Modelling the spatial distribution of snake species in northwestern Tunisia using maximum entropy(Maxent) and Geographic Information System(GIS)

We used GIS and maximum entropy to predict the potential distribution of six snake species belong to three families in Kroumiria（Northwestern Tunisia）： Natricidae（Natrix maura and Natrix astreptophora）, Colubridae（Hemorrhois hippocrepis, Coronella girondica and Macroprotodon mauritanicus）, and Lamprophiidae（Malpolon insignitus）. The suitable habitat for each species was modelled using the maximum entropy algorithm, combining presence field data（collected during 16 years：2000–2015） with a set of seven environmental variables（mean annual precipitation, elevation, slope gradient,aspect, distance to watercourses, land surface temperature and normalized Differential Vegetation Index. The relative importance of these environmental variables was evaluated by jackknife tests and the predictive power of our models was assessed using the area under the receiver operating characteristic. The main explicative variables of the species distribution were distance from streams and elevation, with contributions ranging from 60 to 77 and from 10 to 25%,respectively. Our study provided the first habitat suitability models for snakes in Kroumiria and this information can be used by conservation biologists and land managers concerned with preserving snakes in Kroumiria.

Trends in species distribution modelling in context of rare and endemic plants:a systematic review

Background:Many research papers have utilized Species Distribution Models to estimate a species’current and future geographic distribution and environmental niche.This study aims to(a)understand critical features of SDMs used to model endemic and rare species and(b)to identify possible constraints with the collected data.The present systematic review examined how SDMs are used on endemic and rare plant species to identify optimal practices for future research.Results:The evaluated literature(79 articles)was published between January 2010 and December 2020.The number of papers grew considerably over time.The studies were primarily conducted in Asia(41%),Europe(24%),and Africa(2%).The bulk of the research evaluated(38%)focused on theoretical ecology,climate change impacts(19%),and conservation policy and planning(22%).Most of the papers were published in publications devoted to biodiversity conservation,ecological or multidisciplinary fields.The degree of uncertainty was not disclosed in most studies(81%).Conclusion:This systematic review provides a broad overview of the emerging trends and gaps in the SDMs research.The majority of studies failed to present uncertainties and error estimates.However,when model performance estimates are given,the model results will be highly effective,allowing for more assurance in the predictions they make.Furthermore,based on our systematic review,we recommend that in the future rare and endemic SDMs should represent uncertainty levels and estimates of errors in the modelling process.

Species Distribution Modelling performance and its implication for Sentinel-2-based prediction of invasive Prosopis juliflora in lower Awash River basin, Ethiopia

Background:Species Distribution Modelling(SDM)coupled with freely available multispectral imagery from Sentinel-2(S2)satellite provides an immense contribution in monitoring invasive species.However,attempts to evaluate the performances of SDMs using S2 spectral bands and S2 Radiometric Indices(S2-RIs)and biophysical variables,in particular,were limited.Hence,this study aimed at evaluating the performance of six commonly used SDMs and one ensemble model for S2-based variables in modelling the current distribution of Prosopis juliflora in the lower Awash River basin,Ethiopia.Thirty-five variables were computed from Sentinel-2B level-2A,and out of the variables,twelve significant variables were selected using Variable Inflation Factor(VIF).A total of 680 presence and absence data were collected to train and validate variables using the tenfold bootstrap replication approach in the R software“sdm”package.The performance of the models was evaluated using sensitivity,specificity,True Skill Statistics(TSS),kappa coefficient,area under the curve(AUC),and correlation.Results:Our findings demonstrated that except bioclim all machine learning and regression models provided successful prediction.Among the tested models,Random Forest(RF)performed better with 93%TSS and 99%AUC followed by Boosted Regression Trees(BRT),ensemble,Generalized Additive Model(GAM),Support Vector Machine(SVM),and Generalized Linear Model(GLM)in decreasing order.The relative influence of vegetation indices was the highest followed by soil indices,biophysical variables,and water indices in decreasing order.According to RF prediction,16.14%(1553.5 km^(2))of the study area was invaded by the alien species.Conclusions:Our results highlighted that S2-RIs and biophysical variables combined with machine learning and regression models have a higher capacity to model invasive species distribution.Besides,the use of machine learning algorithms such as RF algorithm is highly essential for remote sensing-based invasive SDM.

