Determining potential niche competition regions between Kazdagi fir (Abies nordmanniana subsp. equi- trojani) & Anatolian black pine (pinus nigra subsp. pallasiana) and conservation priority areas under climate change by using maxent algorithm

Date

2019

Author

Usta Baykal, Nurbahar.

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Kazdagi Fir (Abies nordmanniana subsp. equi-trojani) is an endemic coniferus tree subspecies in Turkey. The species has a narrow distribution and its conservation status defined as EN (Endangered) by IUCN (International Union for Conservation of Nature), due to its decreasing population size. Besides the human activities unfavoring the species viability, it also suffers from a severe competition which has overlapping distribution with Kazdagi fir; Anatolian Black Pine (Pinus nigra subsp. pallasiana). The study presented here, aimed to detect conservation priority areas for Kazdagi fir. In order to achieve this, species distribution modeling approach by using MAXENT algorithm was used to model both Kazdagi fir and Anatolian Black Pine’s potential distributions in 2050 by considering the possible effects of global climate change in near future. Then, a series of overlay analyses were made to be able to detect the areas which are better habitats for Kazdagi fir than Anatolian black pine. The results of the study revealed several regions. Yet, considering the current distribution of the species and its dispersal limits, this study proposes two conservation priority areas for Kazdagi fir; Uludag and Kazdagi (Mt. Ida). The assessed regions are the most important habitats for both species according to both currently and in 2050 climate scenarios. Thus, it is crucial that forestry and conservation practices should be taken into consideration in these areas.

Subject Keywords

Climatic changes., Abies nordmannianna subsp. equi-trojani, Climate Change, Maxent, Conservation, Species Distribution Models.

URI

http://etd.lib.metu.edu.tr/upload/12623233/index.pdf
https://hdl.handle.net/11511/43402

Collections

Graduate School of Natural and Applied Sciences, Thesis