The evaluation of ecological environment quality and the analysis of the causes of ecological change are important aspects of regional ecological management. In this study, based on the factors of greenness (NDVI), humidity (WET), heat (LST), and dryness (NDBSI), the salinity index (SI) was introduced to build an improved ecological remote sensing index (MRSEI). The spatial and temporal distribution pattern and driving mechanism of eco-environmental quality in the Beibu Gulf port area from 2000 to 2024 were analyzed. The results showed as follows: ① From 2000 to 2024, the overall ecological environment quality in the study area showed a slow improvement trend, and the MRSEI grade was mainly in the middle level, with the average annual value ranging from 0.25 to 0.68, showing a spatial distribution pattern of high in the west and low in the east. ② There was a strong spatial autocorrelation of ecological environment quality in the study area. The spatial aggregation patterns were mainly H-H and L-L. The H-H gathering area was mainly forest land and mountain, and the L-L gathering area was mainly agricultural land and construction land. ③ In 2000-2024, the area of ecological environment quality improvement was significantly larger than the area of degradation, and the area of no significant improvement and significant degradation was the most extensive. The future change trend is mainly future degradation. ④ The ecological environment quality in the study area was influenced by both natural and human factors. Among them, the average annual temperature had the strongest explanatory power, followed by evapotranspiration, slope, distance to artificial surface, and NPP. The interaction of all factors increased to a certain extent, and the interaction effect of average annual temperature and evapotranspiration was the strongest.

During rapid urbanization, the total area of green space in Guangzhou remained relatively stable; however, its spatial structure changed substantially. Green space became increasingly fragmented, patch shapes grew more complex, and overall connectivity declined, indicating a systematic degradation of green space structure rather than a simple reduction in area. Land-use transition analysis shows that the continuous conversion of farmland and grassland into construction land was the dominant process driving green space fragmentation during the study period. This suggests that urban expansion primarily reshaped the internal configuration of green space instead of directly reducing its total extent. Spatial econometric results reveal significant spatial dependence in green space dynamics, as indicated by a positive and significant spatial lag coefficient in the spatial Durbin model, highlighting strong interregional interactions. Further decomposition of spatial effects indicates heterogeneous driving mechanisms: urbanization intensity, measured by nighttime light intensity, exerts a negative indirect effect, whereas population density and per capita GDP exhibit positive direct and indirect effects. Overall, the results support a "development pressure-ecological response" mechanism, in which urban expansion generates structural degradation and negative spatial spillovers, while socioeconomic agglomeration may, under certain conditions, produce compensatory or synergistic effects on regional green space systems.

Detecting spatiotemporal changes in ecological environment quality (EEQ) is of great importance for maintaining regional ecological security and supporting sustainable economic and social development. However, research on EEQ detection from a remote sensing perspective is insufficient, especially at the basin scale. Based on two indices, namely, the Ecological Index (EI) and the Remote Sensing Ecological Index (RSEI), we established a dual model, combining the remote sensing ecological comprehensive index (RSECI) and its differential change model, to study the spatiotemporal evolutionary characteristics of EEQ in the Lijiang River Basin (LRB) from 2000 to 2020. The RSECI combines the following five indicators: greenness, wetness, heat, dryness, and aerosol optical depth. The results of this study show that the area of good and excellent EEQ in the LRB decreased from 3676.22 km2 in 2000 to 2083.89 km2 in 2020, while the area of poor and fair EEQ increased from 80.81 km2 in 2000 to 1375.91 km2 in 2020. From 2000 to 2020, the change curve of the EEQ difference in the LRB first rose, fell, and then rose again. The wetness and greenness indicators had positive effects on promoting EEQ, while the heat, aerosol optical depth, and dryness indicators had restraining effects. The results of stepwise regression analysis showed that, among the selected indicators, wetness and greenness were the key factors for improving the EEQ in the LRB during the study period. The RSECI approach and the difference change model proposed in this study can be used to quantitatively evaluate the EEQ and facilitate the analysis of the spatial and temporal dynamic changes and difference changes in EEQ.

