Landscape Pattern Research Articles

Spatial-temporal evolution of habitat quality in tropical monsoon climate region based on “pattern–process–quality” – a case study of Cambodia

Abstract Exploring the coupling relationship of “pattern–process–quality” is conducive to understanding the internal mechanism of habitat quality change, and is of great significance for the function maintenance and sustainable management of regional ecosystems. Existing studies mainly analyze the spatial-temporal evolution of habitat quality from the perspective of “pattern quality” and land use data. However, the variation in habitat quality is the result of many factors such as “pattern–process–quality” of the habitat. Therefore, it is necessary to consider these factors comprehensively when studying the change in habitat quality, so as to understand the change mechanism of habitat quality more comprehensively and deeply. This study takes Cambodia, a tropical monsoon climate region, as the research area, and uses land cover data from 2000 to 2022 as the data source. InVEST model is used to analyze the spatial-temporal evolution of habitat quality, and explore the relationship between habitat quality and land use, landscape pattern, and ecological process. The results show that (1) during 2000–2022, forest in Cambodia covered a wide range, showing a landscape pattern mainly distributed in the east and west. (2) The degree of fragmentation of impervious landscape pattern increased gradually from 2000 to 2022, indicating that it was seriously affected by human activities and natural factors, and with the increase in elevation and slope, the area of various types converted to impervious decreased. (3) During 2000–2022, high habitat quality areas were concentrated in Tonle SAP Lake in the east, southwest, and central part of Cambodia, while low habitat quality areas were concentrated in the central part. (4) Natural factors, socio-economic factors, policies, and regulations all have an impact on the change in land use pattern and habitat quality in Cambodia.

Landscape Pattern Changes and Ecological Vulnerability Assessment in Mountainous Regions: A Multi-Scale Analysis of Heishui County, Southwest China

Against the backdrop of intensifying global climate change, the impact of land use pattern changes on ecosystem vulnerability has garnered increasing attention. However, systematic studies concerning the ecological vulnerability of mountainous regions remains inadequate, with relevant policies primarily remaining at the macro-regulation level and lacking specific guidance measures. Taking Heishui County in southwest China as a case study, this research innovatively combines landscape pattern with the sensitivity–pressure–resilience (SPR) model to systematically analyze land use spatiotemporal evolution characteristics, ecological vulnerability and spatial differentiation patterns, and their driving mechanisms across multiple scales, including county, township, and land use types. The findings reveal that the region’s ecological vulnerability exhibits a spatial distribution pattern of “high in the southeast and low in the northwest”, with a radiating decrease from the centers of Longba and Weigu towns. The high degree of farmland landscape fragmentation is identified as a crucial factor contributing to its heightened ecological vulnerability. Geological disasters, human activities, meteorological conditions, and topographical features are the primary driving factors affecting ecological vulnerability intensity. Furthermore, land use pattern changes, characterized by landscape patch fragmentation, lack of dominant patch types, and decreased landscape diversity have further intensified regional ecological vulnerability. This research holds significant theoretical and practical implications for guiding ecological environmental governance in mountainous regions, enhancing ecological resilience, and promoting regional sustainable development.

The influence of greening management and landscape patterns on plant diversity in urban green spaces in Danzhou, China

The influence of greening management and landscape patterns on plant diversity in urban green spaces in Danzhou, China

Spatial patterns of dune landscapes manifest the history of boundary condition changes

Spatial patterns of dune landscapes manifest the history of boundary condition changes

Waterbird community response to wetland and climate changes in the Liaohe River Estuary wetlands, China.

