Minimum Temperature Of Coldest Month Research Articles

Predicting suitable distribution areas of Juniperus przewalskii in Qinghai Province under climate change scenarios.

Juniperus przewalskii is important for water and soil conservation. It is one of the native tree species suitable for afforestation and greening in high-cold and arid areas of Qinghai Province. Predicting the potential geographic distribution of J. przewalskii in Qinghai Province under the climate change scenario will provide theoretical guidance for its management, introduction, and cultivation. In this study, the current potential distribution of J. przewalskii was simulated firstly based on 88 effective distributional records from field investigation and data collection via Maxent model and ArcGIS spatial analysis. We analyzed dominant factors affecting the potential distribution of J. przewa-lskii by Jackknife test and correlation coefficient. The distribution of J. przewalskii under three climate change scenarios (SSP126, SSP245, SSP585) with the climate model data of the sixth phase of the Coupled Model Intercomparison Projects (CMIP6) were predicted for 2061-2080. The results showed that the area under the receiver operating characteristic curve (AUC) of the Maxent model was greater than 0.92, suggesting a good predictive performance. Under current climatic condition, the suitable distribution area of J. przewalskii was mainly located in the eastern part of Qinghai Province, with the suitable area accounted for 11.2% of the total. The dominant factors affecting the distribution of J. przewalskii were altitude, annual precipitation, the minimum temperature of coldest month, and slope, with a cumulative contribution rate of 85.9%. The suitable areas of J. przewalskii altered under the three future climate scenarios. The suitable areas would shrink under the SSP245 scenario and expand under the SSP126 and SSP585 scenarios. The sui-table area of J. przewalskii would have the most obvious expansion under the SSP126 climate situation, with the expanding areas being mainly located in Zeku County, the north-central part of Henan Mongolian Autonomous County, and the southeast of Qilian County. Under three climatic scenarios, the suitable area of J. przewalskii would gradually migrate to high altitudes, but without clear altitudinal and longitudinal shifts.

Climate warming will increase chances of hybridization and introgression between two Takydromus lizards (Lacertidae).

Coexisting species may experience population and range changes alone or jointly in response to environmental change. Here, we used six climate variables and ten modeling algorithms to predict the distribution of two Takydromus species (T. septentrionalis and T. sexlineatus) in China. We identified the sympatric and allopatric areas by comparing projections between the two species based on habitat suitability under present and future climate scenarios. We constructed the hypervolumes of six climate variables for the two species and then evaluated overlaps between hypervolumes. From this study, we know the following. First, minimum temperature of coldest month contributes the most to the prediction of habitat suitability. Second, habitats suitable for the two species will shift northward in response to climate warming. Third, the range of T. sexlineatus will expand across the four future time intervals before 2,100, namely the 2021–2040, 2041–2060, 2061–2080, and 2081–2100 intervals, under both Shared socioeconomic pathway (SSP) 245 and SSP585 scenarios, and the range of T. septentrionalis will also expand in the future except at the 2081–2100 interval under the SSP585 scenario. Fourth, the sympatric areas will contract or expand under the SSP245 scenario and expand across the four future time intervals before 2,100 under the SSP585 scenario. Fifth, the niche hypervolumes of the two species partially overlapped, and the differences in niche centroid show some degree of niche differentiation between the two species. These results allow to conclude that climate warming will not only drive the northward drift of sympatric areas but also increase the size of these areas if nothing is done to limit the emission of greenhouse gases. Given the existence of hybridization and introgression between T. septentrionalis and T. sexlineatus in the field where they coexist, we also conclude that climate warming will increase chances of hybridization and introgression between the two species.

