Predicting the impacts of climate change, soils and vegetation types on the geographic distribution of Polyporus umbellatus in China

Identifying climate refugia for wild yaks (Bos mutus) on the Tibetan Plateau

Climate change is threatening fragile alpine ecosystems and their resident ungulates, particularly the wild yak (Bos mutus) that inhabits alpine areas between the tree line and glaciers on the Tibetan Plateau. Although wild yaks tend to shift habitats in response to changes in climatic factors, the precise impacts of climate change on their habitat distribution and climate refugia remain unclear. Based on over 1000 occurrence records, the maximum entropy (MaxEnt) algorithm was applied to simulate habitat ranges in the last glacial maximum (LGM), Mid-Holocene, current stage, and three greenhouse gas emission scenarios in 2070. Three habitat patches were identified as climate refugia for wild yaks that have persisted from the LGM to the present and are projected to persist until 2070. These stable areas account for approximately 64% of the current wild yak habitat extent and are sufficiently large to support viable populations. The long-term persistence of these climate refugia areas is primarily attributed to the unique alpine environmental features of the Tibetan Plateau, where relatively stable arid or semi-arid climates are maintained, and a wide range of forage resource supplies are available. However, habitat loss by 2070 caused by insufficient protection is predicted to lead to severe fragmentation in the southeastern and northwestern Kunlun, Hengduan, central-western Qilian, and southern Tanggula-northern Himalaya Mountains. Habitat disturbance has also been caused by increasing anthropogenic effects in the southern Tanggula and northern Himalaya Mountains. We suggest that sufficient protection, transboundary cooperation, and community involvement are required to improve wild yak conservation efforts. Our combined modeling method (MaxEnt-Zonation-Linkage Mapper-FRAGSTAT) can be utilized to identify priority areas and linkages between habitat patches while assessing the conservation efficiency of protected areas and analyzing the coupled relationship between climate change and anthropogenic impacts on the habitat distribution of endangered species.

Predicting the Impact of Climate Change on the Future Distribution of Paederus fuscipes Curtis, 1826, in China Based on the MaxEnt Model

Paederus fuscipes Curtis, 1826, belongs to the Coleoptera order, Staphylinidae family, and Paederus genus (Fabricius, 1775). It has a wide distribution and strong invasive and environmental adaptation capabilities. As a predatory natural enemy of agricultural and forestry pests, understanding its suitable habitat is crucial for the control of other pests. This study, for the first time, uses the MaxEnt model and ArcGIS software, combining known distribution information of P. fuscipes and climate environmental factors to predict the current and future suitable habitat distribution of this insect. The key environmental variables affecting the distribution of P. fuscipes have been identified as mean diurnal range (mean of monthly (max temp-min temp)) (bio2), isothermality (Bio2/Bio7) (*100) (bio3), minimum temperature of the coldest month (bio6), temperature annual range (bio5-bio6) (bio7), mean temperature of the driest quarter (bio9), mean temperature of the coldest quarter (bio11), precipitation of the wettest month (bio13), precipitation of the driest month (bio14), and precipitation seasonality (coefficient of variation) (bio15). The highly suitable areas for P. fuscipes in China are mainly distributed in the hilly regions of Shandong, the North China Plain, and the middle and lower reaches of the Yangtze River Plain, with a total suitable area of 118.96 × 104 km2, accounting for 12.35% of China's total area. According to future climate change scenarios, it is predicted that the area of highly and lowly suitable regions will significantly decrease, while moderately suitable regions will increase (except for the 2090s, SSP2-4.5 scenario). These research findings provide important theoretical support for pest control and ecological conservation applications.

The Spatial Shifts and Vulnerability Assessment of Ecological Niches under Climate Change Scenarios for Betula luminifera, a Fast-Growing Precious Tree in China

The spatial shifts and vulnerability assessments of ecological niches for trees will offer fresh perspectives for sustainable development and preservation of forests, particularly within the framework of rapid climate change. Betula luminifera is a fast-growing native timber plantation species in China, but the natural resources have been severely damaged. Here, a comprehensive habitat suitability model (including ten niche-based GIS modeling algorithms) was developed that integrates three types of environmental factors, namely, climatic, soil, and ultraviolet variables, to assess the species contemporary and future distribution of suitable habitats across China. Our results suggest that the habitats of B. luminifera generally occur in subtropical areas (about 1.52 × 106 km2). However, the growth of B. luminifera is profoundly shaped by the nuances of its local environment, the most reasonable niche spaces are only 1.15 × 106 km2 when limiting ecological factors (soil and ultraviolet) are considered, generally considered as the core production region. Furthermore, it is anticipated that species-suitable habitats will decrease by 10 and 8% with climate change in the 2050s and 2070s, respectively. Our study provided a clear understanding of species-suitable habitat distribution and identified the reasons why other niche spaces are unsuitable in the future, which can warn against artificial cultivation and conservation planning.

Possible potential spread of Anopheles stephensi, the Asian malaria vector

BACKGROUND

Anopheles stephensi is native to Southeast Asia and the Arabian Peninsula and has emerged as an effective and invasive malaria vector. Since invasion was reported in Djibouti in 2012, the global invasion range of An. stephensi has been expanding, and its high adaptability to the environment and the ongoing development of drug resistance have created new challenges for malaria control. Climate change is an important factor affecting the distribution and transfer of species, and understanding the distribution of An. stephensi is an important part of malaria control measures, including vector control.

METHODS

In this study, we collected existing distribution data for An. stephensi, and based on the SSP1-2.6 future climate data, we used the Biomod2 package in R Studio through the use of multiple different model methods such as maximum entropy models (MAXENT) and random forest (RF) in this study to map the predicted global An. stephensi climatically suitable areas.

RESULTS

According to the predictions of this study, some areas where there are no current records of An. stephensi, showed significant areas of climatically suitable for An. stephensi. In addition, the global climatically suitability areas for An. stephensi are expanding with global climate change, with some areas changing from unsuitable to suitable, suggesting a greater risk of invasion of An. stephensi in these areas, with the attendant possibility of a resurgence of malaria, as has been the case in Djibouti.

CONCLUSIONS

This study provides evidence for the possible invasion and expansion of An. stephensi and serves as a reference for the optimization of targeted monitoring and control strategies for this malaria vector in potential invasion risk areas.

Population genetic variation and geographic distribution of suitable areas of Coptis species in China

Introduction

The rhizomes of Coptis plants have been used in traditional Chinese medicine over 2000 years. Due to increasing market demand, the overexploitation of wild populations, habitat degradation and indiscriminate artificial cultivation of Coptis species have severely damaged the native germplasms of species in China.

