Rasoul KARAMIANI, Nasrullah RASTEGAR-POUYANI and Eskandar RASTEGARPOUYANI

1Department of Biology, Faculty of Science, Razi University, Kermanshah 67149, Iran

2Department of Biology, Faculty of Science, Hakim Sabzevari University, Sabzevar, Iran

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) consistantlyin situat their tolerance limits, 2) changing ranges to regions where climate is within the species tolerance limits, 3)extinction (Daviset 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 (Nikolovaet al., 2013). Briefly,the climate of the last interglacial had a relatively stable warm period (Pickarski, 2014). Kerwinet 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 (Texieret al., 2000; Wanneret al.,2008).

Analyzing species distribution models can help in conservation planning (Grahamet al., 2004) and in understanding theoretical research (Phillipset al., 2009)on ecological and evolutionary processes (Daviset al., 2005). Species distribution models can be used to investigate the effect of climate changes on distributions and abundances of species (Thomaset al., 2004), to determine biodiversity (Kleidon and Mooney, 2000), and biogeographical patterns (Yousefkhaniet al., 2013), and predicting potential distribution (Ananjevaet al., 2014),and to appraise possible future changes in the diversity(Ramirez-Villegaset 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 (Elithet al. 2006;Hernandezet al. 2006; Phillipset al., 2006). MaxEnt estimates the probability distribution of maximum entropy (i.e. closest to uniform) based on environmental variables spread over the survey area (Pearsonet al.,2007; Kaliontzopoulouet al., 2008).

The Scincidae family has more than 25% of all living genera and species of lizards (Uetz and Ho?ek, 2016).The genusAblepharusFitzinger, 1823 encompasses 10 valid species:A. bivittatus(Menetries, 1832),A. budakiG?cmen, Kumlutas & Tosunoglu, 1996,A. chernoviDarevsky, 1953,A. darvaziJerem?enko & Panfilov,1990,A. desertiStrauch, 1868,A. grayanus(Stoliczka,1872),A. kitaibelii(Bibron & Bory, 1833),A. lindbergiWettstein, 1960,A. pannonicus(Fitzinger, 1824), andA.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 genusAblepharusin the molecular phylogenic aspect is sister taxon of the central and east AsianAsymblepharus(Pyronet al., 2013).Ablepharusbivittatus(Menetries, 1832),A.grayanus(Stoliczka, 1872) andA.pannonicus(Fitzinger,1824) occur in Iran (Anderson, 1999; Karamianiet al.,2015).

Ablepharus grayanuswas first described asBlepharosteres grayanusfrom Waggur District, northeast Kutch, India (Stoliczka, 1872). Later, Fühn (1969a)regarded it as a subspecies ofA. pannonicusbased on examination of a few specimens (threeA.grayanus,fourA. 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

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

A. pusilusBlanford, 1874 from Basra, Iraq;A. brandtivs.brevipesNikolsky, 1907 from Dech-i-Diz and Karun River, Iran;A. persicusNikolsky, 1907 from Shahrud Iran;A. p. pannonicus,A. p. grayanusFühn 1969a) in wide distribution range ofA. pannonicus, that all species regarded to synonymA. pannonicusby 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.

2. Materials and Methods

2.1. Study area and recordsThe 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 grayanusspecimens were collected and their distribution data were recorded (34 recorded) from Sistan and Baluchestan and Kerman Provinces, southeastern Iran. We gathered distribution data ofA. pannonicusspecimens 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 observedA. pannonicusin between the grasslands, shrubs, and steppes and exact coordinates were marked with GPS (108 recorded).

2.2. Data set and AnalysisWe 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 km2precision (30 s × 30 s) for contemporary (～1950–2000),and 10 km2precision (5 min × 5 min), also examined 19 bioclimatic variables in the past (LIG, and MH)in the related part of the world (Asia) (Hijmanset al.,2005; Otto-Bliesneret 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 Mu?ozet al., 2011), was used. Then we used SPPS IBM (version 22) for Pearson’s correlation coefficient (Elithet 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 (Yousefkhaniet 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 (Phillipset al., 2004;Kaliontzopoulouet 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; Gallienet al., 2012), and values of 0.7–0.9 suggest useful models, the values more than 0.9 indicate high accuracy (Manelet 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) (Hijmanset al., 2001).

3. Results

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 andA. pannonicus= 0.979± 0.007). Moreover, two variables contributed for both species (BIO3, And Slope), six variables forA. grayanus,and six variables forA. pannonicuswere detected separately (Table 1). The last models in the mid-Holocene simulated high AUC values (A. grayanus= 0.975 ± 0.019 andA. pannonicus= 0.988 ± 0.006). In addition, three variables were important for both species, one variable forA. grayanus, and three variables forA. pannonicuswere identified separately (Table 2). The Last Interglacial showed high AUC values (A. grayanus= 0.975 ± 0.019 andA. pannonicus= 0.988 ± 0.006) (Table 3). During this time four variables forA. grayanus, and six variables forA. pannonicuswere recognized separately.

The model forA. grayanuspredicted 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 forA. grayanusthat were more suitable areas than present in southwestern Asia today (Figure 1). The model forA. pannonicuspredicted 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 thatA. pannonicusoccurs 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 forA. pannonicushad 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).

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 forA. grayanus, during three time periods (currently, MH, LIG). In the eastern Iranian PlateauA. grayanusoccurs 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 ofA. grayanusin the United Arab Emirates and Oman but recorded by Gardner(2009) asA. 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).

The suitable habitats forA. pannonicuswere in Iran,Pakistan, Afghanistan, and central Asia (Tajikistan,Turkmenistan, and Uzbekistan). In IranA. 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 withA. bivittatus. Therefore,A. grayanusandA. pannonicusprefer 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.

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.

The occurrence and the present ofA. grayanusis 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 ofA. pannonicusis 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.

The models simulated at the MH distribution ofA.grayanuswas 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 forA. 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 forA. pannonicus. The models simulated at the LIG distribution ofA. grayanuswas influenced by precipitation of the driest month, and the driest quarter of the year (72.7%).A. pannonicus(89.2%) was dependent on temperature.

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.

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.

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

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.

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