Search Results (190)

There is a lack of systematic research on the comprehensive regulatory effects of urea and organic fertilizer application on soil quality and cotton yield in summer direct-seeded cotton fields in the Yangtze River Basin. Additionally, there is a redundancy of indicators in the cotton field soil quality evaluation system and a lack of reports on constructing a minimum dataset to evaluate the soil quality status of cotton fields. We aim to accurately and efficiently evaluate soil quality in cotton fields and screen nitrogen application measures that synergistically improve soil quality, cotton yield, and nitrogen fertilizer utilization efficiency. Taking the summer live broadcast cotton field in Jiangxi Province as the research object, four treatments, including CK without nitrogen application, CF with conventional nitrogen application, N1 with nitrogen reduction, and N2 with nitrogen reduction and organic fertilizer application, were set up for three consecutive years from 2022 to 2024. A total of 15 physical, chemical, and biological indicators of the 0–20 cm plow layer soil were measured in each treatment. A minimum dataset model was constructed to evaluate and verify the soil quality status of different nitrogen application treatments and to explore the physiological mechanisms of nitrogen application on yield performance and stability from the perspectives of cotton source–sink relationship, nitrogen use efficiency, and soil quality. The minimum dataset for soil quality evaluation in cotton fields consisted of five indicators: soil bulk density, moisture content, total nitrogen, organic carbon, and carbon-to-nitrogen ratio, with a simplification rate of 66.67% for the evaluation indicators. The soil quality index calculated based on the minimum dataset (MDS) was significantly positively correlated with the soil quality index of the total dataset (TDS) (R² = 0.904, p < 0.05). The model validation parameters RMSE was 0.0733, nRMSE was 13.8561%, and the d value was 0.9529, all indicating that the model simulation effect had reached a good level or above. The order of soil quality index based on MDS and TDS for CK, CF, N1, and N2 treatments was CK < N1 < CF < N2. The soil quality index of N2 treatment under MDS significantly increased by 16.70% and 26.16% compared to CF and N1 treatments, respectively. Compared with CF treatment, N2 treatment significantly increased nitrogen fertilizer partial productivity by 27.97%, 31.06%, and 21.77%, respectively, over a three-year period while maintaining the same biomass, yield level, yield stability, and yield sustainability. Meanwhile, N1 treatment had the risk of significantly reducing both boll density and seed cotton yield. Compared with N1 treatment, N2 treatment could significantly increase the biomass of reproductive organs during the flower and boll stage by 23.62~24.75% and the boll opening stage by 12.39~15.44%, respectively, laying a material foundation for the improvement in yield and yield stability. Under CF treatment, the cotton field soil showed a high degree of soil physical property barriers, while the N2 treatment reduced soil barriers in indicators such as bulk density, soil organic carbon content, and soil carbon-to-nitrogen ratio by 0.04, 0.04, 0.08, and 0.02, respectively, compared to CF treatment. In summary, the minimum dataset (MDS) retained only 33.3% of the original indicators while maintaining high accuracy, demonstrating the model’s efficiency. After reducing nitrogen by 20%, applying 10% total nitrogen organic fertilizer could substantially improve cotton biomass, cotton yield performance, yield stability, and nitrogen partial productivity while maintaining soil quality levels. This study also assessed yield stability and sustainability, not just productivity alone. The comprehensive nitrogen fertilizer management (reducing N + organic fertilizer) under the experimental conditions has high practical applicability in the intensive agricultural system in southern China. Full article

To achieve regional sustainable development, the low-carbon transformation of agriculture is essential, as it serves both as a significant carbon source and as a potential carbon sink. This study calculated the agricultural carbon emissions in Liaocheng from 2010 to 2022 by analyzing processes including crop cultivation, animal husbandry, and agricultural input. Additionally, a simulation model of the water–energy–food–carbon nexus (WEFC-Nexus) for Liaocheng’s agricultural production process was developed. Using Vensim PLE 10.0.0 software, this study constructed a WEFC-Nexus model encompassing four major subsystems: economic development, agricultural production, agricultural inputs, and water use. The model explored four policy scenarios: business-as-usual scenario (S1), ideal agricultural development (S2), strengthening agricultural investment (S3), and reducing agricultural input costs (S4). It also forecast the trends in carbon emissions and primary sector GDP under these different scenarios from 2023 to 2030. The conclusions were as follows: (1) Total agricultural carbon emissions exhibited a three-phase trajectory, namely, “rapid growth (2010–2014)–sharp decline (2015–2020)–gradual rebound (2021–2022)”, with sectoral contributions ranked as livestock farming (50%) > agricultural inputs (27%) > crop cultivation (23%). (2) The carbon emissions per unit of primary sector GDP (CEAG) for S2, S3, and S4 decreased by 8.86%, 5.79%, and 7.72%, respectively, compared to S1. The relationship between the carbon emissions under the four scenarios is S3 > S1 > S2 > S4. The relationship between the four scenarios in the primary sector GDP is S3 > S2 > S4 > S1. S2 can both control carbon emissions and achieve growth in primary industry output. Policy recommendations emphasize reducing chemical fertilizer use, optimizing livestock management, enhancing agricultural technology efficiency, and adjusting agricultural structures to balance economic development with environmental sustainability. Full article