Invasion of Lantana camara L. and its response to climate change in the mountains of Eastern Ghats

Biological invasion is one of the most sensitive modern–day research problems which has grabbed a lot of attention of several plant and animal scientists globally. Our study has addressed the current extent of habitat suitability of Lantana camara L. and its possible future expansion using MaxEnt model in three climatic years 2050, 2070 and 2080 under two representative concentration pathways (RCP 4.5 and 8.5) in Koraput district of Odisha. A total of seven environmental variables out of total of 23 including 19 bioclimatic, 03 topographic and 01 land cover change variable were taken as the predictors due to their lesser Variance Inflation Factors (VIF) scores to avoid multicollinearity. Slope and Minimum temperature of coldest month (MTCM) contributed the most towards the MaxEnt modelling process. The overall results predict drastic range expansion of Lantana camara L. with the trends 6902.28 km2 < 6996.90 km2 < 7020.97 km2 for RCP 4.5 and from 7001.88 km2 < 7247.56 km2 < 7304.00 km2 for RCP 8.5 between the intervals current–2050, current–2070 and current–2080 respectively. RCP 8.5 scenario showed more expansion compared to the RCP 4.5 scenario. This study is first of its kind in Eastern Ghats of India and as Koraput forests are a part of community managed forests, the invasion of the species can be controlled by involving the local communities in the practices of canopy cover increase, regular uprooting of the weed, decreasing the practice of shifting cultivation and not leaving the croplands barren in the dry period of the year.

Ecological niche modeling as an effective tool to predict the distribution of freshwater organisms: The case of the Sabaleta Brycon henni (Eigenmann, 1913).

Ecological niche models (ENMs) aim to recreate the relationships between species and the environments where they occur and allow us to identify unexplored areas in geography where these species might be present. These models have been successfully used in terrestrial organisms but their application in aquatic organisms is still scarce. Recent advances in the availability of species occurrences and environmental information particular to aquatic systems allow the evaluation of these models. This study aims to characterize the niche of the Sabaleta Brycon henni Eigenmann 1913, an endemic fish of the Colombian Andes, using ENMs to predict its geographical distribution across the Magdalena Basin. For this purpose, we used a set of environmental variables specific to freshwater systems in addition to the customary bioclimatic variables, and species' occurrence data to model its potential distribution using the Maximum Entropy algorithm (MaxEnt). We evaluate the relative importance between these two sets of variables, the model's performance, and its geographic overlap with the IUCN map. Both on-site (annual precipitation, minimum temperature of coldest month) and upstream variables (open waters, average minimum temperature of the coldest month and average precipitation seasonality) were included in the models with the highest predictive accuracy. With an area under the curve of 90%, 99% of the species occurrences and 68% of absences correctly predicted, our results support the good performance of ENMs to predict the potential distribution of the Sabaleta and the utility of this tool in conservation and decision-making at the national level.

Identifying the determinant habitat characteristics influencing the spatial distribution of Ferula ovina (Boiss.) in semiarid rangelands of Iran using machine learning methods

Ferula ovina (Boiss.) is a valuable but vulnerable monocarpic perennial forb species from Apiaceae plant family whose habitat has been degraded over the years; hence identifying the factors controlling its distribution is important to assist range managers for the reclamation activities. The specific objective of this study was to investigate the quantitative relationships between soil properties, topographical features, climate factors and F. ovina distribution in a semiarid part of central Iran and to assess the relative importance of these factors in controlling its spatial variability. To discern these complex relationships, artificial neural networks (ANNs), support vector machines (SVMs), and decision tree CHAID algorithm were employed. Results from the ANN, SVM, and CHAID models indicated that the climate and topographic conditions should be considered more in explaining the variability in F. ovina occurrence and distribution. Factors such as slope, precipitation of warmest month, and minimum temperature of coldest month were identified by the ANN, SVM, and CHAID models as the determinant factors influencing the spatial distribution of F. ovina in central Iran, respectively. Furthermore, CHAID approach showed greater potential in predicting the F. ovina occurrence in the study area. This study provides a strong basis for identifying the most determinant habitat characteristics of F. ovina and other vulnerable or endangered plant species in semiarid rangelands of Iran; however, its general analytical framework could be applied to other parts of the world with similar challenges.

