-board relative radiometric calibration experiment is carried out by using the on-orbit hyperspectral camera of a terrestrial ecological carbon monitoring satellite, and the calibration effect of the calibration coefficient on the original image is tested, and the relative radiometric calibration accuracy is quantitatively analyzed. The experimental results show that the calibration coefficient can effectively eliminate the band noise of the original hyperspectral image. From the quantitative evaluation, the signal-to-noise ratio index of the corrected hyperspectral image is greater than 200, and the generalized noise index is better than 3%, which achieves a good calibration effect and meets the requirements of high-quality remote sensing image application. It provides a reliable guarantee for quantitative remote sensing applications during the satellite’s on-orbit operation.

The increasing rate of net carbon uptake in Eurasia has been declining since the early 2000s

The analysis of terrestrial ecosystem carbon dynamics, based on scarce carbon flux observations or carbon flux products simulated by reanalysis meteorological data, has great uncertainties. A more accurate understanding of carbon dynamics in Eurasia was achieved by using a carbon flux dataset (CFD) from meteorological stations with quasi-observational characteristics. The growth of net carbon uptake of ecosystems over Eurasia has been decreasing since the early 2000s. The net ecosystem productivity (NEP) increased significantly with the growth rate of 8.7 × 10−3 g C m−2d−1 yr−1 in spring, summer, and autumn (SSA) during 2003–2011 (p < 0.05), which was correlated with the enhanced vegetation index (EVI) and land surface water index (LSWI). This growth was mostly in dry subhumid and humid regions. However, the change in Eurasian NEP was not significant after 2011. Additionally, about 79 % of the stations in Eurasia were in net carbon uptake in SSA, and net carbon emission stations were mainly located in southwestern Eurasia. The intensity of net carbon uptake was highest in the forest, with a mean carbon uptake of 1.73 ± 0.76 g C m−2d−1 in SSA during 2003–2018, and almost all stations demonstrated carbon uptake. During 2011–2018, the number of stations experiencing reduced NEP exceeded those with increased NEP, and this ratio was higher compared to 2003–2011, mainly due to the decrease in EVI and LSWI. The rate of NEP decline at stations with reduced NEP was 5.2 × 10−3 g C m−2d−1 yr−1 faster during 2011–2018 than in the previous period (p < 0.01). Most of the decreases in NEP during 2011–2018 occurred in cropland, grassland and urban land. The spatio-temporal dynamic analysis of Eurasian NEP could provide references for effective carbon management.

Negative Asymmetric Response of Pantropical Gross Primary Productivity to Precipitation Anomalies

AbstractThe carbon sink in pantropical biomes play a crucial role in modulating the inter‐annual variations of global terrestrial carbon balance and is threatened by extreme climate events. However, it has not been carefully examined whether an increase in tropical gross primary productivity (GPP) can compensate the decrease during precipitation anomalies. Using the asymmetry index (AI) and multiple GPP products, we assessed responses of pantropical GPP to precipitation anomalies during 2001–2022. Positive AI indicates that GPP increases are greater than GPP decreases during precipitation anomalies, and vice versa. Our results showed an average negative pantropical GPP asymmetry, that is, GPP decreases exceeded the GPP increases during precipitation anomalies. In addition, a positive AI was found in tropical hyper‐arid and arid regions, which is opposite to the negative AI observed in tropical semi‐arid, sub‐humid, and humid regions. This suggest that tropical GPP asymmetry changes from positive to negative as the moisture increases. Notably, a significant decreasing trend of negative AI was observed over the entire tropical region, indicating that the negative effect of inter‐annual precipitation variations on pantropical vegetation productivity has enhanced. Considering the model predicted increasing climate variability and extremes, the negative impact of precipitation variability on tropical carbon cycle may continue to intensify. Lastly, the divergence in AI estimates among multiple GPP products highlight the need to further improve our understanding of the response of tropical carbon cycle to climate changes, especially for the tropical humid regions.

