Spatio-temporal evolution analysis of landscape pattern and habitat quality in the Qinghai Province section of the Yellow River Basin from 2000 to 2022 based on InVEST model

Habitat quality is an important indicator for evaluating the quality of ecosystem.The Qinghai Province section of the Yellow River Basin plays an important role in the ecological protection of the upper reaches of the Yellow River Basin.To comprehensively analysis the alterations of habitat quality in the Qinghai Province section of the Yellow River Basin,this study utilized the Integrated Valuation of Ecosystem Services and Tradeoffs(InVEST)model to calculate the habitat quality index and analyze the spatio-temporal variation characteristics of habitat quality in the study area from 2000 to 2022,and calculated seven landscape pattern indices(number of patches,patch density,largest patch index(LPI),landscape shape index(LSI),contagion index(CONTAG),Shannon diversity index,and Shannon evenness index)to research the variation of landscape pattern in the study area.The results showed that the number of patches,patch density,LPI,LSI,Shannon diversity index,and Shannon evenness index increased from 2000 to 2022,while the CONTAG decreased,indicating that the landscape pattern in the Qinghai Province section of the Yellow River Basin changed in the direction of distribution fragmentation,shape complexity,and heterogeneity.The average value of the habitat quality index in the Qinghai Province section of the Yellow River Basin from 2000 to 2022 was 0.90.Based on the value of habitat quality index,we divided the level of habitat quality into five categories:lower(0.00-0.20),low(0.20-0.40),moderate(0.40-0.60),high(0.60-0.80),and higher(0.80-1.00).Most areas were at the higher habitat quality level.The lower habitat quality patches were mainly distributed in Longyang Gorge and Yellow River-Huangshui River Valley.From 2000 to 2022,the habitat quality in most areas was stable;the increase areas were mainly distributed in Guinan County,while the decrease areas were mainly distributed in Xining City,Maqen County,Xinghai County,Qumarleb County,and Darlag County.To show the extent of habitat quality variation,we calculated Sen index.The results showed that the higher habitat quality area had a decrease trending,while other categories had an increasing tendency,and the decreasing was faster than increasing.The research results provide scientific guidance for promoting ecological protection and high-quality development in the Qinghai Province section of the Yellow River Basin.

Estimation of Potential Habitat of Caragana acanthophylla in Xinjiang Based on Maximum Entropy Model

[Objectives]To determine the potential habitat range of Caragana acanthophylla in Xinjiang.[Methods]The known distribution points of C.acanthophylla were used as samples,and a MaxEnt model was developed based on their climatic variables to identify key environmental factors affecting the potential habitats of C.acanthophylla through jackknife method and construction of a response relationship between representative variables and habitat suitability;the suitability of habitats for C.acanthophylla in Xinjiang was evaluated based on the output results of the model.[Results](i)The accuracy of the model verified by AUC curve was 0.971,indicating that the potential habitats of C.acanthophylla in Xinjiang predicted by MaxEnt model were highly credible.(ii)The optimum climatic characteristics for the distribution of C.acanthophylla in Xinjiang were:isothermality 18.8%-34%,minimum temperature of coldest month-30℃to-13℃,mean temperature of coldest quarter-18℃ to-4℃,annual precipitation 80-410 mm,precipitation of driest month 0-25 mm,precipitation of driest quarter 0-82 mm,and precipitation of coldest quarter 0-75 mm.(iii)The total potential distribution area of C.acanthophylla in Xinjiang was modeled to be 1.03×10^(5) km^(2),of which 8.54×10^(3)km^(2) was high suitability area,mainly in the front mountain belt of the north slope of Tianshan Mountain in Urumqi City,Changji Hui Autonomous Prefecture,Bortala Mongol Autonomous Prefecture,and Yili Kazak Autonomous Prefecture and the front mountain belt of Barluk Mountain in Tacheng Prefecture.[Conclusions]This study is of great significance for the future scientific management,regeneration,vegetation restoration and ecological protection of C.acanthophylla.

