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Search Results (1,113)

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Keywords = forest carbon sequestrations

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32 pages, 2632 KiB  
Article
Spatial Heterogeneity in Carbon Pools of Young Betula sp. Stands on Former Arable Lands in the South of the Moscow Region
by Gulfina G. Frolova, Pavel V. Frolov, Vladimir N. Shanin and Irina V. Priputina
Plants 2025, 14(15), 2401; https://doi.org/10.3390/plants14152401 (registering DOI) - 3 Aug 2025
Abstract
This study investigates the spatial heterogeneity of carbon pools in young Betula sp. stands on former arable lands in the southern Moscow region, Russia. The findings could be useful for the current estimates and predictions of the carbon balance in such forest ecosystems. [...] Read more.
This study investigates the spatial heterogeneity of carbon pools in young Betula sp. stands on former arable lands in the southern Moscow region, Russia. The findings could be useful for the current estimates and predictions of the carbon balance in such forest ecosystems. The research focuses on understanding the interactions between plant cover and the environment, i.e., how environmental factors such as stand density, tree diameter and height, light conditions, and soil properties affect ecosystem carbon pools. We also studied how heterogeneity in edaphic conditions affects the formation of plant cover, particularly tree regeneration and the development of ground layer vegetation. Field measurements were conducted on a permanent 50 × 50 m sampling plot divided into 5 × 5 m subplots, in order to capture variability in vegetation and soil characteristics. Key findings reveal significant differences in carbon stocks across subplots with varying stand densities and light conditions. This highlights the role of the spatial heterogeneity of soil properties and vegetation cover in carbon sequestration. The study demonstrates the feasibility of indirect estimation of carbon stocks using stand parameters (density, height, and diameter), with results that closely match direct measurements. The total ecosystem carbon stock was estimated at 80.47 t ha−1, with the soil contribution exceeding that of living biomass and dead organic matter. This research emphasizes the importance of accounting for spatial heterogeneity in carbon assessments of post-agricultural ecosystems, providing a methodological framework for future studies. Full article
(This article belongs to the Section Plant–Soil Interactions)
12 pages, 2259 KiB  
Article
Soil C:N:P Stoichiometry in Two Contrasting Urban Forests in the Guangzhou Metropolis: Differences and Related Dominates
by Yongmei Xiong, Zhiqi Li, Shiyuan Meng and Jianmin Xu
Forests 2025, 16(8), 1268; https://doi.org/10.3390/f16081268 (registering DOI) - 3 Aug 2025
Abstract
Carbon (C) sequestration and nitrogen (N) and phosphorus (P) accumulation in urban forest green spaces are significant for global climate regulation and alleviating nutrient pollution. However, the effects of management and conservation practices across different urban forest vegetation types on soil C, N, [...] Read more.
Carbon (C) sequestration and nitrogen (N) and phosphorus (P) accumulation in urban forest green spaces are significant for global climate regulation and alleviating nutrient pollution. However, the effects of management and conservation practices across different urban forest vegetation types on soil C, N, and P contents and stoichiometric ratios remain largely unexplored. We selected forest soils from Guangzhou, a major Metropolis in China, as our study area. Soil samples were collected from two urban secondary forests that naturally regenerated after disturbance (108 samples) and six urban forest parks primarily composed of artificially planted woody plant communities (72 samples). We employed mixed linear models and variance partitioning to analyze and compare soil C, N, and P contents and their stoichiometry and its main driving factors beneath suburban forests and urban park vegetation. These results exhibited that soil pH and bulk density in urban parks were higher than those in suburban forests, whereas soil water content, maximum storage capacity, and capillary porosity were higher in urban forests than in urban parks. Soil C, N, and P contents and their stoichiometry (except for N:P ratio) were significantly higher in suburban forests than in urban parks. Multiple analyzes showed that soil pH had the most pronounced negative influence on soil C, N, C:N, C:P, and N:P, but the strongest positive influence on soil P in urban parks. Soil water content had the strongest positive effect on soil C, N, P, C:N, and C:P, while soil N:P was primarily influenced by the positive effect of soil non-capillary porosity in suburban forests. Overall, our study emphasizes that suburban forests outperform urban parks in terms of carbon and nutrient accumulation, and urban green space management should focus particularly on the impact of soil pH and moisture content on soil C, N, and P contents and their stoichiometry. Full article
(This article belongs to the Special Issue Carbon, Nitrogen, and Phosphorus Storage and Cycling in Forest Soil)
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17 pages, 3193 KiB  
Article
Effects of Nitrogen and Phosphorus Additions on the Stability of Soil Carbon Fractions in Subtropical Castanopsis sclerophylla Forests
by Yunze Dai, Xiaoniu Xu and LeVan Cuong
Forests 2025, 16(8), 1264; https://doi.org/10.3390/f16081264 (registering DOI) - 2 Aug 2025
Abstract
Soil organic carbon (SOC) pool plays an extremely important role in regulating the global carbon (C) cycle and climate change. Atmospheric nitrogen (N) and phosphorus (P) deposition caused by human activities has significant impacts on soil C sequestration potential of terrestrial ecosystem. To [...] Read more.
