Acta Herpetologica 17(2): 165-175, 2022 ISSN 1827-9635 (print) © Firenze University Press ISSN 1827-9643 (online) www.fupress.com/ah DOI: 10.36253/a_h-13089 Ecological niche differentiation in the Anatolian rock lizards (Genus: Anatololacerta) (Reptilia: Lacertidae) of the Anatolian Peninsula and Aegean Islands Mehmet Kürşat Şahin1,*, Kamil Candan2,3, Danae Karakasi4, Petros Lymberakis4, Nikos Poulakakis4,5,6, Yusuf Kumlutaş2,3, Elif Yıldırım2,3, Çetin Ilgaz2,3 1 Department of Biology, Kamil Özdag Faculty of Science, Karamanoglu Mehmetbey University, Karaman, Turkey 2 Department of Biology, Faculty of Science, Dokuz Eylül University, Buca, İzmir, Turkey 3 Research and Application Center for Fauna Flora, Dokuz Eylül University, Buca, İzmir, Turkey 4 Natural History Museum of Crete, School of Sciences and Engineering, University of Crete, Knossos Av, 71409 Irakleio, Greece 5 Department of Biology, School of Sciences and Engineering, University of Crete, Vassilika Vouton, 70013, Irakleio, Greece 6 Institute of Molecular Biology and Biotechnology (IMBB), Foundation for Research and Technology – Hellas (FORTH), N. Plastira 100, Vassilika Vouton, GR-70013 Irakleio, Greece *Corresponding author. Email: yasambilimci.kursat@gmail.com Submitted on: 2022, 9th May; revised on: 2022, 8th June; accepted on: 2022, 27th June Editor: Mattia Falaschi Abstract. The genus Anatololacerta is distributed in the eastern Mediterranean region including Asia Minor and some east Aegean islands. Recent phylogenetic studies suggested that this genus displayed cryptic diversity and was divided into five species: A. anatolica, A. pelasgiana, A. ibrahimi, A. finikensis and A. danfordi. The ecological niche differ- entiations of these species have not been studied so far. Our aims for this study were to predict the potential suit- able habitats for the species nested in genus Anatololacerta, and to examine the niche overlaps and differentiations via identity and background tests. The occurrence data were obtained from literature and our own field surveys. Occur- rence records were rarefied and assessed in a 30 arc-second resolution layer, compatible with several bioclimatic and topographic variables. Species distribution analyses were performed using maximum entropy approach and pairwise niche comparisons were evaluated by identity and background tests. Our results demonstrated that the species delim- itation among this genus was not only affected by geographic isolation but also that precipitation and temperature influenced the habitat suitability for these species. Predicted suitability usually well matched the actual species distri- butions. Moreover, the niche overlap (identity test) analyses verified that allopatric Anatololacerta species show clear ecological differentiations. However, a niche overlap between parapatric species A. pelasgiana and A. finikensis, was confirmed by identity and background tests. It has been suggested that these parapatric species could be more affected by microclimatological parameters than the others. The results of our study are in agreement with the latest phyloge- netic study within this genus. Keywords. Squamata, Anatololacerta, niche overlap, precipitation, temperature, MaxEnt, Anatolia. INTRODUCTION Ecological factors, e.g., climatic factors, significantly affect the distribution of organisms and may lead to for- mation of new species (Zhao et al., 2019). Each species often has unique ecological niche characteristics and as a result of it, ecological needs differ even for sympatric or sister species (Soberon and Peterson, 2005). Quantifying 166 Mehmet K. Şahin et alii and visualizing the effects of spatial and temporal eco- logical patterns on speciation processes have contributed to our knowledge of interactions between species and their environments (Jezkova and Wiens, 2018; Kurnaz et al., 2019; Şahin et al., 2021). In the last two decades, Ecological Niche Modeling (ENM) was frequently used to better understand these processes. ENM is a method used to predict the habitat suitability of species across space by using occurrence records and bioclimatic and topographic variables (Barve et al., 2011; Kass et al., 2018; Hosseinian Yousefkhani et al., 2019). Moreover, ENM is a very beneficial approach to better understand aspects of conservation, ecology, distribution, and evolutionary history of the species (Guisan and Zimmermann, 2000; Araújo et al., 2006; Phillips