Search Results (139)

Objective: TNFSF13B, which encodes B-cell-activating factor (BAFF) and peptidylarginine deiminase 4 (PADI4), plays crucial roles in the pathogenesis of ANCA-associated vasculitis (AAV). This study investigated the associations of single-nucleotide polymorphisms (SNPs) in TNFSF13B/BAFF and PADI4 genes with AAV susceptibility, clinical phenotypes, and disease activity in a Guangxi Chinese population. Methods: A case–control study included 324 AAV patients and 324 healthy controls. After propensity score matching (201 pairs), genomic DNA was genotyped for TNFSF13B/BAFF rs3759467 (formerly rs386492354) and rs1041569, and PADI4 rs11203366 and rs874881 using multiplex PCR and high-throughput sequencing. Genetic associations were analyzed via logistic regression, subgroup, haplotype, and clinical correlation analyses. For each of the four SNPs separately, machine learning models (logistic regression, SVM, Random Forest, XGBoost) were built and evaluated via 5-fold cross-validation. No formal adjustment for multiple comparisons was applied due to the exploratory nature of this study. Results: For TNFSF13B/BAFF, the rs3759467 C allele was protective (dominant model OR = 0.60, p = 0.011; log-additive OR = 0.71, p = 0.020; CA haplotype OR = 0.71, p = 0.019), while the rs1041569 T allele was a risk factor (dominant model OR = 1.70, p = 0.016). Subgroup analysis revealed stronger protective effects of rs3759467 in females, Han ethnicity, and MPA patients, and stronger risk effects of rs1041569 in Han ethnicity and MPA patients. Haplotype CA was protective (OR = 0.71, p = 0.019), and TT was risk-associated (OR = 1.55, p = 0.017). Both TNFSF13B/BAFF SNPs were associated with rash and hemoptysis incidence (p < 0.05). rs1041569 was also associated with RBC (red blood cell) count and HB (hemoglobin) levels (p < 0.05). For PADI4, rs11203366 and rs874881 showed no association with AAV susceptibility (all p > 0.05). However, their genotypes were associated with disease activity (BVAS, Birmingham Vasculitis Activity Score), RBC count, and HB levels (p < 0.05). Although machine learning was applied to explore predictive patterns, its performance was suboptimal (AUC < 0.6), indicating limited clinical applicability. Accordingly, the primary findings rely on the genetic model analysis, and the machine learning results should not be overinterpreted as clinically actionable. SHAP analysis indicated that risk-associated genotypes contributed most to model predictions. Conclusions:TNFSF13B/BAFF gene polymorphisms rs3759467 and rs1041569 were associated with AAV susceptibility in this Guangxi cohort, influencing clinical manifestations like rash, hemoptysis, and anemia severity. PADI4 polymorphisms rs11203366 and rs874881 are not associated with susceptibility but may correlate with disease activity and hematological parameters. These findings highlight the ethnic and clinical subtype specificity of genetic influences in AAV. Due to the lack of external validation, these findings are exploratory and require replication. Full article

Ecologically fragile hilly areas are key regions for safeguarding national ecological security and advancing ecological civilization construction. Accurate assessment of ecosystem service value (ESV) and future scenario simulations in these regions is crucial for improving regional land use and attaining sustainable development. Based on high-resolution remote sensing data of the Longji Mountain area in Guangxi, China, from 2013 to 2023, this study systematically assesses the spatiotemporal evolution characteristics of ESV using the equivalent factor method with localized corrections. This study adopts spatial autocorrelation analysis, geographic modeling, and scenario simulation. It predicts the spatial patterns of ESV for 2028 and 2033 under three scenarios: ecological protection, natural development, and tourism development. The results reveal that: (1) from 2013 to 2023, the total ESV in the Longji Mountain area showed an overall fluctuating trend. It increased first, then declined and recovered slightly, with an average annual growth rate of −0.15%. Spatially, the ESV presented a heterogeneous pattern, characterized by “high-value agglomeration in forest land, medium-value transition in terraced fields, and low-value interpolation in constructed areas”, with distinct clustering features; (2) regional ecological functions are mainly dominated by regulating and supporting services. Climate regulation contributes the highest value. Water supply is the only service with negative value, indicating a persistent water ecological deficit that remains unaddressed; (3) scenario simulations reveal that the total ESV is highest and spatial connectivity is strongest under the ecological protection scenario. Furthermore, a consistent trend is observed across all three scenarios: high-value ESV areas tend to become dominant, while spatial connectivity shows progressive enhancement. The human–land system coupling framework for the ecologically fragile hilly region suggests that ecologically oriented decision-making is the core pathway to sustainably improve ecosystem services and realize regional sustainable development. This study offers scientific support for regional ecological conservation and sustainable advancement. Full article

