Spatial Pattern Analysis Research Articles

Spatial pattern and differential expression analysis with spatial transcriptomic data.

The emergence of spatial transcriptomic technologies has opened new avenues for investigating gene activities while preserving the spatial context of tissues. Utilizing data generated by such technologies, the identification of spatially variable (SV) genes is an essential step in exploring tissue landscapes and biological processes. Particularly in typical experimental designs, such as case-control or longitudinal studies, identifying SV genes between groups is crucial for discovering significant biomarkers or developing targeted therapies for diseases. However, current methods available for analyzing spatial transcriptomic data are still in their infancy, and none of the existing methods are capable of identifying SV genes between groups. To overcome this challenge, we developed SPADE for spatial pattern and differential expression analysis to identify SV genes in spatial transcriptomic data. SPADE is based on a machine learning model of Gaussian process regression with a gene-specific Gaussian kernel, enabling the detection of SV genes both within and between groups. Through benchmarking against existing methods in extensive simulations and real data analyses, we demonstrated the preferred performance of SPADE in detecting SV genes within and between groups. The SPADE source code and documentation are publicly available at https://github.com/thecailab/SPADE.

Identification of key areas for Territorial Ecological Restoration: focusing on ecological security and restoration potential

Implementing Territorial Ecological Restoration is a crucial approach to achieving ecological stability and regional sustainable development, and it also serves as an important measure for promoting the coordinated development of socioeconomic and ecological environments in the Yellow River Basin. However, effective identification of key areas for Territorial Ecological Restoration remains challenging in planning ecological restoration projects. This study focuses on ecological security and restoration potential, taking Linxia Prefecture in the ecologically fragile area of the upper Yellow River as an example. By evaluating six types of ecosystem services in this area, utilizing morphological spatial pattern analysis models and circuit theory, we identified the structural elements of ecological security patterns and assessed the potential for ecological restoration, identifying key areas for regional ecological restoration.The findings indicated that (1) 13 ecological patches were identified in total, predominantly distributed in the southwest and central regions of Linxia Prefecture. 25 ecological corridors were identified, demonstrating a high level of spatial coherence in terms of significance and connectivity, establishing a closely integrated ecological security network primarily in the southwest of Linxia Prefecture. (2) Thirteen ecological pinch points and seventeen ecological barrier points have been identified, concentrated in the central and southwestern regions of Linxia Prefecture. (3) Based on the characteristics and urgency of key areas for Territorial Ecological Restoration, they are classified and graded as “point-line-surface” and “primary-very important-important.” The primary restoration areas of the point type are mainly located in the central part of Linxia Prefecture, while the primary restoration areas of the line and plane types are mainly in the southwestern part of Linxia Prefecture. This paper emphasizing a holistic approach that prioritizes ecosystem integrity and social support to guide targeted restoration strategies across various ecological features, ultimately aiming for sustainable regional development and maximizing restoration benefits in ecologically fragile areas.

Assessing Climate Change Impact on Habitat Suitability and Ecological Connectivity of Wych Elm (Ulmus glabra Huds.) in Türkiye

Understanding how climate change influences the geographical distribution of species within an ecological niche is essential for predicting habitat shifts and informing conservation efforts. This study evaluates the impact of climate change on habitat suitability and ecological connectivity of wych elm (Ulmus glabra Huds.) in Türkiye. The study explores the future distribution of U. glabra and how its connectivity is affected by habitat fragmentation arising from changing climatic conditions. Contextually, this paper aims to achieve two primary objectives: estimating the potential geographical ranges of U. glabra under different climate scenarios and assessing alterations in ecological connections between current and future habitats. The maximum entropy (MaxEnt) model was used along with Morphological Spatial Pattern Analysis (MSPA), and the Probability of Connectivity (PC) index was applied to show possible transformations in distribution patterns of U. glabra over time. The findings suggest that there will be a reduction in the suitability of locations for the species. Moreover, it is expected that under future climate scenarios, ecological connectivity will decline, especially from 2061 to 2100 in the SSP585 scenario. Notably, significant alterations are anticipated during the latter half of the twenty-first century, mainly outside the coastal areas of the Black Sea, where extensive regions would become unsuitable. Additionally, the species is projected to shift its range, decreasing its presence in inland regions while expanding along the coasts. The results show the vulnerability of this species against climate change, thereby demanding adaptive conservation measures to preserve it within the forest ecosystems of Türkiye.