Soil organic carbon (SOC) pool plays an extremely important role in regulating the global carbon (C) cycle and climate change. Atmospheric nitrogen (N) and phosphorus (P) deposition caused by human activities has significant impacts on soil C sequestration potential of terrestrial ecosystem. To investigate the effects of N and P deposition on soil C sequestration and C-N coupling relationship in broad-leaved evergreen forests, a 6-year field nutrient regulation experiment was implemented in subtropical Castanopsis sclerophylla forests with four different N and P additions: N addition (100 kg N·hm−2·year−1), N + P (100 kg N·hm−2·year−1 + 50 kg P·hm−2·year−1), P addition (50 kg P·hm−2·year−1), and CK (0 kg N·hm−2·year−1). The changes in the C and N contents and stable isotope distributions (δ13C and δ15N) of different soil organic fractions were examined. The results showed that the SOC and total nitrogen (STN) (p > 0.05) increased with N addition, while SOC significantly decreased with P addition (p < 0.05), and N + P treatment has low effect on SOC, STN (p > 0.05). By density grouping, it was found that N addition significantly increased light fraction C and N (LFOC, LFN), significantly decreased the light fraction C to N ratio (LFOC/N) (p < 0.05), and increased heavy fraction C and N (HFOC, HFN) accumulation and light fraction to total organic C ratio (LFOC/SOC, p > 0.05). Contrary to N addition, P addition was detrimental to the accumulation of LFOC, LFN and reduced LFOC/SOC. It was found that different reactive oxidized carbon (ROC) increased under N addition but ROC/SOC did not change, while N + P and P treatments increased ROC/SOC, resulting in a decrease in SOC chemical stability. Stable isotope analysis showed that N addition promoted the accumulation of new soil organic matter, whereas P addition enhanced the transformation and utilization of C and N from pre-existing organic matter. Additionally, N addition indirectly increased LFOC by significantly decreasing pH; significantly contributed to LFOC and ROC by increasing STN accumulation promoted by NO3-N and NH4+-N; and decreased light fraction δ13C by significantly increasing dissolved organic C (p < 0.05). P addition had directly significant negative effect on LFOC and SOC (p < 0.05). In conclusion, six-year N deposition enhances soil C and N sequestration while the P enrichment reduces the content of soil C, N fractions and stability in Castanopsis sclerophylla forests. The results provide a scientific basis for predicting the soil C sink function of evergreen broad-leaved forest ecosystem under the background of future climate change. Full article
(This article belongs to the Section Forest Soil)
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20 pages, 1205 KiB  
Review
Patterns in Root Phenology of Woody Plants Across Climate Regions: Drivers, Constraints, and Ecosystem Implications
by Qiwen Guo, Boris Rewald, Hans Sandén and Douglas L. Godbold
Forests 2025, 16(8), 1257; https://doi.org/10.3390/f16081257 (registering DOI) - 1 Aug 2025
Viewed by 29
Abstract
Root phenology significantly influences ecosystem processes yet remains poorly characterized across biomes. This study synthesized data from 59 studies spanning Arctic to tropical ecosystems to identify woody plants root phenological patterns and their environmental drivers. The analysis revealed distinct climate-specific patterns. Arctic regions [...] Read more.
