Distribution Area Research Articles

Conserving saproxylic flagship species by complementing 150 years of natural history with citizen science data—the case of the stag beetles (Lucanidae, Coleoptera) of Portugal

Abstract The use of flagship species in conservation, such as the European Stag Beetle (Lucanus cervus), can positively affect the conservation of other taxonomic or functionally related species. This is especially true for taxonomic groups where the knowledge regarding their distribution and ecology is generally limited, as is the case of insects. This work represents the most accurate and up-to-date publication on the distribution, ecology and environmental niche of the four lucanids found in Portugal. Moreover, it unravels how citizen science initiatives can positively impact conservation planning for flagship species and their taxonomic and functionally related species. Compared to non-citizen science sources, citizen science data increased the known distribution area for all four species (1.6 to 7.2 fold) and confirmed most of the current known species distribution (50.0% to 95.5%). It also expanded the known environmental niche breadth for all species (1.1 to 4.2 fold) and the species suitable modelled habitat (1.1 to 2.1 fold) with very good model performances (AUC > 0.8 and TSS > 0.6). Our results suggest that to improve the conservation of these species, it is paramount to value native forests in Portugal. Management actions to accomplish this might include preserving current native forests and small natural features (such as large old trees) throughout the landscape while simultaneously increasing native forest development. In addition, climate change will affect the species' distribution since all are highly susceptible to specific (bio-)climatic conditions that are expected to change in the next decades. These findings not only enhance our understanding of these species' current distribution but also pave the way for targeted and integrative conservation efforts throughout the country, especially in areas where the (now assessed) ecological niche requirements and habitat availability (either in terms of landscape composition or structure) are met. Guidelines and priorities are discussed on how to implement conservation measures in Portugal following the recently approved European Nature Restoration Law.

Spatiotemporal patterns of annual clear-cutting distribution in tropical and subtropical regions of China with time series Landsat and CCDC

ABSTRACT Spatial and temporal clear-cutting distribution is an important data source for investigating forest dynamics and formulating policies related to timber production, land use, and sustainable development. Subtropical and tropical regions of China due to their favorable weather conditions for tree growth are important timber providers, but the spatial distribution of annual clear-cutting areas was unavailable. This research leveraged dense time-series Landsat images (1986–2022) and a novel approach combining Continuous Change Detection and Classification (CCDC) with Random Forest to produce the first annual 30 m resolution clear-cutting map for the China’s subtropical and tropical regions. The per-polygon approach based on the sub-compartment and field survey data was used to evaluate the developed clear-cutting product. The spatiotemporal distribution of clear-cutting areas was further analyzed along longitude and latitude as well as in different provinces. The results indicated that the combination of CCDC and Random Forest successfully detected spatial and temporal distribution of clear-cutting areas with an overall accuracy of 75.6% based on sub-compartments and 93.3% based on field polygons. The cumulative clear-cutting area between 1987 and 2021 was approximately 21.26 × 106 ha, with a mean annual clear-cutting area of 0.61 × 106 ha in China’s subtropics and tropics. About 10.24% of subtropical/tropical vegetation experienced clear-cutting and most areas (85.94%) were clear-cut once. Clear-cutting activities gradually clustered at low latitudes and moderate longitudes, represented by Guangxi Province. More frequent clear-cutting was observed during the later period (2001–2021). This research contributes to an improved understanding of forest dynamics over time at large scale, and provides scientific data to make proper decisions for forest sustainability.

Exploration and Empirical Study on Spatial Distribution of SOC at the Core Area in Coastal Tamarix Forests’ Inland Side of Changyi National Marine Ecological Area