This study used Xinxin 2 (Juglans regia L. ‘Xinxin2’), a major cultivated walnut variety in Xinjiang, China, to clarify the response and adaptation mechanisms of the anatomical structures of walnut related to source–sink–flow under altered source–sink relationships. We anatomically observed the leaves, fruit stalks, and fruit of bearing branches by artificially adjusting the leaf-to-fruit ratio (LFR). The LFR substantially affected the leaf structure and thickness of the fruit-bearing branches obtained via girdled (p < 0.05). The results of the analysis of the leaf anatomy revealed that a low LFR impeded leaf growth and internal structural development while accelerating senescence, whereas a high LFR promoted leaf growth and delayed senescence. The same trend was observed for the phloem area (PA) of the fruit stalk with the increase in fruit load when the number of leaves on the fruit branch was the same. The maximum PA was reached when the number of fruits was high (except for 4L:3F). This indicates that the micro-anatomical structure of the fruit stalk is more developed under the treatment of a higher number of pinnate compound leaves and fruit level of LFRs. The cells of the 1L:3F and 2L:3F were considerably smaller in the green peel and kernel of the fruit on the branches obtained via girdled than those of 5L:1F plants (p < 0.05). No significant difference was found in the number of cells per unit area or the cross-sectional area of cells in the pericarp and kernel of the fruit under LFRs (p > 0.05); however, a large difference was noted in the microanatomical structure of the pericarp and kernel of fruit. Changes in the structural adaptation characteristics of walnut leaves (source), fruit stalk (flow), and fruit (sink) are related to source–sink regulation. A change in the LFR affects the carbohydrate synthesis in the leaves (source), transport in fruit stalks (flow), and the carbohydrate reception in fruits (sink). Full article

Non-structural carbohydrates (NSCs), the main substrates and energy carriers of plants, play an important role in mediating the source-sink balance of carbon (C). However, the trade-offs in the allocation of NSCs remain unclear at critical stages of fruit development. In this study, we evaluated the dynamic and allometric partitioning characteristics of NSCs at the key stage of fruit development in Camellia oleifera. The seed NSCs pool was the highest in the middle stage of rapid fruit expansion, and an inverted “V” shape appeared from July to September and peaked in August. Notably, although the NSC pool of twigs was the smallest and did not change significantly at each stage, the starch pool was the largest. Significant correlations existed between the NSC content of different organs in C. oleifera in the early stage of slow development and the middle stage of rapid fruit expansion. In particular, NSC components, both of the twigs in the early stage and of the twigs and seeds in the middle stage, showed significant allometric partitioning relationships. In summary, seeds are the main carbon sink for fruit development trade-offs of C. oleifera, and twigs may play an important role in transferring C to seeds at the early and middle stages of fruit development. In the future, attention should be paid to controlling the factors affecting the balance of plant C during the rapid fruit expansion period to ensure high yield. Full article