Estimation of Carbon Stock in Chinese Fir Stands Based on Stacking Ensemble Learning and LSTM Models

Abstract Forest carbon sinks, a critical component of the global carbon cycle, constitute nearly half of the total terrestrial carbon pool. This study employed correlation analysis and factor effect analysis to quantify the influences of various factors on the volume of Chinese fir stands. A novel modeling framework was developed using the stacking ensemble learning and LSTM (LongShort-TermMemory) models. This framework incorporated diverse base learners, including XGBoost, Adaboost, KNN, and DT, which are intelligently ensemble via GBDT as a meta learner. The model was further optimized by comparing activation functions and optimizers, with ReLU selected as the activation function and Adam as the optimizer. Model accuracy was evaluated using RMSE, MAE, and R2 metrics, significantly enhancing its learning ability and generalization performance. The findings are as follows: (1) Stand stocking showed strong positive correlations with depression, age group, average diameter at breast height (ADBH), average tree height (ATH), slope, and elevation. Conversely, it exhibited significant negative correlations with origin, stand density, and slope position. In investigating Chinese fir growth on slopes, no significant growth differences were observed between downslopes and midslopes; however, both differed significantly from upper slopes. (2) The stacking ensemble learning method constructed here surpassed all existing single models in terms of estimation and assessment indices, demonstrating superior comprehensive performance. (3) Among the LSTM models, Adam-LSTM performed the best (R2=0.844), followed by Sigmoid-LSTM (R2=0.656), while the RMSprop-LSTM model performed the worst (R2=0.618). Combined with artificial intelligence methods, our optimized carbon stock estimation model can help to improve the ability of forest land management and provide a theoretical basis for the scientific management of forest areas.

Exponential or Unimodal Relationships Between Nighttime Ecosystem Respiration and Temperature at the Eddy Covariance Flux Tower Sites.

Ecosystem respiration is a key flux in the terrestrial carbon cycle and is affected substantially by temperature. This work analysed the time series data of nighttime net ecosystem exchange of carbon dioxide (NEEnight) from 196 FLUXNET2015 sites to re-evaluate the relationships between NEEnight and temperature. A total of 93 sites (48%) were identified to have a unimodal relationship between NEEnight and temperature. Site-specific apparent optimum temperature parameters were then estimated at these sites. We further assessed the impacts of using exponential or unimodal equations on NEEnight predictions. The predicted NEEnight values at high temperatures were substantially higher from the exponential-type equations (mean: ~200%) than from the unimodal equation (mean: ~30%), compared to the observed NEEnight. This study calls for using a unimodal equation to predict NEEnight (often considered as nighttime ecosystem respiration, ERnight), which could substantially improve the accuracy and reduce uncertainty in ER estimates, in particular under the scenario of global warming.

How is particulate organic carbon transported through the river-fed submarine Congo Canyon to the deep sea?

Abstract. The transfer of carbon from land to the near-coastal ocean is increasingly being recognized in global carbon budgets. However, a more direct transfer of terrestrial organic carbon to the deep sea is comparatively overlooked. Among systems that connect coastal to deep-sea environments, the submarine Congo Canyon is of particular interest since the canyon head starts 30 km into the Congo River estuary, which delivers ∼7 % of the dissolved and particulate organic carbon from the world's rivers. However, sediment and particulate organic carbon transport mechanisms that operate in the Congo Canyon and submarine canyons more globally are poorly constrained compared to rivers because monitoring of deep-sea canyons remains challenging. Using a novel array of acoustic instruments, sediment traps, and cores, this study seeks to understand the hydrodynamic processes that control delivery of particulate organic carbon via the submarine Congo Canyon to the deep sea. We show that particulate organic carbon transport in the canyon axis is modulated by two processes. First, we observe periods where the canyon dynamics are dominated by tides, which induce a background oscillatory flow (speeds of up to 0.15 m s−1) through the water column, keeping muds in suspension, with a net upslope transport direction. Second, fast-moving (up to 8 m s−1) turbidity currents occur for 35 % of the time during monitoring periods and transport particulate organic carbon with mud and sand at an estimated transit flux that is more than 3 to 6 times the flux induced by tides. Organic carbon transported and deposited in the submarine canyon has a similar isotopic composition to organic carbon in the Congo River and in the deep-sea fan at 5 km of water depth. Episodic turbidity currents thus promote efficient transfer of river-derived particulate organic carbon in the Congo submarine fan, leading to some of the highest terrestrial carbon preservation rates observed in marine sediments globally.

