Suitable Distribution Research Articles

Potential distribution prediction of Pomacea canaliculata in China based on the Biomod2.

Pomacea canaliculata is a globally significant invasive species that poses substantial threats to agricultural production, ecosystems, and human health in China. To evaluate its habitat suitability in China, we collected and collated 741 county-level occurrence points of P. canaliculata in China through database query, literature search and news reports, and obtained the five most important climatic factors by variance inflation factor and Pearson correlation coefficient from 19 bioclimatic factors. We investigated the potential suitable distribution areas of P. canaliculata under current and future climate scenarios using the Biomod2 ensemble model, and identified the primary environmental variables influencing their distributions. The results showed that under the current climate, the suitable habitat areas were concentrated in southern provinces or municipalities, such as Zhejiang, Shanghai, Fujian, Jiangxi, Guangdong, Guangxi, Hainan, and Yunnan. Under different climate scenarios in the future, the suitable habitat area would show large-scale expansion in the southern provinces or municipalities, and spread to the northern region. The most two important environmental factors affecting the distribution of suitable habitat areas were precipitation of wettest month and mean temperature of wettest quarter. A combination model to predict the potential distribution of P. canaliculata under current and future climate conditions would help manage the risk of its invasion and spread, and provide a reference for relevant regions and departments to take active measures in advance to prevent the spread, monitor and mitigate its invasion.

Mapping the Distribution of Curculio davidi Fairmaire 1878 under Climate Change via Geographical Data and the MaxEnt Model (CMIP6).

Curculio davidi is a major pest in chestnut-producing regions in China, and there have been many studies on its occurrence, biological characteristics, and management strategies. However, few of them have focused on the distribution changes of the pest under climate change. In this study, the MaxEnt model (version 3.3.4) and ArcGIS software (version 10.8) were first employed to map the current and future (2050 s and 2080 s) suitable habitat distribution of the weevil under climate change (CMIP 6: SSP1-2.6, SSP2-4.5, and SSP5-8.5). The results indicate that the highly suitable areas for C. davidi are mainly concentrated in Hubei, Henan, Anhui, Jiangxi, Jiangsu, Zhejiang, the coastal areas of Shandong, and eastern Guizhou, northwestern Hunan, and northeastern Sichuan provinces in China. Through the Jackknife test of 19 climate factors, six climate factors affecting the distribution of C. davidi were identified, with precipitation from July (Prec7), precipitation of warmest quarter (Bio18), and temperature seasonality (standard deviation × 100) (Bio4) contributing a combined percentage of 86.3%. Under three different climate scenarios (CMIP 6: SSP1-2.6, SSP2-4.5, and SSP5-8.5), the area of moderately suitable regions is projected to increase by 22.12-27.33% in the 2050 s and by 17.80-38.22% in the 2080 s compared to the current distribution, while the area of highly suitable regions shows a shrinking trend. This study provides data support for the management strategies of C. davidi and offers new insights into the dynamic changes of similar forestry pests.

Evaluating land suitability for kemiri (Aleurites moluccana) as a multi-purpose tree species in community agroforestry land within Langkat District, North Sumatra

Evaluating land suitability for Aleurites moluccana in community agroforestry land within Langkat District, North Sumatra, is crucial for promoting sustainable development, enhancing livelihoods, and preserving ecosystems while honoring local traditions and cultures. The primary objective of this research was to evaluate and map the land suitability for A. moluccana within Langkat District, located in North Sumatra, Indonesia. To gather the necessary data, this study employed a survey method, involving the collection of soil samples from ten distinct land units within the field. The assessment of land suitability was carried out using the matching method. Geographic Information System (GIS) technology was utilized to create maps illustrating the distribution of land suitability, while a Global Positioning System (GPS) was employed to accurately record the coordinates of the collected soil samples. The findings revealed that within Gunung Ambat, Simpang Kuta Buluh, Rumah Galuh, and Telagah Village, the actual land suitability classes for A. moluccana were classified as moderately suitable (S2) and marginally suitable (S3). The prevailing limiting factors in this region were temperature (tc) and the characteristics of the root zone medium (rc). Consequently, this influenced the potential land suitability classes for A. moluccana, resulting in classifications ranging from highly suitable (S1) to moderately suitable (S2) and marginally suitable (S3). By implementing land suitability evaluation for A. moluccana in community agroforestry land, promoting sustainable land use, enhancing livelihoods, and conserving natural resources.

