Search Results (417)

Investigating the coordination between greenhouse-oriented cultivated-land transformation and low-carbon agricultural emission performance is important for optimizing land use and advancing agricultural decarbonization. Using data for 31 mainland Chinese provinces in 2010, 2016, and 2022, this study constructs corresponding indices and examines their relationship using a coupling coordination model, spatial autocorrelation analysis, fixed-effects estimation, and a spatial Durbin model. The results show that greenhouse-oriented transformation increased but remained regionally uneven, with higher levels concentrated in eastern and northern coastal regions. The interprovincial mean of standardized agricultural carbon-emission intensity increased from 0.3225 in 2010 to 0.3557 in 2016, representing a 10.29% rise, before declining to 0.3279 in 2022—7.83% below the 2016 level but 1.66% above the 2010 level. Coupling coordination improved initially and subsequently entered a period of adjustment and convergence, while remaining predominantly low to moderate. It also exhibited significant positive spatial clustering. Rural economic development was negatively associated with local coordination, whereas population density showed a positive but model-sensitive association, and the urban–rural income gap produced limited spillover effects. The spatial autoregressive coefficient was insignificant. Facility-agriculture policies should therefore prioritize quality improvement, clean energy, input reduction, and resource efficiency rather than continued scale expansion. Full article

Agricultural carbon emissions represent a major source of greenhouse gases and play a critical role in achieving global climate mitigation and sustainable agricultural development targets. In China, the rapid transformation of agricultural production systems has led to substantial spatial heterogeneity in emission patterns and driving mechanisms of agricultural carbon emissions, while the underlying processes at the county scale remain insufficiently understood. This study investigated the spatiotemporal evolution and potential influencing factors of agricultural carbon emissions at the county level from 2000 to 2022 in Guangdong Province, China. First, agricultural carbon emissions were estimated based on a multi-source accounting framework covering land management, crop cultivation, animal production, and straw burning based on internationally recognized emission accounting methods and IPCC global warming potentials. Then, spatial clustering characteristics were analyzed using local spatial autocorrelation (LISA) to identify heterogeneous emission patterns. Finally, an interpretable machine learning framework combining Random Forest (RF) and SHapley Additive exPlanations (SHAP) was employed to quantify the nonlinear effects and relative contributions of multiple socioeconomic and agricultural drivers. The results showed that agricultural carbon emissions in Guangdong Province exhibited a fluctuating but overall decreasing trend, declining from 50.89 Mt CO₂-eq in 2000 to 39.24 Mt CO₂-eq in 2022, with an overall reduction of 22.9%. High-emission clusters were primarily concentrated in western and northern Guangdong, while low-emission areas were mainly located in the Pearl River Delta (PRD). The RF models demonstrated satisfactory predictive performance, with spatial cross-validated R² values ranging from 0.75 to 0.91 across different years. SHAP analysis suggested that ploughing area, fertilizer and pesticide usage, agricultural machinery power, and primary industry GDP were the dominant factors associated with agricultural carbon emissions, whereas urbanization consistently showed a negative association. Furthermore, these drivers exhibited pronounced nonlinear responses and distinct regional heterogeneity, particularly between the PRD and the western and northern parts of Guangdong Province. These findings suggested that agricultural carbon emissions are jointly influenced by agricultural production intensity, mechanization, and socioeconomic transition and can provide a scientific basis for developing region-specific low-carbon agricultural policies and promoting the sustainable transformation of agricultural systems. Full article

