Search Results (145)

In intensive greenhouse agriculture, irrational fertilization practices can exacerbate carbon emissions and impair ecosystem service functions. To address this issue, biogas slurry and biochar were introduced as waste-derived substitutes for mineral fertilizer, and the effects of different fertilization strategies on the net ecosystem carbon balance (N_ECB) and ecosystem service value (ESV) of greenhouse tomato (Solanum lycopersicum L.) production systems over two growing seasons (spring–summer and autumn–winter) were systematically evaluated. When economic return was prioritized, the treatment with 25% biogas slurry substituting for mineral fertilizer (BS25) performed best, with ESVs of 641,606.83 and 629,987.37 CNY ha⁻¹ in the spring–summer and autumn–winter seasons, respectively; the treatment with 50% biogas slurry substitution (BS50) ranked second, and both treatments were significantly superior to the others (p < 0.05). When the objective was to enhance carbon sink capacity while maintaining high yield, the treatment with 75% biogas slurry combined with biochar substituting for mineral fertilizer (BS75 + C) showed the best overall performance, with N_ECB values of 6.30 and 6.34 t ha⁻¹ in the two respective seasons, while also demonstrating clear advantages in soil organic matter accumulation and atmospheric regulation. Based on the VIKOR model with AHP-CRITIC combined weighting, BS75 + C was identified as the optimal option. However, the most suitable fertilization strategy depends on management objectives: BS25 is recommended when maximizing short-term economic return is the primary goal, whereas BS75 + C is preferable for enhancing carbon sink capacity and ecological benefits. Considering both ecosystem service value and comprehensive performance, BS50 and BS75 + C are recommended as sustainable fertilization strategies for greenhouse tomato production. Full article

As a core component of terrestrial ecosystems, forests play an irreplaceable ecological role in carbon sequestration, biodiversity conservation, and global climate regulation. Home to key global forest belts including the Congo Basin, the African continent’s forest changes directly shape regional ecological balance and sustainable development while profoundly affecting global ecological security and climate dynamics. Based on the Shared Socioeconomic Pathways (SSPs), a unified narrative framework for global socioeconomic and environmental change scenarios, this study couples techniques such as the Future Land Use Simulation (FLUS) model, dynamic degree analysis, transition matrix, K-means clustering analysis, and patch fragmentation analysis. This work aims to answer two key questions: (1) What are the spatiotemporal characteristics and dominant drivers of African woodland changes under different SSPs? (2) How do spatial clustering and fragmentation patterns vary across scenarios? It systematically predicts and analyzes the spatiotemporal characteristics, driving mechanisms, and fragmentation change patterns of African woodlands in 2030, 2050, and 2070 under five scenarios (SSP1-SSP5) with 2020 as the baseline. These five official IPCC SSP frameworks represent five distinctly divergent socioeconomic development trajectories ranging from sustainable to fossil-fuel-driven development, which are the core differentiated scenarios recommended by IPCC; full inclusion facilitates systematic comparison of varied forest feedback features across Africa’s diversified national development backgrounds. The research results show that understory forests in the SSP5 (Fossil Fuel-dominated Development) scenario exhibit a stable growth trend, with the total area transferred in significantly exceeding the area transferred out from 2020 to 2070, resulting in a net increase of 143,513 km². This growth occurs because high-income economies under this scenario invest heavily in ecological restoration and forest protection, offsetting carbon-intensive development impacts. The core forest density continues to increase and is distributed in contiguous areas; the SSP4 (uneven development) scenario regarding forest degradation is the most severe, with the dynamic rate expected to drop to −0.05% between 2050 and 2070, and a net transfer of −265,581 km². Forest fragmentation is highest, and the core density area is gradually shrinking. Cluster analysis shows that forest area remains relatively stable in most African countries, with stable countries accounting for as much as 95.49% under scenario SSP5. Regions with woodland expansion are mainly distributed in North Africa and localized parts of Southern Africa. After refinement using independent tree-density evidence, woodland expansion in South Africa is shown to be more limited and spatially heterogeneous; these newly expanded woodlands are mostly artificial plantations and alien invasive tree stands rather than native natural woodlands, mainly occurring in eastern and southeastern areas rather than in arid western regions. The spatiotemporal transfer process exhibits significant periodic differentiation, with 2030–2050 being a critical transitional period for forest change, and the differentiation effect between scenarios intensifying. Fragmentation analysis indicates that scenario SSP3 (regional rivalry, with moderate population growth and weak policy constraints) has the best forest integration and the lowest degree of fragmentation, while scenario SSP4 is most strongly affected by human activities and has the highest risk of patch fragmentation. These findings can provide a scientific basis for African countries to formulate differentiated forest protection policies and optimize ecological restoration plans, while also offering theoretical insights for continental-scale forest ecological management. 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