As a typical karst landform region, the Lijiang River Basin, located in Southwest China, is characterized by both soil erosion and ecological fragility. The transformation of land use, driven by long-term intensive human activities, has exacerbated the degradation of ecosystem services, threatening the region’s carbon sink function. To clarify the coupling mechanism between land use and land cover change (LUCC) and carbon storage, this paper integrates complex network theory with the PLUS-InVEST model framework. Based on land use data from five periods, i.e., 2001, 2006, 2011, 2016, and 2021, the key transformation types are identified, and the evolution of carbon storage from 2021 to 2041 is simulated under three scenarios, namely, inertial scenario, ecological protection scenario, and urban development scenario. The paper finds that (1) land use transformation in the basin exhibits spatial heterogeneity and network complexity, as evidenced by a significant negative correlation between the node clustering coefficient and the average path length, revealing that land type transitions possess small-world network characteristics. (2) The forested land experienced a net decrease of 196.73 km2 from 2001 to 2021, driving a 3.03% decline in carbon storage. This highlights the inhibitory effect of unregulated urban expansion on carbon sink capacity. (3) Scenario simulations indicate that the carbon storage under the ecological protection scenario will be 1.0% higher than under the inertial scenario and 1.5% higher than under the urban development scenario. These suggest that restricting impervious land expansion and promoting forest and grassland restoration can enhance carbon sink capacity. Therefore, this paper provides a quantitative basis for optimizing territorial spatial planning and coordinating the “dual carbon” goals in karst regions.

Quantitative assessment and simulation of terrestrial ecosystem carbon storage are of significant importance for future climate regulation and ecosystem management. In this paper, focusing on the Lijiang River Basin, we utilized the PLUS model and the InVEST model to evaluate the dynamic changes in land use and carbon storage from 2001 to 2041 under different development scenarios. The results indicate: (1) From 2001 to 2021, the areas of forest, shrub, grassland, and water bodies decreased, while the areas of cropland and impervious land increased. (2) Under the three scenarios, the changes in land use areas exhibited distinct characteristics. (3) From 2001 to 2021, the carbon storage in the Basin exhibited an overall declining trend. Under the scenarios of inertial development, ecological priority, and urban development, the projected carbon storage in Basin for 2041 will be 144.27×106t, 145.72×106t, and 143.8×106t, respectively. (4) The carbon storage in the karst landform area decreased by 3.85%, and the carbon storage in the non-karst landform area decreased by 2.57%. Those results suggest that implementing reasonable planning and restrictions in construction areas, as well as controlling the conversion of high carbon density land to low carbon density land, can contribute to increasing regional carbon storage. Therefore, the results obtained can provide scientific references for optimizing regional land use structure, improving regional ecosystem carbon storage, and serving the construction of Guilin National sustainable development agenda innovation demonstration zone.

Rural tourism plays a crucial role in promoting the process of urban-rural integration and regionally co-ordinated development.Drawing on theories of tourism system drive and system science,this study constructed a rural tourism system dynamics model with four subsystems:demand,supply,media,and support.Subsequently,we predicted the optimal mechanism for rural tourism development using scenario simulation methods.The find-ings were four-fold.(1)The rural tourism development dynamics system constructed in this study overcame the limitations of previous subsystem divisions.(2)Under the development scenarios of Natural development mecha-nism(NDM),Demand driven mechanism(DDM),Supply driven mechanism(SDMe),Media driven mechanism(MDM),Support driven mechanism(SDMu),and Synergistic driven mechanism(SDMy),the rural tourism devel-opment index values in 2035 were 0.678,0.702,0.755,0.715,0.776,and 0.836,respectively.Among these sce-narios,SDMy emerged as the ideal mechanism for rural tourism development in Yangshuo County.(3)Based on the characteristics of the rural tourism development index,rural tourism in Yangshuo County has undergone three stages:fluctuating growth,rapid development,and recession.(4)Yangshuo County's rural tourism supply index grows slowly and is always below 0.8,which is a key link for future structural optimization.This study proposes a direction for rural tourism development in Yangshuo and a later impetus,which can accelerate the process of ur-ban-rural integration in Yangshuo and similar areas.

Based on the panel data of Guangxi from 2005 to 2017, the spatiotemporal characteristics and determinants of urban carbon emissions in Guangxi were analyzed using the extended STIRPAT model and the Geographically and Temporally Weighted Regression (GTWR) model. The main findings of our research can be summarized as follows. While the total carbon emissions of cities in Guangxi consistently increased from 2005 to 2014, the growth trend slowed after 2014, leading to a stabilization in the total emissions. In addition, there are significant differences in the total carbon emissions among the cities. The central and northeastern regions have higher emissions, while the southwestern region has lower emissions. Finally, there are variations in the degrees and directions of the impacts that factors have on carbon emissions among the different time periods and cities. Urban land use is a key factor driving carbon emissions, and it has a negative impact on most cities in Guangxi. Meanwhile, factors such as industrial structure, population urbanization, population concentration, and economic growth have significant positive effects on carbon emissions in Guangxi. The influence of urban roads on carbon emissions is generally positive, while the degree of openness to the outside world and environmental regulations has relatively weaker impacts on emissions. In summary, in order to promote the low-carbon transition of Guangxi and achieve high-quality development, the cities in Guangxi should implement differentiated urban carbon reduction strategies that are focused on optimizing urban land use and industrial structure.

