Central Yunnan Research Articles

Study on water resources carrying capacity based on Pressure-State-Response modeling: An empirical study of the urban agglomeration in Central Yunnan, China.

Water resources carrying capacity (WRCC) is the basis for sustainable regional development and an important indicator of core competitiveness, and its quantitative assessment and comparison is a key link in clarifying the development capacity of the region. The study comprehensively considers economic, social, resource, environmental and ecological factors, constructs a WRCC evaluation index system based on the Pressure-State-Response (PSR) model, adopts the entropy value method to assign weights to each index, and utilizes the set-pair analysis method and the obstacle diagnostic model to evaluate WRCC of the urban agglomerations in central Yunnan (UACY) in the period from 2008 to 2020. The results show that the comprehensive development of WRCC of UACY is characterized by stage-by-stage evolution in the time dimension, with a decreasing trend in the carrying capacity from 2008 to 2012, and an overall fluctuating upward development trend from 2013 to 2020. In the spatial dimension, Kunming's WRCC is generally poor, and Honghe and Yuxi have the greatest advantages in water resources storage and conservation capacity. The stress of water use in Kunming is higher, but Kunming has advantages in industrial structure and water resources development and utilization rate. Through the diagnosis of obstacle degree, the main obstacle factors of WRCC have large differences among cities (states), but the main subsystems constraining WRCC are all pressure subsystems. The results of the study can provide data support for water resources related policies and rational water resources dispatching in the UACY.

Association Between Glycated Hemoglobin and the Lipid Profile at the Central Yunnan Plateau: A Retrospective Study.

Dyslipidemia commonly complicates type 2 diabetes mellitus, yet the relationship between glycosylated hemoglobin and blood lipid levels remains uncertain. This retrospective cross-sectional study included 27,158 participants from the People's Hospital of Yuxi. Statistical comparisons for continuous variables utilized analysis of variance (ANOVA), while chi-square analysis was employed for categorical variables. Boxplots assessed the concentration, dispersion, and deviation of total cholesterol (TC), triglycerides (TG), low-density lipoprotein (LDL-C), and high-density lipoprotein (HDL-C) distribution. A linear regression analysis examined the association between HbA1c and lipid profile, complemented by a fitting curve to visualize trends. Participants who developed diabetes exhibited higher age and elevated Body mass index (BMI), systolic blood pressure (SBP), diastolic blood pressure (DBP), TC, TG, LDL-C, and FPG levels compared to those without diabetes (p < 0.001). Linear regression analysis demonstrated significant associations between HbA1c values and TC, TG, LDL-C, and HDL-C (p < 0.001). The plotted curve indicated that as TC, TG, and LDL levels increased, HbA1c levels rose, while HDL levels decreased. HbA1c was positively correlated with TC, TG, LDL-C, and negatively correlated with HDL-C in the population in the central Yunnan Plateau.

Newly discovered high-grade oxidized cobalt ore spot in the central Yunnan Province

Newly discovered high-grade oxidized cobalt ore spot in the central Yunnan Province

Spatiotemporal characteristics of vegetation cover change in the Central Yunnan urban agglomeration from 2000 to 2020 based on Landsat data and its driving factors