et al., 2006). Latest tool devel- opments in modeling studies such as ENMTools (War- ren et al., 2021), ENMeval (Muscarella et al., 2014) and kuenm (Cobos et al., 2019) provide frameworks able not only to generate maps but also to assess the niche overlap and the possible degree of differentiation among multiple species. The complex geological history of Western Asia has shaped the Anatolian Peninsula, the Caucasus Moun- tains, and the Iranian steppes, resulting in high variations in vegetation covers and topographic patterns in these regions (Rajabizadeh et al., 2016). In addition, many environmental dynamics, like atmospheric concentrations of greenhouse gases, precipitation and temperature fluc- tuations, alterations in land use and cover have influence on ecosystem and biodiversity structure in Mediterranean Basin (Klausmeyer and Shaw, 2009). Despite some parts of the Anatolian Peninsula and its close areas have been studied in terms of ENM species distribution analysis for several herptile species (Gül et al., 2015, 2016, 2018; Hosseinian Yousefkhani et al., 2016, 2019; Heidari, 2019; Candan et al., 2021; Kurnaz and Şahin, 2021a), the west- ern part of the peninsula and/or with Aegean Islands and Cyprus has still been less represented (Kıraç et al., 2022). The herpetofauna in the Anatolian Peninsula and Aegean Islands is rich (180 species) (Kurnaz, 2020; Baran et al., 2021; Yaşar et al., 2021), almost as the 60 % of whole European continent (301 species) (Speybroeck et al., 2020). Besides, recent discoveries of the new species have been making the herpetofauna richer (Tuniyev et al., 2018; Jablonski et al., 2019; Yılmaz et al., 2021; Kur- naz and Şahin, 2021b; Arribas et al., 2022; Kurnaz et al., 2022). However, even though this region has been inves- tigated in several biogeographic or phylogeographic stud- ies (Kornilios et al., 2012; Skourtanioti et al., 2016; Kot- sakiozi et al., 2018; Bozkurt and Olgun, 2020), the effects of environmental conditions on the distribution of reptile species or subpopulations are being studied only in the last decade (Fattahi et al., 2014; Gül et al., 2015; Hos- seinian Yousefkhani et al., 2019; Kurnaz and Hosseinian Yousefkhani, 2020, 2021). Anatololacerta Arnold, Arribas & Carranza, 2007 is an Eastern Mediterranean lacertid genus that is distrib- uted along the western and southern parts of Anatolia and some Aegean islands (Karakasi et al., 2021). How- ever, taxonomic debates on some populations of this genus have been historically controversial. Species of this genus represent an example of cryptic diversity (Bellati et al., 2015; Candan et al., 2016), a common phenomenon among lacertids (Kaliontzopoulou et al., 2012; Barata et al., 2012; Tamar et al., 2015; Freitas et al., 2016; Psonis et al., 2017; Šmíd et al., 2017; Mendes et al., 2018). The recent study on the phylogenetic relationships of Anato- lolacerta clades (Karakasi et al., 2021) classified them into five species: i) Anatololacerta anatolica (Werner, 1900) distributed in northwestern Anatolia, Ikaria and Samos islands ii) Anatololacerta pelasgiana (Mertens, 1959) in southwestern Anatolia, Symi and Rodos islands iii) Ana- tololacerta finikensis (Eiselt & Schmidtler, 1987) in west- ern part of Mediterranean region and Psomi island iv) Anatololacerta ibrahimi (Eiselt & Schmidtler, 1987) cen- tral part of Mediterranean region v) Anatololacerta dan- fordi (Günther, 1876) in eastern Mediterranean region. Therefore, the cryptic diversity within this genus inspired us to test if the species delimitations can be affected by bioclimatological and/or topographic factors. That’s why the objectives of the present study are i) to predict highly suitable areas for each Anatololacerta species distribution and determine which environmental factors are impor- tant; ii) to measure and compare the niche divergence within the genus Anatololacerta, as a case study for cryp- tic species. MATERIALS AND METHODS Study area and input data This study was conducted within 25-37° East Longi- tude and 34.5-41° North Latitude, covering the western and southern parts of Anatolia and Aegean islands (Fig. 1). A total of 159 occurrence data (31 for A. anatolica, 46 for A. pelasgiana, 22 for A. finikensis, 37 for A. ibrahimi, and 23 for A. danfordi) were obtained from field surveys and literature (Eiselt and Schmidtler, 1986; Mulder, 1995; Baran and Kumlutaş, 1999; Kumlutaş et al., 2015; Yakın and