Predicting Present and Future Distribution Ranges of an Endemic Flea Beetle, Psylliodes anatolicus Gök and Çilbiroğlu 2004 (Coleoptera: Chrysomelidae) in Türkiye

Abstract

This study aimed to construct species distribution models (SDMs) to predict present and future (2050 and 2070) potential distribution ranges of the endemic leaf beetle Psylliodes anatolicus Gök and Çilbiroğlu, 2004 under different climate change scenarios (Representative Concentration Pathway (RCP) 4.5 and 8.5). The distribution records were gathered from the related literature and unpublished data of the authors. SDMs were constructed by the maximum entropy (MaxEnt) method using the bioclimatic variables of Community Climate System Model 4 (CCSM4). As a result of this study, the most effective bioclimatic factors determining the distribution of species were isothermality, temperature seasonality, and mean temperature of the wettest quarter. The SDM conducted for the present distribution showed that the species may occur in large parts of the Aegean and Mediterranean Regions of Türkiye, beyond the known records. The SDMs for 2050 and 2070 suggest that the range of the species will shrink considerably or go extinct totally in the next 50 years, probably due to the changing climate. In conclusion, this study revealed that changing climate threatens the endemic members of Anatolian biodiversity, especially the endemic species living in mountain ecosystems.

Keywords

• Species distribution modeling
• Maxent
• Bioclimatic variables
• Niche
• Extinction

Endemik Yaprak Böceği, Psylliodes anatolicus Gök ve Çilbiroğlu 2004'un (Coleoptera: Chrysomelidae) Türkiye'deki Şimdiki ve Gelecekteki Dağılış Alanının Tahmin Edilmesi

Abstract

Çalışmada, endemik yaprak böceği Psylliodes anatolicus Gök ve Çilbiroğlu, 2004’nın günümüz ve farklı iklim değişikliği senaryolarına (Representative Concentration Pathway (RCP) 4.5 ve 8.5) göre gelecekteki (2050 ve 2070) potansiyel yayılış alanlarının tahmin edilmesi için tür dağılım modellerinin yapılması amaçlanmıştır. Türün dağılış kayıtları ilgili literatür ve yazarların yayınlanmamış kayıtlarından derlenmiştir. Türün günümüz ve gelecekteki dağılışları Community Climate System Model 4 (CCSM4) iklim değişikliği senaryolarına göre maksimum entropi (MaxEnt) metodu kullanılarak tahmin edilmiştir. Çalışmanın sonucunda, izotermallik, en nemli çeyreğin ortalama sıcaklığı ve mevsimsel sıcaklık türün dağılışını belirleyen en etkili biyoiklimsel faktörler olarak bulunmuştur. Günümüz dağılış modeli, bilinen yayılış alanının aksine, türün Ege ve Akdeniz bölgelerinin büyük bir bölümünde bulunabileceğini ortaya koymuştur. Gelecek dağılış modelleri ise, türün dağılış alanının iklim değişikliği nedeniyle 2050 ve 2070 dönemlerinde oldukça daralacağını veya hatta gelecek 50 yıl içinde neslinin tükenebileceğine işaret etmiştir. Bu çalışma değişen iklime bağlı olarak, dağ ekosistemlerinde yaşayan endemik türlerin başta olmak üzere, tüm Anadolu endemik biyoçeşitliliğinin tehdit altında olduğuna işaret etmektedir.

Keywords

• Tür dağılım modellemesi
• Maxent
• Biyoiklimsel değişkenler
• Niş
• Nesli tükenme

References

1. [1] Döberl, M. 2010. Subfamily Alticinae. pp. 491–563. Löbl, I., Smetana, A. ed. 2010. Catalogue of Palaearctic Coleoptera. Volume 6: Chrysomeloidea. Apollo Books, Stenstrup, 924 pp.
2. [2] Ekiz, A. N., Şen, İ., Aslan, E. G., Gök, A. 2013. Checklist of leaf beetles (Coleoptera: Chrysomelidae) of Turkey, excluding Bruchinae. Journal of Natural History, 47(33-34), 2213-2287.
3. [3] Gök, A., Doguet, S., Çilbiroğlu, E. G. 2003. Psylliodes cerenae sp. nov., a new Alticinae species from Southwest Turkey (Coleoptera: Chrysomelidae). Annales Zoologici 53(2), 201-202.
4. [4] Gök, A., Çilbiroğlu, E. G. 2004. A new species of the genus Psylliodes Latreille (Coleoptera: Chrysomelidae) from Turkey. Zootaxa, 440(1), 1-6.
5. [5] Gök, A. 2005. Psylliodes yalvacensis sp. n.(Coleoptera: Chrysomelidae, Alticinae) from Turkey. Biologia, 60, 133-135.
6. [6] Şen, İ., Gök, A. 2009. Leaf beetle communities (Coleoptera: Chrysomelidae) of two mixed forest ecosystems dominated by pine-oak-hawthorn in Isparta province, Turkey. Annales Zoologici Fennici, 46 (3), 217-232.
7. [7] Aslan, E. G. 2010. Comparative diversity of Alticinae (Coleoptera: Chrysomelidae) between Çığlıkara and Dibek nature reserves in Antalya, Turkey. Biologia, Bratislava, 65 (2), 316-324.
8. [8] Şen, İ., Gök, A. 2014. Leaf beetle (Coleoptera: Chrysomelidae) communities of Kovada Lake and Kızıldağ national parks (Isparta, Turkey): assessing the effects of habitat types. Entomological Research, 44 (3), 176–190.