Due to its unique hydrogeological conditions, the Southwest Karst Area (SKA) in China experiences droughts far more frequently than non-karst regions. Exploring the distribution patterns and driving factors of different drought types is crucial for enhancing the region’s disaster prevention and mitigation capabilities and effectively addressing climate change risks. Using meteorological data from 1979 to 2023 in the SKA—including precipitation, temperature, humidity, potential evapotranspiration, and soil moisture—this study employed Copula theory to construct the Standardized Temperature Deficit Index (SDTI), the Standardized Humidity–Temperature Deficit Index (SDHTI), and the Standardized Atmosphere–Soil Index (SASI). Based on these indices and run theory, this study revealed the spatial distribution characteristics of different drought types (general, atmospheric, and composite) in terms of intensity, frequency, severity, and duration. Furthermore, the Mann–Kendall test and random forest analysis were applied to investigate drought trends and primary driving factors. The results indicate that droughts in the SKA exhibit significant regional characteristics and an overall worsening trend. Among them, droughts in karst-developed regions are generally more severe, though their manifestations vary across areas: compound droughts are particularly severe on the western Sichuan Plateau but relatively mild in Guangxi. In contrast, atmospheric droughts are more pronounced in Guangxi. Regarding trends, the rate of drought intensification was relatively moderate in Guangxi and the western Sichuan Plateau but more pronounced in other regions, with the maximum increase reaching 0.59. However, this upward trend is not statistically significant. Additionally, drought in karst areas was characterized by high frequency and intensity but shorter duration and lower severity, whereas the opposite was true in non-karst areas. Random forest analysis revealed that temperature is the primary driver of SDTI (2.60), while relative humidity and temperature have significant impacts on SDHTI (3.21 and 2.42, respectively). Soil moisture and temperature contribute most significantly to SASI (2.08 and 1.48, respectively). These findings provide important insights to guide the rational allocation of regional water resources and optimize agricultural management strategies. Full article

Volatile organic compounds (VOCs) are key precursors of ozone (O₃) and secondary organic aerosols (SOA), among which biogenic VOCs (BVOCs) constitute the dominant natural source. However, large uncertainties remain in the magnitude, spatial distribution, and seasonal variability of BVOC emissions in China under rapidly changing vegetation and climate conditions. In this study, a refined BVOC emission inventory for China in 2023 was developed using the Model of Emissions of Gases and Aerosols from Nature (MEGAN v3.2) driven by WRF meteorological simulations and MODIS vegetation data. The estimated annual BVOC emissions reached 41.70 Tg, including 26.90 Tg isoprene, 4.84 Tg monoterpenes, 0.55 Tg sesquiterpenes, and 9.41 Tg other VOCs. The corresponding ozone formation potential (OFP) and secondary organic aerosol formation potential (SOAFP) were 346.12 Tg yr⁻¹ and 2137.51 Gg yr⁻¹, respectively. Emissions exhibited a pronounced south–north gradient with hotspots in Guangxi, Guangdong, and Yunnan, and peaked in summer. Broadleaf forests were identified as the dominant emission sources, followed by savannas and shrublands. Isoprene contributed most to OFP, whereas monoterpenes dominated SOAFP. Compared with previous inventories, the updated vegetation data, meteorological inputs, and refined chemical speciation improve the representation of BVOC emissions and their spatial patterns in China. These results highlight the important role of BVOCs in regional O₃ and SOA formation and provide an improved emission basis for atmospheric chemistry modeling and air-quality management. Full article