Tok, 2015; Beşer, 2015; Bellati et al., 2015; Candan et al., 2016; Sarıkaya et al., 2017; Beşer et al., 2020; Karakasi et al., 2021). The raw input data for localities are given in Table S1. Data for these species were error-checked and improved to meet appropriate standards for ecological 167Ecological niche differentiation in the Anatolian rock lizards niche modeling in two steps. Firstly, georeferenced data were checked for error and data consistency for geo- graphic coordinates (Chapman, 2005). Secondly, in order to avoid spatial sampling biases and misinterpretation of the habitat suitability analysis and niche overlap tests, the occurrence records for each species were spatially rarefied with keeping one locality in each 2 km by SDM Toolbox 2.0 (Brown, 2014). Nineteen bioclimatic and one topographic variables were downloaded from WorldClim version 2.1 (Fick and Hijmans, 2017). The bioclimatic data were generated from global ESRI grids for current conditions (~1970- 2000). Additionally, three topographic variables were obtained from the studies of Gavashelishvili and Tarkh- nishvili (2016), and Gavashelishvili et al. (2018). All these environmental variables were at 30 arc-second resolution (~1 km) (Table S2) and each layer was clipped for the study area in ArcGIS 10.6.1 (ESRI, California, CA, USA) for the whole study area. Pearson Correlations between variables were calculated in R v4.1.3 (R Core Team, 2020) and highly correlated variables were eliminated (r ≥ |0.8|) (Fig. S1). Ecological niche modeling Due to its robustness and dependence on presence and pseudo-absence data, maximum entropy approach was used for niche modelling. The maximum entropy algorithm, which generates the probability of presence of a given species that varies between 0 to 1, provides pre- dictions from presence and pseudo-absence data (Phillips et al., 2009). A total of 2000 background points for each species were randomly sampled across the study area. The potential habitat suitability was modeled by using the kuenm package in R for the implementation of Max- Fig. 1. Species occurrence records for genus Anatololacerta in the Anatolian Peninsula and Aegean Islands. 168 Mehmet K. Şahin et alii Ent 3.4.1 (Phillips et al., 2017; Cobos et al., 2019). To cre- ate the models for each Anatololacerta species, 80 % of the occurrences were used for the creation of candidate models and the remaining 20 % for independent presence as test data. The bioclimatic and topographic envelopes, derived from environmental variables, were constructed as set for each species (Table 1). Model selection To optimize model complexity for all 5 species, 31 combinations of MaxEnt’s 5 feature classes [hinge (h), threshold (t), product (p), quadratic (q) and linear (l)] along with 17 regulation multiplier values (0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9, 1, 2, 3, 4, 5, 6, 8, 10) were evaluated. Using these combinations allowed us an opti- mal approach for generating diverse candidate models in order to select the models that explain our data best (Muscarella et al., 2014; Cobos et al., 2019). After that, candidate models were evaluated and best models were selected using not only AUC values (with the highest val- ues), but also Akaike Information Criterion corrected for small sample sizes (AICc) (with the lowest values) (Hur- vich and Tsai, 1989). Significance tests were performed using partial ROC (Peterson et al., 2008), and predictive power with a 5% omission rate (Anderson et al., 2003). Model AUC scores are evaluated as follows: AUC = 0.5: a performance equivalent to random, AUC > 0.7: useful performance, AUC > 0.8: good performance, AUC > 0.9: excellent (Manel et al., 2001). Finally, all model inputs were transformed into binary predictions using mini- mum training presence as the threshold to distinguish unsuitable from suitable areas (Pearson et al., 2007; Rod- ríguez-Ruiz et al., 2020). Niche equivalency In order to assess the niche overlap among Ana- tololacerta species, ENMTools (Warren et al., 2021) was applied to calculate Schoener’s D (Schoener, 1968) and Hellinger’s-based I (Warren et al., 2008) niche similarity metrics for niche overlap test due to their simplicity, long usage time and effective method to measure niche simi- larities (Warren et al., 2008). These indices ranged from 0 (no overlap) to 1 (identical niches). The significance of the niche difference was assessed by pooling the