Search Results (73)

The carbon budget of maize croplands has been widely studied across the Chinese Maize Belt. However, the effects of drought on ecosystem-scale carbon fluxes in rain-fed maize croplands remain poorly understood in Southwest China. To address this gap, we conducted long-term, continuous eddy covariance measurements of carbon fluxes at a rain-fed maize field in Guizhou Province from 2022 to 2025. During the maize growing season, the mean net ecosystem exchange (NEE) was −310 ± 21 g C m⁻², with over 50% of the total seasonal NEE occurring in July. Interannual variability in the NEE was primarily driven by prolonged dry spells during the reproductive stage. Maize cropland without straw return acted as a net C source when harvest removals were considered. We therefore recommend promoting straw return practices in the region to strengthen soil carbon sequestration capacity and enhance agroecosystem resilience to drought. And further research is needed to evaluate the role of straw return practices on the carbon budget in the area. Full article

Rubber plantations are a key component of managed forest ecosystems. Quantifying the carbon budget is essential for assessing their carbon sequestration potential and informing sustainable management practices. However, previous studies have focused primarily on individual carbon pools or specific regions, lacking a comprehensive assessment of the carbon budget in rubber plantation ecosystems (RPEs). This study systematically synthesizes the carbon budget of RPEs based on 678 data points extracted from 58 publications. The results indicate that (1) The carbon stock of RPEs (including plant, soil (0–100 cm), and litter carbon stocks) shows an accumulation trend with stand age, increasing from an average of 113.41 ± 21.63 tC ha⁻¹ in young plantations to 252.64 ± 24.61 tC ha⁻¹ in over-mature plantations. (2) RPEs exhibit high photosynthetic capacity and significant carbon sequestration potential during rotation phase, with mean gross primary productivity (GPP) of 22.99 ± 2.14 tC ha⁻¹ yr⁻¹, mean ecosystem respiration (Reco) of 13.92 ± 2.87 tC ha⁻¹ yr⁻¹, and net ecosystem carbon exchange (NEE) of −9.07 ± 1.91 tC ha⁻¹ yr⁻¹. (3) The carbon sequestration capacity of RPEs is influenced by stand age, and carbon sink capacity varies across different planting regions. (4) RPEs act as carbon sinks during rotation phase (−9.07 ± 1.91 tC ha⁻¹ yr⁻¹), with mean carbon storage of 196.13 ± 23.58 tC ha⁻¹ (comprising plant biomass, litterfall, and soil carbon stocks of 70.25 ± 17.47, 2.50 ± 1.30, and 123.38 ± 14.47 tC ha⁻¹, respectively). This synthesis provides representative baseline values for RPEs carbon dynamics, offering a scientific foundation for assessments of carbon sequestration potential and management practices. Full article

Allometric equations are essential tools for estimating sustainable biomass and carbon dynamics in riparian tree species. This study derived and validated log–log transformation regression equations that relate diameter at breast height (DBH) to the dry weight, stem volume, and total biomass of Salix chaenomeloides Kimura across five river systems in Korea (Byeongcheon, Andong, Boseong, Topyeong, and Yeongdong). DBH was significantly correlated with biomass components and whole-tree biomass, with explanatory power ranging from 0.47 (Byeongcheon-root) to 0.99 (Topyeong-stem) (R²). Model evaluation metrics (RMSE, MAE, MPE) indicated high predictive accuracy across sites. Using the derived allometric equations, net primary productivity (NPP) of individual was 9.40 kg·tree⁻¹·yr⁻¹ and 2.45 ton C·ha⁻¹·yr⁻¹ at the stand level, with site-specific variability reflecting environmental differences. Biomass conversion coefficients, expansion factors, and root-to-aboveground biomass ratios were also obtained, with mean values of 0.29 (branches/stem), 0.10 (leaves/stem), and 0.25 (roots/AGB), a wood density of 0.63 g·cm⁻³, and a biomass expansion factor of 1.37. Independently derived NPP estimates based on stem analysis were comparable (9.02 kg tree⁻¹ yr⁻¹ and 2.43 t C ha⁻¹ yr⁻¹ at individual and stand levels, respectively), supporting the robustness of the approach. These findings provide robust, site-calibrated allometric models for S. chaenomeloides, supporting accurate biomass estimation, carbon accounting, and the evaluation of riparian ecosystems in climate change mitigation and restoration contexts. From a sustainability perspective, these results highlight the development of tools for evaluating the carbon budget of riparian vegetation, which are not yet incorporated into the Korean national IPCC report. They also demonstrate progress in carbon budget assessment by integrating both allometry and stem analysis. Full article

