Xanthium strumarium L., an invasive species in the subtropics: prediction of potential distribution areas and climate adaptability in Pakistan.

Invasive species such as Xanthium strumarium L., can disrupt ecosystems, reduce crop yields, and degrade pastures, leading to economic losses and jeopardizing food security and biodiversity. To address the challenges posed by invasive species such as X. strumarium, this study uses species distribution modeling (SDM) to map its potential distribution in Pakistan and assess how it might respond to climate change. This addresses the urgent need for proactive conservation and management strategies amidst escalating ecological threats. SDM forecasts a species' potential dispersion across various geographies in both space and time by correlating known species occurrences to environmental variables. SDMs have the potential to help address the challenges posed by invasive species by predicting the future habitat suitability of species distributions and identifying the environmental factors influencing these distributions. Our study shows that seasonal temperature dependence, mean temperature of wettest quarter and total nitrogen content of soil are important climatic factors influencing habitat suitability of X. strumarium. The potential habitat of this invasive species is likely to expand beyond the areas it currently colonizes, with a notable presence in the Punjab and Khyber Pakhtunkhwa regions. These areas are particularly vulnerable due to threats to agriculture and biodiversity. Under current conditions, an estimated 21% of Pakistan's land area is infested by X. strumarium, mainly in upper Punjab, central Punjab and Khyber Pakhtunkhwa. The range is expected to expand in most regions except Sindh. The central and northeastern parts of the country are proving to be particularly suitable habitats for X. strumarium. Effective strategies are crucial to contain the spread of X. strumarium. The MaxEnt modeling approach generates invasion risk maps by identifying potential risk zones based on a species' climate adaptability. These maps can aid in early detection, allowing authorities to prioritize surveillance and management strategies for controlling the spread of invasive species in suitable habitats. However, further research is recommended to understand the adaptability of species to unexplored environments.

Research on planting planning of Glycyrrhiza uralensis in Naiman Banner based on MaxEnt model and remote sensing technology.

Benefits of Glycyrrhiza uralensis include removing heat, detoxifying, and moistening the lungs, easing coughs, refueling the spleen, and balancing medications. In addition to providing theoretical guidance for the development of the G. uralensis industry and rural revitalization plan, it is anticipated that this paper will also provide basic data for the formulation of production layout of the G. uralensis industry at the county level, the control of cultivation industry direction, the establishment of high-quality G. uralensis cultivation technology system. The Maximum Entropy (MaxEnt) model was used to simulate the potential distribution of G. uralensis, a Chinese medicine resource, in Naiman Banner. By conducting a field inquiry and a broad assessment of the available Chinese medicine resources, the distribution information was acquired. The random forest technique was used to classify G. uralensis. The phenological cycle and development mode of vegetation, which exhibits diverse temporal traits and aids in identification, were elucidated through long-term series analysis. The random forest classification algorithm based on multiple features showed high accuracy in remote sensing (RS) recognition of G. uralensis. Comparative analysis of the MaxEnt and RS results showed that the planting area of G. uralensis was smaller than that of its potential distribution. The expansion to high-suitability areas planting should be prioritized. Based on the dual analysis of regional and remote sensing, it not only proved the great potential of using geographic information to predict the distribution of G. uralensis, but also verified the great potential of extracting the distribution of G. uralensis from GF-6 images. These results will guide the planting and development of G. uralensis in Naiman Banner and a scientific basis for the development of G. uralensis economy, conducive to optimizing the ecological environment and promoting rural revitalization programs.

Assessment of suitable region of Asparagus cochinchinensis (Lour.) Merr. under different climatic conditions in China by the MaxEnt model and HPLC analysis.

