Search Results (648)

Greenhouse gas (GHG) fluxes from forests, including carbon dioxide (CO₂), methane (CH₄), and nitrous oxide (N₂O), are regulated by complex interactions of abiotic and biotic factors. A better understanding of these interactions involving GHGs can help manage forests and enhance their sequestration potential. This review examines how soil properties (moisture, temperature, and pH) and tree species-specific traits (litter quality, carbon storage, and microbial regulation) interactively control GHG dynamics in temperate forest soils, moving beyond a single-factor perspective. This literature review confirms that temperate forest soils are CH₄ sinks and sources of CO₂ and N₂O; however, flux direction and magnitude differ across spatial and temporal scales. CH₄ fluxes show high spatial variability and are sensitive to biogeochemical conditions. While soil temperature and moisture are well studied, their combined effects with site-specific variables such as substrate availability, soil texture, and canopy structure remain underexplored. Tree litter plays a dual role: chemically influencing microbial physiological/functional traits through priming, thereby affecting CO₂ and N₂O, and physically limiting CH₄ diffusion. These mechanisms collectively determine whether soils act as GHG sources or sinks, and future research should account for how litter priming may override their carbon sink function while integrating site-specific factors to improve GHG predictions and forest management. Full article

Mangrove ecosystems play a critical role in global carbon cycling, serving as significant carbon sinks by storing carbon in both aboveground biomass (ACG) and soil carbon stock (SOC). However, the temporal dynamics of ACG and SOC, as well as their spatial variations across different mangrove age stages, remain poorly understood, particularly under the influence of introduced species such as Sonneratia apetala Buch.-Ham. To address these gaps, our study used a long-term series of NDVI from Landsat (from 1990 to 2024) and the mangrove product of China (1990, 2000, 2010, and 2018) to estimate the mangrove age stage ($\mathrm{Stage}\mathrm{I}$ 10–24 years, $\mathrm{Stage}\mathrm{II}$ 24–34 years, and $\mathrm{Stage}\mathrm{III}$ > 34 years). UAV-LiDAR and in-situ surveys were applied to measure mangrove canopy height to calculate ACG and measure the belowground soil carbon stock, respectively. Combined with the mangrove age stage, ACG, and SOC, our results reveal that ACG accumulates rapidly in younger mangroves dominated by Sonneratia apetala, peaking early (<20 years) and then stabilizing as mangroves, indicating that the introduction of Sonneratia apetala changed the increase in ACG with age. In contrast, SOC increases more gradually over time, with only older mangroves (over 30 years) storing significantly higher SOC. Root structure, TN, and TP were sensitive to the SOC. The different root structures (pneumatophore, plank, pop, and knee root) had different SOC results, and the pneumatophore had the lowest SOC. Remote sensing data revealed that the introduction of Sonneratia apetala altered the species composition of younger mangroves, leading to its predominance within these ecosystems. This shift in species composition not only altered the temporal dynamics of aboveground carbon (ACG) but also favored pneumatophore-dominated root structures, which were associated with the lowest soil organic carbon (SOC). Consequently, younger stands may require more time to accumulate SOC to levels comparable to older mangrove forests. These results suggest that restoration targets for vegetation carbon and soil carbon should be set on different timelines, explicitly accounting for stand age, species composition, and root functional types. Full article

Under the context of global climate change and China’s dual carbon strategy (DCS), the impact of land use/land cover change (LULCC) on regional carbon stocks has garnered increasing attention. As a key economic and ecological hub in Southwest China, Chengdu has undergone significant urbanization over the past two decades, and it is necessary to quantitatively assess how shifts in land use affect its carbon stock function. This study integrates multi-period remote sensing data from 2000 to 2020, combining socioeconomic and natural environmental drivers. The PLUS model was employed to simulate land use in 2030 under four scenarios: Natural Development Scenario (NDS), Urban Development Scenario (UDS), Conservation of Cropland Scenario (CPS), and Ecological Protection Scenario (EPS). The InVEST model was then used to calculate changes in carbon stocks and their spatial distribution characteristics. The results indicate the following: (1) From 2000 to 2020, Chengdu’s cropland decreased by 1188.6174 km², while built-up land increased by 1006.5465 km², resulting in a net carbon stock decrease of approximately 3.25 × 10⁶ t, with carbon gains from forest restoration offsetting part of the cropland-to-built-up loss; (2) Under all scenarios, built-up land exhibited an expansion trend, with the UDS showing the most significant increase, reaching 1919.2455 km². In the EPS, the forest increased to 4035.258 km², achieving the largest carbon stock increase of 8.5853 × 10⁶ t. (3) Chengdu’s carbon stock exhibits a spatial distribution pattern characterized by “high in the northwest, low in the center”. High-value areas are concentrated in the ecologically sound Longmen Mountains and Longquan Mountains, while low-value areas are primarily located in urban built-up zones and their peripheries. The study indicates that rationally controlling the expansion of Built-up land, strengthening ecological restoration, and protecting forests can effectively enhance Chengdu’s carbon sink capacity and achieve regional low-carbon and sustainable development. This study aims to address the gap in carbon stock assessments under different development scenarios at the urban scale in Southwest China, and to provide a scientific basis for Chengdu’s regional spatial planning, ecological conservation, low-carbon development, and sustainable land management. Full article

