Assessing the suitable regions and the key factors for three Cd-accumulating plants (Sedum alfredii, Phytolacca americana, and Hylotelephium spectabile) in China using MaxEnt model

Predicting the Global Distribution of Nitraria L. Under Climate Change Based on Optimized MaxEnt Modeling

The genus of Nitraria L. are Tertiary-relict desert sand-fixing plants, which are an important forage and agricultural product, as well as an important source of medicinal and woody vegetable oil. In order to provide a theoretical basis for better protection and utilization of species in the Nitraria L., this study collected global distribution information within the Nitraria L., along with data on 29 environmental and climatic factors. The Maximum Entropy (MaxEnt) model was used to simulate the globally suitable distribution areas for Nitraria L. The results showed that the mean AUC value was 0.897, the TSS average value was 0.913, and the model prediction results were excellent. UV-B seasonality (UVB-2), UV-B of the lowest month (UVB-4), precipitation of the warmest quarter (bio18), the DEM (Digital Elevation Model), and annual precipitation (bio12) were the key variables affecting the distribution area of Nitraria L, with contributions of 54.4%, 11.1%, 8.3%, 7.4%, and 4.1%, respectively. The Nitraria L. plants are currently found mainly in Central Asia, North Africa, the neighboring Middle East, and parts of southern Australia and Siberia. In future scenarios, except for a small expansion of the 2030s scenario model Nitraria L., the potential suitable distribution areas showed a decreasing trend. The contraction area is mainly concentrated in South Asia, such as Afghanistan and Pakistan, North Africa, Libya, as well as in areas of low suitability in northern Australia, where there was also significant shrinkage. The areas of expansion are mainly concentrated in the Qinghai-Tibet Plateau to the Iranian plateau, and the Sahara Desert is also partly expanded. With rising Greenhouse gas concentrations, habitat fragmentation is becoming more severe. Center-of-mass migration results also suggest that the potential suitable area of Nitraria L. will shift northwestward in the future. This study can provide a theoretical basis for determining the scope of Nitraria L. habitat protection, population restoration, resource management and industrial development in local areas.

Identifying the habitat suitability of Pteris vittata in China and associated key drivers using machine learning models

Pteris vittata (P. vittata) possesses significant potential in remediating arsenic (As) soil pollution. Understanding the habitat suitability of P. vittata in China and pinpointing the key drivers that influence its distribution can facilitate the identification of optimal areas for using P. vittata as a remediation tool for As-polluted soils. In this study, a comparative analysis was conducted using ten machine learning models to assess the habitat suitability of P. vittata based on 744 specimen records and 20 environmental factors. The key drivers affecting the distribution of P. vittata were also investigated based on the optimal model. The results indicate that the XGBOOST model was the most reliable and stable, achieving a coefficient of determination of 0.95. Approximately 24.47 % of China's land area was identified as suitable for P. vittata. Particularly, it was predominantly found in Hainan (45.9 %), Guangxi (92.96 %), Guangdong (91.68 %), Hunan (91.26 %), Guizhou (90.83 %), Chongqing (88.17 %), Fujian (85.70 %), Yunnan (77.44 %), Jiangxi (73.99 %) and Zhejiang (57.05 %). Furthermore, this study pinpointed the lowest temperature, annual temperature range, and mining density as key drivers, contributing 45.9 %, 31.9 %, and 7.2 %, respectively. Spatial correlation analysis revealed a significant correlation between mining density and the habitat distribution of P. vittata (Moran' I = 0.519). This study confirmed that both natural factors and anthropogenic activities affect the distribution of P. vittata and provided valuable insights for optimizing the application of P. vittata in soil phytoremediation and reclamation.

Impact of Climate Change on Distribution of Endemic Plant Section Tuberculata (Camellia L.) in China: MaxEnt Model-Based Projection

