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Climate change can significantly impact the ecological suitability and diversity of species. Pyrethrum tatsienense, a critically endangered species in China, requires a thorough understanding of its habitat distribution and the environmental factors that affect it in the context of climate change. The Maxent algorithm was used to examine the key factors influencing the distribution of P. tatsienense in China, using data from 127 species occurrences and environmental variables from the Last Interglacial (LIG), Last Glacial Maximum (LGM), Mid‐Holocene (MH), current, and future scenarios. The Maxent model was optimized utilizing the R package ENMeval, providing the most accurate predictions for suitable habitats across various scenarios. Results show that suitable regions for P. tatsienense encompass approximately 15.02% (14.42 × 105 km2) of China, predominantly on the Qinghai‐Tibetan Plateau. The mean UV‐B of the highest month (UVB3: 39.7%), elevation (elev: 28.7%), and the warmest season of precipitation (Bio18: 17.4%) are the major limiting factors for suitable habitat. The optimal species distribution ranges are identified as > 7500 J m−2 day−1 for UVB3, 2700–5600 m for elev, and 150–480 mm for Bio18. Predictions for the historical climate indicate the presence of refugia at the junction of Sichuan, Tibet, and Qinghai. The MH predictions show an increase in climatic suitability for P. tatsienense compared to the LIG and LGM, with an expansion of suitable areas westward. Future climate change scenarios indicate that the potential suitable habitat for P. tatsienense is expected to increase with increasing radiative forcing, with higher latitude regions becoming new marginally suitable habitats. However, predicted environmental changes in western Tibet may drive the loss of highly suitable habitats in the future. These findings enhance our understanding of how environmental factors impact the habitat suitability of P. tatsienense and provide valuable insights for developing effective management and conservation strategies for this important species. [ABSTRACT FROM AUTHOR]

ABSTRACT Climate change can significantly impact the ecological suitability and diversity of species. Pyrethrum tatsienense, a critically endangered species in China, requires a thorough understanding of its habitat distribution and the environmental factors that affect it in the context of climate change. The Maxent algorithm was used to examine the key factors influencing the distribution of P. tatsienense in China, using data from 127 species occurrences and environmental variables from the Last Interglacial (LIG), Last Glacial Maximum (LGM), Mid‐Holocene (MH), current, and future scenarios. The Maxent model was optimized utilizing the R package ENMeval, providing the most accurate predictions for suitable habitats across various scenarios. Results show that suitable regions for P. tatsienense encompass approximately 15.02% (14.42 × 105 km2) of China, predominantly on the Qinghai‐Tibetan Plateau. The mean UV‐B of the highest month (UVB3: 39.7%), elevation (elev: 28.7%), and the warmest season of precipitation (Bio18: 17.4%) are the major limiting factors for suitable habitat. The optimal species distribution ranges are identified as > 7500 J m−2 day−1 for UVB3, 2700–5600 m for elev, and 150–480 mm for Bio18. Predictions for the historical climate indicate the presence of refugia at the junction of Sichuan, Tibet, and Qinghai. The MH predictions show an increase in climatic suitability for P. tatsienense compared to the LIG and LGM, with an expansion of suitable areas westward. Future climate change scenarios indicate that the potential suitable habitat for P. tatsienense is expected to increase with increasing radiative forcing, with higher latitude regions becoming new marginally suitable habitats. However, predicted environmental changes in western Tibet may drive the loss of highly suitable habitats in the future. These findings enhance our understanding of how environmental factors impact the habitat suitability of P. tatsienense and provide valuable insights for developing effective management and conservation strategies for this important species.