Rising atmospheric CO₂ is expected to fertilize forest photosynthesis; yet, ecosystem-scale observations often reveal muted responses, creating a critical knowledge gap in global climate projections. In this review, we explore this paradox by moving beyond the traditional ‘CO₂ fertilization’ paradigm. We propose an integrated framework that positions elevated CO₂ as a complex modulator whose net effect is determined by a hierarchy of cross-scale constraints. At the plant level, photosynthetic acclimation acts as a universal first brake on the initial biochemical potential. At the ecosystem level, nutrient availability—primarily nitrogen in temperate/boreal systems and phosphorus in the tropics—emerges as the dominant bottleneck limiting long-term productivity gains. Furthermore, interactions with the water cycle, such as increased water-use efficiency, create state-dependent dynamic responses. By synthesizing evidence from pivotal Free-Air CO₂ Enrichment (FACE) experiments, we systematically evaluate these constraining factors. We conclude that accurately predicting the future of the forest carbon sink necessitates a paradigm shift: from single-factor analysis to multi-stressor approaches, and from ecosystem-scale observations to an integrated understanding that links these phenomena to their underlying molecular and genetic mechanisms. This review provides a roadmap for future research and informs more realistic strategies for forest management and climate mitigation in a high-CO₂ world. Full article

Understanding the coordination between regional carbon sequestration and human activities is essential for achieving ecological sustainability and carbon neutrality. This study explored the spatiotemporal evolution, driving mechanisms, and sustainability of net ecosystem productivity (NEP) and human activity intensity (HAI) in the Zhangjiakou–Chengde (ZC) region of northern China from 2000 to 2023. NEP and HAI were integrated through a coupling coordination framework to assess their dynamic balance and relative development. Results show that the coordination between carbon sinks and human activities has improved continuously over the past two decades, shifting from human-dominated imbalance to a more synergistic pattern. Spatially, higher coordination levels were concentrated in forested mountain areas, while agricultural and transitional zones exhibited instability or lagging development. Land use regulation, vegetation recovery, and terrain conditions were identified as the primary factors shaping this pattern, with interaction effects amplifying spatial disparities. Trend analysis suggests that northeastern and eastern regions will likely sustain their positive trajectories, whereas the agro-pastoral transition belt remains vulnerable. These findings deepen understanding of carbon–human interactions in fragile ecosystems and provide scientific evidence for differentiated land management, ecological restoration, and carbon neutrality planning in northern China and similar regions worldwide. Full article

Achieving carbon neutrality requires a comprehensive understanding of terrestrial carbon dynamics, particularly the capacity of ecosystems to act as carbon sinks. This study quantified the temporal and spatial variability of net primary production (NPP) and net ecosystem production (NEP) across South Korea from 2010 to 2024, assessing long-term carbon sink trends and their implications for carbon neutrality and nature-based solutions (NbSs). Using the Carnegie–Ames–Stanford Approach (CASA) model driven by Moderate Resolution Imaging Spectroradiometer (MODIS) satellite data and climate variables, we estimated ecosystem carbon fluxes at high spatial and temporal resolutions. In 2024, national NPP totaled 78.63 Mt CO₂ yr⁻¹, with a mean value of 1956.63 t CO₂ ha⁻¹ yr⁻¹. High productivity was concentrated in upland forests of Gangwon-do, Mt. Jirisan, and northern Gyeongsangbuk-do, where favorable vegetation indices and climatic conditions enhanced photosynthesis. Lower productivity occurred in urbanized areas and intensively farmed lowlands. Heterotrophic respiration (RH) was estimated at 15.35 Mt CO₂ yr⁻¹, with elevated rates in warm, humid lowlands and reduced values in high-elevation forests. The resulting NEP in 2024 was 63.29 Mt CO₂ yr⁻¹, with strong sinks along the Baekdudaegan Range and localized negative NEP pockets in lowlands dominated by urban development or agriculture. From 2010 to 2024, the spatially averaged NPP increased from 1170 to 1543 g C m⁻² yr⁻¹, indicating a general upward trend in ecosystem productivity. However, interannual variability was influenced by climatic fluctuations, land-cover changes, and data masking adjustments. These findings provide critical insights into the spatiotemporal dynamics of terrestrial carbon sinks in South Korea, offering essential baseline data for national greenhouse gas inventories and the strategic integration of NbSs into carbon-neutral policies. Full article