Cultivated Land Information Extraction and Spatial Pattern Analysis in Beijing Based on Deep Learning

Abstract. Cultivated land is the basic resource and material condition for human survival, providing the necessary material basis for agricultural development and agricultural modernization (Tian and Shi, 2024). For this reason, this paper takes Beijing as an experimental area to study the cultivated land extraction method and analyze the distribution pattern of cultivated land and the degree of fragmentation. The results show that (1) the extraction results are evaluated by using confusion matrix and Kappa coefficient, and the Kappa coefficient is obtained to be 0.8358.(2) The cultivated land in Beijing is mainly distributed in the southeast as well as the northwest of the local area of gentle terrain, and the The range of the extremely high value of cultivated land kernel density in 2017–2022 is significantly reduced, the slope of the area with the smallest reduction in the proportion of cultivated land is less than 5°, the reduction in the area of cultivated land in water resource-rich areas is small, and the reduction in the proportion of cultivated land in road-intensive areas is large. (3) Due to various natural factors and human activities, the degree of cultivated land fragmentation in Beijing is increasing, the boundary shape of cultivated land patches tends to be irregular.

Anatomical Location of Rib Fractures and Associated Analgesic Benefits Achieved From Serratus Anterior Plane Blocks: A Spatial Point Pattern Analysis.

Anatomical Location of Rib Fractures and Associated Analgesic Benefits Achieved From Serratus Anterior Plane Blocks: A Spatial Point Pattern Analysis.

Effect of Aspect and Elevation on the Degree of Aggregation and the Functional Traits in Phlomis floccosa D. Don (Lamiacae) Populations

ABSTRACTPhlomis floccosa D. Don populations are distributed in different microhabitats within Al‐Akhdar mountainous landscape, in Libya. Five populations were selected for the study. Spatial relationships among individuals were investigated using the spatial point pattern analysis. Functional traits were recorded at the vegetative, flowering and fruiting stages. Seeds were collected at the dispersal stage to estimate the regeneration potential. Greater degree of aggregation was found at higher elevations on both northern and southern sides of the mountain but with different demography and traits. On the northern side, greater degree of aggregation was accompanied by absence of large adults and greater percentage of seedlings, and it was positively associated with the reproductive output, while negatively associated with the size and regeneration indices. On the southern side, greater degree of aggregation was accompanied by greater contribution of large adults and greater percentage of seedlings, and it was positively associated with the size and regeneration indices, while negatively associated with the reproductive output. On the other hand, the population in the wadi (valley) microhabitat showed coarse‐scale clumped pattern, higher values for most of the functional traits and higher contribution of seedlings but with lower facilitation offered by adults. The variations in the degree of aggregation and the functional traits trade‐offs in P. floccosa populations ensured successful survival and regeneration in the heterogeneous microhabitats. Meanwhile, stressed conditions greatly affect the survival and regeneration of the species suggesting the need for conservation measures to overcome the adverse effects of climate change.

The construction of international wetland urban ecological security pattern coupled with MSPA and ESF.

