Maksimum Entropi Modelleme Kullanarak Avrupa Yer Sincabı'nın İki Soyhattı Arasındaki İklim Tercihinin Tahmini

Abstract

Estimation of the Climate Preference Between Two Lineages of Europe-an Ground Squirrel Using Maximum Entropy Modeling

Abstract

Spermophilus citellus (Linnaeus, 1766), commonly referred to as the European ground squirrel, exists in specific areas of Central Europe and the Balkans. The species is currently listed as ‘‘vulnerable’’ on the IUCN Red List of Threatened Species. Recently genetic studies have shown that the species has two main lineages; the northern and the southern. The northern lineage shows distribution range at the central and western part of the Balkans and Central Europe, whereas the southern lineage is spread in a more limited area, which includes the southern and eastern parts of the Balkans. The purpose of this study is to reveal the potential geographic distribution in Last Glacial Maximum (approximately 22 kya), present and future (average 2070) periods of these lineages using Maximum Entropy modeling (MaxEnt). This study also contributes to comparing the distribution of two lineages between past, present and future periods. The final MaxEnt with ten replicate runs was constructed based on 80 occurrence records from Austria, Bulgaria, Czech Republic, Greece, Hungary, Slovakia, Serbia, Macedonia, Mol-dova, Romania, Turkey and Ukraine, and twelve abiotic bioclimatic variables obtained from WorldClim. Thus, it was attempted to estimate the importance of bioclimatic factors influencing the potential geographical distribution for each lineage as well as assessing the area under curve values. This study showed that the two lineages of the European ground squirrel had different geographic distribution patterns for past, present and future periods. More-over, the study will make important contributions to conservation studies such as management strategies, species action plans and translocation.

Keywords

• Climatic preference
• ecological niche modeling
• European ground squirrel
• geographic distribution
• maxent

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