The global expansion of tree plantations has led to extensive fragmentation of natural forests, posing significant challenges for biodiversity conservation. Understanding the diversity patterns and underlying mechanisms of ground-dwelling insects in these fragmented landscapes is critical to inform effective conservation strategies. To address this, we sampled ground-dwelling insects using pitfall traps across nine remnant natural forest fragments (“islands”) embedded within a tree plantation matrix in Guangxi, China. We examined insect family-level diversity and community composition in relation to fragment isolation (low vs. high) and size (large vs. small) and explored the mechanisms driving the observed patterns. Our results revealed no significant difference in ground-dwelling insect diversity between low-isolation and high-isolation fragments. However, diversity was significantly lower in smaller fragments compared to larger ones. This reduction was primarily driven by decreased seedling density within smaller fragments, directly reflecting the adverse effects of plantation-driven fragmentation on native seedling establishment. Furthermore, we observed noble shifts in community composition of ground-dwelling insects along both fragment isolation and size gradients. Highly isolated fragments exhibited a decline in phytophagous insects and omnivores (with detritivore-herbivore diets), but an increase in detritivores. Smaller fragments exhibited consistent declines across multiple insect taxa spanning various dietary guilds. The observed changes in ground-dwelling insect composition were driven by shifts in plant (especially seedling) community composition. Our findings reveal a clear cascading effect: plantation-driven fragmentation limits native plant regeneration, and these limitations subsequently propagate to higher trophic levels, profoundly impacting ground-dwelling insects. Effective restoration of plantation-fragmented landscapes requires strategies that both prioritize the preservation of large, continuous forest fragments and promote native seedling recruitment within existing fragments. Full article

Against the background of the acceleration of the integration of the “double carbon” target and transportation energy, the green transformation and business model innovation of highway service areas, as a high-energy-consumption traffic node, are becoming more and more urgent. However, the existing research focuses on a single technology path, and lacks a systematic quantitative evaluation of the “PV–charging–new format” coordination mechanism and its operating efficiency. Therefore, this paper proposes a collaborative framework that integrates photovoltaic power generation, new energy charging piles, and diversified new formats, and introduces a random forest regression algorithm. Based on the actual operation data of the Guangxi expressway service area, the synergistic effect and regional heterogeneity of multiple factors are systematically evaluated. The results show that a photovoltaic system can reduce the unit electricity price by 25–35%, and the investment recovery period is about 7 years. When the penetration rate of charging piles increases to 35%, the annual income can reach CNY 3.285 million, and the return on investment increases to 2.3 times when the utilization rate exceeds 80%. The new business combination can increase the average daily income by 13.3–26.7%. At the same time, the coordinated implementation of the three elements can achieve an annual net income increase of 27–32%, which is better than the linear superposition of the benefits of a single measure. In addition, the analysis of regional heterogeneity shows that the photovoltaic benefit in the western mountainous area is outstanding, the charging benefit in the coastal area is significant, and the comprehensive benefit in the central hub area is the best. This study provides a quantitative basis to support decisions on the differentiated development path of expressway service areas in the background of traffic–energy integration. Full article

Human activities and climate change are influencing the survival and distribution of species, threatening the current distribution pattern of biodiversity and potentially leading to the “sixth mass extinction.” The forest musk deer (Moschus berezovskii) is among the most numerous and widely distributed musk deer species in China. However, its habitat is severely threatened by human activities and climate change. Due to the lack of field surveys and research data, it is difficult to assess the threats posed by human activities and climate change effectively. In this study, we integrate the new records of forest musk deer with climate and human activity data, and apply the MaxEnt species distribution model to evaluate the impact of human activities and climate change on the forest musk deer under current conditions and future scenarios (SSP1-2.6 and SSP5-8.5 for the 2030s, 2050s, and 2070s). Our results showed that the forest musk deer prefer areas with high vegetation cover (NDVI > 0.7), low GDP, and low levels of human activity disturbance. The areas of high-suitability habitats are 90.10 × 10⁴ km², 72.85 × 10⁴ km², and 30.43 × 10⁴ km², respectively. The optimal climatic conditions are an annual precipitation (BIO12) of 750–1500 mm and a seasonal temperature variation (BIO4) of 500–600. Their occurrence probability is highest at elevations between 1500 and 3000 m. Under the current climate conditions, the area of high-suitability habitats is estimated at 5.54 × 10⁴ km², primarily distributed across central–northern Sichuan, northwestern Guangxi, and southern Gansu. Under the future climate scenarios, low and medium-suitability habitats are projected to shrink to varying degrees, whereas the high-suitability area is expected to expand, particularly under the SSP5-8.5-2030s scenario where it is projected to increase by 2.88 × 10⁴ km². The centroid of suitable habitat is projected to shift toward higher-elevation areas in northwestern China, with regional hotspots emerging in southwestern regions such as central–northern Sichuan and northwestern Guangxi. These elevational and distributional shifts highlight the vulnerability of current habitats and the importance of adaptive conservation strategies to strengthen species protection, including continuously advancing forest protection programs, mitigating the impact of human activities in high-altitude areas, and strengthening the protection of key areas in the southwestern region. Full article