Impacts of fire and flooding on sediment carbon storage in a large, forested floodplain

Summary Natural disturbances influence wetland carbon cycling, and fire is a key driver of terrestrial carbon stocks. However, the influence of fire on wetland carbon cycling remains poorly understood. Here, we investigated how prescribed fire and wildfire impact soil carbon storage in a forested floodplain of south-eastern Australia. We sampled four areas within Murray Valley National Park, the world’s largest river red gum (Eucalyptus camaldulensis) stand, and compared soil carbon (C), nitrogen (N) and C:N ratios between control (unburnt in the 50 years prior to sampling), prescribed burn and wildfire-impacted floodplain areas. Mean soil C and N concentrations were 4.7% ± 0.32% and 0.36% ± 0.02%, respectively, and mean C:N ratios were 14.23 ± 0.33. Carbon concentrations and C:N were highest in control areas of the floodplain, while N concentrations were highest at wildfire-impacted areas. However, flood frequency was a stronger driver of soil C than fire disturbance. Soils at more frequently flooded areas had higher C concentrations compared to less frequently flooded areas, suggesting that resilience to C loss through fire could be enhanced through hydrological restoration. We believe this warrants further research as a potential nature-based climate measure. Mean C density data indicate soil C stocks of 9.4 Tg across Barmah-Millewa Forest, highlighting the significant carbon storage value of this ecosystem.

Quantification of biomass availability for wood harvesting and storage in the continental United States with a carbon cycle model

BackgroundWood Harvesting and Storage (WHS) is a form of Biomass Carbon Removal and Storage (BiCRS) that utilizes a combined natural and engineered process to harvest woody biomass and put it into long term storage, most frequently in the form of subterranean burial. This paper aims to quantify the availability of woody biomass for the purposes of WHS in the continental United States using a carbon cycle modeling approach. Using a regional version of the VEGAS terrestrial carbon cycle model at 10 km resolution, this paper calculates the annual woody net primary production in the continental United States. It then applies a series of constraints to exclude woody biomass that is unavailable for WHS. These constraints include fine woody biomass, current land use, current wood utilization, land conservation, and topographical limitations. These results were then split into state by state and regional totals.ResultsIn total, the model projects the continental United States could produce 1,274 MtCO2e (CO2 equivalent) worth of coarse woody biomass annually in a scenario with no anthropogenic land use or constraints. In a scenario with anthropogenic land use and constraints on wood availability, the model projects that 415 MtCO2e of coarse woody biomass is available for WHS annually. This is enough to offset 8.5% of the United States’ 2020 greenhouse gas emissions. Of this potential, 20 MtCO2e is from the Pacific region, 77 MtCO2e is from the Western Interior, 91 MtCO2e is from the Northeast region, and 228 MtCO2e is from the Southeast region.ConclusionThere is enough coarse woody biomass available in the continental United States to make WHS a viable form of carbon removal and storage in the country. There is coarse woody biomass available across the continental United States. All four primary regions analyzed have enough coarse woody biomass available to justify investment in WHS projects.