Creating an ecological security pattern is crucial for balancing the sustainable development of areas where human activities and the natural environment intersect. Using Hefei, an internationally recognized Wetland City, as a case study, we extracted ecological sources through ecological service function (ESF) analysis and morphological spatial pattern analysis (MSPA) core area connectivity analysis. Based on these ecological sources, we developed an ecological resistance surface system and identified ecological corridors and nodes using circuit theory. The findings are as follows: (1) Ecological source areas: The primary ecological sources in Hefei are located in the water bodies, forested areas, and scattered grasslands in the central and eastern parts of the city. This ecological source area covers 978.96 km2, which constitutes 8.55% of the city's total area. (2) Ecological corridors: Hefei contains 43 ecological corridors with a total length of 940.3km, averaging 21.87km each. These corridors are crucial for maintaining ecological connectivity and facilitating species movement. (3) Ecological nodes: There are 13 significant ecological nodes in Hefei, including 6 ecological obstacle points and 7 ecological pinpoints. These nodes play a vital role in supporting ecological processes and ensuring habitat connectivity. (4) Evaluation metrics: The α and β values for the source identification method that integrates MSPA with ecological service functions were 2.15 and 0.8, respectively, which are higher than those of the control group. Conversely, the γ-value was 0.18, lower than that of the control group. These results indicate that the combined ecological source extraction method provides significant advantages in terms of ecological corridor integrity, connectivity, and ecological flow management.

Analysis of the Spatiotemporal Distribution Characteristics and Influencing Factors of High-Grade Cultural Heritage in the Region Surrounding Mount Song

Situated in central China, the region surrounding Mount Song is a pivotal area within the Central Plains, renowned for its extensive and high-grade cultural heritage. This study aims to analyze the spatiotemporal distribution of this heritage using advanced spatial pattern analysis methods, including the Average Nearest Neighbor Ratio and Kernel Density Estimation within ArcGIS. Our findings reveal a distinct continuity in temporal distribution and a pronounced clustering in spatial terms. By investigating the underlying factors such as the geographical setting, historical political capitals, cultural and religious influences, water transportation systems, and traditional Fengshan ceremonies, this research elucidates the dynamics shaping this distribution. This study’s outcomes provide essential insights for policymakers and stakeholders involved in the protection and revitalization of cultural heritage, ensuring informed decision making for sustainable cultural conservation.

How can geostatistics help us understand deep learning? An exploratory study in SAR-based aircraft detection

Deep Neural Networks (DNNs) have garnered significant attention across various research domains due to their impressive performance, particularly Convolutional Neural Networks (CNNs), known for their exceptional accuracy in image processing tasks. However, the opaque nature of DNNs has raised concerns about their trustworthiness, as users often cannot understand how the model arrives at its predictions or decisions. This lack of transparency is particularly problematic in critical fields such as healthcare, finance, and law, where the stakes are high. Consequently, there has been a surge in the development of explanation methods for DNNs. Typically, the effectiveness of these methods is assessed subjectively via human observation on the heatmaps or attribution maps generated by eXplanation AI (XAI) methods. In this paper, a novel GeoStatistics Explainable Artificial Intelligence (GSEAI) framework is proposed, which integrates spatial pattern analysis from Geostatistics with XAI algorithms to assess and compare XAI understandability. Global and local Moran’s I indices, commonly used to assess the spatial autocorrelation of geographic data, assist in comprehending the spatial distribution patterns of attribution maps produced by the XAI method, through measuring the levels of aggregation or dispersion. Interpreting and analyzing attribution maps by Moran’s I scattergram and LISA clustering maps provide an accurate global objective quantitative assessment of the spatial distribution of feature attribution and achieves a more understandable local interpretation. In this paper, we conduct experiments on aircraft detection in SAR images based on the widely used YOLOv5 network, and evaluate four mainstream XAI methods quantitatively and qualitatively. By using GSEAI to perform explanation analysis of the given DNN, we could gain more insights about the behavior of the network, to enhance the trustworthiness of DNN applications. To the best of our knowledge, this is the first time XAI has been integrated with geostatistical algorithms in SAR domain knowledge, which expands the analytical approaches of XAI and also promotes the development of XAI within SAR image analytics.