Suitability Evaluation of Urban Underground Space Development: A Case Study of Qingdao City

Urban underground space, as an underutilized land resource, holds tremendous potential and value. Efficient and rational development and utilization of this resource are key to addressing current urban challenges. This study takes the main urban area of Qingdao City as an example and establishes a comprehensive evaluation system for the suitability of urban underground space development at different depth levels through the integration of geological, hydrological, and urban planning factors. By utilizing the Analytic Hierarchy Process to assign weights to evaluation criteria within the system, both a multi-objective linear weighting function model and a fuzzy comprehensive evaluation model are employed to assess the suitability of underground space development. The results delineate the distribution of underground space development suitability within the study area. Comparative analysis of the two models reveals that the fuzzy comprehensive evaluation model offers a more detailed and comprehensive reflection of the complexity and diversity of underground space development, providing forward-looking and insightful evaluation results for urban planning and development. The evaluation indicates that certain streets within the main urban area of Qingdao exhibit excellent prospects for underground space development.

Effect of climate change on current and future potential distribution of Strawberry tree (Arbutus unedo L.) in Türkiye

The demand for nontimber forest products (NTFPs) has increased significantly in recent years. Hundreds of plant species that grow naturally in Türkiye have medicinal and aromatic value. Medicinal and aromatic plants are primarily used as a sources of tea, spices, condiments and essential oils. Species belonging to the genus Arbutus L. are used for decorative purposes and as fuel wood in many wood-based industries, they also have a wide range of uses in packaging, chairs making and furniture production. Additionally, the fruits of these trees are widely consumed by humans and animals because they are rich in sugar and vitamin C. It is predicted that changes in climatic conditions will significantly change the distribution, composition and function of forests threatening biodiversity. The purpose of this study was to model current and future potential geographical distributions of Arbutus unedo L., which is among the species that naturally grow in Türkiye and is of substantial value in terms of its ecological contribution to forest ecosystems, based on species presence data and environmental variables (bioclimatic variables and altitude). The current and future distribution area models for Arbutus unedo L. indicate that the potential distribution areas of the species in the coming years will gradually decrease, and in the SSP5 8.5 model, which represents the highest level of world resource usage this gradual decrease will reach its highest level and there will be no suitable distribution area left for the species. Therefore, it is predicted that the species will become endangered. In-situ and ex-situ conservation measures need to be taken to ensure the sustainability of the species in forestry and landscape areas.

Will climate change cause Sargassum beds in temperate waters to expand or contract? Evidence from the range shift pattern of Sargassum

Understanding the range shift patterns of foundation species (e.g., macroalgae) under future climatic conditions is critical for biodiversity conservation in coastal ecosystems. These predictions are typically made using species distribution models (SDMs), and severe habitat loss has been predicted for most brown algal forests. Nevertheless, some models showed that local adaptation within species can reduce range loss projections. In this study, we used the brown algae Sargassum fusiforme and Sargassum thunbergii, which are distributed in the Northwest Pacific, to determine whether climate change will cause the Sargassum beds in Northwest Pacific temperate waters to expand or contract. We divided S. fusiforme and S. thunbergii into northern and southern lineages, considering the temperature gradients and phylogeographic structures. We quantified the realized niches of the two lineages using an n-dimensional hypervolume. Significant niche differentiation was detected between lineages for both species, suggesting the existence of local adaptation. Based on these results, lineage-level SDMs were constructed for both species. The prediction results showed the different responses of different lineages to climate change. The suitable distribution area for both species was predicted to move northward, retaining part of the suitable habitat at low latitudes (along the East China Sea). Unfortunately, this expansion could not compensate for losing middle-low latitude areas. Our results have important implications for the future management and protection of macroalgae and emphasize the importance of incorporating intraspecific variation into species distribution predictions.