Aquaporin-4-IgG-seropositive neuromyelitis optica spectrum disorders:progress of experimental models based on disease pathogenesis

Neuromyelitis optica spectrum disorders are neuroinflammatory demyelinating disorders that lead to permanent visual loss and motor dysfunction.To date,no effective treatment exists as the exact causative mechanism remains unknown.Therefore,experimental models of neuromyelitis optica spectrum disorders are essential for exploring its pathogenesis and in screening for therapeutic targets.Since most patients with neuromyelitis optica spectrum disorders are seropositive for IgG autoantibodies against aquaporin-4,which is highly expressed on the membrane of astrocyte endfeet,most current experimental models are based on aquaporin-4-IgG that initially targets astrocytes.These experimental models have successfully simulated many pathological features of neuromyelitis optica spectrum disorders,such as aquaporin-4 loss,astrocytopathy,granulocyte and macrophage infiltration,complement activation,demyelination,and neuronal loss;however,they do not fully capture the pathological process of human neuromyelitis optica spectrum disorders.In this review,we summarize the currently known pathogenic mechanisms and the development of associated experimental models in vitro,ex vivo,and in vivo for neuromyelitis optica spectrum disorders,suggest potential pathogenic mechanisms for further investigation,and provide guidance on experimental model choices.In addition,this review summarizes the latest information on pathologies and therapies for neuromyelitis optica spectrum disorders based on experimental models of aquaporin-4-IgG-seropositive neuromyelitis optica spectrum disorders,offering further therapeutic targets and a theoretical basis for clinical trials.

Exploiting fly models to investigate rare human neurological disorders

Rare neurological diseases,while individually are rare,collectively impact millions globally,leading to diverse and often severe neurological symptoms.Often attributed to genetic mutations that disrupt protein function or structure,understanding their genetic basis is crucial for accurate diagnosis and targeted therapies.To investigate the underlying pathogenesis of these conditions,researchers often use non-mammalian model organisms,such as Drosophila(fruit flies),which is valued for their genetic manipulability,cost-efficiency,and preservation of genes and biological functions across evolutionary time.Genetic tools available in Drosophila,including CRISPR-Cas9,offer a means to manipulate gene expression,allowing for a deep exploration of the genetic underpinnings of rare neurological diseases.Drosophila boasts a versatile genetic toolkit,rapid generation turnover,and ease of large-scale experimentation,making it an invaluable resource for identifying potential drug candidates.Researchers can expose flies carrying disease-associated mutations to various compounds,rapidly pinpointing promising therapeutic agents for further investigation in mammalian models and,ultimately,clinical trials.In this comprehensive review,we explore rare neurological diseases where fly research has significantly contributed to our understanding of their genetic basis,pathophysiology,and potential therapeutic implications.We discuss rare diseases associated with both neuron-expressed and glial-expressed genes.Specific cases include mutations in CDK19 resulting in epilepsy and developmental delay,mutations in TIAM1 leading to a neurodevelopmental disorder with seizures and language delay,and mutations in IRF2BPL causing seizures,a neurodevelopmental disorder with regression,loss of speech,and abnormal movements.And we explore mutations in EMC1 related to cerebellar atrophy,visual impairment,psychomotor retardation,and gain-of-function mutations in ACOX1 causing Mitchell syndrome.Loss-of-function mutations in ACOX1 result in ACOX1 deficiency,characterized by very-long-chain fatty acid accumulation and glial degeneration.Notably,this review highlights how modeling these diseases in Drosophila has provided valuable insights into their pathophysiology,offering a platform for the rapid identification of potential therapeutic interventions.Rare neurological diseases involve a wide range of expression systems,and sometimes common phenotypes can be found among different genes that cause abnormalities in neurons or glia.Furthermore,mutations within the same gene may result in varying functional outcomes,such as complete loss of function,partial loss of function,or gain-of-function mutations.The phenotypes observed in patients can differ significantly,underscoring the complexity of these conditions.In conclusion,Drosophila represents an indispensable and cost-effective tool for investigating rare neurological diseases.By facilitating the modeling of these conditions,Drosophila contributes to a deeper understanding of their genetic basis,pathophysiology,and potential therapies.This approach accelerates the discovery of promising drug candidates,ultimately benefiting patients affected by these complex and understudied diseases.