The Liaohe River Estuary (LRE) wetland is a critical stopover on the East Asian-Australasian Flyway (EAAF), vital to coastal ecological balance and biodiversity. However, the drivers of changes in waterbird diversity remain unclear. This study utilised random forests to produce reliable time-series wetland mapping from 2010 to 2023. Spatial and temporal changes in wetlands and landscape structures were analysed using landscape pattern indices-the Alpha and Beta diversity analyses were based on monitoring records that assessed waterbird diversity and community structure. The response of waterbirds to wetland, landscape, and climate changes was quantified using a Generalized Linear Mixed Effects Model (GLMM). Between 2010 and 2023, 78 species of waterbirds from 8 orders and 14 families were recorded. In 2023, waterbird counts reached 1,014,908, marking an increase of 868,102 compared to 2010. Over 14 years, waterbird diversity consistently increased, with community structure becoming more stable. Positive responses to climatic factors, such as seasonal precipitation and mean temperatures (both year and seasonal), were observed, while extreme weather inhibited recovery, like heavy precipitation and strong winds. Changes in Suaeda salsa (Sua) and forested areas significantly impacted waterbird diversity compared to other land cover types. These findings highlight the strong influence of climate, wetland, and landscape changes on waterbird diversity and community structure. Managers are encouraged to prioritise monitoring temperature, precipitation, Sua, and forested landscapes while enhancing artificial wetland management to support waterbird diversity and ecological balance in the LRE.

Dynamic Evolution of PM2.5 Removal by Urban Forests During Rapid Urbanization: From Forest Landscape Pattern Dominance to Impervious Surfaces

Dynamic Evolution of PM2.5 Removal by Urban Forests During Rapid Urbanization: From Forest Landscape Pattern Dominance to Impervious Surfaces

Assessing the influence of green space morphological spatial pattern on urban waterlogging: A case study of a highly-urbanized city.

The extensive expansion of impervious surfaces encroaches on green spaces and causes frequent urban waterlogging disasters. Previous studies have focused mainly on the influence of green space landscape pattern on waterlogging, with less attention given to green space morphological spatial pattern (MSPA). MSPA can be used to differentiate various types of land use morphologies from a microscopic perspective and reveal visualized spatial characteristics. Therefore, this study selected Shenzhen, a city with serious waterlogging problems, as the study area. The anthropogenic/natural environments and green space morphological spatial pattern were considered. Pearson correlation analysis and random forest regression were combined to investigate the influence of these drivers on the density of waterlogging hotspots and quantify the degree of importance for each driver. The results were supplemented with explanations using SHapley Additive exPlanations and Partial Dependence Plots. Pearson correlation analysis revealed that green space morphological spatial pattern, the proportion of green spaces, and the proportion of impervious surfaces were the dominant drivers. Additionally, the random forest regression showed that incorporating green space morphological spatial pattern and average tree height as potential drivers could strengthen the model's goodness-of-fit. While the proportion of impervious surfaces, the proportion of green spaces, and population density were important drivers, the green space morphological spatial pattern, specifically the "loop", "edge", and "core", was even more crucial and had an optimal design range. Therefore, green space morphological spatial pattern should be emphasized during the planning of "sponge cities" to maximize the ability of green spaces to mitigate waterlogging. In summary, our findings are expected to provide feasible suggestions for waterlogging control and green space planning.

Multi-scale urban ecosystem service changes and their impact mechanisms on human well-being.

With increasing urbanization pressures, there is an urgent need to improve the urban residents' well-being and achieve the sustainable development goals (SDGs). Ecosystem services (ESs) are vital for human well-being (HW) and survival, providing essential benefits like clean water while supporting the SDGs. However, understanding the impact mechanism of urban ESs on the HW under the framework of the SGDs in a changing world remains challenging. This study simulated five key ESs: net primary productivity (NPP), water yield (WY), soil conservation (SC), soil fixation (SF), and ecosystem carbon sink (ECSI) using ecological models at the pixel, urban green space and county scales, and calculated supply services at the county scale. Then we established an evaluation index system of the HW to reveal the impact mechanism of the ESs on the HW. The study found that in Beijing, the ESs improved by 29.14%-267.42%, while SF decreased by 55.84% during 2000-2020, and the urban green space became a carbon sink since 2010. At the pixel and urban green space scales, vegetation significantly drove the ES dynamics, with the relative importances exceeding 90% in supporting NPP and exceeding 55% in restraining WY. The urban landscape patterns dominated the ES dynamics at the county scale. The impervious landscape percentage inhibited NPP, ECSI and SC with the relative importances of 66.47%, 39.94% and 19.52%. The HW in Beijing increased from 2005 to 2020, with a notable difference between central urban and non-central urban counties. The supporting services supply had significantly negative direct and indirect impacts on the HW. The indirect impact of the urban ecosystem supporting service supply on the HW was through restraining provisioning service supply and supporting regulating service supply. The provisioning service supply had a significantly positive direct influence on the HW. This study can provide valuable references for sustainable urban management.

