Potential Distribution Research Articles

Past, present and future in the geographical distribution of Mexican Tepezmaite cycads: Genus Ceratozamia.

Ceratozamia morettii, C. brevifrons, and C. tenuis are cycads considered endangered in montane forests in the center of Veracruz state. However, the amount of theoretical and empirical information available on the historical distribution of these species and how they could be affected in the future by the effects of climate change still needs to be increased. Our objective was to generate information on the spatial distribution of the species since the last glacial maximum, present, and future. To map the spatial distribution of species, we created a potential distribution model for each species. The spatial data used for the models included 19 bioclimatic data variables in the present, at the last glacial maximum using two models (CCSM4 and MIROC), and in the future (2080) using two models of the RCP 8.5 scenario of climate change (HadGEM2-CC and MIROC5). We found that each species occupies a unique ecoregion and climatic niche. Ceratozamia morettii and C. tenuis have a similar pattern with an expansion of their distribution area since the last glacial maximum with a larger distribution area in the present and a projected reduction in their distribution under future climatic conditions. For C. brevifrons, we also showed an increase in their distributional area since the last glacial maximum. We also showed that this expansion will continue under future climatic conditions when the species reaches its maximum distributional area. Projections about the future of these endemic cycad species show changes in their habitat, highlighting that temperate zone species (C. morettii and C. tenuis) will face imminent extinction if no effort is made to protect them. On the other hand, the tropical climate species (C. brevifrons) will be favored.

The past is uncertain: alternative responses of cloud forest mammals to the Last Glacial Maximum in the Oaxacan Highlands, Mexico

ABSTRACTThe Last Glacial Maximum (LGM; 26,000–19,000 years before the present) altered the distribution of species worldwide. Its effect is poorly known in tropical regions because the cooling and drought reached during that period are uncertain. Here, I generated hypotheses regarding the possible responses of cloud forest mammals in the Oaxacan Highlands (OH) of Mexico, a region with one of the most extensive cloud forests in the Neotropics. First, I used three General Circulation Models (GCMs: CCSM3, MIROC‐ESM and MPI) to characterize probable climates during the LGM. Then, I used ecological niche models to estimate the current and LGM potential distributions of four cloud forest species. As in other locations, the results show that GCMs are consistent with cooler conditions relative to today; however, the three GCMs estimate precipitation regimes with notable variations in the region. MPI indicates that the LGM could have been even wetter than present. Consequently, the MPI scenario allowed more widespread potential distributions of mammals. The paleodistributions show how mid‐ and lowlands were essential for the long‐term survival of these ‘high‐mountain mammals’ throughout the last glacial–interglacial cycle. The paleodistributions presented here are precise hypotheses that can be tested based on paleoecological and genetic evidence.

Spatial Conservation Prioritization for Land in Megacity Facing Climate Change and Biodiversity Loss

Climate change and biodiversity loss are two major threats to the world. Ecosystem conservation is an important issue for humanity, and international intergovernmental science-policy platforms highlight the mutually beneficial relationships among biodiversity conservation, ecosystem services and measures to mitigate climate change. Rapid urbanization has brought various deeply interconnected ecological problems to large cities. Therefore, key areas for conservation must be identified in an integrative manner to maximize conservation effectiveness and meet both ecological and human social needs. Spatial conservation prioritization provides a way to consider different functional needs as a whole in light of certain objectives while highlighting their contradictions and overlaps in spatial utilization. The megacity of Beijing continues to experience frequent extreme weather events despite the implementation of a series of ecological restoration measures. We integrated the potential distributions of 64 critically endangered native species to represent biodiversity and used five main ecosystem services required for climate governance to represent ecosystem services in the city. Using the spatial prioritization software Zonation 5, we assessed the spatial distribution of conservation priorities at the municipal scale and changes in conservation effectiveness in four protection scenarios. The results showed that the existing PAs in Beijing could protect 24.99% of the current distribution of biodiversity and ecosystem services. The conservation effectiveness can reach 78.75% when the PAs are increased to 30%. This efficiency rate is 4.46% lower than that of the optimal scenario, which does not consider the existing PAs. An emphasis on urban rewilding spaces may be the key to overcoming conservation bottlenecks to further enhance the efficiency of ecological conservation. To achieve future conservation targets, policy development may start with urban built-up areas.