Evaluating landscape characteristics of predicted hotspots for plant invasions

AbstractInvasive species are widely recognized as a major threat to global diversity and an important factor associated with global change. Species distribution models (SDMs) have been widely applied to determine the range that invasive species could potentially occupy, but most examples focus on predictive variables at a single spatial scale. In this study, we simultaneously considered a broad range of variables related to climate, topography, land cover, land use, and propagule pressure to predict what areas in the southeastern United States are more susceptible to invasion by 45 invasive terrestrial plant species. Using expert-verified occurrence points from EDDMapS, we modeled invasion susceptibility at 30-m resolution for each species using a maximum entropy (MaxEnt) modeling approach. We then analyzed how environmental predictors affected susceptibility to invasion at different spatial scales. Climatic and land-use variables, especially minimum temperature of coldest month and distance to developed areas, were good predictors of landscape susceptibility to invasion. For most of the species tested, human-disturbed systems such as developed areas and barren lands were more prone to be invaded than areas that experienced minimal human interference. As expected, we found that landscape heterogeneity and the presence of corridors for propagule dispersal significantly increased landscape susceptibility to invasion for most species. However, we also found a number of species for which the susceptibility to invasion increased in landscapes with large core areas and/or less-aggregated patches. These exceptions suggest that even though we found the expected general patterns for susceptibility to invasion among most species, the influence of landscape composition and configuration on invasion risk is species specific.

Shifts in potential geographical distribution of Pterocarya stenoptera under climate change scenarios in China.

Climate change poses a serious threat to biodiversity. Predicting the effects of climate change on the distribution of a species' habitat can help humans address the potential threats which may change the scope and distribution of species. Pterocarya stenoptera is a common fast‐growing tree species often used in the ecological restoration of riverbanks and alpine forests in central and eastern China. Until now, the characteristics of the distribution of this species' habitat are poorly known as are the environmental factors that influence its preferred habitat. In the present study, the Maximum Entropy Modeling (Maxent) algorithm and the Genetic Algorithm for Ruleset Production (GARP) were used to establish the models for the potential distribution of this species by selecting 236 sites with known occurrences and 14 environmental variables. The results indicate that both models have good predictive power. Minimum temperature of coldest month (Bio6), mean temperature of warmest quarter (Bio10), annual precipitation (Bio12), and precipitation of driest month (Bio14) were important environmental variables influencing the prediction of the Maxent model. According to the models, the temperate and subtropical regions of eastern China had high environmental suitability for this species, where the species had been recorded. Under each climate change scenario, climatic suitability of the existing range of this species increased, and its climatic niche expanded geographically to the north and higher elevation. GARP predicted a more conservative expansion. The projected spatial and temporal patterns of P. stenoptera can provide reference for the development of forest management and protection strategies.

Temperature Tolerance and Thermal Environment of European Seed Bugs.

Heteroptera, or true bugs populate many climate zones, coping with different environmental conditions. The aim of this study was the evaluation of their thermal limits and derived traits, as well as climatological parameters which might influence their distribution. We assessed the thermal limits (critical thermal maxima, CTmax, and minima, CTmin) of eight seed bug species (Lygaeidae, Pyrrhocoridae) distributed over four Köppen–Geiger climate classification types (KCC), approximately 6° of latitude, and four European countries (Austria, Italy, Croatia, Bulgaria). In test tubes, a temperature ramp was driven down to −5 °C for CTmin and up to 50 °C for CTmax (0.25 °C/min) until the bugs’ voluntary, coordinated movement stopped. In contrast to CTmin, CTmax depended significantly on KCC, species, and body mass. CTmax showed high correlation with bioclimatic parameters such as annual mean temperature and mean maximum temperature of warmest month (BIO5), as well as three parameters representing temperature variability. CTmin correlated with mean annual temperature, mean minimum temperature of coldest month (BIO6), and two parameters representing variability. Although the derived trait cold tolerance (TC = BIO6 − CTmin) depended on several bioclimatic variables, heat tolerance (TH = CTmax − BIO5) showed no correlation. Seed bugs seem to have potential for further range shifts in the face of global warming.

Could a new record change the range of distribution of a little - known bat species (Vespertilionidae: Eptesicus innoxius)?