Towards optimizing cooling rate, microstructure, and compressive strength in rapidly solidified Cu–20Fe alloy

There is currently interest in the development new Cu–Fe alloys with higher Fe content (>5 wt%), a low-cost element. In order to improve electrical, thermal and mechanical properties, there is a need to decrease the size of the Fe-rich phase and improve its distribution, whose possibilities rely on adding alloying third elements and heat treatments. However, the prospect of controlling the size of the phase through dendritic spacing control by means of rapid solidification processes may be feasible and deserves to be explored, as is the case in the present study. The following methods were employed to evaluate the round stepped cast samples of the Cu-20 wt% Fe alloy: centrifugal casting in a Cu mold, optical microscopy, CALPHAD, Scanning Electron Microscopy/Energy Dispersive Spectroscopy (SEM/EDS), X-ray Diffraction (XRD), Vickers hardness, and compressive tests, in samples corresponding to different coarsening microstructures. Finally, dendritic growth is modelled using the Kirkwood equation. The results demonstrate a promising processing route with control of the secondary dendrite arm spacing (SDAS), whose methodology and modeling can serve as a basis for other alternative processes with the Cu–Fe alloys, allowing suitable size and distribution of Fe phase to be attained. It is further demonstrated that the Kirkwood model is able to match experimental SDAS in both slowly and rapidly solidified Cu–Fe samples. While Fe (BCC) is expected to increase strength, this is only slightly observed in the hardness results for smaller SDAS, as the loads are more superficial. In the case of compressive yield strength, SDAS in the observed range (1.4 μm–2.2 μm) is found to have no effect.

The Distribution Range of Populus euphratica Oliv. (Salicaceae) Will Decrease Under Future Climate Change in Northwestern China

Climate change has been regarded as a primary threat to biodiversity at local, regional, and global scales. Populus euphratica Oliv. is one of the main constructive species in dryland regions and has a key role in regulating ecosystem processes and services. However, there is a knowledge gap regarding the spatial distribution of habitat suitability of P. euphratica and how it will be affected by future climate change. Based on the distribution records collected from an online database and specialized literature, we applied an optimized MaxEnt model to predict the distribution range of P. euphratica in China under four climate change scenarios (SSP126, SSP245, SSP370, and SSP585) for both current and future (2090s) conditions. We found that (1) future climate change would reduce the adaptability of P. euphratica, resulting in a significant decrease in its distribution area; (2) water availability had the most important effect on P. euphratica distribution; (3) the habitat for P. euphratica would shift northwestward and contract towards lower elevations closer to rivers in the future. These findings can provide a reference for developing long-term biodiversity conservation and management strategies in arid regions.

Prediction of Adaptability of Typical Vegetation Species in Flood Storage Areas under Future Climate Change: A Case in Hongze Lake FDZ, China