The forest soil carbon pool plays a vital role in terrestrial ecosystems, being of great significance for maintaining global balance, regulating the global carbon cycle, and facilitating ecological restoration. Shandong Changyi Marine Ecological Special Protection Area is the only state-level marine special protection area in China with tamarisk as the main object of protection, and it is the largest continuous and the best preserved natural tamarisk forest distribution area on the mainland coast of China. Compared to other forested areas, research on the spatial distribution of SOC at the core area in coastal Tamarix forests’ inland side appears to be relatively scarce. Based on this, this paper takes the core area of the Changyi National Marine Ecological Special Protection Zone, located on the southern coast of Laizhou Bay, as the research subject, based on the potassium dichromate oxidation-external heating, one-way ANOVA, and Bonferroni methods, analyzing the spatial distribution of the SOC content inland of coastal Tamarix forests. The research yielded the following conclusions: (1) The surface layer (0–10 cm) contributes significantly to the total SOC content within a 0–60 cm depth, accounting for at least 31% and shows notable surface accumulation. (2) The combined SOC content in the surface and subsurface layers (10–20 cm) accounts for at least 50% of the total SOC content within a 0–60 cm depth, indicating the dominance of these two soil layers in carbon storage. (3) The SOC content decreases with the soil depth at all six sampling points within the 0–60 cm range, with a marked drop from 0–10 cm to 10–20 cm. (4) One-way ANOVA and multiple comparisons reveal that the soil depth significantly affects the SOC distribution, particularly between the surface and 20–30 cm layers (p < 0.001), indicating high robustness and statistical significance. (5) Horizontally, the total SOC at 0 m is 45% lower than at 2 m in the 0–60 cm layer. The SOC in the 0–20 cm layer fluctuates significantly with distance from the shrub trunk, while the SOC in the 30–60 cm layers is low and stable, with minimal variations with depth. In addition, this study found that the SOC content in the core area of the protected area is lower than that in the common forest ecosystem. In the future, scientific ecological restoration projects and management protection methods should be used to improve soil’s carbon storage and carbon sink capacity. These findings not only validate the patterns of SOC’s spatial distribution in coastal Tamarix forest wetlands but also provide a scientific basis for carbon assessment and the formulation of ecological protection measures in coastal wetlands.

Global Potential Geographic Distribution of Anthonomus eugenii Under Climate Change: A Comprehensive Analysis Based on an Ensemble Modeling Approach.

Climate warming is affecting the ranges and population dynamics of invasive species, including insects, which have become a global problem, causing biodiversity declines and agricultural economic losses. Anthonomus eugenii as an important invasive pest on pepper is now mainly located in the USA and Mexico. However, the global potential geographic distribution (PGD) of A. eugenii with climate change remains unknown, which makes it difficult to monitor and control. In this study, based on the global distribution areas and important environmental variables, we constructed an ensemble model to predict the global PGD of A. eugenii under the current climate and three climate scenarios (SSP1-2.6, SSP2-4.5, and SSP5-8.5) in the 2030s and 2050s. The mean true skill statistics (TSS) and the area under the receiver operating characteristic curve (AUC) of the EM were 0.825 and 0.988, respectively, indicating that the EM was reliable. The mean temperature of the driest (bio9) and wettest (bio8) quarter and precipitation of the coldest quarter (bio19) were the most important environmental variables affecting the PGD of A. eugenii. Under the current climate, the PGD of A. eugenii was mainly concentrated in southern North America and central South America. The suitable areas of A. eugenii could increase significantly, reaching the maximum under SSP5-8.5 in the 2030s, approximately 1911.7 × 104 km2. Moreover, the distribution centroid would shift to higher latitudes with global warming. It also had the potential invasion risk in Russia, China, the Republic of the Congo, and Romania, which should enhance quarantine control and early warning.

Unraveling the shifts in the belowground microbiota and metabolome of Pinus pinaster trees affected by forest decline.

Pinus pinaster Aiton (maritime pine) stands are suffering a generalized deterioration due to different decline episodes throughout all its distribution area. It is well known that external disturbances can alter the plant associated microbiota and metabolome, which ultimately can entail the disruption of the normal growth of the hosts. Notwithstanding, very little is known about the shifts in the microbiota and the metabolome in pine trees affected by decline. The aim of our work was to unravel whether bacterial and fungal communities inhabiting the rhizosphere and root endosphere of P. pinaster trees with symptoms of decline and affected by Matsucoccus feytaudi in the National Park of Sierra Nevada (Granada, Spain) showed alterations in the structure, taxonomical profiles and associative patterns. We also aimed at deciphering potential changes in the rhizosphere and root metabolome. Trees infected by M. feytaudi and healthy individual harbored distinct microbial communities at both compositional and associative patterns. Unhealthy trees were enriched selectively in certain plant growth promoting microorganisms such as several ectomycorrhizal fungi (Clavulina) and Streptomyces, while other beneficial microorganisms (Micromonospora) were more abundant in unaffected pines. The rhizosphere of unhealthy trees was richer in secondary metabolites involved in plant defense than healthy pines, while the opposite trend was detected in root samples. The abundance of certain microorganisms was significantly correlated with several antimicrobial metabolites, thus, being all of them worthy of further isolation and study of their role in forest decline.