Applying various algorithms for species distribution modelling

Species distribution models have been used extensively in many fields,including climate change biology,landscape ecology and conservation biology.In the past 3 decades,a number of new models have been proposed,yet researchers still find it difficult to select appropriate models for data and objectives.In this review,we aim to provide insight into the prevailing species distribution models for newcomers in the field of modelling.We compared 11 popular models,including regression models(the generalized linear model,the generalized additive model,the multivariate adaptive regression splines model and hierarchical modelling),classification models(mixture discriminant analysis,the generalized boosting model,and classification and regression tree analysis)and complex models(artificial neural network,random forest,genetic algorithm for rule set production and maximum entropy approaches).Our objectives are:(i)to compare the strengths and weaknesses of the models,their characteristics and identify suitable situations for their use(in terms of data type and species-environment relationships)and(ii)to provide guidelines for model application,including 3 steps:model selection,model formulation and parameter estimation.

Mapping the potential distribution suitability of 16 tree species under climate change in northeastern China using Maxent modelling

Knowledge on the potential suitability of tree species to the site is very important for forest management planning.Natural forest distribution provides a good reference for afforestation and forest restoration.In this study,we developed species distribution model(SDM)for 16 major tree species with 2,825 permanent sample plots with natural origin from Chinese National Forest Inventory data collected in Jilin Province using the Maxent model.Three types of environmental factors including bioclimate,soil and topography with a total of 33 variables were tested as the input.The values of area under the curve(AUC,one of the receiver operating characteristics of the Maxent model)in the training and test datasets were between 0.784 and 0.968,indicating that the prediction results were quite reliable.The environmental factors affecting the distribution of species were ranked in terms of their importance to the species distribution.Generally,the climatic factors had the greatest contribution,which included mean diurnal range,annual mean temperature,temperature annual range,and iosthermality.But the main environmental factors varied with tree species.Distribution suitability maps under current(1950-2000)and future climate scenarios(CCSM4-RCP 2.6 and RCP 6.0 during 2050)were produced for 16 major tree species in Jilin Province using the model developed.The predicted current and future ranges of habitat suitability of the 16 tree species are likely to be positively and negatively affected by future climate.Seven tree species were found to benefit from future climate including B etula costata,Fraxinus mandshurica,Juglans mandshurica,Phellodendron amurense,Populus ussuriensis,Quercus mongolica and Ulmus pumila;five tree species will experience decline in their suitable habitat including B.platyphylla,Tilia mongolica,Picea asperata,Pinus sylvestris,Pinus koraiensis;and four(Salix koreensis,Abies fabri,Pinus densiflora and Larix olgensis)showed the inconsistency under RCP 2.6 and RCP 6.0 scenarios.The maps of the habitat suitability can be used as a basis for afforestation and forest restoration in northeastern China.The SDMs could be a potential tool for forest management planning.

Modelling the nesting-habitat of threatened vulture species in the caucasus:An ecosystem approach to formalising environmental factors in species distribution models