Lakes are important sources of greenhouse gases (GHGs), but diurnal flux dynamics across different aquatic vegetation habitats are not well quantified, leading to uncertainties in ecosystem-scale budgets. Here, we used high-frequency monitoring (static chamber coupled with Picarro G2301) to examine diurnal CO₂ and CH₄ fluxes at the water–air interface in three habitats—submerged macrophytes (SM), emergent macrophytes (EM), and non-vegetated control (BC)—in the shallow lake (Changshu Emergency Water Source Lake). During the study period, the lake was a consistent net CO₂ sink (mean flux: −17.53 ± 1.64 μmol·m⁻²·d⁻¹) but a net CH₄ source (mean flux: 5.86 ± 1.70 μmol·m⁻²·d⁻¹). Pronounced diel variability was observed: CO₂ uptake was strongly enhanced during the day, whereas CH₄ emissions peaked at night. Vegetation type exerted a strong control on flux magnitudes, with the SM habitat showing the highest CO₂ uptake and the EM habitat the lowest CH₄ emissions. Generalized linear models (GLMs) revealed that the regulatory effects of key environmental drivers (e.g., temperature, dissolved oxygen, turbidity) on gas fluxes varied significantly by habitat type and diurnal cycle, exhibiting distinct patterns of differentiation. Our findings highlight that accurate assessment of GHG fluxes from shallow lakes—and thus reliable carbon budgeting—must explicitly account for both diurnal cycles and the distinct regulatory roles of aquatic vegetation types. Full article

Urban wetlands on the Qinghai–Tibetan Plateau are increasingly recognized as potentially important components of city-scale carbon budgets; however, their CO₂ flux dynamics and associated environmental drivers remain insufficiently quantified, particularly under high-altitude urban conditions. In this study, we addressed this knowledge gap by conducting continuous eddy covariance observations at Haihu Wetland Park in Xining City, China. Carbon fluxes were monitored throughout 2023 using the Huangshui Park Station flux tower. We quantified the temporal dynamics of gross primary productivity (GPP), ecosystem respiration (Re), and net ecosystem exchange (NEE), and systematically assessed their responses to key environmental drivers across multiple temporal scales. GPP and Re exhibited unimodal seasonal patterns, with substantially higher values during the growing season. NEE showed pronounced diel cycling, with nighttime CO₂ release and daytime uptake, and shifted seasonally between net source and net sink states. At the daily scale (n = 365), Pearson correlations showed that air temperature (T_a), 5 cm soil temperature (T_s5) and volumetric soil water content (SWC) exhibited the strongest associations with the flux components, whereas photosynthetic photon flux density (PPFD) showed moderate associations and precipitation was weak. At the monthly scale (n = 12), Mantel tests further highlighted a dominant thermal control on GPP and Re (T_a and T_s5), whereas precipitation showed additional associations with Re and NEE. Overall, the ecosystem acted as a net CO₂ sink in 2023 (annual NEE = −292.25 g C m⁻² yr⁻¹ under our sign convention), with uptake concentrated in the first eight months of the year. Under the combined effects of multiple environmental factors, plateau urban wetlands functioned as a strong carbon sink, and the results of this study provide a data basis for improving the accuracy of carbon budget estimates for this type of ecosystem. Full article

As a critical agroforestry crop in Southern China, Moso bamboo, maintains regional timber security and bamboo shoot production, with its net ecosystem productivity (NEP) directly determining dry matter accumulation and economic yield. This study integrates 2024 continuous flux observations with XGBoost and SHAP explanations to characterize the subtropical bamboo forest carbon budget and its nonlinear driving mechanisms. The results show a weak carbon sink in 2024 with an annual cumulative NEP of 120 g C m⁻², as high respiration of 860 g C m⁻² limited organic matter conversion by consuming nearly 88% of the 980 g C m⁻² total primary production. The peak production period during May and June was offset by growth stagnation in August, caused by extreme heat and drought. Net radiation served as the primary driver, with a positive contribution threshold of 75.28 W m⁻², whereas precipitation exceeding 1.85 mm or air temperatures over 17.85 °C hindered carbon accumulation through radiation attenuation and metabolic heat loss. Strong radiation–precipitation interactions confirm that water’s impacts on yield are deeply contingent upon radiation backgrounds. These nonlinear regulatory pathways provide a scientific foundation for stabilizing bamboo forest productivity through synergistic water-radiation management and structural optimization during extreme climate events. Full article