Sect. Tuberculata, as one of the endemic plant groups in China, belongs to the genus Camellia of the Theaceae family and possesses significant economic and ecological value. Nevertheless, the characteristics of habitat distribution and the major eco-environmental variables affecting its suitability are poorly understood. In this study, using 65 occurrence records, along with 60 environmental factors, historical, present and future suitable habitats were estimated using MaxEnt modeling, and the important environmental variables affecting the geographical distribution of sect. Tuberculata were analyzed. The results indicate that the size of the its potential habitat area in the current climate was 1.05 × 105 km2, and the highly suitable habitats were located in Guizhou, central-southern Sichuan, the Wuling Mountains in Chongqing, the Panjiang Basin, and southwestern Hunan. The highest probability of presence for it occurs at mean diurnal range (bio2) ≤ 7.83 °C, basic saturation (s_bs) ≤ 53.36%, temperature annual range (bio7) ≤ 27.49 °C, -7.75 °C < mean temperature of driest quarter (bio9) < 7.75 °C, annual UV-B seasonality (uvb2) ≤ 1.31 × 105 W/m2, and mean UV-B of highest month (uvb3) ≤ 5089.61 W/m2. In particular, bio2 is its most important environmental factor. During the historical period, the potential habitat area for sect. Tuberculata was severely fragmented; in contrast, the current period has a more concentrated habitat area. In the three future periods, the potential habitat area will change by varying degrees, depending on the aggressiveness of emissions reductions, and the increase in the potential habitat area was the largest in the SSP2.6 (Low-concentration greenhouse gas emissions) scenario. Although the SSP8.5 (High-concentration greenhouse gas emissions) scenario indicated an expansion in its habitat in the short term, its growth and development would be adversely affected in the long term. In the centroid analysis, the centroid of its potential habitat will shift from lower to higher latitudes in the northwest direction. The findings of our study will aid efforts to uncover its originsand geographic differentiation, conservation of unique germplasms, and forestry development and utilization.

The spatiotemporal patterns of the beet webworm (Lepidoptera: Crambidae) in China and possible dynamics under future climate scenarios

The beet webworm (BWW), Loxostege sticticalis (L.), is a notorious migratory agriculture pest of crops and fodder plants, inducing sudden outbreaks and huge losses of food and forage production. Quantifying its spatiotemporal patterns and possible dynamics under future climate scenarios may have significant implications for management policies and practices against this destructive agriculture pest. In this paper, a database containing nearly 7,000 occurrence records for the spatiotemporal distribution of BWW in China was established and its possible dynamics under future climate scenarios predicted using Maxent. We found that BWW could affect a vast geographic range of Northern China, about one third of the country's land area. The beet webworm overwintered in most of its distribution regions. Maxent model found a northward movement and distribution reduction for BWW in China under future climate scenarios. The occurrence and overwintering regions will move northward about 0.3°N-0.9°N under warming climate scenarios, and about 40%-70% of the suitable habitat and overwintering habitat will disappear by 2100. Most of the northward movement and suitable area reduction likely will happen in 2 decades. Given the vast affected area, the abrupt outbreaks, the diverse host plants, the sensitivity to climate change, as well as their long-distance migration capacity, global scale research, and monitoring the population dynamics of BWW are essential for developing effective management strategies and mitigating its impact on agriculture and ecosystems.

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.

Impact of climate change on the future distribution of three Ferulago species in Iran using the MaxEnt model

The decline of habitats supporting medicinal plants is a consequence of climate change and human activities. In the Middle East, Ferulago angulata, Ferulago carduchorum, and Ferulago phialocarpa are widely recognized for their culinary, medicinal, and economic value. Therefore, this study models these Ferulago species in Iran using the MaxEnt model under two representative concentration pathways (RCP4.5 and RCP8.5) for 2050 and 2070. The objective was to identify the most important bioclimatic (n = 6), edaphic (n = 4), and topographic (n = 3) variables influencing their distribution and predict changes under various climate scenarios. Findings reveal slope percentage as the most significant variable for F. angulata and F. carduchorum, while solar radiation was the primary variable for F. phialocarpa. MaxEnt modeling demonstrated good to excellent performance, as indicated by all the area under the curve values exceeding 0.85. Projections suggest negative area changes for F. angulata and F. carduchorum (i.e., predictions under RCP4.5 for 2050 and 2070 indicate -34.0% and -37.8% for F. phialocarpa, and -0.3% and -6.2% for F. carduchorum; additionally, predictions under RCP 8.5 for 2050 and 2070 show -39.0% and -52.2% for F. phialocarpa, and -1.33% and -9.8% for F. carduchorum), while for F. phialocarpa, a potential habitat increase (i.e., predictions under RCP4.5 for 2050 and 2070 are 23.4% and 11.2%, and under RCP 8.5 for 2050 and 2070 are 64.4% and 42.1%) is anticipated. These insights guide adaptive management strategies, emphasizing conservation and sustainable use amid global climate change. Special attention should be paid to F. angulata and F. carduchorum due to anticipated habitat loss. Integr Environ Assess Manag 2024;20:1046-1059. © 2024 SETAC.