Abiotic factors play an important role in species localisation,but biotic and anthropogenic predictors must also be considered in distribution modelling for models to be biologically meaningful.In this study,we formalised the biotic predictors of nesting sites for four threatened Caucasian vultures by including species distribution models(wild ungulates,nesting tree species)as biotic layers in the vulture Maxent models.Maxent was applied in the R dismo package and the best set of the model parameters were defined in the R ENMeval package.Performance metrics were continuous Boyce index,Akaike's information criterion,the area under receiver operating curve and true skill statistics.We also calculated and evaluated the null models.Kernel density estimation method was applied to assess the overlap of vulture ecological niches in the environmental space.The accessibility of anthropogenic food resources was estimated using the Path Distance measure that considers elevation gradient.The availability of pine forests(Scots Pine)and wild ungulates(Alpine Chamois and Caucasian Goat)contributed the most(29.6%and 34.3%)to Cinereous Vulture(Aegypius monachus)nesting site model.Wild ungulate distribution also contributed significantly(about 46%)to the Bearded Vulture(Gypaetus barbatus)model.This scavenger nests in the highlands of the Caucasus at a minimum distance of 5–10 km from anthropogenic facilities.In contrast,livestock as a food source was most important in colony distribution of Griffon Vulture(Gyps fulvus).The contribution of distances to settlements and agricultural facilities to the model was 45%.The optimal distance from Egyptian Vulture(Neophron percnopterus)nesting sites to settlements was only 3–10 km,to livestock facilities no more than 15 km with the factor contribution of about 57%.Excluding the wild ungulate availability,the ecological niches of studied vultures overlapped significantly.Despite similar foraging and nesting requirements,Caucasian vultures are not pronounced nesting and trophic competitors due to the abundance of nesting sites,anthropogenic food sources and successful niche sharing.

Potential distributional shifts in North America of allelopathic invasive plant species under climate change models

Predictive studies play a crucial role in the study of biological invasions of terrestrial plants under possible climate change scenarios.Invasive species are recognized for their ability to modify soil microbial communities and influence ecosystem dynamics.Here,we focused on six species of allelopathic flowering plants-Ailanthus altissima,Casuarina equisetifolia,Centaurea stoebe ssp.micranthos,Dioscorea bulbifera,Lantana camara,and Schinus terebinthifolia-Xhat are invasive in North America and examined their potential to spread further during projected climate change.We used Species Distribution Models(SDMs)to predict future suitable areas for these species in North America under several proposed future climate models.ENMEval and Maxent were used to develop SDMs,estimate current distributions,and predict future areas of suitable climate for each species.Areas with the greatest predicted suitable climate in the future include the northeastern and the coastal northwestern regions of North America.Range size estimations demonstrate the possibility of extreme range loss for these invasives in the southeastern United States,while new areas may become suitable in the northeastern United States and southeastern Canada.These findings show an overall northward shift of suitable climate during the next few decades,given projected changes in temperature and precipitation.Our results can be utilized to analyze potential shifts in the distribution of these invasive species and may aid in the development of conservation and management plans to target and control dissemination in areas at higher risk for potential future invasion by these allelopathic species.

Mapping the current and future distributions of Onosma species endemic to Iran

Climate change may cause shifts in the natural range of species especially for those that are geographically restricted and/or endemic species.In this study,the spatial distribution of five endemic and threatened species belonging to the genus Onosma(including O.asperrima,O.bisotunensis,O.kotschyi,O.platyphylla,and O.straussii)was investigated under present and future climate change scenarios:RCP2.6(RCP,representative concentration pathway;optimistic scenario)and RCP8.5(pessimistic scenario)for the years 2050 and 2080 in Iran.Analysis was conducted using the maximum entropy(MaxEnt)model to provide a basis for the protection and conservation of these species.Seven environmental variables including aspect,depth of soil,silt content,slope,annual precipitation,minimum temperature of the coldest month,and annual temperature range were used as main predictors in this study.The model output for the potential habitat suitability of the studied species showed acceptable performance for all species(i.e.,the area under the curve(AUC)>0.800).According to the models generated by MaxEnt,the potential current patterns of the species were consistent with the observed areas of distributions.The projected climate maps under optimistic and pessimistic scenarios(RCP2.6 and RCP8.5,respectively)of 2050 and 2080 resulted in reductions and expansions as well as positive range changes for all species in comparison to their current predicted distributions.Among all species,O.bisotunensis showed the most significant and highest increase under the pessimistic scenario of 2050 and 2080.Finally,the results of this study revealed that the studied plant species have shown an acute adaptability to environmental changes.The results can provide useful information to managers to apply appropriate strategies for the management and conservation of these valuable Iranian medicinal and threatened plant species in the future.

