1. Introduction

Climate change plays an important role on the species distributions of biota. The response of species to persistent climate changes may be as follows: 1) consistantly in situ at their tolerance limits, 2) changing ranges to regions where climate is within the species tolerance limits, 3)extinction (Davis et al., 2005; Sillero and Carreterob,2012). During the Pleistocene, several ice sheets in the Northern Hemisphere occurred at intervals of around 40,000–100,000 years (Sillero and Carreterob, 2012).The glaciations were separated by interglacial periods(Ray, 1992). During interglacial periods, the climate warmed and forests returned to areas that once supported tundra vegetation (Sillero and Carreterob, 2012). During the Last Interglacial period (LIG: 150,000–120,000 years), temperature gradient increased in polar regions toward lower latitudes and caused sea-level to rise and reduction of ice sheets (Nikolova et al., 2013). Briefly,the climate of the last interglacial had a relatively stable warm period (Pickarski, 2014). Kerwin et al. (1999)simulated terrestrial conditions at the mid-Holocene (6 ka), that indicated summer temperatures were warmer than at present in the high-latitude Northern Hemisphere.But during the mid-Holocene, northern Africa, Arabia,and southern Asia underwent conditions much wetter than at present, these conditions resulting in both African and Asian monsoons (Texier et al., 2000; Wanner et al.,2008).

1.字理识字。语文课程标准指出：“语文课程应特别关注汉语言文字的特点对学生识字写字的影响”。我国的汉字在其演变、构字上均有其特点，教师应该遵循字理帮助学生识字。

Analyzing species distribution models can help in conservation planning (Graham et al., 2004) and in understanding theoretical research (Phillips et al., 2009)on ecological and evolutionary processes (Davis et al., 2005). Species distribution models can be used to investigate the effect of climate changes on distributions and abundances of species (Thomas et al., 2004), to determine biodiversity (Kleidon and Mooney, 2000), and biogeographical patterns (Yousefkhani et al., 2013), and predicting potential distribution (Ananjeva et al., 2014),and to appraise possible future changes in the diversity(Ramirez-Villegas et al., 2014). Lizards, like other ectotherms (Barabanov and Litvinchuk, 2015), provide excellent models for analysis of species distribution under climate change (Sillero and Carreterob, 2012). MaxEnt is a general approach for characterizing probability distributions from small sample sizes (Elith et al. 2006;Hernandez et al. 2006; Phillips et al., 2006). MaxEnt estimates the probability distribution of maximum entropy (i.e. closest to uniform) based on environmental variables spread over the survey area (Pearson et al.,2007; Kaliontzopoulou et al., 2008).

河横村并不是单独发展农业经济，同时还在大力发展旅游业。河横村拥有近千亩油菜花。与全国其它油菜花景区不同的是，河横油菜花田里有20多种油菜花，这些品种的油菜花来自省内外十多家科研机构，被誉为“中国最有科技含量的油菜花海”。一年一度的中国河横菜花节创办于2005年，13年来，河横菜花节集中展示了河横生态建设和新农村建设取得的成果，放大了河横的生态效应，提升了河横的品牌形象，丰富了河横的旅游资源。

The Scincidae family has more than 25% of all living genera and species of lizards (Uetz and Hošek, 2016).The genus Ablepharus Fitzinger, 1823 encompasses 10 valid species: A. bivittatus (Menetries, 1832), A. budaki Göcmen, Kumlutas & Tosunoglu, 1996, A. chernovi Darevsky, 1953, A. darvazi Jeremčenko & Panfilov,1990, A. deserti Strauch, 1868, A. grayanus (Stoliczka,1872), A. kitaibelii (Bibron & Bory, 1833), A. lindbergi Wettstein, 1960, A. pannonicus (Fitzinger, 1824), and A.ruppellii (Gray, 1839) which are distributed in Europe,Turkey, Syria to Egypt, Azerbaijan, Armenia, Caucasus,Tajikistan, Kazakhstan, Kyrgyzstan, Uzbekistan,Turkmenistan, Afghanistan, Iran, Iraq, United Arab Emirates, Pakistan, NW India (Leviton 1959; Fühn 1969a,b; Anderson, 1999; Khan 2002; Vyas, 2011). The genus Ablepharus in the molecular phylogenic aspect is sister taxon of the central and east Asian Asymblepharus (Pyron et al., 2013). Ablepharusbivittatus (Menetries, 1832), A.grayanus (Stoliczka, 1872) and A.pannonicus (Fitzinger,1824) occur in Iran (Anderson, 1999; Karamiani et al.,2015).

