biodicon Biological Diversity and Conservation 1308-5301 1308-8084 Ersin YÜCEL 10.46309/biodicon.2024.1384960 Forestry Sciences (Other) Ormancılık (Diğer) Prediction of potential geographic distribution of Capparis spinosa Prediction of potential geographic distribution of Capparis spinosa https://orcid.org/0000-0003-4975-8878 Çıvğa Alican ISPARTA UYGULAMALI BİLİMLER ÜNİVERSİTESİ https://orcid.org/0000-0002-9425-3724 Özdemir Serkan ISPARTA UYGULAMALI BİLİMLER ÜNİVERSİTESİ https://orcid.org/0000-0003-2011-8324 Gülsoy Serkan ISPARTA UYGULAMALI BİLİMLER ÜNİVERSİTESİ 12 15 2024 17 3 206 215 11 02 2023 05 21 2024 Copyright © 2008, Biological Diversity and Conservation 2008 Biological Diversity and Conservation

Capparis spinosa, Türkiye'nin batı ve güney kıyı bölgelerinde yayılış gösteren, ekonomik (örneğin gıda, hayvancılık, ilaç) ve ekolojik (örneğin erozyon kontrolü, orman yangınlarıyla mücadele) öneme sahip tıbbi bir bitkidir. Çevre koşullarının etkisiyle C. spinosa’nın potansiyel dağılım alanlarını simüle etmek için MaxEnt modeli kullanılmıştır. Sonuçlar, C. spinosa için potansiyel uygun alanın 6109 hektar olduğunu ve Babadağ Bölgesi'nde çoğunlukla 1000 metrenin altında dağıldığını göstermiştir. Modele katkı sağlayan değişkenlerin sırasıyla ana kaya, yükselti, topoğrafik pozisyon indeksi ve gölgelenme indeksi olduğu belirlendi. Elde edilen model, AUC değerlerine (Eğitim AUC: 0,909 ve test AUC: 0,906) göre mükemmel performans sergiledi. Çalışmada ortaya çıkan sonuçların türe yönelik ileride yapılacak araştırmalara ışık tutacağı düşünülmektedir.

Capparis spinosa is a medicinal plant with economic (e.g., food, animal breeding, medicine) and ecological (e.g., erosion control, fighting wildfires) importance that is distributed in the western and southern coastal regions of Turkey. The MaxEnt model was used to simulate potential distribution areas of C. spinosa with the effect of environmental conditions. The results showed that the potential suitable area of C. spinosa is 6109 hectares, mainly distributed below 1000 meters in Babadağ Region. It was determined that the variables contributing to the model were bedrock, elevation, topographic position index and hillshade index, respectively. The acquired model presented excellent performance according to its AUC values (Training AUC: 0.909 and test AUC: 0.906). It is thought that the results revealed in the study will provide an insight for future investigations to be carried out for the species.

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