Analysis on Ecological Network Pattern Changes in the Pearl River Delta Forest Urban Agglomeration from 2000 to 2020

The advancement of urbanization has led to a decline in the ecological function and environmental quality of cities, seriously reducing the services and sustainable development capacity of urban ecosystems. The construction of the National Forest Urban Agglomeration of China is conducive to alleviating the ecological and environmental problems brought about by rapid urbanization and promoting sustainable urban development. A time series analysis of ecological network changes can quickly and effectively explore the development and changes of ecological spatial patterns over time. Identifying ecological protection and restoration areas in urban agglomerations is an important way to promote ecosystem restoration and optimize ecological networks. This paper takes the Pearl River Delta forest urban agglomeration as the research area, uses multi-source remote sensing data from 2000 to 2020 (every 5 years), identifies ecological sources based on the morphological spatial pattern analysis (MSPA) method, generates ecological corridors based on the minimum cumulative resistance (MCR) model, constructs a time series ecological network pattern in the Pearl River Delta region, and analyzes the evolution process of the ecological network pattern over time. The results indicate that over time, the core green area in the ecological network pattern of the Pearl River Delta first decreased and then increased, and the complexity of ecological corridors first decreased and then increased. The main reason is that the urbanization process in the early 21st century led to severe ecological fragmentation. Under the promotion of the national forest urban agglomeration construction, the ecological network pattern of the Pearl River Delta was restored in 2015 and 2020. The time series analysis of the ecological network pattern in the Pearl River Delta region of this research confirms the effectiveness of the construction of forest urban agglomerations, providing a scientific reference for the identification of ecological networks and optimization of spatial patterns in forest urban agglomerations.

Construction, assessment, and protection of green infrastructure networks from a dynamic perspective: A case study of Dalian City, Liaoning Province, China

The green infrastructure (GI) network, an important nature-based solution (NBS) strategy, is pivotal for sustainable urban development. However, current research perspectives focus on constructing a static GI network, and research on evaluating and protecting GI networks in the context of spatiotemporal changes has been limited. This research aims to comprehensively characterise the spatio-temporal changes in the GI network and protect its efficiency. We selected Dalian City as a case study and applied the Future Land-use Simulation (FLUS) model to predict its land use for 2030 and 2040. Based on predicted and historical land-use data, the 1990–2040 GI network of Dalian City was constructed utilising the Integrated valuation of ecosystem services and trade-offs (InVEST), morphological spatial pattern analysis (MSPA) and minimum cumulative resistance (MCR) model, while its spatiotemporal changes were evaluated. The results revealed that the hub area exhibited positive growth over time, whereas the link lengths showed an opposite trend. Furthermore, the overall position of the GI network shifted toward the southwest. The flatness indicator detected that the direction of the GI network shape gradually became less pronounced. Consequently, the structure of the GI network shifted from multi-centre to mono-centre. Additionally, priority protection for hubs is mainly in the northeast, while links are primarily in the coastal regions. The urgency of protection for both increases over time. This research developed a dynamic GI network construction and assessment method, providing a scientific basis and reference for future rational GI network planning, ecological protection planning, and related land policy formulation.

Urban Habitat Quality Enhancement and Optimization under Ecological Network Constraints

The process of urbanization leads to the rapid expansion of construction land and brings a series of ecological and environmental problems. The ecological network, as a linear landscape element, is of great significance to improve the quality of the regional ecological environment. In this study, the Morphological Spatial Pattern Analysis (MSPA) and the model of Minimum Cumulative Resistance (MCR) were used to construct the ecological corridors in the central city of Fuzhou, and the land use pattern under the constraints of the ecological network was simulated and quantified by the patch-level land use simulation (PLUS) tool with the results of the identification of ecological corridors. Meanwhile, with the help of InVEST habitat quality model, the regional habitat quality under different development scenarios was compared. The results show that (1) 19 ecological sources and 35 ecological corridors were identified; (2) under the constraints of ecological corridors, the area of forested land in the study area in 2027 was increased by 1.57% and the area of built-up land was reduced by 0.55% compared with that in 2022; (3) and under the constraints of ecological corridors, the mean value of habitat quality in Fuzhou City improved by 0.0055 and 0.0254 compared with 2022 and 2027 natural evolution scenarios, respectively. The study provides decision-making assistance for the construction of ecological corridors from the perspective of land use planning.