Non-grain production of cultivated land has increasingly affected regional food security and the stability of agricultural ecosystems. In traditional rice-producing regions, changes associated with non-rice cultivation, fallow land, rice-fishery integrated farming, and intensive agricultural management are reshaping the spatial structure of paddy landscapes. To identify the long-term spatiotemporal evolution of paddy systems, this study investigated Northern Jiangxi, China, using Landsat surface reflectance imagery from 2000, 2005, 2010, 2015, and 2020 on the Google Earth Engine (GEE) platform. The Enhanced Vegetation Index (EVI) and Land Surface Water Index (LSWI) were used to construct a phenology-based Flooding Frequency (FF) indicator. Based on the annual frequency with which pixels satisfied the condition LSWI > EVI, cultivated land was classified into three categories: non-flooded cropland, standard rice paddy, and high-frequency flooded cropland. In this study, non-flooded cropland was used as an indicator of potential non-rice cultivation rather than as direct evidence of confirmed non-grain production. Landscape metrics, transition matrices, gravity center migration, standard deviation ellipses, and geographically weighted regression (GWR) were then used to examine paddy landscape dynamics, fragmentation patterns, and county-level spatial associations with socioeconomic factors. The results suggest that the paddy system in Northern Jiangxi experienced marked stage-based fluctuations between 2000 and 2020. Standard rice paddy recovered during 2005–2010, whereas non-flooded cropland expanded considerably during 2010–2015, accompanied by intensified paddy landscape fragmentation. Non-flooded cropland was mainly distributed around urban fringes, transport corridors, and some hilly margins. Standard rice paddy was concentrated in traditional grain-producing areas, including the Poyang Lake Plain and the Gan-Fu Plain. High-frequency flooded cropland was primarily located in low-lying lake areas, where its dynamics were likely associated with rice-fishery integrated farming, continuous irrigation, and hydrological fluctuations. Landscape metrics showed that the largest patch index and mean patch size of standard rice paddy declined after 2010, indicating reduced spatial continuity of core paddy fields. The GWR analysis provided auxiliary evidence that total population, per capita gross domestic product (GDP), and urbanization rate were spatially associated with changes in non-flooded cropland at the county level; however, the results should be interpreted as exploratory associations rather than causal mechanisms. Overall, paddy landscape change in Northern Jiangxi was expressed not only through changes in cultivated land area, but also through the reorganization of paddy function, spatial continuity, and land-use intensity. Future cropland protection should therefore move beyond area-based control toward integrated management of quantity, quality, function, and spatial configuration. Future research should further verify these findings using dynamic cropland boundaries, higher-resolution imagery, and more detailed socioeconomic data. Full article

Terrestrial water storage in semi-arid basins is increasingly affected by the combined pressures of climate variability, land use change and intensive human activities. However, how landscape composition and configuration interact with climatic forcing to shape basin-scale terrestrial water storage anomalies (TWSA) remains insufficiently understood, particularly in rapidly urbanising tributary basins of the Yellow River. This study integrates GRACE/GRACE-FO-derived TWSA, meteorological observations and multi-period land use data to examine the coupled relationships among climate variability, landscape patterns and water storage in the human-dominated Yiluo River Basin. The results show that basin-averaged TWSA experienced a significant long-term decline during the GRACE/GRACE-FO period (−4.47 mm yr⁻¹), with a statistically detectable transition around 2012 and stronger depletion in the northern and eastern parts of the basin. Precipitation exhibited a cumulative and delayed relationship with TWSA, with the strongest raw association occurring under a six-month accumulation and one-month lag (Pearson’s r = 0.44, p < 0.001, n = 134). After removing the seasonal cycle, the relationship remained significant but weaker (r = 0.30, p = 0.001, n = 129), indicating that precipitation explains part, but not all, of the interannual variability in water storage. Landscape composition showed stronger associations with TWSA than landscape configuration. Construction land was negatively associated with water storage, whereas cultivated land and grassland showed positive associations, suggesting that impervious surface expansion and the loss of permeable land may weaken the basin’s water retention capacity. These findings indicate that water storage change in the Yiluo River Basin is shaped by both climatic forcing and human-induced land surface transformation. Basin management should therefore prioritise the control of urban impervious surface expansion, the protection of permeable agricultural and ecological land, and the integration of land use planning with adaptive water resource regulation. Full article

Crop monitoring is an important aspect of agricultural management, as it provides insights into cultivated area, crop health, growth patterns, and yields potential. Mapping cultivated areas and identifying crop types was historically conducted through field surveys and manual mapping, which are time-consuming and labor-intensive. Remote sensing classification has transformed large-scale land cover mapping, including crop identification. This work aims to: (1) compare the performance of Dynamic Time Warping (DTW) and two machine learning families (artificial neural networks and decision trees) for crop classification using Sentinel-2 data; (2) assess whether reflectance data, spectral indices, or both yield better classification results; and (3) evaluate the effect of hyperparameters on model performance. Among the DTW variants evaluated, dynamic time warping without a time constraint performed the best, with an overall accuracy of 0.921 using the combination of both reflectance and spectral indices. Most machine learning methods outperformed DTW. Although the convolutional neural network reached the highest single accuracy (0.948), the transformer was selected as the best model overall (accuracy of 0.944), as it combined a comparable accuracy with the lowest sensitivity to hyperparameter variations, making it a reliable option when testing machine learning architectures applied to crop mapping. This work also provides insights for model architecture development based on an exhaustive hyperparameter search for the machine learning models. Full article