Terrestrial carbon sink has exhibited significant interannual variability (IAV) over the past five decades. However, the dominant regions and factors controlling the IAV of global land carbon sink remain controversial. Using six TRENDY models, we quantified regional contributions to the IAV of global land carbon sink from 1981 to 2017 and identified the dominant factors across different ecosystems and the globe. Results indicated that forests and savannas contributed most to global net biome productivity (NBP) IAV (27% and 29%, respectively). Further analyses revealed that root zone soil moisture (RZSM) and vapor pressure deficit (VPD) played a dominant role at the local and global scales, particularly in regions between 20° S and 40° S and 40° N–60° N. Across different ecosystems, the dominant drivers of NBP IAV varied greatly. More precisely, in tropical forests, NBP IAV was dominated by temperature variability, whereas in extra-tropical forests and croplands, VPD variability played a dominant role. Furthermore, in shrublands and grasslands, RZSM and VPD have comparable effects on NBP anomalies. Our findings provided robust evidence for an important joint control of RZSM and VPD in the IAV of land carbon sink, and reduced some of the uncertainty around the dominant drivers of temporal variability in NBP. Full article

Aboveground biomass (AGB) is a key indicator of forest structure and carbon sequestration, yet its dynamics under concurrent anthropogenic disturbances remain poorly understood. This study investigates the spatiotemporal dynamics and driving mechanisms of AGB in the Jianfengling tropical lowland rainforest (JFLTLR) within Hainan Tropical Rainforest National Park (NRHTR) from 2015 to 2023. Six machine learning models—Extreme Gradient Boosting (XGBoost), Gradient Boosting Machine (GBM), Support Vector Machine (SVM), k-Nearest Neighbors (KNN), Decision Tree (DT), and Random Forest (RF)—were evaluated, with RF achieving the highest accuracy (R² = 0.83). Therefore, RF was employed to generate high-resolution annual AGB maps based on Sentinel-1/2 data fusion, field surveys, socio-economic indicators, and topographic variables. Human pressure was quantified using the Human Influence Index (HII). Threshold analysis revealed a critical breakpoint at ΔHII ≈ 0.1712: below this level, AGB remained relatively stable, whereas beyond it, biomass declined sharply (≈−2.65 mg·ha⁻¹ per 0.01 ΔHII). Partial least squares structural equation modeling (PLS-SEM) identified plantation forests as the dominant negative driver, while GDP (−0.91) and road (−1.04) exerted strong indirect effects through HII, peaking in 2019 before weakening under ecological restoration policies. Spatially, biomass remained resilient within central core zones but declined in peripheral regions associated with road expansion. Temporally, AGB exhibited a trajectory of decline, partial recovery, and renewed loss, resulting in a net reduction of ≈ 0.0393 × 10⁶ mg. These findings underscore the urgent need for a “core stabilization–peripheral containment” strategy integrating disturbance early-warning systems, transportation planning that minimizes impacts on high-AGB corridors, and the strengthening of ecological corridors to maintain carbon-sink capacity and guide differentiated rainforest conservation. Full article

Forest and grassland fire behavior prediction is increasingly critical under climate change, as rising fire frequency and intensity threaten ecosystems and human societies worldwide. This paper reviews the status and future development trends of wildfire behavior modeling and prediction technologies. It provides a comprehensive overview of the evolution of models from empirical to physical and then to data-driven approaches, emphasizing the integration of multidisciplinary techniques such as machine learning and deep learning. While conventional physical models offer mechanistic insights, recent advancements in data-driven models have enabled the analysis of big data to uncover intricate nonlinear relationships. We underscore the necessity of integrating multiple models via complementary, weighted fusion and hybrid methods to bolster robustness across diverse situations. Ultimately, we advocate for the creation of intelligent forecast systems that leverage data from space, air and ground sources to provide multifaceted fire behavior predictions in regions and globally. Such systems would more effectively transform fire management from a reactive approach to a proactive strategy, thereby safeguarding global forest carbon sinks and promoting sustainable development in the years to come. By offering forward-looking insights and highlighting the importance of multidisciplinary approaches, this review serves as a valuable resource for researchers, practitioners, and policymakers, supporting informed decision-making and fostering interdisciplinary collaboration. Full article