Spatiotemporal Relationship Between Landscape Pattern and Ecosystem Service Connectivity in Wetland Environment: Evidence from Yellow River Delta, China

Ecosystem service connectivity (ESC) is the spatial and functional links among and within ecosystems that support unimpeded service flows, and that could play an important role in ecosystem stability enhancement and regional land planning. Understanding the relationships between landscape patterns and ESC is crucial to achieving certain sustainable development goals, but it has not yet received an adequate amount of attention. Here, we evaluated the changes and connectivity of five key types of ecosystem services from 2000 to 2020 and analyzed the correlations and spatial aggregations between the ESCs and landscape metrics in the wetlands of the Yellow River Delta, China. Various research methods, such as the InVEST model, spatial autocorrelation analysis, Spearman’s correlation, and self-organizing map, were applied. The results showed that water yield, water purification, and habitat quality showed high connectivity, but the overall ESC declined along with the restoration of the wetland area. Meanwhile, the High-High ESC cluster of water yield, water purification, and habitat quality had similar spatial distribution patterns, and both were dominated by tidal flats. Moreover, the ESC and landscape metrics showed significant correlations and spatial heterogeneity, and a potential connectivity between water yield and habitat quality was also found. These findings can assist decision-makers in developing effective ecosystem management strategies and provide a reference for future research on ecosystem service connectivity.

Interpretation of the Jiangnan Landscape and Countryside (Shan-Shui) Pattern: Evidence from the Classification and Spatial Form of Traditional Settlements in the Nanxi River Basin

Against the backdrop of accelerated globalization and urbanization, traditional settlements in the Jiangnan waterside areas of China face challenges such as morphological distortion and a simplified spatial structure. The ecological adaptability and cultural value of settlements urgently need scientific protection. There has not been enough research on how to better classify settlements, how to conduct systematic morphological analysis, or how to use dynamic protection methods. This makes it hard to fully show the variety of settlement types and how they differ in different areas. To this end, this study uses a combination of GIS spatial analysis, type classification, and case study methods to classify and morphologically analyze 159 traditional settlement patches in the Nanxi River Basin. We construct a settlement type map from quantitative research on topographical, water system, and spatial morphological characteristics, and extract a spatial organization model of mountains and water. The results show the following: (1) The main morphological types, such as the plain–waterfront–strip-shaped and cluster-shaped/finger-shaped types, are typical patterns of traditional settlements in the basin. This indicates how well settlements can adapt to their natural surroundings. (2) This study summarizes six typical settlement sample spaces. (3) The settlement digital protection strategy suggested in this paper uses GIS and 3D modeling technology to make it easier to record, show, and manage information about settlement spaces. This offers a new way to protect traditional settlements scientifically. The study not only enriches the theoretical understanding of the settlement morphology of Jiangnan landscape pastoral areas but also provides an important reference for the protection and sustainable development of settlements in similar basins around the world.

Identification and Optimization of Attractive Territorial Spaces in Gansu Province Based on the Supply-Demand Ratio of Ecosystem Services