Understanding how climate and land-use change influence habitat suitability is essential for the conservation of the François’ langur (Trachypithecus francoisi). In this study, climatic, land-use, and topographic variables were integrated to model the current distribution and future dynamics of suitable T. francoisi habitats in southwestern China. The model performed well, climatic factors were the primary determinants of distribution, particularly precipitation of the driest month (BIO14), mean diurnal temperature range (BIO2), and precipitation seasonality (BIO15); additionally, forest cover, slope, and elevation further improved model performance. Suitable habitat currently covers 53,109 km² (10.75% of the study area) and is mainly concentrated in Chongqing and Guizhou, with smaller areas in Guangxi. Future projections indicate substantial habitat redistribution and an overall decline in suitable area under both scenarios. By the 2050s and 2070s, suitable habitats will show strong spatial turnover, with coexistence of retained, newly suitable, and lost areas. Suitable habitat is projected to shift toward northern areas. These results suggest that conservation priorities should shift focus northward under climate warming, with emphasis on protecting mountainous refuges and improving habitat connectivity. Full article

The teak defoliator, Hyblaea puera, native to South Asia and Southeast Asia (e.g., India, Laos, and Myanmar), has recently caused frequent outbreaks in mangrove forests across Guangdong, Guangxi, and other regions of China. Its larvae feed extensively on the leaves of Avicennia marina, severely threatening local mangrove ecosystems. However, accurate morphological identification of H. puera across its eggs, larvae, and pupae remains challenging. Therefore, the development of rapid molecular detection methods is essential for effective pest identification and monitoring, thereby supporting timely management interventions. In this study, mitochondrial protein-coding genes (PCGs) were analyzed from H. puera and related species were analyzed. Sliding window analysis was conducted to estimate nucleotide diversity (Pi), leading to the selection of the cytochrome c oxidase subunit I (COI) gene as the optimal target. Species-specific primers were designed based on the H. puera COI sequence, and two molecular detection assays—SS-PCR and LAMP—were developed. Both assays exhibited high specificity, stability, and sensitivity, successfully amplifying target fragments from H. puera across all tested geographic populations and different developmental stages. The limit of detection of the SS-PCR method was 83 fg/µL DNA, while that of the LAMP method reached 8.3 fg/µL DNA. The newly developed assays offer reliable and robust tools: the SS-PCR method is suitable for precise, large-scale detection in laboratory settings, whereas the LAMP assay is preferable for rapid, field-based detection of H. puera. These methods contribute to the early detection and effective management of H. puera populations, thereby safeguarding mangrove ecosystems. Full article

Soil heavy metal pollution caused by mineral resource extraction activities poses a serious threat to the ecological environment within and surrounding mining areas. As a highly concealed toxic heavy metal, arsenic (As) urgently requires the establishment of efficient pollution monitoring methods to achieve pollution prevention and control, as well as environmental remediation in mining areas. This study investigated the feasibility of hyperspectral remote sensing inversion for soil heavy metal arsenic based on ZY-1 02E hyperspectral satellite imagery, focusing on a mining area and its surrounding soils in Sanlisha’an, Wuxuan County, Guangxi. Full Constrained Least Squares (FCLS) was employed to separate mixed pixels and enhance soil spectral contributions in ZY-1 02E imagery, thereby mitigating vegetation interference. Six mathematical transformations, including RT, AT, FD, RTFD, ATFD, and SD, were applied to both the original and enhanced spectra to enhance spectral features. The correlations between the transformed spectra, as well as the original image spectra (S), and soil As concentration were analyzed; then the spectra strongly correlated with soil As concentration were selected to construct Ratio Spectral Index (RSI) and Normalized Difference Spectral Index (NDSI). Correlation matrices were calculated between RSI/NDSI indices and As concentration. Sensitive features were screened using an improved Successive Projection Algorithm (SPA). As concentration inversion was also performed with four models: traditional regression models, PLSR and MLR, and ensemble learning models (RF and XGBoost). In the soil contribution-enhanced spectral modeling results, the optimal transformation–index combination is ATFD-NDSI. The performance indicators of each model are as follows: MLR test set R² = 0.65, PLSR test set R² = 0.62, RF test set R² = 0.7, and XGBoost test set R² = 0.64. The results indicate that the ATFD-NDSI-RF ensemble model provides the best performance. By integrating multiple decision trees, RF effectively handles complex nonlinear relationships, thus enhancing the accuracy and generalization ability of predication. The analysis of NDSI–ATFD–RF inversion results based on sampling points indicates that model error correlates with the pollution intensity gradient, showing greater errors, especially in high-concentration areas, but still maintaining strong correlations (tailings reservoir: r = 0.92, forested areas: r = 0.96, and cropland: r = 0.83). The spatial distribution reveals that the inversion results are closely similar to the spatial distribution of IDW interpolation. Areas with high As concentrations are concentrated in the tailings reservoir and in the southeastern part of the study area. The correlation coefficient between the inversion results and IDW interpolation is 0.6, which further verifies that the inversion results effectively reproduce the spatial distribution trend of highly polluted areas. Full article