Effects of joule heating and viscous dissipation on electromagneto-hydrodynamic flow in a microchannel with electroosmotic effect: Enhancement of MEMS cooling

This paper inspects the effect of Joule heating and viscous dissipation due to electric double layer (EDL) and electroosmotic effect on steady fully developed electromagnetohydrodynamic flow in a microchannel. Dimensionless formulations of the Poisson-Boltzmann, momentum, and energy equations are derived for the electric potential, velocity profile, and temperature distribution in the microchannel. Exact solutions for the temperature distributions and velocity profile were obtained using the method of undetermined coefficients. The Debye-Hückel linearization is used to get exact solution for the electric potential. The results showed that Brinkmann number [Formula: see text], Joule heating parameter [Formula: see text], Debye-Hückel parameter [Formula: see text], Hartmann number [Formula: see text], and electric field [Formula: see text] have a substantial impact on flow formation and heat transfer. The complex interaction between joule heating, viscous dissipation, and the EOF effect were accurately captured. The range values for the governing parameter for [Formula: see text], [Formula: see text], [Formula: see text], [Formula: see text], and [Formula: see text] are [Formula: see text], and[Formula: see text] respectively.

Modelling EEG Dynamics with Brain Sources

An electroencephalogram (EEG), recorded on the surface of the scalp, serves to characterize the distribution of electric potential during brain activity. This method finds extensive application in investigating brain functioning and diagnosing various diseases. Event-related potential (ERP) is employed to delineate visual, motor, and other activities through cross-trial averages. Despite its utility, interpreting the spatiotemporal dynamics in EEG data poses challenges, as they are inherently subject-specific and highly variable, particularly at the level of individual trials. Conventionally associated with oscillating brain sources, these dynamics raise questions regarding how these oscillations give rise to the observed dynamical regimes on the brain surface. In this study, we propose a model for spatiotemporal dynamics in EEG data using the Poisson equation, with the right-hand side corresponding to the oscillating brain sources. Through our analysis, we identify primary dynamical regimes based on factors such as the number of sources, their frequencies, and phases. Our numerical simulations, conducted in both 2D and 3D, revealed the presence of standing waves, rotating patterns, and symmetric regimes, mirroring observations in EEG data recorded during picture naming experiments. Notably, moving waves, indicative of spatial displacement in the potential distribution, manifested in the vicinity of brain sources, as was evident in both the simulations and experimental data. In summary, our findings support the conclusion that the brain source model aptly describes the spatiotemporal dynamics observed in EEG data.

Elucidating Piezoelectricity and Strain in Monolayer MoS2 at the Nanoscale Using Kelvin Probe Force Microscopy.

Strain engineering modifies the optical and electronic properties of atomically thin transition metal dichalcogenides. Highly inhomogeneous strain distributions in two-dimensional materials can be easily realized, enabling control of properties on the nanoscale; however, methods for probing strain on the nanoscale remain challenging. In this work, we characterize inhomogeneously strained monolayer MoS2 via Kelvin probe force microscopy and electrostatic gating, isolating the contributions of strain from other electrostatic effects and enabling the measurement of all components of the two-dimensional strain tensor on length scales less than 100 nm. The combination of these methods is used to calculate the spatial distribution of the electrostatic potential resulting from piezoelectricity, presenting a powerful way to characterize inhomogeneous strain and piezoelectricity that can be extended toward a variety of 2D materials.

Fine Scale Modeling for Potential Distribution of Dengue Fever in Tampan District, Indonesia

Larvisiding is one common way used to reduce mosquito density in breeding areas before metamorphosizing into adults. Despite numerous eradication efforts, the outcomes have not met expectations, leading to additional issues such as environmental pollution in urban areas. In the context of dengue hemorrhagic fever (DHF), addressing the challenge of mitigating the endemic outbreak entails formulating an effective strategy through a vector eradication approach. Therefore, this study explored the spatial pattern of DHF and estimated the potential spread of outbreaks. A geographic information system approach, with nearest neighbor analysis and kernel density estimation (KDE), was used to generate information regarding the pattern and potential for transmission of Aedes aegypti mosquitoes. The results showed that in 2019, a random pattern was observed, while in 2020, a clustered pattern of virus spread occurred. Furthermore, in terms of the potential transmission, an exposed zone of 9.73 km² was identified in 2019, and this increased to 15.72 km² in 2020. In this study, several important actions were implemented with a spatial approach, enabling the detection and polarization of events. However, the limitations included not being comprehensive in addressing the hygiene, sanitation, drainage, and population density aspects.