Root phenology significantly influences ecosystem processes yet remains poorly characterized across biomes. This study synthesized data from 59 studies spanning Arctic to tropical ecosystems to identify woody plants root phenological patterns and their environmental drivers. The analysis revealed distinct climate-specific patterns. Arctic regions had a short growing season with remarkably low temperature threshold for initiation of root growth (0.5–1 °C). Temperate forests displayed pronounced spring-summer growth patterns with root growth initiation occurring at 1–9 °C. Mediterranean ecosystems showed bimodal patterns optimized around moisture availability, and tropical regions demonstrate seasonality primarily driven by precipitation. Root-shoot coordination varies predictably across biomes, with humid continental ecosystems showing the highest synchronous above- and belowground activity (57%), temperate regions exhibiting leaf-before-root emergence (55%), and Mediterranean regions consistently showing root-before-leaf patterns (100%). Winter root growth is more widespread than previously recognized (35% of studies), primarily in tropical and Mediterranean regions. Temperature thresholds for phenological transitions vary with climate region, suggesting adaptations to environmental conditions. These findings provide a critical, region-specific framework for improving models of terrestrial ecosystem responses to climate change. While our synthesis clarifies distinct phenological strategies, its conclusions are drawn from data focused primarily on Northern Hemisphere woody plants, highlighting significant geographic gaps in our current understanding. Bridging these knowledge gaps is essential for accurately forecasting how belowground dynamics will influence global carbon sequestration, nutrient cycling, and ecosystem resilience under changing climatic regimes. Full article
(This article belongs to the Section Forest Ecophysiology and Biology)
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20 pages, 2782 KiB  
Article
Urban Forest Fragmentation Reshapes Soil Microbiome–Carbon Dynamics
by Melinda Haydee Kovacs, Nguyen Khoi Nghia and Emoke Dalma Kovacs
Diversity 2025, 17(8), 545; https://doi.org/10.3390/d17080545 (registering DOI) - 1 Aug 2025
Viewed by 25
Abstract
Urban expansion fragments once-contiguous forest patches, generating pronounced edge gradients that modulate soil physicochemical properties and biodiversity. We quantified how fragmentation reshaped the soil microbiome continuum and its implications for soil carbon storage in a temperate urban mixed deciduous forest. A total of [...] Read more.
Urban expansion fragments once-contiguous forest patches, generating pronounced edge gradients that modulate soil physicochemical properties and biodiversity. We quantified how fragmentation reshaped the soil microbiome continuum and its implications for soil carbon storage in a temperate urban mixed deciduous forest. A total of 18 plots were considered in this study, with six plots for each fragment type. Intact interior forest (F), internal forest path fragment (IF), and external forest path fragment (EF) soils were sampled at 0–15, 15–30, and 30–45 cm depths and profiled through phospholipid-derived fatty acid (PLFA) chemotyping and amino sugar proxies for living microbiome and microbial-derived necromass assessment, respectively. Carbon fractionation was performed through the chemical oxidation method. Diversity indices (Shannon–Wiener, Pielou evenness, Margalef richness, and Simpson dominance) were calculated based on the determined fatty acids derived from the phospholipid fraction. The microbial biomass ranged from 85.1 to 214.6 nmol g−1 dry soil, with the surface layers of F exhibiting the highest values (p < 0.01). Shannon diversity declined systematically from F > IF > EF. The microbial necromass varied from 11.3 to 23.2 g⋅kg−1. Fragmentation intensified the stratification of carbon pools, with organic carbon decreasing by approximately 14% from F to EF. Our results show that EFs possess a declining microbiome continuum that weakens their carbon sequestration capacity in urban forests. Full article
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21 pages, 5062 KiB  
Article
Forest Management Effects on Breeding Bird Communities in Apennine Beech Stands
by Guglielmo Londi, Francesco Parisi, Elia Vangi, Giovanni D’Amico and Davide Travaglini
Ecologies 2025, 6(3), 54; https://doi.org/10.3390/ecologies6030054 (registering DOI) - 1 Aug 2025
Viewed by 31
Abstract
Beech forests in the Italian peninsula are actively managed and they also support a high level of biodiversity. Hence, biodiversity conservation can be synergistic with timber production and carbon sequestration, enhancing the overall economic benefits of forest management. This study aimed to evaluate [...] Read more.