This study reviews and synthesizes published data to estimate the net carbon flux associated with the complete potato production process. It identifies the key components that contribute to this flux and explores potential mitigation strategies, including both cultivation and post-harvest storage. Data were compiled from field-scale studies (primarily using eddy covariance) and life cycle assessment studies. The results indicate that potato production can act as a carbon sink or a carbon source, depending on the production scenario. In Scenario 1, which represents the worst-case scenario, potato production acts as a carbon source, with a carbon flux of 13,874.816 kg CO₂ eq ha⁻¹ season⁻¹. In contrast, in Scenario 2, the best-case scenario, potato production acts a carbon sink with a carbon flux of −12,830.567 kg CO₂ eq ha⁻¹ season⁻¹. Similarly, in Scenario 3, which is the average scenario, potato production acts as a carbon sink, though a minor one, with a carbon flux of −90.703 kg CO₂ eq ha⁻¹ season⁻¹. Notably, the growing phase has the most significant impact on potato production’s overall carbon flux, as it is the period in which the highest levels of carbon sequestration and emissions occur. Fertilization is the primary carbon source among all potato production operations, averaging 1219.225 kg CO₂ eq ha⁻¹ season⁻¹. Optimizing farming practices, including fertilization, irrigation, tillage methods, and cultivar selection, are essential to enhance carbon sequestration and reduce greenhouse gas emissions. Additionally, further research through controlled experiments is recommended to deepen the understanding of the relationships between various farming factors and carbon flux, ultimately supporting more sustainable potato production practices. Full article

Sugar beet is a nitrogen (N)-sensitive crop, and its N regulation and utilization are critical for enhancing productivity. Sugar beet seedlings at the two-true-leaf-pair stage were hydroponically grown in an artificial climate chamber. Leaves and roots from three seedlings per treatment were sampled at 10, 20, 25, and 30 days after exposure to N treatments (N5: 5 mmol/L, N10: 10 mmol/L, N15: 15 mmol/L, and N20: 20 mmol/L) to assess the effects of N supply level on growth, photosynthesis, and carbon and nitrogen metabolism. The results revealed a time-dependent dynamics in beet biomass accumulation, with N20 inducing chlorosis and necrosis symptoms by 10 days post-treatment (DPT), resulting in the lowest biomass. While N15 significantly promoted root biomass by 30 DPT, showing a 23.70% (root dry weight, RDW) increase over N20; chlorophyll content and gas exchange parameters-net photosynthetic rate (Pn), stomatal conductance (Gs), transpiration rate (Tr) exhibited significant N dependence, with N15 maintaining high chlorophyll level (0.78 mg/g) and photosynthetic rate (220.33 μmol/(m²·s). Nitrogen assimilation, as indicated by glutamine synthetase and glutamate synthetase activity (GS and GOGAT), was stronger under N15, promoting amino acid synthesis and root growth, whereas N20 inhibited enzyme activity. Carbon metabolism analysis revealed that N15-driven sucrose synthesis significantly increased root sucrose content, sucrose phosphate synthase and sucrose synthase activity (SPS and SS), optimizing source–sink allocation. Correlation analysis showed a positive relationship between leaf and root biomass (r = 0.91), and root sucrose content was positively correlated with GOGAT activity (r = 0.90), emphasizing the synergistic regulation of C/N metabolism. On the contrary, N20 led to disrupted C/N metabolic homeostasis, inhibited enzyme activity, and C/N distribution. These results indicated that the photosynthetic output, enzyme efficiency, and sucrose distribution were coordinated by nitrogen optimization, and the growth of sugar beet seedlings was optimized. Full article

With the increasing consumer demand for healthy and natural foods, strawberries have emerged as one of the most popular small berries globally. Consequently, careful investigation of the relationship between leaf photosynthetic activity (source strength) and fruit development (sink strength) during strawberry growth provides important insights for maximizing the production potential of this crop. This objective necessitates accurate strawberry organ segmentation. Recently, advancements in deep learning (DL) have driven the development of numerous semantic segmentation models that have performed effectively on benchmark datasets. Nevertheless, their small-organ plant segmentation efficacy remains insufficiently explored. Consequently, this study evaluates eight representative point-based semantic segmentation models for the strawberry organ segmentation task: PointNet++, PointMetaBase, Point Transformer V2, Swin3D, KPConv, RandLA-Net, PointCNN, and Sparse UNet. The employed dataset comprises two components: the open-source LAST-Straw strawberry dataset and a custom Japanese strawberry dataset. Strawberry point cloud organs were categorized into four classes: leaf, stem, flower, and berry. The sparse convolution-based Sparse UNet achieved the highest mean intersection over union of 81.3, followed by the PointMetaBase model at 80.7. This study provides insights into the strengths and limitations of existing architectures, assisting researchers and practitioners in selecting appropriate models for strawberry organ segmentation tasks. Full article