Current and future distribution of Eucalyptus globulus under changing climate in Ethiopia: implications for forest management

Eucalyptus globulus is a species endemic to southeastern Australia. It has naturalized non-native ranges in other parts of Australia, Europe, Africa, and the western United States. This study is the first of its kind in Ethiopia to model and map the spatiotemporal distribution of the species using species distribution models (SDMs). A total of 874 occurrence records were used from the online Global Biodiversity Information Facility (GBIF) database and field observation. Three environmental variables, including terrain, climate, and soil were used to predict the species’ distribution. The terrain, climate, and soil raster grids were resampled to a 200-meter resolution. The Global Circulation Model (GCM) HadGEM3-GC3.1 was used to extract future climate data. This GCM has a good match between the atmospheric and oceanic components showing little drift in its surface climate. Besides, it has the best coverage of Africa. Three climate change scenarios (SSPs 1-2.6, SSPs 2-4.5, and SSPs 5-8.5) were used for predicting suitable habitat of the species. The jackknife test was chosen to assess the importance of each environmental predictor variable. The model’s performance was evaluated using the Area under the Curve (AUC) of the Receiver Operating Characteristic (ROC) curve. The model had excellent predictive performance with an average AUC of 0.94. Altitude, rooting conditions, slope, dry-month precipitation, and temperature seasonality are the most important environmental factors in shaping E. globulus distribution. Ethiopian highlands are predicted to be more suitable to the species, but the increase in temperature seasonality may reduce suitable habitat under the high-forcing climate change scenario. Climate change is expected to create more suitable habitats for eucalyptus in the future which may encourage plantations in potential distribution areas. Consequently, ensuring long-term forest health necessitates robust management systems prioritizing native trees and responsible grower or farmer practices.

Maximum Entropy Model Prediction of the Distributions of Two Sympatric Bean Weevil Species, Megabruchidius dorsalis (Fahraeus, 1839) and Bruchidius coreanus (Chûjô, 1937), under Various Climate Scenarios in Guizhou Province, China

Megabruchidius dorsalis and Bruchidius coreanus are sympatric bean weevil species that bore into Gleditsia sinensis seeds, seriously affecting the commercial development of this plant. Here, we aimed to understand potential changes in the distribution of these two sympatric pests under current and future climate conditions to provide a reference for the prediction of their occurrence and facilitate their prevention and control. Based on empirical field data, we predicted the potential distribution of M. dorsalis and B. coreanus in suitable habitat areas using the MaxEnt model and explored the relationships among different spatiotemporal distributions using change analysis. Our findings showed that compared with the current situation, the suitable areas for M. dorsalis and B. coreanus were predicted to increase by 4.8141% and 3.1009%, respectively, in the future. Isothermality (BIO3), min temperature of coldest month (BIO6), and variance in precipitation (BIO15) in the coldest month were determined to be the main factors restricting the current distribution of M. dorsalis and B. coreanus. Areas currently suitable for the two species are mainly in the central region of Guizhou and are predicted to move eastward in the future. Significant area under the receiver operating characteristics curve values for M. dorsalis (0.878) and B. coreanus (0.833) indicated that MaxEnt could be used to predict the potential habitats of these weevils, providing valuable information to inform their control in Guizhou Province.