We report the first record of Eptesicus innoxius in northwestern Ecuador, in the province of Esmeraldas, occurring in a disturbed area, at 134.3 km northwest from the nearest known locality in Ecuador, which represents an important latitudinal extension in the distribution of this species. A predictive distribution model is presented using a total of 43 records from localities of Ecuador and Peru, and its distribution area is determined by a minimum convex polygon (PMC). The sensitivity value obtained in the test data was 0.984 and the area under curve ROC (AUC) value obtained (0.979) indicates an acceptable confidence level. Based on new records and known records, we estimate its distribution area in 135,243 km2. The environmental variables with the greatest influence in the distribution of E. innoxius were: Precipitation seasonality (37.4 %), Minimum temperature of coldest month (20.1 %), Precipitation of driest month (14.5 %), and Mean temperature of wettest quarter (12.8 %). This data show that E. innoxius has been recorded mainly in tropical dry forest, but also has presence in humid areas. Within these new reports, we recommended an upgrade of its conservation status in Ecuador and Peru.

Potential distribution of two invasive pineapple pests under climate change.

The number of global invasive species has significantly increased during the past two centuries due to globalization. The understanding of species invasion under climate change is crucial for sustainable biodiversity conservation, community dynamics, ecosystem function, and resource distribution. Two invasive species, Dysmicoccus brevipes (Cockerell) and D. neobrevipes (Beardsley) have greatly expanded their ranges during recent years. These insects are now considered as extremely serious pests for various plants, especially pineapple. In addition, they are the primary vectors for pineapple wilt associated virus. However, the potential distribution range and management strategies for these pests are unclear. In this study, potential risk maps were developed for these pests with MaxEnt (maximum entropy) based on occurrence data under different environmental variables. The potential distributions of these pests were projected for 2050s and 2070s under three climate change scenarios as described in the Special Report on Emissions Scenarios of the Intergovernmental Panel on Climate Change. Results showed that both pests have similar potential distributions, with high environmental suitability in South America, Africa and South Asia. In addition, potential range expansions or reductions were predicted under different climate change scenarios. The annual mean temperature was the most important factor, accounting for 43.4% of D. brevipes distribution. The minimum temperature of coldest month and mean temperature of coldest quarter was found to be responsible for 90.3% of D. neobrevipes distribution. This research provided a theoretical reference framework to develop policies in the management and control of these invasive pests. © 2019 Society of Chemical Industry.

INVESTIGATION AND EVALUATION OF STONE PINE ( Pinus pinea L.) CURRENT AND FUTURE POTENTIAL DISTRIBUTION UNDER CLIMATE CHANGE IN TURKEY

ABSTRACT Climate change has negative effects on especially plant species that have a limited habitat. In this context, the stone pine (Pinus pinea L.), which has a limited distribution, is prominent with its economic, ecological and aesthetical characteristics, and it is frequently preferred in afforestation. In this study, the habitats in Turkey that are suitable for distribution of P. pinea L. were modelled by using Maxent based on high-resolution environmental data. In total, 13 field-based occurrence points and 19 bioclimatic variables were used to model the potential distribution area under current and two prediction model (RCP4.5 and RCP8.5) for the years 2050 and 2070. According to the results, the most important bioclimatic variables effective on the potential distribution of P. pinea L. were found as the minimum temperature of coldest month (Bio6), annual precipitation (Bio12) and precipitation of wettest quarter (Bio16). Prediction models under two future climate change scenarios displayed that P. pinea L. will lose habitat and it will shift geographical distribution towards north and higher elevation sites. Considering especially the economic contributions provided by P. pinea L., these results necessitate consideration of the areas where the rate of potential distribution of the species is the highest in afforestation work aiming rural development. In addition to habitat losses, climate change affects many variables of the ecosystem.