The study of dynamic changes in vegetation coverage has significant implications for urban clusters in terms of ecological environment protection, climate change research, water resource management and urban planning. A thorough understanding of the driving mechanisms behind vegetation coverage helps provide scientific basis and policy recommendations for the ecological environment protection, sustainable development and decision-making of urban clusters. Taking the central Yunnan urban cluster as an example, this study utilizes long-term Landsat remote sensing image data from 2000 to 2020 on the Google Earth Engine platform. The fractional vegetation cover (FVC) is estimated using a pixel-based binary model. The Sen’s slope, Mann–Kendall trend analysis and Hurst index methods are employed to investigate the spatiotemporal dynamic characteristics of FVC. The impacts of climate change and human activities on vegetation coverage are explored through partial correlation analysis and residual analysis. Finally, considering natural factors such as topography and climate, as well as socioeconomic factors, the geographic detector is used to quantitatively analyze the driving factors behind FVC changes. The results indicate that: (1) From 2000 to 2020, the FVC in the central Yunnan urban cluster changed significantly, showing an overall improvement trend. The average FVC is 0.496 with a growth rate of 0.0024 per year, and it exhibits a distribution pattern of higher values in the west and lower values in the east. (2) In terms of percentage distribution, areas with low FVC and high FVC account for a relatively high proportion. The trend of FVC changes is as follows: improvement (49.6%) > degradation (26.4%) > no change (24%). The average Hurst value is 0.45, indicating that future FVC changes in the study area will be opposite to the past. (3) FVC shows a positive correlation with precipitation and a negative correlation with temperature. Human activities have a positive impact on FVC in the study area, accounting for 55.1% of the regional proportion. (4) Slope and nighttime light contribute the most to FVC. The explanatory power of the interaction between slope and precipitation/temperature is the most significant.

Analysis on the spatial dynamic characteristics of land use in the urban agglomeration in central Yunnan based on random forest algorithm

Analysis on the spatial dynamic characteristics of land use in the urban agglomeration in central Yunnan based on random forest algorithm

Expansion and contraction of lake basin shape the genetic structure of Sinocyclocheilus (Osteichthyes: Cypriniformes: Cyprinidae) populations in Central Yunnan, China.

Geological events can strongly affect the genetic structures and differentiation of fish populations. Especially, as an endemic fish of the genus Sinocyclocheilus in the Yunnan-Guizhou Plateau, the effects of key geological events on the distributions and genetic structures remain poorly understood. Examining the phylogeographic patterns of Sinocyclocheilus fishes can be useful for elucidating the spatio-temporal dynamics of their population size, dispersal history and extent of geographical isolation, thereby providing a theoretical basis for their protection. Here, we used single nucleotide polymorphisms (SNP) method to investigate the phylogeographic patterns of Sinocyclocheilus fishes. Our analysis supports the endemicity of Sinocyclocheilus, but the samples of different regions of Sinocyclocheilus contain multiple ancestral components, which displayed more admixed and diversified genetic components, this may be due to the polymorphism of the ancestors themselves, or gene infiltration caused by hybridization between adjacent species of Sinocyclocheilus. We estimate that the most recent common ancestor (MRCA) of Sinocyclocheilus fish in the Central Yunnan Basin at approximately 3.75~3.11 Ma, and infer that the evolution of Sinocyclocheilus in the central Yunnan Basin is closely related to the formation of plateau lakes (around 4.0~0.02 Ma), and identifies the formation of Dianchi Lake and Fuxian Lake as key geological events shaping Sinocyclocheilus population structure. It is also the first time to prove that the altitude change has a great influence on the genetic variation among the populations of Sinocyclocheilus.

Spatiotemporal evolution and Sustainably comprehensive zoning optimization of production–living–ecological functions in the Mountain–Flatland areas

Examining the spatiotemporal changes of territorial space is crucial for addressing the conflict between economic-social development and the natural environment and achieving optimal territorial space utilization. However, there is a research gap regarding the spatial characteristics and optimization in the mountain–flatland area. To address this gap, this paper focuses on the urban agglomeration in Central Yunnan (UACY) as a representative mountain-flatland area. A mountain–flatland classification model was established. Based on the evaluation of production– living– ecological functions, the economic models were introduced to measure the balance degree, and further researched the spatiotemporal evolution and coupling coordination characteristics by spatial analysis from 2010 to 2020. The findings indicate the following: (1) The study area exhibited distinct mountain-flatland differentiation, with "western mountainous counties (MCs)/semi-mountainous and semi-flatland counties (SMSFCs), central flatland counties (FCs), and eastern SMSFCs". production function (PF) primarily formed a cluster in the central-northeastern areas of FCs and of SMSFCs, living function (LF) was highly clustered in the central areas of FCs, remained stable, and ecological function (EF) was significantly clustered in the northwestern regions of MCs and of SMSFCs, significantly enhanced in the northeast. (2) The imbalance degree followed the order LF > PF > EF, showing a decreasing trend primarily driven by intra-group imbalances within FCs, SMSFCs, and MCs. The coordinate areas were mainly concentrated in central FCs, and the dysfunctional areas was largely located in MCs and SMSFCs, the degree was improved, especially in northwestern and southeastern MCs and SMSFCs. (3) The study area fell into 18 functional areas, optimized into 13 areas, with recommendations for differentiated development control paths to achieve an optimization of PLEFs. These results provide theoretical references for promoting sustainable utilization of territorial resources and facilitating high-quality regional development in UACY and other parts of the country.