A promising approach for quantifying focal stroke modeling and assessing stroke progression:optical resolution photoacoustic microscopy photothrombosis

To investigate the mechanisms underlying the onset and progression of ischemic stroke,some methods have been proposed that can simultaneously monitor and create embolisms in the animal cerebral cortex.However,these methods often require complex systems and the effect of age on cerebral embolism has not been adequately studied,although ischemic stroke is strongly age-related.In this study,we propose an optical-resolution photoacoustic microscopy-based visualized photothrombosis methodology to create and monitor ischemic stroke in mice simultaneously using a 532 nm pulsed laser.We observed the molding process in mice of different ages and presented age-dependent vascular embolism differentiation.Moreover,we integrated optical coherence tomography angiography to investigate age-associated trends in cerebrovascular variability following a stroke.Our imaging data and quantitative analyses underscore the differential cerebrovascular responses to stroke in mice of different ages,thereby highlighting the technique's potential for evaluating cerebrovascular health and unraveling age-related mechanisms involved in ischemic strokes.

Reduced mesencephalic astrocyte-derived neurotrophic factor expression by mutant androgen receptor contributes to neurodegeneration in a model of spinal and bulbar muscular atrophy pathology

Spinal and bulbar muscular atrophy is a neurodegenerative disease caused by extended CAG trinucleotide repeats in the androgen receptor gene,which encodes a ligand-dependent transcription facto r.The mutant androgen receptor protein,characterized by polyglutamine expansion,is prone to misfolding and forms aggregates in both the nucleus and cytoplasm in the brain in spinal and bulbar muscular atrophy patients.These aggregates alter protein-protein interactions and compromise transcriptional activity.In this study,we reported that in both cultured N2a cells and mouse brain,mutant androgen receptor with polyglutamine expansion causes reduced expression of mesencephalic astrocyte-de rived neurotrophic factor.Overexpressio n of mesencephalic astrocyte-derived neurotrophic factor amelio rated the neurotoxicity of mutant androgen receptor through the inhibition of mutant androgen receptor aggregation.Conversely.knocking down endogenous mesencephalic astrocyte-derived neurotrophic factor in the mouse brain exacerbated neuronal damage and mutant androgen receptor aggregation.Our findings suggest that inhibition of mesencephalic astrocyte-derived neurotrophic factor expression by mutant androgen receptor is a potential mechanism underlying neurodegeneration in spinal and bulbar muscular atrophy.

Modeling foraging habitats of Hume’s Pheasant (Syrmaticus humiae) in Dazhong Mountain, Yunnan, southwestern China

We modeled foraging habitats of Hume’s Pheasant (Syrmaticus humiae) on a macro-habitat level using ArcGIS in an attempt to provide scientific reference for management and restoration of habitats. Field work was conducted from March to April in 2006 and 2008, and from October to November in 2005 and 2008 in Dazhong Mountain, Yunnan Province, southwestern China. The selection of ecological factors was estimated by means of a resource selection index, distance analysis and the method of hierarchical habitat selection. The foraging habitat patches were modeled spatially by ArcGIS. The results show that actual and potential foraging patches overlapped considerably in spring and autumn. The number and total areas of patches in the autumn were smaller than those in the spring. The minimum and average areas of patches in the autumn were larger than those in the spring, while the maximum areas of actual and potential foraging patches in the autumn were equal to those in the spring. Similarity in the selection for survival and safety consideration in both seasons was the main strategy for landscape factors of habitats by Hume’s Pheasant, while seasonal difference in selecting a landscape matrix was their secondary strategy, affecting landscape factors in the habitat. Changes of foraging patches in both seasons reflect a difference of resources requirement by the bird. Fragmentation and miniaturization of foraging patches would result in the formation of a meta-population of Hume’s Pheasant.