Asparagus cochinchinensis is a member of the Asparagaceae family whose medicinal part is the dried root tuber. The distribution of A. cochinchinensis and its secondary metabolites are closely associated with environmental factors, such as climate and soil properties. By establishing and optimizing a maximum entropy model, we analyzed and predicted the distribution pattern and migration direction of suitable habitats for A. cochinchinensis and determined the main environmental factors affecting the accumulation of secondary metabolites. Under current climatic conditions, the area of suitable habitats for A. cochinchinensis (208.38 × 104 km2) accounts for 21.71% of the land area of China, and the areas of lowly, moderately, and highly suitable areas were 64.15 × 104 km2, 113.66 × 104 km2, and 30.57 × 104 km2, respectively. Under future climate scenarios, the total area of suitable habitats hardly changes. The area of highly suitable habitats significantly decreases under the SSP1-RCP2.6 scenario (to 83.22% of the current value) and the SSP3-RCP7 scenario (to 48.94% of the current value), but eventually increases to 112.86% of the current value under the SSP5-RCP8.5 scenario, which indicates that A. cochinchinensis might adapt better to a high-carbon-emissions scenario. Under different climate scenarios, low-impact areas mainly occur in southern China and will correspond 92.07% of the current suitable area. Highly suitable habitats primarily occur in the southeastern Sichuan Basin, northern Guangxi, eastern Guizhou, and western Hunan. HPLC analysis showed that the content of protodioscin (0.373%) and protogracillin (0.044%) in S2 was the highest. The total saponins contents of S1 and S2 were the highest, which were 35.6586 and 33.1262 mg/g, respectively. The total polysaccharide content of S9 was the highest (16.9467%). The total contents of saponins and polysaccharides in A. cochinchinensis were significantly, but oppositely, correlated with temperature, precipitation, and other factors. This study has identified environmental factors affecting the growth and quality of A. cochinchinensis, which has guiding significance for resource conservation and site selection for large-scale cultivation.

Reconstructing the biological invasion of noxious invasive weed Parthenium hysterophorus and invasion risk assessment in China.

Invasive alien plants (IAPs) present a severe threat to native ecosystems and biodiversity. Comprehending the potential distribution patterns of these plant invaders and their responses to climate change is essential. Parthenium hysterophorus, native to the Americas, has become an aggressively invasive species since its introduction to China in the 1930s. This study aims to collect and reconstruct the historical occurrence and invasion of P. hysterophorus. Using the optimal MaxEnt model, the potential geographical distributions of P. hysterophorus were predicted based on screened species occurrences and environmental variables under the current and three future scenarios in the 2030s, 2050s, and 2070s (i.e., SSP1-2.6, SSP2-4.5, and SSP5-8.5), and the invasion risk of P. hysterophorus in Chinese cities, croplands, forests, and grasslands was assessed. The results show that: (1) The species initially invaded highly suitable areas and further spread to regions with non-analogous climate conditions. (2) Under the current climatic conditions, the overall potential distribution of P. hysterophorus is characterized by more in the southeast and less in the northwest. Climate variables, including mean annual temperature (bio1), precipitation in the wettest month (bio13), isothermality (bio3), and temperature seasonality (bio4), are the primary factors influencing its distribution. (3) The potential distribution of P. hysterophorus will expand further under future climate scenarios, particularly toward higher latitudes. (4) Forests and crop lands are the areas with the most serious potential invasion risk of P. hysterophorus. Therefore, we suggest that the government should strengthen the monitoring and management of P. hysterophorus to prevent its spread and protect agro-ecosystems and human habitats. Depending on the potential risk areas, measures such as quarantine, removal, and publicity should be taken to mitigate the threat of P. hysterophorus invasion and to raise awareness of P. hysterophorus invasion prevention.

Predicting the geographical potential distribution of species Opisina arenosella Walker in China under different climate scenarios based on the MaxEnt model.