2.2. Data set and Analysis We implemented Maximum Entropy modeling (MaxEnt, 3.3.3e http://www.cs.princeton.edu/～schapire/MaxEnt) of species geographic distributions with default parameters of the data to test samples. We examined 19 bioclimatic variables and two topographical variables with grids approximately 1 km2 precision (30 s × 30 s) for contemporary (～1950–2000),and 10 km2 precision (5 min × 5 min), also examined 19 bioclimatic variables in the past (LIG, and MH)in the related part of the world (Asia) (Hijmans et al.,2005; Otto-Bliesner et al., 2006; www.worldclim.org)(see the Appendix). To identify the correlation ratios between variables and presence records, Openmodeller(V. 1.0.7) (de Souza Muñoz et al., 2011), was used. Then we used SPPS IBM (version 22) for Pearson’s correlation coefficient (Elith et al., 2006). We selected variables with a Pearson correlation lower than 0.75 to choose the variables that are ecologically important for species separation according to our observations and to describe habitat (Yousefkhani et al., 2016). We conducted MaxEnt software with 10 replicates of the analysis that yield the best model for the studied species. MaxEnt provides state distribution models by the receiver operating characteristic (ROC) plots, ROC curves plot true-positive rate against false-positive rate (Phillips et al., 2004;Kaliontzopoulou et al., 2008). A value of the area under the curve (AUC) of 0.5–0.7 is taken to indicate that the result is a stochastic prediction (Raes and ter Steege,2007; Gallien et al., 2012), and values of 0.7–0.9 suggest useful models, the values more than 0.9 indicate high accuracy (Manel et al., 2001). We used DIVA-GIS 7.3.0.1 software for the mean predicted map and a logistic output of presence records with suitability ranging that show from zero (unsuitable habitat) to one (the best suitable habitat) (Hijmans et al., 2001).

The suitable habitats for A. pannonicus were in Iran,Pakistan, Afghanistan, and central Asia (Tajikistan,Turkmenistan, and Uzbekistan). In Iran A. pannonicus,was present in the majority of habitat types (Anderson,1999) except deserts, showing the effect of barriers on dispersion of the terrestrial species. This lizard inhabited palm groves (Abadan, and Mahshahr), Karoon River shore region and Darvishab River Park of Khuzestan Province, southwestern Iran (Figure 3). It was absent in the steppes of northwestern Iran, probably, due to competition with A. bivittatus. Therefore, A. grayanus and A. pannonicus prefer different climatic conditions across the Middle East and Central Asia. In addition, our results showed that the distributions of these species are restricted by different climatic conditions.

2.1. Study area and records The study area encompasses the whole Iranian territory. We assembled the species occurrence data for each species based on a systematic biological survey by walking randomly through the habitat from 09:00 to 12:00 AM and 15:00 PM to evening(much of the activity time of species) during spring to summer 2010 and 2015. We used localities mentioned in previous studies (e. g. Anderson, 1999; Vyas, 2011).Ablepharus grayanus specimens were collected and their distribution data were recorded (34 recorded) from Sistan and Baluchestan and Kerman Provinces, southeastern Iran. We gathered distribution data of A. pannonicus specimens collected under rocks or leaves on the floor of oak forest in the Zagros Mountains, and in between the meadow grass in the Darvishab River Park (Baghmalek,Khuzestan Province) and recorded the exact location using the Global Positioning System (GPS). In other areas (Esfahan, Ilam, Kermanshah, Khorasan Razavi,Kurdistan, Lorestan, Mazandaran, Qum, Semnan, Zanjan,and Yassuj Provinces), we observed A. pannonicus in between the grasslands, shrubs, and steppes and exact coordinates were marked with GPS (108 recorded).