Construction of Cross-basin Ecological Security Patterns Based on Carbon Sinks and Landscape Connectivity

Artificial water system creation and land use changes have great effects on ecosystems. The construction of cross-basin ecological security patterns based on carbon sinks and landscape connectivity plays a key role in regional ecological environment protection. The linkage area between the Xiang River and the Li River was selected as the research object. Based on the land use data from 2000 to 2020, this study examined the ecological security network of the Xiang-Li connected region using the InVEST model combined with morphological spatial pattern analysis （MSPA） and evaluated the temporal and spatial evolution of carbon storage and ecological security patterns. The results showed that： ① From 2000 to 2020, the land cover types of the Xiang-Li linkage area were mainly forest land and arable land. The changes of land use types were characterized by decreases in arable land, forest land, and grassland and by increases in watersheds and construction land. ② The carbon storage in the Xiang-Li linkage area was characterized by a blocky distribution, and the high and medium areas were dominant. The carbon stock increased slowly from 2000 to 2010 and decreased dramatically from 2010 to 2020, with a cumulative decrease of 18.32×103 t due to the influence of land use changes. ③ The area of ecological sources （five in total） decreased firstly and then increased, whereas the length of ecological corridors （ten in total） increased firstly and then decreased in the Xiang-Li linkage area. Overall, in the process of urbanization, the distribution of the high ecological resistance value in the Xiang-Li linkage area gradually shifted to the northeast with an expansion, whereas the barycenter of the ecological safety pattern shifted to the southwest. Determining the dynamic distribution and stability of ecological sources by coupling carbon storage patches and landscape patterns can provide a new way to construct ecological security patterns in cross-basin ecosystems.

Phasic perfusion dynamics among migraine subtypes: a multimodel arterial spin labeling investigation

BackgroundMigraine-related perfusion changes are documented but inconsistent across studies due to limited sample size and insufficient phenotyping. The phasic and spatial dynamics across migraine subtypes remains poorly characterized. This study aimed to determine spatiotemporal dynamics of gray matter (GM) perfusion in migraine.MethodsWe prospectively recruited episodic (EM) and chronic migraine (CM) patients, diagnosed with the International Headache Society criteria and healthy controls (HCs) between 2021 and 2023 from the headache center in a tertiary medical center, and adjacent communities. Magnetic resonance (3-tesla) arterial spin labeling (ASL) was conducted for whole brain cerebral blood flow (CBF) in all participants. The voxel-wise and whole brain gray matter (GM) CBF were compared between subgroups. Spatial pattern analysis of CBF and its correlations with headache frequency were investigated regarding different migraine phases and subtypes. Sex- and age-adjusted voxel-wise and whole brain GM comparisons were performed between HCs and different EM and CM phases. Spatial pattern analysis was conducted by CBF clusters with phasic differences and spin permutation test. Correlations between headache frequency and CBF were investigated regarding different EM and CM phases.ResultsTotally 344 subjects (172 EM, 120 CM, and 52 HCs) were enrolled. Higher CBF in different anatomical locations was identified in ictal EM and CM. The combined panels of the specific locations with altered CBF in ictal EM on receiver operating characteristic curve analysis demonstrated areas under curve of 0.780 (vs. HCs) and 0.811 (vs. preictal EM). The spatial distribution of ictal-interictal CBF alteration of EM and CM were not correlated with each other (p = 0.665; r = − 0.018). Positive correlations between headache frequency and CBF were noted in ictal EM and CM regarding whole GM and specific anatomical locations.ConclusionsPatients with migraine exhibited unique spatiotemporal CBF dynamics across different phases and distinct between subtypes. The findings provide neurobiological insights into how selected anatomical structures engage in a migraine attack and adapt to plastic change of repeated attacks along with chronicity.