The high demands of corn (Zea mays L.) grain production coupled with water quality goals and phosphorus (P) conservation pose a great challenge to farmers and society and necessitate improved P utilization efficiency (PUtE: grain yield per mass total P (TP) content). The objective of this study was to evaluate PUtE among six Pioneer corn hybrids released over a span of 75 years. Corn was grown in a sand culture hydroponics system that eliminated confounding plant–soil interactions and root architecture and allowed for precise control of nutrient availability. Four P concentration levels (4, 7, 10, and 12 mg P L⁻¹) were applied to hybrids released in 1936, 1942, 1946, 1952, 2008, and 2011. Nutrients other than P were applied at sufficient levels. Shoots and roots were harvested at maturity (R6) and biomass and P concentration determined. Results showed that total biomass did not differ among hybrids, but partitioning of biomass varied with hybrid. Grain yield varied between hybrids, but there was no trend with the year of release. Grain P content was negatively correlated with stem P content (R² = 0.89). PUtE differed between the most recently released hybrids (2008 and 2011) whereas older hybrids had intermediate and similar PUtE. Grain yield was not solely determined by TP in the plant, but was strongly influenced by biomass and P partitioning, which was manifested as relative differences in PUtE between hybrids. While the PUtE did not necessarily change as a function of the breeding period, there were differences between hybrids. The findings highlight the critical role of the source–sink relationship in determining PUtE and grain yield. Full article

Despite being one of China’s largest soybean (Glycine max L. Merr.) production areas, the Huanghuaihai Farming Region (HFR) has long been plagued by suboptimal yields. While cultivar development has contributed to yield gains in the past, whether such breeding will afford resilience under more adverse climatic conditions expected in future remains an open question. Here, we conducted two-year field experiments to contrast the growth and development of soybean cultivars released between 1960 and 2010 in the HFR. We found that cultivar breeding significantly influenced phenology, with contemporary cultivars having shorter and longer vegetative and reproductive growth phases, respectively. Grain filling duration of modern cultivars (LD11, HD14, JD21, and QH34) was 10 days longer than that of older cultivars (JX23 and WF7). Maturity height of modern cultivars decreased over time to a current value of ~80 cm, despite having higher leaf area index (LAI) and SPAD values compared with older cultivars during reproductive development. The quantum yield of electron transport in photosystem I, quantum yield of electron transport chain, photosynthetic performance index, stomatal conductance, net photosynthetic rate, and Rubisco activity of contemporary cultivars was stronger than those of older cultivars during grain filling. Prolonged grain filling duration, higher LAI, greater light interception, and stronger photosynthetic capacity evoked greater rates of grain filling, leading to higher grain weight, seed number, and yield. Genetic evolution of the cultivars over time, warmer conditions, and more precipitation together afforded longer reproductive stages. Our results indicate that yield gains have been realized primarily by cultivar breeding, and to a lesser extent, beneficial climate change. We highlight dynamic source/sink relationships underpinning the co-evolution of photosynthetic traits through soybean breeding, and provide practical advice to guide future breeding efforts. Full article

Boreal forests have historically been regarded as some of the largest terrestrial carbon (C) sinks. However, increased soil organic matter (SOM) decomposition due to forest harvesting and post-harvest silviculture (e.g., site preparation, planting, and managing for competing vegetation) may exacerbate the effects of climate warming and shift boreal forests from being C sinks to C sources. We used an established stand-scale, fully replicated, experimental study to identify how two levels of forest management (harvesting = Harvest Only, and harvesting with post-harvest silviculture = Harvest Plus) influence SOC dynamics at three boreal forest sites varying in soil texture. Each site was surveyed for forest floor (litter and F/H horizons) and mineral soils pre-harvest (0) and 5, 14, and 20 years post-harvest. We predicted that sites harvested and left to revegetate naturally would have the lowest SOC stocks after 20 years, as sites that were planted and managed for competing vegetation would recover faster and contribute to a larger nutrient pool, and that the sand-dominated site would have the largest SOC losses following harvest due to the inherently lower ability of sand soils to chemically and/or physically protect SOC from decomposition following harvest. Over a 20-year period, both forest management treatments generally resulted in reduced total (litter, F/H, and mineral horizon) SOC stocks compared with the control: the Harvest Only treatment reduced overall SOC stocks by 15% at the silt-dominated site and 31% at the clay-dominated site but increased overall SOC stocks by 4% at the sand-dominated site, whereas the Harvest Plus treatment reduced overall SOC stocks by 32% at the sand- and silt-dominated sites and 5% at the clay-dominated site. This suggests that harvesting and leaving plots to revegetate naturally on sand-dominated sites and harvesting followed by post-harvest silviculture on clay-dominated sites may minimize total SOC losses at similar sites, though a full replicated field experiment is needed to test this hypothesis. Most treatment effects in this study were observed only in the second decade post-harvest (14 and 20 years post-harvest), highlighting the importance of long-term field experiments on the effects of forest harvesting and post-harvest silviculture. This research improves our understanding of the relationship between C dynamics, forest management, and soil texture, which is integral for developing sustainable management strategies that optimize C sequestration and contribute to the resilience of boreal forest ecosystems in the face of climate change. Full article