New early Oligocene age for the Mouding Basin, Southwestern China: Source and paleoenvironment

Sedimentary basins in the southeastern margin of the Tibetan Plateau yield valuable geophysical and fossil records, documenting the paleoenvironmental and biodiversity changes in the Tibetan Plateau and the Hengduan Mountains. Constraining the age of sediment deposition is fundamental in understanding the evolutionary history of biodiversity, climate (e.g. development of the monsoon), and regional landscape changes. Many basins in this area were originally considered as Miocene basins based on regional lithostratigraphic comparison and biostratigraphy, although this has been challenged recently for several basins (e.g. Lühe, Markma, Jianchuan, Wenshan and Relu basins). Here we report a new age for the Mouding Basin, Central Yunnan, China. We arrive at an early Oligocene (33 ± 1 Ma) instead of a Miocene age for the fossil-bearing strata of this basin. UPb and 40Ar/39Ar dating of a volcanic ash layer from the Mouding Basin and one from the Lühe Basin in combination with zircon Hf isotope data suggest that the early Oligocene Laojiezi eruption is a likely source for ash layers in both basins. Fossilized dicot leaves were used to reconstruct the paleoclimate and the paleo-elevation of the Mouding Basin. This paleoclimate reconstruction indicates that the paleoclimate in the Mouding Basin closely resembles that of the Lühe Basin. The paleoclimate between the two floras is in fact more similar than their respective modern climates. During the early Oligocene, the Mouding Basin experienced colder and more humid winters with a milder monsoonal climate compared to today. Despite this, the Mouding flora exhibits high floristic similarities with its contemporary Lühe and Markam floras, as well as with the modern vegetation in southwestern China, supporting that the modernization of the biodiversity in the SE margin of the Tibetan Plateau has initiated since the Paleogene.

Landscape Ecological Risk Assessment and Spatial Pattern Evolution Analysis of the Central Yunnan Urban Agglomeration from 1995 to 2020 Based on Land Use/Cover Change

The central Yunnan urban agglomeration represents a typical urban cluster in the southwestern region of China. The swift urbanization and land use changes in this region pose a severe threat to the ecosystem. A thorough assessment of the landscape ecological risk in the central Yunnan urban agglomeration holds paramount importance for devising effective risk management strategies and sustainable, high-quality development plans. This study utilizes long-term land-use raster data for six time periods (1995, 2000, 2005, 2010, 2015, and 2020) in the Central Yunnan urban agglomeration. Using GIS technology, a landscape risk index model is constructed, and a comprehensive assessment of landscape ecological risks in the Central Yunnan urban agglomeration is conducted using the 5 km × 5 km grid analysis method and Kriging interpolation. The results indicate that, between 1995 and 2020, the Central Yunnan urban agglomeration was dominated by forest land, grassland, and cultivated land as the primary land-use types. Forest land covered over 48% of the total area, while grassland and cultivated land accounted for more than 26% and 18%, respectively. Notably, construction land underwent a significant increase, mainly due to conversions from cultivated land, forest land, and grassland. Over a span of 25 years, the study area has experienced a continual rise in landscape ecological risk. The landscape ecological risk was mainly characterized by medium, higher, and high ecological risk. Grassland predominated in areas with medium levels of ecological risk, while cultivated land and construction land were predominant in regions with higher and high levels of ecological risk. Spatially, regions with lower ecological risk were primarily distributed in the Chuxiong Yi Autonomous Prefecture, whereas areas with higher and high levels of ecological risk were concentrated in Qujing City and Kunming City. The spatial aggregation patterns of landscape ecological risk in the Central Yunnan urban agglomeration featured “high–high” (H–H) and “low–low” (L–L) clusters, both displaying an initial increase followed by a decrease. The primary factors contributing to the rise in the landscape ecological risk index were identified as urban expansion, population growth, ecological fragmentation, and vegetation destruction. The study’s outcomes can offer valuable insights for optimizing land resources and promoting sustainable development in the Central Yunnan urban agglomeration.