Eff ects of climate change on the potential habitat distribution of swimming crab Portunus trituberculatus under the species distribution model

Over the last decades,the species distribution model(SDM)has become an essential tool for studying the potential eff ects of climate change on species distribution.In this study,an ensemble SDM was developed to predict the changes in species distribution of swimming crab Portunus trituberculatus across diff erent seasons in the future(2050s and 2100s)under the climate scenarios of Representative Concentration Pathway(RCP)4.5 and RCP8.5.Results of the ensemble SDM indicate that the distribution of this species will move northward and exhibit evident seasonal variations.Among the four seasons,the suitable habitat for this species will be signifi cantly reduced in summer,with loss rates ranging from 45.23%(RCP4.5)to 88.26%(RCP.8.5)by the 2100s.The loss of habitat will mostly occur in the East China Sea and the southern part of the Yellow Sea,while a slight increase in habitat will occur in the northern part of the Bohai Sea.These fi ndings provide an information forecast for this species in the future.Such forecast will be helpful in improving fi shery management under climate change.

Species distribution modeling in regions of high need and limited data： waterfowl of China

Background: A number of conservation and societal issues require understanding how species are distributed on the landscape, yet ecologists are often faced with a lack of data to develop models at the resolution and extent desired, resulting in inefficient use of conservation resources.Such a situation presented itself in our attempt to develop waterfowl distribution models as part of a multi-disciplinary team targeting the control of the highly pathogenic H5N1 avian influenza virus in China.Methods: Faced with limited data, we built species distribution models using a habitat suitability approach for China's breeding and non-breeding(hereafter, wintering) waterfowl.An extensive review of the literature was used to determine model parameters for habitat modeling.Habitat relationships were implemented in GIS using land cover covariates.Wintering models were validated using waterfowl census data, while breeding models, though developed for many species, were only validated for the one species with sufficient telemetry data available.Results: We developed suitability models for 42 waterfowl species(30 breeding and 39 wintering) at 1 km resolution for the extent of China, along with cumulative and genus level species richness maps.Breeding season models showed highest waterfowl suitability in wetlands of the high-elevation west-central plateau and northeastern China.Wintering waterfowl suitability was highest in the lowland regions of southeastern China.Validation measures indicated strong performance in predicting species presence.Comparing our model outputs to China's protected areas indicated that breeding habitat was generally better covered than wintering habitat, and identified locations for which additional research and protection should be prioritized.Conclusions: These suitability models are the first available for many of China's waterfowl species, and have direct utility to conservation and habitat planning and prioritizing management of critically important areas, providing an example of how this approach may aid others faced with the challenge of addressing conservation issues with little data to inform decision making.

Common Species Distribution Models in Biodiversity Analysis and Their Challenges and Prospects in Application

Species distribution models have been widely used to explore suitable habitats of species,the impact of climate change on the distribution of suitable habitats of species,and the construction of ecological reserves.This paper introduced species distribution models commonly used in biodiversity analysis,as well as model performance evaluation indexes,challenges in the application of species distribution models,and finally prospected the development trend of research on species distribution models.