Methods

Genome-wide simple-sequence repeat (SSR) markers were developed using the genomic data of C. chinensis. Population genetic diversity and structure of 345 Coptis accessions collected from 32 different populations were performed based on these SSRs. The distribution of suitable areas for three taxa in China was predicted and the effects of environmental variables on genetic diversity in relation to different population distributions were further analyzed.

Results

22 primer pairs were selected as clear, stable, and polymorphic SSR markers. These had an average of 16.41 alleles and an average polymorphism information content (PIC) value of 0.664. In the neighbor-joining (N-J) clustering analysis, the 345 individuals clustered into three groups, with C. chinensis, C. chinensis var. brevisepala and C. teeta being clearly separated. All C. chinensis accessions were further divided into four subgroups in the population structure analysis. The predicted distributions of suitable areas and the environmental variables shaping these distributions varied considerably among the three species.

Discussion

Overall, the amount of solar radiation, precipitation and altitude were the most important environmental variables influencing the distribution and genetic variation of three species. The findings will provide key information to guide the conservation of genetic resources and construction of a core reserve for species.

Prediction of potential suitable habitats in the 21st century and GAP analysis of priority conservation areas of Chionanthus retusus based on the MaxEnt and Marxan models

Chionanthus retusus (C. retusus) has a high economic and medicinal value, but in recent years it has been included in the list of China's major protected plants and China's Red List of Biodiversity due to the serious destruction of its wild germplasm resources. Based on 131 sample points of C. retusus, this study simulated potential habitats and spatial changes of C. retusus in the 21st century using the Maxent model combined with the geographic information system ArcGIS, predicted prioritized protected areas by the Marxan model, and assessed current conservation status through GAP analysis. The results showed that (1) when the regularization multiplier was 1.5 and the feature combinations were linear, quadratic, and fragmented, the area under the curve of the subjects in the training and test sets were both above 0.9, the true skill statistic value was 0.80, and the maximum Kappa value was 0.62, meaning that the model had high accuracy; (2) Temperature seasonality, annual precipitation, min temperature for coldest month, and precipitation of wettest month had relatively strong influences on species' ranges. (3) The moderately and optimally suitable habitats of C. retusus were primly located in the areas of southwestern Shanxi, central Hebei, western Henan, Shandong, Shaanxi, Anhui and Hubei; (4) Under different future climate scenarios, the area of each class of suitable habitat will increase for varied amounts compared to the current period, with a general trend of expansion to the south; (5) The C. retusus priority protected areas were mainly located in most of Shandong, southern Liaoning, southwestern Shanxi, western Henan, and central Hebei, and its conservation vacancy area was relatively large compared to its protected area. These results will provide scientific strategies for implementing long-term conservation of C. retusus in China and similar regions under warming conditions in the 21st century.

Predicting the potential distribution of 12 threatened medicinal plants on the Qinghai-Tibet Plateau, with a maximum entropy model

Climate change is a vital driver of biodiversity patterns and species distributions, understanding how organisms respond to climate change will shed light on the conservation of endangered species. In this study, the MaxEnt model was used to predict the potential suitable area of 12 threatened medicinal plants in the QTP (Qinghai-Tibet Plateau) under the current and future (2050s, 2070s) three climate scenarios (RCP2.6, RCP4.5, RCP8.5). The results showed that the climatically suitable habitats for the threatened medicinal plants were primarily found in the eastern, southeast, southern, and some parts of the central regions on the QTP. Moreover, 25% of the threatened medicinal plants would have reduced suitable habitat areas within the next 30-50 years in the different future global warming scenarios. Among these medicinal plants, RT (Rheum tanguticum) would miss the most habitat (98.97%), while the RAN (Rhododendron anthopogonoides) would miss the least habitat (10.15%). Nevertheless, 33.3% of the threatened medicinal plants showed an increase in their future habitat area because of their physiological characteristics which are more adaptable to a wide range of climates. The climatic suitable habitat for 50% of the threatened medicinal plants would migrate to higher altitudes or higher latitudes regions. This study provides a data foundation for the conservation of biodiversity and wild medicinal plants on the QTP.

Climate change may drive the distribution of tribe Zyginelline pests in China and the Indo-China Peninsula to shift towards higher latitude river-mountain systems

BACKGROUND

Tribe Zyginelline leafhoppers can transmit plant viruses and are important pests that affect agriculture, forestry, and animal husbandry, causing serious economic losses. The potential distribution patterns of Zyginellini will change under climate change. Therefore, the best-performing random forest and maximum entropy models among 12 commonly used ecological niche models, alongside an ensemble model, were selected to predict the changes in habitat suitability distribution of Zyginellini under current and future climate scenarios [represented by two shared socio-economic pathways (SSPs), namely SSP126 and SSP585, for three periods (2050s, 2070s, and 2090s)] in China and the Indo-China Peninsula for the first time.

RESULTS

The results revealed that the distribution of Zyginellini was mainly dominated by minimum temperature of coldest month. Under current and future climate scenarios, Zyginellini was mostly distributed southeast of the 400 mm equivalent precipitation line in China, and Vietnam. Under the future SSP126 scenario, the alert areas will mainly be concentrated in Hunan, Jiangxi, Zhejiang, Anhui, and Hebei in China, alongside Myanmar and Thailand in the Indo-China Peninsula. Meanwhile, in the SSP585 scenario, the alert areas in China will increase, whereas there will be little change in the Indo-China Peninsula. Interestingly, from the current to the future, the cores of Zyginelline distribution occurred around rivers and mountains, and shifted from Guizhou along the Yuanjiang River system to higher latitudes in Hunan.

CONCLUSION

Zyginellini prefers higher latitude river-mountain systems under climate change. Our results will contribute to effective pest control strategies and biogeographical research for Zyginellini alongside other Cicadellidae insects. © 2023 Society of Chemical Industry.