The construction of ecological safety network system plays a critical role in ecological protection and restoration for people’s welfare and national security. In order to construct a better ecological security pattern, we took the Lijiang River basin with typical karst landforms as a research example, to extract ecological source sites with landscape ecological risk and connectivity indices, to identify and grade the potential ecological corridors and nodes with the minimum cumulative resistance and gravity models, and finally to construct the regional ecological security pattern in a coordinated way the conservation of Mountains-RiversForests-Farmlands-Lakes-Grasslands-Deserts ecosystem. The results showed that:（1） The ecological risk of the Lijiang River basin was characterized as high in the center and south, and low in the east and north. The high and higher risk areas accounted 43.34% of the total watershed area.（2） There were five ecological source areas, mainly located in forests and nature reserves, accounting for 28.99%（1689.05km2） of the total watershed area.（3） Six potential ecological corridors and 38 potential ecological nodes were identified, which were concentrated in the vicinity of Lingtian town.（4） The Lijiang River basin was constructed as a protective pattern of ecological conservation, restoration, control, and corridor construction. In addition, more ecological compensation funds and techniques should be supported to Lingchuan and Xingan counties in order to ensure the successful construction of the corridor.We hope this study could provide scientific knowledge for improving the ecosystem function of the Lijiang River basin and the successful implementation of national land use plan.

The forest ecosystem is the largest carbon reservoir in the terrestrial ecosystem, with soil organic carbon (SOC) being its most important component. How does the distribution of forest SOC distribution change under the influence of regional location, forest succession, human activities, and soil depth? It is the basis for understanding and evaluating the value of forest SOC reservoirs and improving the function of forest soil carbon sinks. In this paper, soil organic carbon concentrations (SOCCs) and environmental factors were measured by setting 14 experimental plots and 42 soil sampling sites in different forest communities and different elevations in the Maoershan Mountains. The redundancy analysis (RDA) method was used to study the relationship between SOC distribution and external factors. The results show that SOC distribution was sensitive to elevation, forest community, and soil layer. It had obvious surface aggregation characteristics and increased significantly with the increase in elevation. Among them, SOCCs increase by 1.80 g/kg with every 100 m increase in elevation, and that decreased by 5.43 g/kg with every 10 cm increase in soil depth. The SOC distribution in natural forests is greater than that in plantations, and the spatial variation in SOC distribution in plantations is higher due to the effect of cutting and utilization. SOC distribution is the result of many environmental factors. The response of SOC distribution to the forest community indicates that the development of plantations into natural forests will increase SOC, and excessive interference with forests will aggravate SOC emissions. Therefore, strengthening the protection of natural forests, restoring secondary forests, and implementing scientific and reasonable plantation management are important measures for improving the SOC reservoir’s function.

Given the high degree of fragmentation and poor resistance to disturbance in karst landscapes, it is important to clarify the spatial and temporal dynamics of landscape patterns in karst areas when designing karst ecological protection strategies. Using the Li River Basin as the study area, the spatial distribution and dynamic evolution of landscape patterns in the basin were analyzed at the levels of landscape utilization, landscape type dynamics and landscape pattern indices based on the Landsat series images for 2000 to 2020 obtained from the GEE platform as the data source. The results show three important aspects of this typical karst watershed. (1) There are large differences in landscape structure and landscape type trends between the karst and non-karst areas in the Li River Basin. (2) The comprehensive landscape type dynamic attitude of the Li River Basin is 0.22%, and the composite index of landscape type use varies from 239.49 to 244.88. The degree of landscape use is higher in karst areas than in non-karst areas, and the rate of landscape change in karst areas is more intense. The integrated index of landscape use in karst areas ranges from 262.32 to 270.50, and in non-karst areas it spans 225.28 to 227.01. The integrated landscape type motility in the karst areas is 0.31%, which is about twice as high as that in non-karst areas. (3) The overall landscape evolution of the Li River Basin shows trends of increasing fragmentation, decreasing connectivity, decreasing dominance and increasing heterogeneity, and these trends are particularly prominent in the karst areas. The results of this study can provide a scientific basis for realizing the construction goals of the National Sustainable Development Innovation Demonstration Zone in Guilin, and a technical reference for the ecological environmental management of the karst watershed.