9. [9] Bayram, F., Aslan, E. G. 2015. Comparation of Alticini (Coleoptera: Chrysomelidae: Galerucinae) species diversity in different habitats selected from Bafa Lake Natural Park (Aydın) basin with a new record for Turkish fauna. Turkish Journal of Entomology, 39(2), 147-157.
10. [10] Şimşek, A., Bolu, H. 2017. Diyarbakır İli antepfıstığı Pistacia vera L. bahçelerindeki zararlı böcek faunasının belirlenmesi. Dicle Üniversitesi Fen Bilimleri Enstitüsü Dergisi, 6(2), 43-58.
11. [11] Aslan, E. G. 2018. Alticini (Coleoptera: Chrysomelidae) species occurring on Akşehir extensions (Konya) of the Sultan Mountains, Turkey. Biological Diversity and Conservation, 11(3), 122-125.
12. [12] Brown, J. H., Stevens, G. C., Kaufman, D. M. 1996. The geographic range: size, shape, boundaries, and internal structure. Annual Review of Ecology and Systematics, 27, 597– 623.
13. [13] Ebach, M. C. 2015. A History of Biogeography for the Twenty-First Century Biogeographer. pp. 1-20. Ebach, M. C. 2015. Origins of Biogeography Springer, Dordrecht, 185 pp.
14. [14] Elith, J., Leathwick, J. R. 2009. Species distribution models: ecological explanation and prediction across space and time. Annual Review of Ecology, Evolution and Systematics, 40, 677–697.
15. [15] Franklin, J. 2010. Mapping Species Distributions: Spatial Inference and Prediction. Cambridge University Press, Cambridge, 320 pp.
16. [16] Elith, J., Franklin, J. 2013. Species distribution modelling. pp. 692–705. Levin, S. A. ed. 2013. Encyclopedia of Biodiversity. Academic Press, Waltham, MA, 5504 pp.
17. [17] Moses, A. 2017. Statistical modeling and machine learning for molecular biology. Chapman and Hall/CRC, New York, 280 pp.
18. [18] Guisan, A., Thuiller, W. 2005. Predicting species distribution: offering more than simple habitat models. Ecology Letters, 8(9), 993-1009.
19. [19] Dambach, J., Rödder, D. 2010. Applications and future challenges in marine species distribution modeling. Aquatic Conservation: Marine and Freshwater Ecosystems, 21(1), 92–100.
20. [20] Brunetti, M., Magoga, G., Iannella, M., Biondi, M., Montagna, M. 2019. Phylogeography and species distribution modelling of Cryptocephalus barii (Coleoptera: Chrysomelidae): is this alpine endemic species close to extinction? ZooKeys, 856, 3-25.
21. [21] 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. International Journal of Climatology: A Journal of the Royal Meteorological Society, 25(15), 1965-1978.
22. [22] Hijmans, R. J. 2021. Package ‘raster’ Geographic Data Analysis and Modeling. https://cran.r-project.org/web/packages/raster/index.html (Date Accessed: 10.12.2021).
23. [23] RStudio Team 2021. RStudio: Integrated Development Environment for R. RStudio, PBC, Boston, MA. http://www.rstudio.com/. (Date Accessed: 10.12.2021).
24. [24] Warren, D. L., Matzke, N .J., Cardillo, M., Baumgartner, J. B., Beaumont, L. J., Turelli, M., Glor, R. E., Huron, N. A., Simões, M., Iglesias, T. L. Piquet, J. C., Dinnage, R. 2021. ENMTools 1.0: an R package for comparative ecological biogeography. Ecography, 44(4), 504-511.
25. [25] Elith, J., Kearney, M., Phillips, S. 2010. The art of modelling range shifting species. Methods in Ecology and Evolution/British Ecological Society 1, 330–342.
26. [26] Stohlgren, T. J., Ma, P., Kumar, S., Rocca, M., Morisette, J. T., Jarnevich, C. S., Benson, N. 2010. Ensemble habitat mapping of invasive plant species. Risk Analysis 30, 224–235.
27. [27] Gent, P. R., Danabasoglu, G., Donner, L. J., Holland, M .M., Hunke, E. C., Jayne, S. R., Lawrenceits, D. M., Neale, R. B., Rasch, P. J., Vertenstein, M., Worley, P., Yang, Z. L., Zhang, M. 2011. The community climate system model version 4. Journal of Climate, 24(19), 4973-4991.