Liriodendron chinense (Hemsl.) Sarg. (Magnoliales: Magnoliaceae), valued for its medicinal properties and timber and as an ornamental plant, is now classified as an endangered species. Investigating how future climate-change scenarios might affect the potential geographic distribution of L. chinense will provide a crucial scientific basis for its protection and management strategies. The MaxEnt model was calibrated using the ENMeval optimization package, and then it was coupled with ArcGIS 10.8 to forecast the possible distribution areas of L. chinense in China, utilizing elevation data, bioclimatic factors, and human footprint as environmental variables. The results indicate: (1) The optimal model parameters were set as follows: FC = LQ, RM = 0.5, the MaxEnt model demonstrated high predictive accuracy and minimal overfitting; (2) The total suitable habitat area for the potential geographical distribution of L. chinense during the current period is estimated at 151.55 × 104 km2, predominantly located in central, eastern, and southwestern regions of China; (3) The minimum temperature of the coldest month (bio6), precipitation of the driest month (bio14), precipitation of the driest quarter (bio17), precipitation of the warmest quarter (bio18), elevation (alt), and human footprint (hf) are the main environmental variables determining the suitable habitat distribution of L. chinense; (4) During the period from 2041 to 2060, under the carbon emission scenarios of SSP126, SSP245, and SSP370, the suitable habitat for L. chinense shows varying degrees of increase compared to the current period. However, under the highest concentration scenario of SSP585, the suitable habitat area decreases to some extent; (5) The distribution of L. chinense is likely to move towards higher latitudes and elevations in the future due to changes in the climate. This research provides a comprehensive analysis of the potential impacts of climate change on L. chinense, offering valuable information for its protection and management under future climatic conditions. [ABSTRACT FROM AUTHOR]

Simple Summary: Exploring species' potential suitable habitats is crucial for endangered species conservation, in particular under future global climate change conditions. The Wushan salamander (Liua shihi) is an endangered salamander in China, which is a national protected species (level II). Based on the distribution records of L. shihi, the main objective of this study was to predict the distribution of suitable habitats under current and future climate conditions for L. shihi. Our results showed that precipitation, cloud density, vegetation type, and ultraviolet radiation were the main environmental factors affecting the distribution of suitable habitat for L. shihi. At present, the suitable habitats are mainly distributed in the Daba Mountain area. Under the future climate conditions, the area of suitable habitats increased, which mainly occurred in central Guizhou Province. These findings provided important information for the conservation of L. shihi. Climate change has been considered to pose critical threats for wildlife. During the past decade, species distribution models were widely used to assess the effects of climate change on the distribution of species' suitable habitats. Among all the vertebrates, amphibians are most vulnerable to climate change. This is especially true for salamanders, which possess some specific traits such as cutaneous respiration and low vagility. The Wushan salamander (Liua shihi) is a threatened and protected salamander in China, with its wild population decreasing continuously. The main objective of this study was to predict the distribution of suitable habitat for L. shihi using the ENMeval parameter-optimized MaxEnt model under current and future climate conditions. Our results showed that precipitation, cloud density, vegetation type, and ultraviolet radiation were the main environmental factors affecting the distribution of L. shihi. Currently, the suitable habitats for L. shihi are mainly concentrated in the Daba Mountains, including northeastern Chongqing and western Hubei Provinces. Under the future climate conditions, the area of suitable habitats increased, which mainly occurred in central Guizhou Province. This study provided important information for the conservation of L. shihi. Future studies can incorporate more species distribution models to better understand the effects of climate change on the distribution of L. shihi. [ABSTRACT FROM AUTHOR]