China experiences frequent heavy rainfall and flooding events, which have particularly increased in recent years. As flood storage zones (FDZs) play an important role in reducing disaster losses, their ecological restoration has been receiving widespread attention. Hongze Lake is an important flood discharge area in the Huaihe River Basin of China. Previous studies have preliminarily analyzed the protection of vegetation zones in the FDZ of this lake, but the future growth trend of typical vegetation in the area has not been considered as a basis for the precise protection of vegetation diversity and introductory cultivation of suitable species in the area. Taking the FDZ of Hongze Lake as an example, this study investigated the change trend of the suitability of typical vegetation species in the Hongze Lake FDZ based on future climate change and the distribution pattern of the suitable areas. To this end, the distribution of potentially suitable habitats of 20 typical vegetation species in the 2040s was predicted under the SSP1-2.6, SSP2-4.5, SSP3-7.0, and SSP5-8.5 climate scenarios using the latest Coupled Model Intercomparison Project CMIP6. The predicted distribution was compared with the current distribution of potentially suitable habitats. The results showed that the model integrating high-performance random forest, generalized linear model, boosted tree model, flexible discriminant analysis model, and generalized additive model had significantly higher TSS and AUC values than the individual models, and could effectively improve model accuracy. The high sensitivity of these 20 typical vegetation species to temperature and rainfall related factors reflects the climatic characteristics of the study area at the junction of subtropical monsoon climate and temperate monsoon climate. Under future climate scenarios, with reference to the current scenario of the 20 typical species, the suitability for Nelumbo nucifera Gaertn decreased, that for Iris pseudacorus L. increased in the western part of the study area but decreased in the eastern wetland and floodplain, and the suitability of the remaining 18 species increased. This study identified the trend of potential suitable habitat distribution and the shift in the suitability of various typical vegetation species in the floodplain of Hongze Lake. The findings are important for the future enhancement of vegetation habitat conservation and suitable planting in the study area, and have implications for the restoration and conservation of vegetation diversity in most typical floodplain areas.

RAD-seq data for Engelhardia roxburghiana provide insights into the palaeogeography of Hainan Island and its relationship to mainland China since the late Eocene

Hainan Island in southern China is situated within the Indo-Burma biodiversity hotspot, and has attracted the attention of evolutionary biologists, geologists, and biogeographers. However, the palaeogeography of Hainan Island and its relationship with mainland China remains contested. In this paper, we report RAD-seq data for Engelhardia roxburghiana populations from Hainan Island and adjacent mainland areas to identify genetic diversity, structure, divergence time, and demographic dynamics over geologic time. Findings were assessed using climate model data to constrain suitable distribution areas. Results indicate that E. roxburghiana dispersed from the Chinese mainland to Hainan Island via a hypothetical land bridge during the late Eocene so that the drift of Hainan Island was impossible. We cast doubt on the hypothesis that Hainan Island was connected to Vietnam and Guangxi at this time. We emphasize that higher genetic diversity in the Yunnan-Guizhou Plateau and Chiang-nan regions is the result of mixed populations or the existence of refugia, and lower genetic diversity in the Indochina Peninsula is due to a historical bottleneck. From the late Eocene to Oligocene, the arid belt that dominated East Asia retreated, facilitating the expansion of E. roxburghiana from the Indochina Peninsula to southern China. The main diversification of E. roxburghiana occurred in the Miocene following the strengthening precipitation within the East Asian Summer Monsoon. Climatic oscillations during the Quaternary led to the contraction of E. roxburghiana in the Indochina Peninsula, with expansion after Last Glacial Period (LGP; 119 to 11.7 ka). Southern China has served as a refugium and continues to do so in the future. In summary, our study elucidates the evolutionary trajectory of E. roxburghiana through large-scale sampling, providing insights into the palaeogeography of Hainan Island and itsbiogeographic relationships with adjacent mainlands.

Prediction of potential suitable distribution for sweet cherry (Prunus avium) based on the MaxEnt model.

