Predicting spatial patterns of Cuculus canorus under climate change in Türkiye

Abstract

Climate change is reshaping species distributions worldwide, with migratory birds representing one of the most vulnerable groups in this process. The Common Cuckoo (Cuculus canorus), a species of high ecological importance, is widely distributed across Eurasia but is increasingly threatened by habitat loss and climatic shifts. In this study, we applied the MaxEnt algorithm to predict the current and future distribution of the cuckoo in Türkiye under present and projected climate conditions. In addition to bioclimatic predictors, topographic variables were included in the modeling framework. Pearson correlation analysis was used to minimize multicollinearity, and variable contributions were evaluated through jackknife tests. The model performed strongly (AUC = 0.81), and response curves indicated that temperature and precipitation were the primary determinants of habitat suitability. Projections for the year 2100 under SSP3-7.0 and SSP5-8.5 scenarios revealed substantial contractions of suitable areas, with no new habitat gains. The extent of climatically suitable habitat is predicted to decline from 631001 km² at present to 285035 km² under SSP3-7.0 and to 151822 km² under SSP5-8.5. Losses were most pronounced at lower elevations, consistent with thermophilization and upslope range shifts. The results highlight potential refugia as critical targets for conservation, while also emphasizing the importance of considering host species distribution, habitat connectivity, and migratory stopover sites in management strategies. This study provides the first comprehensive, spatially explicit projection of cuckoo distribution in Türkiye, offering novel insights into the species’ vulnerability to climate change.

Keywords

• Climate scenarios
• Common cuckoo
• Habitat suitability
• MaxEnt
• Species distribution modeling

İklim değişikliğine bağlı olarak Cuculus canorus türünün Türkiye’deki mekansal dağılımının tahmin edilmesi

Abstract

İklim değişikliği dünya genelinde türlerin dağılımını yeniden şekillendirmektedir. Göçmen kuşlar bu değişim sürecinin en hassas gruplardan birini oluşturmaktadır. Yüksek ekolojik öneme sahip bir tür olan guguk kuşu (Cuculus canorus), Avrasya genelinde yayılış göstermekte ancak habitat kaybı ve iklimsel değişimlerden giderek daha fazla etkilenmektedir. Bu çalışmada, Türkiye’deki guguk kuşu dağılımını mevcut ve gelecekteki iklim koşulları altında tahmin etmek amacıyla MaxEnt algoritması uygulanmıştır. Modellemede biyoklimatik değişkenlere ek olarak topoğrafik değişkenler kullanılmıştır. Değişken seçiminde çoklu bağlantıyı azaltmak için Pearson korelasyon analizi uygulanmış, değişken katkıları ise jackknife testleriyle değerlendirilmiştir. Model güçlü bir performans sergilemiştir (AUC = 0.81) ve tepki eğrileri sıcaklık ve yağış değişkenlerinin habitat uygunluğunda belirleyici olduğunu göstermiştir. 2100 yılı için SSP3-7.0 ve SSP5-8.5 senaryoları altında yapılan projeksiyonlar, yeni kazanım olmaksızın uygun alanlarda ciddi daralmalar öngörmektedir. Mevcut durumda 631001 km² olan uygun habitat alanı, SSP3-7.0 senaryosunda 285035 km²’ye, SSP5-8.5 senaryosunda ise 151822 km²’ye düşmektedir. Bu kayıplar özellikle düşük rakımlarda yoğunlaşmış olup, termofilizasyon ve yükseltiye doğru dağılım kaymaları ile uyumludur. Bulgular, iklim değişikliğine karşı görece stabil kalabilecek refugia alanlarının koruma açısından kritik olduğunu ortaya koymakta; aynı zamanda konak türlerin dağılımı, habitat bağlantısı ve göç sırasında kullanılan konaklama alanlarının da dikkate alınması gerektiğini vurgulamaktadır. Bu çalışma, Türkiye’de guguk kuşunun dağılımına yönelik ilk kapsamlı ve mekânsal projeksiyonu sunarak, türün iklim değişikliğine karşı kırılganlığına dair yeni bilgiler sağlamaktadır.