Characteristics of relative tectonic activity in the Longchuan River Basin, central Yunnan: evidence from digital elevation model-based geomorphological analysis

Characteristics of relative tectonic activity in the Longchuan River Basin, central Yunnan: evidence from digital elevation model-based geomorphological analysis

Spatial and temporal variations of vegetation phenology and its response to urbanization in central Yunnan urban agglomeration, Southwest China

Vegetation phenology is an important sensor that responds to environmental changes. Based on MOD13Q1 EVI data, we used the dynamic threshold method to extract vegetation phenological parameters of the central Yunnan urban agglomeration from 2001 to 2020, namely the start of growing season, the end of growing season, and the length of growing season, aiming to reveal the spatiotemporal variations in vegetation phenology and urban-rural differences. The results showed that vegetation phenology of the central Yunnan urban agglomeration from 2001 to 2020 generally showed a phenomenon of delayed start of growing season, delayed the end of growing season (0.66 days per year), and prolonged growing season. Compared with suburban and rural areas, growing season in urban areas in the past 20 years had started earlier (1.05 days per year), ended later (0.91 days per year), and thus growing season had been prolonged (1.79 days per year). Vegetation phenology showed significant difference on the gradient of urban, suburban, and rural areas. The start and the end of growing season of urban vegetation were the earliest, and the length of growing season was the longest, with the most significant changes in the urban areas and within the range of 0-2 km outward. The start of growing season in urban area was significantly earlier, the end of growing season was significantly delayed, and length of growing season was prolonged significantly with the increase of population density, per capita GDP, and the proportion of built-up area. The sensitivity of different phenological periods of vegetation and their duration to environmental changes varied on the gradient of urban, suburban and rural areas. Population density and proportion of built-up area in the study area played an important role in delaying the end of growing season of vegetation in the central Yunnan urban agglomeration.

Identification of critical ecological restoration and early warning regions in the five-lakes basin of central Yunnan

The scientific determination of crucial regions for ecological land restoration and reasonable early warnings for ecologically weak areas are vital for implementing land ecological restoration. Five major plateau lake basins in central Yunnan (China) are selected as the study area in this research. An ecological security pattern (ESP) is constructed using the source-resistance surface-corridor-pinch point framework to effectively identify crucial areas for ecological restoration. Finally, the land use/cover change (LUCC) in the study region in 2030 is simulated in terms of the natural development prospect (NDP), with priority given to urban development (PUD) and priority given to ecological protection (PEP) scenarios, and identify areas where future urban expansion poses a threat to current ecological source areas and corridors as early warning regions. The results indicate the following: (1) There are 15 ecological source regions in the Five Lakes Basin, mainly forestland and waters, with a total area of 787.54 km2. The ecological corridor spans 245.72 km, with a total area of 439.90 km2. (2) The key ecological restoration areas include 72.87 km2 of ecological pinch points, 70.46 km2 of barrier points of ecological, and 71 breakpoints. (3) The ecological land under the NDP scenario and the PUD scenario were damaged to varying degrees. The ecological land dominated by forestland and water area under the PEP scenario is effectively protected. (4) The seven ecological protection space early warning points are mainly distributed in the eastern part of Dianchi Lake and the northern part of Fuxian Lake, which have good economic development and better habitat quality. The comprehensive analysis identified key ecological restoration areas and identified future ecological stresses due to land use change in the Five-Lakes Basin. Restoration strategies are proposed based on current land use and future scenarios to enhance the ESP in central Yunnan's Five Lakes Basin.