Net solar radiation is an essential parameter that characterizes surface energy exchange and plays a critical role in climate change, solar power generation, and agricultural irrigation. Although the global GLASS surface all-wave daily net radiation (NR) product exhibits high overall accuracy, a comprehensive quality assessment for continental China remains lacking, resulting in unclear regional applicability. Therefore, this study focuses on mainland China. Based on solar net radiation observations from 50 meteorological stations (2000–2016) and 37 ecological stations (2000–2020), four evaluation metrics were used: the correlation coefficient (R), mean bias error (MBE), root mean square error (RMSE), and coefficient of determination (R²). The results indicate that, during the study period, GLASS NR showed relatively small deviations from the observed values across most regions of China, with significant discrepancies observed only in southern Yunnan, Guangdong, Guangxi, and Hainan. Seasonally, GLASS NR performed better in autumn and winter than in spring and summer. Interannually, there was only a slight decline in data quality for a few individual years; however, overall, an upward trend was observed. Regarding land cover types, GLASS NR accuracy was lower for shrublands, forests, and grasslands, whereas it performed better for other land cover types. Overall, the GLASS NR product demonstrates high accuracy and good temporal continuity across mainland China. However, significant regional variations exist, and localized applications require optimization and refinement. This study provides valuable insights for improving net radiation products across multiple spatiotemporal scales. Full article

Masson pine (Pinus massoniana Lamb.) is the most widely planted tree species in southern China, playing a critical role in forestry production and reforestation. Understanding the contribution of Masson pine plantations to biodiversity conservation is essential for sustainable land-use policies. We conducted comparative studies to examine the family diversity and composition of ground-dwelling and aerial insects in Masson pine plantations and adjacent natural forests at regional (spanning five forest types across Guangxi, China) and local (at Yachang, Guangxi) scales. We investigated the mechanisms driving the differences in insect community assemblages between the two forest types at the local scale. Our results indicated that aerial insect diversity and composition in Masson pine plantations were comparable to those in natural forests. However, ground-dwelling insects in plantations showed a significant decline in diversity and a notable shift in community composition, with a decrease in highly mobile omnivores (e.g., Drosophilidae and Nitidulidae) and an increase in crawling detritivores (e.g., Blattidae and Gryllidae). These patterns were consistent at both regional and local scales. At the local scale, the shift in ground-dwelling insect community composition was linked to decreased understory tree density (explaining 45.9% of the compositional variation), reduced litter Ca content (29.7%), and increased litter cover (13.5%) in plantations. To enhance ground-dwelling insect diversity in Masson pine plantations, mixed planting with broad-leaved species offers an effective management strategy. This approach both enriches litter nutrients and reduces needle litter accumulation, thereby supporting the recovery of understory vegetation. Full article

To clarify the spatial–temporal evolution patterns and climate-driven mechanisms of carbon sinks of forest ecosystems under climate change, we calculated the net ecosystem productivity (NEP) of forests in the Guangxi region using remote sensing and meteorological data from 2000 to 2023. By employing trend analysis, spatial clustering, the Hurst index, and climate contribution evaluation, we analyzed the spatial and temporal changes, sustainability, and the relative contribution of climate impacts on forest carbon sinks. The results are as follows: The carbon sink capacity of forests in Guangxi increased continuously from 2000 to 2023, at a rate of 3.57 g C·m⁻²·a⁻¹, reaching 39.19% higher in 2023 than in 2000. The carbon sink capacity was higher in the southwest and lower in the northeast, with hotspots mainly located in evergreen/deciduous broad-leaved forest areas. The Hurst index indicates that 84.44% of regions are likely to maintain this increasing trend, suggesting stability in forest carbon sink function. The climate contribution rate to forest carbon sinks was moderate, with significant temporal fluctuations. Temperature governed annual variation in forest carbon sinks, influencing up to 36.37% of the area. The annual average contribution rate of climate change to forest carbon sinks was 30.28%, but there were temporal fluctuations and spatial heterogeneity. Over time, climate contributions had a positive driving impact; however, extreme climate events tended to produce a negative effect. The pattern of forest carbon sinks in Guangxi showed a “heat sink-coupling” phenomenon, with 16.23% of the hotspots of forest carbon sinks coinciding with temperature control zones, highlighting the enhancing effect of temperature rise on carbon sinks against a background of water and heat synergy. This study provides a scientific basis for the assessment of forest carbon sink potential and climate suitability management in Guangxi. Full article

