Effects of Climate Change on Distribution Areas of Former Endemic Plant Species Campanula lyrata Lam.

Yıl 2021, , 663 - 672, 30.06.2021

Behlül Güler

https://doi.org/10.16984/saufenbilder.877932

Öz

Species distribution models (SDMs) are useful tools for future potential distribution patterns of species in the face of climate change. Turkey is expected to be affected considerably from climatic change i.e., up to 6°C increase in temperature and 50% decrease in precipitation by 2070. Therefore, there is an urgent need for conservation and management practices for future patterns of species. It is aimed current and future (using CMIP5 projected to 2070) potential distribution areas of Campanula lyrata Lam., which is formerly an endemic species. To do this, presence-only data was used, which is obtained from the Global Biodiversity Information Facility (GBIF). Bioclimatic data from was downloaded from WorldClim dataset with 10 km2 resolution. Species distribution modelling was performed using R program. Two regression techniques and two machine learning techniques namely Generalized Linear Models (GLMs), Generalized Additive Models (GAMs), Support Vector Machine (SVM) and Random Forest (RF), were used, respectively. The bootstrapping method as partitioning resampling was also used for all analysis. Considerably high model performances as well as AUC values for all possible models were found. Significant range shifts between current and future climatic conditions were found. The most relevant relative importance variables were precipitation seasonality and precipitation of the wettest month. This study reveals the importance of the future distributional areas of species.Species distribution models (SDMs) are useful tools for future potential distribution patterns of species in the face of climate change. Turkey is expected to be affected considerably from climatic change i.e., up to 6°C increase in temperature and 50% decrease in precipitation by 2070. Therefore, there is an urgent need for conservation and management practices for future patterns of species. It is aimed current and future (using CMIP5 projected to 2070) potential distribution areas of Campanula lyrata Lam., which is formerly an endemic species. To do this, presence-only data was used, which is obtained from the Global Biodiversity Information Facility (GBIF). Bioclimatic data from was downloaded from WorldClim dataset with 10 km2 resolution. Species distribution modelling was performed using R program. Two regression techniques and two machine learning techniques namely Generalized Linear Models (GLMs), Generalized Additive Models (GAMs), Support Vector Machine (SVM) and Random Forest (RF), were used, respectively. The bootstrapping method as partitioning resampling was also used for all analysis. Considerably high model performances as well as AUC values for all possible models were found. Significant range shifts between current and future climatic conditions were found. The most relevant relative importance variables were precipitation seasonality and precipitation of the wettest month. This study reveals the importance of the future distributional areas of species.

Anahtar Kelimeler

Biology, Botany, Vascular plant, Species distribution models.