Crafting high-quality Attractive Territorial Spaces(ATS) has become an essential approach to enhancing the quality of national territorial spaces at present. Previous studies have offered multidimensional identification methods but have overlooked the intrinsic connections between ATS and factors such as ecology, culture, and society. This study proposes a systematic method for identifying and optimizing ATS, which includes assessing the supply-demand ratio of ecosystem services(ES), interactive detection of driving factors, identification of ATS, landscape pattern analysis, and a matrix of optimization strategies for ATS. The results indicate: (1) There is a significant spatial imbalance between the supply and demand of ES in Gansu Province, with the western region serving as a crucial water source and carbon sink area, while the eastern region stands out in the provision of cultural services. The supply-demand ratio analysis reveals an imbalance in key services such as water resources and soil conservation(SC), particularly in densely populated and rapidly developing economic regions where the demand is urgent. (2) Geographic detector analysis reveals that Normalized Difference Vegetation Index(NDVI) and population(POP) are the two main driving factors affecting the spatial differences in ES, with NDVI having a high explanatory power for the spatial heterogeneity of carbon sequestration(CS) services, and POP significantly influencing recreation(RE) and aesthetic landscapes(AL) services. (3) Landscape pattern analysis shows that urban spaces exhibit fragmentation; agricultural spaces, though concentrated, lack landscape diversity and connectivity; ecological spaces, despite having larger core areas, have weak connectivity between patches and a high degree of fragmentation. Based on the above analysis, this study has constructed the Attractiveness Territorial Index (ATI), combined with the main functional areas of Gansu Province's territorial space planning, identified ATS, and proposed targeted optimization strategies for territorial spaces. The framework for identifying ATS established in this study effectively implements the requirements of higher-level planning, clarifies guidance and control requirements, and is conducive to enhancing the value and quality of territorial spaces, as well as providing systematic and holistic protection for elements of attractiveness.

From sky to ground: decoding migratory bird’s habitat selection along the multi-scale sequence

ContextMigratory birds select habitats by observing landscape patterns at different scales as they descend from higher elevations, weighing habitat availability. Understanding how this selection process operates at multiple scales and how decisions at different scales interact is crucial for identifying the optimal scale for efficient habitat conservation.ObjectivesWe aimed to investigate the regularity of changes in migratory birds’ habitat selection in response to landscape variables over multi-scales, using the Oriental White Stork (Ciconia boyciana) as an example.MethodWe developed Scale Response Models and Habitat Selection Models using a sequence of nine scales (5–200 km) within the East Asian-Australasian Flyway to evaluate the stork’s scale-sensitivity and assess the change of explanatory power of landscape variables across scales at different periods.ResultScale-sensitivity of storks was highest during the wintering period. The explanatory power of the suitable habitat indicator is higher at larger scales, but decreases with decreasing scale; while the opposite is true for the unsuitable habitat indicator. At large scales, wetland indicators dominated in breeding period, while water indicators dominated in other periods; at smaller scales, unsuitable habitat indicators had stronger impacts in wintering period.ConclusionsWe revealed a nested relationship in multi-scale habitat selection among storks: “benefit-tendency” decisions at larger scales provide context and constraints; “risk-avoidance” decisions at smaller scales determine settlement. Due to internal and external factors, migratory birds displayed different scale-sensitivities and landscape preferences across periods. Our findings highlight the scale-dependence of organisms’ behavior and landscape characteristics, providing guidance for multi-scale habitat conservation.

Interaction of population density and slope will exacerbate spatiotemporal changes in land use and landscape patterns in mountain city

The complex topography of the mountain cities leads to uneven distribution of land resources. Currently, available studies mainly focuse on land use and landscape patterns (LU and LP) in plains or plateaus. Thus, it is necessary to carry out an analysis of the drivers of changes in LU and LP in mountain cities. As the typical mountain city in China, Chongqing has changed significantly of land use in recent years. Here, we identified LU and LP changes from 2000 to 2020, and explored their drivers using GeoDetector in Yubei District, Chongqing. The following are the outcomes: (1) From 2000 to 2020, construction land, wetland and cropland had the greatest change in area, with 876.03%, -70.72% and -24.53%, respectively. The area of cropland transferred out was larger than the area transferred into it, while cropland still the largest among all land use types. (2) At the landscape level,construction landscape was at a low level. Grassland had the greatest degree of fragmentation, but showed a decreasing trend. The landscape’s complexity resulted from the conversion of various land uses. (3) The results of GeoDetector indicated that the interaction of population density and slope was the primary LU and LP changing factor. The results of the study provided a rational basis for the development of land use and landscape plans in the mountain cities.