Simple Summary: Trachycarpus nanus is a national, second-class, rare and endangered plant in China, and a plant species endemic to Yunnan. This species has a high medicinal, ecological, and scientific value, but it is currently on the verge of extinction. Therefore, it is urgent to learn its extinction risk under global warming. We predict its multi-temporal distribution pattern based on the optimized MaxEnt model. The results show that precipitation is the most important factor. In the future, drastic climatic changes and human disturbances may lead to the extinction of this species, so it is necessary to strengthen the protection of this species using specific strategies. Climate change affects the geographical distribution of plant species. Rare Trachycarpus nanus with a narrow distribution range, high medicinal value and extremely small population is facing increasing extinction risks under global climate change. In this study, 96 recorded occurrences and 23 environmental factors are used to predict the potential suitable area of T. nanus based on the optimized MaxEnt (3.4.4) model and ArcGIS (10.7) software. The results show that when the parameters are FC = LQ and RM = 1, the MaxEnt model is optimal and AUC = 0.946. The distribution patterns were predicted in the past, present, and four future phases, i.e., 2021–2040 (2030), 2041–2060 (2050), 2061–2080 (2070), and 2081–2100 (2090). The main factors are the annual precipitation (bio12), mean temperature of the coldest quarter (bio11), temperature seasonality (bio4), precipitation of the wettest quarter (bio16), and isothermality (bio3). The potential distribution of T. nanus is primarily concentrated in central Chuxiong, encompassing a total potential suitable area of 5.65 × 104 km2. In historical periods, the total habitat area is smaller than that in the present. In the future, the potential suitable area is generally increased. The centroid analysis shows that T. nanus will move to a high-altitude area and to the southeast. But its dispersal capacity may not keep up with the climate change rate. Therefore, additional protection sites for this species should be appropriately established and the habitat connectivity should be enhanced. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Leonurus japonicus Houtt. is a traditional Chinese medicinal plant with high medicinal and edible value. Wild L. japonicus resources have reduced dramatically in recent years. This study predicted the response of distribution range of L. japonicus to climate change in China, which provided scientific basis for the conservation and utilization. In this study, 489 occurrence points of L. japonicus were selected based on GIS technology and spThin package. The default parameters of MaxEnt model were adjusted by using ENMeva1 package of R environment, and the optimized MaxEnt model was used to analyze the distribution of L. japonicus. When the feature combination in the model parameters is hing and the regularization multiplier is 1.5, the MaxEnt model has a higher degree of optimization. With the AUC of 0.830, our model showed a good predictive performance. The results showed that L. japonicus were widely distributed in the current period. The maximum temperature of warmest month, the min temperature of coldest month, the precipitation of wettest month, the precipitation of driest month, and altitude were the main environmental factors affecting the distribution of L. japonicus. Under the three climate change scenarios, the suitable distribution area of L. japonicus will range shift to high latitudes, indicating that the distribution of L. japonicus has a strong response to climate change. The regional change rate is the lowest under the SSP126‐2090s scenario and the highest under the SSP585‐2090s scenario. [ABSTRACT FROM AUTHOR]

Climate change has been considered to pose critical threats for wildlife. During the past decade, species distribution models were widely used to assess the effects of climate change on the distribution of species’ suitable habitats. Among all the vertebrates, amphibians are most vulnerable to climate change. This is especially true for salamanders, which possess some specific traits such as cutaneous respiration and low vagility. The Wushan salamander (Liua shihi) is a threatened and protected salamander in China, with its wild population decreasing continuously. The main objective of this study was to predict the distribution of suitable habitat for L. shihi using the ENMeval parameter-optimized MaxEnt model under current and future climate conditions. Our results showed that precipitation, cloud density, vegetation type, and ultraviolet radiation were the main environmental factors affecting the distribution of L. shihi. Currently, the suitable habitats for L. shihi are mainly concentrated in the Daba Mountains, including northeastern Chongqing and western Hubei Provinces. Under the future climate conditions, the area of suitable habitats increased, which mainly occurred in central Guizhou Province. This study provided important information for the conservation of L. shihi. Future studies can incorporate more species distribution models to better understand the effects of climate change on the distribution of L. shihi.

Climate change affects the geographical distribution of plant species. Rare Trachycarpus nanus with a narrow distribution range, high medicinal value and extremely small population is facing increasing extinction risks under global climate change. In this study, 96 recorded occurrences and 23 environmental factors are used to predict the potential suitable area of T. nanus based on the optimized MaxEnt (3.4.4) model and ArcGIS (10.7) software. The results show that when the parameters are FC = LQ and RM = 1, the MaxEnt model is optimal and AUC = 0.946. The distribution patterns were predicted in the past, present, and four future phases, i.e., 2021–2040 (2030), 2041–2060 (2050), 2061–2080 (2070), and 2081–2100 (2090). The main factors are the annual precipitation (bio12), mean temperature of the coldest quarter (bio11), temperature seasonality (bio4), precipitation of the wettest quarter (bio16), and isothermality (bio3). The potential distribution of T. nanus is primarily concentrated in central Chuxiong, encompassing a total potential suitable area of 5.65 × 104 km2. In historical periods, the total habitat area is smaller than that in the present. In the future, the potential suitable area is generally increased. The centroid analysis shows that T. nanus will move to a high-altitude area and to the southeast. But its dispersal capacity may not keep up with the climate change rate. Therefore, additional protection sites for this species should be appropriately established and the habitat connectivity should be enhanced.