Comparative Assessment of Habitat Suitability and Niche Overlap of Three Cytospora Species in China

The plant pathogenic fungus Cytospora is notoriously known for causing woody plant canker diseases, resulting in substantial economic losses to biological forests and fruit trees worldwide. Despite their strong negative ecological impact, the existing and prospective distribution patterns of these plant pathogens in China, according to climate change, have received little attention. In this study, we chose three widely dispersed and seriously damaging species, namely, Cytospora chrysosperma, Cytospora mali, and Cytospora nivea, which are the most common species that damage the Juglans regia, Malus domestica, Eucalyptus, Pyrus sinkiangensis, Populus spp., and Salix spp. in China. We utilized ecological niche modeling to forecast their regional distribution in China under four climate change scenarios (present, SSP 126, SSP 370, and SSP 585). The results show that temperature-related climate factors limit the current distribution ranges of the three species. Currently, the three studied species are highly suitable for northeast, northwest, north, and southwest China. Under future climate scenarios, the distribution ranges of the three species are projected to increase, and the centers of the adequate distribution areas of the three species are expected to shift to high-latitude regions. The three species coexist in China, primarily in the northwest and north regions. The ecological niches of C. chrysosperma and C. nivea are more similar. The distribution range of C. mali can reach the warmer and wetter eastern region, whereas C. chrysosperma and C. nivea are primarily found in drought-prone areas with little rainfall. Our findings can help farmers and planners develop methods to avoid the spread of Cytospora spp. and calculate the costs of applying pesticides to reduce contamination and boost yields.

Environmental factors influencing potential distribution of Schisandra sphenanthera and its accumulation of medicinal components

Schisandrae Sphenantherae Fructus (SSF), the dry ripe fruit of Schisandra sphenanthera Rehd. et Wils., is a traditional Chinese medicine with wide application potential. The quality of SSF indicated by the composition and contents of secondary metabolites is closely related to environmental factors, such as regional climate and soil conditions. The aims of this study were to predict the distribution patterns of potentially suitable areas for S. sphenanthera in China and pinpoint the major environmental factors influencing its accumulation of medicinal components. An optimized maximum entropy model was developed and applied under current and future climate scenarios (SSP1-RCP2.6, SSP3-RCP7, and SSP5-RCP8.5). Results show that the total suitable areas for S. sphenanthera (179.58×104 km2) cover 18.71% of China's territory under the current climatic conditions (1981-2010). Poorly, moderately, and highly suitable areas are 119.00×104 km2, 49.61×104 km2, and 10.98×104 km2, respectively. The potentially suitable areas for S. sphenanthera are predicted to shrink and shift westward under the future climatic conditions (2041-2070 and 2071-2100). The areas of low climate impact are located in southern Shaanxi, northwestern Guizhou, southeastern Chongqing, and western Hubei Provinces (or Municipality), which exhibit stable and high suitability under different climate scenarios. The contents of volatile oils, lignans, and polysaccharides in SSF are correlated with various environmental factors. The accumulation of major secondary metabolites is primarily influenced by temperature variation, seasonal precipitation, and annual precipitation. This study depicts the potential distribution of S. sphenanthera in China and its spatial change in the future. Our findings decipher the influence of habitat environment on the geographical distribution and medicinal quality of S. sphenanthera, which could have great implications for natural resource conservation and artificial cultivation.

Geographical origin traceability of mulberry leaves using stable hydrogen, oxygen, and carbon isotope ratios

Geographical discrimination of mulberry leaves is very important for their efficacy and quality as a traditional Chinese medicine. Stable hydrogen, oxygen, and carbon isotope ratios were measured in 292 mulberry leaves collected at 2 growth stages in 2 seasons from 8 regions of China. A stepwise linear discriminant analysis (LDA) approach were proposed to combine with stable isotope technology to tracing the origin of mulberry leaves. The results showed that leaves sampled in autumn were extremely depleted in 2H and 18O and slightly enriched in 13C compared with leaves sampled in summer, correlated with the effect of season, transpiration and photorespiration on stable isotopes. δ2H and δ18O of the leaves were enriched during the growth process. The overall discrimination accuracy of the autumn tender model was 81%, demonstrating that analysis of δ2H, δ18O, and δ13C is a promising technique for tracing the geographical origin of mulberry leaves, although season, growth stage and number of samples affect the accuracy of discrimination.

Recent trends of machine learning applied to multi-source data of medicinal plants

In traditional medicine and ethnomedicine, medicinal plants have long been recognized as the basis for materials in therapeutic applications worldwide. In particular, the remarkable curative effect of traditional Chinese medicine during corona virus disease 2019 (COVID-19) pandemic has attracted extensive attention globally. Medicinal plants have, therefore, become increasingly popular among the public. However, with increasing demand for and profit with medicinal plants, commercial fraudulent events such as adulteration or counterfeits sometimes occur, which poses a serious threat to the clinical outcomes and interests of consumers. With rapid advances in artificial intelligence, machine learning can be used to mine information on various medicinal plants to establish an ideal resource database. We herein present a review that mainly introduces common machine learning algorithms and discusses their application in multi-source data analysis of medicinal plants. The combination of machine learning algorithms and multi-source data analysis facilitates a comprehensive analysis and aids in the effective evaluation of the quality of medicinal plants. The findings of this review provide new possibilities for promoting the development and utilization of medicinal plants.

Modelling the effects of topographic heterogeneity on distribution of Nitraria tangutorum Bobr. species in deserts using LiDAR-data

Microclimate ecology is attracting renewed attention because of its fundamental importance in understanding how organisms respond to climate change. Many hot issues can be investigated in desert ecosystems, including the relationship between species distribution and environmental gradients (e.g., elevation, slope, topographic convergence index, and solar insolation). Species Distribution Models (SDMs) can be used to understand these relationships. We used data acquired from the important desert plant Nitraria tangutorum Bobr. communities and desert topographic factors extracted from LiDAR (Light Detection and Ranging) data of one square kilometer in the inner Mongolia region of China to develop SDMs. We evaluated the performance of SDMs developed with a variety of both the parametric and nonparametric algorithms (Bioclimatic Modelling (BIOCLIM), Domain, Mahalanobi, Generalized Linear Model, Generalized Additive Model, Random Forest (RF), and Support Vector Machine). The area under the receiver operating characteristic curve was used to evaluate these algorithms. The SDMs developed with RF showed the best performance based on the area under curve (0.7733). We also produced the Nitraria tangutorum Bobr. distribution maps with the best SDM and suitable habitat area of the Domain model. Based on the suitability map, we conclude that Nitraria tangutorum Bobr. is more suited to southern part with 0-20 degree slopes at an elevation of approximately 1010 m. This is the first attempt of modelling the effects of topographic heterogeneity on the desert species distribution on a small scale. The presented SDMs can have important applications for predicting species distribution and will be useful for preparing conservation and management strategies for desert ecosystems on a small scale.

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.