Dynamic of Land Use and Associated Ecosystem Service Value in the Chengdu–Chongqing Urban Agglomeration, China

Understanding the long-term land use changes in the Chengdu–Chongqing urban agglomeration, a vital element of the Yangtze River Economic Belt and a key economic growth center in western China, can offer scientific basis and policy direction for improving regional ecosystem service values (ESVs), environmental conservation, and sustainable development. This study investigated the features connected to land use change, changes in landscape patterns, and variations in ESV across this region by means of time series of remote sensing and socio-economic data from 1990 to 2020. Additionally, the correlations between landscape pattern indices and ESV were examined. The findings indicated that: (1) cultivated land and grassland in the Chengdu–Chongqing urban agglomeration exhibited a declining trend, while forest, water, and construction land demonstrated increasing trends; (2) human activities significantly affected the Chengdu–Chongqing urban agglomeration, resulting in severe landscape fragmentation, heterogeneity, complexity of types, and patch separation, although the predominant patch types maintained strong connectivity; (3) the ESV of the Chengdu–Chongqing urban agglomeration initially decreased, reaching a minimum of CNY 5.017 billion in 2000, and subsequently rose again. Forest land accounted for approximately 69% of the overall ESV in the region over the preceding decades. The policy of reverting farmland to forest, the establishment of wetland parks, and the increased awareness of environmental protection have led to notable alterations in land use types and landscape patterns within the Chengdu–Chongqing urban agglomeration, which can significantly improve the regional ecosystem service value; however, the extent of influence and trends among various landscape indices are disparate.

Land use and landscape pattern changes in the Fenhe River Basin, China

The composition and pattern of ecosystems play a crucial role in determining the overall condition and spatial variations of ecosystem services. In this study, we explored the Normalized Difference Vegetation Index (NDVI), six land use/land cover change (LULC) types, and their landscape patterns to reflect spatial-temporal dynamics from 2010 to 2020 in the upper and middle reaches of the Fenhe River Basin. The trend analysis of Mann-Kendall tests was used to assess the NDVI variation of each pixel over the past decade. Shannon’s Diversity Index (SHDI) was used to quantify the complexity of the landscape pattern of local LULC. Meanwhile, the spatial-temporal dynamic variations of vegetation NDVI and six LULC types were illustrated using geographic mapping methods. The results were presented as follows: (1) From 2010 to 2020, vegetation cover increased, with an annual NDVI increment of 0.003 (P < 0.001). Spatially, there was a significant increasing trend in NDVI, particularly in high-altitude mountainous areas where the vegetation cover mostly consisted of forests or grasslands. However, there was no significant change in vegetation cover in the low-lying urban agglomeration area. (2) During the period from 2010 to 2020, there was a significant decrease in the area of water bodies and wetlands, the rate of decrease slowed from 2015 to 2020. Specifically, the percentage of decrease from 2010 to 2015 increased by more than 14%. This proportion exceeded 30% when compared to the final governmental ecological management goal set during the 13th Five-Year Plan Period (2016–2020). (3) During the same period, the SHDI of LULC exhibited heterogeneous characteristics. In the high-altitude areas near the river basin boundary, SHDI values were below 1.0. Conversely, in the low-altitude plains and urban areas with frequent human activities, SHDI values exceeded 1.0, reaching above 1.5 in urban areas. This study provides a scientific reference for the construction and management of the ecological environment in the Fenhe River Basin, along with practice insights for ecological protection and high-quality development in the Yellow River Basin.