The Influence of Climate Change on the Distribution of Hibiscus mutabilis in China: MaxEnt Model-Based Prediction

Our study utilized 374 geographical distribution records of H. mutabilis and 19 bioclimatic factors, employing the MaxEnt model and the Geographic Information System (ArcGIS). The key environmental variables influencing the suitable distribution areas of H. mutabilis were analyzed through the comprehensive contribution rate, permutation importance, and Pearson correlation coefficient. Based on this analysis, the contemporary and future suitable distribution areas and their extents were predicted. The results indicate that the key limiting factor affecting the suitable distribution areas of H. mutabilis is the precipitation of the driest month (bio14), with secondary factors being annual precipitation (bio12), annual mean temperature (bio1), and annual temperature range (bio7). Under contemporary climate conditions, the total suitable area for H. mutabilis is approximately 2,076,600 km2, primarily concentrated in the tropical and subtropical regions of southeastern China. Under low-to-medium-emission scenarios (SSP1-2.6, SSP2-4.5), the total suitable area of H. mutabilis shows a trend of first decreasing and then increasing compared to the current scenario. In contrast, under high-emission scenarios (SSP5-8.5), it exhibits a trend of first increasing and then decreasing. The spatial pattern changes indicate that the retention rate of suitable areas for H. mutabilis ranges from 95.28% to 99.28%, with the distribution centers primarily located in Hunan and Guizhou provinces, showing an overall migration trend towards the west and north. These findings suggest that H. mutabilis possesses a certain level of adaptability to climate change. However, it is crucial to consider regional drought and sudden drought events in practical cultivation and introduction processes. The results of our study provide a scientific basis for the rational cultivation management, conservation, and utilization of germplasm resources of H. mutabilis.

Novel insights into hotspots of insect vectors of GLRaV-3: Dynamics and global distribution

Grapevine leafroll-associated virus 3 (GLRaV-3) is the most prevalent and economically damaging virus in grapevines and is found on nearly all continents, except Antarctica. Ten mealybugs act as vector insects transmitting the GLRaV-3. Understanding the potential distribution range of vector insects under climate change is crucial for preventing and managing vector insects and controlling and delaying the spread of GLRaV-3. This study investigated the potential geographical range of insect vectors of GLRaV-3 worldwide using MaxEnt (maximum entropy) based on occurrence data under environmental variables. The potential distributions of these insects were projected for the 2030s, 2050s, 2070s, and 2090s under the three climate change scenarios. The results showed that the potential distribution range of most vector insects is concentrated in Southeastern North America, Europe, Asia, and Southeast Australia. Most vector insects contract their potential distribution ranges under climate-change conditions. The stacked model suggested that potential distribution hotspots of vector insects were present in Southeastern North America, Europe, Southeast Asia, and Southeast Australia. The potential distribution range of hotspots would shrink with climate change. These results provide important information for governmental decision-makers and farmers in developing control and management strategies against vector insects of GLRaV-3. They can also serve as references for studies on other insect vectors.

Potentially suitable habitats of Daodi goji berry in China under climate change

Introduction

Goji berry (Lycium barbarum L.) is a famous edible and medicinal herb worldwide with considerable consumption. The recent cultivation of goji berries in the Daodi region was seriously reduced due to increased production costs and the influence of policy on preventing nongrain use of arable land in China. Consequently, production of Daodi goji berry was insufficient to meet market demands for high-quality medicinal materials. Searching for regions similar to the Daodi region was necessary.

Methods

The MaxEnt model was used to predicted the current and future potential regions suitable for goji berry in China based on the environmental characteristics of the Daodi region (including Zhongning County of Zhongwei prefecture-level city, and its surroundings), and the ArcGIS software was used to analyze the changes in its suitable region.

Results

The results showed that when the parameters were FC = LQHP and RM = 2.1, the MaxEnt model was optimal, and the AUC and TSS values were greater than 0.90. The mean temperature and precipitation of the coldest quarter were the most critical variables shaping the distribution of Daodi goji berries. Under current climate conditions, the suitable habitats of the Daodi goji berry were 45,973.88 km2, accounting for 0.48% of China's land area, which were concentrated in the central and western Ningxia Province (22,589.42 km2), and the central region of Gansu Province (18,787.07 km2) bordering western Ningxia. Under future climate scenarios, the suitable area was higher than that under current climate conditions and reached the maximum under RCP 6.0 (91,256.42 km2) in the 2050s and RCP 8.5 (82,459.17 km2) in the 2070s. The expansion regions were mainly distributed in the northeast of the current suitable ranges, and the distributional centroids were mainly shifted to the northeast. The moderately and highly suitable overlapping habitats were mainly distributed in Baiyin (7,241.75 km2), Zhongwei (6,757.81 km2), and Wuzhong (5, 236.87 km2) prefecture-level cities.

