Estimating potential future distribution of some selected Oak species in the Marmara Region

Öz

In this study, climate simulations were obtained by reducing the global model results to 2.5 km resolution with the COSMO-CLM model with a dynamic downscaling approach. Bioclimatic variables corresponding to the reference years 2031-2040, 2051-2060, 2071-2080 and 2091-2100 were calculated by using high-resolution meteorological parameters produced from the current and future RCP8.5 emission scenario. With the help of the MaxEnt program run with these variables, habitat suitability analysis was carried out for Quercus frainetto, Q. cerris, Q. petraea and Q. infectoria species distributed in the Marmara Region. When examining the obtained results, it has been concluded that the areas of Quercus frainetto, Q. cerris and Q. petraea increase while the area of Quercus infectoria decrease. It has been revealed that the suitable areas for Quercus frainetto increase from 2020 to 2050, but the highly suitable areas decrease from 2050 to 2070. Furthermore, it has been found that there will be an increase in the highly suitable areas from 2070 to 2100, while both less suitable and suitable areas will experience a decrease. It has been determined that future climatic conditions will increase the habitat suitability of Quercus cerris and Q. petraea and will create the most favourable conditions for their establishment. In contrast, it has been observed that the suitable areas for Quercus infectoria are projected to increase from 2020 to 2050 but decrease from 2050 to 2070 and subsequently from 2070 to 2100.

Anahtar Kelimeler

• Oak
• climate change
• habitat suitability modeling
• Marmara Region

Marmara Bölgesinde seçilen bazı Meşe türlerinin gelecekteki potansiyel yayılış alanlarının tahmin edilmesi

Öz

Bu çalışmada, iklim simülasyonları COSMO-CLM modeli ile küresel model sonuçlarının 2,5 km çözünürlüğe dinamik ölçek küçültme yaklaşımıyla indirgenmesi ile elde edilmiştir. Günümüz ve gelecek RCP8.5 emisyon senaryosundan hareketle üretilen yüksek çözünürlüklü meteorolojik parametreler kullanılarak 2031-2040, 2051-2060, 2071-2080 ve 2091-2100 referans yıllarına karşı gelen biyoiklimsel değişkenler hesaplanmıştır. Bu değişkenlerle çalıştırılan MaxEnt programı yardımıyla, Marmara Bölgesinde yayılış gösteren Quercus frainetto, Q. cerris, Q. petraea ve Q. infectoria türleri için habitat uygunluk analizi gerçekleştirilmiştir. Elde edilen sonuçlar irdelendiğinde, Quercus frainetto, Q. cerris ve Q. petraea’nın alanlarının artacağı ve Quercus infectoria’nın ise azalacağı sonucuna varılmıştır. Quercus frainetto için uygun alanların 2020 yılından 2050 yılına doğru arttığı, ancak yüksek uygun alanlarının ise 2050’den 2070’e azalacağı ortaya konmuştur. Ayrıca, 2070’den 2100’e kadar yüksek uygun alanlar artsa da, az uygun ve uygun alanların azalacağı tespit edilmiştir. Gelecek iklim koşullarının Quercus cerris ve Q. petraea’nın habitat uygunluğunu artacağı ve yüzyılın sonunda en elverişli koşulların oluştuğu tespit edilmiştir. Aksine, Quercus infectoria için uygun alanların 2020’den 2050’e artacağı, fakat 2050’den 2070’e ve sonrasında 2070’den 2100’e kadar azalacağı gözlemlenmiştir.

Anahtar Kelimeler

• Meşe
• iklim değişikliği
• habitat uygunluğu modellemesi
• Marmara Bölgesi

Kaynakça

1. Araújo, M.B., Pearson R.G., Thuiller W., Erhard M., 2005. Validation of species-climate impact models under climate change. Global Change Biology, 11, 1504-1513.
2. Araujo, M.B., Guisan, A., 2006. Five (or so) challenges for species distribution modelling. Journal of Biogeography, 33, 1677-1688.
3. Avcı, M., 2010. The Oak – Ecology, History, Management and Planning II. 01-03 June 2010, Abstract book. Suleyman Demirel University, Isparta/TURKEY
4. CBD, 2010. Convention on Biological Diversity. Global Biodiversity Outlook 2, 2010. https://www.cbd.int/2010-target (Accessed on 17.04.2022).
5. Elith, J.H., Graham, C.P., Anderson, R., Dudík, M., Ferrier, S., Guisan, A.J., Hijmans, R., Huettmann, F.R., Leathwick, J., Leh-mann, A., 2006. Novel methods improve prediction of species’ distributions from occurrence data. Ecography 29 (2): 129–151.
6. ESRI, 2018. How Cut Fill Works. http://destop.arcgis.com/en/arcmap/10.3/tools/spatial analist-toolbox/how-cut-fill-works.htm. (Accessed:19.04.2022).
7. Faussett, J.G., 2021. Oak Trees: Kings of Biodiversity. One Earth, 2021. https://www.oneearth.org/oak-trees-kings-of-biodiversity. (Accessed on 03.05.2022).
8. Fosso, L.C., Karahalil, U., 2020. Some important parameters to display the effects of climate change on forest: a case study in Cerle planning unit, Antalya, Turkey. Artvin Çoruh University Journal of Forestry Faculty, 21 (1): 45-58.