Invasive Trends of Spartina alterniflora in the Southeastern Coast of China and Potential Distributional Impacts on Mangrove Forests

Mangrove forests are one of the most productive and seriously threatened ecosystems in the world. The widespread invasion of Spartina alterniflora has seriously imperiled the security of mangroves as well as coastal mudflat ecosystems. Based on a model evaluation index, we selected RF, GBM, and GLM as a predictive model for building a high-precision ensemble model. We used the species occurrence records combined with bioclimate, sea-land topography, and marine environmental factors to predict the potentially suitable habitats of mangrove forests and the potentially suitable invasive habitats of S. alterniflora in the southeastern coast of China. We then applied the invasion risk index (IRI) to assess the risk that S. alterniflora would invade mangrove forests. The results show that the suitable habitats for mangrove forests are mainly distributed along the coastal provinces of Guangdong, Hainan, and the eastern coast of Guangxi. The suitable invasive habitats for S. alterniflora are mainly distributed along the coast of Zhejiang, Fujian, and relatively less in the southern provinces. The high-risk areas for S. alterniflora invasion of mangrove forests are concentrated in Zhejiang and Fujian. Bioclimate variables are the most important variables affecting the survival and distribution of mangrove forests and S. alterniflora. Among them, temperature is the most important environmental variable determining the large-scale distribution of mangrove forests. Meanwhile, S. alterniflora is more sensitive to precipitation than temperature. Our results can provide scientific insights and references for mangrove forest conservation and control of S. alterniflora.

Spatial Distribution Characteristics of Suitable Planting Areas for Pyrus Species under Climate Change in China

Planting suitability determines the distribution and yield of crops in a given region which can be greatly affected by climate change. In recent years, many studies have shown that carbon dioxide fertilization effects increase the productivity of temperate deciduous fruit trees under a changing climate, but the potential risks to fruit tree planting caused by a reduction in suitable planting areas are rarely reported. In this study, Maxent was first used to investigate the spatial distribution of five Pyrus species in China, and the consistency between the actual production area and the modeled climatically suitable area under the current climatic conditions were determined. In addition, based on Coupled Model Intercomparison Project Phase 6, three climate models were used to simulate the change in suitable area and the migration trend for different species under different emission scenarios (SSP1-2.6, SSP2-4.5, SSP3-7.0 and SSP5-8.5). The results showed that the suitable area for pear was highly consistent with the actual main production area under current climate conditions. The potential planting areas of P. ussuriensis showed a downward trend under all emission paths from 2020 to 2100; other species showed a trend of increasing first and then decreasing or slowing down and this growth effect was the most obvious in 2020-2040. Except for P. pashia, other species showed a migration trend toward a high latitude, and the trend was more prominent under the high emission path. Our results emphasize the response difference between species to climate change, and the method of consistency analysis between suitable planting area and actual production regions cannot only evaluate the potential planting risk but also provide a reasonable idea for the accuracy test of the modeled results. This work has certain guiding and reference significance for the protection of pear germplasm resources and the prediction of yield.

The impact of global warming on the potential suitable planting area of Pistacia chinensis is limited

Pistacia chinensis Bunge. is one of the main woody oil crops with a large artificial planting area in China and has important economic and ecological value. Here, based on 237 occurrence data and 22 environmental variables, we explored the potential planting area of P. chinensis in China in the present and future climate change scenarios by using a comprehensive model method. To fully consider the potential planting area of P. chinensis under specific climate change conditions and the limitations of soil conditions, we separately built two niche models to simulate the climate niche and soil demand niche, and then used the intersection of the two models as the result of the comprehensive habitat suitability model, finally, we used land-use data to filter the CHS model result. Our results showed, that under the baseline condition, the potential planting area of P. chinensis covers approximately 0.74 × 10⁶ km² in China. The future projection showed that the impact of global warming on the potentially suitable planting area of P. chinensis is limited, and most of the existing suitable habitats are not affected by climate change. With increasing temperature, the potential planting area will expand northward and slightly contract in the south margin, and its area will be slightly increased. Therefore, this species has great planting potential in China and should be given priority in the future afforestation plan.

Modeling current geographic distribution and future range shifts of Sanghuangporus under multiple climate change scenarios in China

The genus Sanghuangporus is well-known for its edible and medicinal values. In this study, the most comprehensive occurrence records of Sanghuangporus with accurate species identification are subjected to MaxEnt, to model the current geographic distribution and future range shifts under multiple climate change scenarios in China. The current potential distribution model of Sanghuangporus is excellently predicted as indicated by the value of Area Under Receiver Operator Characteristic Curve. The current potential distribution basically corresponds to the known occurrence records of Sanghuangporus, and provides clues to new suitable habitats. The critical environmental variables to the distribution are annual precipitation, host plant, annual mean temperature and elevation. Host plant is not the most critical contribution to the model, but it indeed plays a decisive role in restricting the distribution of Sanghuangporus. This role is further confirmed by the distribution area of the highly suitable habitat increasing by 155.468%, when excluding host plant from environmental variables. For future scenarios, generally the area of highly suitable habitat for Sanghuangporus extremely increases, but the locations do not change a lot. In conclusion, this study provides important ecological information for the utilization and conservation of the edible and medicinal fungus Sanghuangporus.

ResNet and MaxEnt modeling for quality assessment of Wolfiporia cocos based on FT-NIR fingerprints

As a fungus with both medicinal and edible value, Wolfiporia cocos (F. A. Wolf) Ryvarden & Gilb. has drawn more public attention. Chemical components' content fluctuates in wild and cultivated W. cocos, whereas the accumulation ability of chemical components in different parts is different. In order to perform a quality assessment of W. cocos, we proposed a comprehensive method which was mainly realized by Fourier transform near-infrared (FT-NIR) spectroscopy and ultra-fast liquid chromatography (UFLC). A qualitative analysis means was built a residual convolutional neural network (ResNet) to recognize synchronous two-dimensional correlation spectroscopy (2DCOS) images. It can rapidly identify samples from wild and cultivated W. cocos in different parts. As a quantitative analysis method, UFLC was used to determine the contents of three triterpene acids in 547 samples. The results showed that a simultaneous qualitative and quantitative strategy could accurately evaluate the quality of W. cocos. The accuracy of ResNet models combined synchronous FT-NIR 2DCOS in identifying wild and cultivated W. cocos in different parts was as high as 100%. The contents of three triterpene acids in Poriae Cutis were higher than that in Poria, and the one with wild Poriae Cutis was the highest. In addition, the suitable habitat plays a crucial role in the quality of W. cocos. The maximum entropy (MaxEnt) model is a common method to predict the suitable habitat area for W. cocos under the current climate. Through the results, we found that suitable habitats were mostly situated in Yunnan Province of China, which accounted for approximately 49% of the total suitable habitat area of China. The research results not only pave the way for the rational planting in Yunnan Province of China and resource utilization of W. cocos, but also provide a basis for quality assessment of medicinal fungi.