Importance of Weighting for Multi-Variable Habitat Suitability Index Model: A Case Study of Winter- Spring Cohort of Ommastrephes bartramii in the Northwestern Pacific Ocean

Weighting values for different habitat variables used in multi-factor habitat suitability index (HSI) modeling reflect the relative influences of different variables on distribution of fish species. Using the winter-spring cohort of neon flying squid (Ommastrephes bartramii) in the Northwestern Pacific Ocean as an example, we evaluated the impact of different weighting schemes on the HSI models based on sea surface temperature, gradient of sea surface temperature and sea surface height. We compared differences in predicted fishing effort and HSI values resulting from different weighting. The weighting for different habitat variables could greatly influence HSI modeling and should be carefully done based on their relative importance in influencing the resource spatial distribution. Weighting in a multi-factor HSI model should be further studied and optimization methods should be developed to improve forecasting squid spatial distributions.

采用STAMP-24Model的多组织事故分析

安全生产事故往往由多组织交互、多因素耦合造成,事故原因涉及多个组织。为预防和遏制多组织生产安全事故的发生,基于系统理论事故建模与过程模型(Systems-Theory Accident Modeling and Process,STAMP)、24Model,构建一种用于多组织事故分析的方法,并以青岛石油爆炸事故为例进行事故原因分析。结果显示:STAMP-24Model可以分组织,分层次且有效、全面、详细地分析涉及多个组织的事故原因,探究多组织之间的交互关系;对事故进行动态演化分析,可得到各组织不安全动作耦合关系与形成的事故失效链及管控失效路径,进而为预防多组织事故提供思路和参考。

基于改进24Model-ISM-SNA建筑工人不安全行为关联路径研究

建筑施工现场环境复杂,为有效控制不安全行为发生,基于行为安全“2-4”模型对360份具有代表性的建筑安全事故调查报告进行分析,提取出22个不安全行为的主要影响因素。利用灰色关联分析方法(GRA)改进的集成ISM-SNA模型,将不安全行为风险因素划分为表层、过渡层与深层,然后对风险因素进行可视化分析、中心度分析及凝聚子群分析,揭示了各致因因素间的关联关系和传导路径。结果表明,建筑工人不安全行为影响因素可划分成7级3阶的多级递阶结构,安全意识、现场监管、外部环境是建筑工人不安全行为的关键影响因素,同时现场监管和隐患排查到位能有效降低不安全行为的发生。

Assessment of habitat suitability of the snow leopard (Panthera uncia) in Qomolangma National Nature Reserve based on MaxEnt modeling

Habitat evaluation constitutes an important and fundamental step in the management of wildlife populations and conservation policy planning. Geographic information system （GIS） and species presence data provide the means by which such evaluation can be done. Maximum Entropy （MaxEnt） is widely used in habitat suitability modeling due to its power of accuracy and additional descriptive properties To survey snow leopard populations in Qomolangma （Mt. Everest） National Nature Reserve （QNNR）, Xizang （Tibet）, China, we pooled 127 pugmarks, 415 scrape marks, and 127 non-invasive identifications of the animal along line transects and recorded 87 occurrences through camera traps from 2014-2017. We adopted the MaxEnt model to generate a map highlighting the extent of suitable snow leopard habitat in QNNR. Results showed that the accuracy of the MaxEnt model was excellent （mean AUC=0.921）. Precipitation in the driest quarter, ruggedness, elevation, maximum temperature of the warmest month, and annual mean temperature were the main environmental factors influencing habitat suitability for snow leopards, with contribution rates of 20.0%, 14.4%, 13.3%, 8.7%, and 8.2% respectively The suitable habitat area extended for 7 001.93 km^2, representing 22.72% of the whole reserve. The regions bordering Nepal were the main suitable snow leopard habitats and consisted of three separate habitat patches Our findings revealed that precipitation, temperature conditions, ruggedness, and elevations of around 4 000 m a.s.I, influenced snow leopard preferences at the landscape level in QNNR. We advocate further research and cooperation with Nepal to evaluate habitat connectivity and to explore possible proxies of population isolation among these patches. Furthermore, evaluation of subdivisions within the protection zones of QNNR is necessary to improve conservation strategies and enhance protection.