Against the backdrop of global climate change and carbon neutrality strategies, land use carbon emissions have become a prominent topic amid regional efforts toward low-carbon transformation. However, existing studies on land-use carbon emissions have predominantly focused on humid and economically developed regions, while the unique carbon metabolism pathways of arid oasis–desert ecosystems, which are characterized by extremely low environmental carrying capacity and high sensitivity to land-use disturbance, remain largely unexplored. This study takes the oasis urban cluster in the Tarim Basin in southern Xinjiang Uygur Autonomous Region as the research object. This region belongs to a typical oasis–desert composite ecosystem, with a simple structure and low environmental carrying capacity (reflected by sparse vegetation cover < 20%, annual precipitation < 100 mm, extremely limited water resources, and high sensitivity to land disturbance). Its carbon metabolism pathway (i.e., the dynamic balance between carbon sources and sinks induced by land-use change) is fundamentally different from that in humid areas, and thus merits dedicated investigation. This study selects the period from 2000 to 2020 as the research period, which completely covers the acceleration period of urbanization and agricultural expansion in the Tarim Basin oasis urban cluster since the advancement of China’s Western Development Initiative. The data have a temporal resolution of 5 years (samples in 2000, 2005, 2010, 2015, 2020) and a spatial resolution of 30 m for land use and prefecture level for socio-economic indicators. Based on this, to fill the above-mentioned research gap, a research framework integrating the carbon emission coefficient accounting method, landscape pattern index, spatial autocorrelation analysis and geographic detector is adopted. Specifically, this study aims to systematically quantify the spatio-temporal evolution of land use carbon emissions and identify the most robust driving factors in the Tarim Basin oasis urban cluster by integrating multiple models, an approach that has not been previously applied to arid oasis regions. The research results show: (1) Based on the carbon emission coefficient method, total carbon emissions increased from 1.4455 million tons to 22.364 million tons, following a ‘slow-then-fast’ trajectory. In terms of temporal evolution, the study period can be further divided into three sub-stages: 2000–2005 (slow diffusion, with emission center skewed toward the northern energy-intensive zone), 2005–2015 (rapid restructuring, characterized by a ‘unipolar surge’ in Aksu and spread to the central oasis belt), and 2015–2020 (high-intensity stabilization, forming a cross-regional emission belt). Meanwhile, the land use structure has undergone a significant transformation. Construction land and cultivated land have continued to expand, while ecological land has significantly shrunk, resulting in a complex transformation pattern of oasis–desert ecotone. (2) The overall landscape became increasingly fragmented and diversified, the integrity of ecological space was damaged, and the regional carbon sink function was weakened. (3) The spatial autocorrelation analysis indicates that the spatial distribution of carbon emissions shows a heterogeneous pattern, forming a high-emission concentration area centered around Aksu-Bayingol. However, the global Moran’s I index is negative (such as −0.171 in 2020, p > 0.05), suggesting that carbon emissions have not formed a significant spatial clustering. (4) Carbon emissions are dominated by human and economic factors, and the interaction of factors is significant. The geographic detector identifies population density (average q value 0.904) and the proportion of construction land (average q value 0.858) as the key determinants of spatial variation in carbon emissions, reflecting the sensitive response of the human-nature system of arid zones to the urbanization process. These findings not only clarify the spatio-temporal features and driving forces of land use carbon emissions in the Tarim Basin oasis urban cluster, but also provide a replicable analytical framework for carbon-emission research in other arid and semi-arid regions worldwide. Based on these findings, we discuss the unique driving mechanisms of carbon emissions in arid regions, conclude that construction land expansion and population density are the dominant factors, and recommend a three-tier zoning governance system (carbon source control zone, carbon sink enhancement zone, coordinated development zone) for low-carbon spatial planning in arid areas. Full article