2. Materials and Methods

A. pusilus Blanford, 1874 from Basra, Iraq; A. brandti vs. brevipes Nikolsky, 1907 from Dech-i-Diz and Karun River, Iran; A. persicus Nikolsky, 1907 from Shahrud Iran; A. p. pannonicus, A. p. grayanus Fühn 1969a) in wide distribution range of A. pannonicus, that all species regarded to synonym A. pannonicus by Anderson (1999).The general aim of this work is, (1) to identify potential areas of distribution during three periods of the past: Last Interglacial (LIG: ～120,000–140,000 years BP)mid-Holocene (MH: ～6,000 years BP), (2) to describe current (～1950–2000) distribution, suitable habitat,and understand the biogeographical patterns of the two mentioned species in Asia.

Ablepharus grayanus was first described as Blepharosteres grayanus from Waggur District, northeast Kutch, India (Stoliczka, 1872). Later, Fühn (1969a)regarded it as a subspecies of A. pannonicus based on examination of a few specimens (three A.grayanus,four A. pannonicus). Ablepharus grayanus (Stoliczka,1872) is now regarded as a distinct species. Ablepharus grayanus (Stoliczka, 1872) has distribution range from northern and western India through Pakistan and Afghanistan to eastern Iran (Anderson, 1999; Karamiani

3. Results

The model for A. grayanus predicted the distribution range presence of the species in the riparian, and wet areas of northwest India, through Pakistan, Afghanistan, and oases and Palm groves of the eastern, and southeastern Iran. That distribution of the species was verified by using a comparison of environmental variables. Moreover,the climate variables model suggests that there are more suitable potential regions in the United Arab Emirates,Oman, Saudi Arabia, Iraq, Jordan, central Turkey, north Syria, south Turkmenistan and Uzbekistan, west of China. The MH and the LIG simulated the distribution model for A. grayanus that were more suitable areas than present in southwestern Asia today (Figure 1). The model for A. pannonicus predicted the occurrence of range of the species in steppe areas, grassy, rocky hills separated by Oak forest of the Zagros Mountains in the west, and palm groves in southwestern Iran. In addition to the mentioned habitat, the distribution range model of the species predicted that A. pannonicus occurs in Iraq,Kuwait, Pakistan, Afghanistan, Tajikistan, Turkmenistan,Uzbekistan, and suitable potential northeast in Syria,Turkey, Kazakhstan, and patchwork areas of northern India. The simulated MH distribution range model for A. pannonicus had continuous restriction in east Syria,throughout Iraq, north Saudi Arabia toward southeastern Turkmenistan. Also, simulated suitable potential fragmented areas of north India, and central China were demonstrated. The LIG simulated distribution ranges were the same as the MH suitable potential habitat (Figure 2).

The final models in the present study showed good match and closely fitted the presence of the two species recorded in the study areas, as suggested by high AUC values (A.grayanus = 0.929 ± 0.087 and A. pannonicus = 0.979± 0.007). Moreover, two variables contributed for both species (BIO3, And Slope), six variables for A. grayanus,and six variables for A. pannonicus were detected separately (Table 1). The last models in the mid-Holocene simulated high AUC values (A. grayanus = 0.975 ± 0.019 and A. pannonicus = 0.988 ± 0.006). In addition, three variables were important for both species, one variable for A. grayanus, and three variables for A. pannonicus were identified separately (Table 2). The Last Interglacial showed high AUC values (A. grayanus = 0.975 ± 0.019 and A. pannonicus = 0.988 ± 0.006) (Table 3). During this time four variables for A. grayanus, and six variables for A. pannonicus were recognized separately.