Responses of Vegetation Phenology to Urbanization in Plateau Mountains in Yunnan, China

The process of urbanization alters the distribution of land use and gives rise to certain climatic modifications that have a direct influence on vegetation phenology. Mountainous areas have a fragile biological environment, and vegetation phenology is relatively sensitive to urbanization. However, there is a paucity of research on the impact of urbanization in mountainous areas on vegetation phenology. The Urban Agglomeration of Central Yunnan (UACY) is located on the Yunnan–Guizhou Plateau in China. This study explored the vegetation phenological changes in different terrains from 2001 to 2020 in the UACY based on remote sensing data. Using the dynamic gradient method, we examined the response of vegetation phenology to urbanization from three aspects: urban–rural gradient, urbanization intensity (UI), and population density. The results showed that landform has a significant impact on SOS (start of growing season), with a topographic relief difference of 200 m acting as the dividing line. The findings derived from the dynamic gradient analysis indicate that UI has the most significant effect. SOS advances by 5.77 days (R2 = 0.96), EOS (end of growing season) advances by 2.30 days (R2 = 0.83), and LOS (length of growing season) lengthens by 2.59 days (R2 = 0.87) for every 10% increase in UI. This study has the potential to serve as a valuable resource for future urban planning and administration in the UACY. Additionally, it could provide decision-making support for the development of mountainous urban agglomerations in ecological environments.

Seasonal variation in C:N:P stoichiometry, nonstructural carbohydrates, and carbon isotopes of two coniferous pioneer tree species in subtropical China.

The characteristics of C:N:P stoichiometry, nonstructural carbohydrate (NSC) content, and C stable isotopes and their relationships affect plant responses to environmental changes and are critical to understanding the ecosystem carbon and water cycles. We investigated the water use strategies and physiological changes of two pioneer tree species (Pinus armandii and Pinus yunnanensis) in response to seasonal drought in subtropical China. The seasonal variation in needle δ13C values, C:N:P stoichiometry, and NSC contents of the two tree species were studied in 25-year-old plantation in central Yunnan Province. The needle δ13C values of both species were highest in summer. Soluble sugars, starch and NSC content of the two tree species decreased from spring to winter, while there was no significant difference in the seasonal variation of soluble sugars/starch in P. armandii needles, the maximum soluble sugars/starch in P. yunnanensis needles was in autumn. In addition, the C, N, and P contents of the needles and the C:N and C:P ratios of the two species showed different seasonal fluctuations, whereas the N:P ratio decreased with the season. The C:N:P stoichiometry and NSC content of the needles showed significant correlations, whereas the needle δ13C was weakly correlated with C:N:P stoichiometry and NSC content. Phenotypic plasticity analysis and principal component analysis revealed that the needle nutrient characteristics (NSC and P contents and N:P ratio) and needle δ13C values were critical indicators of physiological adaptation strategies of P. armandii and P. yunnanensis for coping with seasonal variation. These results increase our understanding of the water-use characteristics of the two pioneer tree species and the dynamic balance between the NSC, C, N, and P contents of the needles.

Upper crustal structure across the Xiaojiang fault system revealed by ambient noise tomography from a dense short-period array

The Central Yunnan block (CYB) plays a key role in accommodating the crustal tectonic deformation of the southeastern Tibet, but its exact mechanism is poorly understood. Here we obtained a fine S-wave velocity structure of the upper crust across the Xiaojiang fault system in CYB, using the ambient noise tomography with a linear dense short-period array. The result shows a strong S-wave velocity variation along the profile, which is consistent with geomorphology and hypocenters occurred in this area. The velocity variations along the profile correspond well to the major faults seen on the surface and are consistent with the transition from surface erosion, to ductile basement and to rigid basement in the greater depth. Combining the upper crustal structure from our image with the location of hypocenters, we propose that most faults of Xiaojiang fault system cut through the upper crust steeply and control the tectonic deformation of the upper crust in the CYB.