The sweet cherry (Prunus avium) is among deciduous fruit trees with high economic value and its planting area is gradually expanding. However, little was known about its accurately suitable area in China. Herein, the potential distributions were modeled based on the MaxEnt model under the current conditions. Its performance was excellent, with AUCs >0.9 for model training and testing. The key environmental factors were the thermal factors (minimum temperature of the coldest month (bio06) from -14.5 to 4.5°C, the mean temperature of the warmest quarter (bio10) from 21.0 to 28.0°C), followed by the water factor (the annual precipitation (bio12) from 500 to 1200 mm), indicating that it is not resistant to cold and heat, nor is it resistant to drought or floods. The suitable area in China mainly is found in seven geographical regions including southwest China (eastern Sichuan, northeast and main urban areas of Chongqing, mid-western Guizhou and mid-northern Yunnan), northwest China (mid-southern Shaanxi, southern Ningxia mid-southern and eastern Gansu), northeast China (Coastal region of Liaoning), central China (most of Henan, mid-northern Hubei and central Hunan), north China (Beijing, Tianjing, mid-southern Shanxi), east China (Shanghai, Jiangsu, Shandong, central Zhejiang, central and northern Anhui and eastern Jiangxi) and south China (western Guangxi). Based on statistical analysis, these fourteen provinces or cities, namely, Shaanxi, Beijing, Tianjing, Shanxi, Hebei, Henan, Shanghai, Jiangsu, Shandong, Sichuan, Guizhou, Yunnan, Liaoning and Hubei were the main regions for current development and utilization while for the twelve provinces with higher moderate suitable areas, namely, Chongqing, Guizhou, Yunnan, Shaanxi, Ningxia, Liaoning, Hubei, Hunan, Zhejiang, Anhui, Jiangxi and Guangxi, we should supplement the appropriate irrigation and winter insulation facilities etc. Additionally, Hubei, Hunan, Anhui, also have been identified to have some potentially suitable areas. These information will help avoid the loss of human labor, material, and financial resources and provide a scientific basis for its current introduction, cultivation, and management.

A Bayesian approach with double group sampling plan to estimate quality regions for proportion of nonconforming products in industry based on beta prior

To succeed in the global market, firms must prioritize quality over individual goals and preferences. One of the two primary approaches for ensuring quality is acceptance sampling, which is employed in statistical process control to inspect attributes of the product for acceptance. In acceptance sampling, the lot is either accepted or not-accepted based on predetermined acceptance criteria for inspection. This paper presents a proposed Bayesian double group sampling plan (BDGSP) for estimating quality regions. The binomial distribution is used to construct the likelihood function for both nonconforming and conforming products based on acceptance criteria. To calculate the average probability of acceptance, the beta distribution is used as a suitable prior distribution of the binomial distribution. Four distinct quality regions are predicted for various indicated producer’s and consumer’s risk levels. Based on various combinations of values for design parameters, the suggested plan generates variation point values. Risks for producers and consumers are related to acceptable quality level and limiting quality level. To track the effects of changes in the values of the specified parameters, operating characteristic curves are utilized. The applicability of the proposed plan for current industrial strategies is demonstrated using a real dataset.

Possible changes of Pinus nigra distribution regions in Türkiye with the impacts of global climate change

Global climate change poses significant threats to ecosystems worldwide, particularly impacting long-lived forest tree species such as Pinus nigra. This study assessed the potential shifts in distribution areas for Pinus nigra, an important tree species, one highly vulnerable to global climate change, given its prevalence in continental climates, in Türkiye under different climate scenarios (SSPs 585 and 245). In this study, suitable distribution regions of Pinus nigra were evaluated based on SSPs 585 and SSPs 245 using nine different models. Results indicated potential losses in Pinus nigra distribution areas ranging from 15.0% to 43.5% (SSPs 245) and 19.7% to 48.9% (SSPs 585) by 2100. However, in 2100, new suitable distribution areas are expected to be formed at rates ranging from 13.8% to 32.1% and 15.1% to 34.4% according to the above scenarios. Because most of the newly formed suitable distribution regions are quite far from the areas where the species currently spreads, it seems necessary to provide the migration mechanism needed by the species by humans to prevent population losses in this process.