Kaynakça

• [1] A. Jentsch, J. Kreyling, and C. Beierkuhnlein, "A new generation of climate‐change experiments: events, not trends", Frontiers in Ecology and the Environment, vol. 5, no. 7, pp. 365-374, 2007.
• [2] C. Parmesan, "Ecological and evolutionary responses to recent climate change", Annual Review of Ecology, Evolution, and Systematics, vol. 37, pp. 637-669, 2006.
• [3] SHM. Butchart, M. Walpole, B. Collen, A. van Strien, JPW. Scharlemann, REA. Almond, et al., "Global biodiversity: indicators of recent declines", Science, vol. 328, pp. 1164–1168, 2010.
• [4] BJ. Cardinale, JE. Duffy, A. Gonzalez, DU. Hooper, C. Perrings, P. Venail, et al., "Biodiversity loss and its impact on humanity", Nature, vol. 486, pp. 59–67, 2012.
• [5] A. Guisan, and W. Thuiller, "Predicting species distribution: offering more than simple habitat models", Ecology letters, vol. 8, no. 9, pp. 993-1009, 2005.
• [6] M. Demircan, H. Gürkan, O. Eskioğlu, H. Arabacı, and M. Coşkun, "Climate change projections for Turkey: three models and two scenarios", Türkiye Su Bilimleri ve Yönetimi Dergisi, vol. 1, no.1, pp. 22-43, 2017.
• [7] A. Akçakaya, O. Eskioğlu, H. Atay, and O. Demir, "Yeni senaryolar ile Türkiye için iklim değişikliği projeksiyonları. – Meteoroloji Genel Müdürlüğü Matbaası, Turkey", 2013.
• [8] B. Önol, and YS. Unal, "Assessment of climate change simulations over climate zones of Turkey", Regional Environmental Change, vol. 14, no.5, pp. 1921-1935, 2014.
• [9] NE. Zimmermann, JrTC. Edwards, CH. Graham, PB. Pearman, and JC. Svenning, "New trends in species distribution modelling", Ecography, vol. 33, no.6, pp. 985-989, 2010.
• [10] H. Yilmaz, OY. Yilmaz, and YF. Akyüz, "Determining the factors affecting the distribution of Muscari latifolium, an endemic plant of Turkey, and a mapping species distribution model", Ecology and Evolution, vol. 7, no.4, pp. 1112-1124, 2017.
• [11] B. Naimi, and MB. Araújo, "sdm: a reproducible and extensible R platform for species distribution modelling", Ecography, vol. 39, no.4, pp. 368-375, 2016.
• [12] SJ. Phillips, RP. Anderson, and RE. Schapire, "Maximum entropy modeling of species geographic distributions", Ecological Modelling, vol. 190, pp. 231–259, 2006.
• [13] G. Carpenter, AN. Gillison, and J. Winter, "DOMAIN: A flexible modelling procedure for mapping potential distributions of plants and animals", Biodiversity Conservation, vol. 2, pp. 667–680, 1993.
• [14] HA. Nix, "A biogeographic analysis of Australian elapid snakes", In R. Longmore (Ed., pp. Atlas of elapid snakes of Australia, Australian flora and fauna series, Canberra, ACT: Australian Government Publishing Service, no. 7, pp. 4–15, 1986.
• [15] A. Herrero, and R. Zamora, "Plant responses to extreme climatic events: a field test of resilience capacity at the southern range edge", Plos one, vol. 9, no. 1, pp. 1-12, 2011.
• [16] A. Jentsch, J. Kreyling, M. Elmer, E. Gellesch, B. Glaser, K. Grant, … C. Beierkuhnlein, "Climate extremes initiate ecosystem‐regulating functions while maintaining productivity", Journal of Ecology, vol. 99, no. 3, pp. 689-702, 2011.
• [17] JE. Weaver, "Prairie Plants and Their Environment, A Fifty-five Year Study in the Midwest", University of Nebraska Press, Lincoln, NE, 1968.
• [18] CW. MacGillivray, JP. Grime, and The Integrated Screening Programme (ISP) Team, "Testing predictions of the resistance and resilience of vegetation subjected to extreme events", Functional Ecology, pp. 640-649, 1995.
• [19] CD. Allen, and DD. Breshears, "Drought-induced shift of a forest–woodland ecotone: rapid landscape response to climate variation", Proceedings of the National Academy of Sciences, vol. 95, no. 25, pp. 14839-14842, 1998.
• [20] Z. Wu, P. Dijkstra, GW. Koch, J. Peñuelas, and BA. Hungate, "Responses of terrestrial ecosystems to temperature and precipitation change: A meta‐analysis of experimental manipulation", Global Change Biology, vol. 17, no. 2, pp. 927-942, 2011.
• [21] A. Güner, S. Aslan, T. Ekim, M. Vural, and MT. Babaç, "Plant List of Turkey: Vascular Plants", Nezahat Gökyiǧit Botanical Garden Press, ANG Foundation, İstanbul, 2012.
• [22] J. Noroozi, G. Zare, M. Sherafati, M. Mahmoodi, D. Moser, Z. Asgarpour, and GM. Schneeweiss, "Patterns of endemism in Turkey, the meeting point of three global biodiversity hotspots, based on three diverse families of vascular plants", Frontiers in Ecology and Evolution, vol. 7, no.159, 2019.
• [23] Ç. Şenkul, and K. Seda, "Türkiye endemik bitkilerinin coğrafi dağılışı", Türk Coğrafya Dergisi, no. 69, pp. 109-120, 2017.
• [24] PH. Davis, "Flora of Turkey and the East Aegean Islands", Edinburgh University Press, Edinburgh, vol 1-9, 1965-1985.
• [25] PH. Davis, RR. Mill, and K. Tan, "Flora of Turkey and the East Aegean Islands", Edinburgh University Press, Edinburgh, vol 10, 1965-1985.
• [26] A. Güner, N. Özhatay, T. Ekim, and KHC. Baser, "Flora of Turkey and the East Aegean Islands", Edinburgh University Press, Edinburgh Herbaceous plants, vol. 11, 2000.
• [27] RJ. Hijmans, SE. Cameron, JL. Parra, PG. Jones, and A. Jarvis, "Very high-resolution interpolated climate surfaces for global land areas", International Journal of Climatology: A Journal of the Royal Meteorological Society, vol. 25, no. 15, pp. 1965-1978, 2005.
• [28] SE. Fick, and RJ. Hijmans, "WorldClim 2: new 1‐km spatial resolution climate surfaces for global land areas", International journal of climatology, vol. 37, no. 12, pp. 4302-4315, 2017.
• [29] ER. Mansfield, and BP. Helms, "Detecting multicollinearity. The American Statistician", vol. 36, no. 3a, pp. 158-160, 1982.
• [30] RC. Team, "R: A language and environment for statistical computing", Vienna, Austria.
• [31] J. Franklin, "Mapping species distributions: Spatial inference and prediction", Cambridge: Cambridge University Press, 2009.
• [32] FEJr. Harrell, "Regression modeling strategies: With applications to linear models, logistic regression, and survival analysis", New York, NY: Springer, 2001.
• [33] E. Meineri, O. Skarpaas, and V. Vandvik, "Modeling alpine plant distributions at the landscape scale: Do biotic interactions matter?", Ecological Modeling, no. 231, pp. 1–10, 2012.
• [34] L. Pellissier, K. Anne Bråthen, J. Pottier, CF. Randin, P. Vittoz, A. Dubuis, ... A. Guisan, "Species distribution models reveal apparent competitive and facilitative effects of a dominant species on the distribution of tundra plants", Ecography, vol. 33, pp. 1004–1014, 2010.