While deep fertilization improves crop yields and fertilizer use efficiency, it alters crop growth and soil nutrient/moisture distribution, driving nitrous oxide (N₂O) emissions—a potent greenhouse gas. However, conflicting evidence and the unknown effects of varying fertilizer placement depths in mechanized direct-seeded winter rapeseed fields leave the critical trade-off between productivity and emissions mitigation poorly understood. A 2-year field experiment (2019–2021) was conducted in the Yangtze River basin, China. The static closed chamber technique combined with gas chromatography was utilized to investigate the impacts of fertilizer placement depths (5 cm, 10 cm, and 15 cm, designated as D5, D10, and D15, respectively) on soil N₂O emissions, with a no-fertilization treatment serving as the control. Results demonstrated that N₂O fluxes under all treatments exhibited a rapid decline during the early growth stages of rapeseed, subsequently stabilizing at low levels; these dynamics were partially linked to soil temperature and soil water content (SWC). Specifically, N₂O flux showed a significant but moderate exponential response to soil temperature and a weak quadratic trend with SWC. As fertilization depth increased, the richness and diversity of AOA, AOB, and nirK communities showed a numerical decline (p > 0.05). N₂O emissions under D5 were on average 8.7% higher than D10 (p > 0.05), but were significantly 18.0% higher than D15 (p < 0.05). Yield-scaled N₂O emissions under D10 were reduced by 12.7% and 22.3% relative to D5 and D15, respectively. Compared with D10 and D15, the N₂O emission factor increased by 12.9% and 29.0% under D5, respectively (p < 0.05). The net ecosystem economic budget under D10 was 6.5% and 48.6% greater than that of D5 and D15, respectively. Considering crop yield, production costs, and carbon emission, a fertilizer placement depth of 10 cm is recommended as optimal. These findings offer valuable insights for mitigating N₂O emissions and informing rational fertilization strategies in rapeseed cultivation. Full article

This study was carried out to investigate stand structure, growth dynamics, and carbon fluxes in Pinus rigida plantations of varying ages in South Korea. Field measurements across four mountain sites quantified diameter-class distributions, net primary productivity (NPP), soil respiration, and net ecosystem production (NEP). P. rigida exhibited normally distributed diameter structures in larger classes, whereas Quercus spp. showed reverse J-shaped patterns, indicating active regeneration and ongoing succession toward mixed broadleaved stands. Individual NPP was highest in P. densiflora (4.77 kg yr⁻¹) and P. rigida (4.31 kg yr⁻¹), while Quercus spp. displayed lower growth due to light limitation. Stand-level NPP peaked in 20–40-year-old stands (4.27–4.88 ton C ha⁻¹ yr⁻¹) and declined with age (2.30 ton C ha⁻¹ yr⁻¹). Soil respiration averaged 1.0 ton C ha⁻¹ yr⁻¹ and was strongly temperature dependent (R² = 0.56; Q₁₀ = 2.70). NEP on Mt. Galmi reached 4.38 ton C ha⁻¹ yr⁻¹, demonstrating substantial carbon sink capacity. These findings indicate that aging P. rigida plantations maintain ecosystem-level carbon uptake through successional compensation. Policy efforts should prioritize adaptive thinning, assisted natural regeneration, and long-term monitoring frameworks to accelerate the transition toward climate-resilient mixed forests and to strengthen national forest carbon neutrality strategies. Future research should integrate long-term carbon flux observations, species interaction modeling, and assessments of climate-driven disturbance regimes to refine management pathways for resilient mixed-forest landscapes. Full article

Flood events, intensified by climate change, pose significant threats to both human settlements and ecological systems. This study presents an integrated approach to evaluate flood impacts on ecosystem carbon dynamics using remote sensing and machine learning techniques. The case of the Emilia-Romagna region in Italy is presented, which experienced intense flooding in 2023. To understand flood-induced changes in the short term, we quantified the differences in net primary productivity (NPP) and above-ground biomass (AGB) before and after flood events. Short-term analysis of NPP and AGB revealed substantial localized losses within flood-affected areas. NPP showed a net deficit of 7.0 × 10³ g C yr⁻¹, and AGB a net deficit of 0.5 × 10³ Mg C. While the wider region gained NPP (6.7 × 10⁵ g C yr⁻¹), it suffered a major AGB loss (3.3 × 10⁵ Mg C), indicating widespread biomass decline beyond the flood zone. Long-term ecological assessment using the Remote Sensing Ecological Index (RSEI) showed accelerating degradation, with the “Fair” ecological class shrinking from 90% in 2014 to just over 50% in 2024, and the “Poor” class expanding. “Good” and “Very Good” classes nearly disappeared after 2019. High-hazard flood zones were found to contain 9.0 × 10⁶ Mg C in AGB and 1.1 × 10⁷ Mg C in soil organic carbon, highlighting the vulnerability of carbon stocks. This study underscores the importance of integrating flood modeling with ecosystem monitoring to inform climate-adaptive land management and carbon conservation strategies. It represents a clear, quantifiable carbon loss that should be factored into regional carbon budgets and post-flood ecosystem assessments. Full article