Comparison between optimized MaxEnt and random forest modeling in predicting potential distribution: A case study with Quasipaa boulengeri in China

Random forest (RF) and MaxEnt models are shallow machine learning approaches that perform well in predicting species' potential distributions. RF models can produce robust results with the default automatic configuration in most cases, but it is necessary for MaxEnt to optimize the model settings to improve the performance, and the predictive performance difference between optimized MaxEnt and RF is uncertain. To explore this issue, the potential distribution of the endangered amphibian Quasipaa boulengeri in China was predicted using optimized MaxEnt and RF models. A total of 408 occurrence data were selected, 1000 locations were generated as pseudo-absence data by the geographic distance method, and 10,000 sites were selected as background data by creating a bias file. Partial ROC at different thresholds and success rate curves were used to compare the predictive performances between optimized MaxEnt and RF. Our results showed that the RF and optimized MaxEnt models both had good performance in predicting the potential distribution of Q. boulengeri, with the RF model performing slightly better whether based on partial ROC or success rate curves. Furthermore, the core suitable habitat regions of Q. boulengeri identified by RF and MaxEnt were similar and were all located in the Sichuan, Chongqing, Hubei, Hunan, and Guizhou provinces. However, the RF model produced a habitat suitability map with higher discrimination and greater heterogeneity. Temperature annual range, mean temperature of the driest quarter, and annual precipitation were the vital environmental variables limiting the distribution of Q. boulengeri. The RF model is the stronger machine learner. We believe it may be more applicable in predicting the native potential distributions of species with sufficient occurrence data, given the additional predictive detail, the simplicity of use, the computational time involved, and the operational complexity.

Response of distribution patterns of two closely related species in Taxus genus to climate change since last inter-glacial

Climate change affects the species spatio-temporal distribution deeply. However, how climate affects the spatio-temporal distribution pattern of related species on the large scale remains largely unclear. Here, we selected two closely related species in Taxus genus Taxus chinensis and Taxus mairei to explore their distribution pattern. Four environmental variables were employed to simulate the distribution patterns using the optimized Maxent model. The results showed that the highly suitable area of T. chinensis and T. mairei in current period was 1.616 × 10⁵ km² and 3.093 × 10⁵ km², respectively. The distribution area of T. chinensis was smaller than that of T. mairei in different periods. Comparison of different periods shown that the distribution area of the two species was almost in stasis from LIG to the future periods. Temperature and precipitation were the main climate factors that determined the potential distribution of the two species. The centroids of T. chinensis and T. mairei were in Sichuan and Hunan provinces in current period, respectively. In the future, the centroid migration direction of the two species would shift towards northeast. Our results revealed that the average elevation distribution of T. chinensis was higher than that of T. mairei. This study sheds new insights into the habitat preference and limiting environment factors of the two related species and provides a valuable reference for the conservation of these two threatened species.

Phytochemistry and bioactivities of the main constituents of Polyporus umbellatus (Pers.) Fries

BACKGROUND

Edible fungi resources have good application prospects in the research and development of food, medicine, and health products. Polyporus umbellatus (Pers.) Fries, as a precious edible and medicinal fungus, has long been used by Chinese medicine to treat urinary systems and related kidney diseases.

PURPOSE

In recent years, researchers have discovered and isolated a variety of active compounds from P. umbellatus. Modern phytochemical and pharmacological experiments showed that the crude extract of P. umbellatus had many biological functions and could be widely used in the fields of food, pharmaceutical and cosmetics. This paper summarizes the active components of P. umbellatus, through elaborating its mechanism of action, further clarify the action substances, in order to improve the utilization rate of P. umbellatus, promote the development and application of P. umbellatus in food, pharmaceutical and cosmetics industry.

METHODS

In this paper, the literatures related to P. umbellatus were summarized and classified by "China National Knowledge Instructure (CNKI)", "Google Scholar" and "Web of Science". Compared with other articles, this work systematically sorted out all the active substances with clear structures in P. umbellatus. On this basis, combined with the chemical composition of P. umbellatus, its functional efficacy was expounded, and the effects of different types of active substances in P. umbellatus were further presented.

RESULTS

The main chemical constituents of P. umbellatus include polysaccharide and sterol, and the secondary compounds include fatty acids, phenols and other small molecules. These active substances endowed P. umbellatus anti-cancer, antibacterial, diuretic, antioxidant, enhance immune system, promote hair growth and other pharmacological activities, which has been verified many times in vivo and in vitro experiments.

CONCLUSION

Modern in vitro or in vivo pharmacological experiments and clinical practice for the efficacy of P. umbellatus provides a strong support, and the separation of compounds in P. umbellatus has also deepened people's understanding of this traditional Chinese medicine, greatly promoted the development and application of P. umbellatus. However, the complex active substances of poring also hinder the research of P. umbellatus to some extent, and the mechanism of action and potential synergistic or antagonistic effect of the mixture of various active ingredients have not been clearly analyzed. How to use the bioactivity-guided separation strategy to identify more bioactive components and analyze the molecular mechanism of the main active components have become the main problems of P. umbellatus research, but also provides a direction for the further study of it.

Large-scale forecasting of Heracleum sosnowskyi habitat suitability under the climate change on publicly available data

This research aims to establish the possible habitat suitability of Heracleum sosnowskyi (HS), one of the most aggressive invasive plants, in current and future climate conditions across the territory of the European part of Russia. We utilised a species distribution modelling framework using publicly available data of plant occurrence collected in citizen science projects (CSP). Climatic variables and soil characteristics were considered to follow possible dependencies with environmental factors. We applied Random Forest to classify the study area. We addressed the problem of sampling bias in CSP data by optimising the sampling size and implementing a spatial cross-validation scheme. According to the Random Forest model built on the finally selected data shape, more than half of the studied territory in the current climate corresponds to a suitability prediction score higher than 0.25. The forecast of habitat suitability in future climate was highly similar for all climate models. Almost the whole studied territory showed the possibility for spread with an average suitability score of 0.4. The mean temperature of the wettest quarter and precipitation of wettest month demonstrated the highest influence on the HS distribution. Thus, currently, the whole study area, excluding the north, may be considered as s territory with a high risk of HS spreading, while in the future suitable locations for the HS habitat will include high latitudes. We showed that chosen geodata pre-processing, and cross-validation based on geospatial blocks reduced significantly the sampling bias. Obtained predictions could help to assess the risks accompanying the studied plant invasion capturing the patterns of the spread, and can be used for the conservation actions planning.