occurrences from each taxon, and gener- ating 100 pseudo-replicates. Afterwards, one-sided test and an α level of 0.05 was applied to compare the true calculated overlap to the null distribution of niche over- lap. This means that the ENM of two species is not equiv- alent when the overlap value is smaller than 5% of the null distribution. Background test Background test was conducted in order to deter- mine the differential availability of habitat for examined species (Warren et al., 2008). The running conditions of the background test were similar to the niche overlap tests (identity test). RESULTS Ecological niche models and the contribution of environ- mental variables On the basis of minimum training presence thresh- old, ecological niche modeling predictions for each Ana- tololacerta species were reliable enough to result in realis- tic maps, and these predictions were separately conduct- ed for each species with lowest AICc values. A total of 4 bioclimatic and 2 topographic variables contributed to map the predicted distribution of each species (Table 1). The ultimate models were selected based on the lowest AICc from evaluation metric results (Table 2). The MaxEnt models demonstrated a significant ability to generate ecological niche models for Anatololac- erta species with average test AUC of models as follows: 0.818 ± 0.093 for A. anatolica, 0.818 ± 0.083 for A. pelas- giana, 0.927 ± 0.045 for A. finikensis, 0.830 ± 0.083 for A. ibrahimi and 0.895 ± 0.104 for A. danfordi. Based on these results, most of the suitable predicted areas were relatively wider than the present distributions of each species. The potential distribution of all Anatololacerta species are shown in Fig. 2 a-e. Although the bioclimatic and topographic variables that contributed to species dis- tribution were the same, their contribution percentiles were different. The distribution of A. anatolica is highly associ- ated with the temperature annual range - Bio 7 - (35.4 %), while that of A. danfordi with the Mean Leaf Area Index Table 1. Percentage contribution of the environmental layers used in species distribution modeling of Anatololacerta species. Species Bio 3 Bio 5 Bio 7 Bio 17 River_dist Lai A. anatolica 3.1 11.1 35.4 29.5 5.9 15.1 A. danfordi 13.5 1.5 17.8 19.9 3.6 43.7 A. finikensis 19.7 27.3 5.5 35.7 6.5 5.3 A. ibrahimi 0.9 8 7.2 36.6 36.9 10.4 A. pelasgiana 7.3 26 19.6 23 10.7 13.3 169Ecological niche differentiation in the Anatolian rock lizards (43.7 %), and that of A. finikensis with the precipitation of driest quarter - Bio 17 - (35.7 %). The distribution of the remaining two species was highly determined by the envi- ronmental variables as follows: distance to the river (36.9 %) for A. ibrahimi and maximum temperature of the warmest period - Bio 5 - (26 %) for A. pelasgiana. Table 2. Summary statistics for the best models selected for species distribution maps of Anatololacerta species via kuenm package. AICc: a corrected AIC score, used for a small sample size by increasing the cost for each parameter; wAICc: the model weight is the relative likeli- hood for each model, divided by the total relative likelihood for all models that were considered; ΔAICc: the difference between the model with the lowest score (the “best” model) and the AICc score for each model; AUC: area under the curve is a measure of the accuracy of the model; mean AUC ratio ≥1.00, p<0.05 means predictions are significantly better than a random model. Species Best MaxEnt features AICc wAICc ΔAICc AUC Mean AUC ratio A. anatolica hinge 765.536 0.191 0.134 0.818 ± 0.093 1.672 (p = 0.03) A. danfordi threshold 583.369 0.584 1.881 0.895 ± 0.104 1.000 (p = 0.02) A. finikensis quadratic 394.171 0.182 0.395 0.927 ± 0.045 1.619 (p = 0.03) A. ibrahimi threshold 908.851 1.000 0.143 0.830 ± 0.083 1.353 (p = 0.01) A. pelasgiana product 993.837 1.000 0.111 0.818 ± 0.083 1.720 (p = 0.02) Fig. 2. Habitat suitability predictions of a. A. anatolica, b. A. danfordi, c. A. ibrahimi, d. A. finikensis, e. A. pelasgiana in the Anatolian Penin- sula and Aegean Islands (Warmer colors refer to high suitability). 