Mapping of Agate-like Soil Cover Structures Based on a Multitemporal Soil Line Using Neural Network Filtering of Remote Sensing Data

The present study focuses on analysis of the soil cover structure (SCS, SCSs), which is the most detailed level of soil organization in space. The detail in which complex SCS can be studied is often insufficient, since until now it has not been possible to map it over large areas at scales larger than 1:10,000. To increase the detail in which SCS can be studied, the methods of identifying the bare soil surface (BSS) and averaging its multitemporal spectral characteristics were used, which opens up new possibilities for mapping complex SCS over large areas. New SCSs of leached chernozems (Luvic Chernic Phaeozem) were discovered, which can produce patterns on satellite images similar to sections of Timan agate—agate-like soil cover structures (ASCS, ASCSs). ASCSs are formed on Quaternary sediments of varying thickness from 0.3 to 6 m, underlain by carbonate and red sediments of the Permian period. The ASCS pattern is formed by ring-shaped stripes (rings) of different colors and brightness, which are determined by the carbonate and red-colored inclusions involved in the arable horizon. Eight soil varieties were identified to describe ASCSs during the study. According to the WRB, there are six main soil types, and according to the classification of Russian soils in 1977, there are four types. ASCSs were identified over large areas and soil maps of ASCSs were constructed using multitemporal spectral characteristics of the BSS in the form of multitemporal soil line coefficients. Neural networks were used to identify BSS on big remote sensing data. ASCSs have contrasting soil properties and contrasting fertility (productivity of agricultural crops). ASCS maps can serve as the basis for task maps of precision farming systems. Perhaps ASCSs are unique objects for the area of chernozem distribution, where in one soil profile there are rocks with an age from the first thousand years (Quaternary) to 250 million years (Permian). Chernozems are fertile, studied, mercilessly exploited, but sometimes they are simply beautiful—agate-like.

Finding Galictis cuja (Molina, 1782) (Carnivora, Mustelidae) at a northern Chilean site in the potential distribution area of the species

Finding Galictis cuja (Molina, 1782) (Carnivora, Mustelidae) at a northern Chilean site in the potential distribution area of the species

Deconstructing the Properties of Solar Super Active Region 13664 in the Context of the Historic Geomagnetic Storm of 2024 May 10–11

Abstract Active regions (ARs) are sites of strong magnetic fields on the solar surface whose size can be several times that of Earth. They spawn dynamic activity, sometimes resulting in severe space weather. Some ARs characterized by extraordinary magnetic properties and exhibiting extreme activity are termed as super active regions (SARs). Recently, solar AR 13664 produced 23 X-class flares and unleashed multiple coronal mass ejections, which triggered a severe geomagnetic storm during 2024 May 10–11—the strongest storm on record since 2003. Here, we put AR 13664 in historical context over the cumulative period of 1874 May–2024 June. We find that AR 13664 stands at the 99.95th percentile in the distribution of area over 1874 May–2024 June and at the 99.10th percentile in terms of flux content among all ARs over the period 1996 April–2024 June. Our analysis indicates that five of its magnetic properties rank at the 100.00th percentile among all ARs observed during 2010 May–2024 June by the Solar Dynamic Observatory. A total of 16 magnetic properties of AR 13664 are ranked higher than the 99.00th percentile when compared to other ARs recorded in Space-weather Helioseismic Magnetic Imager Active Region Patch data series, which includes all well-established flare relevant parameters. Furthermore, we demonstrate that AR 13664 reached its most dynamic flare productive state following a rapid rate of rise of its flare-relevant parameters and that the X-class flares were more frequent near their peak values. Our analyses establish AR 13644 to be an SAR and provide a paradigm for investigating their flare-relevant physical characteristics.

Halophilic Fungi—Features and Potential Applications

Extremophiles are of significant scientific interest due to their unique adaptation to harsh environmental conditions and their potential for diverse biotechnological applications. Among these extremophiles, filamentous fungi adapted to high-salt environments represent a new and valuable source of enzymes, biomolecules, and biomaterials. While most studies on halophiles have focused on bacteria, reports on filamentous fungi remain limited. This review compiles information about salt-adapted fungi and details their distribution, adaptation mechanisms, and potential applications in various societal areas. Understanding the adaptive mechanisms of halophilic fungi not only sheds light on the biology of extremophilic fungi but also leads to promising biotechnological applications, including the development of salt-tolerant enzymes and strategies for bioremediation of saline habitats. To fully realize this potential, a comprehensive understanding of their ecology, diversity and physiology is crucial. In addition, understanding their survival mechanisms in saline environments is important for the development of astrobiology. The significant potential of applications of halophilic fungi is highlighted.