4. Discussion

Our results verify the known distribution of the minor snake-eyed skink (A. grayanus), and Asian snakeeyed skink (A. pannonicus) based on current climatic conditions. The eastern regions of the Iranian Plateau, part of the areas of Afghanistan, northwest India, and Pakistan had the highest suitability for A. grayanus, during three time periods (currently, MH, LIG). In the eastern Iranian Plateau A. grayanus occurs in the natural Parks (e.g.,Khobar National Park, and the area of the Presidential Museum in Rafsanjan, Kerman Province), and Palm graves (Sistan and Baluchestan Province). Recorded from Pakistan at oases, grasslands, backyard gardens, grass fields in the Indus riparian system by Khan (1999, 2012).Vyas (2011) mentioned three localities (Wagger village of Kutch district, Gujarat; Mount Abu of Sirohi district,Rajasthan; Jassore Wildlife Sanctuary, Gujarat) from India for the species. Model ranges of current distribution predicted areas of western Afghanistan that had conditions suitable as for the same regions mentioned in Pakistan.The model predicted the presence of A. grayanus in the United Arab Emirates and Oman but recorded by Gardner(2009) as A. pannonicus.

Figure 1 Distribution map of Ablepharus grayanus in southwestern Asia and much of their potential distribution pattern in the region during: A) currently (1950-2000), B) the mid-Holocene (6 ka), C) the last interglacial (120 ka).

et al., 2015). Researchers based on the morphological characters identified different species and subspecies(A. brandtii Strauch, 1868 from Samarkand, Turkestan;

The occurrence and the present of A. grayanus is more influenced by precipitation of the driest quarter of the year (24%), mean temperature of the coldest quarter of the year (23.3%), and precipitation of the driest month(18.45%). Therefore, it is more likely to be found in hot regions under the influence of the rainy monsoon.The prevalence of A. pannonicus is more impacted by temperature seasonality (27%), slope (19.2%), and mean temperature of the wettest quarter of the year (18.5%).Due to relationship between temperature and humidity,we claim that seasonal temperatures, especially during the spring are the most effective factors for suitable habitat.

Figure 2 Distribution map of Ablepharus pannonicus in southwestern Asia and much of their potential distribution pattern in the region during: A) currently (1950-2000), B) the mid-Holocene (6 ka), C) the last interglacial (120 ka).

Figure 3 Habitat of Ablepharus pannonicus in Kermanshah, Ilam Provinces, western (A-B), Khuzestan (C), and Fars (D) Provinces southwestern Iran. The specimens were collected under a relatively small plate stone or under the dead Oak leaves, grassland, or steppes; E-F:Habitat of Ablepharus grayanus in southeastern Iran. The specimens were found under the dead Palm leaves, and grassland in Parks.

(1)引导学生自主提问评估，理清问题思维.在对物理知识进行学习时，由于物理学科需要较强的逻辑思维，因此学生的发散思维在物理学习过程中起着重要的作用.因此在物理学习中作为教师应引导学生善于提出疑问、进行自我提问、进行自我评估.这样学生不仅能够理解题意、剖析题意，更能从深层次掌握该题的内涵，从而具有清晰的解题思路，提高解题效率.

The models simulated at the MH distribution of A.grayanus was highly influenced by precipitation of the driest quarter of the year (59.7%), isothermality(22.8), and mean temperature of the driest quarter of the year (15.3) resulted from both African and Asian rainymonsoons. Those established damp environments and stable habitats for A. grayanus. The another species was highly (79.6%) dependent on temperature (isothermality,temperature seasonality, mean temperature of the wettest quarter of the year, temperature annual range)that indicated the importance of temperature in range extension for A. pannonicus. The models simulated at the LIG distribution of A. grayanus was influenced by precipitation of the driest month, and the driest quarter of the year (72.7%). A. pannonicus (89.2%) was dependent on temperature.

2016年全国民政工作会议上提出，要依靠标准化实施民政服务对象保障政策，提高民政管理服务水平，防范民政工作风险，实现民政部门政府职能的转变。近年来，随着社会的开放性发展，社会工作的专业化、职业化以及标准化的纵深发展，在应对转型期婚姻家庭问题中具有专业优势，为婚姻家庭社会工作服务的实践发展提供了可能性。

Table 1 Relative of variables (in percentages) at the current (1950-2000) used in MaxEnt model for the two studied species of the genus Ablepharus.