Spatiotemporal Dynamics of the Suitability for Ecological Livability of Green Spaces in the Central Yunnan Urban Agglomeration

Green spaces are an essential aspect of building an eco-livable city and play an important role in building for eco-livability in the central Yunnan urban agglomeration. However, there are relatively few studies evaluating the eco-livability of green spaces. The establishment of a green-space eco-livability assessment system may help researchers to analyze the eco-livability of urban green spaces more effectively. To address this research gap, we constructed an ecological livability-evaluation index system for green spaces that incorporates three determinants—economic development, social life, and the ecological environment—using the green spaces of the urban agglomeration in central Yunnan as a case study. We used the entropy method to calculate the suitability for ecological livability of the green spaces in each district and county in the central Yunnan urban agglomeration for 2010, 2015 and 2020. We used the spatial autocorrelation analysis function of ArcGIS 10.8 software to explore the spatial clustering characteristics of the suitability for ecological livability of green spaces in the central Yunnan urban agglomeration. The results showed that, from 2010 to 2020, the suitability for ecological livability of green spaces of the 49 districts and counties in the central Yunnan urban agglomeration increased in some districts and decreased in others. The spatial characteristics were high in the central districts and counties and low in the peripheral districts and counties. The spatial characteristics of the suitability of the target layers for economic development and ecological-environment target were consistent with the overall suitability. Through a spatial autocorrelation analysis, we observed that the suitability of green spaces for ecological livability had a positive spatial correlation and demonstrated significant spatial clustering. In this study, we propose recommendations to improve the suitability for ecological livability of green spaces from two dimensions of government policy and urban development, using a combination of the three target layers. The results of the study provide a reference for decision-making in the construction of eco-livable cities in the central Yunnan urban agglomeration.

Spatial differentiation characteristics of regional self-driving tourism flow: A case study of central Yunnan urban agglomeration

The aim of this study was investigate the spatial effects of A-class scenic spots and the spatial distribution of highway networks on the influence of self-driving tour behavioral patterns in China at the urban agglomeration scale, based on big data of road traffic during three holidays. A spatial analysis method and a geographically weighted regression model were used to analyze the spatial distribution differences and influencing factors of self-driving tourism flows in the central Yunnan urban agglomeration. The results showed that holiday self-driving tourism in the central Yunnan urban agglomeration presented a typical core-edge spatial pattern. The mean value of the spatial autocorrelation coefficient was 0.54, indicating significant spatial autocorrelation. The influence of tourism resources and traffic conditions on self-driving tourism flow showed a decreasing trend from the center of the high positive value to the periphery of the main urban area of Kunming. This study reveals the spatial differentiation characteristics of self-driving tourism flows in urban agglomerations and lays a theoretical foundation for understanding flow pattern.

Composite interpretability optimization ensemble learning inversion surrounding rock mechanical parameters and support optimization in soft rock tunnels

The mechanical parameters of the surrounding rock of a tunnel are the premise and foundation of the supporting design in soft rock tunnel engineering. To obtain the mechanical parameters of the surrounding rock accurately and quickly, a composite inversion model is proposed, and different models are used to invert different mechanical parameters. In this paper, first, the Latin hypercube and Monte Carlo sampling methods are used to construct the mechanical parameter samples from the surrounding rocks. The numerical simulation of the water diversion project in central Yunnan is carried out by using FLAC3D, and the corresponding displacement data are obtained, three sets of effective inversion datasets are formed along with the mechanical parameter samples. Second, the adjusted coefficient of determination and the symmetrical mean absolute percentage error are used as the performance evaluation indices. The Bayesian 10-fold cross-validation iteration is used to optimize the five regression model hyperparameters for the three sets of inversion parameters. The base model of the best performance is selected for inverting the friction angle (φ) and cohesion (c). For the deformation modulus (Em) inversion parameters, LIME interpretability is used to optimize the weights and integrate the five models. Finally, by developing a calculation tool for the elastic modulus of tunnel support, an orthogonal experimental design is applied based on the verified engineering numerical model. The results show that the average error of the inversion results of the mechanical parameters of the surrounding rock by the proposed composite model is 9.32%, the minimum error is only 0.81%, and the error is within 15%. The inversion trend is similar to the actual displacement height, and the optimized support scheme provides a reference for the engineering site.