Dynamics of urban green spaces in a megacity under the green economy framework and their influencing factors: a case study of Chongqing urban area

IntroductionIn the context of escalating public health crises in megacities, promoting green and healthy urban spatial development is crucial. It not only contributes to economic growth and environmental sustainability but also significantly impacts the public health of urban residents.MethodsThis study utilized land use data from 2000 to 2021 in Chongqing, China, to investigate the characteristics and patterns of change in urban green space distribution. Spatial analysis methods were employed, and an econometric model was constructed to analyze the mechanisms of these changes, considering factors such as economic drivers, governmental regulation, and social dynamics.ResultsThe results reveal that urban green spaces in the Chongqing metropolitan area are primarily concentrated in the inner suburbs with limited distribution in central urban areas, exhibiting a distinct spatial gradient. The overall size of urban green spaces has been decreasing, particularly in the inner suburbs. The primary patterns of this reduction include edge erosion in the inner suburbs, inward contraction in central urban areas, and minor perforation in new towns.DiscussionThe analysis indicates that economic drivers, such as industrial development and economic growth, are the dominant factors contributing to the reduction of urban green spaces. The impact of social dynamics, such as public demand, appears to be relatively insignificant. Conversely, government planning policies and public investments play a crucial role in the protection and development of urban green spaces. These findings emphasize the need for effective urban planning strategies that prioritize the conservation and expansion of green spaces to enhance public health and environmental sustainability in megacities.

Understanding the spread of agriculture in the Western Mediterranean (6th-3rd millennia BC) with Machine Learning tools

The first Neolithic farmers arrived in the Western Mediterranean area from the East. They established settlements in coastal areas and over time migrated to new environments, adapting to changing ecological and climatic conditions. While farming practices and settlements in the Western Mediterranean differ greatly from those known in the Eastern Mediterranean and central Europe, the extent to which these differences are connected to the local environment and climate is unclear. Here, we tackle this question by compiling data and proxies at a superregional and multi-scale level, including archaeobotanical information, radiocarbon dates and paleoclimatic models, then applying a machine learning approach to investigate the impact of ecological and climatic constraints on the first Neolithic humans and crops. This approach facilitates calculating the pace of spread of farming in the Western Mediterranean area, modelling and estimating the potential areas suitable for settlement location, and discriminating distinct types of crop cultivation under changing climatic conditions that characterized the period 5900 – 2300 cal. BC. The results of this study shed light onto the past climate variability and its influence on human distribution in the Western Mediterranean area, but also discriminate sensitive parameters for successful agricultural practices.

Is the skull of the black-headed gull dimorphic? Analysis of shape variation

The black-headed gull (Chroicocephalus ridibundus) is a small bird belonging to the Laridae family. Their distribution and breeding broad area primarily cover the northern part of the Eurasian continent. Gulls are considered monomorphic birds, and distinguishing the sexes based on external morphological features is extremely difficult. In this study, a 3D shape analysis of the skull of black-headed gulls from central-northern Poland was performed to reveal the variation in shape between individuals and whether male skulls differ from females. For these purposes, 82 skulls were used (32 females and 50 males). 3D surface models of the skull were extracted using computed tomography. Twenty-one landmarks were designed on each skull. The principal components method was used to assess the variability of skull shapes. The first two principal components accounted for 48.28% of the cumulative shape variation. The most significant shape variation relative to PC1 was observed in the braincase. Positive PC2 values reflected the neurocranium expanding more rapidly dorso-ventrally with a wider orbit, and the nasofrontal hinge moved dorsally. According to the Procrustes ANOVA, the centroid size was statistically different between the sexes (p < 0.0001). Male skulls were longer than females. Neurocranium was wider in male gulls. The nasofrontal hinge was more caudal in females. The results of this study are consistent with the observations of other authors applying linear morphometry.