Energy consumption and environmental pollution pose significant challenges to sustainable development. This study develops a comprehensive coupled framework model that advances the quantitative integration of carbon (C), nitrogen (N), and phosphorus (P) cycles driven by multiple anthropogenic pollution sources. This paper used Panjin city as a case study to analyze the dynamic changes and interconnections among C, N, and P. Results indicated that net anthropogenic carbon inputs (NAI_C) increased by 33% from 2016–2020, while net anthropogenic nitrogen inputs (NAI_N) and net anthropogenic phosphorus inputs (NAI_P) decreased by 14% and 28%, respectively. The primary driver of NAI_C was energy consumption, while wetlands were the dominant carbon sequestration sink. Agricultural production was identified as the primary source of NAI_N and NAI_P, and approximately 4.5% of NAI_N and 2.9% of NAI_P were discharged into receiving water bodies. We demonstrate that human activities and natural processes exhibit dual attributes, producing positive and negative environmental effects. The increase in carbon emissions drives economic growth and industrial restructuring; however, the enhanced economic capacity also strengthens the ability to mitigate pollution through environmental protection measures. Similarly, natural ecosystems, including forests and grasslands, contribute to carbon sequestration and the release of non-point source pollution. The comprehensive environmental impact assessment of C, N, and P revealed that the comprehensive environmental index for Panjin city exhibited an improved trend. The factors of energy structure, energy efficiency, and economic scale promoted NAI_C growth, with the economic scale factor alone accounting for 93% of the total increment. Environmental efficiency factor and population size factor were the primary drivers in reducing NAI_N and NAI_P discharges into the receiving water bodies. We propose a novel management model, ecological restoration, clean energy utilization, resource recycling, and pollution source reduction to achieve systemic governance of C, N, and P inputs. Full article

Against the background of global warming, the carbon emission of cities accounts for more than 70%, and its carbon sink increase and emission reduction have become the research focus. The water bodies and green spaces in the urban blue–green space have a synergistic carbon sequestration effect, but current research pays less attention to the small and medium scales. Therefore, taking the waterfront green space on both sides of Qinhuai New River in Nanjing as the research object, this paper explores the impact of the synergy between water and greenery on the carbon sequestration efficiency of green space. The study first estimates the carbon sequestration efficiency of green spaces by integrating measured Leaf Area Index (LAI) data with the mean carbon sequestration rate per unit leaf area for typical tree and shrub species. It then constructs a set of water–green spatial relationship indicators and applies a random forest regression model to identify the key factors influencing carbon sequestration efficiency. Finally, multiple scenario models are developed to simulate the effects of green spaces on CO₂ reduction, thereby validating the roles of the identified influencing factors. The study found that waterfront green spaces tended to exhibit slightly higher carbon sequestration efficiency compared with non-waterfront green spaces. The proportion of 10 m forest land area and the proportion of 10–20 m forest land area had a higher impact on the carbon sequestration capacity of waterfront green space; that is, the closer the distance between the green space and the water, the better the carbon sequestration capacity. In order to improve the carbon sequestration efficiency of the waterfront area, the green space should be arranged along the water bank as much as possible, the depth of the green space should be increased, the proportion of the forest land area should be increased, the arbor and shrub should be planted evenly, and ribbon planting should be avoided. The study confirmed the synergistic effect of water and greenery in carbon sequestration benefits, providing data support and theoretical reference for the optimization and renewal of urban waterfront green space, and contributing to the realization of urban waterfront green space planning, design, and renewal with the goal of a high carbon sink. Full article

Soil erosion is an increasingly severe problem and a global focus. As one of the countries facing relatively serious soil erosion, China encounters significant ecological challenges. This study focuses on the carbon sink benefits of comprehensive soil and water conservation management in the red soil erosion area of southern China, conducting an in-depth analysis using the Ziyang small watershed in Shangyou County, Jiangxi Province, as a typical case. Research methods involved constructing an integrated monitoring approach combining basic data, measured data, and remote sensing data. Changes in soil and vegetation carbon storage in the Ziyang small watershed across different years were determined by establishing a baseline scenario and applying inverse distance spatial interpolation, quadrat calculation, feature extraction, and screening. The results indicate that from 2002 to 2023, after 21 years of continuous implementation of various soil and water conservation measures under comprehensive watershed management, the carbon storage of the Ziyang small watershed increased significantly, yielding a net carbon sink of 54,537.28 tC. Tending and Management of Coniferous and Broad-leaved Mixed Forest, Low-efficiency Forest Improvement, and Thinning and Tending contributed substantially to the carbon sink, accounting for 72.72% collectively. Furthermore, the carbon sink capacity of the small watershed exhibited spatial variation influenced by management measures: areas with high carbon density were primarily concentrated within zones of Tending and Management of Coniferous and Broad-leaved Mixed Forest, while areas with low carbon density were mainly found within zones of Bamboo Forest Tending and Reclamation. The increase in watershed carbon storage was attributed to contributions from both vegetation and soil carbon pools. Comprehensive management of soil erosion demonstrates a significant carbon accumulation effect. The annual growth rate of vegetation carbon storage was higher than that of soil carbon storage, yet the proportion of soil carbon storage increased yearly. This study provides a theoretical basis and data foundation for the comprehensive management of soil and water conservation in small watersheds in the southern red soil erosion region of China and can offer technical and methodological support for other soil and water conservation carbon sink projects in this area. Full article