Abstract Leonurus japonicus Houtt. is a traditional Chinese medicinal plant with high medicinal and edible value. Wild L. japonicus resources have reduced dramatically in recent years. This study predicted the response of distribution range of L. japonicus to climate change in China, which provided scientific basis for the conservation and utilization. In this study, 489 occurrence points of L. japonicus were selected based on GIS technology and spThin package. The default parameters of MaxEnt model were adjusted by using ENMeva1 package of R environment, and the optimized MaxEnt model was used to analyze the distribution of L. japonicus. When the feature combination in the model parameters is hing and the regularization multiplier is 1.5, the MaxEnt model has a higher degree of optimization. With the AUC of 0.830, our model showed a good predictive performance. The results showed that L. japonicus were widely distributed in the current period. The maximum temperature of warmest month, the min temperature of coldest month, the precipitation of wettest month, the precipitation of driest month, and altitude were the main environmental factors affecting the distribution of L. japonicus. Under the three climate change scenarios, the suitable distribution area of L. japonicus will range shift to high latitudes, indicating that the distribution of L. japonicus has a strong response to climate change. The regional change rate is the lowest under the SSP126‐2090s scenario and the highest under the SSP585‐2090s scenario.

Predicting the spatial distribution of species in relation to suitable areas under global climate change could provide some references for conservation and long-term management strategies for the species. In this study, the MaxEnt was optimized by adjusting the feature combination and regulation magnification parameters with the ENMeval data package. Based on 127 Cremastra appendiculata spatial distribution locations and 14 environmental factors, the potential distribution areas of C. appendiculata under the present and future climate conditions (2050s, 2070s) were simulated, and the dominant environmental factors influencing the spatial distribution of C. appendiculata were analyzed. The feature combination (FC) and the regularization multiplier (RM) were selected as per the Akaike information criterion (AIC). The model showed complexity and degree of over-fitting (delta AICc = 0, omission rate = 0.106, the difference in the curve values between the training and testing areas was 0.021) after establishing the optimal model (FC = LQH and RM = 2.5), and the results indicated that the optimal model performed well in simulating the potential spatial distribution of C. appendiculata (the area under the receiver operating characteristic curve = 0.933). The results showed that the suitable habitat of C. appendiculata currently in China is 187.60 × 104 km2, while the highly suitable habitat is 118.47 × 104 km2, the moderately suitable habitat is 53.25 × 10 4 km2, and the poorly suitable habitat is 15.88 × 104 km2. There is an increasing trend in the suitable habitat of C. appendiculata under six climate scenarios, including SSP1-2.6, SSP2-4.5, and SSP5-8.5 in the 2050s and the 2070s, and that habitat will extend to the northwest as a whole. The highly suitable habitat of C. appendiculata in nature reserves is 0.47 × 104 km2; consequently, there is a large gap in the protection of C. appendiculata. The distribution of C. appendiculata was influenced by the temperature, precipitation, and normalized vegetation index.

Mineral licks are faunal attractors, whose distribution determines the structure and composition of Amazonian landscapes and the way they are used by wildlife and traditional communities. Research on the distribution of mineral licks is scarce, limiting the possibility of using them in conservation beyond local scales. Using the species distribution modeling framework, we predicted the distribution of suitable conditions for mineral licks in the Northwest Amazon, compiling localities from academic and traditional sources and using environmental variables associated with geology, geomorphology, edaphology, topography, and hydrology. Best models, selected according to evaluation metrics incorporated in the ENMeval "R" package, showed to be robust and predict sectors with different areas, but similar distributions. Suitable areas covered up to 14.6% of the study area and confirmed the association of mineral licks with the drainage system. The erosive capacities of the rivers and their roles in terms of sediment deposition allowed the generation of ideal conditions for the expression of mineral licks in past and present riparian zones. Closeness to salt deposits and the seacoast was also important, giving information about the underground and aboveground mineral availability, crucial aspects for mineral lick formation. Considering the extension and distribution of our predictions, we proposed its use as input for other spatial modeling exercises, for example, as part of a complex resistance matrix to evaluate ecological connectivity or as criteria to prioritize sectors for restoration in the Colombian Amazon, where it is imperative to consolidate functional networks to prevent isolation between the Amazon and Andes regions. [ABSTRACT FROM AUTHOR]