With accelerating climate change and urbanization, regional carbon balance faces increasing uncertainty. Terrestrial carbon sinks play a crucial role in advancing China’s sustainable development under the dual-carbon strategy. This study quantitatively modeled China’s terrestrial carbon sink capacity and analyzed the multidimensional relationships between impact factors and carbon sinks. After preprocessing multi-source raster data, we introduced kernel normalized the difference vegetation index (kNDVI) to the Carnegie–Ames–Stanford approach (CASA) model, together with a heterotrophic respiration (R_h) empirical equation, to simulate pixel-level net ecosystem productivity (NEP) across China. A light gradient-boosting machine (LightGBM) model, optimized via Bayesian algorithms, was trained to regress NEP drivers, categorized into atmospheric components (O₃, NO₂, and SO₂) and subsurface properties (a digital elevation model (DEM), enhanced vegetation index (EVI), soil moisture (SM)), and human activities (land use/cover change (LUCC), POP, gross domestic product (GDP)). Shapley Additive Explanation (SHAP) values were used for model interpretation. The results reveal significant spatial heterogeneity in NEP across geographic and climatic contexts. The pixel-level mean and total NEP in China were 268.588 gC/m²/yr and 2.541 PgC/yr, respectively. The north tropical zone (NRZ) exhibited the highest average NEP (828.631 gC/m²/yr), while the middle subtropical zone (MSZ) and south subtropical zone (SSZ) demonstrated the most stable NEP distributions. LightGBM achieved high simulation accuracy, further enhanced by Bayesian optimization. SHAP analysis identified EVI as the most influential factor, followed by SM, NO₂, DEM, and POP. Additionally, LightGBM effectively captured nonlinear relationships and variable interactions. Full article

The long-term arid climate in Xinjiang poses a major challenge to sustainable jujube production. In this study, we systematically evaluated the impacts of deficit irrigation (DI) by comparing a full irrigation control (CK) with six DI treatments—mild DI (75% CK) and severe DI (50% CK) water deficits applied during either flowering + fruit setting or fruit enlargement stages. The key findings demonstrate that flowering + fruit setting DI effectively balances water conservation with productivity. Mild DI (75% CK) during flowering + fruit setting reduced irrigation by 72 mm while maintaining near-optimal photosynthesis (95% recovery post-rewatering) and significantly improving fruit quality (5.49–10.28% higher sugar content, 3.40–5.06% larger fruit volume), despite a moderate 4.22–11.36% yield reduction. In contrast, severe DI caused irreversible physiological stress (only 75% photosynthetic recovery), and fruit-enlargement-stage DI uniformly compromised both yield and fruit size. An economic analysis confirmed flowering + fruit setting mild DI as optimal, generating 17,139–20,550 RMB·ha⁻¹ profit through enhanced water use efficiency (WUE) and premium-quality fruit production. PLS-PM validation revealed that targeted flowering + fruit setting water deficit suppresses vegetative overgrowth while optimizing source–sink relationships, achieving a 23–31% WUE improvement without sacrificing marketable yield. Thus, mild DI during flowering + fruit setting is a climate-smart irrigation strategy for Xinjiang’s jujube industry, resolving water scarcity challenges with economic viability. Full article