Study on the Spatiotemporal Evolution Relationship Between Ecological Resilience and Land Use Intensity in Hebei Province and Scenario Simulation

The ecological health of Hebei Province is critical to the sustainable development of the Beijing–Tianjin–Hebei region. However, the increasing intensity of land use in recent years has placed significant pressure on local ecosystems, making it essential to understand how land use changes affect ecological resilience across different regions and time periods. This study takes Hebei Province as the research area and selects four time points—1990, 2000, 2010, and 2020—to systematically evaluate the spatiotemporal variations in ecological resilience and land use intensity using indicators such as the water resource supply, climate regulation, hydrological regulation, biodiversity, the landscape pattern index, and land use types. This study employs spatial analysis methodologies, including the spatial autocorrelation model and the Geographically Weighted Regression (GWR) model, to systematically analyze spatial clustering patterns, spatial heterogeneity, and influencing mechanisms. Scenario simulations are also conducted to predict ecological resilience trends in 2030 under a sustainable development scenario. The results indicate that (1) over the past 30 years, both ecological resilience and land use intensity in Hebei Province have generally increased, with notable spatial disparities among cities. (2) Moreover, a significant negative correlation exists between ecological resilience and land use intensity, with the GWR model revealing pronounced spatial heterogeneity. The impact of land use intensity on ecological resilience is relatively minor in highly urbanized central and southern regions, while northern and northwestern regions are more sensitive to changes, highlighting the need for better coordination between land use planning and ecological protection. (3) Finally, scenario simulations predict a slight overall decline in ecological resilience by 2030, with central and southern cities projected to experience the largest decreases, while some northern cities are expected to see modest improvements. These findings underscore the importance of regionally differentiated land use management and ecological protection strategies. This study provides scientific evidence and planning recommendations to improve ecological resilience and environmental protection in Hebei Province. At the same time, this study contributes to a deeper understanding of how land use dynamics influence ecological resilience. The methodologies and findings presented in this study can also be applied to guide sustainable development planning in other rapidly urbanizing areas, providing a valuable framework for addressing regions facing similar ecological challenges.

Estimating the impact of 2D urban landscape patterns on extreme precipitation based on non-stationary models in the Guangdong-Hong Kong-Macao Greater Bay Area, China.

Rapid urbanization has significantly altered surface landscape configurations, leading to complex urban climates. While much attention has been focused on impervious surfaces' impact on extreme precipitation, a critical gap remains in understanding how various 2D urban landscape components influence extreme precipitation across different durations. Through an analysis of the non-stationarity and spatiotemporal variations in extreme precipitation across the Guangdong-Hong Kong-Macao Greater Bay Area (GBA) from 1990 to 2020, we constructed the non-stationary Generalized Additive Models for Location Scale and Shape (GAMLSS) model by introducing six urban landscape structural metrics as explanatory variables for each of the 27 meteorological stations in the GBA. Additionally. we assessed the frequency of these metrics in the best-fitting models and predicted design values across different interannual periods. Our findings reveal that aggregation metrics (patch density: PD) and diversity metrics (Shannon's Diversity Index: SHDI) appeared more frequently in the best-fitting models than other metrics within all extreme precipitation indices. For short-duration extreme precipitation indices (≤ 3h), the area matrix (Impervious Surface Percentage: ISP), PD, and SHDI were selected more often than other metrics, whereas for long-duration (> 3h), PD and SHDI had a higher relative frequency as ISP's impact decreased. Design values peaked in the 2010s across all return periods (100, 50, and 20years), highlighting the importance of integrating urban landscape features into non-stationary models of extreme precipitation. This research provides valuable insights for improving the management of urbanization-induced heavy precipitation and flood risks.

Quantifying and Mapping the Impact of Construction Land Expansion on Cultivated Land Fragmentation—A Case Study of Fuqing City, China

To ensure the sustainable utilization of cultivated land resources, it is essential to quantify and map the characteristics of construction land and cultivated land and analyze the mechanisms by which construction land expansion affects cultivated land. However, few studies have been conducted focusing on this issue. This study integrated morphological spatial pattern analysis, spillover effect analysis, landscape pattern analysis, and a land use transition monitoring method to investigate the characteristics of construction land expansion and cultivated land fragmentation. Fuqing City of China was selected as the case study area for demonstration. The results demonstrated that the expansion of construction land resulted in fragmented patterns within the cultivated land landscape: (1) The large core area of cultivated land was subdivided into smaller core areas during 2000–2020, while the construction land exhibited a tendency towards aggregation and a spillover effect; (2) The expansion rate of the construction land in the study area accelerated, while the extent of the cultivated land decreased; (3) Cultivated land fragmentation intensified as landscape aggregation weakened, leading to an expansion in the agglomeration of construction land. The highlights of this study are: (1) examining the characteristics of construction land expansion and cultivated land fragmentation from morphological and geospatial perspectives; (2) categorizing the core areas of cultivated land based on their size to facilitate the analysis of factors contributing to cultivated land fragmentation. The findings in this study can be used to develop models to predict future patterns of cultivated and construction land to provide suggestions for landscape planning.