The urban fringe, a critical transitional zone between urban and rural areas, exhibits the most intense land-use conflicts and the most dynamic spatial restructuring. Its fragmentation not only undermines the efficiency of spatial land use but also threatens ecosystem stability, thereby posing a challenge to sustainable urban development. This study aims to examine the characteristics and future trends of spatial fragmentation within the urban fringe of Xi’an. Using multi-source datasets—including nighttime light imagery, land use data, and building vector data—we delineated the urban fringe boundary based on a light gradient threshold method. By combining landscape metrics with spatial overlay analysis, we assessed land use changes and spatial fragmentation patterns from 2000 to 2020 and projected land use conditions for 2030, 2040, and 2050. The results reveal that between 2000 and 2020, cultivated land became increasingly fragmented due to the expansion of construction land, while forest areas continued to expand under ecological restoration policies. Impervious surfaces exhibited infill aggregation. Rapid increases in nighttime light intensity were strongly correlated with heightened fragmentation (R² = 0.65, p < 0.01), confirming that urban expansion is the dominant driver of fragmentation. Projections indicate that the proportion of cultivated land will decline to 0.51, approaching a “critical warning threshold”. Full article

Carbon has increasingly been incorporated into economic and financial architectures as a tradable commodity within contemporary climate governance. Yet, carbon is not produced, stored, or mobilized in abstract space; it emerges from territorially specific land-use systems, ecological processes, and socio-spatial trajectories. This study examines carbon as a territorial commodity by analyzing long-term land-use and land-cover (LULC) dynamics in the municipality of Alegrete, located in the Brazilian Pampa biome, between 1985 and 2024. Based on MapBiomas Collection 10, and using cloud-based processing in Google Earth Engine combined with reproducible statistical workflows in R, the analysis identifies structural land-use trajectories shaping carbon-relevant territorial conditions. Results reveal a strong contraction of native grasslands, corresponding to approximately 17.8% of the municipal territory and a 24.2% reduction relative to the 1985 grassland area, alongside the expansion of mechanized agriculture, particularly soybean cultivation (+10.8% of the territory; +1343% relative to 1985 soybean area), and the consolidation of flooded rice systems (+7.6% of the territory; +146% relative to 1985 rice area). Rather than estimating carbon stocks or fluxes, the study establishes a territorial baseline linking land-use trajectories to key carbon-relevant processes, including soil carbon stability, disturbance intensity, permanence constraints, and multi-gas trade-offs. From a historical–structural perspective, these trajectories contrast with prevailing policy narratives and market-based instruments that assume an expanding carbon sequestration capacity, revealing a governance gap between valuation mechanisms and land-use realities. By conceptualizing carbon as a territorially embedded economic asset linked to land-use trajectories, the article contributes to interdisciplinary debates on climate governance, MRV integrity, environmental valuation, and the structural limits of market-based environmental instruments. Full article

Rapid urbanization and climate change are reshaping land-use systems, intensifying conflicts among urban growth, cultivated land conservation, and ecosystem protection. Understanding how land-use change affects carbon balance is important for designing sustainable land management and climate-resilient spatial planning. Taking Nanjing, China, as a case study, this study investigates how land-use change shaped carbon emissions, carbon sequestration, and net carbon emissions from 2000 to 2020 and further evaluates their future changes in 2030 under SSP–RCP scenarios. By integrating land-use simulation, carbon accounting, and contribution–sensitivity analysis, this study distinguishes land-use conversion effects from intra-type intensity change effects associated with changes in carbon emission or sequestration intensity within unchanged land categories. From 2000 to 2020, Nanjing experienced a substantial increase in net carbon emissions, with construction land expansion and higher emission intensity of construction land serving as the primary drivers. Although the carbon sink function was still mainly supported by cultivated land and forest land, land conversion and changes in sequestration intensity weakened the regional carbon balance. Under all SSP–RCP scenarios, simulated net carbon emissions for 2030 exceed the 2020 level, even though lower carbon intensity under SSP1–2.6 can partially mitigate emission growth. Conversion to construction land shows the highest carbon cost, especially when cultivated or ecological land is occupied. These findings highlight the need to coordinate urban expansion control, farmland protection, ecological restoration, and low-carbon industrial transformation. The study offers empirical support for improving sustainable land management and guiding spatial planning toward low-carbon development. Full article