Beech forests in the Italian peninsula are actively managed and they also support a high level of biodiversity. Hence, biodiversity conservation can be synergistic with timber production and carbon sequestration, enhancing the overall economic benefits of forest management. This study aimed to evaluate the effect of forest management regimes on bird communities in the Italian Peninsula during 2022 through audio recordings. We studied the structure, composition, and specialization of the breeding bird community in four managed beech stands (three even-aged beech stands aged 20, 60, and 100 years old, managed by a uniform shelterwood system; one uneven-aged stand, managed by a single-tree selection system) and one uneven-aged, unmanaged beech stand in the northern Apennines (Tuscany region, Italy). Between April and June 2022, data were collected through four 1-hour audio recording sessions per site, analyzing 5 min sequences. The unmanaged stand hosted a richer (a higher number of species, p < 0.001) and more specialized (a higher number of cavity-nesting species, p < 0.001; higher Woodland Bird Community Index (WBCI) values, p < 0.001; and eight characteristic species, including at least four highly specialized ones) bird community, compared to all the managed forests; moreover, the latter were homogeneous (similar to each other). Our study suggests that the unmanaged beech forests should be a priority option for conservation, while in terms of the managed beech forests, greater attention should be paid to defining the thresholds for snags, deadwood, and large trees to be retained to enhance their biodiversity value. Studies in additional sites, conducted over more years and including multi-taxon communities, are recommended for a deeper understanding and generalizable results. Full article
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20 pages, 2327 KiB  
Article
From Climate Liability to Market Opportunity: Valuing Carbon Sequestration and Storage Services in the Forest-Based Sector
by Attila Borovics, Éva Király, Péter Kottek, Gábor Illés and Endre Schiberna
Forests 2025, 16(8), 1251; https://doi.org/10.3390/f16081251 - 1 Aug 2025
Viewed by 52
Abstract
Ecosystem services—the benefits humans derive from nature—are foundational to environmental sustainability and economic well-being, with carbon sequestration and storage standing out as critical regulating services in the fight against climate change. This study presents a comprehensive financial valuation of the carbon sequestration, storage [...] Read more.
Ecosystem services—the benefits humans derive from nature—are foundational to environmental sustainability and economic well-being, with carbon sequestration and storage standing out as critical regulating services in the fight against climate change. This study presents a comprehensive financial valuation of the carbon sequestration, storage and product substitution ecosystem services provided by the Hungarian forest-based sector. Using a multi-scenario framework, four complementary valuation concepts are assessed: total carbon storage (biomass, soil, and harvested wood products), annual net sequestration, emissions avoided through material and energy substitution, and marketable carbon value under voluntary carbon market (VCM) and EU Carbon Removal Certification Framework (CRCF) mechanisms. Data sources include the National Forestry Database, the Hungarian Greenhouse Gas Inventory, and national estimates on substitution effects and soil carbon stocks. The total carbon stock of Hungarian forests is estimated at 1289 million tons of CO2 eq, corresponding to a theoretical climate liability value of over EUR 64 billion. Annual sequestration is valued at approximately 380 million EUR/year, while avoided emissions contribute an additional 453 million EUR/year in mitigation benefits. A comparative analysis of two mutually exclusive crediting strategies—improved forest management projects (IFMs) avoiding final harvesting versus long-term carbon storage through the use of harvested wood products—reveals that intensified harvesting for durable wood use offers higher revenue potential (up to 90 million EUR/year) than non-harvesting IFM scenarios. These findings highlight the dual role of forests as both carbon sinks and sources of climate-smart materials and call for policy frameworks that integrate substitution benefits and long-term storage opportunities in support of effective climate and bioeconomy strategies. Full article
(This article belongs to the Section Forest Economics, Policy, and Social Science)
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12 pages, 1886 KiB  
Article
Methodology-Dependent Reversals in Root Decomposition: Divergent Regulation by Forest Gap and Root Order in Pinus massoniana
by Haifeng Yin, Jie Zeng, Size Liu, Yu Su, Anwei Yu and Xianwei Li
Plants 2025, 14(15), 2365; https://doi.org/10.3390/plants14152365 (registering DOI) - 1 Aug 2025
Viewed by 134
Abstract
Understanding root decomposition dynamics is essential to address declining carbon sequestration and nutrient imbalances in monoculture plantations. This study elucidates how forest gaps regulate Pinus massoniana root decomposition through comparative methodological analysis, providing theoretical foundations for near-natural forest management and carbon–nitrogen cycle optimization [...] Read more.