基于24Model的地铁内涝事故原因分析与评估

为降低地铁内涝事故灾害风险,基于事故致因“2-4”模型,分析了地铁内涝事故致灾因子,采用层次分析法构建了地铁内涝事故原因分析指标体系,确定了各风险因子的权重,并利用模糊综合评价法对地铁内涝事故进行了定量评估,识别出关键的影响因素。结果表明:地铁内涝事故一级指标中不安全动作与物态因素最重要,其中影响最大的指标包括擅自更改建筑设计、未按照要求检查水位情况、未及时排水、出入口不符合防汛标准等因素;习惯性不安全行为的权重位居第二,表明该指标因素较为重要,同时安全管理体系得分位居第二,表明该指标因素较易发生。对关键指标采取防范措施,可有效降低风险,从而减少地铁内涝事故的发生。

Two-dimensional physical habitat modeling of effects of habitat structures on urban stream restoration

River corridors, even if highly modified or degraded, still provide important habitats for numerous biological species, and carry high aesthetic and economic values. One of the keys to urban stream restoration is recovery and maintenance of ecological flows sufficient to sustain aquatic ecosystems. In this study, the Hongje Stream in the Seoul metropolitan area of Korea was selected for evaluating a physically-based habitat with and without habitat structures. The potential value of the aquatic habitat was evaluated by a weighted usable area （WUA） using River2D, a two-dimensional hydraulic model. The habitat suitability for Zacco platypus in the Hongje Stream was simulated with and without habitat structures. The computed WUA values for the boulder, spur dike, and riffle increased by about 2%, 7%, and 131%, respectively, after their construction. Also, the three habitat structures, especially the riffle, can contribute to increasing hydraulic heterogeneity and enhancing habitat diversity.

Modeling a habitat suitability index for the eastern fall cohort of Ommastrephes bartramii in the central North Pacific Ocean

The eastern fall cohort of the neon flying squid, Ommastrephes bartramii, has been commercially exploited by the Chinese squid jigging fleet in the central North Pacific Ocean since the late 1990s. To understand and identify their optimal habitat, we have developed a habitat suitability index （HSI） model using two potential important environmental variables -- sea surface temperature （SST） and sea surface height anomaly （SSHA） -- and fishery data from the main fishing ground （165°-180°E） during June and July of 1999-2003. A geometric mean model （GMM）, minimum model （MM） and arithmetic weighted model （AWM） with different weights were compared and the best HSI model was selected using Akaike＇s information criterion （AIC）. The performance of the developed HSI model was evaluated using fishery data for 2004. This study suggests that the highest catch per unit effort （CPUE） and fishing effort are closely related to SST and SSHA. The best SST- and SSHA-based suitability index （SI） regression models were SISST-based = 0.7SIeffort-SST ＋ 0.3 SICPUE-SST, and SISSHA-based =0.5Sleffort-SSHA ＋ 0.5SICPUE-SSHA, respectively, showing that fishing effort is more important than CPUE in the estimation of SI. The best HSI model was the AWM, defined as HSI=0.3SISSHA-based＋ 0.7SISSHA-based, indicating that SSHA is more important than SST in estimating the HSI of squid. In 2004, monthly HSI values greater than 0.6 coincided with the distribution of productive fishing ground and high CPUE in June and July, suggesting that the models perform well. The proposed model provides an important tool in our efforts to develop forecasting capacity of squid spatial dynamics.