Processing of fully dense and high conductivity W[sbnd]20Cu composite via copper melt infiltration into a pressed tungsten wire skeleton

The current study proposed melt infiltration into entangled pressed wire as a proper method for rapid and energy-efficient production of tungsten‑copper composites. The process includes wire packing through different strategies, pressing, and infiltration steps. First, a predesigned wire structure through different strategies of simple, spiral, cylindrical, and spherical is packed and pressed to form a permeable tungsten skeleton. Then, by infiltrating molten copper under a dry hydrogen atmosphere into the porous preforms, the W20Cu composite is fabricated and characterized. An almost fully dense sample with excellent hardness of 238.1 HV1 and high conductivity of 58.64% IACS in W20Cu composite was achieved. These values are almost 25% and 50% higher than that from the conventional melt infiltration method, respectively. It was seen that the packing strategy is so effective in achieving the best properties where the processed composite by spherical packing strategy exhibits better density, conductivity, and hardness than the sample produced via the other three packing strategies. However, all the properties of the melt infiltration into entangled pressed wire processed composite via all packing strategies are higher than those processed via conventional methods. These excellent properties could be attributed to the mostly bonded tungsten phase, high purity, pore-free, and suitable distribution of tungstens which are a result of this process characteristics. Besides, lower cycle time and energy consumption are other advantages of the new process compared to conventional melt infiltration via powder metallurgy. This approach presents a promising prospect for future industrial applications.

Local calibration of flexible performance models using maximum likelihood estimation approach

The pavement mechanistic-empirical design (PMED) is a widely used pavement analysis and design approach. The transfer functions are generally calibrated to implement the PMED for local conditions. The least square (LS) approach has been commonly used to calibrate these transfer functions. Although LS is a simplistic approach, the assumptions may not be valid, especially for non-normally distributed data. This paper uses the maximum likelihood estimation (MLE) approach to calibrate bottom-up cracking, total rutting, and international roughness index (IRI) transfer function for flexible pavements. The results show that overall, MLE outperforms the LS approach for synthetic and measured data. The difference is more evident in the case of bottom-up cracking data, which does not follow a normal distribution. Gamma distribution for bottom-up cracking and total rutting, whereas negative binomial for IRI is the most suitable distribution for the MLE approach. Overall, MLE using resampling methods provides a robust and better estimate than the LS approach.

Probability of maximum values of stress concentration factors in tubular DKT-joints reinforced with FRP under axial loads

In the paper, the most suitable probability distributions for SCFmax in DKT-Joints stiffened with FRP under axial loading conditions are studied. To this end, 1296 models were generated and then analyzed in the ANSYS to provide five reliable samples. Created FE models were validated using previous laboratory and FE data. Afterward, to predict the appropriate probability distribution models, 12 different kinds of distributions were utilized to check the fit distribution curve to the samples. Next, the accuracy and reliability of the distribution curves were assessed with the help of goodness-of-fit tests, such as the Kolmogorov-Smirnov (KS) and the Chi-squared (CS). The results of the analysis reveal that the Birnbaum-Saunders distribution is the best option. Furthermore, based on the probability graphs, it was concluded that the developed distribution is suitable enough for the given data sets.

High-Efficiency Photo-Fenton-like Catalyst of FeOOH/g-C3N4 for the Degradation of PNP: Characterization, Catalytic Performance and Mechanism Exploration.

The composite photocatalyst FeOOH/g-C3N4 was prepared through thermal polycondensation and co-precipitation methods, followed by XRD, SEM and UV-vis characterization. The stability of FeOOH/g-C3N4 was explored by the recycling test. The active species in the reaction system were investigated by the capture experiment. The results indicated that the optimal preparation condition for g-C3N4 involved calcination at 600 °C for 4 h. XRD analysis revealed that g-C3N4 exhibits a high-purity phase, and Fe in FeOOH/g-C3N4 exists in a highly dispersed amorphous state. SEM analysis showed that FeOOH/g-C3N4 has a rough surface with an irregular layered structure. Element composition analysis confirmed that the content of elements in the prepared catalyst is consistent with the theoretical calculation. FeOOH/g-C3N4 possesses the largest specific surface area of 143.2 m2/g and a suitable pore distribution. UV-vis DRS analysis showed that the absorption intensity of FeOOH/g-C3N4 is stronger than that of g-C3N4. When the catalyst dosage was 1.0 g/L, the H2O2 dosage was 4 mmol/L, the PNP initial concentration was 10 mg/L and the initial pH value was 5, the PNP removal could reach 92% in 120 min. Even after 5 cycles, the efficiency of PNP removal by FeOOH/g-C3N4 remains nearly 80%. The capture experiment indicated that both •OH and •O2- play roles in the photocatalytic degradation of PNP, with •OH being more significant. These findings affirm that FeOOH has been successfully incorporated into g-C3N4, resulting in a conspicuous catalytic effect on the degradation of PNP in the visible light-assisted Fenton-like reaction.