Understanding the contributions of source–sink relationships to photosynthesis will help achieve high wheat grain yields. A single-factor field experiment was conducted to quantify the regulatory effects of different sink–source ratios on wheat photosynthetic characteristics, including two wheat cultivars with different source–sink relationships as materials for detailed source–sink manipulations through flag leaf removal (LR) and removal of spikelets on one side of each spike (SR). Compared with a control (CK), LR increased the sink–source ratio (23.84%) and significantly reduced the yield (16.17%), 1000-kernel weight (11.73%), and kernels per spike (7.33%). LR increased the leaves’ net photosynthetic rate (Pn) (4.27–15.82%), the electron transfer rate (3.97–14.93%), and the Rubisco activity (2.16–12.25%) in the short term, and LR increased sucrose synthesis-related enzyme activities (3.96–19.95%) and gene expressions (SPS1, SUS1, CIN1, and SUT1). Compared with CK, SR reduced the sink–source ratio (44.12%) and significantly increased the 1000-kernel weight (10.02%) but reduced the yield (43.93%) and kernels per spike (49.31%). SR reduced the leaves’ Pn (8.54–21.41%), the electron transfer rate (3.51–16.71%), and the Rubisco activity (5.96–21.51%), and the photosynthetic process was limited. SR decreased sucrose synthesis-related enzyme activities (5.12–29.09%) and gene expressions (SPS1, SUS1, CIN1, and SUT1). Therefore, a higher sink–source ratio is an important indicator of high photosynthetic efficiency, which can be used as a screening and judgment index in variety selection and cultivation regulation. Full article

Silicon (Si) is one of the biogenic elements in lake aquatic ecosystems. Sediments are both sinks and sources of Si, but little is known about its influence on the biogeochemical cycle of Si in lakes and its relationship to other biogenic factors such as carbon and nitrogen. Examining Caohai Lake, a typical macrophytic lake in China, this study systematically examined the different Si forms and biogenic silica (BSi) distribution characteristics and their coupling relationships with total organic carbon (TOC) and total nitrogen (TN) in surface sediments. Iron–manganese-oxide-bonded silicon (IMOF-Si) and organic sulfide-bonded silicon (OSF-Si) jointly accounted for 95.9% of Valid-Si in the sediments, indicating that the fixation of Si by organic matter and iron–manganese oxides was the main mechanism underlying the formation of the different forms of Valid-Si in sediments. The release and recycling of Si in sediments may be mainly driven by mineralized degradation of organic matter and anoxic reduction conditions at the sediment–water interface. The content of biogenic Si (BSi) in the sediments was relatively higher in the southern and eastern areas, which could be explained by the intensification of eutrophication and the increased abundance of diatomaceous siliceous organisms in these areas seen in recent years. The TOC and TN contents in the sediments were generally high, and the sources of organic matter in the sediments included both the residues of endophytes (main contributors) and the input of terrigenous organic matter. TOC and TN both had highly significant correlations with OSF-Si and Valid-Si, which demonstrated that Valid-Si had excellent coupling relationships with C and N in the sediments. The good correlation between BSi, TOC and TN (p < 0.01), as well as the high C/Si, N/Si mole ratio of TOC and TN to BSi, respectivelny, indicating that the dissolution and release rate of BSi may be much higher than the degradation rate of organic matter from the sediments, especially in the areas with a higher abundance of siliceous organisms. Full article

As important energy suppliers in China, coal-resource-based cities are pivotal to achieving the nation’s 2060 carbon-neutrality goal. This study focused on Jincheng City, utilizing the LOW EMISSIONS ANALYSIS PLATFORM (LEAP) model to predict carbon emissions from energy consumption under various scenarios from 2020 to 2060. Then, combined with the Markov-PLUS model to map carbon emissions to land-use types, it evaluated spatial changes in carbon metabolism and analyzed carbon-transfer patterns across different land-use types. The results showed the following: (1) Across all scenarios, Jincheng’s carbon emissions exhibited an initial increase followed by a decline, with the industrial sector accounting for over 70% of total emissions. While the baseline scenario deviated from China’s carbon peaking target, the high-limit scenario achieved an early carbon peak by 2027. (2) High-negative-carbon-metabolism areas were concentrated in central urban zones and industrial parks. Notably, arable land shifted from a carbon-sink area to a carbon source area by 2060 in both the low- and high-limit scenarios. (3) In the baseline scenario, industrial and transportation land uses were the primary barriers to carbon metabolism balance. In the low-carbon scenario, the focus shifted from industrial and transportation emissions to urban construction land emissions. In the high-limit scenario, changes in urban–rural land-use relationships significantly influenced carbon metabolism balance. This study emphasizes the importance of industrial green transformation and land-use planning control to achieve carbon neutrality, and it further explores the significant impact of territorial spatial planning on the low-carbon transition of coal-resource-based cities. Full article