Research on Optimal Crop Planting Strategy Based on Improved Quantum Genetic Algorithm

In order to effectively cope with the complex agricultural environment and market uncertainty, this study proposed a crop planting optimization strategy based on the improved quantum genetic algorithm (QGA). Single-objective and multi-objective optimization models were proposed, focusing on profit maximization and risk balance under market fluctuations. The single-objective model used QGA to evaluate the optimal planting scheme under surplus and discount sales scenarios, and analyzed the crop area distribution and total income. For multi-objective optimization, the enhanced MO-QGA model combined with orthogonal experimental design generated a scheme that maximized expected income while minimizing the worst outcome. In addition, this study combined Pearson correlation and hierarchical clustering to quantify the substitutability and complementarity of crops, and optimized the planting strategy through crop combination analysis. The experimental results show that the enhanced QGA effectively balances profits and risks, and the effect is significantly better than traditional methods, which is conducive to improving agricultural decision-making efficiency

Two new species of Boaedon from Ethiopia and Somalia, with a review of the species of East Africa

We conducted a molecular study based on 112 mitochondrial 16S rRNA sequences, which revealed 20 monophyletic species-level groups in Africa, five of these in East and Northeast Africa. Based on genetic data, we describe two new species, B. broadleyi sp. nov. from Ethiopia and B. subniger sp. nov. from Somalia, and we elevate B. fuliginosus arabicus to full species level. We detected further morphologically divergent specimens that may represent a distinct taxon but refrain from a formal description due to insufficient data. The morphological variation of the recently described B. montanus from Central Africa is shown and discussed over its whole distribution area. Moreover, we provide a new country record for Sudan and South Sudan, namely of B. paralineatus. Finally, we provide an updated distribution map for all Boaedon species occurring in Northeast and East Africa.

A Study on the Residual Oil Distribution in Tight Reservoirs Based on a 3D Pore Structure Model

A tight reservoir is characterized by low porosity and permeability as well as a complex pore structure, resulting in low oil recovery efficiency. Understanding the micro-scale distribution of residual oil is of great significance for improving oil production and water flooding recovery rates. In this study, a 3D pore structure model of tight sandstone was established using CT scanning to characterize the residual oil distribution after water flooding. The effects of displacement methods and wettability on residual oil distribution at the micro-scale were then studied and discussed. Moreover, increasing the displacement rate has little effect on the distribution area and dominant seepage channels. Microscopic residual oil is classified into five discontinuous phases according to the oil–water–pore–throat contact relationship. The microscopic residual oil exhibits characteristics of being dispersed overall but locally concentrated. Under water-wet conditions, the injected water tends to strip the oil phase along the pore walls. Under oil-wet conditions, the pore walls have an improved adsorption capacity for the oil phase, resulting in a large amount of porous and membranous residual oil retained in the pores, which leads to a decrease in the overall recovery rate.

Texture mapping of warp knitted shoe upper based on ARAP parameterization method

Abstract In order to realize the design of the warp knitted upper based on the three-dimensional shoe model, this study investigates the texture mapping technique based on angle-preserving and area-regularizing as-rigid-as-possible (ARAP) parameterization. The ARAP algorithm, based on both partial and global considerations, is utilized to parameterize the 3D mesh. Moreover, detailed methods for calculating 3D vertex adjustments and selecting seam lines during the unfolding process are provided. Additionally, discrete harmonic and parametric optimization unfolding algorithms are employed to enhance texture mapping quality. To reduce mesh distortion, the results of discrete harmonic parameterization are used as inputs for ARAP parameterization, making the mapping effect more natural and reducing the number of required optimizations. Experimental results demonstrate that the proposed method maintains a balanced distribution of angles and areas while minimizing conformal distortions, thereby achieving superior texture mapping.

A Promising Strategy for Searching High Energy Density Materials Based on 2,4,5‐Trinitro‐Imidazole Functional Backbone

AbstractA series of high energy density compounds are designed by altering the triazole, tetrazine, oxadiazole rings and energetic groups (such as −CN, −N3, −NH2, −NHNH2, −NO2, −NHNO2, −C(NO2)3, −CH(NO2)2) into 2,4,5‐trinitro‐imidazole skeleton. Their structures are optimized by density functional theory (DFT) methods at B3LYP/6‐311G (d,p) method. Based on the optimized structures, the impact of different rings and energetic groups on their energy gaps, heats of formation, detonation performance and sensitivities are investigated. The results show that compound F4 possesses the highest values of heats of formation due to their high nitrogen content. However, compound F2 possesses the highest values of detonation pressure and detonation velocity which indicates that the detonation performance are determined by values of density rather than those of heats of formation. Taking both detonation performance and impact sensitivities into consideration, compounds B4, C4, F4, I4, J4 and J8 are screened as high energy density compounds due to their excellent detonation performance and acceptable sensitivities compared to those of RDX. Finally, the distribution of frontier molecular orbital, the electrostatic potential area distribution, thermodynamic properties and weak interactions of the screened compounds are fully investigated.