Symplocos is an ecologically important genus that plays vital roles in subtropical evergreen broad-leaved mountain forests, including contributing to nutrient cycling, providing shelter and habitats for various organisms, and supporting overall plant diversity across East and Southeast Asia. Many species exhibit high levels of endemism and sensitivity to environmental change. China, with its wide range of ecosystems and climatic zones, is home to 18 endemic Symplocos species. Studies revealed that global warming is driving shifts in species diversity, particularly in mountains. Our study explores the current and projected richness patterns of endemic Symplocos species in China under climate change scenarios, emphasizing the implications for conservation planning. We applied stacked species distribution models (SSDMs), using key bioclimatic and environmental variables to predict current and future habitat suitability for endemic Symplocos species, evaluated model performance through multiple accuracy metrics, and generated ensemble projections to assess richness patterns under climate change scenarios. To assess the spatial configuration and fragmentation patterns of the endemic species richness under current and future climate scenarios, landscape metrics were calculated based on classified richness maps. The produced models demonstrated high accuracy with AUC > 0.9 and TSS > 0.75, highlighting the critical role of bioclimatic variables, particularly precipitation and temperature, in shaping endemic Symplocos distribution. Our analysis identifies the current hotspots of Symplocos endemism along southeastern China, particularly in Zhejiang, Fujian, Jiangxi, Hunan, southern Anhui, and northern Guangdong and Guangxi. These areas are at high risk, with up to 35% of endemic Symplocos species richness predicted to be lost over the next 60 years due to climate change. The study predicts a high decrease in endemic Symplocos species richness, especially in South China (e.g., Fujian, Guangdong, Guizhou, Yunnan, southern Shaanxi), and mid-level decreases in East China (e.g., Heilongjiang, Jilin, eastern Inner Mongolia, Liaoning). Conversely, potential increases in endemic Symplocos species richness are projected in northern and western Xinjiang, western Tibet, and parts of eastern Sichuan, Guangxi, Hunan, Hebei, and Anhui, suggesting these regions may serve as future refugia for endemic Symplocos species. The analysis of the landscape structure and configuration revealed relatively minor but notable variations in the spatial structure of endemic Symplocos richness patterns under current and future climate scenarios. However, under the SSP585 scenario by 2080, the medium richness class showed a more pronounced decrease in aggregation index and increase in number of patches relative to other richness classes, suggesting that higher emissions may drive fragmentation of moderately rich areas, potentially isolating populations of Symplocos. These structural changes suggest a potential reduction in habitat quality and connectivity, posing significant risks to the persistence of endemic Symplocos populations, which underscores the urgent need for targeted smart-climate conservation strategies that prioritize both current hotspots and potential future refugia to enhance the resilience of endemic Symplocos forests and their ecosystems in the face of climate change. Full article

Amidst the intensifying challenges of global climate change and the increasing demand for regional sustainable development, accurately assessing the contributions and dynamic characteristics of different land-use types to regional carbon sink patterns is essential for understanding ecosystem carbon cycling mechanisms and optimizing carbon management strategies. Based on land-use and Net Primary Productivity (NPP) remote sensing data from 2018 to 2022, this study employs a land-use change coding method and a hydrothermal (temperature and precipitation) sensitivity coefficient approach to analyze the spatiotemporal variation in NPP in Guangxi Zhuang Autonomous Region and its differential responses to hydrothermal conditions. On this basis, sensitivity coefficients were calculated to assess the spatial patterns of NPP sensitivity to temperature and precipitation, revealing spatial sensitivity characteristics and potential ecological risks. The results indicate significant differences in NPP variations among different land-use types, with broadleaf forests, mixed forests, savannas, and croplands identified as the primary contributors to NPP flows. Additionally, the response of NPP to hydrothermal factors exhibits clear spatial heterogeneity: precipitation sensitivity hotspots are mainly concentrated in the northern and southern ecosystems, while temperature sensitivity hotspots are predominantly located in the northern region. Further analysis reveals that the ecosystems in the central and northern regions are more sensitive to temperature changes, whereas coastal areas exhibit higher stability. Full article