Variable Description of variables A. grayanus A. pannonicus BIO2 Annual daily temperature difference (minimal temperature maximal temperature) 0.5 BIO3 Isothermality [(BIO2 / BIO7) × 100] 11.4 8.2 BIO4 Temperature seasonality (standard deviation × 100) 27 BIO5 Maximum temperature of the warmest month 1.1 BIO8 Average temperature of the wettest quarter of the year 18.5 BIO9 Average temperature of the driest quarter of the year 23.3 BIO11 Average temperature of the coldest quarter of the year 16 BIO14 Precipitation of the driest month 18.4 BIO15 Seasonality of precipitation (coefficient of variation)10.5 BIO17 Precipitation of the driest quarter of the year 24 BIO19 Precipitation of the coldest quarter of the year 15.4 Slope Slope 6.5 19.2

Table 2 Relative of variables (in percentages) at the mid-Holocene (6 ka) used in MaxEnt model for the two studied species of the genus Ablepharus.

Variable Description of variables A. grayanus A. pannonicus BIO2 Annual daily temperature difference (minimal temperature maximal temperature) 2.1 0.6 BIO3 Isothermality [(BIO2 / BIO7) × 100] 22.8 33.9 BIO4 Temperature seasonality (standard deviation × 100) 27.5 BIO7 Temperature annual range (BIO5 - BIO6) 59.7 1 BIO8 Average temperature of the wettest quarter of the year 16.6 BIO9 Mean temperature of the driest quarter of the year 15.3 BIO15 Seasonality of precipitation (coefficient of variation)20.3

Table 3 Relative of variables (in percentages) at the Last Interglacial (120 ka) used in MaxEnt model for two species of the genus Ablepharus.

Variable Description of variables A. grayanus A. pannonicus BIO2 Annual daily temperature difference (minimal temperature maximal temperature) 15.5 BIO3 Isothermality [(BIO2 / BIO7) × 100] 28.8 BIO4 Temperature seasonality (standard deviation × 100) 17 BIO7 Temperature annual range (BIO5 - BIO6) 7.2 BIO8 Average temperature of the wettest quarter of the year 20.7 BIO9 Average temperature of the driest quarter of the year 8.5 BIO14 Precipitation of the driest month 56 BIO15 Seasonality of precipitation (coefficient of variation)10.7 BIO17 Precipitation of the driest quarter of the year 16.4 BIO19 Precipitation of the coldest quarter of the year 19.2

From the last simulation models (6 and 120 thousand years ago) it is clear that in those times wider distribution ranges and areas that are now part of unsuitable habitat,at that time, due to better climatic and environmental conditions influenced by monsoon rainfall, would have been favorable habitat. Finally, study of the effective bioclimatic variables in a species’ distribution over time provide heuristic methods for the management of important habitat by conservation assessments of current habitats and identification of habitats suitability.According to results obtained based on this study, the minor snake-eyed skink, A. grayanus, and the Asian snake-eyed skink, A. pannonicus, are good indicators for assessing the effects of climatic changes on distribution range of the species over time, and for understanding biodiversity patterns in Asia.

通过MEGA6.0计算出所测核苷酸序列中变异碱基的比例，代表氨基酸的变异，用平均进化距离（P-distance）表示差异的大小。将本研究中的MV野毒株序列与GenBank的A基因型疫苗株、H1及H2参考株进行组内及组间的遗传距离计算及比较。

References

Ananjeva N. B., Golynsky E. A., Hosseinian Y. S. S., Masroor R. 2014. Distribution and environmental suitability of the smallscaled rock agama, Paralaudakia microlepis (Sauria:Agamidae) in the Iranian Plateau. Asian Herpetol Res, 5(3):161–167

Anderson S.C. 1999. The Lizards of Iran. Society for the study of Amphibians and Reptiles, Oxford, Ohio, 442 pp

Barabanov A. V., Litvinchuk S. N. 2015. A new record of the Kurdistan newt (Neurergus derjugini) in Iran and potential distribution modeling for the species. Rus J Herpetol, 22(2):107–115