Global population growth and the demand for sustainable food systems have pushed microalgae into the spotlight as promising novel food resources. They are rich in protein, omega-3 fatty acids, and bioactive pigments including astaxanthin and phycocyanin. Unlike conventional farming, microalgae cultivation can be conducted on non-arable land and may reduce direct competition with conventional food crops for land resources, depending on the production system used. Regulatory progress in China, the European Union (EU), and the United States has resulted in the authorization or approval of several microalgal species and microalgae-derived ingredients for specific food and nutritional applications, including dietary supplements, infant nutrition products, and alternative protein ingredients. Despite these advances, broader commercial adoption remains constrained by several challenges, such as off-flavors and the dark green color, high production costs from closed photobioreactors and energy-intensive downstream purification, fragmented regulatory frameworks across jurisdictions and limited long-term data on bioavailability, allergenicity, safety, and dose–response relationships for some emerging strains. This review focuses on microalgae as novel food resources, covering regulatory approvals, strain selection, high-value utilization, and market translation, synthesizes evidence on nutritional evaluation, application scenarios, and global regulatory differences, analyzes key bottlenecks, and proposes pathways to bridge fundamental research with industrial practice. It also highlights unresolved knowledge gaps to guide future research and policy. Full article

Rice monoculture systems, often involving double- or triple-cropping cycles annually, require intensive agricultural practices that can lead to land degradation. This study evaluates land degradation within the long-term rice monoculture systems of Nakhon Sawan, Thailand, using the Sustainable Development Goal 15.3.1 framework. By focusing exclusively on persistent rice-growing areas, the study minimized the confounding signals of land-use conversion, allowing for an evaluation of the trajectories driven by combined agricultural management and climatic factors. The assessment integrated land use and land cover (LULC), soil organic carbon (SOC) stocks, and land productivity. Findings indicate that 83% of the original paddy area remained long-term monoculture, with LULC-related degradation limited to 4% of the original paddy cultivation area. While SOC depletion was observed in a few districts, a broader potential carbon accretion trend was identified across the province, likely driven by sustainable post-harvest practices such as stubble retention and organic amendments. Land productivity analysis revealed partial stress only in a few districts. The study demonstrated that long-term rice cultivation did not result in widespread deterioration of soil health on an aggregate provincial scale; however, district-localized degradation hotspots suffering from soil organic carbon depletion and climate-induced productivity stress were identified, demanding targeted regional management. Full article

Intermediate crops, such as Brassica carinata and Camelina sativa, offer a promising pathway for expanding sustainable feedstock supply for advanced biofuels in Europe without competing with food and feed production. This study applies a competitive priority framework to assess the performance of intermediate crops in Italy and Spain, integrating agronomic, environmental, and regulatory dimensions. Using Member State-specific agroecological conditions, cost structures, and land-use profiles, the analysis identifies key challenges across land use and biomass-production stages and links them to measurable indicators and targeted optimisation strategies. Evidence from both experimental studies and modelling indicates that camelina can be seamlessly integrated into existing cropping systems without compromising crop yields or triggering soil carbon losses. These findings highlight the potential of intermediate crops to enhance soil health, to reduce erosion, and to stabilise yields under climate variability. This study also examines the policy conditions required to enable deployment, emphasising the need for region-specific crop calendars, digital traceability systems, and coherent implementation of RED III, CAP, ESCA, and CRCF frameworks. The distinction between volumetric and GHG-based targets is shown to be critical: intermediate crops perform strongly under GHG-based intensity reduction frameworks that reward soil carbon gains and sustainable cultivation. National instruments in Italy and Spain—including the Piano Strategico della PAC, Decreto Biocarburanti, Plan Estratégico de la PAC, and Real Decreto 376/2022—provide mechanisms for operationalising these strategies. Overall, the results demonstrate that intermediate crops can contribute meaningfully to both national and EU renewable energy, soil restoration, and climate mitigation objectives when supported by coherent agronomic and policy frameworks. Full article