Ziziphus jujuba has high ecological and economic value and is widely distributed in northern China. Reconstructing the historical geographic distribution patterns of Z. jujuba and determining the environmental distribution restrictions could provide a scientific basis for its germplasm conservation and management. Here, the R packages ENMeval and Biomod2 were used assess to 121 distribution records and 18 environmental variables and model and analyze the geographic distribution changes of Z. jujuba in different periods since the last interglacial period. Environmental anomalies and factors underlying the geographical distribution changes and migration trends in distribution areas under climate change were assessed. The optimized MaxEnt model generated the best predictions, and the modern highly suitable area was located in the Yellow and Haihe river basins. Climate anomalies in the historical periods ranged in decreasing order from the last interglacial > last glacial maximum > middle Holocene. The degree of climate anomalies under RCP (Representative Concentration Pathways) 2.6-2050s was the lowest, and the degree of climate anomalies under RCP8.5-2070s was the highest. From the last interglacial period to the 2070s, the most dissimilar variable was initially precipitation but gradually changed to temperature with climate change, which was the key factor for the geographical distribution of Z. jujuba. Although extensive habitat expansion occurred during the last interglacial period, the area suitable for Z. jujuba retreated to higher latitudes during the last glacial maximum and middle Holocene. As climate warming intensifies, suitable habitats will shift to higher latitudes while habitats in lower latitudes will become scarcer. The whole suitable region in China will migrate to a higher latitude area, indicating that the Z. jujuba distribution shows a strong response to climate change. This study provides a theoretical basis for establishing conservation measures for Z. jujuba genetic resources and studying trends in plant formation and evolution in North China.

Aim: Species distribution models (SDMs) are valuable for rare species conservation and are commonly used to extrapolate predictions of habitat suitability geographically to regions where species occurrence is unknown (i.e., transferability). Spatially structured cross‐validation can be used to infer transferability, yet, few studies have evaluated how delineation of cross‐validation folds affects model complexity and predictions. We developed SDMs using multiple cross‐validation approaches to understand the implications for predicting habitat suitability for northern Idaho ground squirrels, a rare, federally threatened species that has been extensively surveyed in regions where known populations occur, resulting in >8000 presence locations. Location: Idaho, USA. Methods: We delineated cross‐validation folds by mimicking the manner in which predictions would be geographically extrapolated or by using existing dispersal barriers. We varied the distance between, number, and directionality of folds. We conducted a grid search on statistical regularization parameters to optimize model complexity, covering a range of values exceeding that typically implemented. For each cross‐validation approach, we selected optimal regularization and model complexity based on out‐of‐sample predictive ability. Results: Delineation of cross‐validation folds substantially affected resulting model complexity and extrapolated predictions. All cross‐validation approaches resulted in models with apparently high out‐of‐sample predictive ability, yet optimal model complexity varied substantially among the approaches. Regularization demonstrated a noisy relationship between model complexity and prediction, where local optima in predictive performance were common at small values. Main conclusion: Subtle modelling decisions can have large consequences for predictions of habitat suitability and transferability of SDMs. When transferability is the goal, cross‐validation approaches should be considered carefully and mimic the manner in which spatial extrapolation will occur, else overly complex models with inflated assessments of predictive accuracy may result. Further, spatially structured cross‐validation may not guard against over‐parameterization, and assessing a broader range of regularization parameters may be necessary to optimize model complexity for transferability. [ABSTRACT FROM AUTHOR]

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., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2024 Wang, Wu, Zhao, Xie, Li, Zhao and Zhang.)

Since 1998, Nipah virus (NiV) (genus: Henipavirus; family: Paramyxoviridae), an often-fatal and highly virulent zoonotic pathogen, has caused sporadic outbreak events. Fruit bats from the genus Pteropus are the wildlife reservoirs and have a broad distribution throughout South and Southeast Asia, and East Africa. Understanding the disease biogeography of NiV is critical to comprehending the potential geographic distribution of this dangerous zoonosis. This study implemented the R packages ENMeval and BIOMOD2 as a means of modeling regional disease transmission risk and additionally measured niche similarity between the reservoir Pteropus and the ecological characteristics of outbreak localities with the Schoener’s D index and I statistic. Results indicate a relatively high degree of niche overlap between models in geographic and environmental space (D statistic, 0.64; and I statistic, 0.89), and a potential geographic distribution encompassing 19% (2,963,178 km2) of South and Southeast Asia. This study should contribute to current and future efforts to understand the critical ecological contributors and geography of NiV. Furthermore, this study can be used as a geospatial guide to identify areas of high disease transmission risk and to inform national public health surveillance programs.