Inter- and intra-annual variability and climatic responses of ecosystem water use efficiency in a cool-temperate freshwater wetland

Wetland ecosystems play a pivotal role in terrestrial carbon and water cycles, thereby possessing great potential to regulate terrestrial water use efficiency (WUE), which is calculated as the ratio of gross primary productivity (GPP) to evapotranspiration (ET). However, it remains unclear the possible changes in wetland WUE under present and future climate conditions. In this research, WUE variations in a Phragmites australis-dominated freshwater wetland were determined by the eddy covariance method during 2020–2023. Further, we projected future GPP, ET, and WUE under four Representative Concentration Pathway (RCP) scenarios based on five Earth System Models. The 3-year average field observation suggested that the P. australis marsh exhibited high GPP (1149 g C m−2), but consumed large amounts of water through ET (611 mm H2O), resulting in relatively low WUE (1.89 g C mm−1 H2O). During wet years, the studied marsh consumed much more water through evaporation than through transpiration, thus exhibiting lower WUE. Contrarily, large amounts of water were utilized to maintain high primary productivity through transpiration in 2021–2022 dry year, leading to higher WUE. In future scenarios, GPP in the P. australis marsh shows consistently faster uptrends compared to ET from 2020 to 2100, consequently yielding persistent growths of WUE. Future growths of WUE indicate that P. australis marsh tends consume more water for maintaining productivity levels rather than loss via evaporation under future climate conditions, thereby intensifying the carbon–water interaction. Driven by the most rapid growth of environmental drivers, the RCP8.5 scenario shows the fastest increasing trends in GPP, ET, and WUE among four RCP scenarios, whereas the reverse ocurres under RCP2.6 scenario. Overall, our study advocates for more comprehensive research encompassing field observation and model simulation to address the current knowledge gap regarding the response of wetland WUE to contemporary and future climate change.

Increasing evapotranspiration in peatlands from the monsoon regions of East China with the rapid warming during the early Holocene

Peatlands are one of the largest natural terrestrial carbon store, which evolve closely with the hydrological functioning. Evapotranspiration serves as a nexus of the carbon and water cycles in peatlands. Its long-term changes in the geological past are essential to gain a complete understanding of its response to global warming. Here, the evapotranspiration changes in peatlands from the monsoon regions of East China during the significant warming period of ∼ 11.5–10 ka in the Early Holocene are investigated, based on a new leaf wax δD record from the Hani peatland in Northeast China along with the previously reported representative records across monsoonal eastern China. All of the leaf wax δD records exhibit less depleted values during this episode, which follow neither with the changes in precipitation isotopes nor the vegetation compositions. They are thus interpreted as enhanced evapotranspiration. Further comprehensive comparisons based on paleoenvironmental records reveal that evapotranspiration changes are highly sensitive to rising temperatures but are intricately linked with precipitation variations. The strong evapotranspiration appears to be potentially linked to water table drawdown on longer timescales, which further actively interacts with peat-forming plants. Our results suggest that evapotranspiration is expected to increase in peatlands as the climate warms, but its changes might be complicated by accompanying hydrological and vegetational shifts.

ENSO modulates soil organic carbon retention and deposition in the East China Sea

Accurately quantifying the contribution of terrestrial soil organic carbon (SOC) in marine environment is still a challenge. Moreover, reassessing the effect of climate change on SOC variability is necessary, with the increasing variability of El Niño under greenhouse warming. Here, we present new insights from bacterial 3-hydroxy fatty acids (3-OH-FAs) by systematically analyzing the distributions of 3-OH-FA in soils, lake/river sediments and marine sediments, and propose a novel proxy (RIA, the ratio of odd carbon number iso to anteiso 3-OH-FAs) to quantificationally evaluate the contribution of OC from different components. The reliability of the RIA proxy is tested by using a three end-member model and Monte Carlo simulations along a transect from the Yangtze River estuary to the ECS shelf. Then the RIA proxy is applied to a core in the East China Sea covering the past 700 years, and the results reveal that El Niño (La Niña) induced more (less) precipitation and increased (decreased) SOC deposition. This study provides a novel approach for quantifying terrigenous OC inputs and burial in marginal seas and shows the impact of El Niño-Southern Oscillation (ENSO) modes on SOC loss and burial in marginal seas under global warming.