Integrating three-dimensional greenness into RSEI improved the scientificity of ecological environment quality assessment for forest

Normalized Difference Vegetation Index (NDVI) is widely used to represent the greenness indicator for the Ecological Environment Quality (EEQ) assessment based on the traditional Remote Sensing Ecological Index (RSEI). However, NDVI saturation issues are reported in agriculture and forest ecosystems at high greenness and biomass, creating a challenge when using NDVI to reflect the greenness components for forest EEQ assessment. In this paper, three-dimensional greenness (TDG) was obtained by the Forest Canopy Height (FCH) and Fractional Vegetation Cover (FVC) to quantify the forest greenness. The NDVI of RSEI was replaced with TDG to establish an improved remote sensing ecological index (TDRSEI) for the forest EEQ evaluation in the Central Yunnan, China. Moreover, we analyzed the difference between RSEI and TDRESI by qualitative and quantitative means and discussed deeply the optical saturation of NDVI by the quadratic function. The results shown that there were similar spatial distribution patterns and a strong correlation between TDG and FCH, Leaf Area Index (LAI), FVC, and NDVI, the TDG can be used to replace NDVI for reflecting forest greenness. The standard deviation of TDRSEI from the same FCH pixels was all less than that of RSEI, the absolute correlation coefficient between TDRSEI and ecological components were all greater than 0.63, and the mean values of TDRSEI (0.73, 0.84, and 0.90) from the relatively high FCH (20 m, 25 m, and 30 m) were greater than RSEI (0.71, 0.78, and 0.85), showing that the TDRSEI were more stable than RSEI for forest EEQ assessment and it can improve the EEQ in the high FCH. In Central Yunnan, China, the forest EEQ from TDRSEI and RSEI maps both increased with the growth of FCH, the distribution of RSEI had no significant difference between the low FCH and the high FCH, while the mean values of TDRSEI increased linearly with FCH growth. Besides, the ecological saturation points of TDRSEI and RSEI corresponding to the FCH were 19.50 m and 34.02 m, respectively. Therefore, TDRSEI method integrates the three-dimensional greenness to evaluate the forest EEQ objectively.

Study on the response and prediction of SDGs based on different climate change scenarios: The case of the urban agglomeration in central Yunnan

Climate change has become one of the biggest challenges facing the world, which will affect the process of sustainable development in all aspects such as economy, society, environment, etc., and the integration of climate change into the sustainable development management strategy will help to realize the process of SDGs indicators. However, there is a lack of quantitative research on the correlation between climate variables and sustainable development, especially from the perspective of climate change. Therefore, the experiment systematically proposes a framework for ecosystem service-based sustainable development assessment in the context of climate change, and tries to explore the response relationship between climate variables and sustainable development goals. The experiment takes the central Yunnan urban agglomeration as the study area, and based on the climate data of CMIP6, adopts the PLUS model and the InVEST model, predicts the spatial distribution of ESs and calculates the indicators of future SDGs, and explores the response of the climate to the indicators of SDGs by using the Spearman's correlation analysis. The experimental results showed that both the overall ESs and SDGs metrics declined under the influence of future climate change. Through the response analysis, among the eight climate indicators, evapotranspiration, dryness, barometric pressure, and temperature showed negative impacts in the study go, while precipitation, relative humidity, wind speed, and solar radiation promoted sustainable progress in the study area. However, under the influence of future climate change, the positive indicators may translate into negative impacts. There is a strong correlation between climate change and sustainable development, and the results of this experiment can provide a scientific reference for the sustainable development of similar regions in order to minimize the negative impacts of climate change in the future.