Organic vegetable cultivation requires soil management strategies that improve carbon balance and suppress soilborne diseases. This study evaluated the efficacy of acidified microbial biochar pellets (ABPM) in enhancing net ecosystem carbon balance (NECB) and suppressing clubroot disease (Plasmodiophora brassicae) during organic Chinese cabbage (Brassica rapa ssp. pekinensis) cultivation. In a field-scale evaluation, three treatments were compared: guano fertilizer (control), ABPM 27 (inoculated with Pseudomonas fluorescens 22BCO027), and ABPM 86 (inoculated with Bacillus megaterium 22BCO086). Soil incorporation of ABPM 27 and ABPM 86 significantly increased soil carbon sequestration by 29.1% and 22.4%, respectively, while simultaneously reducing cumulative greenhouse gas emissions under the experimental conditions. This resulted in positive NECB values of 2.63 and 2.94 t CO₂-eq ha⁻¹, suggesting enhanced carbon retention potential within the studied cultivation system. Beyond its impact on carbon dynamics, ABPM 27 increased marketable yield by 8.6% (77.4 t ha⁻¹) and reduced clubroot incidence by 46.2%. Rhizosphere microbial analysis revealed that ABPM 27 promoted late-season microbial diversity and the persistence of beneficial Bacillus spp. and Pseudomonas spp. populations. These findings suggest the potential multifunctional role of microbially engineered biochar pellets in improving crop production, carbon retention, and pathogen suppression under organic cultivation conditions. However, these findings are based on a single-season field experiment and NECB-based carbon balance estimates, and therefore require validation across multiple growing seasons and cultivation environments. Full article

Net ecosystem productivity (NEP) reflects the net carbon balance of forest ecosystems and is widely used to evaluate their carbon sink capacity. For the Ganjiang River Basin, identifying where forest NEP is high or low and explaining its controlling factors can support more targeted carbon sink management. However, under complex environmental conditions, the nonlinear responses of NEP and the differences among vegetation types are still not fully clear. In this study, forest NEP in the middle and upper reaches of the Ganjiang River Basin was estimated for 2023. An XGBoost–SHAP framework was then used to examine the effects of climatic, topographic, and stand structural factors and to identify possible threshold responses. The results showed that forest NEP had clear spatial differences. High NEP values were mainly distributed in peripheral areas, whereas low values were concentrated in the central region. The spatial distribution also showed significant positive autocorrelation. At the regional scale, elevation (DEM), mean annual temperature (TEMP), and vapor pressure deficit (VPD) were the dominant factors affecting NEP. However, the main drivers varied among different vegetation types. The SHAP results further indicated that several factors had nonlinear threshold effects. Precipitation showed an inhibitory effect within 1400–1680 mm, and VPD showed a similar negative response within 0.48–0.54 kPa. These results help explain the formation of regional forest carbon sinks and provide a reference for forest-type-specific ecological management. Full article

Soil Organic Matter (SOM) and Soil Organic Carbon (SOC) are essential for regulating ecosystem functions, soil fertility, and influencing climate change processes, especially in semi-arid regions. The recent improvements in remote sensing instruments and the development of artificial intelligence methodologies, such as machine learning, enable an improved understanding of carbon dynamics, facilitate the estimation of SOC content, and support predictive modeling. This study presents an integrated framework to analyze past and future carbon dynamics in the Sfax Governorate (Tunisia). Land-use and land-cover (LULC) maps for the years 2019, 2020, 2022, and 2024 were generated using a Random Forest algorithm applied to multispectral satellite data in the Google Earth Engine platform, achieving high classification accuracy (overall accuracy up to 0.90). Carbon stocks and their temporal variations were estimated using the InVEST Carbon Storage and Sequestration model, while carbon emissions and the Net Ecosystem Carbon Balance (NECB) were derived by integrating land-use-specific emission factors. Future LULC scenarios for 2030 were simulated through a Cellular Automata model under three alternative development pathways: conservation-oriented (CONS), business-as-usual (BAU), and urban expansion (URB+). The study demonstrates how the integration of machine learning, remote sensing, and ecosystem modeling supports spatially explicit assessment of SOC-related carbon dynamics and provides useful insights for land management and climate mitigation strategies. Full article