Modeling Bat Species Richness and Spatial Distribution in Burkina Faso

The spatial distribution of bats in Burkina Faso is little-known. Previous studies have only described the bat species’ richness in Burkina Faso. This study was conducted to highlight bat species’ richness distribution within Burkina Faso and environmental variables that influence this distribution with the aim to give support for protection and further sampling for biodiversity. The Species Distribution Models (SDMs) were used to perform this study. To do that, species occurrences were collected throughout literature and field sampling and correlated to environmental variables through the Maxent software (Maximum Entropy). Our modeling variables included climate, vegetation cover, topography and hydrography data. The Jackknife test was performed to determine the importance of environmental variables that influence the species distribution model. The results showed that bats are present in all areas of vegetation in Burkina Faso. Species richness varies across the country. The species richness for major families increases from North to South. The total annual precipitation and topography are the main variables that positively influence bats distribution in Burkina Faso but the bare ground cover and standard deviation of the maximum temperature negatively influence this distribution. This modeling approach of bat species richness is important for policies makers and represents an invaluable tool in ecological management, particularly in the current context of climate change.

Climate-change habitat shifts for the vulnerable endemic oak species(Quercus arkansana Sarg.)

Quercus arkansana(Arkansas oak)is at risk of becoming endangered,as the total known population size is represented by a few isolated populations.The potential impact of climate change on this species in the near future is high,yet knowledge of its predicted effects is limited.Our study utilized the biomod2 R package to develop habi-tat suitability ensemble models based on bioclimatic and topographic environmental variables and the known loca-tions of current distribution of Q.arkansana.We predicted suitable habitats across three climate change scenarios(SSP1-2.6,SSP2-4.5,and SSP5-8.5)for 2050,2070,and 2090.Our findings reveal that the current suitable habitat for Q.arkansana is approximately 127,881 km^(2) across seven states(Texas,Arkansas,Alabama,Louisiana,Mississippi,Georgia,and Florida);approximately 9.5%is encompassed within state and federally managed protected areas.Our models predict that all current suitable habitats will disap-pear by 2050 due to climate change,resulting in a northward shift into new regions such as Tennessee and Kentucky.The large extent of suitable habitat outside protected areas sug-gests that a species-specific action plan incorporating pro-tected areas and other areas may be crucial for its conserva-tion.Moreover,protection of Q.arkansana habitat against climate change may require locally and regionally focused conservation policies,adaptive management strategies,and educational outreach among local people.

Finer topographic data improves distribution modeling of Picea crassifolia in the northern Qilian Mountains

The Qilian Mountains, a national key ecological function zone in Western China, play a pivotal role in ecosystem services. However, the distribution of its dominant tree species, Picea crassifolia (Qinghai spruce), has decreased dramatically in the past decades due to climate change and human activity, which may have influenced its ecological functions. To restore its ecological functions, reasonable reforestation is the key measure. Many previous efforts have predicted the potential distribution of Picea crassifolia, which provides guidance on regional reforestation policy. However, all of them were performed at low spatial resolution, thus ignoring the natural characteristics of the patchy distribution of Picea crassifolia. Here, we modeled the distribution of Picea crassifolia with species distribution models at high spatial resolutions. For many models, the area under the receiver operating characteristic curve (AUC) is larger than 0.9, suggesting their excellent precision. The AUC of models at 30 m is higher than that of models at 90 m, and the current potential distribution of Picea crassifolia is more closely aligned with its actual distribution at 30 m, demonstrating that finer data resolution improves model performance. Besides, for models at 90 m resolution, annual precipitation (Bio12) played the paramount influence on the distribution of Picea crassifolia, while the aspect became the most important one at 30 m, indicating the crucial role of finer topographic data in modeling species with patchy distribution. The current distribution of Picea crassifolia was concentrated in the northern and central parts of the study area, and this pattern will be maintained under future scenarios, although some habitat loss in the central parts and gain in the eastern regions is expected owing to increasing temperatures and precipitation. Our findings can guide protective and restoration strategies for the Qilian Mountains, which would benefit regional ecological balance.