170 Mehmet K. Şahin et alii On the other hand, even though ENM in geographic space was generally suited to determine geographic isola- tion between the cryptic species, discussions on species delimitation have been continuing for the last two dec- ades (Raxworthy et al., 2007; Fišer et al., 2018). Therefore, over-predicted areas were discarded from our final dis- cussion. Niche overlap tests The measured niche overlaps among all species are presented in Table 3. The null hypothesis of niche over- lap between Anatololacerta species (except pelasgiana vs finikensis) were rejected because empirical values for Sch- oener’s D and Hellinger’s based I test statistics were sig- nificantly different than the null distribution of overlap test for each species comparisons (Fig. S2 a-j) (t test, df = 99, P < 0.05). In other words, the ecological niche models of most of these species were nonequivalent. Background test for the parapatric A. pelasgiana and A. finikensis con- firmed the niche overlap between these species in terms of global bioclimatic and selected topographic variables (Fig. S2 k). On the other hand, background tests for spe- cies that represent allopatric diversification patterns dem- onstrated that empirical values for Schoener’s D and Hell- inger’s based I test statistics did not significantly differ from the null distribution (Fig. S2 l-t). DISCUSSION ENM on environmental layers has revealed not only additional insights into evolutionary lineages (Rissler and Apodaca, 2007) but also niche distinctiveness of species (Nakazato et al., 2010). Climatic niche has a remarkable effect on the area where species occur and each species requires a unique niche according to its ecological needs (Gewin, 2006; Rissler and Apodaca, 2007; Gül, 2019). There has been no study on the ecological niche of all Anatolian rock lizards so far. In this study, we have mod- eled environmental niches of all Anatololacerta species on the Anatolian Peninsula and the Aegean islands. Our results suggested that the niche divergence among the genus was confirmed for allopatric species (Fig. S2 a-j). However, the results for A. pelasgiana and A. finikensis showed that there is a niche overlap between these spe- cies (Fig. S2 k). The present study showed the differentiation in the requirements of the ecological conditions among the Anatololacerta species (Fig. 2 a-e, Table 1). In other words, we assessed ecological niche differentiation to examine the phylogenetic-based taxonomic outputs for this genus. The speciation process within this genus was so far explained only by the geological factors and physi- cal barriers (Schmidtler, 1998; Bellati et al., 2015). Based on the given results, we could assume that the differen- tiation within the genus and their present allopatric dis- tribution on the Anatolian Peninsula and the Aegean islands is associated with ecological factors as well. The bioclimatological and topographical conditions provided remarkable contributions to the genetic diversity among this genus in terms of allopatric speciation. Even though ENM for each Anatololacerta species were generated using the same bioclimatic and topographic layers, the contribution percentiles of these variables were different. For instance, the dominant contributing variable for each Anatololacerta species is different: temperature annual Table 3. Niche overlap analyses among Anatololacerta species in the Anatolian Peninsula and Aegean islands. Comparisons Anatololacerta sp. Measured Niche Overlap Identity Test Background Test** Schoener’s D Hellinger’s based I Schoener’s D Hellinger’s based I Schoener’s D Hellinger’s based I pelasgiana vs. anatolica 0.418 0.712 0.679* 0.896* 0.362 0.648 pelasgiana vs. danfordi 0.529 0.803 0.639* 0.867* 0.307 0.586 pelasgiana vs. finikensis 0.666 0.888 0.633 0.862* 0.342 0.610 pelasgiana vs. ibrahimi 0.641 0.879 0.693* 0.910* 0.346 0.623 anatolica vs. danfordi 0.389 0.669 0.693* 0.909* 0.347 0.625 anatolica vs. finikensis 0.341 0.688 0.592* 0.851* 0.328 0.606 anatolica vs. ibrahimi 0.453 0.740 0.646* 0.883* 0.305 0.577 danfordi vs. finikensis 0.472 0.748 0.582* 0.835* 0.292 0.569 danfordi vs. ibrahimi 0.593 0.847 0.649* 0.884* 0.294 0.574 finikensis vs. ibrahimi 0.547 0.822 0.655* 0.895* 0.313 0.559 * Identity test showed significant niche differentiation (all p-value < 0.05). ** No background test showed significant overlap (all p-values > 0.05). 