Kokulu Ardıç’ın (Juniperus foetidissima Willd.) Günümüz ve Gelecekteki Potansiyel Yayılışının Makine Öğrenmesi ile Modellenmesi

Year 2021, Issue: 22, 1 - 12, 31.01.2021

E. Seda Arslan , Derya Gülçin , Ayşe Gül Sarıkaya , Zafer Ölmez , Süleyman Gülcü , İsmail Şen , Ömer K. Örücü

https://doi.org/10.31590/ejosat.848961

Cited By: 1

Abstract

Küresel ölçekte incelendiğinde, biyolojik çeşitlilik sağlama ve karbon tutma bakımından önemli ekosistemler arasındaki ormanların, biyotik, abiyotik ve antropojenik etkenler nedeniyle önemli değişimler içerisinde olduğu görülmektedir. Bu süreçte, iklimin belirleyici bir rolü olduğu kabul edilmiştir. Buna ek olarak, değişen iklim koşullarının, ormanların dağılımını, bileşimini, işlevini önemli oranda değiştireceği ve sonuç olarak biyolojik çeşitliliği tehdit edeceği öngörülmüştür. Bu çalışmanın amacı; Türkiye’de doğal yayılış gösteren ve orman ekosistemine ekolojik katkısı ile ön planda olan türler arasındaki kokulu ardıçın (Juniperus foetidissima Willd.), günümüz ve gelecekteki potansiyel coğrafi dağılımının tür varlığı verisi ve çevresel değişkenler (biyoiklimsel değişkenler ve yükseklik) ile modellenmesidir. Ayrıca, J. foetidissima Willd.’nin potansiyel yayılış alanlarının, günümüzde ve gelecekte alansal ve konumsal olarak nasıl değişiklik gösterdiği de değişim analizleri ile ortaya konmuştur. Bu kapsamda, tür dağılımı SSP2 4.5 ve SSP5 8.5 senaryolarına göre 2041-2060 ve 2081-2100 periyotlarını kapsayacak şekilde belirlenmiştir. Maksimum entropi modelinin kullanıldığı bu çalışmada, her bir tahmin değişkeninin göreceli katkısı Jackknife (çek-çıkar) testi ile belirlenmiş, çoklu doğrusallığı önlemek amacıyla Pearson korelasyonundan yararlanılmıştır. Bulgular, J. foetidissima Willd.’nin yayılışında en önemli değişkenlerin sırasıyla yükseklik, soğuk ayın en az sıcaklığı (BIO6) ve en nemli mevsimin ortalama sıcaklığı (BIO8) olduğunu göstermiştir. Tahmin doğruluğunu ifade eden ROC eğrisi, kullanılan modelin simülasyon gücünün çok yüksek olduğunu ifade etmektedir. Model sonuçlarına göre, J. foetidissima Willd.’nin potansiyel yayılışında önemli miktarda değişiklikler olacağı ve türün iklim değişikliğinden ciddi oranda olumsuz etkileneceği tahmin edilmiştir. Değişim analizi sonuçları, habitat uygunluğundaki alansal kaybın, kazanç miktarından daha fazla olduğunu göstermektedir. Sonuç olarak, bu çalışmada J. foetidissima Willd.’nin iklim değişikliklerine adaptasyon direncinin düşük olacağı ve dolayısıyla tür koruma çalışmalarına dâhil edilmesi gerektiği vurgulanmıştır. Bu çalışmanın bulguları, türün gelecekte sürdürülebilmesi ve korunmasına yönelik güçlü stratejilerin belirlenebilmesi amacıyla kullanılabilir.

Keywords

Kokulu ardıç, tür dağılım modeli, değişim analizi, MaxEnt

Modeling of the current and future potential distribution of Stinking juniper (Juniperus foetidissima Willd.) with machine learning techniques

Abstract

Forest ecosystems, which are seen relevant in terms of providing biodiversity and capturing carbon, have been affected by significant changes due to biotic, abiotic, and anthropogenic factors over time. There is no doubt that climate has a decisive role in this process. In addition, previous studies claim that changing climatic conditions will significantly alter the distribution, composition, and function of forests and, consequently, threaten biodiversity. This study aims to model the present and future potential geographic distribution of the stinking juniper (Juniperus foetidissima Willd.), which has a natural and potential distribution in Turkey as an ecologically important species, with presence data and diverse environmental variables (bioclimatic predictors and altitude). In this context, species distributions were modelled to cover the 2041-2060 and 2081-2100 periods under the SSP2 4.5 and SSP5 8.5 scenarios. Using maximum entropy model, this study analyzed the relative contribution of each environmental predictor by Jackknife test. In order prevent high correlation and multicollinearity, the correlated factors were determined by Pearson correlation coefficient. The findings showed that the most significant variables in the distribution of J. foetidissima were elevation, minimum temperature of coldest month (BIO6), and mean temperature of wettest quarter (BIO8), respectively. Representing the prediction accuracy, ROC curve indicates that the predictive power of the model used in this study was great. According to the model results, it was predicted that there would be significant changes in the potential distribution of J. foetidissima Willd. and this species would be seriously adversely affected by climate change. The results of change analysis pointed out that the spatial loss in habitat suitability was greater than the amount of gain. As a result, this study suggested that J. foetidissima Willd.'s adaptation resistance to climate changes would be low, and therefore should be incorporated into species conservation. The findings of this study can be used to identify robust strategies for the future survival and conservation of the species.

Keywords

Stinking juniper, species distribution model, change analysis, MaxEnt

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