The potential habitat of desert locusts is contracting: predictions under climate change scenarios

Desert locusts are notorious for their widespread distribution and strong destructive power. Their influence extends from the vast arid and semiarid regions of western Africa to northwestern India. Large-scale locust outbreaks can have devastating consequences for food security, and their social impact may be long-lasting. Climate change has increased the uncertainty of desert locust outbreaks, and predicting suitable habitats for this species under climate change scenarios will help humans deal with the potential threat of locust outbreaks. By comprehensively considering climate, soil, and terrain variables, the maximum entropy (MaxEnt) model was used to predict the potential habitats of solitary desert locusts in the 2050s and 2070s under the four shared socioeconomic pathways (SSP126, SSP245, SSP370, and SSP585) in the CMIP6 model. The modeling results show that the average area under the curve (AUC) and true skill statistic (TSS) reached 0.908 ± 0.002 and 0.701, respectively, indicating that the MaxEnt model performed extremely well and provided outstanding prediction results. The prediction results indicate that climate change will have an impact on the distribution of the potential habitat of solitary desert locusts. With the increase in radiative forcing overtime, the suitable areas for desert locusts will continue to contract, especially in the 2070s under the SSP585 scenario, and the moderately and highly suitable areas will decrease by 0.88 × 10⁶ km² and 1.55 × 10⁶ km², respectively. Although the potentially suitable area for desert locusts is contracting, the future threat posed by the desert locust to agricultural production and food security cannot be underestimated, given the combination of maintained breeding areas, frequent extreme weather events, pressure from population growth, and volatile sociopolitical environments. In conclusion, methods such as monitoring and early warning, financial support, regional cooperation, and scientific prevention and control of desert locust plagues should be further implemented.

Predicting the Potential Geographic Distribution and Habitat Suitability of Two Economic Forest Trees on the Loess Plateau, China

The Loess Plateau is one of the most fragile ecosystems in the world. In order to increase the biodiversity in the area, develop sustainable agriculture and increase the income of the local people, we simulated the potential geographic distribution of two economic forest trees (Malus pumila Mill and Prunus armeniaca L.) in the present and future under two climate scenarios, using the maximum entropy model. In this study, the importance and contributions of environmental variables, areas of suitable habitats, changes in habitat suitability, the direction and distance of habitat range shifts, the change ratios for habitat area and land use proportions, were measured. According to our results, bioclimatic variables, topographic variables and soil variables play a significant role in defining the distribution of M. pumila and P. armeniaca. The min temperature of coldest month (bio6) was the most important environmental variable for the distribution of the two economic forest trees. The second most important factors for M. pumila and P. armeniaca were, respectively, the elevation and precipitation of the driest quarter (bio17). At the time of the study, the area of above moderately suitable habitats (AMSH) was 8.7967 × 104 km2 and 11.4631 × 104 km2 for M. pumila and P. armeniaca. The effect of Shared Socioeconomic Pathway (SSP) 5-85 was more dramatic than that of SSP1-26. Between now and the 2090s (SSP 5-85), the AMSH area of M. pumila is expected to decrease to 7.5957 × 104 km2, while that of P. armeniaca will increase to 34.6465 × 104 km2. The suitability of M. pumila decreased dramatically in the south and southeast regions of the Loess Plateau, increased in the middle and west and resulted in a shift in distance in the range of 78.61~190.63 km to the northwest, while P. armeniaca shifted to the northwest by 64.77~139.85 km. This study provides information for future policymaking regarding economic forest trees in the Loess Plateau.

Predicting the invasive trend of exotic plants in China based on the ensemble model under climate change: A case for three invasive plants of Asteraceae

Ageratina adenophora, Eupatorium odoratum, and Mikania micrantha are three highly destructive invasive plants of Compositae in China. Through the screening of SDMs, random forest (RF), gradient boosting model (GBM), artificial neural network (ANN), and flexible discriminant analysis (FDA) with TSS greater than 0.8 are selected to construct a high-precision ensemble model (EM) as the prediction model. We use specimen sites and environmental variables containing climate, soil, terrain, and human activities to simulate and predict the invasion trend of three invasive weeds in China in current, the 2050s, and the 2070s. Results indicate that the highly invasive risk area of three exotic plants is mostly distributed along the river in the provinces south of 30° N. In the future scenario, the three exotic plants obviously invade northwards Yunnan, Sichuan, Guizhou, Jiangxi and Fujian. Climate is the most important variable that affects the spread of three kinds of alien plant invasions. Temperature and precipitation variables have a similar effect on A. adenophora and E. odoratum, while M. micrantha is more sensitive to temperature. It has been reported that Ipomoea batatas and Vitex negundo can prevent the invasion of three invasive plants. Hence, we also simulate the suitable planting areas for I. batatas and V. negundo. The results show that I. batatas and V. negundo are suitable to be planted in the areas where the three weeds show invasion tendency. In the paper, predicting invasion trends of exotic plants and simulating the planting suitability of crops that can block invasion, to provide a practical significance reference and suggestion for the management, prevention, and control of the invasion of exotic plants in China.

Chinese caterpillar fungus (Ophiocordyceps sinensis) in China: Current distribution, trading, and futures under climate change and overexploitation

Chinese caterpillar fungus (Ophiocordyceps sinensis) is a precious traditional medicine which is mostly distributed on the Qinghai-Tibetan Plateau (QTP). Due to its medicinal values, it has become one of the most valuable biological commodities and widely traded in recent years worldwide. However, its habitat has changed profoundly in recent years under global warming as well as anthropogenic pressures, resulting in a sharp decline in its wild population in recent years. Based on the occurrence samples, this paper estimates the potential distribution of caterpillar fungus using MaxEnt model. The model simulates potential geographical distribution of the species under current climate conditions, and examine future distributions under different climatic change scenarios (i.e., RCP 2.6, RCP 4.5, RCP 6.0 and RCP 8.5 have been modelled in 2050s and 2070s, respectively). For examining the impacts of climate change in future, the integrated effects of climatic impact, trading, and overexploitation had been analyzed in detailed routes. The results show that: 1) The distribution patterns of caterpillar fungus under scenario RCP 2.6 have been predicted without obvious changes. However, range shift has been observed with significant shrinks across all classes of suitable areas in Tianshan, Kunlun Mountains, and the southwestern QTP in 2050s and 2070s under RCP 4.5, RCP 6.0 and RCP 8.5 scenarios, respectively. 2) The exports were decreasing drastically in recent years. Guangzhou and Hongkong are two international super import and consumption centres of caterpillar fungus in the world. 3) Both ecological and economic sustainable utilization of the caterpillar fungus has been threatened by the combined pressures of climate change and overexploitation. A strict but effective regulation and protection system, even a systematic management plan not just on the collectors but the whole explore process are urgently needed and has to be issued in the QTP.