As global warming increases with the frequency of extreme weather, the distribution of species is inevitably affected. Among them, highly damaging invasive species are of particular concern. Being able to effectively predict the geographic distribution of invasive species and future distribution trends is a key entry point for their control. Opisina arenosella Walker is an invasive species, and its ability to live on the backs of foliage and generate canals to hide adds to the difficulty of control. In this paper, the current and future distributions of O. arenosella under three typical emission scenarios in 2050 and 2090 are projected based on the MaxEnt model combining 19 bioclimatic variables. Filter through the variables to find the four key environment variables: BIO 1, BIO 6, BIO 11 and BIO 4. The results show that O. arenosella is distributed only in the eight provinces of Tibet, Yunnan, Fujian, Guangxi, Taiwan, Guangdong, Hong Kong and Hainan in the southeastern region. Its high suitability area is concentrated in Taiwan and Hainan. In the long run, highly suitable areas will continue to increase in size, while moderately suitable areas and poorly suitable areas will decrease to varying degrees. This paper aims to provide theoretical references for the control of O. arenosella.

Genetic diversity, population structure and ecological niche modeling of Thyrinteina arnobia (Lepidoptera: Geometridae), a native Eucalyptus pest in Brazil.

Thyrinteina arnobia (Lepidoptera: Geometridae) is a native American species. Despite its historical importance as an insect pest in Eucalyptus plantations, more information is needed regarding the population diversity, demography, and climatic variables associated with its distribution in different regions of Brazil. We used a phylogeographic approach to infer the genetic diversity, genetic structure, and demographic parameters of T. arnobia. We also conducted an ecological niche modeling (ENM) to predict suitable areas for T. arnobia occurrence in Brazil and other countries worldwide. Although T. arnobia populations have low genetic diversity in Brazil, we identified mitochondrial haplogroups predominating in different Brazilian regions and high ФST and ФCT values in AMOVA, suggesting a low frequency of insect movement among these regions. These results indicate that outbreaks of T. arnobia in Eucalyptus areas in different regions of Brazil are associated with local or regional populations, with no significant contribution from long-distance dispersal from different regions or biomes, suggesting that pest management strategies would be implemented on a regional scale. In Brazil, the demographic and spatial expansion signals of T. arnobia seem to be associated with the history of geographical expansion of Eucalyptus plantations, a new sustainable host for this species. ENM indicated that isothermality and annual rainfall are critical climatic factors for the occurrence of T. arnobia in tropical and subtropical areas in the Americas. ENM also suggested that T. arnobia is a potential pest in Eucalyptus areas in all Brazilian territory and in regions from Africa, Asia, and Oceania.

Predicting potential habitat distribution of the invasive species Rhynchophorus ferrugineus Olivier in China based on MaxEnt modelling technique and future climate change.

Changes in the distribution of species due to global climate change have a critically significant impact on the increase in the spread of invasive species. An in-depth study of the distribution patterns of invasive species and the factors influencing them can help to better predict and combat invasive alien species. Rhynchophorus ferrugineus Olivier is an invasive species that primarily harms plants of Trachycarpus H. Wendl. The pest invades trees in three main ways: by laying eggs and incubating them in the crown of the plant, on roots at the surface and at the base of the trunk or petiole. Most of the plants in the genus Trachycarpus are taller, and the damage is concentrated in the middle and upper parts of the plant, making control more difficult. In this paper, we combine 19 bioclimatic variables based on the MaxEnt model to project the current and future distributions of R. ferrugineus under three typical emission scenarios (2.6 W m-2 (SSP1-2.6), 4.5 W m-2 (SSP2-4.5) and 8.5 W m-2 (SSP5-8.5)) in the 2050s and 2090s. Among the 19 bioclimatic variables, five variables were screened out by contribution rates, namely annual mean temperature (BIO 1), precipitation of driest quarter (BIO 17), minimum temperature of coldest month (BIO 6), mean diurnal range (BIO 2) and precipitation of wettest quarter (BIO 16). These five variables are key environmental variables that influence habitat suitability for R. ferrugineus and are representative in reflecting its potential habitat. The results showed that R. ferrugineus is now widely distributed in the southeastern coastal area of China (high suitability zone), concentrating in the provinces of Hainan, Guangdong, Fujian, Guangxi and Taiwan. In the future, the area of high and low suitability zones will increase and the area of medium suitability zones will decrease. The area of low suitability zone will still be in the largest proportion. This study aims to provide a theoretical reference for the future control of R. ferrugineus from the perspective of geographic distribution.