Davis M. B., Shaw R. G., Etterson J. R. 2005. Evolutionary responses to changing climate. Ecology, 86(7): 1704–1714

de Souza Muoz M. E., De Giovanni R., de Siqueira M. F.,Sutton T., Brewer P., Pereira R. S., Canhos D. A. L., Canhos V. P. 2011. OpenModeller: A generic approach to species’potential distribution modelling. GeoInformatica, 15(1): 111–135

Elith J., Graham C. H., Anderson R. P., Dudk M., Ferrier S.,Guisan A., Hijmans R. J., Huettmann F., Leathwick J. R.,Lehmann A., Li J., Lohmann L. G., Loiselle B. A., Manion G., Moritz C., Nakamura M., Nakazawa Y., Overton J. M.,Peterson A. T., Phillips S. J., Richardson K. S., Scachetti-Pereira R., Schapire R. E., Soberon J., Williams S., Wisz M. S., Zimmermann N. E. 2006. Novel methods improve prediction of species’ distributions from occurrence data.Ecography, 29(2): 129–151

Fühn I. 1969a. Revision and redefinition of the genus Ablepharus Lichtenstein, 1823 (Reptilia, Scincidae). Rev Roum Biol Zool,14: 23–41

Fühn I. 1969b. The “Polyphyletic” origin of the genus Ablepharus(Reptilia, Scincidae): a case of parallel evolution. J Zool Syst Evol Res, 7(1): 67–76

Gallien L., Douzet R., Pratte S., Zimmermann N. E., Thuiller W. 2012. Invasive species distribution models–how violating the equilibrium assumption can create new insights. Glob Ecol Biogeogr, 21(11): 1126–1136

Gardner A. 2009. Mapping the terrestrial reptile distributions in Oman and the United Arab Emirates. ZooKeys, 31: 165

Graham C. H., Ferrier S., Huettman F., Moritz C., Peterson A.T. 2004. New developments in museum-based informatics and applications in biodiversity analysis. Trend Ecol Evol, 19(9):497–503

Hernandez P. A., Graham C. H., Master L. L., Albert D. L.2006. The effect of sample size and species characteristics on performance of different species distribution modeling methods.Ecography, 29(5): 773–785

Hijmans R. J., Cameron S. E., Parra J. L., Jones P. G., Jarvis A. 2005. Very high resolution interpolated climate surfaces for global land areas. Int J Climatol, 25(15): 1965–1978

Hijmans R., Cruz M., Rojas E., Guarino L. 2001. DIVAGIS, version 1.4. A geographic information system for the management and analysis of genetic resources data. Plant Genet Resour Newsl, 127: 15–19

Kaliontzopoulou A., Brito J., Carretero M., Larbes S., Harris D. 2008. Modelling the partially unknown distribution of wall lizards (Podarcis) in North Africa: ecological affinities, potential areas of occurrence, and methodological constraints. Can J Zool,86(9): 992–1001

Karamiani R., Rastegar-Pouyani N., Rastegar-Pouyani E.,Akbarpour M., Damadi E. 2015. Verification of the Minor Snake-eyed Skink, Ablepharus grayanus (Stoliczka, 1872)(Sauria: Scincidae), from Iran. Zool Middle East, 61(3): 226–230

Kerwin M. W., Overpeck J. T., Webb R. S., DeVernal A.,Rind D. H., Healy R. J. 1999. The role of oceanic forcing in mid-Holocene northern hemisphere climatic change.Paleoceanography, 14(2): 200–210

Khan M. S. 1999. Herpetology of habitat types of Pakistan. Pak J Zool, 31(3): 275–289

Khan M. S. 2002. Key and checklist to the lizards of Pakistan.Herpetozoa, 15(3/4): 99–119

Khan M. S. 2012. Herpetological Laboratory. In SERIES F. G.,Pakistan J. (Eds.), Zool Suppl Ser, 11: 1–12

Kleidon A., Mooney H. A. 2000. A global distribution of biodiversity inferred from climatic constraints: results from a process-based modelling study. Glob Chan Biol, 6(5): 507–523

Leviton A. E. 1959. Report on a collection of reptiles from Afghanistan. Proc California Acad Sci, 29: 445–463

Manel S., Williams H. C., Ormerod S. J. 2001. Evaluating presence-absence models in ecology: The need to account for prevalence. J Appl Ecol, 38(5): 921–931