171Ecological niche differentiation in the Anatolian rock lizards range for A. anatolica, mean leaf area index for A. danfor- di, distance to river for A. ibrahimi, precipitation of driest quarter for A. finikensis, and maximum temperature of the warmest period for A. pelasgiana. On the other hand, allopatric speciation dynamics were not only supported climatologically but also geo- graphically (Eiselt and Schmidtler, 1986; Bellati et al., 2015). For example, separation between A. anatolica and the rest of the genus was highly related to the occurrence of the Great Menderes River. Additionally, A. danfordi was isolated from the rest of the genus by Central Tau- rus Mountains and located in the eastern part of Medi- terranean region. Lastly, A. ibrahimi was only distributed in the northern and southern slopes of Central Taurus Mountains. When it comes to parapatric speciation, the niche overlap case, that was demonstrated in the comparison between A. pelasgiana and A. finikensis, was needed to be discussed in another way, because distribution of both species was limited to only southwestern Anatolia and some Aegean islands. The actual utilization of the niche is significantly influenced by ecological interactions of vari- ous sorts. Thus, it could be helpful to use data on differ- ent selective regimes to examine the speciation dynamics of these parapatric species (Gavrilets et al., 2000; Mam- mola et al., 2018). In order to discuss these speciation dynamics among this genus, it might be also beneficial to have evalua- tions on climate based historical perspective. Karakasi et al. (2021) revealed that the first split in Anatololac- erta occurred in Early Pleistocene approximately 1.62 Mya with the separation of A. anatolica and the recent one was between A. pelasgiana and A. ibrahimi (0.56 Mya). The latter split matches the Mindel glacial peri- od. According to the literature, 16 glacial periods have occurred during the last 2.4 million years in the Pleis- tocene (Webb and Bartlein, 1992; Hewitt 1996, 2000). Moreover, it was highly thought that the last four glacial periods in Pleistocene had a remarkable impact on fau- nal composition of Anatolia and related areas (Çıplak, 2004). Fluctuations in the temperature during these peri- ods not only affected the movements of old Anatolian populations (Çıplak, 2004) but also shaped the vegetation dynamics with important changes (Jiménez-Moreno et al., 2015). In addition, the precipitation and temperature dynamics for a long time might have an impact on the vegetation patterns along western and southern parts of Anatolian Peninsula (Şahin et al., 2021). On the other hand, the comparisons among allopat- ric Anatololacerta species revealed that, while their niches are not more similar than expected by chance (Fig. S2 a-j), their niches are not equivalent (Fig. S2 l-u). Studies on allopatric Neurergus species in Anatolia (Gül, 2019), speciation dynamics of endemic lizards in Madagas- car (Nunes et al., 2022) and diversification of shrews in island dispersal events (Esselstyn et al., 2011) demon- strated that differences between their climatic niches are compatible with the abiotic environmental conditions between the geographical regions where allopatric spe- cies have been inhabiting. In fact, although this situation shows that allopatric Anatololacerta species living in the same geography have different niche requirements, the isolation areas between the inhabiting zones do not have an effect on the differentiation of environmental charac- teristics. If species fit to particular climatic conditions (or var- ious local conditions), it brings to niche differentiation because of the unique adaptations needed to survive and breed (Nakazato et al., 2010). In the present study, eco- logical niche divergence has been inferred to display eco- logical speciation of species with allopatric distributions. Our results are compatible with the taxonomic suggestion of the work of Karakasi et al. (2021) that discerns each allopatric clade at the species level. ACKNOWLEDGEMENTS The field surveys were carried out with the per- mission of Republic of Turkey Ministry of Agricul- ture and Forestr y (Permission Number: B.23.0.D MP.0.15.01-510.02-2943). We appreciate the editor and anonymous reviewers for helpful comments on the improving of the manuscript. We also would like to thank Leona Walter for proofreading. SUPPLEMENTARY MATERIALS Supplementary material associated with this article can be found at manuscript number 13089 REFERENCES Anderson, R.P., Lew, D., Peterson, A.T. (2003): Evaluating predictive models of species’ distributions: Criteria for selecting optimal models. Ecol. Modell. 162: 211-232. Araújo, M.B., Thuiller, W., Pearson, R.G. 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