Understanding root decomposition dynamics is essential to address declining carbon sequestration and nutrient imbalances in monoculture plantations. This study elucidates how forest gaps regulate Pinus massoniana root decomposition through comparative methodological analysis, providing theoretical foundations for near-natural forest management and carbon–nitrogen cycle optimization in plantations. The results showed the following: (1) Root decomposition was significantly accelerated by the in situ soil litterbag method (ISLM) versus the traditional litterbag method (LM) (decomposition rate (k) = 0.459 vs. 0.188), reducing the 95% decomposition time (T0.95) by nearly nine years (6.53 years vs. 15.95 years). ISLM concurrently elevated the root potassium concentration and reconfigured the relationships between root decomposition and soil nutrients. (2) Lower-order roots (orders 1–3) decomposed significantly faster than higher-order roots (orders 4–5) (k = 0.455 vs. 0.193). This disparity was amplified under ISLM (lower-/higher-order root k ratio = 4.1) but diminished or reversed under LM (lower-/higher-order root k ratio = 0.8). (3) Forest gaps regulated decomposition through temporal phase interactions, accelerating decomposition initially (0–360 days) while inhibiting it later (360–720 days), particularly for higher-order roots. Notably, forest gap effects fundamentally reversed between methodologies (slight promotion under LM vs. significant inhibition under ISLM). Our study reveals that conventional LM may obscure genuine ecological interactions during root decomposition, confirms lower-order roots as rapid nutrient-cycling pathways, provides crucial methodological corrections for plantation nutrient models, and advances theoretical foundations for precision management of P. massoniana plantations. Full article
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19 pages, 3532 KiB  
Article
Machine Learning Prediction of CO2 Diffusion in Brine: Model Development and Salinity Influence Under Reservoir Conditions
by Qaiser Khan, Peyman Pourafshary, Fahimeh Hadavimoghaddam and Reza Khoramian
Appl. Sci. 2025, 15(15), 8536; https://doi.org/10.3390/app15158536 (registering DOI) - 31 Jul 2025
Viewed by 98
Abstract
The diffusion coefficient (DC) of CO2 in brine is a key parameter in geological carbon sequestration and CO2-Enhanced Oil Recovery (EOR), as it governs mass transfer efficiency and storage capacity. This study employs three machine learning (ML) models—Random Forest (RF), [...] Read more.
The diffusion coefficient (DC) of CO2 in brine is a key parameter in geological carbon sequestration and CO2-Enhanced Oil Recovery (EOR), as it governs mass transfer efficiency and storage capacity. This study employs three machine learning (ML) models—Random Forest (RF), Gradient Boost Regressor (GBR), and Extreme Gradient Boosting (XGBoost)—to predict DC based on pressure, temperature, and salinity. The dataset, comprising 176 data points, spans pressures from 0.10 to 30.00 MPa, temperatures from 286.15 to 398.00 K, salinities from 0.00 to 6.76 mol/L, and DC values from 0.13 to 4.50 × 10−9 m2/s. The data was split into 80% for training and 20% for testing to ensure reliable model evaluation. Model performance was assessed using R2, RMSE, and MAE. The RF model demonstrated the best performance, with an R2 of 0.95, an RMSE of 0.03, and an MAE of 0.11 on the test set, indicating high predictive accuracy and generalization capability. In comparison, GBR achieved an R2 of 0.925, and XGBoost achieved an R2 of 0.91 on the test set. Feature importance analysis consistently identified temperature as the most influential factor, followed by salinity and pressure. This study highlights the potential of ML models for predicting CO2 diffusion in brine, providing a robust, data-driven framework for optimizing CO2-EOR processes and carbon storage strategies. The findings underscore the critical role of temperature in diffusion behavior, offering valuable insights for future modeling and operational applications. Full article
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24 pages, 2410 KiB  
Article
Predictive Modeling and Simulation of CO2 Trapping Mechanisms: Insights into Efficiency and Long-Term Sequestration Strategies
by Oluchi Ejehu, Rouzbeh Moghanloo and Samuel Nashed
Energies 2025, 18(15), 4071; https://doi.org/10.3390/en18154071 (registering DOI) - 31 Jul 2025
Viewed by 187
Abstract
This study presents a comprehensive analysis of CO2 trapping mechanisms in subsurface reservoirs by integrating numerical reservoir simulations, geochemical modeling, and machine learning techniques to enhance the design and evaluation of carbon capture and storage (CCS) strategies. A two-dimensional reservoir model was [...] Read more.