Soil Organic Carbon Dynamics: Drivers of Climate Change-induced Soil Organic Carbon Loss at Various Ecosystems

At roughly 2500 Peta gram (Pg) C, soil organic carbon (SOC) is the biggest carbon store in terrestrial ecosystems and is a crucial contributor to vital soil functions and ecosystem services, such as agricultural soil productivity. SOC stocks are in a dynamic equilibrium between C inputs, primarily from crop residues and organic manures, and C loss owing to decomposition and mineralization of soil organic matter (SOM) under long-term constant land management and environmental circumstances. In addition, the rate of C addition in native ecosystems is governed by the nature and productivity of the local flora, which is mostly influenced by climatic conditions. However, being a complex system, various factors, such as soil management and land-use change influence the soil C pool. Along with temperature gradients from temperate to tropical regions, SOC supplies were shown to be shrinking on a global and regional basis. This reflects the rates of SOM decomposition as a function of temperature, which fluctuates more rapidly than net primary production (NPP). SOM decomposition rates are also influenced by several parameters, including soil temperature and moisture, soil respiration and pH, and soil physical properties including texture and clay mineralogy. Nonetheless, increased temperatures as a result of climate change are thought to be the primary driver of accelerated decomposition, which results in considerable reductions in SOC supplies and sequestration. Furthermore, climatic change contributes to soil deterioration by increasing the mineralization of the SOC pool and causing desertification (irreversible expansion of desert landforms). Similarly, erosion is a degrading process that affects C dynamics and leads to terrestrial carbon loss through the breakdown of structural aggregates, as well as lower productivity in eroding areas due to a lack of soil nutrients. Thus, for an in-depth understanding of worldwide soil C dynamics and to provide support to C management and decision support systems to policymakers and land managers in the face of changing climates, comprehensive research on the influence of multiple climate-induced drivers on soil C is required.

Water controls the divergent responses of terrestrial plant photosynthesis under nitrogen enrichment

Abstract Quantifying leaf photosynthetic response to nitrogen (N) deposition under contrasting water conditions is important for reliably modelling terrestrial carbon and water cycles, a topic that has not been well understood. Here, we analysed 737‐paired observations from 102 publications to assess the response of 11 leaf photosynthesis‐related properties to N addition under different water conditions. Our research includes global experiments, with 19 conducted in the field and 83 in greenhouses. Treatments without water reduction were classified as ‘no water change’, while those with reduced water or precipitation causing physiological drought were categorized as ‘drought’. We found that, compared to the control group, N addition significantly increased leaf photosynthetic rate (Pn; 20.9%), leaf transpiration (E; 8.3%) and stomatal conductance (gs; 14.1%). However, the decrease in Pn (−11.6%), E (−24.7%) and gs (−23.9%) under the combination of N addition and drought indicated that N addition could not offset the negative effects of drought. Furthermore, N addition significantly enhanced water‐use efficiency (WUE) by 19.8% under no water change conditions and by 21.1% under drought conditions. Within plant functional groups, herbaceous species exhibited greater susceptibility to N addition than woody species, especially under drought conditions. The observed patterns of increase in Pn with longer experimental duration and WUE with higher N rate under drought conditions showed that plants would gradually adapt to long‐term water stress in the context of N deposition. Furthermore, our results showed that drought could strengthen the correlations between leaf photosynthetic properties. Lastly, our study demonstrated that N addition and drought significantly impacted leaf nitrogen content and SPAD, respectively, and further affected gs, Pn and WUE. Synthesis. Our results emphasize the crucial role of water conditions in shaping the response of leaf photosynthesis to nitrogen (N) enrichment and also acknowledge the significance of leaf functional traits in regulating the dynamics of leaf photosynthetic processes.