Spatiotemporal Response Relationships Between Changes in Water Conservation Service and Landscape Pattern in Zoige Plateau, China

ABSTRACTUnderstanding the link between landscape pattern and water conservation service (WCS) is crucial for effective water resource conservation and landscape planning. However, the impact of landscape configuration on WCS remains unclear. This study explored the spatiotemporal relationships between WCS and landscape pattern in the Zoige Plateau (ZP), a vital waterhead of the yellow river, from 1990 to 2020. The results showed that woodland and high‐coverage grassland exhibited the highest WCS capacity and contributed the greatest to total WCS, suggesting the importance of protecting coverage and area of woodland and grassland. From 1990 to 2020, the areas of high‐ and medium‐coverage grasslands significantly decreased, implying adverse effects of landscape composition changes on ZP's WCS during the past few decades. The effects of landscape configuration metrics on WCS exhibited significant variability across years, climate scenarios and regions, highlighting the significant role of climatic and underlying surface. Under realistic climatic scenarios, for greater WCS, in most parts of the western and northern ZP, which negatively correlated with aggregation index, patch density, and mean fractal dimension index but positively correlated with shannon's diversity index, it is better to increase the proportion of large patches, reduce landscape fragmentation, and maintain diverse patch types. Conversely, in southeastern part of the central ZP, where WCS showed an opposite correlation with the aforementioned metrics, maintaining simpler patch type diversity and higher landscape connectivity may be useful. These findings provided important insights for identifying sensitive areas where landscape pattern changes affect WCS and optimizing landscapes to sustain ZP's WCS.

Identification of critical biomarkers and immune landscape patterns in glioma based on multi-database

PurposeGlioma is the most prevalent tumor of the central nervous system. The poor clinical outcomes and limited therapeutic efficacy underscore the urgent need for early diagnosis and an optimized prognostic approach for glioma. Therefore, the aim of this study was to identify sensitive biomarkers for glioma.Patients and methodsDifferentially expressed genes (DEGs) of glioma were downloaded from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. The potential biomarkers were identified using weighted gene co-expression network analysis (WGCNA) and least absolute shrinkage and selection operator (LASSO) regression. The prognostic ability of the potential biomarkers was evaluated by Cox regression and survival curve. CellMiner was used to access the correlation between the expression of potential biomarkers and anticancer drug sensitivity. We then explored the association of potential biomarkers and tumor immune infiltration by single-sample GSEA (ssGSEA) and CIBERSORT. Immune staining in glioma patient samples and cell experiments of potential biomarkers further verified their expression and function.ResultsUltimately, we identified three potential biomarkers: SLC8A2, ATP2B3, and SRCIN1. These 3 genes were found significantly correlated with clinicopathological features (age, WHO grade, IDH mutation status, 1p19q codeletion status). Furthermore, the overall survival (OS), disease-specific survival (DSS), and progression-free survival (PFS) were found to be positively correlated with high expression of these 3 potential biomarkers. Besides, there was a substantial relationship between the sensitivity of anticancer drugs and these biomarkers expression. More importantly, the negative association between the 3 genes with most tumor immune cells was also established. Moreover, the decreased expression of the biomarkers was also verified in glioma patient samples. Finally, we confirmed that these 3 genes might promotes glioma proliferation and migration in vitro.ConclusionSLC8A2, ATP2B3, and SRCIN1 were identified as underlying biomarkers for glioma associated with prognosis assessments and personal immunotherapy.Graphical