Conservation of challenging endemic plant species at high risk of extinction in arid mountain ecosystems:a case study of Rosa arabica Crép.in Egypt

Rosa arabica Crép.is a perennial shrub belonging to the family Rosaceae.It is endemic to the high mountain area of St.Catherine Protected Area(SCPA)in southern Sinai,Egypt,and is listed as one of the most 100 threatened plants in the world.Recently,it has been listed as critically endangered by IUCN Red List due to its small extent of occurrence and tiny population size.We reported the continuous decline in habitat quality for this species and the urgent need to carry out on-ground conservation actions.So,this research aims to conserve Rosa arabica through in situ practices by implementing the following steps,respectively:a)evaluate the current conservation status through IUCN Red List to extract the environmental factors controlling the species’distribution necessary for establishing the recovery program,b)determine the potential species habitat suitability under the current climate conditions using Maxent,and c)based on the previous two steps,the translocation process for R.arabica in the suitable habitat will be done after the simple layering process as one of the most effective traditional vegetative methods for wild cultivation for this species.These steps aimed to reduce the impact of threats and the risk of extinction through increasing the population size,the Extent of Occurrence(EOO),and the Area of Occupancy(AOO).We extracted the environmental factors controlling the target species’distribution and habitat suitability range using the IUCN Red List assessment and Species Distribution Model(SDM).The most suitable habitat for R.arabica is predicted in the middle northern parts of SCPA,with the highest suitability in the High Mountains.Precipitation of driest quarter,precipitation of wettest month,precipitation of coldest quarter,and aspect are the highest mean contributors determining the distribution of R.arabica in SCPA.Rosa arabica potential distribution covers 324.4 km^(2)(7.46%)of the total SCPA area(4350 km^(2)).This area is divided into:18.1 km^(2)high probability,124.3 km^(2)moderate probability,and 182 km^(2)low probability.After one year of the simple layering process,ten branches rooted and were translocated into three sites that had been previously identified to cover three habitat suitability ranges(high,moderate,and low suitability).After a year of translocation in the wild,the survival rate ranged from 66%to 100%,the geographical range increased by 65%,and the population size by 6.8%.Therefore,if the new individuals continue to grow and adapt it may lead to the expansion of other environmental factors such as climatic and topographical factors that probably increase the resilience of the global population of the species to adverse events.Detailed information is provided in this research about the recovery program,from planning to implementation and monitoring,and recommendations for best practices.

Distribution and Environmental Suitability of the Smallscaled Rock Agama, Paralaudakia microlepis(Sauria: Agamidae) in the Iranian Plateau

Predictive potential distribution modeling is of increasing importance in modern herpetological studies and determination of environmental and conservation priorities. In this article we provided results of analysis and forecasts of the potential distribution of smallscaled rock agama Paralaudakia microlepis （Blanford, 1874） using the distribution models through Maxent （www.cs.princeton.edu/- schapire / maxent）. We made an attempt for comparison of input of bioclimatic factors and characteristics of biotope distribution for three species of genus Paralaudalda. Constructed model identified dissemination of Paralaudakia microlepis enough performance （AUC = 0.972 with dispersion 0.003）. According to the map constructed, the most suitable habitats of smallscaled rock agama Paralaudakia microlepis are located in southern and eastern Iran, the west of central Pakistan and southeastern Afghanistan.

Limiting climatic factors in shaping the distribution pattern and niche differentiation of Prunus dielsiana in subtropical China

Subtropical forest in China has received much attention due to its complex geologic environment and bioclimatic heterogeneity.There have been very few studies addressing which climatic factors have shaped both distribution patterns and niche differentiation of species from this region.It also remains unclear whether phylogenetic niche conservatism retains in plant species from this biodiversityrich subtropical region in China.In this study,we used geographic occurrence records and bioclimatic factors of Prunus dielsiana(Rosaceae),a wild cherry species,combined with the classical ENM-based DIVA-GIS software to access contemporary distribution and richness patterns of its natural populations.The current distribution of P.dielsiana occupied a relatively wide range but exhibited an uneven pattern eastward in general,and the core distribution zone of its populations are projected to concentrate in the Wushan and Wuling Mountain ranges of western China.Hydrothermic variables,particularly the Temperature Seasonality(bio4)are screened out quantitatively to be the most influential factors that have shaped the current geographical patterns of P.dielsiana.By comparison with other sympatric families,climatic niche at regional scale showed a pattern of phylogenetic niche conservatism within cherry species of Ros aceae.The effect of habitat filtering from altitude is more significant than those of longitude and latitude.We conclude that habitat filtering dominated by limiting hydrothermic factors is the primary driving process of the diversity pattern of P.dielsiana in subtropical China.