Biogeomorphological niche of a landform: Machine learning approaches reveal controls on the geographical distribution of Nitraria tangutorum nebkhas

AbstractNebkhas are distinctive biogeomorphological landforms prevalent in global drylands and coastal environments. They play a crucial role in supporting local biodiversity and preventing land desertification and often serve as an indicator of local environmental change. Despite their significance, the environmental factors that affect their geographical distribution and how they respond to climate change have not been fully explored. This study represents a novel application of machine learning models to quantifying the biogeomorphological niche of Nitraria nebkhas in northern China and simulating their geographical distribution under future climate change conditions. Findings underscore that climatic variables influence the growth of formative shrub species on nebkhas, whereas climate, soil and geomorphological conditions, along with their spatial configuration, determine the probability of nebkha occurrence. Predictions under medium and high greenhouse gas emission scenarios indicate a northward shift in the potential distribution of nebkhas in northern China by the end of the century, accompanied by a decrease in the south due to rising temperatures. Given the potential impact of nebkha field degradation on biodiversity and soil hydrological conditions, adaptive land use strategies should be designed to protect nebkhas and mitigate the impact of climate change. Our study not only provides valuable insights for informing policy‐making and conservation initiatives but also serves as an example for quantifying the niche of biogeomorphological landforms and simulating their dynamics by integrating machine learning approaches into empirical geomorphological studies.

Multi-scale habitat modeling framework for predicting the potential distribution of sheep gastrointestinal nematodes across Iran’s three distinct climatic zones: a MaxEnt machine-learning algorithm

Ecological niche models (ENMs) serve as valuable tools in assessing the potential species distribution, identifying crucial habitat components for species associations, and facilitating conservation efforts. The current study aimed to investigate the gastrointestinal nematodes (GINs) infection in sheep, predict and analyze their ecological niches and ranges, and identify the key bioclimatic variables influencing their distribution across three distinct climatic regions in Iran. In a cross-sectional study, a total of 2140 fecal samples were collected from semi-arid (n = 800), arid (n = 500), and humid-subtropical (n = 840) climates in East Azerbaijan, Kerman, and Guilan provinces, respectively. The flotation method was employed to assess stool samples, whereby the fecal egg count (the number of parasite eggs per gram [EPG]) was ascertained for each individual specimen. Employing a presence-only approach, the multi-scale maximum entropy (MaxEnt) method was used to model GINs' habitat suitability using 93 selected points/locations. The findings revealed that Guilan (34.2%) and East Azerbaijan (19.62%) exhibited the utmost proportion of Strongyle-type eggs. East Azerbaijan province also displayed the highest proportion of Marshallagia and Nematodirus, respectively (approximately 40% and 27%), followed by Guilan and Kerman provinces, while Kerman province had the highest proportion of Trichuris (approximately 15%). Ecological niche modeling revealed that the precipitation of the driest quarter (Bio17) exerted the most significant influence on Marshallagia, Nematodirus, Trichuris, and ُSُُُtrongyle-type eggs' presence in East Azerbaijan and Kerman provinces. For Guilan province, the most influential factor defining habitat suitability for Strongyle-type eggs, Marshallagia, and Nematodirus was increasing slope. Additionally, the distribution of Trichuris was most affected by the variable Bio2 in Guilan province. The study highlights the response of GINs to climate drivers in highly suitable regions, providing insights into ecologically favorable areas for GINs. In conclusion, this study provides a better understanding of GINs and the environmental factors influencing their transmission dynamics.

Impact of anthropogenic emission control in reducing future PM2.5 concentrations and the related oxidative potential across different regions of China

Affected by both future anthropogenic emissions and climate change, future prediction of PM2.5 and its Oxidative Potential (OP) distribution is a significant challenge, especially in developing countries like China. To overcome this challenge, we estimated historical and future PM2.5 concentrations and associated OP using the Danish Eulerian Hemispheric Model (DEHM) system with meteorological input from WRF weather forecast model. Considering different future socio-economic pathways and emission scenario assumptions, we quantified how the contribution from various anthropogenic emission sectors will change under these scenarios. Results show that compared to the CESM_SSP2–4.5_CLE scenario (based on moderate radiative forcing and Current Legislation Emission), the CESM_SSP1–2.6_MFR scenario (based on sustainability development and Maximum Feasible Reductions) is projected to yield greater environmental and health benefits in the future. Under the CESM_SSP1–2.6_MFR scenario, annual average PM2.5 concentrations (OP) are expected to decrease to 30 μgm−3 (0.8 nmolmin−1m−3) in almost all regions by 2030, which will be 65 % (67 %) lower than that in 2010. From a long-term perspective, it is anticipated that OP in the Fen-Wei Plain region will experience the maximum reduction (82.6 %) from 2010 to 2049. Largely benefiting from the effective control of PM2.5 in the region, it has decreased by 82.1 %. Crucially, once emission reduction measures reach a certain level (in 2040), further reductions become less significant. This study also emphasized the significant role of secondary aerosol formation and biomass-burning sources in influencing OP during both historical and future periods. In different scenarios, the reduction range of OP from 2010 to 2049 is estimated to be between 71 % and 85 % by controlling precursor emissions involved in secondary aerosol formation and emissions from biomass burning. Results indicate that strengthening the control of anthropogenic emissions in various regions are key to achieving air quality targets and safeguarding human health in the future.