Enhancing bird habitat networks in metropolitan areas: Resilience assessment and improvement strategies - A case study from Shanghai.

Constructing bird habitat networks (BHNs) is crucial for maintaining the health and service equilibrium of urban ecosystems, especially in large metropolitan areas where the pressure of urbanization is intense. However, most existing BHNs fail to account for the dynamic changes and unique requirements of local species, leading to homogenized construction outcomes and ecological corridor objectives. This study employs a comprehensive approach to identify bird habitat patches using multiple high-quality sources, then utilize circuit theory and complex network theory to construct and assess the resilience of BHN. Our key findings showed: (1)93 bird habitat sources were identified, predominantly situated in the continuous green spaces of southern and southeastern Shanghai, whereas habitat sources in the city center and other densely built-up areas are more dispersed, highlighting them as prime targets for future ecological restoration efforts. (2) The distribution of bird habitat corridors exhibits significant spatial heterogeneity, with primary corridors predominantly spanning the southwestern and eastern parts of the study area, while secondary corridors are more abundant in the western and northern parts, forming a denser network, whereas the central area shows fewer and more isolated corridors. (3) The decline in structural and functional resilience was notably more rapid under targeted attacks than under random attacks, underscoring the need to prioritize crucial bird habitat sources on the city's periphery, especially near highly urbanized areas, in urban planning and biodiversity conservation efforts to sustain ecological balance and biodiversity. These insights provide a crucial scientific basis for urban planners, emphasizing the integration of biodiversity conservation into urban development strategies by optimizing ecological sources and corridors to balance development with ecological preservation.

Globally suitable areas for Lycorma delicatula based on an optimized Maxent model.

Lycorma delicatula, a globally invasive pest, has caused considerable economic losses in many countries. Determining the potential distribution range of L. delicatula is crucial for its effective management and control; however, our understanding of this species remains limited. In this study, Maxent model with occurrence records and environmental variables were fit first and then optimized by selecting the best combination of feature classes and regularization multipliers using the lowest score of corrected Akaike information criterion. Subsequently, we predicted global suitable areas for L. delicatula both currently and in the future (2041-2060, 2061-2080, and 2081-2100). The results indicated that the mean temperature of the driest quarter is the most important environmental variable limiting L. delicatula distribution. Currently, the suitable areas are concentrated in East Asia (mainly in China, South Korea, and Japan), central and eastern United States, and southern Europe. Compared with current environmental conditions, in all future climate scenarios, the number of suitable areas for L. delicatula increased. In addition, we revealed that suitable areas are likely to expand northward in the future. Our study results suggest that policymakers and governments should prioritize the development of pest management measures in suitable areas for L. delicatula, especially in high suitable areas, to control this invasive pest and minimize global economic losses.

Environmental DNA reveals the spatiotemporal distribution and migration characteristics of the Yangtze finless porpoise, the sole aquatic mammal in the Yangtze River.

The Yangtze Finless Porpoise (YFP) is one of the 13 global flagship species identified by the World Wildlife Fund and is classified as "Critically Endangered." It is also the only extant aquatic mammal in the Yangtze River. In this study, 44 sampling points were deployed across the middle and lower reaches of the Yangtze River, with vertical sampling sections established in four key areas. Using environmental DNA (eDNA) and species distribution model(SDM), we explored the spatiotemporal distribution of YFPs and predicted their potential suitable habitats. The results indicate that the YFP has a relatively wide distribution during the flood season but exhibits clustering behavior during the dry season, showing a patchy distribution and a migratory trend from the midstream to downstream of the main channel. Predictions using the MAXENT model reveal varying trends in suitable habitat under different scenarios. Overall, YFP's potential habitat is expected to expand by 2050, but due to rising temperatures, it will contract by 2070. Elevation (dem, 65.4%), human footprint index (hfp, 8.8%), and isothermality (bio3, 8%) are key factors influencing habitat suitability. These findings demonstrate that eDNA is an effective tool for monitoring large aquatic organisms and provide scientific evidence for the conservation of the YFP.