以广西兴安县华江瑶族乡高寨村为例,利用ArcGIS10.2提取村域"三生"空间景观要素,结合土地利用变更调查数据分析和实地调研,研究了村域"三生"空间利用、管控.结果表明高寨村"三生"空间以生态空间为主,其次为生产空间,生活空间面积最小;"三生"空间景观聚焦程度较好,但破碎化程度较高,形状复杂;存在生产空间效益较差、生活空间品质下降、生态空间遭受破坏等问题.为实现乡村振兴,需要加强建设用地整理、挖掘生产空间潜力、改善基础设施条件、强化生态环境治理等,进一步提高土地集约节约利用水平、激发乡村产业发展活力、营建宜居生活空间、提高生态服务功能.

为客观诊断桂林市可持续发展现状和问题,运用基于熵的城市生态系统可持续发展能力评价方法,结合联合国SDG 11可持续城市和社区目标,构建桂林城市生态系统可持续发展能力评价指标体系和评价模型,对其可持续发展能力进行评价.结果显示,在2005—2017年间:(1)随着社会经济的不断发展,桂林市社会经济生态系统对自然生态系统的压力逐渐增大,同时自然生态系统对社会经济生态系统的支持能力总体呈上升趋势;(2)桂林市生态环境保护的压力越来越大,生态环境治理和保护的力度近些年逐渐跟不上生态环境压力的增长;(3)桂林城市生态系统可持续发展能力总得分呈现较大波动,在2007—2014年呈"V"形坑,整体呈下降趋势,可持续发展能力不容乐观.最终将指标熵权与指标时间序列变化相结合分析,提出了具体的可持续发展能力提升对策,以促进桂林市可持续发展.

从时代变迁之视镜洞观中国古典园林,最具"精神"的莫过于明清江南园林.寄畅园作为江南园林的典型个案,始终受锡山秦氏家族传承之影响,彰显了不同时期的文人精神和家族风貌.其文源体现隐逸风情和诗画情意;文脉贯穿于寄畅园初建、转折、改建和兴盛各时期,从最初的山林原野到臻入佳境;文体集中体现在山水、植物和建筑方面,园林山水具有环山而园、山水相依的特点;园林植物具有错落搭配、时序有节等特点;园林建筑以"凤谷行窝"为特色,集诗书文化于一体.探析寄畅园文人精神不仅可观察江南"山水园林"之实,亦可知文学望族孝友传承之礼,以及江南文人乐知天命、隐遁自然之风骨.

In recent years, the removal of hexavalent chromium by green iron nanoparticles (FeNPs) has attracted attention due to the environmental friendliness, low price, and good durability of this adsorbent. In this paper, a new synthetic method was developed and optimized under the aspects of improved synthesis yield and Cr(VI) removal. For the first time, peel extracts of yali pear and FeSO4 were employed in the synthesis of FeNPs (YL-FeNPs), and the synthesis conditions were optimized for five factors including extraction temperature, extraction time, peel mass, Fe2+-extract ratio, and drying method. For optimized synthesis conditions, the following parameters were determined: 27 g of pear peel was extracted with 360 mL of 50 vol

The ratio between nitrogen and phosphorus (N/P) in plant leaves has been widely used to assess the availability of nutrients. However, it is challenging to rapidly and accurately estimate the leaf N/P ratio, especially for mixed forest. In this study, we collected 301 samples from nine typical karst areas in Guangxi Province during the growing season of 2018 to 2020. We then utilized five models (partial least squares regression (PLSR), backpropagation neural network (BPNN), general regression neural network (GRNN), PLSR+BPNN, and PLSR+GRNN) to estimate the leaf N/P ratio of plants based on these samples. We also applied the fractional differentiation to extract additional information from the original spectra of each sample. The results showed that the average leaf N/P ratio of plants was 17.97. Plant growth was primarily limited by phosphorus in these karst areas. The sensitive spectra to estimate leaf N/P ratio had wavelengths ranging from 400–730 nm. The prediction capabilities of these five models can be ranked in descending order as PLSR+GRNN, PLSR+BPNN, PLSR, GRNN, and BPNN when considering both accuracy and robustness. The PLSR+GRNN model yielded high R2 and performance to deviation (RPD), and low root mean squared error (RMSE) with values of 0.91, 3.15, and 1.98, respectively, for the training test and 0.81, 2.25, and 2.46, respectively, for validation test. Compared with the PLSR model, both PLSR+BPNN and PLSR+GRNN models had higher accuracy and were more stable. Moreover, both PLSR+BPNN and PLSR+GRNN models overcame the issue of overfitting, which occurs when a single model is used to predict leaf N/P ratio. Therefore, both PLSR+BPNN and PLSR+GRNN models can be used to predict the leaf N/P ratio of plants in karst areas. Fractional differentiation is a promising spectral preprocessing technique that can improve the accuracy of models. We conclude that the leaf N/P ratio of mixed forest can be effectively estimated using combined models based on field spectroradiometer data in karst areas.