Keywords

• İklim senaryoları
• Guguk kuşu
• Habitat uygunluğu
• MaxEnt
• Tür dağılım modellemesi

References

1. Acarer, A., Mert, A., 2025. Mapping habitat suitability of the brown bear in Artvin-Şavşat region, Turkey. Ursus, 2025(36e8): 1-15.
2. Bellard, C., Bertelsmeier, C., Leadley, P., Thuiller, W., Courchamp, F., 2012. Impacts of climate change on the future of biodiversity. Ecology Letters, 15(4): 365–377. https://doi.org/10.1111/j.1461-0248.2011.01736.x.
3. Both, C., Bouwhuis, S., Lessells, C.M., Visser, M.E., 2006. Climate change and population declines in a long-distance migratory bird. Nature, 441(7089): 81–83. https://doi.org/10.1038/nature04539.
4. Brooke, M.L., Davies, N.B., 1987. Recent changes in host usage by cuckoos Cuculus canorus in Britain. Journal of Animal Ecology, 56(3): 873–883. https://doi.org/10.2307/4954.
5. Brooke, M., Davies, N., 1988. Egg mimicry by cuckoos Cuculus canorus in relation to discrimination by hosts. Nature 335: 630–632. https://doi.org/10.1038/335630a0.
6. Chen, I.C., Hill, J.K., Ohlemüller, R., Roy, D.B., Thomas, C.D., 2011. Rapid range shifts of species associated with high levels of climate warming. Science, 333(6045): 1024–1026. https://doi.org/10.1126/science.1206432.
7. Çıvğa, A., 2025. Unlocking the habitat suitability of wild olive to improve its industrial potential: a comprehensive distribution modeling study. BioResources, 20(1): 1214-1229.
8. Çıvğa, A., Özdemir, S., Gülsoy, S., 2024. Prediction of potential geographic distribution of Capparis spinosa. Biological Diversity and Conservation, 17(3): 206-215.