Potential distribution and suitability regionalization of kiwifruit canker disease in Sichuan Province, China

To detect the suitability of kiwifruit bacterial canker in Sichuan, a MaxEnt model based on distribution information and environmental variables was used to predict its potential distribution area and to analyze the impact of major environmental variables. The receiver operating characteristic curve was used to evaluate the accuracy of the model simulation. The average area under curve of 10 replicates was 0.914, which indicated that the predictive results were reliable. The highly sui-table distribution areas of kiwifruit bacterial canker were Chengdu, Deyang, Mianyang, Guangyuan, Bazhong, Dazhou, and Ya'an. All the 21 cities of Sichuan were classified as moderately suitable areas. The main environmental factors affecting the potential distribution of kiwifruit bacterial canker as determined by Jackknife method were minimum temperature of coldest month (-6.8-7.5 ℃), mean temperature of warmest Quarter (15.6-32.3 ℃), mean temperature of driest quarter (-0.8-21 ℃), annual precipitation (709-950.9 mm), and standard variation of temperature seasonality (4.7-9.6 ℃). Our results are impotant for early monitoring, early warning, and developing control measures for kiwifruit bacterial canker.

Bergmann\u2019s rule and Allen\u2019s rule in two passerine birds in China

BackgroundAnimals that live at higher latitudes/elevations would have a larger body size (Bergmann’s rule) and a smaller appendage size (Allen’s rule) for thermoregulatory reasons. According to the heat conservation hypothesis, large body size and small appendage size help animals retain heat in the cold, while small body size and large appendage size help them dissipate heat in the warm. For animals living in seasonal climates, the need for conserving heat in the winter may tradeoff with the need for dissipating heat in the summer. In this study, we tested Bergmann’s rule and Allen’s rule in two widely-distributed passerine birds, the Oriental Magpie (Pica serica) and the Oriental Tit (Parus minor), across geographic and climatic gradients in China.MethodsWe measured body size (body mass and wing length) and appendage size (bill length and tarsus length) of 165 Oriental Magpie and 410 Oriental Tit individuals collected from Chinese mainland. We used linear mixed-effect models to assess variation patterns of body size and appendage size along geographic and climatic gradients.ResultsOriental Magpies have a larger appendage size and Oriental Tits have a smaller body size in warmer environments. Appendage size in Oriental Magpies and body size in Oriental Tits of both sexes were more closely related to the climates in winter than in summer. Minimum temperature of coldest month is the most important factor related to bill length and tarsus length of male Oriental Magpies, and wing length of male and female Oriental Tits. Bill length and tarsus length in female Oriental Magpies were related to the annual mean temperature and mean temperature of coldest quarter, respectively.ConclusionsIn this study, Oriental Magpies and Oriental Tits followed Allen’s rule and Bergmann’ rule respectively. Temperatures in the winter, rather than temperatures in the summer, drove morphological measurements in Oriental Magpies and Oriental Tits in Chinese mainland, demonstrating that the morphological measurements reflect selection for heat conservation rather than for heat dissipation.

Environmental suitability for Aedes aegypti and Aedes albopictus and the spatial distribution of major arboviral infections in Mexico

BackgroundThis paper discusses a comparative geographic distribution of Aedes aegypti and Aedes albopictus mosquitoes in Mexico, using environmental suitability modeling and reported cases of arboviral infections. MethodsUsing presence-only records, we modeled mosquito niches to show how much they influenced the distribution of Ae. aegypti and Ae. albopictus based on mosquito records collected at the municipality level. Mosquito surveillance data were used to create models regarding the predicted suitability of Ae. albopictus and Ae. aegypti mosquitos in Mexico. ResultsAe. albopictus had relatively a better predictive performance (area under the curve, AUC = 0.87) to selected bioclimatic variables compared to Ae. aegypti (AUC = 0.81). Ae. aegypti were more suitable for areas with minimum temperature of coldest month (Bio6, permutation importance 28.7%) −6 °C to 21.5 °C, cumulative winter growing degree days (GDD) between 40 and 500, and precipitation of wettest month (Bio13) >8.4 mm. Minimum temperature range of the coldest month (Bio6) was −6.6 °C to 20.5 °C, and average precipitation of the wettest month (Bio13) 8.9 mm ~ 600 mm were more suitable for the existence of Ae. albopictus. However, arboviral infections maps prepared from the 2012–2016 surveillance data showed cases were reported far beyond predicted municipalities. ConclusionsThis study identified the urgent necessity to start surveillance in 925 additional municipalities that reported arbovirus infections but did not report Aedes mosquito.