Against the backdrop of global climate change and the “carbon neutrality” target, the ecological quality improvement of the Loess Plateau—a key region for ecological restoration in China—and its impact on vegetation carbon sources hold significant importance for regional carbon balance and ecological security. Based on MODIS and meteorological reanalysis data from 2002 to 2024, this study constructed the Remote Sensing Ecological Index (RSEI). Combined with a carbon source/sink model, it systematically assessed the spatiotemporal coupling evolution characteristics of ecological environment quality and vegetation carbon storage capacity in the Loess Plateau, and explored the synergistic driving mechanisms of major hydrothermal and surface factors. The results indicate the following: (1) From 2002 to 2024, the ecological environment of the Loess Plateau improved significantly, with the RSEI rising from moderate to good. This improvement was accompanied by a marked decrease in surface dryness, an increase in surface wetness, and notable growth in vegetation cover, revealing a positive coupling relationship characterized by “reduced surface dryness—increased surface wetness—enhanced vegetation restoration.” (2) Regional vegetation carbon storage capacity strengthened markedly. Gross Primary Productivity (GPP), Net Primary Productivity (NPP), and Net Ecosystem Productivity (NEP) all showed significant increasing trends, and the proportion of area classified as carbon sink increased substantially. (3) Spatially, carbon sink distribution exhibited a pattern of “higher in the southeast, lower in the northwest.” Sub-regions A and D were identified as core areas with higher ecological quality and carbon sink capacity, whereas sub-regions B and C were more ecologically fragile and served as primary carbon source areas. (4) The implementation of soil and water conservation measures on the Loess Plateau has effectively enhanced regional carbon storage capacity. Vegetation restoration, improved water conditions, and reduced surface dryness have jointly driven the transition of the Loess Plateau ecosystem from a “vulnerable type” to a “recovering type”, while ecological restoration projects have played a certain role in enhancing the carbon sink. This study provides a theoretical basis and scientific–technological support for ecological protection and high-quality development in the Yellow River Basin. Full article

Globally, greenhouse gas (GHG) emissions have risen dramatically due to accelerated industrialization, excessive fossil fuel extraction, and agricultural activities, leading to global warming and ecosystem collapse. Achieving net-zero carbon emissions has therefore become a crucial global priority. Despite substantial international efforts, only a small number of countries have achieved carbon neutrality so far, with the majority aiming to do so by 2050 or 2060. Progress remains hindered by fragmented international coordination and inadequate integration of mitigation and adaptation co-benefits. However, agriculture is a major carbon emitter with significant mitigation potential. Attaining local carbon neutrality in agricultural landscapes is highly costly and strongly impacted by the spatial heterogeneity of GHG emissions and the diversity of available mitigation possibilities. This sector remains a major contributor to methane (CH₄) and nitrous oxide (N₂O) emissions, mainly through enteric fermentation and fertilizer use, and thus must be prioritized in global carbon neutrality strategies. Tactics such as improved livestock management, reduced use of synthetic fertilizers, conservation agriculture, afforestation, and renewable energy adoption can reduce emissions. These technical approaches should be supported by effective policy instruments, like carbon taxes, cap-and-trade schemes, low-carbon practice subsidies, and regulatory frameworks. Together, these measures can enable a transition toward long-term sustainability in agriculture by balancing emissions with removals through enhanced carbon sinks and credible offset mechanisms. Full article