Enhancing the freshness of particulate organic carbon through the regulation of dam and river-lake interactions

The composition and fluxes of organic carbon transported by river systems are important for the terrestrial carbon cycle in terms of source to sink, and the impacts of dam regulation on large rivers are well documented. However, complex river–lake interactions and extreme weather events still hinder a comprehensive understanding of the transformation of riverine carbon within the large river basin. This study investigated particulate organic matter during the 2012 flood in the Changjiang Basin (CJB) and collected suspended particles from the mainstream of the CJB, Dongting and Poyang lakes. The amount, grain size, particulate organic carbon (POC) content, chlorophyll a (Chl-a), and lignin phenols of samples were measured. The results indicate that soil is the primary source of POC in lake-unaffected stations (46.9%–86.9%), while lake-affected stations exhibit significant contributions from phytoplankton (41.4%–78%). Notable alterations in the composition of terrestrial organic carbon occur during its transfer from soil to the river and from the upper to the lower reaches. Comparing the POC characteristics in the Changjiang across various years and hydrological conditions reveals that the characterization of POC in the Changjiang during flooding is mainly influenced by the dams. Another notable finding is that Dongting and Poyang lakes intercepted sediment and transported algae-rich organic matter to the mainstream. This process potentially converts the middle reaches of the Changjiang into a carbon source. River-lake interactions are complex and affected by lake morphology and flooding events. This study enhances our understanding of biogeochemical processes in dam-regulated rivers under extreme weather conditions, and emphasizes the importance of river–lake interactions for the transformation and transportation of riverine organic carbon in large fluvial system.

Forest Canopy Height Estimation Combining Dual-Polarization PolSAR and Spaceborne LiDAR Data

Forest canopy height data are fundamental parameters of forest structure and are critical for understanding terrestrial carbon stock, global carbon cycle dynamics and forest productivity. To address the limitations of retrieving forest canopy height using conventional PolInSAR-based methods, we proposed a method to estimate forest height by combining single-temporal polarimetric synthetic aperture radar (PolSAR) images with sparse spaceborne LiDAR (forest height) measurements. The core idea of our method is that volume scattering energy variations which are linked to forest canopy height occur during radar acquisition. Specifically, our methodology begins by employing a semi-empirical inversion model directly derived from the random volume over ground (RVoG) formulation to establish the relationship between forest canopy height, volume scattering energy and wave extinction. Subsequently, PolSAR decomposition techniques are used to extract canopy volume scattering energy. Additionally, machine learning is employed to generate a spatially continuous extinction coefficient product, utilizing sparse LiDAR samples for assistance. Finally, with the derived inversion model and the resulting model parameters (i.e., volume scattering power and extinction coefficient), forest canopy height can be estimated. The performance of the proposed forest height inversion method is illustrated with L-band NASA/JPL UAVSAR from AfriSAR data conducted over the Gabon Lope National Park and airborne LiDAR data. Compared to high-accuracy airborne LiDAR data, the obtained forest canopy height from the proposed approach exhibited higher accuracy (R2 = 0.92, RMSE = 6.09 m). The results demonstrate the potential and merit of the synergistic combination of PolSAR (volume scattering power) and sparse LiDAR (forest height) measurements for forest height estimation. Additionally, our approach achieves good performance in forest height estimation, with accuracy comparable to that of the multi-baseline PolInSAR-based inversion method (RMSE = 5.80 m), surpassing traditional PolSAR-based methods with an accuracy of 10.86 m. Given the simplicity and efficiency of the proposed method, it has the potential for large-scale forest height estimation applications when only single-temporal dual-polarization acquisitions are available.

Current status and research prospects of terrestrial ecosystem carbon sink in Northeast China.