Distribution Changes of Chinese Skink(Eumeces chinensis) in China: the Impacts of Global Climate Change

Repaid global climate changes in temperature and rainfall influence the species distribution and diversity patterns.Chinse skink is a common species with large population and widely distribution in China.To access potential effect of climate changes on the unendangered species,we used the maximum-entropy modeling(MaxEnt)method to estimate the current and future potential distributions of Chinese Skink.Predictions were based on two periods(2050 and 2070),three general circulation models(GCMs:BCC-CSM1-1,HadGEM2-ES,MIROC5),four representative concentration pathways(RCP:2.6,4.5,6.0 and 8.0)and 28 environmental variables including topography,human impact,bio-climate and habitat.We found that the model were better fit with high values in AUC,KAPPA and TSS.The jackknife tests showed that variables of BIO9,BIO14,BIO15,HFI and GDP were relatively higher contributions to the model.Although the size of suitable areas for skink have less effect by future climate change under full and mull dispersal hypothesis,we should still focuse on the effect of human impact and climate changes on the protection and management for Chinese skink due to the variables uncertainty.

Potential global distribution of the guava root-knot nematode Meloidogyne enterolobii under different climate change scenarios using MaxEnt ecological niche modeling

In recent years,Meloidogyne enterolobii has emerged as a major parasitic nematode infesting many plants in tropical or subtropical areas.However,the regions of potential distribution and the main contributing environmental variables for this nematode are unclear.Under the current climate scenario,we predicted the potential geographic distributions of M.enterolobii worldwide and in China using a Maximum Entropy(MaxEnt)model with the occurrence data of this species.Furthermore,the potential distributions of M.enterolobii were projected under three future climate scenarios(BCC-CSM2-MR,CanESM5 and CNRM-CM6-1)for the periods 2050s and 2090s.Changes in the potential distribution were also predicted under different climate conditions.The results showed that highly suitable regions for M.enterolobii were concentrated in Africa,South America,Asia,and North America between latitudes 30°S to 30°N.Bio16(precipitation of the wettest quarter),bio10(mean temperature of the warmest quarter),and bio11(mean temperature of the coldest quarter)were the variables contributing most in predicting potential distributions of M.enterolobii.In addition,the potential suitable areas for M.enterolobii will shift toward higher latitudes under future climate scenarios.This study provides a theoretical basis for controlling and managing this nematode.

The rapid climate change-caused dichotomy on subtropical evergreen broad-leaved forest in Yunnan： Reduction in habitat diversity and increase in species diversity

Yunnan's biodiversity is under considerable pressure and subtropical evergreen broad-leaved forests in this area have become increasingly fragmented through agriculture,logging,planting of economic plants,mining activities and changing environment.The aims of the study are to investigate climate changeinduced changes of subtropical evergreen broad-leaved forests in Yunnan and identify areas of current species richness centers for conservation preparation.Stacked species distribution models were created to generate ensemble forecasting of species distributions,alpha diversity and beta diversity for Yunnan's subtropical evergreen broad-leaved forests in both current and future climate scenarios.Under stacked species distribution models in rapid climate changes scenarios,changes of water-energy dynamics may possibly reduce beta diversity and increase alpha diversity.This point provides insight for future conservation of evergreen broad-leaved forest in Yunnan,highlighting the need to fully consider the problem of vegetation homogenization caused by transformation of water-energy dynamics.