Diagnosis of Protected Agriculture in Imbabura—Ecuador, Period 2016–2023

Protected agriculture in Ecuador began in the 1990s and has expanded due to its comparative advantages over open field production. However, there are no statistics on this sector, which limits decision-making. The aim of this research was to provide a baseline of greenhouse agriculture in Imbabura. Sentinel-2 satellite imagery was used to estimate the spatial distribution of plastic-covered surface area in 2016 and 2023. To minimize biases in estimation, manual verification was also conducted. Based on population data, a structured survey was administered to a probabilistic sample of 234 greenhouses. The results highlight the presence of 1958 greenhouses that cover 527 hectares, with an average of 0.26 hectares. The greenhouses were characterized in terms of their design, construction materials and equipment. The main crop under plastic is tomato, with 76.9%, of which the management characteristics and the productive and economic results obtained in 2023 were identified. The findings could inform the formulation of public policies or specific interventions to strengthen protected agriculture in the region; however, support mechanisms are needed to fully exploit its potential. Among these, producer organization could be a viable strategy to address food security challenges in the context of climate change.

Improving Forest Canopy Height Mapping in Wuyishan National Park Through Calibration of ZiYuan-3 Stereo Imagery Using Limited Unmanned Aerial Vehicle LiDAR Data

Forest canopy height (FCH) is a critical parameter for forest management and ecosystem modeling, but there is a lack of accurate FCH distribution in large areas. To address this issue, this study selected Wuyishan National Park in China as a case study to explore the calibration method for mapping FCH in a complex subtropical mountainous region based on ZiYuan-3 (ZY3) stereo imagery and limited Unmanned Aerial Vehicle (UAV) LiDAR data. Pearson’s correlation analysis, Categorical Boosting (CatBoost) feature importance analysis, and causal effect analysis were used to examine major factors causing extraction errors of digital surface model (DSM) data from ZY3 stereo imagery. Different machine learning algorithms were compared and used to calibrate the DSM and FCH results. The results indicate that the DSM extraction accuracy based on ZY3 stereo imagery is primarily influenced by slope aspect, elevation, and vegetation characteristics. These influences were particularly notable in areas with a complex topography and dense vegetation coverage. A Bayesian-optimized CatBoost model with directly calibrating the original FCH (the difference between the DSM from ZY3 and high-precision digital elevation model (DEM) data) demonstrated the best prediction performance. This model produced the FCH map at a 4 m spatial resolution, the root mean square error (RMSE) was reduced from 6.47 m based on initial stereo imagery to 3.99 m after calibration, and the relative RMSE (rRMSE) was reduced from 36.52% to 22.53%. The study demonstrates the feasibility of using ZY3 imagery for regional forest canopy height mapping and confirms the superior performance of using the CatBoost algorithm in enhancing FCH calibration accuracy. These findings provide valuable insights into the multidimensional impacts of key environmental factors on FCH extraction, supporting precise forest monitoring and carbon stock assessment in complex terrains in subtropical regions.

Surrogate-assisted global and distributed local collaborative optimization algorithm for expensive constrained optimization problems

This paper presents a surrogate-assisted global and distributed local collaborative optimization (SGDLCO) algorithm for expensive constrained optimization problems where two surrogate optimization phases are executed collaboratively at each generation. As the complexity of optimization problems and the cost of solutions increase in practical applications, how to efficiently solve expensive constrained optimization problems with limited computational resources has become an important area of research. Traditional optimization algorithms often struggle to balance the efficiency of global and local searches, especially when dealing with high-dimensional and complex constraint conditions. For global surrogate-assisted collaborative evolution phase, the global candidate set is generated through classification collaborative mutation operations to alleviate the pre-screening pressure of the surrogate model. For local surrogate-assisted phase, a distributed central region local exploration is designed to achieve intensively search for promising distributed local areas which are located by affinity propagation clustering and mathematical modeling. More importantly, a three-layer adaptive selection strategy where the feasibility, diversity and convergence are balanced effectively is designed to identify promising solutions in global and local candidate sets. Therefore, the SGDLCO efficiently balances global and local search during the whole optimization process. Experimental studies on five classical test suites demonstrate that the SGDLCO provides excellent performance in solving expensive constrained optimization problems.