HABITAT SUITABILITY INDEX MODELS: GREY HERON NESTING IN ZHALONG NATIONAL NATURE RESERVE

Grey heron (Ardea cimerca) is one kind of the great birds which are often seen in the northeast marsh area of P.R.China, and there are many grey herons to reproduce in Zhalong Nature Reserve from March to August annually. In this paper, through the inveingation of the grey herons nesting habitat and according to the water depth, vegetation type, cover density and plan heigh of the nesting place, the grey heron’s nesting habitat suitability index medes are established. The main model is s=(s1xs2xs3xs4)1/4,where s1 is the water depth suitability index, s2 is the vegetation type suitability index, s3 is the cover density index, sa is the plant height suitability index. These models provide a kind of reliable method for evaluating the habitat quality of the grey heron’s nesting.

基于24Model-D-ISM的地铁站火灾疏散影响因素研究

为预防地铁站火灾事故,深入了解地铁站火灾人员疏散影响因素间的内在联系与层次结构,基于第6版“2-4”模型(24Model)分析63起地铁站火灾疏散事故,充分考虑各个因素之间的交互作用,提取19个影响地铁站人员疏散的关键因素,建立地铁站火灾人员疏散影响因素指标体系;采用算子客观赋权法(C-OWA)改进决策试验与评价实验法(DEMATEL),确定地铁站火灾人员疏散的重要影响因素;在此基础上,采用解释结构模型(ISM)分析各个因素间的层次结构及相互作用路径,构建地铁站火灾人员疏散影响因素的多级递阶结构模型。研究结果表明:疏散引导、恐慌从众行为、人员拥挤为地铁站火灾人员疏散的关键影响因素;地铁站火灾人员疏散受表层因素、中间层因素、深层因素共同作用的影响,其中,疏散教育与培训、设施维护与检查、疏散预案等因素是根源影响因素,重视根源影响因素的改善有利于从本质上预防和控制事故的发生。

Optimization of environmental variables in habitat suitability modeling for mantis shrimp Oratosquilla oratoria in the Haizhou Bay and adjacent waters

Habitat suitability index(HSI)models have been widely used to analyze the relationship between species abundance and environmental factors,and ultimately inform management of marine species.The response of species abundance to each environmental variable is different and habitat requirements may change over life history stages and seasons.Therefore,it is necessary to determine the optimal combination of environmental variables in HSI modelling.In this study,generalized additive models(GAMs)were used to determine which environmental variables to be included in the HSI models.Significant variables were retained and weighted in the HSI model according to their relative contribution(%)to the total deviation explained by the boosted regression tree(BRT).The HSI models were applied to evaluate the habitat suitability of mantis shrimp Oratosquilla oratoria in the Haizhou Bay and adjacent areas in 2011 and 2013–2017.Ontogenetic and seasonal variations in HSI models of mantis shrimp were also examined.Among the four models(non-optimized model,BRT informed HSI model,GAM informed HSI model,and both BRT and GAM informed HSI model),both BRT and GAM informed HSI model showed the best performance.Four environmental variables(bottom temperature,depth,distance offshore and sediment type)were selected in the HSI models for four groups(spring-juvenile,spring-adult,falljuvenile and fall-adult)of mantis shrimp.The distribution of habitat suitability showed similar patterns between juveniles and adults,but obvious seasonal variations were observed.This study suggests that the process of optimizing environmental variables in HSI models improves the performance of HSI models,and this optimization strategy could be extended to other marine organisms to enhance the understanding of the habitat suitability of target species.