This study presents a comprehensive analysis of CO2 trapping mechanisms in subsurface reservoirs by integrating numerical reservoir simulations, geochemical modeling, and machine learning techniques to enhance the design and evaluation of carbon capture and storage (CCS) strategies. A two-dimensional reservoir model was developed to simulate CO2 injection dynamics under realistic geomechanical and geochemical conditions, incorporating four primary trapping mechanisms: residual, solubility, mineralization, and structural trapping. To improve computational efficiency without compromising accuracy, advanced machine learning models, including random forest, gradient boosting, and decision trees, were deployed as smart proxy models for rapid prediction of trapping behavior across multiple scenarios. Simulation outcomes highlight the critical role of hysteresis, aquifer dynamics, and producer well placement in enhancing CO2 trapping efficiency and maintaining long-term storage stability. To support the credibility of the model, a qualitative validation framework was implemented by comparing simulation results with benchmarked field studies and peer-reviewed numerical models. These comparisons confirm that the modeled mechanisms and trends align with established CCS behavior in real-world systems. Overall, the study demonstrates the value of combining traditional reservoir engineering with data-driven approaches to optimize CCS performance, offering scalable, reliable, and secure solutions for long-term carbon sequestration. Full article
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13 pages, 2073 KiB  
Article
Quantifying Ozone-Driven Forest Losses in Southwestern China (2019–2023)
by Qibing Xia, Jingwei Zhang, Zongxin Lv, Duojun Wu, Xiao Tang and Huizhi Liu
Atmosphere 2025, 16(8), 927; https://doi.org/10.3390/atmos16080927 (registering DOI) - 31 Jul 2025
Viewed by 152
Abstract
As a key tropospheric photochemical pollutant, ground-level ozone (O3) poses significant threats to ecosystems through its strong oxidative capacity. With China’s rapid industrialization and urbanization, worsening O3 pollution has emerged as a critical environmental concern. This study examines O3 [...] Read more.
As a key tropospheric photochemical pollutant, ground-level ozone (O3) poses significant threats to ecosystems through its strong oxidative capacity. With China’s rapid industrialization and urbanization, worsening O3 pollution has emerged as a critical environmental concern. This study examines O3’s impacts on forest ecosystems in Southwestern China (Yunnan, Guizhou, Sichuan, and Chongqing), which harbors crucial forest resources. We analyzed high-resolution monitoring data from over 200 stations (2019–2023), employing spatial interpolation to derive the regional maximum daily 8 h average O3 (MDA8-O3, ppb) and accumulated O3 exposure over 40 ppb (AOT40) metrics. Through AOT40-based exposure–response modeling, we quantified the forest relative yield losses (RYL), economic losses (ECL) and ECL/GDP (GDP: gross domestic product) ratios in this region. Our findings reveal alarming O3 increases across the region, with a mean annual MDA8-O3 anomaly trend of 2.4% year−1 (p < 0.05). Provincial MDA8-O3 anomaly trends varied from 1.4% year−1 (Yunnan, p = 0.059) to 4.3% year−1 (Guizhou, p < 0.001). Strong correlations (r > 0.85) between annual RYL and annual MDA8-O3 anomalies demonstrate the detrimental effects of O3 on forest biomass. The RYL trajectory showed an initial decline during 2019–2020 and accelerated losses during 2020–2023, peaking at 13.8 ± 6.4% in 2023. Provincial variations showed a 5-year averaged RYL ranging from 7.10% (Chongqing) to 15.85% (Yunnan). O3 exposure caused annual ECL/GDP averaging 4.44% for Southwestern China, with Yunnan suffering the most severe consequences (ECL/GDP averaging 8.20%, ECL averaging CNY 29.8 billion). These results suggest that O3-driven forest degradation may intensify, potentially undermining the regional carbon sequestration capacity, highlighting the urgent need for policy interventions. We recommend enhanced monitoring networks and stricter control methods to address these challenges. Full article
(This article belongs to the Special Issue Coordinated Control of PM2.5 and O3 and Its Impacts in China)
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25 pages, 1103 KiB  
Article
The Low-Carbon Development Strategy of Russia Until 2050 and the Role of Forests in Its Implementation
by Evgeny A. Shvarts, Andrey V. Ptichnikov, Anna A. Romanovskaya, Vladimir N. Korotkov and Anastasia S. Baybar
Sustainability 2025, 17(15), 6917; https://doi.org/10.3390/su17156917 - 30 Jul 2025
Viewed by 164
Abstract
This article examines the role of managed ecosystems, and particularly forests, in achieving carbon neutrality in Russia. The range of estimates of Russia’s forests’ net carbon balance in different studies varies by up to 7 times. The. A comparison of Russia’s National GHG [...] Read more.