Net ecosystem productivity (NEP) serves as a key indicator for assessing regional carbon sink potential, with its dynamics regulated by nonlinear interactions among multiple factors. However, its driving factors and their coupling processes remain insufficiently characterized. This study investigated terrestrial ecosystems in Yunnan Province, China, to elucidate the drivers of NEP using 14 environmental factors (including topography, meteorology, soil texture, and human activities) and 21 remote sensing features. We developed a research framework based on “Feature Selection–Machine Learning–Mechanism Interpretation.” The results demonstrated that the Variable Selection Using Random Forests (VSURF) feature selection method effectively reduced model complexity. The selected features achieved high estimation accuracy across three machine learning models, with the eXtreme Gradient Boosting Regression (XGBR) model performing optimally (R² = 0.94, RMSE = 76.82 gC/(m²·a), MAE = 55.11 gC/(m²·a)). Interpretation analysis using the SHAP (SHapley Additive exPlanations) method revealed the following: (1) The Enhanced Vegetation Index (EVI), soil pH, solar radiation, air temperature, clay content, precipitation, sand content, and vegetation type were the primary drivers of NEP in Yunnan. Notably, EVI’s importance exceeded that of other factors by approximately 3 to 10 times. (2) Significant interactions existed between soil texture and temperature: Under low-temperature conditions (−5 °C to 12.15 °C), moderate clay content (13–25%) combined with high sand content (40–55%) suppressed NEP. Conversely, within the medium to high temperature range (5 °C to 23.79 °C), high clay content (25–40%) coupled with low sand content (25–43%) enhanced NEP. These findings elucidate the complex driving mechanisms of NEP in subtropical ecosystems, confirming the dominant role of EVI in carbon sequestration and revealing nonlinear regulatory patterns in soil–temperature interactions. This study provides not only a robust “Feature Selection–Machine Learning–Mechanism Interpretation” modeling framework for assessing carbon budgets in mountainous regions but also a scientific basis for formulating regional carbon management policies. Full article

Eucalyptus has become a major plantation crop in southern China, with a carbon sequestration capacity significantly higher than that of other species. However, its long-term carbon sequestration capacity and regional-scale potential remain highly uncertain due to commonly applied short-rotation management practices. The InTEC (Integrated Terrestrial Ecosystem Carbon) model is a process-based biogeochemical model that simulates carbon dynamics in terrestrial ecosystems by integrating physiological processes, environmental drivers, and management practices. In this study, the InTEC model was enhanced with an optimized eucalyptus module (InTEC_euc) and a data assimilation module (InTEC_DA), and driven by multiple remote sensing products (Net Primary Productivity (NPP) and carbon density) to simulate the carbon budgets of eucalyptus plantations from 2003 to 2023. The results indicated notable improvements in the performance of the InTEC_euc model when driven by different datasets: carbon density simulation showed improvements in R² (0.07–0.56), reductions in MAE (5.99–28.51 Mg C ha⁻¹), reductions in RMSE (8.1–31.85 Mg C ha⁻¹), and improvements in rRMSE (12.37–51.82%), excluding NPP_Lin. The carbon density-driven InTEC_euc model outperformed the NPP-driven model, with improvements in R² (0.28), MAE (−8.15 Mg C ha⁻¹), RMSE (−9.43 Mg C ha⁻¹), and rRMSE (−15.34%). When the InTEC_DA model was employed, R² values for carbon density improved by 0–0.03 (excluding ACD_Yan), with MAE reductions between 0.17 and 7.22 Mg C ha⁻¹, RMSE reductions between 0.33 and 12.94 Mg C ha⁻¹ and rRMSE improvements ranging from 0.51 to 20.22%. The carbon density-driven InTEC_DA model enabled the production of high-resolution and accurate carbon budget estimates for eucalyptus plantations from 2003 to 2023, with average NPP, Net Ecosystem Productivity (NEP), and Net Biome Productivity (NBP) values of 17.80, 10.09, and 9.32 Mg C ha⁻¹ yr⁻¹, respectively, offering scientific insights and technical support for the management of eucalyptus plantations in alignment with carbon neutrality targets. Full article