Impact of Past and Future Climate Change on the Potential Distribution of an Endangered Montane Shrub Lonicera oblata and Its Conservation Implications

Climate change is an important driver of biodiversity patterns and species distributions, understanding how organisms respond to climate change will shed light on the conservation of endangered species. In this study, we modeled the distributional dynamics of a critically endangered montane shrub Lonicera oblata in response to climate change under different periods by building a comprehensive habitat suitability model considering the effects of soil and vegetation conditions. Our results indicated that the current suitable habitats for L. oblata are located scarcely in North China. Historical modeling indicated that L. oblata achieved its maximum potential distribution in the last interglacial period which covered southwest China, while its distribution area decreased for almost 50% during the last glacial maximum. It further contracted during the middle Holocene to a distribution resembling the current pattern. Future modeling showed that the suitable habitats of L. oblata contracted dramatically, and populations were fragmentedly distributed in these areas. As a whole, the distribution of L. oblata showed significant migration northward in latitude but no altitudinal shift. Several mountains in North China may provide future stable climatic areas for L. oblata, particularly, the intersections between the Taihang and Yan mountains. Our study strongly suggested that the endangered montane shrub L. oblata are sensitive to climate change, and the results provide new insights into the conservation of it and other endangered species.

The Impact of Human Pressure and Climate Change on the Habitat Availability and Protection of Cypripedium (Orchidaceae) in Northeast China

Human pressure on the environment and climate change are two important factors contributing to species decline and overall loss of biodiversity. Orchids may be particularly vulnerable to human-induced losses of habitat and the pervasive impact of global climate change. In this study, we simulated the extent of the suitable habitat of three species of the terrestrial orchid genus Cypripedium in northeast China and assessed the impact of human pressure and climate change on the future distribution of these species. Cypripedium represents a genus of long-lived terrestrial orchids that contains several species with great ornamental value. Severe habitat destruction and overcollection have led to major population declines in recent decades. Our results showed that at present the most suitable habitats of the three species can be found in Da Xing’an Ling, Xiao Xing’an Ling and in the Changbai Mountains. Human activity was predicted to have the largest impact on species distributions in the Changbai Mountains. In addition, climate change was predicted to lead to a shift in distribution towards higher elevations and to an increased fragmentation of suitable habitats of the three investigated Cypripedium species in the study area. These results will be valuable for decision makers to identify areas that are likely to maintain viable Cypripedium populations in the future and to develop conservation strategies to protect the remaining populations of these enigmatic orchid species.

Predicting the Potential Distribution of Apple Canker Pathogen (Valsa mali) in China under Climate Change

Apple valsa canker (AVC), caused by Valsa mali, is a serious wood disease of apple trees. The pathogen decays the barks and branches of trees and ruins entire orchards under severe conditions. However, studies have rarely focused on the suitable habitat of the pathogen, especially on a relatively large scale. In this study, we applied the maximum entropy model (MaxEnt 3.4.1, Princeton, NJ, USA) to predict the distribution of V. mali using climate factors, topographic factors, and soil factors under current and future climate scenarios. We measured the area of suitable habitat, change ratio of the suitable habitat area, increase and decrease maps under climate change, direction and distance of range shifts from the present to the end of the 21st century, and the contribution of environmental variables. The results showed that the area of suitable habitat is currently 183.46 × 104 km2 in China, among which 27.54% is moderately suitable habitat (MSH) and 13.13% is highly suitable habitat (HSH). Compared with current distribution, the area of MSH and HSH increases in future and the change ratio are positive. The Shared Socioeconomic Pathways (SSPs) 3–70 is considered the optimum climate scenario for V. mali. The suitability of V. mali increased mainly in Northwest, North, and Northeast China. V. mali will shift to the northwest with climate change. The shift distance optimistically increased from the SSP1–26 to the SSP5–85, with the biggest shift distance of 758.44 km in the 2090s under the SSP5–85 scenario. Minimum temperature of the coldest month (bio6) was the most critical climate factor affecting the distribution of the pathogen, and topographic factors played a more important role than soil factors. This study demonstrates that the potential distribution of V. mali is vitally affected by climate change and provides a method for large–scale research on the distribution of pathogens.

Wetlands rise and fall: Six endangered wetland species showed different patterns of habitat shift under future climate change

Degradation and loss of species' suitable habitats in response to global warming are well documented, which are assumed to be affected by increasing temperature. Conversely, habitat increase of species is little reported and is often considered anomalous and unrelated to climate change. In this study, we first revealed the climate-change-driven habitat shifts of six endangered wetland plants - Bruguiera gymnorrhiza, Carex doniana, Glyptostrobus pensilis, Leersia hexandra, Metasequoia glyptostroboides, and Pedicularis longiflora. The current and future potential habitats of the six species in China were predicted using a maximum entropy model based on thirty-year occurrence records and climate monitoring (from 1960 to 1990). Furthermore, we observed the change of real habitats of the six species based on eight-year field observations (from 2011 to 2019). We found that the six species exhibited three different patterns of habitat shifts including decrease, unstable, and increase. The analysis on the main decisive environmental factors showed that these patterns of habitat shifts are counter to what would be expected global warming but are mostly determined by precipitation-related environmental factors rather than temperature. Collectively, our findings highlight the importance of combining multiple environmental factors including temperature and precipitation for understanding plant responses to climate change.

Potential distribution of Notopterygium incisum Ting ex H. T. Chang and its predicted responses to climate change based on a comprehensive habitat suitability model

Notopterygium incisum Ting ex H. T. Chang is a rare and endangered traditional Chinese medicinal plant. In this research, we built a comprehensive habitat suitability (CHS) model to analyze the potential suitable habitat distribution of this species in the present and future in China. First, using nine different algorithms, we built an ensemble model to explore the possible impacts of climate change on the habitat distribution of this species. Then, based on this model, we built a CHS model to further identify the distribution characteristics of N. incisum-suitable habitats in three time periods (current, 2050s, and 2070s) while considering the effects of soil and vegetation conditions. The results indicated that the current suitable habitat for N. incisum covers approximately 83.76 × 103 km2, and these locations were concentrated in the Tibet Autonomous Region, Gansu Province, Qinghai Province, and Sichuan Province. In the future, the areas of suitable habitat for N. incisum would significantly decrease and would be 69.53 × 103 km2 and 60.21 × 103 km2 in the 2050s and 2070s, respectively. However, the area of marginally suitable habitat would remain relatively stable. This study provides a more reliable and comprehensive method for modelling the current and future distributions of N. incisum, and it provides valuable insights for highlighting priority areas for medicinal plant conservation and resource utilization.