Discussion

In this stduy, MaxEnt and ArcGIS were applied to predict and analyze the suitable habitats of Daodi goji berry in China under climate change. Our results indicate that climate warming is conducive to cultivating Daodi goji berry and will not cause a shift in the Daodi region. The goji berry produced in Baiyin could be used to satisfy the demand for high-quality medicinal materials. This study addresses the insufficient supply and guides the cultivation of Daodi goji berry.

Rhizospheric Lactobacillus spp. contribute to the high Cd-accumulating characteristics of Phytolacca spp. in acidic Cd-contaminated soil

Screening high Cd-accumulating plants and understanding the interactions between plants, rhizospheric microbes and Cd are important in developing microbe-assisted phytoremediation techniques for Cd-contaminated soils. In this study, the Cd tolerance and accumulation characteristics of Phytolacca americana L., P. icosandra L. and P. polyandra Batalin growing in acidic Cd-contaminated soil were compared to evaluate their phytoremediation potential. According to Cd concentrations (root: 8.26-37.09 mg kg-1, shoot: 2.80-9.26 mg kg-1), bioconcentration factors (BCFs) and translocation factors (TFs), the three Phytolacca species exhibited high Cd-accumulation capacities, ranked in the following order: P. icosandra (root BCF: 1.25, shoot BCF: 0.31, TF: 0.25) > P. polyandra (root BCF: 0.68, shoot BCF: 0.26, TF: 0.44) > P. americana (root BCF: 0.28, shoot BCF: 0.09, TF: 0.38). Phytolacca icosandra and P. polyandra can thus be considered as two new Cd accumulators for phytoremediation. Soil pH, available Cd (ACd) concentration and certain bacterial taxa (e.g. Lactobacillus, Helicobacter, Alistipes, Desulfovibrio and Mucispirillum) were differentially altered in the rhizospheres of the three Phytolacca species in comparison to unplanted soil. Correlation analysis showed that there were significant interactions between rhizospheric ACd concentration, pH and Lactobacillus bacteria (L. murinus, L. gasseri and L. reuteri), which affected Cd uptake by Phytolacca plants. The mono- and co-inoculation of L. murinus strain D51883, L. gasseri strain D51533 and L. reuteri strain D24591 in the rhizosphere of P. icosandra altered the rhizospheric pH and ACd concentrations, in addition to increasing the shoot Cd contents by 31.9%-44.6%. These results suggest that recruitment of rhizospheric Lactobacillus spp. by Phytolacca plants contributes to their high Cd-accumulating characteristics. This study provides novel insights into understanding the interactions between plants, rhizobacteria and heavy metals.

Analysis of the distribution pattern of the ectomycorrhizal fungus Cenococcum geophilum under climate change using the optimized MaxEnt model

Cenococcum geophilum (C. geophilum) is a widely distributed ectomycorrhizal fungus that plays a crucial role in forest ecosystems worldwide. However, the specific ecological factors influencing its global distribution and how climate change will affect its range are still relatively unknown. In this study, we used the MaxEnt model optimized with the kuenm package to simulate changes in the distribution pattern of C. geophilum from the Last Glacial Maximum to the future based on 164 global distribution records and 17 environmental variables and investigated the key environmental factors influencing its distribution. We employed the optimal parameter combination of RM = 4 and FC = QPH, resulting in a highly accurate predictive model. Our study clearly shows that the mean temperature of the coldest quarter and annual precipitation are the key environmental factors influencing the suitable habitats of C. geophilum. Currently, appropriate habitats of C. geophilum are mainly distributed in eastern Asia, west-central Europe, the western seaboard and eastern regions of North America, and southeastern Australia, covering a total area of approximately 36,578,300 km2 globally. During the Last Glacial Maximum and the mid-Holocene, C. geophilum had a much smaller distribution area, being mainly concentrated in the Qinling-Huaihe Line region of China and eastern Peninsular Malaysia. As global warming continues, the future suitable habitat for C. geophilum is projected to shift northward, leading to an expected expansion of the suitable area from 9.21% to 21.02%. This study provides a theoretical foundation for global conservation efforts and biogeographic understanding of C. geophilum, offering new insights into its distribution patterns and evolutionary trends.