Prediction of the potential distribution area of Spodoptera frugiperda and its parasitic wasp, Trichogramma pretiosum.

Spodoptera frugiperda is a migratory agricultural pest with fast-spreading speed, long migration distance, and wide host range, which seriously threatens the safety of economic crops. To predict the trends of S. frugiperda and its parasitoid wasp Trichogramma pretiosum in their habitats under current and future climatic conditions, based on MaxEnt model and geographic distribution data of their historical occurrence, we project the feasibility of introducing T. pretiosum to control S. frugiperda by evaluating on their potential global distribution. The results show that, under the current greenhouse gasconcentration, the potential distribution area of S. frugiperda is concentrated in 50° N-30° S, with a total area of 1.74 × 106 km2 , and the potential distribution area of T. pretiosum in the whole world is 2.91 × 106 km2 . The suitable areas of T. pretiosum cover almost all the suitable areas of S. frugiperda, which indicates that T. pretiosum can be introduced to control S. frugiperda. The results of this study can provide a theoretical basis for the monitoring and early warning of S. frugiperda and the use of T. pretiosum to control S. frugiperda.

Electromechanical behavior of piezolaminated shell structures with imperfect functionally graded porous materials using an improved solid-shell element

This work introduces a solid-shell element with eight nodes for the bending behavior of structures embedded with piezoelectric layers using the FSDT theory. The mechanical degrees of freedom are coupled, through the constitutive equations, with the piezoelectric one considering the linear distribution of the electric potential along the piezoelectric face's thickness. In order to subdue shear and thickness locking, the Assumed Natural Strain (ANS) method as well as the Enhanced Assumed Strain (EAS) method are adopted. Bonding the external faces of shell structures with piezofaces accentuates the smart aspect of solid shells. The middle part of the structure is made of a Functionally Graded Material (FGM) with distributed pores along the thickness. The formulated finite element model is implemented to investigate the effects of some parameters on the bending response of solid shells such as the impact of various configurations of porous FGM, the power law index of FGM and some geometrical parameters of solid shell structures.

Polarization of disk electrodes in high-conductivity electrolyte solutions.

We investigate the polarization of disk electrodes immersed in an electrolyte solution and subjected to a small external AC voltage over a wide range of frequencies. A mathematical model is developed based on the Debye-Falkenhagen approximation to the coupled Poisson-Nernst-Planck equations. Analytical techniques are used for predicting the spatial distribution of the electric potential and the complex impedance of the system. Scales for impedance and frequency are identified, which lead to a self-similar behavior for a range of frequencies. Experiments are conducted with gold electrodes of sizes in the range 100-350 μm immersed in a high-conductivity KCl solution over five orders of magnitude in frequency. A collapse of data on impedance magnitude and phase angle onto universal curves is observed with scalings motivated by the mathematical model. A direct comparison with the approximate analytical formula for impedance is made without any fitting parameters, and a good agreement is found for the range of frequencies where the analytical model is valid.

Potential Global Distribution of Paracoccus marginatus, under Climate Change Conditions, Using MaxEnt.