Potential distribution and habitat connectivity of Crotalus triseriatus in Central Mexico

The dusky rattlesnake,Crotalustriseriatus, used to be very abundant in many parts of the highlands of central Mexico, but with the increasing human population and associated activities, the rattlesnake habitats and populations have suffered drastic reductions and fragmentation. At the moment, the most important habitat features, associated with the presence ofC.triseriatus, the current potential distribution and the landscape connectivity amongst the populations of the State of Mexico and Mexico City, are unknown. Therefore, we used the maximum entropy modelling software (MAXENT) to analyse the current potential distribution and most important habitat features, associated with the presence of the species. The variables with the highest contribution to the model were: proportion ofAbiesforest, minimum temperature of coldest month, maximum temperature of the warmest month, proportion ofPinusforest and annual precipitation. Furthermore, we found connectivity corridors only within mountain chains. Our results highlight the necessity for conserving the patches ofAbiesforest and preserving the populations ofC.triseriatusand the connectivity of the landscape.

Study of potential environmental factors predisposing ewes to subclinical mastitis in Greece.

Objectives of the work presented herewith were to investigate association of prevalence of subclinical mastitis with environmental (climatic and topographic) factors and to identify factors potentially predisposing ewes to the disease. Milk samples were collected from 2198 sheep in 111 farms, in all 13 administrative regions of Greece, for bacteriological and cytological examination. Data on farm location were collected in the field using hand-held Global Positioning System Garmin units. The geo-references were resolved to specific farm level. Prevalence of subclinical mastitis was 0.260. Main aetiological agents were staphylococci (Staphylococcus aureus and coagulase-negative species), which accounted for 0.699 of all isolates recovered. In a multivariable mixed-effects analysis, the two environmental variables found to be associated with increased prevalence of subclinical mastitis were the minimum temperature of coldest month (coefficient: -0.084 ± 0.033, P = 0.014) and the mean temperature for 30 days prior to sampling date (coefficient: 0.031±0.014, P = 0.029).

Predicting the impacts of climate change on the distribution of Juniperus excelsa M. Bieb. in the central and eastern Alborz Mountains, Iran

In recent years, global climate change has had significant biological, temporal, and spatial effects on many terrestrial habitats. The objective of this study was to evaluate the effect of climate change on the geographic distribution of Juniperus excelsa and prioritize its habitats for protection against these effects until 2070. The study was conducted using the MaxEnt species distribution model and two data series GFDL-CM3 and MRI-CGCM3 under scenarios RCP2.6 and RCP4.5 of the 5th IPCC report. Our results revealed that elevation, minimum temperature of coldest month, precipitation of coldest quarter, annual mean temperature, and slope aspect, in that order, have the greatest effects on the species’ distribution in the study area. Under optimistic scenario RCP2.6, both models predicted that the species’ presence area will grow, but under RCP4.5, models predicted that by 2070, some parts of its habitat in western and central heights will be lost because of change in climate parameters like minimum temperature of coldest month and precipitation of coldest quarter. Under the latter scenario, the northeastern parts of the study area showed no changes in terms of climatic parameters and climatic niche. The results of both climate data series indicated that the Juniperus excelsa will slowly migrate to higher elevations to cope with the changing climate. Assessment of the results through field studies showed that outputs of GFDL-CM3 are closer to the reality.

Influence of climate change on the suitable ranges for planting pickled mustard tuber in Chongqing.