This study investigates ecosystem service valuation on Zhoushan Island. Based on Landsat remote sensing images for 2000, 2010, and 2020 acquired through the Google Earth Engine (GEE) platform, six land use types are extracted using the Random Forest method. By integrating land use dynamic degree, transfer matrix, ecosystem service value (ESV) accounting, and five-level land–sea gradient zoning approaches, this study systematically analyzes the spatiotemporal evolution of land use and its effects on ESV over the 20-year period, and reveals the spatial differentiation pattern of land use change and ESV gains and losses along the land–sea gradient. The results indicate that from 2000 to 2020, water bodies and cultivated land on Zhoushan Island experienced continuous decline while construction land expanded rapidly, driven by policy regulation, urbanization, and industrial transformation. Localized coastal areas exhibited a typical chain conversion process of “water body → bare land → construction land,” which is closely associated with reclamation and land reclamation activities. Regional ESV declined continuously, reaching only 56.7% of its 2000 level by 2020, with regulating and provisioning services exhibiting the most pronounced deterioration. Analysis of the ESV net transfer matrix indicates that the primary driver of ESV decline was the large-scale conversion of high-value water bodies to low-value construction land and bare land, the magnitude of which far exceeded the positive ecological gains generated by all other land use conversions. The reduction in cultivated land area, compounded by adjustments in cropping structure, has placed sustained pressure on regional food security, and policy responses have lagged considerably behind the pace of ecological degradation. In terms of spatial differentiation, both the intensity of land use change and ESV loss exhibited a gradient pattern that decreases progressively from the coastal zone moving inland. Zone 1 and Zone 2 in the nearshore area together accounted for approximately 80% of total ESV loss, whereas Zone 4 and Zone 5 maintained relatively stable land use structures and ecological support capacity, owing to higher forestland coverage. Spearman’s rank correlation analysis confirmed a statistically significant monotonically decreasing relationship between land use dynamic degree and coastal distance. Policy regulation served as the primary driver of regional land use pattern evolution: early sea reclamation policies facilitated rapid land transformation along the coastline, while subsequent tightening of controls effectively curbed disorderly expansion. Full article

Cultivated Land “Non-grain” Rectification is reshaping crop allocation across China, yet whether the policy promotes or impedes agricultural growth remains contested. This paper argues that the same uniform regulation generates spatially heterogeneous outcomes along a continuous topographic relief: strict enforcement on contiguous plain farmland raises compliance costs for horticultural production and displaces it toward higher-elevation counties, where land-use rules bind less tightly and micro-climates favor cash crops. Using a panel of 2077 Chinese counties from 2019 to 2023, we construct a municipal-level measure of rectification intensity from government work reports and examine how its effect varies with county-level terrain relief. The results show that the marginal effect of policy intensity on agricultural value added rises monotonically with terrain, turning from negative in flat plains to increasingly positive beyond 0.5–1.0 km of relief; at the sample mean a one-standard-deviation increase in policy intensity raises agricultural value added by about 0.36 percent, and at 2 km of relief by 1.16 percent. The mechanism is spatial reallocation, not land expansion. Rectification shrinks horticultural area in plains and expands it in mountains. A Moran’s I test confirms this: counties with very different terrain show opposite changes in orchard cover. Further heterogeneity tests indicate that rectification primarily promotes the relocation and expansion of fruit orchards toward higher-relief counties. The growth effect is stronger where transport networks are denser, whereas water endowment does not significantly moderate the effect. Results are robust to alternative keyword classifications, concurrent-policy controls, and two instrumental-variable strategies. Full article

Restoration-oriented forest management is increasingly recognized as an important strategy for enhancing long-term carbon sequestration and rehabilitating degraded peri-urban forest landscapes. This study presents a scenario-based assessment of projected carbon sequestration trajectories under a National Reserve Forest Project implemented in peri-urban Wuhan, central China. Thirteen silvicultural models were grouped into three management pathways: intensive plantation cultivation, transformation of existing degraded stands, and tending of young and middle-aged forests. Carbon sequestration was evaluated over a 40-year assessment period (2024–2063) using a Biomass Expansion Factor-based accounting framework incorporating above- and belowground biomass, harvested wood products, and conservative baseline deductions consistent with national and provincial methodologies. The results indicate a sustained long-term increase in projected carbon sequestration despite periodic short-term declines associated with planned thinning and harvesting cycles. Transformation-oriented pathways contributed the largest cumulative project-scale sequestration and generally exhibited relatively strong area-normalized sequestration performance compared with intensive plantation and tending pathways. Intensive plantation systems displayed greater temporal fluctuation associated with shorter rotation cycles and repeated harvesting events. The analysis also highlights the importance of distinguishing between area-normalized sequestration efficiency and cumulative project-scale contribution, as models with moderate per-hectare performance generated substantial total carbon benefits because of their larger implementation area. The findings suggest that restoration-oriented management of existing degraded stands may provide a relatively stable long-term carbon-sequestration pathway in peri-urban forest systems where land availability for large-scale afforestation is constrained. The study also demonstrates the applicability of conservative scenario-based accounting frameworks for restoration-oriented forest carbon assessment and planning under data-limited conditions. Full article