Effective cooling networks: Optimizing corridors for Urban Heat Island mitigation

The detrimental impacts of the Urban Heat Island (UHI) effect are widely recognized in cities globally. Despite the natural cooling capacity of urban cold islands (UCIs), their fragmented state diminishes overall effectiveness. Previous research focused on identifying corridors to connect these isolated UCIs, aiming to enhance cooling networks. However, optimal connection strategies remained elusive. This study introduces a novel framework to address this gap. Utilizing ArcGIS Pro's optimal region connection tools alongside Morphological Spatial Pattern Analysis (MSPA) and ecological parameters, corridors in Ghaemshahr, Iran were meticulously planned and assessed. Through minimum cumulative resistance and gravity models, 63 potential corridors totaling 153 km were identified. Optimization procedures then refined this selection to 27 key corridors spanning 22 km, with 67% measuring less than 0.5 km and strategically positioned near UCIs. This prioritizes adjacency, maximizing corridor protection and construction likelihood. This cost-effective approach fosters stronger connectivity between adjacent UCIs, ultimately linking all UCIs within the region. This innovative methodology provides a holistic solution for mitigating UHI effects, promoting sustainable urban development.

Does Urban Green Space Pattern Affect Green Space Noise Reduction?

The effect of urban green spaces on traffic noise reduction has been extensively studied at the level of single vegetation, hedges, etc., but there is a lack of corresponding studies at the scale of spatial patterns of urban green spaces. Therefore, this study aims to analyze the relationship between the spatial pattern of urban green space and the change in green space’s noise reduction capacity. Through the morphology spatial pattern analysis method, this analysis divides the urban green space in the Fuzhou high-tech zone into seven types of elements with different ecological definitions and simulates the noise condition of the urban environment with the presence of green space as well as without the presence of green space by computer simulation, calculates the distribution map of the noise reduction produced by the urban green space, and analyzes the correlation between the seven types of green space elements and the noise reduction with the geographically weighted regression modeling analysis. The study finds that (1) Urban green space patterns can significantly affect the net noise reduction of green space. Areas with high green coverage can produce a stronger green space noise reduction effect. (2) More complex green space shapes and more fragmented urban green space can produce higher noise reduction. (3) The green space close to the source of noise can exert a stronger noise reduction effect. Therefore, in the process of planning and design, from the perspective of improving the urban acoustic environment, the configuration of high-quality green spaces in areas with higher levels of noise pollution should be given priority, which may have better noise reduction effects.

Measuring Land Preservation Success: Applying Fragstats to Preserved Farmland in Lancaster County, Pennsylvania

Edge effects are traditionally discussed in biogeography and ecosystem protection. Yet preserved farmland can also experience challenging pressures at its perimeter, such as increased development pressure and conflicts between farms and nonfarm neighbors. Academic assessments of the most common farmland preservation goal—large, contiguous blocks—have focused on the area and connectivity of preserved parcels and largely overlooked the block or shape component, which relates most strongly to these types of pressures. This study fills that gap, applying the edge-effects concept to preserved farmland for the first time and tracking the shape of preserved farmland patches in Lancaster County, Pennsylvania, a leading agricultural county in the United States. The study uses the spatial pattern analysis program Fragstats to examine preserved farmland patch size, shape, and area in Lancaster County between 2000 and 2023. Results show that although land preservation organizations in Lancaster County had success at increasing the area and contiguity of preserved land, the perimeter of farmland patches increased even more significantly, even when accounting for differences in area. Farmland patches became increasingly irregular over the study period, with meandering shapes that maximize edge. The outcome suggests that tracking edge separately from area and contiguity is important because success in one does not mean success in the others. Information on edge and shape can help land preservation organizations prioritize parcels that reduce the edge effects that make it more expensive to purchase easements and more challenging for farmers to keep farming.