• · Biomod2 and MaxEnt models was tested, and the predictions of the two models were compared. • · The optimized model was used to predict and analyze the potential suitable habitat for Z. jujuba. • · Reconstruct the history of changes in the geographical distribution pattern of Z. jujuba. • · Establish a theoretical foundation for studies on the evolution of North China flora. Ziziphus jujuba has high ecological and economic value and is widely distributed in northern China. Reconstructing the historical geographic distribution patterns of Z. jujuba and determining the environmental distribution restrictions could provide a scientific basis for its germplasm conservation and management. Here, the R packages ENMeval and Biomod2 were used assess to 121 distribution records and 18 environmental variables and model and analyze the geographic distribution changes of Z. jujuba in different periods since the last interglacial period. Environmental anomalies and factors underlying the geographical distribution changes and migration trends in distribution areas under climate change were assessed. The optimized MaxEnt model generated the best predictions, and the modern highly suitable area was located in the Yellow and Haihe river basins. Climate anomalies in the historical periods ranged in decreasing order from the last interglacial > last glacial maximum > middle Holocene. The degree of climate anomalies under RCP (Representative Concentration Pathways) 2.6-2050s was the lowest, and the degree of climate anomalies under RCP8.5-2070s was the highest. From the last interglacial period to the 2070s, the most dissimilar variable was initially precipitation but gradually changed to temperature with climate change, which was the key factor for the geographical distribution of Z. jujuba. Although extensive habitat expansion occurred during the last interglacial period, the area suitable for Z. jujuba retreated to higher latitudes during the last glacial maximum and middle Holocene. As climate warming intensifies, suitable habitats will shift to higher latitudes while habitats in lower latitudes will become scarcer. The whole suitable region in China will migrate to a higher latitude area, indicating that the Z. jujuba distribution shows a strong response to climate change. This study provides a theoretical basis for establishing conservation measures for Z. jujuba genetic resources and studying trends in plant formation and evolution in North China. [ABSTRACT FROM AUTHOR]

The continuous global climate change has affected the living habits, morphological characteristics and spatial distribution of tree species. Chinese fir (C. lanceolata (Lamb.) Hook) is one of the most important conifer tree species in China, which plays a major role in terms of timber supplies and environment protection. Predict the potential suitable habitats of Chinese fir under different climatic scenarios, can not only provide scientific theoretical basis for the planning and planting of Chinese fir, but also have great significance for maintaining the stability of the plantation ecosystem. Here, we used the maximum entropy (Maxent) model which optimized by the ENMeval package, to predicted the potential suitable habitats for Chinese fir under current climatic conditions and two climatic scenarios in 2070s. Our results showed that the complexity of the model was relative low, when the regularization multiplier (RM) was 0.5 and feature combination (FC) was linear (L) and quadratic (Q). Under this parameter setting, the high and moderate suitable habitat area of Chinese fir were 83.90 × 104 km2 and 97.62 × 104 km2, respectively, which suggested we can carry out Chinese fir planting activities with different cultivation purposes. The minimum temperature of the coldest month, annual precipitation, annual mean temperature and mean temperature of warmest quarter were identified as the essential factors shaping habitat suitability for Chinese fir. Under future climate scenarios, the high suitable habitat was reduced and the degree of fragmentation was increased, and the total potential suitable habitat of Chinese fir had the tendency to migrate to high-altitude regions. Managers should be cautious about the cultivation area selection of Chinese fir plantation as the potential suitable habitat changed under the global climate change continuously. It is therefore imperative to adjust the long-term management and protection strategy of Chinese fir plantation. • Maxent was used to predicted the potential habitat of Chinese fir. • R package ENMeval was used to optimized the Maxent model. • Potential habitat of Chinese fir were concentrated in subtropical regions. • Potential habitat had a tendency to migrate to high-altitude regions. • Temperature and precipitation were main factors affecting potential distribution. [ABSTRACT FROM AUTHOR]