The papaya mealybug, Paracoccus marginatus, is an invasive pest species found all over the world. It is native to Mexico and Central America, but is now present in more than 50 countries and regions, seriously threatening the economic viability of the agricultural and forestry industry. In the current study, the global potential distribution of P. marginatus was predicted under current and future climatic conditions using MaxEnt. The results of the model assessment indicated that the area under the curve of the receiver operating characteristic ( ROC-AUC) was 0.949, while the TSS value was 0.820. The results also showed that the three variables with the greatest impact on the model were min temperature of coldest month (bio6), precipitation of wettest month (bio13), and precipitation of coldest quarter (bio19), with corresponding contributions of 46.8%, 31.1%, and 13.1%, respectively. The results indicated that the highly suitable areas were mainly located in tropical and subtropical regions, including South America, southern North America, Central America, Central Africa, Australia, the Indian subcontinent, and Southeast Asia. Under four climate scenarios in the 2050s and 2070s, the area of suitability will change very little. Moreover, the results showed that the area of suitable areas in 2070s increased under all four climate scenarios compared to the current climate. In contrast, the area of suitable habitat increases from the current to the 2050s under the SSP370 and SSP585 climate scenarios. The current study could provide a reference framework for the future control and management of papaya mealybug and other invasive species.

Prediction of the potential distribution and analysis of the freezing injury risk of winter wheat on the Loess Plateau under climate change

Determining the suitable areas for winter wheat under climate change and assessing the risk of freezing injury are crucial for the cultivation of winter wheat. We used an optimized Maximum Entropy (MaxEnt) Model to predict the potential distribution of winter wheat in the current period (1970–2020) and the future period (2021–2100) under four shared socioeconomic pathway scenarios (SSPs). We applied statistical downscaling methods to downscale future climate data, established a scientific and practical freezing injury index (FII) by considering the growth period of winter wheat, and analyzed the characteristics of abrupt changes in winter wheat freezing injury by using the Mann-Kendall (M-K) test. The results showed that the prediction accuracy AUC value of the MaxEnt Model reached 0.976. The minimum temperature in the coldest month, precipitation in the wettest season and annual precipitation were the main factors affecting the spatial distribution of winter wheat. The total suitable area of winter wheat was approximately 4.40×107 ha in the current period. In the 2070s, the moderately suitable areas had the greatest increase by 9.02×105 ha under SSP245 and the least increase by 6.53×105 ha under SSP370. The centroid coordinates of the total suitable areas tended to move northward. The potential risks of freezing injury in the high-latitude and -altitude areas of the Loess Plateau, China increased significantly. The northern areas of Xinzhou in Shanxi Province, China suffered the most serious freezing injury, and the southern areas of the Loess Plateau suffered the least. Environmental factors such as temperature, precipitation and geographical location had important impacts on the suitable area distribution and freezing injury risk of winter wheat. In the future, greater attention should be paid to the northward boundaries of both the winter wheat planting areas and the areas of freezing injury risk to provide the early warning of freezing injury and implement corresponding management strategies.

Current and Future Distribution of Camellia sinensis in China Estimated by MaxEnt

Tea (Camellia sinensis L.) is an important cash crop. In the context of climate change, analyzing the current distribution of tea trees and climate change environmental variables to predict the potential distribution area of tea trees in the future can help decision-makers make appropriate planting decisions and promote sustainable management. In this study, an optimized MaxEnt model was used to predict the limiting factors of tea tree growth and distribution under current and future climate change scenarios. The climate soil mixing model [area under the curve (AUC) = 0.934] performed excellently. The results showed that precipitation, temperature, slope, and soil factors all affected the distribution of suitable habitats for tea trees. Compared with the current distribution area of tea trees, under three shared socioeconomic pathways (SSP126, SSP245, and SSP585), the area of highly suitable habitats for tea trees will expand, especially in 2061–2080 and 2081–2100 years, and the suitable area will extend overall to the north of China, indicating that future climate change may create more new suitable habitats for tea production, especially in Shandong, Shaanxi, Guizhou, and Yunnan provinces. This study will provide important scientific insights for tea production decision-making, tea garden location selection, and future adaptation methods, and will help in the cultivation and transplantation of tea trees in the future.

The influence of climate oscillations and geological events on population differentiation of Camponotus japonicus in the Chinese mainland.