Non-Pessimistic Predictions of the Distributions and Suitability of Metasequoia glyptostroboides under Climate Change Using a Random Forest Model

Metasequoia glyptostroboides Hu & W. C. Cheng, which is a remarkable rare relict plant, has gradually been reduced to its current narrow range due to climate change. Understanding the comprehensive distribution of M. glyptostroboides under climate change on a large spatio-temporal scale is of great significance for determining its forest adaptation. In this study, based on 394 occurrence data and 10 bioclimatic variables, the global potential distribution of M. glyptostroboides under eight different climate scenarios (i.e., the past three, the current one, and the next four) from the Quaternary glacial to the future was simulated by a random forest model built with the biomod2 package. The key bioclimatic variables affecting the distribution of M. glyptostroboides are BIO2 (mean diurnal range), BIO1 (annual mean temperature), BIO9 (mean temperature of driest quarter), BIO6 (min temperature of coldest month), and BIO18 (precipitation of warmest quarter). The result indicates that the temperature affects the potential distribution of M. glyptostroboides more than the precipitation. A visualization of the results revealed that the current relatively suitable habitats of M. glyptostroboides are mainly distributed in East Asia and Western Europe, with a total area of approximately 6.857 × 106 km2. With the intensification of global warming in the future, the potential distribution and the suitability of M. glyptostroboides have a relatively non-pessimistic trend. Whether under the mild (RCP4.5) and higher (RCP8.5) emission scenarios, the total area of suitable habitats will be wider than it is now by the 2070s, and the habitat suitability will increase to varying degrees within a wide spatial range. After speculating on the potential distribution of M. glyptostroboides in the past, the glacial refugia of M. glyptostroboides were inferred, and projections regarding the future conditions of these places are expected to be optimistic. In order to better protect the species, the locations of its priority protected areas and key protected areas, mainly in Western Europe and East Asia, were further identified. Our results will provide theoretical reference for the long-term management of M. glyptostroboides, and can be used as background information for the restoration of other endangered species in the future.

Spatiotemporal evolution and impacts of climate change on bamboo distribution in China

Understanding the impact and restriction of climate change on potential distribution of bamboo forest is crucial for sustainable management of bamboo forest and bamboo-based economic development. In this study, climatic variables and maximum entropy model were used to simulate the potential distribution of bamboo forest in China under the future climate scenarios. Seven climatic variables, such as Spring precipitation, Summer precipitation, Autumn precipitation, average annual relative humidity, Autumn average temperature, average annual temperature range and annual total radiation, were selected as input variables of maximum entropy model based on the relative importance of those climate variables for predicting bamboo forest presence. The suitable ranges of the seven climatic variables for potential distribution of bamboo forest were 337-794 mm, 496-705 mm, 213-929 mm, 74.3%-83.4%, 16.6-23.8 °C, 2.3-10.1 °C and 3.2 × 10⁴-4.3 × 10⁴ W m^-2, respectively. Under RCP4.5 and RCP8.5 climate scenarios, the suitable area of bamboo forest growth first increased and then decreased, and showed range contractions towards the interior and expansions towards southwest in China. The results of the present study can serve as a useful reference to dynamic monitoring of the spatial distribution and sustainable utilization of bamboo forest in the future under climate change.

Assessing Habitat Suitability of Parasitic Plant Cistanche deserticola in Northwest China under Future Climate Scenarios

: Cistanche deserticola Ma, a perennial parasitic herb of family Orobanchaceae, is mainly parasitic on the roots of the Haloxylon ammodendron Bunge. In view of this special parasitic relationship, we applied random forest (RF) model to forecast potential geographic distribution, and developed a comprehensive habitat suitability model by integrating bioclimatic and soil factors to assess the suitable distribution of C. deserticola and H. ammodendron across China in 2050s and 2070s under RCP2.6, RCP4.5, and RCP8.5, respectively. We modeled the core potential geographic distribution of C. deserticola by overlaying the distribution of these two species, and analyzed the spatial distribution pattern and migration trend of C. deserticola by using the standard deviational ellipse. In addition, we evaluated the accuracy of RF model through three evaluation indexes, and analyzed the dominant climate factors. The results showed that the core potential distribution areas of C. deserticola are distributed in the Xinjiang Uygur Autonomous Region, the junction of Shaanxi–Gansu–Ningxia provinces, and the Inner Mongolia Autonomous Region. The spatial dispersion would intensify with the increasing of emission scenarios, and the geographical habitat is moving towards higher latitude. Among the three evaluation indexes, the area under the ROC curve (AUC) and True Skill Statistic (TSS) have better assessment results. The main bioclimatic factors affecting the distribution are min temperature of coldest month (Bio6), annual precipitation (Bio12), precipitation of wettest month (Bio13), precipitation of wettest quarter (Bio16), and precipitation of warmest quarter (Bio18), among which the importance of precipitation factors is greater than temperature factors. More importantly, the results of this study could provide some guidance for the improvement of desert forest system, the protection of endangered species and the further improvement of the ecological environment.

Yield Data Provide New Insight into the Dynamic Evaluation of Maize’s Climate Suitability: A Case Study in Jilin Province, China

Examining the effects of climate change on spring maize, and its suitability under dynamic cultivation patterns, will aid strategic decision-making for future agricultural adaptation. This paper investigates the climate suitability of spring maize, based on daily data from 50 meteorological stations, and statistics on maize yield and area at the county level in Jilin Province, China, between 1986 and 2015. Based on a significant correlation between the cultivation patterns indicator ≥10 °C accumulated temperature (AAT10) and the average yield (R2 = 0.503), the yield data are used to determine suitable thresholds for meteorological factors under the dynamic cultivation pattern, and a fuzzy fitness approach is used to evaluate the climate suitability. The results showed a good agreement between suitability estimates and scaled observed yields (average d = 0.705). Moreover, good consistency between cultivation patterns, climate suitability and yield show that the late-maturing varieties of maize have gradually moved northward and eastward, and the areas of high suitability and high yield have gradually expanded eastward. In addition, drought and chilling hazard factors limit the suitability of climate resources, especially in the eastern and western regions.