Potential adaptive habitats for the narrowly distributed and rare bamboo species Chimonobambusa tumidissinoda J. R. Xue & T. P. Yi ex Ohrnb. under future climate change in China.

The global climate change has resulted in substantial modifications to the distribution patterns of narrowly distributed species across different time periods, leading to an imminent threat to the survival of some vulnerable species. Chimonobambusa tumidissinoda J. R. Xue & T. P. Yi ex Ohrnb., a bamboo species endemic to the transition zone from the Yunnan-Guizhou Plateau to the Sichuan Basin with high economic and ecological value, exhibits a limited range and rarity. Utilizing eight environmental variables and 56 occurrence records, we employed the MaxEnt model to predict the potential distribution range of C. tumidissinoda under current and future climate scenarios. The findings revealed that precipitation of the driest month (Bio14), elevation and isothermality (Bio3) were the crucial factors determining the species' distribution, accounting for 31.24%, 28.27% and 17.24% of data variability, respectively. The distribution centroid of C. tumidissinoda is anticipated to shift towards higher latitudes in response to future climate change, and the projected habitat suitability is expected to expand under ssp245 and ssp585 scenarios while remaining unchanged or contracting under the ssp126 scenario. Despite these expansions, the suitable habitats remain limited, with the largest being approximately 2.08 × 104 km2, indicating a significant threat to its survival. Our study provides insights into the adaptive responses of C. tumidissinoda to climate change, enriching scientific knowledge for developing effective conservation measurements as well as sustainable utilization.

Predicting the Impact of Climate Change on the Selection of Reintroduction Sites for the South China Tiger (Panthera tigris amoyensis) in China.

The South China tiger (Panthera tigris amoyensis) is a tiger subspecies unique to China and one of the top ten endangered species in the world. It used to play an important role in the overall function of the ecosystem. This study rationally screened out key prey species of the South China tiger-the Chinese serow, Chinese goral, tufted deer, water deer, Chinese muntjac, red muntjac, sambar deer, and wild boar. Candidate sites for the rewilding and reintroduction of the South China tiger were derived by exploring changes in suitable habitats for the prey using the MaxEnt model. The results show that: (1) by 2070, except for the high-suitability areas of water deer and Chinese muntjac, the areas of suitable habitats for the other six prey species would all have decreased significantly; (2) the location of the high-suitability area of the South China tiger obtained by superimposing the suitable areas of the eight prey species would be almost stable in 2050 and 2070, but the habitat index of some high- and medium-suitability areas would decrease and turn into low-suitability areas; (3) the core candidate sites were 83,415 km2 in total, of which 25,630 km2 overlapped with existing protected areas, accounting for 30.7% of the core candidate sites, and the remaining 69.3% of the core candidate sites were mostly distributed around the protected areas; (4) the maximum core candidate site area was projected to be 10,000 km2 by 2070, which could support a small population of 23 male tigers and 66 female tigers to survive and reproduce in the wild. This study revealed the core candidate sites for the rewilding of South China tigers and estimated the number of tigers that could be reintroduced to these areas, providing a preliminary research basis for promoting the rewilding of South China tigers in China.

Evaluating the impact of ecological factors on the quality and habitat distribution of Lonicera japonica Flos using HPLC and the MaxEnt model.