Effect of Spatial and Temporal Scales on Habitat Suitability Modeling:A Case Study of Ommastrephes bartramii in the Northwest Pacific Ocean

Temporal and spatial scales play important roles in fishery ecology,and an inappropriate spatio-temporal scale may result in large errors in modeling fish distribution.The objective of this study is to evaluate the roles of spatio-temporal scales in habitat suitability modeling,with the western stock of winter-spring cohort of neon flying squid （Ornmastrephes bartramii） in the northwest Pacific Ocean as an example.In this study,the fishery-dependent data from the Chinese Mainland Squid Jigging Technical Group and sea surface temperature （SST） from remote sensing during August to October of 2003-2008 were used.We evaluated the differences in a habitat suitability index model resulting from aggregating data with 36 different spatial scales with a combination of three latitude scales （0.5°,1 ° and 2°）,four longitude scales （0.5°,1°,2° and 4°）,and three temporal scales （week,fortnight,and month）.The coefficients of variation （CV） of the weekly,biweekly and monthly suitability index （SI） were compared to determine which temporal and spatial scales of SI model are more precise.This study shows that the optimal temporal and spatial scales with the lowest CV are month,and 0.5° latitude and 0.5° longitude for O.bartramii in the northwest Pacific Ocean.This suitability index model developed with an optimal scale can be cost-effective in improving forecasting fishing ground and requires no excessive sampling efforts.We suggest that the uncertainty associated with spatial and temporal scales used in data aggregations needs to be considered in habitat suitability modeling.

Habitat quality assessment of mining cities based on InVEST model—a case study of Yanshan County,Jiangxi Province

The assessment of the spatiotemporal evolution of habitat quality caused by land use changes can provide a scientifc basis for the ecological protection and green development of mining cities.Taking Yanshan County as an example of a typical mining city,this article discussed the spatial pattern and evolution characteristics of habitat quality in 2000 and 2018 based on the ArcGIS platform and the InVEST model.The conclusions are as below:from 2000 to 2018,the area of farmland and construction land changed the most in the study area.Among them,the area of farmland decreased by 3.48%,and the area of industrial and mining land and construction land increased by 53.25%.Areas of low,relatively low and high habitat quality expanded,and areas of medium and relatively high habitat quality shrank,which is closely related to the distribution of land use.The areas with high habitat degradation degrees appear around cities,mining areas and watersheds,while the areas with low habitat degradation degrees are mainly distributed in the southern woodland.The distribution of cold and hot spots in the habitat quality distribution of Yanshan County presents a pattern of“hot in the south and cold in the north”.The results are of great signifcance to the precise implementation of ecosystem management decisions in mining cities and the creation of a landscape pattern of“beautiful countrysides,green cities,and green mines”.

Modeling habitat suitability of range plant species using random forest method in arid mountainous rangelands

Mountainous rangelands play a pivotal role in providing forage resources for livestock, particularly in summer, and maintaining ecological balance. This study aimed to identify environmental variables affecting range plant species distribution, ecological analysis of the relationship between these variables and the distribution of plants, and to model and map the plant habitats suitability by the Random Forest Method(RFM) in rangelands of the Taftan Mountain, Sistan and Baluchestan Province, southeastern Iran. In order to determine the environmental variables and estimate the potential distribution of plant species, the presence points of plants were recorded by using systematic random sampling method(90 points of presence) and soils were sampled in 5 habitats by random method in 0–30 and 30–60 cm depths. The layers of environmental variables were prepared using the Kriging interpolation method and Geographic Information System facilities. The distribution of the plant habitats was finally modelled and mapped by the RFM. Continuous maps of the habitat suitability were converted to binary maps using Youden Index(?) in order to evaluate the accuracy of the RFM in estimation of the distribution of species potentialhabitat. Based on the values of the area under curve(AUC) statistics, accuracy of predictive models of all habitats was in good level. Investigating the agreement between the predicted map, generated by each model, and actual maps, generated from fieldmeasured data, of the plant habitats, was at a high level for all habitats, except for Amygdalus scoparia habitat. This study concluded that the RFM is a robust model to analyze the relationships between the distribution of plant species and environmental variables as well as to prepare potential distribution maps of plant habitats that are of higher priority for conservation on the local scale in arid mountainous rangelands.