Nikolova I., Yin Q., Berger A., Singh U. K., Karami M. 2013.The last interglacial (Eemian) climate simulated by LOVECLIM and CCSM3. Clim Past, 9(4): 1789–1806

Otto-Bliesner B. L., Marshall S. J., Overpeck J. T., Miller G.H., Hu A. 2006. Simulating Arctic climate warmth and icefield retreat in the last interglaciation. Science, 311(5768): 1751–1753

Pearson R. G., Raxworthy C. J., Nakamura M., Townsend Peterson A. 2007. Predicting species distributions from small numbers of occurrence records: a test case using cryptic geckos in Madagascar. J Biogeogr, 34(1): 102–117

Phillips S. J., Anderson R. P., Schapire R. E. 2006. Maximum entropy modeling of species geographic distributions. Ecol Model, 190(3): 231–259

Phillips S. J., Dudk M., Elith J., Graham C. H., Lehmann A., Leathwick J., Ferrier S. 2009. Sample selection bias and presence–only distribution models: Implications for background and pseudo-absence data. Ecol Appl, 19(1): 181–197

Phillips S. J., Dudk M., Schapire R. E. 2004. A maximum entropy approach to species distribution modeling. Proceedings of the twenty-first international conference on Machine learning. 83pp

Pickarski N. 2014. Vegetation and climate history during the last glacial-interglacial cycle at Lake Van, eastern Anatolia. Thesis.Universitts-und Landesbibliothek Bonn.

Pyron R. A., Burbrink F. T., Wiens J. J. 2013. A phylogeny and revised classification of Squamata, including 4161 species of lizards and snakes. BMC Evol Biol, 13(1): 1

Raes N., ter Steege H. 2007. A null-model for significance testing of presence–only species distribution models. Ecography, 30(5):727–736

Ramirez-Villegas J., Cuesta F., Devenish C., Peralvo M., Jarvis A., Arnillas C. A. 2014. Using species distributions models for designing conservation strategies of Tropical Andean biodiversity under climate change. J Nat Cons, 22(5): 391–404

Ray L. L. 1992. The Great Ice Age. US Department of the Interior,US Geological Survey

Sillero N., Carretero M. A. 2013. Modelling the past and future distribution of contracting species. The Iberian lizard Podarcis carbonelli (Squamata: Lacertidae) as a case study. Zoologischer Anzeiger–J Comp Zool, 252(3): 289–298

Texier D., De Noblet N., Braconnot P. 2000. Sensitivity of the African and Asian monsoons to mid-Holocene insolation and data-inferred surface changes. J Clim, 13(1): 164–181

Thomas C. D., Cameron A., Green R. E., Bakkenes M.,Beaumont L. J., Collingham Y. C., Erasmus B. F., De Siqueira M. F., Grainger A., Hannah L. 2004. Extinction risk from climate change. Nature, 427(6970): 145–148

Uetz P., Hoek J. 2016. The Reptile Database. http://www. reptiledatabase. org

Vyas R. 2011. Preliminary Survey on Reptiles of Jassore Wildlife Sanctuary, Gujarat State, India. Russ J Herpetol, 18(3): 210–214

Wanner H., Beer J., Bütikofer J., Crowley T. J., Cubasch U.,Flückiger J., Goosse H., Grosjean M., Joos F., Kaplan J. O.2008. Mid-to Late Holocene climate change: An overview. Quat Sci Rev, 27(19): 1791–1828

Yousefkhani S. S. H., Ficetola G. F., Rastegar-Pouyani N.,Ananjeva N. B., Rastegar-Pouyani E., Masroor R. 2013.Environmental suitability and distribution of the Caucasian Rock Agama, Paralaudakia caucasia (Sauria: Agamidae) in western and central Asia. Asian Herpetol Res, 4(3): 207–213

Yousefkhani S. S. H., Tehrani S. J., Moodi B., Gül S. 2016.Distribution patterns and habitat suitability for three species of the genus Hyla Laurenti, 1768 in the Western Palearctic. Turk J Zool, 40(2): 257–261