Differences in the Suitable Distribution Area between Northern and Southern China Landscape Plants

Climate change, a global biodiversity threat, largely influences the geographical distribution patterns of species. China is abundant in woody landscape plants. However, studies on the differences in the adaptive changes of plants under climate change between northern and southern China are unavailable. Therefore, herein, the MaxEnt model was used to predict changes in the suitable distribution area (SDA) and dominant environmental variables of 29 tree species under two climate change scenarios, the shared socioeconomic pathways (SSPs) 126 and 585, based on 29 woody plant species and 20 environmental variables in northern and southern China to assess the differences in the adaptive changes of plants between the two under climate change. Temperature factors dominated the SDA distribution of both northern and southern plants. Southern plants are often dominated by one climatic factor, whereas northern plants are influenced by a combination of climatic factors. Northern plants are under greater pressure from SDA change than southern plants, and their SDA shrinkage tendency is significantly higher. However, no significant difference was observed between northern and southern plants in SDA expansion, mean SDA elevation, and latitudinal change in the SDA mass center. Future climate change will drive northern and southern plants to migrate to higher latitudes rather than to higher elevations. Therefore, future climate change has varying effects on plant SDAs within China. The climate change intensity will drive northern landscape plants to experience greater SDA-change-related pressure than southern landscape plants. Therefore, northern landscape plants must be heavily monitored and protected.

Prediction of Suitable Habitat Distribution of Cryptosphaeria pullmanensis in the World and China under Climate Change

Years of outbreaks of woody canker (Cryptosphaeria pullmanensis) in the United States, Iran, and China have resulted in massive economic losses to biological forests and fruit trees. However, only limited information is available on their distribution, and their habitat requirements have not been well evaluated due to a lack of research. In recent years, scientists have utilized the MaxEnt model to estimate the effect of global temperature and specific environmental conditions on species distribution. Using occurrence and high resolution ecological data, we predicted the spatiotemporal distribution of C. pullmanensis under twelve climate change scenarios by applying the MaxEnt model. We identified climatic factors, geography, soil, and land cover that shape their distribution range and determined shifts in their habitat range. Then, we measured the suitable habitat area, the ratio of change in the area of suitable habitat, the expansion and shrinkage of maps under climate change, the direction and distance of range changes from the present to the end of the twenty-first century, and the effect of environmental variables. C. pullmanensis is mostly widespread in high-suitability regions in northwestern China, the majority of Iran, Afghanistan, and Turkey, northern Chile, southwestern Argentina, and the west coast of California in the United States. Under future climatic conditions, climate changes of varied intensities favored the expansion of suitable habitats for C. pullmanensis in China. However, appropriate land areas are diminishing globally. The trend in migration is toward latitudes and elevations that are higher. The estimated area of possible suitability shifted eastward in China. The results of the present study are valuable not only for countries such as Morocco, Spain, Chile, Turkey, Kazakhstan, etc., where the infection has not yet fully spread or been established, but also for nations where the species has been discovered. Authorities should take steps to reduce greenhouse gas emissions in order to restrict the spread of C. pullmanensis. Countries with highly appropriate locations should increase their surveillance, risk assessment, and response capabilities.

Sulfur fertilization and water management ensure phytoremediation coupled with argo-production by mediating rhizosphere microbiota in the Oryza sativa L.-Sedum alfredii Hance rotation system

Sulfur (S) fertilizers, water management and crop rotation are important agronomic practices, related to soil heavy metal bioavailability. However, the mechanisms of microbial interactions remain unclear. Herein, we investigated how S fertilizers (S⁰ and Na₂SO₄) and water management affected plant growth, soil cadmium (Cd) bioavailability, and rhizospheric bacterial communities in the Oryza sativa L. (rice)-Sedum alfredii Hance (S. alfredii) rotation system through 16S rRNA gene sequencing and ICP-MS analysis. During rice cultivation, continuous flooding (CF) was better than alternating wetting and drying (AWD). CF treatment decreased soil Cd bioavailability by the promotion of insoluble metal sulfide production and soil pH, thus lowering Cd accumulation in grains. S application recruited more S-reducing bacteria in the rhizosphere of rice, whilst Pseudomonas promoted metal sulfide production and rice growth. During S. alfredii cultivation, S fertilizer recruited S-oxidizing and metal-activating bacteria in the rhizosphere. Thiobacillus may oxidize metal sulfides and enhance Cd and S absorption into S. alfredii. Notably, S oxidation decreased soil pH and elevated Cd content, thereby promoting S. alfredii growth and Cd absorption. These findings showed rhizosphere bacteria were involved in Cd uptake and accumulation in the rice-S. alfredii rotation system, thus providing useful information for phytoremediation coupled with argo-production.