This article examines the role of managed ecosystems, and particularly forests, in achieving carbon neutrality in Russia. The range of estimates of Russia’s forests’ net carbon balance in different studies varies by up to 7 times. The. A comparison of Russia’s National GHG inventory data for 2023 and 2024 (with the latter showing 37% higher forest sequestration) is presented and explained. The possible changes in the Long-Term Low-Emission Development Strategy of Russia (LT LEDS) carbon neutrality scenario due to new land use, land use change and forestry (LULUCF) data in National GHG Inventory Document (NID) 2024 are discussed. It is demonstrated that the refined net carbon balance should not impact the mitigation ambition in the Russian forestry sector. An assessment of changes in the drafts of the Operational plan of the LT LEDS is presented and it is concluded that its structure and content have significantly improved; however, a delay in operationalization nullifies efforts. The article highlights the problem of GHG emissions increases in forest fires and compares the gap between official “ground-based” and Remote Sensing approaches in calculations of such emissions. Considering the intention to increase net absorption by implementing forest carbon projects, the latest changes in the regulations of such projects are discussed. The limitations of reforestation carbon projects in Russia are provided. Proposals are presented for the development of the national forest policy towards increasing the net forest carbon absorption, including considering the projected decrease in annual net absorption by Russian forests by 2050. The role of government and private investment in improving the forest management of structural measures to adapt forestry to modern climate change and the place of forest climate projects need to be clearly defined in the LT LEDS. Full article
(This article belongs to the Section Sustainable Forestry)
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25 pages, 9676 KiB  
Article
A Comparative Analysis of SAR and Optical Remote Sensing for Sparse Forest Structure Parameters: A Simulation Study
by Zhihui Mao, Lei Deng, Xinyi Liu and Yueyang Wang
Forests 2025, 16(8), 1244; https://doi.org/10.3390/f16081244 - 29 Jul 2025
Viewed by 220
Abstract
Forest structure parameters are critical for understanding and managing forest ecosystems, yet sparse forests have received limited attention in previous studies. To address this research gap, this study systematically evaluates and compares the sensitivity of active Synthetic Aperture Radar (SAR) and passive optical [...] Read more.