Rapid urbanization and climate change demand innovative green solutions in city planning. Tiny forests—small artificial wooded areas in urban or peri-urban settings—are gaining attention. This paper explores the use of the Miyawaki method to establish such forests in Italy, highlighting their environmental and educational benefits. The study defines micro-forests (100–200 m²) and mini-forests (200–2000 m²) per legislative standards and describes the qualitative features needed for self-sustaining ecosystems. Mimicking natural succession, these forests support biodiversity, reduce urban heat, improve air quality, and act as carbon sinks. Beyond ecological functions, they offer strong pedagogical value, fostering naturalistic intelligence and reconnecting people with natural rhythms and ecosystems. Case studies from Vigevano and Rome show practical applications, demonstrating how tiny forests can enhance sustainability, community well-being, and environmental awareness in cities. Full article

Soil organic carbon (SOC) constitutes the largest terrestrial carbon pool and plays a crucial role in climate regulation, soil fertility, and ecosystem functioning. Understanding its spatiotemporal dynamics is particularly important in semi-arid regions, where fragile environments and extensive ecological restoration may alter carbon cycling. The Loess Plateau, the world’s largest loess accumulation area with a history of severe erosion and large-scale vegetation restoration, provides a natural laboratory for examining how environmental gradients influence SOC storage over time. This study used a random forest model with multi-source environmental data to quantify soil organic carbon density (SOCD) dynamics in the 0–100 cm soil layer of the Loess Plateau from 2005 to 2020. SOCD showed strong spatial heterogeneity, decreasing from the humid southeast to the arid northwest. Over the 15-year period, total SOC storage increased from 4.84 to 5.23 Pg C (a 7.9% rise), while the annual sequestration rate declined from 0.046 to 0.020 kg·m⁻²·yr⁻¹, indicating that the regional carbon sink may be approaching saturation after two decades of restoration. Among soil types, Cambisols were the largest carbon pool, accounting for over 44% of total SOC storage. Vegetation productivity emerged as the dominant driver of SOC variability, with clay content as a secondary factor. These results indicate that although ecological restoration has substantially enhanced SOC storage, its marginal benefits are diminishing. Understanding the spatial and temporal patterns of SOC and their environmental drivers provides essential insights for evaluating long-term carbon sequestration potential and informing future land management strategies. Broader generalization requires multi-regional comparisons, long-term monitoring, and deeper soil investigations to capture ecosystem-scale carbon dynamics fully. Full article

Forest aboveground biomass (AGB) is a key component of terrestrial carbon storage, essential for understanding the carbon cycle and evaluating carbon sink potential. However, estimating long-term AGB in tropical forests and detecting its spatial and temporal trends remain challenging due to observational gaps and methodological constraints. Here, we integrate GEDI L4B gridded biomass data with features from MODIS, PALSAR/PALSAR-2, SRTM, and climate datasets, and apply the AutoGluon ensemble learning framework to develop AGB retrieval models. We generated annual AGB maps at 1 km resolution for Borneo’s forests from 2007 to 2023, achieving high predictive accuracy (R² = 0.92, RMSE = 32.84 Mg/ha, rRMSE = 21.06%). Residuals were generally balanced and close to a symmetric distribution, indicating no strong bias within the moderate biomass range (50–350 Mg/ha). However, in very high-biomass stands, the model tended to underestimate AGB, reflecting saturation effects that persist despite clear improvements over existing products. Estimated mean AGB values ranged from 180.52 to 214.09 Mg/ha, with total AGB varying between 13.05 and 14.10 Pg. Trend analysis using Sen’s slope and the Mann–Kendall test revealed significant AGB trends in 31.31% of forested areas, with 68.76% showing increases. This study offers a robust and scalable framework for continuous tropical forest carbon monitoring, providing critical support for carbon accounting, forest management, and policy-making. Full article