Increasing the carbon sink capacity of terrestrial ecosystems is a primary strategy to mitigate climate change and achieve the "carbon neutrality" goal. Clarifying the status and future dynamics of carbon sink of terrestrial ecosystems in Northeast China is crucial for achieving "carbon neutrality" as this region is a core contributor to carbon sink in China's terrestrial ecosystems. Here, we systematically summarized current research on carbon sink of terrestrial ecosystems across Northeast China, including the measurements and spatial-temporal patterns of carbon sinks, driving mechanisms of carbon sinks, the assessments of carbon sink potential, and technologies for increasing carbon sequestration. There are substantial uncertainties in quantifying terrestrial ecosystem carbon sink in Northeast China due to differences in data sources and methods, especially for forest carbon sink measurements, ranging from 0.020 to 0.157 Pg C·a-1. Carbon sink function depends on carbon exchange processes across plant-soil-atmosphere interfaces. The key pathways to enhance carbon sequestration in Northeast China under different temporal and spatial scales remains unclear. Improving terrestrial ecosystem quality is the key and core of carbon sequestration and sink enhancement. However, there is an urgent need to develop a multi-ecosystem collaborative carbon sequestration and sink enhancement technology system for the "dual carbon" goal. Future research needs to develop an accurate carbon sink measurement system that integrates multi-source data and multi-scale technologies to accurately assess the function and potential of carbon sink in Northeast China, focus on the multi-scale driving mechanism of carbon sink functions, develop new technical systems for coordinated enhancement of carbon sink for the Northeast terrestrial ecosystems, and carry out demonstrations of carbon sink enhancement technologies. These efforts will provide the scientific and technological supports for achieving the "carbon neutrality" goal.

Effects of simulated warming on content, fractions and chemical structure of soil organic carbon:Progress and prospects.

Soil organic carbon (SOC) represents the largest terrestrial organic carbon pool and plays an important role in mitigating global climate change. Warming can change the stabilization process and the balance of inputs and outputs of the SOC pool, thereby affecting the content, fraction, and chemical structure of SOC. It has become a research hotspot to reveal the mechanisms underlying the effects of warming on SOC stability by analyzing the fraction and molecular structure of C. Here, we reviewed the warming effects on the SOC pool from three aspects, e.g., the content, fraction, and chemical structure of SOC. We also summarized the response of key ecosystem processes to warming, including plant productivity and community composition, microbial activity and community structure. We highlighted the importance of prospective and systematic research focusing on elucidating the microbial mechanism, identifying SOC source and turnover processes, establishing long-term dynamic networked experiments, and mining and optimizing key parameters in C cycle models. This would provide theoretical support for better understanding the change and mechanism of SOC under global warming and predicting the alterations of SOC pool under climate change.

Fertilization and tillage influence on soil organic carbon fractions: A global meta-analysis

Soilorganic carbon(SOC), as the largest terrestrial carbon pool, plays an important role in global carbon cycling, which is significantly impacted by agricultural practices. However, our ability to accurately detect and predict the impacts of fertilization and tillage onSOC dynamicsis still limited. Investigating the effects of fertilization and tillage on different SOC fractions [i.e. mineral-associated organic carbon (MAOC), particulate organic carbon (POC), free POC (frPOC), occluded POC (oPOC), coarse POC (cPOC), and fine POC (fiPOC)]can aid in the understanding of overall SOC accumulation and stabilization. To this end, we evaluated the fertilization and tillage influences on SOC fractions through a global meta-analysis. We also quantified the role of environmental and agronomic factors in modulating these effects. Fertilization increased SOC fractions by mean percent change (MPC)13 %-77 %, while tillage decreased by MPC 4 %-63 %. Among them, cPOC was the most sensitive to fertilization, while frPOC had the highest sensitivity to tillage. MAOC was the least sensitive to both practices. The application of organic fertilizer increased MAOC, SOC, and POC the most (MPC 20 %-77 %), while mineral-organic fertilizer increased frPOC, oPOC, fiPOC, and cPOC the most (MPC 81 %-126 %). Fertilization in alkaline soils with warm and humid (MAT=16–24 °C, MAP>1000 mm) climate could maximally increase SOC contents from various fractions in surface layer (<20 cm depth), particularly when the altitude was 500–1000 m. However, tillage in acidic soils with low temperatures and rainy climate (MAT=8–16 °C, MAP>1000 mm) reduced the contents of SOC fractions the most in deep layer (>40 cm depth), especially at altitudes greater than 2000 m. Whether under fertilization or tillage, POC (occupying 62 %-74 %) consistently contributed more to SOC than MAOC (26 %-38 %). Overall, we suggest that SOC fractions should be prioritized over total SOC when evaluating the effects of site-specific management strategies on carbon sequestration in agricultural lands.