Robust quantification of greenhouse gas (GHG) balances in tea plantations is critical for evaluating their contribution to agricultural carbon neutrality. This study aimed to develop data-driven models to quantify soil organic carbon (SOC) sequestration and N₂O emissions in Chinese tea plantations, evaluate their net GHG balance at the national scale, and assess the mitigation potential under alternative nitrogen management scenarios. Using a comprehensive national dataset, we compared multiple machine learning (ML) approaches with a conventional multiple linear regression (MLR) model to simulate N₂O emissions and SOC changes in Chinese tea plantations. All ML models substantially outperformed the MLR model, with the Random Forest (RF) algorithm achieving the highest predictive accuracy. The RF models yielded R² values of 0.68 for N₂O emissions and 0.67 for SOC changes, with no significant prediction bias. Variable importance and marginal effect analyses revealed strong non-linear controls. Mineral N fertilizer input was the dominant driver of N₂O emissions, followed by organic N input, soil clay content, and SOC. In contrast, SOC dynamics were primarily regulated by organic carbon inputs, tea plantation age, climate variables, and soil pH. National-scale simulations indicated an average N₂O emission intensity of 9.03 kg N₂O ha⁻¹ yr⁻¹ and a mean SOC sequestration rate of 0.88 t C ha⁻¹ yr⁻¹. Overall, SOC sequestration offset N₂O emissions, rendering Chinese tea plantations a net GHG sink (−2525 Gg CO₂-eq yr⁻¹). Scenario analyses showed that mineral N reduction increased net GHG uptake by 1804 Gg CO₂-eq, while organic fertilizer substitution achieved a substantially larger mitigation potential of 5961 Gg CO₂-eq. By integrating SOC sequestration and N₂O emissions within a unified modeling framework and applying machine-learning-based national-scale simulations, this study provides a more comprehensive and data-driven quantification of GHG balances in tea ecosystems, offering a scientific basis for evaluating their role in agricultural carbon neutrality strategies. Full article

Dryland farming on the Loess Plateau faces significant challenges due to water scarcity and low nitrogen use efficiency. Although conventional urea sustains crop yields, it is associated with elevated greenhouse gas emissions and nitrogen losses. Despite growing interest in both slow-release fertilizers and plastic mulching, their environmental footprints remain insufficiently evaluated. This study, therefore, aimed to identify a management strategy that maximizes productivity while minimizing environmental impacts. Using a life-cycle assessment (LCA) framework, we compared four cultivation strategies, flat cultivation with urea (NU), flat cultivation with slow-release fertilizer (NS), mulching with urea (PU), and mulching with slow-release fertilizer (PS), each at nitrogen rates of 125, 225, and 325 kg ha⁻¹. The results demonstrated that PS reduced the carbon footprint per unit of net ecosystem economic benefits (NEEB) by 3.74–27.86% and the nitrogen footprint per unit of NEEB by 10.48–47.41%. At 225 kg ha⁻¹, PS increased grain yield and NEEB by 7.40% and 9.87%, respectively, compared to 125 kg ha⁻¹. Compared to 325 kg ha⁻¹, the 225 kg ha⁻¹ rate improved energy use efficiency by 19.81% while reducing carbon emissions, carbon, and nitrogen footprint per unit of NEEB by 10.29%, 14.36%, and 24.47%, respectively. In conclusion, mulching combined with slow-release fertilizer at 225 kg ha⁻¹ represents a balanced and regionally appropriate strategy, achieving strong agronomic performance alongside reduced environmental costs and improved economic returns. Full article

Our work develops the financial engineering module of the REGENerative Agriculture (REGENA) Production Function, with Soil Organic Carbon (SOC) as ecosystem service and contract underlying index, contributing to the global literature and business practices. Specifically, we design and engineer a 30-year Net Present Value (NPV) intergenerational ecological bond instrument tailored for carbon farming (CF) as a part of regenerative practices. With SOC constituting a fundamental soil health indicator for the European Union Soil Observatory (EUSO), we model the flow of value from atmospheric CO₂ removal and its metabolism into SOC within a stochastic SOC Value at Risk (VaR) framework. We assess the SOC VaR in five experimental plots in five Mediterranean countries in South Europe and North Africa for three different treatments in each plot. In turn, the SOC VaR is incorporated into an adjusted Shannon entropy index (H(X)_ADJ) to estimate the coefficient of a positive, net-zero, or negative carbon balance and further assess the risk-adjusted discount rate. The monetary value per gram of carbon per kilogram of soil (g C/kg Soil) signifies a clear advantage of combined regenerative treatments. Finally, three selected extensions of our work are discussed, such as the application of the framework to other nutrients, the establishment full cost–benefit accounting methods for monetizing the environmental benefits of CF to upscale investments and the lifecycle accounting of ecosystem services. Full article