Forest structure parameters are critical for understanding and managing forest ecosystems, yet sparse forests have received limited attention in previous studies. To address this research gap, this study systematically evaluates and compares the sensitivity of active Synthetic Aperture Radar (SAR) and passive optical remote sensing to key forest structure parameters in sparse forests, including Diameter at Breast Height (DBH), Tree Height (H), Crown Width (CW), and Leaf Area Index (LAI). Using the novel computer-graphics-based radiosity model applicable to porous individual thin objects, named Radiosity Applicable to Porous Individual Objects (RAPID), we simulated 38 distinct sparse forest scenarios to generate both SAR backscatter coefficients and optical reflectance across various wavelengths, polarization modes, and incidence/observation angles. Sensitivity was assessed using the coefficient of variation (CV). The results reveal that C-band SAR in HH polarization mode demonstrates the highest sensitivity to DBH (CV = −6.73%), H (CV = −52.68%), and LAI (CV = −63.39%), while optical data in the red band show the strongest response to CW (CV = 18.83%) variations. The study further identifies optimal acquisition configurations, with SAR data achieving maximum sensitivity at smaller incidence angles and optical reflectance performing best at forward observation angles. This study addresses a critical gap by presenting the first systematic comparison of the sensitivity of multi-band SAR and VIS/NIR data to key forest structural parameters across sparsity gradients, thereby clarifying their applicability for monitoring young and middle-aged sparse forests with high carbon sequestration potential. Full article
(This article belongs to the Section Forest Inventory, Modeling and Remote Sensing)
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24 pages, 1599 KiB  
Article
Climate-Regulating Industrial Ecosystems: An AI-Optimised Framework for Green Infrastructure Performance
by Shamima Rahman, Ali Ahsan and Nazrul Islam Pramanik
Sustainability 2025, 17(15), 6891; https://doi.org/10.3390/su17156891 - 29 Jul 2025
Viewed by 248
Abstract
This paper presents an Industrial–Ecological Symbiosis Framework that enables industrial operations to achieve quantifiable ecological gains without compromising operational efficiency. The model integrates Mixed-Integer Linear Programming (MILP) with AI-optimised forecasting to allow real-time adjustments to production and resource use. It was tested across [...] Read more.
This paper presents an Industrial–Ecological Symbiosis Framework that enables industrial operations to achieve quantifiable ecological gains without compromising operational efficiency. The model integrates Mixed-Integer Linear Programming (MILP) with AI-optimised forecasting to allow real-time adjustments to production and resource use. It was tested across the apparel manufacturing, metalworking, and mining sectors using publicly available benchmark datasets. The framework delivered consistent improvements: fabric waste was reduced by 10.8%, energy efficiency increased by 15%, and carbon emissions decreased by 14%. These gains were statistically validated and quantified using ecological equivalence metrics, including forest carbon sequestration rates and wetland restoration values. Outputs align with national carbon accounting systems, SDG reporting, and policy frameworks—specifically contributing to SDGs 6, 9, and 11–13. By linking industrial decisions directly to verified environmental outcomes, this study demonstrates how adaptive optimisation can support climate goals while maintaining productivity. The framework offers a reproducible, cross-sectoral solution for sustainable industrial development. Full article
(This article belongs to the Section Environmental Sustainability and Applications)
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24 pages, 10078 KiB  
Article
Satellite Hyperspectral Mapping of Farmland Soil Organic Carbon in Yuncheng Basin Along the Yellow River, China
by Haixia Jin, Rutian Bi, Huiwen Tian, Hongfen Zhu and Yingqiang Jing
Agronomy 2025, 15(8), 1827; https://doi.org/10.3390/agronomy15081827 - 28 Jul 2025
Viewed by 272
Abstract
This study combined field survey data with Gaofen 5 (GF-5) satellite hyperspectral images of the Yuncheng Basin (China), considering 15 environmental variables. Random forest (RF) was used to select the optimal satellite hyperspectral model, sequentially introducing natural and farmland management factors into the [...] Read more.
This study combined field survey data with Gaofen 5 (GF-5) satellite hyperspectral images of the Yuncheng Basin (China), considering 15 environmental variables. Random forest (RF) was used to select the optimal satellite hyperspectral model, sequentially introducing natural and farmland management factors into the model to analyze the spatial distribution of farmland soil organic carbon (SOC). Furthermore, RF factorial experiments determined the contributions of farmland management, climate, vegetation, soil, and topography to the SOC. Structural equation modeling (SEM) elucidated the driving mechanisms of SOC variations. Integrating satellite hyperspectral data and environmental variables improved the prediction accuracy and SOC-mapping precision of the model. The integration of natural variables significantly improved the RF model performance (R2 = 0.78). The prediction accuracy enhanced with the introduction of crop phenology (R2 = 0.81) and farmland management factors (R2 = 0.87). The model that incorporated all 15 variables demonstrated the highest prediction accuracy (R2 = 0.89) and greatest spatial SOC variability, with minimal uncertainty. Farmland management activities exerted the strongest influence on SOC (0.38). The proposed method can support future investigations on soil carbon sequestration processes in river basins worldwide. Full article
(This article belongs to the Section Precision and Digital Agriculture)
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