Actinidia arguta (Siebold and Zucc.) Planch.ex Miq, called "hardy kiwifruit", "baby kiwi" or "kiwi berry", has a unique taste, is rich in nutrients and has high economic value and broad market prospects. Active research on the potential geographic distribution of A. arguta in China aims to provide a reference basis for its resource investigation, conservation, development and utilization and introduction of cultivation. In this study, the Maxent model was used to combine climatic factors, soil factors and geographical factors (elevation, slope and aspect) to predict the current and future (2041–2060 and 2081–2100) potential distribution of A. arguta and to analyze the impact of climate change on it. The results showed that the suitable distribution range of A. arguta in China was 23–43 N and 100–125 E, with a total area of about 3.4451 × 106 km2. The highly suitable area of A. arguta was mainly concentrated in the middle and low mountain areas of the south of Shaanxi, the east of Sichuan, the middle and west of Guizhou and the west of Yunnan, presenting a circular distribution. The Jackknife test was used to calculate the main environmental factors affecting the distribution of A. arguta. The first four main factors were annual mean temperature (bio_1), precipitation of the warmest quarter (bio_18), elevation (ELE) and mean temperature of the warmest quarter (bio_10), which provided a contribution up to 81.7%. Under the scenarios of three representative concentrations (SSP1_2.6, SSP2_4.5 and SSP5_8.5) in the future, the area of low and moderate suitable habitat decreased, while the area of highly suitable habitat increased. The migration direction of the centroid in the highly suitable habitat moved to the southwest in the future scenario period. [ABSTRACT FROM AUTHOR]

Semiliquidambar cathayensis is a special and endangered plant in China, used for traditional Chinese medicine and in landscape applications. Predicting the impact of climate change on the distribution of S. cathayensis is crucial for its protection and the sustainable use of resources. We used the maximum entropy (MaxEnt) model optimized by the ENMeval data packet to analyze the potential geographic distribution changes of S. cathayensis in 12 provinces of Southern China for the different periods since the last interglacial period (LIG, 120–140 ka). Considering the potential geographic distribution changes in the province, and based on the two climate scenarios of Representative Concentration Pathways (RCP) 2.6 and RCP 8.5, the distribution range of S. cathayensis was analyzed and we predicted the range for the 2050s (average for 2041–2060) and 2070s (average for 2061–2080). The area under AUC (Area under the receiver operating characteristic (ROC) curve) is 0.9388 under these parameters, which indicates that the model is very accurate. We speculate that the glacial period refugia were the Nanling and Wuyi Mountains for S. cathayensis, and central and Western Fujian and Taiwan are likely to be the future climate refugia. In the mid-Holocene (MH, 6 ka), the growth habitat was 32.41% larger than the modern habitat; in the 2050s and 2070s (except RCP2.6–2070s), the growth habitat will shrink to varying degrees, so efforts to support its in situ and ex situ conservation are urgently needed. The jackknife test showed that the main factors affecting the geographical distribution of S. cathayensis were annual precipitation, precipitation of the wettest month, and precipitation of the driest month. The annual precipitation may be the key factor restricting the northward distribution of S. cathayensis. In general, the centroid of the distribution of S. cathayensis will move northward. The centroid of the adaptive habitats will move northward with the highest degree of climate abnormality. We think that Hainan Island is the most likely origin of S. cathayensis. These findings provide a theoretical basis for the establishment of genetic resources protection measures, the construction of core germplasm resources, and the study of the formation and evolution of Hamamelidaceae. [ABSTRACT FROM AUTHOR]

Since 1998, Nipah virus (NiV) (genus: Henipavirus ; family: Paramyxoviridae), an often-fatal and highly virulent zoonotic pathogen, has caused sporadic outbreak events. Fruit bats from the genus Pteropus are the wildlife reservoirs and have a broad distribution throughout South and Southeast Asia, and East Africa. Understanding the disease biogeography of NiV is critical to comprehending the potential geographic distribution of this dangerous zoonosis. This study implemented the R packages ENMeval and BIOMOD2 as a means of modeling regional disease transmission risk and additionally measured niche similarity between the reservoir Pteropus and the ecological characteristics of outbreak localities with the Schoener's D index and I statistic. Results indicate a relatively high degree of niche overlap between models in geographic and environmental space (D statistic, 0.64; and I statistic, 0.89), and a potential geographic distribution encompassing 19% (2,963,178 km²) of South and Southeast Asia. This study should contribute to current and future efforts to understand the critical ecological contributors and geography of NiV. Furthermore, this study can be used as a geospatial guide to identify areas of high disease transmission risk and to inform national public health surveillance programs.