Camponotus japonicus (Hymenoptera: Formicidae) is an omnivorous social insect which builds sizable colonies in sparse woodlands or cropland and spreads across multiple climatic zones in the Chinese mainland. This study aims to reveal the role of climate changes and geological events in driving the genetic structure of social insect populations by investigating the phylogenetics and historical demography of C. japonicus in the Chinese mainland. Phylogenetic analyses were conducted based on the mitochondria DNA dataset using MrBayes and IQ-TREE. We constructed a haplotype network, calculated analyses of molecular variance, estimated the divergence time, and reconstructed the maximum clade credibility tree. Mismatch distribution and Bayesian skyline plots were used to infer historical population fluctuations. Additionally, ecological niche modeling was employed to predict the potential distribution of the species during the present, mid-holocene, and last glacial maximum periods in the Chinese mainland. The phylogenetic tree and median-joining network analyses support the presence of four distinct lineages in C. japonicus. These lineages exhibit significant genetic differentiation and limited gene flow. The divergence among the four lineages began in the early Pleistocene, approximately 1.41 million years ago (Ma). Subsequently, the central lineage diverged from both the northern and southern lineages around 1.16 Ma, while the northern and southern lineages diverged from each other at approximately 1.07 Ma. Population expansion was observed in the southern, central, and northern lineages prior to the last glacial maximum, while the Yunnan-Sichuan lineage experienced a slight increase in population size in more recent times. The predicted distribution of the species corresponds well with the actual distribution. Furthermore, the current suitable habitat areas in northern Xinjiang, southern Tibet, and the southeast coastal regions have significantly decreased compared to the last glacial maximum and the mid-holocene periods. Our results suggest that climate oscillations and geological events play an important role in driving genetic patterns and differentiation of C. japonicus. Mountain barriers isolate populations from each other, hinder the flow of genes, and effectively prevent the spread of this species. But at the same time, it also formed refugia at low altitudes areas such as Qinling-Bashan Mountains and Yanshan-Taihang Mountains and provide suitable habitats during glaciation. This study provides a good model for understanding how complex climate changes and geological events affect population genetic differentiation of social insects in the Chinese mainland.

Modeling the Effects of Climate Change on the Current and Future Potential Distribution of Berberis vulgaris L. with Machine Learning

Species of the Berberis genus, which are widely distributed naturally throughout the world, are cultivated and used for various purposes such as food, medicinal applications, and manufacturing dyes. Model-based machine learning is a language for specifying models, allowing the definition of a model using concise code, and enabling the automatic creation of software that implements the specified model. Maximum entropy (MaxEnt 3.4.1) is an algorithm used to model the appropriate distribution of species across geographical regions and is based on the species distribution model that is frequently also used in modeling the current and future potential distribution areas of plant species. Therefore, this study was conducted to estimate the current and future potential distribution areas of Berberis vulgaris in Türkiye for the periods 2041–2060 and 2081–2100, according to the SSP2 4.5 and SSP5 8.5 scenarios based on the IPSL-CM6A-LR climate change model. For this purpose, the coordinates obtained in the WGS 84 coordinate system were marked using the 5 m high spatial resolution Google Satellite Hybrid base maps, which are readily available in the 3.10.4 QGIS program, the current version of QGIS (Quantum GIS). The CM6A-LR climate model, the latest version of the IPSL climate models, was used to predict the species’ future distribution area. The area showed a high correlation with the points representing B. vulgaris, which is generally distributed in the Mediterranean and the central and eastern Black Sea regions of Türkiye, and the very suitable areas encompassed 45,413.82 km2. However, when the SSP2 4.5 scenario was considered for the period 2041–2060, the areas very suitable for Berberis vulgaris comprised 59,120.05 km2, and in the SSP2 4.5 scenario, very suitable areas were found to encompass 56,730.46 km2 in the 2081–2100 period. Considering the SSP5 8.5 scenario for the period 2041–2060, the area most suitable for the B. vulgaris species is 66,670.39 km2. In the SSP5 8.5 scenario, very suitable areas were found to cover 20,108.29 km2 in the 2081–2100 period. Careful consideration of both the potential positive and negative impacts of climate change is essential, and these should be regarded as opportunities to implement appropriate adaptation strategies. The necessary conditions for the continued existence and sustainability of B. vulgaris—that is, areas with ecological niche potential—have been determined.