Introduction: The quality of traditional Chinese medicine is based on the content of their secondary metabolites, which vary with habitat adaptation and ecological factors. This study focuses on Lonicera japonica Flos (LJF), a key traditional herbal medicine, and aims to evaluate how ecological factors impact its quality. Methods: We developed a new evaluation method combining high-performance liquid chromatography (HPLC) fingerprinting technology and MaxEnt models to assess the effects of ecological factors on LJF quality. The MaxEnt model was used to predict suitable habitats for current and future scenarios, while HPLC was employed to analyze the contents of key compounds. We also used ArcGIS for spatial analysis to create a quality zoning map. Results: The analysis identified 21 common chromatographic peaks, with significant variations in the contents of Hyperoside, Rutin, Chlorogenic acid, Cynaroside, and Isochlorogenic acid A across different habitats. Key environmental variables influencing LJF distribution were identified, including temperature, precipitation, and elevation. The current suitable habitats primarily include regions south of the Yangtze River. Under future climate scenarios, suitable areas are expected to shift, with notable expansions in southern Gansu, southeastern Tibet, and southern Liaoning. The spatial distribution maps revealed that high-quality LJF is predominantly found in central and southern Hebei, northern Henan, central Shandong, central Sichuan, southern Guangdong, and Taiwan. Discussion: The study indicates that suitable growth areas can promote the accumulation of certain secondary metabolites in plants, as the accumulation of these metabolites varies. The results underscore the necessity of optimizing quality based on cultivation practices. The integration of HPLC fingerprinting technology and the MaxEnt model provides valuable insights for the conservation and cultivation of herbal resources, offering a new perspective on evaluating the impact of ecological factors on the quality of traditional Chinese medicines.

Effects of environment and human activities on rice planting suitability based on MaxEnt model.

Rice is one of the major food crops, and the study of suitable planting areas for rice plays an important role in improving rice yield and optimizing the production layout. This study used Maximum Entropy (MaxEnt) model to simulate and predict the distribution of suitable rice planting areas in China from 1981 to 2020 by combining the climate, soil, and human activities, analyzed the spatial and temporal changes of suitable rice planting areas in China, and determined the main factors affecting rice planting suitability. The results indicated that the main factors influencing the distribution of suitable planting areas for rice in China were gross domestic product (GDP), population density (Pop), and annual sunshine duration (Sun), with human activities playing a dominant role. The high suitable planting areas of rice were mainly distributed in Hubei, Hunan, Jiangxi, Anhui, Guangdong, southeastern Sichuan and western Guizhou. The total suitable planting areas for rice were 346.00 × 104 km2, 345.66 × 104 km2, 347.01 × 104 km2, and 355.57 × 104 km2 from 1981 to 1990, 1991 to 2000, 2001 to 2010 and 2011 to 2020, respectively. With the passage of time, the area of unsuitable areas for rice gradually decreased, and the area of medium suitable areas increased, with large changes in the area of high- and low-suitable areas. Moreover, due to the transfer of a large number of rural laborers to the cities in recent years, the tension between people and land caused by the population explosion has led to the increasing impact of Pop on rice suitable areas and the relatively weakening of the impact of GDP on rice production interventions. The results can be used to provide scientific evidence for the management of rice cultivation and food production safety, with a view to reducing the impacts of climate change on agricultural production in the context of global climate change.

Predicting the spatial distribution of three Ephedra species under climate change using the MaxEnt model.