Forest ecosystems play a pivotal role in maintaining the balance of the global carbon cycle and conserving biodiversity. High-density point clouds derived from unmanned aerial vehicle (UAV) structure from motion (SfM) and multi-view stereo (MVS) technologies offer a cost-effective solution for data acquisition. These technologies have become efficient tools for facilitating precision forest resource management and extracting individual tree structural parameters. However, in complex forest scenarios during the leaf-off season, canopies exhibit unstructured branch network morphologies due to the absence of leaf occlusion, and adjacent crowns are heavily interlaced. Consequently, existing segmentation methods struggle to overcome challenges associated with fuzzy boundaries and instance adhesion. To address these challenges, this study proposes TreeSeg-Net, an end-to-end instance segmentation network designed to precisely separate individual trees directly from raw point clouds. The network incorporates a global context attention module (GCAM) to capture long-range feature dependencies, thereby compensating for the limitations of sparse convolution in perceiving global information. Simultaneously, a spatial proximity weighting module (SPWM) is designed. By introducing geometric center constraints and a distance penalty mechanism, this module effectively mitigates under-segmentation issues caused by the feature similarity of adjacent branches in high-canopy-density environments. Experimental results demonstrate that TreeSeg-Net achieves an average precision (AP) of 97.2% in instance segmentation tasks and a mean intersection over union (mIoU) of 99.7% in semantic segmentation tasks. Compared to mainstream networks, the proposed method exhibits superior segmentation accuracy, providing an efficient and automated technical solution for precise resource inventory in complex forest environments. Full article

The adoption of conservation systems in agriculture has been increasingly explored as a strategy to improve soil quality and potentially influence greenhouse gas (GHG) emissions. This study reports the first assessment of GHG emissions within a long-term (14 years) agroecological field experiment evaluating soil management systems for onion (Allium cepa L.) production in a Humic Dystrudept (Cambissolo Húmico Distrófico, Brazilian Soil Classification System) in Southern Brazil. Three management systems based on permanent soil cover and crop diversification were evaluated in an onion–maize rotation: conventional tillage (CT) without cover crops, no-till (NT) without cover crops, and a no-till vegetable system (NTV) with a summer cover crop mixture of pearl millet (Pennisetum americanum), velvet bean (Mucuna aterrima), and sunflower (Helianthus annuus). Short-term GHG emissions were monitored during one onion growing season (106 days), while soil chemical and physical properties reflect long-term management effects. Evaluations included (i) daily and cumulative GHG (N₂O, CH₄, and CO₂) emissions, (ii) soil carbon (C) and nitrogen (N) stocks, (iii) soil aggregation, porosity, and bulk density in different soil layers (0.00–0.05, 0.05–0.10, and 0.10–0.30 m), and (iv) onion yield and cover crop dry matter production. The NTV system improved soil physical and chemical quality and increased onion yield compared to NT and CT. However, higher cumulative N₂O emissions were observed in NTV, highlighting a short-term trade-off between increased N₂O emissions and long-term improvements in soil quality and crop productivity. All systems acted as methane sinks, with greater CH₄ uptake under NTV. Despite higher short-term emissions, the NTV system maintained a positive C balance due to long-term C accumulation in soil. Short-term greenhouse gas emissions were assessed during a single onion growing season, whereas soil carbon stocks reflect long-term management effects; CO₂ fluxes measured using static chambers represent ecosystem respiration rather than net ecosystem carbon balance. These results provide an initial baseline of GHG dynamics within a long-term agroecological system and support future multi-year assessments aimed at refining mitigation strategies in diversified vegetable production systems. Full article

Banana plantations are important tropical agro-ecosystems, and quantifying their greenhouse gas emissions is essential for developing low-carbon agriculture and mitigating global warming. The carbon balance of two banana cultivars (Musa paradisiaca AA (MA) and M. AAA Cavendish var. Brazil (MB)) was evaluated using the life cycle assessment (LCA) approach, based on field trials and farmer surveys in Chengmai County, Hainan Province, China. The results indicated that (1) both cultivation systems functioned as net carbon sinks, and the MB cultivar demonstrated a superior carbon balance, with a net sequestration of 21,652.88 kg CO₂ eq·ha⁻¹, significantly higher than the MA cultivar (15,197.96 kg CO₂ eq·ha⁻¹); (2) fertilizer management was the dominant source of anthropogenic emissions, contributing 74.03–81.76% of the carbon footprint from agricultural inputs; and (3) the MB cultivar’s enhanced carbon fixation capacity outweighed its higher emissions, resulting in a more favorable carbon balance than the MA cultivar. Concurrently, the banana plantations significantly increased soil carbon sequestration by 13.47–24.48%. Thus, within the studied system boundary, banana agro-ecosystems serve as net carbon sinks, a function that can be enhanced by optimizing fertilizer management to reduce emissions and by increasing both plant biomass and soil carbon sequestration. These results provide a scientific basis for low-carbon practices and promoting a more sustainable banana industry. Full article

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