Spatial pattern and coupling characteristics analysis of maritime traffic and economic development based on shipping big data

The rapid development of maritime transport and the gradual increase in the number of ports, ships and shipping routes can produce direct economic benefits for regional development, and a profound grasp of the actual situation of maritime transport makes it possible to make practical plans for economic development and thus rationally develop and use marine resources. However, there is a lack of research on maritime transport, so this study is based on the AIS, waterways, routes and ports data in the near-shore sea area of Guangdong Province. Using GIS spatial analysis technology and various mathematical models, we refer to the evaluation method of road traffic dominance. It analyses and proposes the evaluation indexes of maritime traffic advantages, such as the density of maritime traffic network and the proximity of ports. Based on the actual situation of the study regions, the indicators were quantitatively evaluated and analyzed. The economic development level of each region was also quantitatively evaluated using principal component analysis, and the study regions were classified based on the coupling-coordination model. The results show that the coastal area of Guangdong Province is divided into four types of zones according to the coupling-coordination type of zoning criteria. Corresponding development suggestions are put forward for different zones, and the research results provide certain practical guidelines for promoting the benign cycle development of maritime traffic and economy, and have important guiding significance and application value for the organization and safety of maritime traffic.

The Role of Spatial Morphology in Forest Landscape Fragmentation: Insights From Planted and Natural Forests of the Chinese Loess Plateau

ABSTRACTThis study aimed to emphasize the key role of spatial morphology of planted and natural forests on landscape fragmentation and to furnish a scientific foundation for the effective assessment of ecological restoration projects of vegetation on the Loess Plateau. The spatial morphological pattern and landscape fragmentation characteristics were analyzed using morphological spatial pattern analysis (MSPA) and forest area density methods. This is the inaugural study to reveal the linear and nonlinear relationships between forest landscape fragmentation and its driving factors using machine learning methods and introducing morphological indicators with two different strategies. The results showed significant differences in the spatial patterns and landscape fragmentation characteristics between planted and natural forests. The spatial patterns of planted and natural forests were found to be dominated by “Core” in terms of area, while “Branch” was more prevalent in terms of number. Compared to natural forests, planted forests were more fragmented. The introduction of the MSPA indicator significantly enhanced the explanatory power and predictive performance of the model despite the disparate contribution rates of the driving factors in planted and natural forests. This study highlights the importance of spatial morphology in understanding forest landscape fragmentation and provides a new combination of analytical techniques to better understand the complexity of forest ecosystems. These provide new insights into forest landscape restoration and sustainable management on the Loess Plateau.

Spatial Pattern Analysis and Conservation Assessment of Apiaceae in Mongolia.

The family Apiaceae, distributed throughout the Northern Hemisphere, is the largest family of angiosperms. However, little is known about the conservation status, diversity, and distribution of Apiaceae species in Mongolia. This study had two main aims: (1) to assess the national status of Apiaceae species under IUCN Red List Criterion B; (2) to evaluate the species diversity and richness of Apiaceae across Mongolia. We utilized ConR packages to assess the national Red List status of all known Mongolian Apiaceae species by analyzing their most comprehensive occurrence records. The results indicated that 27 species were classified as threatened, including 4 Critically Endangered (CR), 9 Endangered (EN), and 14 Vulnerable (VU) species. Meanwhile, 39 species were assessed as non-threatened, with 2 Near Threatened (NT) species and 37 species of Least Concern (LC). Furthermore, detailed distribution maps for 66 Apiaceae species in Mongolia were presented. We assessed the species diversity and Shannon and Simpson diversity indices of Apiaceae by analyzing all occurrence records using the iNext package. Overall, the Hill diversity estimates indicate that the sampling conducted in Mongolia adequately captured species occurrences. For species pattern analysis, we examined the species richness, weighted endemism, and the corrected weighted endemism index using Biodiverse v.4.1 software. Mongolia was portioned into 715 grid cells based on 0.5° × 0.5° grid sizes (equivalent to approximately 50 × 50 km2). There was a total of 3062 unique occurrences of all Apiaceae species across Mongolia. In the species richness analysis, we identified 10 grids that exhibited high species richness (18-29 species) and 36 grids with 11-17 species. For genus richness, we observed seven grids that exhibited a high genus richness of 16-22 genera. Furthermore, we analyzed species richness with a specific focus on threatened species, encompassing CR, EN, and VU species throughout Mongolia. A total of 92 grids contained at least one threatened species. There were six grids that had two to five threatened species, which were adequately covered by protected areas in western Mongolia. Overall, our results on species richness and conservation status will serve as important foundational research for future conservation and land management efforts in Mongolia.