Pickled mustard tuber (Brassica juncea var. tumida) belonging to Cruciferae, is a unique economic crop in China. Climate is an important factor affecting the distribution of pickled mustard tuber. Based on species presence data at 279 locations and 22 high-resolution environmental factor layers, we analyzed the potential planting area of pickled mustard tuber in Chongqing by MaxEnt model under the current conditions and the future distributions for the periods 2050s and 2070s under the climate change scenarios of RCP 2.6, RCP 4.5, RCP 6.0 and RCP 8.5 described in the Special Report on Emissions Scenarios (SRES) of IPCC (Intergovernmental Panel on Climate Change). The results showed that MaxEnt model was excellent in predicting its potential plan-ting area. The cumulative contributions of dominant factors reached as high as 81.7%, including precipitation of wettest month, temperature annual range, minimum temperature of coldest month, isothermality, mean diurnal range and average maximum temperature. The threshold of those factors was 173-183 mm, 27.2-28.3 ℃, 1.8-3.8 ℃, 22.5-24 ℃, 6.2-6.8 ℃ and 14.8-18.0 ℃, respectively. Under current condition, the optimum suitable areas of pickled mustard tuber, which amounted to 4.2%, were in the northeast, west and east of Fuling, the east and south of Changshou, the south and southeast of Dianjiang, the northwest and north of Fengdu, the southeast of Zhongxian, and a small part of Wulong and Nanchuan, while the proportion of moderately suitable areas was 6.3%. Under four climate change scenarios, the optimum suitable areas would drop to 2.7%, 3.8%, 3.1%, 3.2% and 3.1%, 3.7%, 3.5%, 2.9% for the periods 2050s and 2070s, respectively, while moderately suitable areas would rise gradually.

Predicting the potential distribution area of Solidago ×niederederi (Asteraceae)

In this study, we aimed to investigate the potential distribution area of Solidago xniederederi, a natural hybrid between North American S. canadensis and European S. virgaurea, in Central and East Europe using the MAXENT modeling approach. The final MAXENT model was constructed based on 83 occurrence records from Austria, Poland, Lithuania, and Latvia and six abiotic environmental variables. The jackknife test revealed that annual temperature range, mean temperature of wettest quarter, and minimum temperature of coldest month had the highest gain for the training and test data when used alone, whereas precipitation seasonality, precipitation of coldest quarter, and precipitation of warmest quarter reduced the gain the most when excluded from the model and thus contributed the most information not presented with the other variables. A high probability of occurrence (>0.6) for S. xniederederi was found in 12 countries, namely Austria, Belarus, the Czech Republic, Germany, Hungary, Italy, Lithuania, Poland, Russia (Kaliningrad Oblast), Slovenia, Slovakia, and Ukraine. Our results showed in which areas the hybrid may be established under the European temperate climatic conditions; however, we do not indicate which areas exactly may be under invasion by the hybrid because such a statement needs population dynamic data for proper investigation. To prevent the negative impact of S. xniederederi on native S. virgaurea (i.e. competition for pollinators and introgression) we suggest that it should be controlled first in areas of high probability of occurrence, especially in Lithuania, Kaliningrad Oblast, Slovakia, Poland, and Austria, where the areas of high probability of hybrid occurrence account for more than 5% of the territory concerned.

Predictive distribution and planting GAP of Cyathula officinalis in China based on 3S technology and MaxEnt modelling

Research on predictive distribution and planting GAP of Cyathula officinalis in China is helpful to provide scientific basis for its protection and planting popularization. According to the data in 63 distribution sites and 49 ecological variables, using MaxEnt ecological niche model and 3S technology, we performed a quantitative analysis of suitable distribution and planting GAP of C. officinalis in China. Our results show that: ① the area of suitable distribution of C. officinalis is about 634 385.80 km² in total, and mainly in Northeastern and Southeastern Sichuan, Northern and Southeastern Yunnan, Western and Southwestern Guizhou, Southwestern and Northeastern Chongqing, Southwestern Shaanxi, Southeastern Gansu, Western Guangxi, Southeastern Tibet. ② The main ecological factors determining the potential distribution are precipitation, altitude, minimum temperature of coldest month, soil type, monthly mean temperature. ③ The planting GAP region are mainly in Guangyuan, Mianyang, Ya'an, Leshan, Liangshan, Panzhihua of Sichuan province, Hanzhong of Shaanxi province, Dali, Nujiang, Chuxiong, Baoshan, Qujing, Wenshan of Yunnan province, southwestern autonomous prefecture in Guizhou province. The results are of great significance for realizing the growth environment, predicting the potential distribution and promoting planting popularization for C. officinalis.