This study explores biochar’s impact on soil fertility, greenhouse gas (GHG) emissions, grain yield, carbon footprint (CF), and net ecosystem carbon budget (NECB) in northwest China’s arid regions. A two-year field experiment tested three biochar rates (15, 30, and 45 t ha⁻¹) against a control. The results showed that biochar significantly reduced overall soil GHG emissions, though the highest rate increased methane emissions. The 30 t ha⁻¹ rate yielded the highest average grain production (13.9 t ha⁻¹), boosted soil organic carbon storage by 76 kg ha⁻¹, and decreased global warming potential (GWP) by 87.8 kg CO₂ ha⁻¹ and GHG emission intensity by 6.74 kg t⁻¹. Biochar also lowered the CF and enhanced the NECB, primarily through increased net primary production and improved soil fertility and crop yields. CO₂ emissions and fertilizer use were major CF contributors, but biochar reduced both the biomass-scaled and yield-scaled CFs. Overall, biochar improved crop yields, NECB, and soil carbon storage while reducing GWP, GHGI, and CF. This study recommends 30 t ha⁻¹ biochar to optimize crop production, enhance carbon balance, and mitigate climate change impacts, highlighting biochar’s potential as a sustainable soil amendment in arid ecosystems. Full article

An earlier ecosystemic study on carbon balance calculations of a Posidonia oceanica system in the Bay of Calvi [Corsica, France], indicated that the bacterial carbon demand [BCD] between May and October [Temp > 18 °C] in the seagrass meadow could not be sustained by net leaf production of P. oceanica and its epiphytes [NPP]. Hence, the system was clearly heterotrophic as only one autotrophic region was recorded, namely the depth range from 0–10 m. Already published data on the production of algal macrophytes and Cymodocea nodosa meadows and their mapping in the Bay of Calvi allowed a re-evaluation of the carbon budgets for each specific depth range. It was shown that C. nodosa could contribute significantly to covering the bacterial carbon demand of the P. oceanica system and that a positive carbon balance could be obtained for the seagrass meadow due to this carbon input when the temperature was higher than 18 °C, even though the depth ranges between 21–30 m and 31–38 m were negative. The overall trend indicates that the system cannot rely on the phytoplanktonic production of the water column, as BCD is higher than phytoplanktonic carbon production. When integrating BCD and net primary production [NPP] of the water column in summer we noticed a lack of some 97.6 to 104.3 tons of carbon which is not covered by the seagrasses leaf production and the algal macrophytes. The obtained data indicate clearly that other carbon carbon-producing compartments like the microphytobenthos, the NPP of rhizome epiphytes, and the detrital carbon import into the Bay of Calvi need to be investigated. Full article

Accurate assessment of net primary production (NPP) can truly reflect the carbon budget balance of the forest ecosystem. In this study, the boreal ecosystem productivity simulation (BEPS) model was used to simulate the NPP of Saihanba mechanized forest farm in 2020, and the influencing factors of NPP were analyzed. The meteorological, forest cover, leaf area index (LAI) and other data required for the model, as well as the data for verifying, were from field surveys or downloaded from different sources. The results showed that: (1) Within the scale of the flux tower, the diurnal variation of NPP reached a maximum in June. The monthly average peak value of latent heat flux was in June, and the sensible heat flux was in March. The temperature of the understory canopy was mostly higher than that of the overstory canopy and air temperature. (2) At the regional scale, the total NPP in the study area in 2020 was 4.25 × 10¹¹ g C a⁻¹, with an average of 564.71 g C m⁻² a⁻¹. The annual average NPP of silver birch (Betula platyphylla) was the largest, and the total NPP of northern Chinese larch (Larix principis-ruprechtii) was the largest. (3) NPP was highly sensitive to LAI. Topographic factors had effects on NPP. The average value of NPP was relatively high in the shady slope and the gentle slope. Full article

Climate change is rapidly progressing as the carbon budget balance is broken due to excessive energy and land use. This study was conducted to find and quantify new carbon sinks to implement the carbon neutrality policy prepared by the international community to solve these problems. To reach this goal, an allometric equation of the willow community, which dominates riparian vegetation, was developed and applied to calculate the net primary productivity of the willow community. Furthermore, after the amount of carbon emitted via soil respiration was quantified, the net ecosystem production was calculated by subtracting the amount of soil respiration from the net primary productivity. In comparisons of the results obtained via this process with those obtained from forest vegetation, the willow community, representative of riparian vegetation, showed a much higher carbon sequestration rate than forest vegetation. Considering these results comprehensively, the willow community could be a new and significant carbon absorption source. In this context, proper river restoration should be realized to contribute to carbon neutrality and secure various ecosystem service functions. Full article