28. [28] Barry, S. C., Elith, J. 2006. Error and uncertainty in habitat models. Journal of Applied Ecology, 43, 413–423.
29. [29] 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. Journal of Biogeography, 34, 102–117.
30. [30] Elith, J., Phillips, S. J., Hastie, T., Dudík, M., Chee, Y. E., Yates, C. J. 2010. A statistical explanation of MaxEnt for ecologists. Diversity and distributions, 17(1), 43-57.
31. [31] Phillips, S. J., Anderson, R. P., Schapire, R. E. 2006. Maximum entropy modeling of species geographic distributions. Ecological Modelling, 190, 231–259.
32. [32] Phillips, S. J., Anderson, R. P., Dudík, M., Schapire, R. E., Blair, M. E. 2017. Opening the black box: an open-source release of Maxent. Ecography, 40, 887–893.
33. [33] Angilletta, M. J. 2009. Thermal Adaptation: A Theoretical and Empirical Synthesis. Oxford University Press, New York. 302 pp.
34. [34] Janzen, D. H. 1967. Why mountain passes are higher in the tropics. The American Naturalist, 101(919), 233-249.
35. [35] Ghalambor, C. K., Huey, R. B., Martin, P. R., Tewksbury, J. J., Wang, G. 2006. Are mountain passes higher in the tropics? Janzen's hypothesis revisited. Integrative and Comparative Biology, 46(1): 5-17.
36. [36] Gough, L. A., Sverdrup‐Thygeson, A., Milberg, P., Pilskog, H. E., Jansson, N., Jonsell, M., Birkemoe, T. 2015. Specialists in ancient trees are more affected by climate than generalists. Ecology and evolution, 5(23), 5632-5641.
37. [37] Urbani, F., D'Alessandro, P., Frasca, R., Biondi, M. 2015. Maximum entropy modeling of geographic distributions of the flea beetle species endemic in Italy (Coleoptera: Chrysomelidae: Galerucinae: Alticini). Zoologischer Anzeiger-A Journal of Comparative Zoology, 258, 99-109.
38. [38] Cerasoli, F., Thuiller, W., Guéguen, M., Renaud, J., D'Alessandro, P., Biondi M. 2020. The role of climate and biotic factors in shaping current distributions and potential future shifts of European Neocrepidodera (Coleoptera, Chrysomelidae). Insect Conservation and Diversity, 13, 47-62.
39. [39] Kubisz, D., Magoga, G., Mazur, M. A., Montagna, M., Ścibior, R., Tykarski, P., Kajtoch, L. 2020. Biogeography and ecology of geographically distant populations of sibling Cryptocephalus leaf beetles. The European Zoological Journal, 87(1), 223-234.
40. [40] Pearson, R. G. 2006. Climate change and the migration capacity of species. Trends in Ecology and Evolution, 21, 111–113.
41. [41] Engler, R., Randin, C.F., Vittoz, P., Czáka, T., Beniston, M., Zimmermann, N. E., Guisan, A. 2009. Predicting future distributions of mountain plants under climate change: does dispersal capacity matter? Ecography, 32, 34–45.
42. [42] Ozinga W. A., Römermann, C., Bekker, R. M. Prinzing, A., Tamis, W. L. M., Schaminée, J. H. J., Hennekens, S. M., Thompson, K., Poschlod, P., Kleyer, M., Bakker, J. P., van Groenendael, J. M. 2009. Dispersal failure contributes to plant losses in NW Europe. Ecology Letters, 12, 66–74.
43. [43] Çoban, H. O., Orucu, O. K., Arslan, E. S. 2020. MaxEnt modeling for predicting the current and future potential geographical distribution of Quercus libani Olivier. Sustainability, 12(7), 2671.
44. [44] Babalik, A. A., Sarikaya, O., Orucu, O. K. 2021. The current and future compliance areas of kermes oak (Quercus coccifera L.) under climate change in Turkey. Fresenius Environmental Bulletin, 30(1), 406-413.
45. [45] Chichorro, F., Juslén, A., Cardoso, P. 2019. A review of the relation between species traits and extinction risk. Biological Conservation, 237, 220-229.