In the context of global warming, the habitats of Ephedra, including Ephedra sinica Stapf, Ephedra intermedia Schrenk ex Mey, and Ephedra equisetina Bunge, have been substantially threatened and deteriorated in recent years. Little is known about the potential geographic dynamics of economically renowned species, including those used in sand fixation and traditional Chinese medicine, under climate change. Therefore, evaluating their potential habitat and determining the crucial environmental variables affecting E. sinica, E. intermedia and E. equisetina under the driving force of global warming are extremely important. In this study, an optimized MaxEnt model in the kuenm package on the basis of occurrence records (a total of 103, 101 and 97 points for E. sinica, E. intermedia and E. equisetina, respectively) and 37 environmental factors were utilized to simulate the distribution of the three species. Two representative concentration pathways (SSP2.6 and SSP8.5) at 2041-2060 and 2061-2080, respectively, were used to establish a future distribution model of the three species. The results indicated that approximately 6.92 × 105 km2, 2.95 × 105 km2, and 11.5 × 105 km2 of suitable regions for E. sinica, E. intermedia and E. equisetina were obtained, which were mostly distributed in central and eastern Inner Mongolia, eastern and southern Gansu, and northern Xinjiang, respectively. Critical environmental variables, such as land cover and annual precipitation, were regarded as critical parameters for the three species. Future assessment revealed that over 60 % of the potential distribution area was affected, and the stability of E. sinica under the SSP8.5 scenario was the greatest. The spatial dynamic changes in suitable areas for E. intermedia were smaller than those for E. equisetina and E. sinica in the future. The comprehensive analysis revealed that the fluctuations in the distributions of the three Ephedra species under climate change are small and provide useful information for future conservation. Therefore, target conservation and management measures should be implemented in combination with the suitability thresholds of different environmental parameters. Our results provide useful recommendations for the current and future protection of Ephedra populations.

The potential habitat of Angelica dahurica in China under climate change scenario predicted by Maxent model.

Since the 20th century, global climate has been recognized as the most important environmental factor affecting the distribution of plants. Angelica dahurica (A. dahurica) has been in great demand as a medicinal herb and flavoring, but the lack of seed sources has hindered its development. In this study, we utilized the Maxent model combined with Geographic Information System (GIS) to predict the potential habitat of A. dahurica in China based on its geographical distribution and 22 environmental factors. This prediction will serve as a valuable reference for the utilization and conservation of A. dahurica resources.The results indicated that: (1) the Maxent model exhibited high accuracy in predicting the potential habitat area of A. dahurica, with a mean value of the area under the ROC curve (AUC) at 0.879 and a TSS value above 0.6; (2) The five environmental variables with significant effects were bio6 (Min temperature of the coldest month), bio12 (Annual Precipitation), bio17 (Precipitation of Driest Quarter), elevation, and slope, contributing to a cumulative total of 89.6%. Suitable habitats for A. dahurica were identified in provinces such as Yunnan, Guizhou, Guangxi, Sichuan, Hunan, and others. The total area of suitable habitat was projected to increase, with expansion primarily in middle and high latitudes, while areas of decrease were concentrated in lower latitudes. Under future climate change scenarios, the centers of mass of suitable areas for A. dahurica were predicted to shift towards higher latitudes in the 2050s and 2090s, particularly towards the North China Plain and Northeast Plain. Overall, it holds great significance to utilize the Maxent model to predict the development and utilization of A. dahurica germplasm resources in the context of climate change.

Predicting the Current and Future Distribution of Monolepta signata (Coleoptera: Chrysomelidae) Based on the Maximum Entropy Model.

Monolepta signata is a polyphagous and highly destructive agricultural pest, currently only distributed in Asia. In its place of origin, it poses a serious threat to important economic crops, for instance, maize (Zea mays L.) and cotton (Gossypium hirsutum L.). Based on morphological and molecular data research, it has been found that M. quadriguttata (Motschulsky), M. hieroglyphica (Motschulsky), and M. signata are actually the same species. This discovery means that the range of this pest will expand, and it also increases the risk of it spreading to non-native areas worldwide. It is crucial for global agricultural production to understand which countries and regions are susceptible to invasion by M. signata and to formulate corresponding prevention, control, and monitoring strategies. This study uses the maximum entropy model, combined with bioclimatic variables and elevation, to predict the potentially suitable areas and diffusion patterns of M. signata worldwide. The results indicate that in its suitable area, M. signata is mainly affected by three key climatic factors: Precipitation of Wettest Month (bio13), Mean Temperature of Warmest Quarter (bio10), and Temperature Seasonality (bio4). Under the current status, the total suitable region of M. signata is 252,276.71 × 104 km2. In addition to its native Asia, this pest has potentially suitable areas in Oceania, South America, North America, and Africa. In the future, with climate change, the suitable area of M. signata will expand to high-latitude areas and inland areas. This study found that by the 2070s, under the SSP5-8.5 climate scenario, the change in the potentially suitable area of this insect is the largest. By identifying the potentially suitable areas and key climatic factors of M. signata, we can provide theoretical and technical support to the government, enabling them to more effectively formulate strategies to deal with the spread, outbreak, and invasion of M. signata.