9. Fosso, L.C., Karahalil, U., 2021. ‘Climate change perception and adaptation strategies elaborated by forestry professionals in Tur-key’, Internationa Journal of Global Warming, 23 (1): 11–29.
10. Fosso, L.C., 2021. Integration of climate change to forest management practices: an analysis of future tree species distribution, eco-system services and perception of forestry professionals. Karadeniz Technical University, Institute of Science, PhD thesis, Trabzon.
11. Fosso, L.C. Karahalil, U., 2022. Spatial Distribution of Oak According to Different Selected Parameters in Turkey. II International Oak workshop. General Directorate of Forestry, Marmara Forest Research Institute, 10 - 12 May.
12. Hausfather, Z., 2019. Explainer: The high-emissions ‘RCP8.5’ global warming scenario. CarbonBrief https://www.carbonbrief.org/explainer-the-high-emissions-rcp8-5-global-warming-scenario/ (Accessed on 17.04.2023)
13. IPCC, 2007. IPCC Fourth Assessment Report: Climate change. Working Group I: The Physical Science Basis. https://archive.ipcc.ch/publications_and_data/ar4/wg1/en/ch1s1-5.html (Accessed: 28.04.2023).
14. Jansson, N., Avcı, M., Bergner, A., Kayis, T., Coskun, M., Abacıgil, T.Ö., Varlı, S.V., Tezcan, S., Aytar, F., Niklasson, M., Westerberg, L., Milberg, P., 2017. Turkey’s oak forests are important for biodiversity. Internationa Symposium on new Horizons in Forestry (ISFOR 2017). 17-20 October 2017. Isparta -Turkey.
15. Karahalil U., Köse S., 2015. Modelling Fire Risk and Its Reflection in Management Plans: The Case of Köprülü Canyon National Park, Operation Research and Industrial Engineering (YAEM) 35th National Congress, Book of Abstracts, 89, 9-11 September, Ankara.
16. Koç, D.E., Svenning, J.C., Avcı, M., 2018. Climate change impacts on the potential distribution of Taxus baccata L. in the Eastern Mediterranean and the Bolkar Mountains (Turkey) from last glacial maximum to the future. Eurasian Journal of Forest Science, 6 (3): 69-82.
17. 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.
18. Phillips S., 2006. A brief tutorial on MaxEnt. AT&T Research. (biodiversityinformat-ics.amnh.org/open_source/maxent/Maxent_tutorial_2021.pdf)
19. Phillips S., 2017. A Brief Tutorial on Maxent. http://biodiversityinformatics.amnh.org/open_source/maxent/. (Accessed on 08.05.2023).
20. Rockel, B., and Geyer, B., 2008.The performance of the regional climate model CLM in different Climate regions, based on the example of precipitation, Meteorologische Zeitschrift, 17 (4): 487– 498.
21. Swet J.A., 1988. Measuring the accuracy of diagnostic systems. Science, 240 (4857): 1285-1293.
22. Tüfekçioğlu, A., Kalay, H.Z., Küçük, M., Kahriman, A., Özbayram, A.K.., 2005. Institutions Seen from Insect Damages in Artvin-Hatilla National Park and Their Ecological Causes Triggering it, Spruce Symposium, Artvin, Türkiye . 142-151.
23. Yaltırık, F., 1998. Dendrology Textbook II, Angiospermae (Angiosperms), İstanbul Üniversitesi. Publication No: 4104. Forestry faculty publication No. 420. ISBN 975 - 404 - 594 – 1
24. Yang, X., Kushwaha, S.P.S., Saran, S., Xu, J., Roy, P.S., 2013. MaxEnt modeling for predicting the potential distribution of medic-inal plant, Justicia adhatoda L. in Lesser Himalayan foothills. Ecological Engineering, 51: 83–87.
25. Zhang, Q., Shao, M., Jia, X., Wei, X., 2017. Relationship of Climatic and Forest Factors to Drought and Heat-Induced Tree Mortali-ty. PLoS ONE, 12 (1): 69-77.
26. Zhang, L., Zhu, L., Li, Y., Zhu, W., Chen, Y., 2022. Maxent Modelling Predicts a Shift in Suitable Habitats of a Subtropical Ever-green Tree (Cyclobalanopsis glauca) under Climate Change Scenarios in China. Forests,2022,13(1):126. https://doi.org/10.3390/f13010126