9. Davies, N.B., Brooke, M.L., 1989. An experimental study of co‐evolution between the cuckoo, Cuculus canorus, and its hosts. I. Host egg discrimination. Journal of Animal Ecology, 58(1): 207–224. https://doi.org/10.2307/4995.
10. De Frenne, P., Rodríguez-Sánchez, F., Coomes, D.A., Baeten, L., Verstraeten, G., Vellend, M., Verheyen, K., 2013. Microclimate moderates plant responses to macroclimate warming. Proceedings of the National Academy of Sciences, 110(46): 18561-18565. https://doi.org/10.1073/pnas.1311190110. Duque, A., Stevenson, P.R., Feeley, K.J., 2015. Thermophilization of adult and juvenile tree communities in the northern tropical Andes. Proceedings of the National Academy of Sciences, 112(15): 4696–4701. https://doi.org/10.1073/pnas.1506570112.
11. Ertan, K.T., 1999. Cuckoo Cuculus canorus distribution, breeding biology and interactions with hosts in Türkiye. Sandgrouse, 21: 14–22.
12. Evcin, Ö., 2023. Can highway tunnel constructıon change the habitat selection of roe deer (Capreolus capreolus Linnaeus, 1758)?. Environmental Monitoring and Assessment, 195(12): 1410. https://doi.org/10.1007/s10661-023-12003-0
13. Evcin, Ö., 2024a. Unexpected expansion: Climate change-induced movement of the cream-colored courser (Cursorius cursor) into Central Anatolia. Turkish Journal of Forestry, 25(3): 258-266. DOI: 10.18182/tjf.1533024.
14. Evcin, Ö., 2024b. Can the White-throated Kingfisher (Halcyon smyrnensis) be able to resist climate change?. Artvin Çoruh Üniversitesi Orman Fakültesi Dergisi, 25(2): 144-153. https://doi.org/10.17474/artvinofd.1529475
15. Fick, S.E., Hijmans, R.J., 2017. WorldClim 2: new 1km spatial resolution climate surfaces for global land areas. International Journal of Climatology, 37(12): 4302-4315. https://doi.org/10.1002/joc.5086
16. GBIF.org, 2025. GBIF Occurrence Download, https://doi.org/ 10.15468/dl.yxjcbq, Accessed: 14.01.2025
17. Haddad, N.M., Brudvig, L.A., Clobert, J., Davies, K.F., Gonzalez, A., Holt, R.D., Lovejoy, T.E., Sexton, J.O., Austin, M.P., Collins, C.D., Cook, W.M., Damschen, E.I., Ewers, R.M., Foster, B.L., Jenkins, C.N., King, A.J., Laurance, W.F., Levey, D.J., Margules, C.R., Townshend, J.R., 2015. Habitat fragmentation and its lasting impact on Earth’s ecosystems. Science Advances, 1(2): e1500052. https://doi.org/ 10.1126/sciadv.1500052.
18. Kaya, C., Acarer, A., Tekin, S., 2025. Global climate change, a threat: example of the chamois’ case. Šumarski List, 149(3-4): 169-180.
19. Keten, A., Eroglu, E., Kaya, S., Anderson, J. T., 2020. Bird diversity along a riparian corridor in a moderate urban landscape. Ecological Indicators, 118: 106751. https://doi.org/10.1016/j.ecolind.2020.106751
20. Kirwan, G., Demirci, B., Welch, H., Boyla, K., Özen, M., Castell, P., Marlow, T., 2010. The Birds of Türkiye. Bloomsbury Publishing, London.
21. Kleven, O., Moksnes, A., Røskaft, E., Honza, M., 1999. Host species affects the growth rate of cuckoo (Cuculus canorus) chicks. Behavioral Ecology and Sociobiology, 47: 41-46. https://doi.org/10.1007/s002650050647.
22. Lee, H., Calvin, K., Dasgupta, D., Krinner, G., Mukherji, A., Thorne, P., Zommers, Z., 2023. Summary for Policymakers. IPCC, Climate Change 2023, Synthesis Report, doi: 10.59327/IPCC/AR6-9789291691647.001
23. Liu, J., Tingley, M.W., Wu, Q., Ren, P., Jin, T., Ding, P., Si, X., 2024. Habitat fragmentation mediates the mechanisms underlying long-term climate-driven thermophilization in birds. eLife, 13: RP98056. https://doi.org/10.7554/eLife.98056.
24. López-Hernández, F., Rosero-Alpala, M.G., Rosero, A., Cortés, A.J., 2025. Projected shifts in Colombian sweet potato germplasm under climate change. Horticulturae, 11(9): 1080. https://doi.org/10.3390/horticulturae11091080. Lotem, A., 1993. Learning to recognize nestlings is maladaptive for cuckoo Cuculus canorus hosts. Nature, 362: 743–745. https://doi.org/10.1038/362743a0.
25. Møller, A.P., Saino, N., Adamík, P., Ambrosini, R., Antonov, A., Campobello, D. Shykoff, J.A., 2011. Rapid change in host use of the common cuckoo Cuculus canorus linked to climate change. Proceedings of the Royal Society B: Biological Sciences, 278(1706): 733–738. https://doi.org/10.1098/rspb.2010.1592.
26. Nasa, M., 2018. Aist, Japan Space systems, and US/Japan Aster Science Team: Aster Global Digital Elevation Model V003. Nasa Eosdıs Land Processes Daac. https://doi.org/10.5067/ASTER/ASTGTM.003, Accessed: 07.05.2025.
27. Posit team, 2025. RStudio: Integrated Development Environment for R. Posit Software, PBC, Boston, MA. URL http://www.posit.co/, Accessed: 07.09.2025.
28. R Core Team, 2025. R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. https://www.R-project.org/, Accessed: 07.09.2025.
29. Özdemir, S., 2024. A brief history of species distribution modeling: bibliometric study on the web of science. Düzce University Faculty of Forestry Journal of Forestry, 20(2): 334-351.
30. Özdemir, S., Gülsoy, S., Mert, A., 2020. Predicting the effect of climate change on the potential distribution of Crimean Juniper. Kastamonu University Journal of Forestry Faculty, 20(2): 133-142.
31. Phillips, S.J., Dudík, M., Schapire, R.E., 2017. Maxent software for modeling species niches and distributions (Version 3.4.1). American Museum of Natural History. http://biodiversityinformatics.amnh.org/open_source/maxent/, Accessed: 07.09.2025.
32. Schmaljohann, H., Eikenaar, C., Sapir, N., 2022. Understanding the ecological and evolutionary function of stopover in migrating birds. Biological Reviews, 97(3): 1231–1252. https://doi.org/10.1111/brv.12839.
33. Schulze-Hagen, K., Stokke, B.G., Birkhead, T.R., 2009. Reproductive biology of the European cuckoo Cuculus canorus: Early insights, persistent errors and the acquisition of knowledge. Journal of Ornithology, 150(1): 1–16. https://doi.org/10.1007/s10336-008-0340-8.
34. Soler, J.J., Martín-Vivaldi, M., Møller, A.P., 2009. Geographic distribution of suitable hosts explains the evolution of specialized gentes in the European cuckoo Cuculus canorus. BMC Evolutionary Biology, 9: 88. https://doi.org/10.1186/1471-2148-9-88.
35. Süel, H., 2019. Predicting distribution of white stork (Ciconia ciconia Linnaeus, 1758) under climate change in Turkey. Turkish Journal of Forestry, 20(3): 243-249.
36. Tekeş, A., Özdemir, S., Aykurt, C., Gülsoy, S., Özkan, K., 2025. Species distribution modeling of red hawthorn (Crataegus monogyna Jacq.) in response to climate change. Šumarski List, 149(5-6).
37. Uyar, Ç., Özdemir, S., Perkumienė, D., Aleinikovas, M., Šilinskas, B., Škėma, M., 2025. Spatiotemporal patterns of avian species richness across climatic regions. Diversity, 17(8): 557. https://doi.org/10.3390/d17080557.
38. Wang, X., Liu, G., Xiao, S., Quan, M., 2025. Habitat suitability distribution and fragmentation of Camellia oleifera in China under current and future climate scenarios based on MaxEnt and Fragstats. Environmental Monitoring and Assessment, 197: 1113. https://doi.org/10.1007/s10661-025-14597-z.