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.

Exploring the distribution and habitat preferences of Polytrichaceae (Bryophyta) in Tibet, China.

The Qinghai-Tibet Plateau stands as one of the most ecologically fragile and biodiversity-rich regions globally. Understanding the distribution of different taxa and their relationship with environmental factors is crucial for effective conservation and sustainable management. Polytrichaceae, a significant bryophyte family widely distributed in Tibet, displays distinct structural, morphological, and phylogenetic traits compared to other mosses. Despite its importance, the distribution of Polytrichaceae in Tibet and its correlation with environmental factors have yet to be explored. In this study, we used an optimized Maximum Entropy (MaxEnt) model to explore the potential suitable habitats of Polytrichaceae in Tibet, aiming to clarify their geographic distribution pattern as well as the key environmental influence factors. The model had high accuracy with an average Area Under the Curve (AUC) of 0.933 and True Skill Statistics (TSS) value of 0.789. The results showed that the potential suitability habitats of Polytrichaceae were mainly located in southeastern Tibet, and the low suitable, moderately suitable, and highly suitable habitats accounted for 12.53 %, 6.84 %, and 3.31 % of the total area of Tibet respectively. Unsuitable habitats were mainly located in northwestern Tibet, accounting for about 77.32 %. In Tibet, temperature factors (Mean Temperature of Coldest Quarter (Bio11) and Annual Mean Temperature (Bio1)) played a pivotal role in determining the potential suitable habitats for Polytrichaceae, and elevation, precipitation, and vegetation coverage also had an important influence. The family preferred warm, moist and densely vegetated habitats in Tibet. This study enriched our ecological understanding of bryophyte ecology in this region and provided data-driven support for biodiversity conservation and ecosystem management in Tibet.

The Potential Habitat Response of Cyclobalanopsis gilva to Climate Change.

Cyclobalanopsis gilva, a valuable timber species in China, holds significant importance for understanding the constraints imposed by climate change on the dynamic geographic distribution of tree species. This study utilized the MaxEnt maximum entropy model to reconstruct the migratory dynamics of C. gilva geographical distribution since the Last Glacial Maximum. The objective was to comprehend the restrictive mechanisms of environmental factors on its potential geographical distribution, aiming to provide insights for mid-to-long-term afforestation planning of C. gilva. The optimized MaxEnt model exhibited a significantly high predictive accuracy, with an average AUC value of 0.949 ± 0.004 for the modern suitable habitat model of C. gilva. The total suitable habitat area for C. gilva in contemporary times was 143.05 × 104 km2, with a highly suitable habitat area of 3.14 × 104 km2. The contemporary suitable habitat was primarily located in the southeastern regions of China, while the highly suitable habitat was concentrated in eastern Fujian and central-eastern Taiwan. Bioclimatic variables such as mean diurnal range (Bio2), min temperature of coldest month (Bio6), precipitation of driest quarter (Bio17), and precipitation of driest month (Bio14) predominantly influenced the modern geographic distribution pattern of C. gilva, with temperature factors playing a leading role. With global climate warming, there is a risk of fragmentation or even loss of suitable habitat for C. gilva by 2050 and 2090. Therefore, the findings of this study can significantly contribute to initiating a habitat conservation campaign for this species.