According to the law of diminishing marginal utility, the marginal utility when consumers purchase a certain product shows a diminishing trend. As a special product, cultural tourism products, whether is the marginal utility produced during consumption also affected by the law of diminishing marginal utility. This paper takes “Impression Liu Sanjie” as the research object and uses a linear regression equation model to study the marginal utility of tourists “Impression Liu Sanjie” cultural tourism products. The results show that the marginal utility produced by tourists buying the cultural tourism products of “Impression Liu Sanjie” shows an obvious decreasing trend. The main reason is that the cultural tourism products of “Impression Liu Sanjie” lack innovation and strong brand characteristics, the overall scale is small, the positioning is not accurate, etc., affected by the competition of homogenized products in the surrounding area, and the return rate of tourists is low. Moreover, there is a gap between existing products and the development trend of high-end tourism, which cannot meet the needs of tourists for indepth experience and research tourism. Therefore, “Impression Liu Sanjie” needs to intensify innovation, fundamentally solve the problem of diminishing marginal utility, further stabilize the source of tourists and meet the needs of tourists for repeated consumption quality, and realize sustainable tourism development.

特色小镇是新时期新型城镇化的一种创新模式,是破除城乡二元结构,推动农村产业转型升级,实现农村经济社会发展和人民生活水平改善的重要举措.以广西恭城县莲花镇为研究对象,分析了莲花镇旅游特色小镇建设发展的资源优势、进展成效、存在问题、 发展动力等,认为莲花镇旅游特色小镇建设发展外部拉力强劲、内部推力旺盛.在新发展时期提质增效需要通过优化产业体系、 强化设施建设、 创新品牌特色、重塑发展空间、协调利益关系等路径来实现,重点是深挖传统优势,打造形成以现代生态农业为主导、休闲农业旅游为特色的高品质新型产业体系,夯实旅游特色小镇提质增效的产业基础;核心是创新农旅融合发展模式和机制,激发旅游特色小镇活力,全面提升镇域经济可持续发展能力和水平.

It is of great significance for the coordinated development of the environment and the economy to study the impact of the human driving factors of land use change (LUC) on ecosystem service value (ESV). In this study, we combined the biomass and remote sensing data of the Lijiang River Basin (LRB), which is a typical karst basin with a fragile ecological environment, to establish an ESV model to calculate the ESV. We also introduced the Lorenz curve and Gini coefficient to further analyze the impacts of the human driving factors of LUC on ESV. The results show that (1) the ESV in the LRB from 1995 to 2015 decreased from 8640.03 million yuan to 8595.38 million yuan, with a total decrease of 44.65 million yuan, indicating that the overall ESV in the region has a decreasing trend; (2) the obvious changes in land use caused a significant loss in ESV and changes in the structure of ecosystem services; and (3) the human driving factors of the total population, GDP, and urbanization rate are inversely related to the ESV in the LRB.

As one of the important concentrated manifestations of Chinese rural culture, vernacular landscape is related to the success or failure of new rural construction and village planning. How to protect the existing vernacular landscape in the practical village planning advocated by “multi-planning” and how to play the role of vernacular landscape in supporting development and protecting cultural heritage is one of the important tasks of village planning. This paper takes Changlong Village in Pinggui District, Hezhou City, Guangxi Province, as an example to explore and study the issue of planning the native landscape of Changlong Village in the multi-planning village planning, so as to provide technical support for the scientific protection and reasonable development and utilization of the native landscape for rural revitalization, and to provide reference and reference for the native landscape planning in the village planning of similar areas in China.

在旅游用地利益相关者分类基础上,明确其关系格局,探讨核心利益相关者利益诉求和策略,构建合作博弈模型并进行分析.研究表明,旅游用地效益主要来自旅游用地获取时土地自身价值价格化和开发利用后增值价值市场化,旅游用地收益按照地方政府一半、旅游企业和农民分享另一半的比例进行分配时,三方合作效果帕累托最优.同时,定价的有效性、博弈者协商和行为约束机制对旅游用地合作博弈得以实现具有重要作用.从政府平台搭建,完善农村土地交易市场,建立有效博弈者行为约束机制,增强旅游企业与农民多模式合作以降低投入成本等四个方面提出促进旅游用地健康可持续发展建议.