A suitable probability distribution for the prediction of rainfall in northern regions of Kashmir Himalaya

A suitable probability distribution for the prediction of rainfall in northern regions of Kashmir Himalaya

Empirical Model of Equatorial ElectroJet (EEJ) Using Long‐Term Observations From the Indian Sector

AbstractThe Equatorial Electrojet (EEJ) is one of the important near‐earth space weather phenomena which exhibits significant diurnal, seasonal and solar activity variations. This paper investigates the EEJ variations at diurnal, seasonal and solar cycle time scales from the Indian sector and portrays a new empirical EEJ field model developed using the observations spanning over nearly two solar cycles. The Method of Naturally Orthogonal Components (MNOC), also known as Principal Component Analysis (PCA), was employed to extract the dominant patterns of principal diurnal, semi‐diurnal, and ter‐diurnal components contributing to the EEJ variation. The amplitudes of these diurnal, semi‐diurnal, and ter‐diurnal components in EEJ are found to vary significantly with the season and solar activity. The seasonal and solar activity dependencies of these principal components are modeled using suitable bimodal distribution functions. Finally, the empirical model for EEJ field was built by combining the principal components with their corresponding modeled amplitudes. This model accurately reproduces the diurnal, seasonal and solar activity variations of EEJ. The modeled monthly mean variations of EEJ field at ground exhibit excellent correlation of 0.96 with the observations with the root mean square error <5 nT. It also successfully captures the seasonal and solar activity variations of Counter Electrojet (CEJ). Finally, this model named “Indian Equatorial Electrojet (IEEJ) Model” is made publicly available for interested scientific users (https://iigm.res.in/system/files/IEEJ_model.html).

Global climate change-driven impacts on the Asian distribution of Limassolla leafhoppers, with implications for biological and environmental conservation.

Knowing the impacts of global climate change on the habitat suitability distribution of Limassolla leafhoppers contributes to understanding the feedback of organisms on climate change from a macroecological perspective, and provides important scientific basis for protecting the ecological environment and biodiversity. However, there is limited knowledge on this aspect. Thus, our study aimed to address this gap by analyzing Asian habitat suitability and centroid shifts of Limassolla based on 19 bioclimatic variables and occurrence records. Selecting five ecological niche models with the outstanding predictive performance (Maxlike, generalized linear model, generalized additive model, random forest, and maximum entropy) along with their ensemble model from 12 models, the current habitat suitability of Limassolla and its future habitat suitability under two Shared Socio-economic Pathways (SSP1-2.6 and SSP5-8.5) in the 2050s and 2090s were predicted. The results showed that the prediction results of the five models are generally consistent. Based on ensemble model, 11 potential biodiversity hotspots with high suitability were identified. With climate change, the suitable range of Limassolla will experience both expansion and contraction. In SSP5-8.52050s, the expansion area is 118.56 × 104 km2, while the contraction area is 25.40 × 104 km2; in SSP1-2.62090s, the expansion area is 91.71 × 104 km2, and the contraction area is 26.54 × 104 km2. Furthermore, the distribution core of Limassolla will shift toward higher latitudes in the northeast direction, and the precipitation of warmest quarter was found to have the greatest impact on the distribution of Limassolla. Our research results supported our four hypotheses. Finally, this research suggests establishing ecological reserves in identified contraction to prevent habitat loss, enhancing the protection of biodiversity hotspots, and pursuing a sustainable development path with reduced emissions.