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ŠUMARSKI LIST 7-8/2022 str. 76     <-- 76 -->        PDF

becoming more widely used to model species distributions, which has led to discussions about the types of distributions (e.g., potential vs. realized) it can model that presence-absence data cannot (Hirzel and Le Lay 2008; Soberon and Nakamura 2009; Lobo et al. 2010). As mentioned in previous studies, the subject is complex because of the interplay among data quality (amount and accuracy of species data; ecological relevance of predictor variables; and access to data on disturbances, dispersal limitations, and biotic interactions), modelling method, and scale of analysis (Elith et al. 2011; Mondal et al. 2012).
A pre-requisite for properly rehabilitating a species in an ecosystem understands that species’ distribution in detail (Franklin 2013). Although discrepancies exist between various climate modelling systems (Cheaib et al. 2012), the species distribution approach nevertheless functions as an important research tool that is used to estimate and predict the changes occurring in terms of species distribution.
The leopard has the broadest range of prey of all predators in Felidae, and it can adapt to multiple climates zones and environments with various ecological features as long as there is an ample food supply; leopards can also inhabit non-mountainous areas (Balme et al. 2009; Henschel et al. 2011). I suggest that leopards frequently use mountainous areas because they offer both a refugia from anthropogenic disturbance and less direct competition with humans for living space (Norton et al. 1996; Gavashelishvili and Lukarevskiy 2008).
A number of studies have identified potentially suitable leopard habitats using ENM and argued that these habitats are as important as those that leopards currently inhabit (Zimmermann et al. 2007; Gavashelishvili and Lukarevskiy 2008; Mondal et al. 2012; Swanepoel et al. 2012; Farhadinia et al. 2015; Ebrahimi et al. 2017). However, this model uses ecological values of the areas where findings related to the species were obtained to make predictions. The current data on the density and habitat use of the leopard, a species that is difficult to study, may be considered insufficient in Türkiye. Therefore, although the habitats predicted by the ecological niche model to be suitable are important, it is clear that this model cannot produce sound results without evaluating the areas known to host the species. Moreover, there are regions where the current data indicate that the leopard density is low or the leopard has gone extinct; acting on the basis of these data can produce very dangerous consequences for the continuity of the species.
The habitat in northeastern and eastern Türkiye would be suitable for the Anatolian leopard, and the area remains interesting for further surveys – mainly the regions bordering Armenia and Iran (Zimmermann et al. 2007). Kumerloeve (1956), Baºkaya (2003), Baºkaya and Bilgili (2004), Arpacık (2018) and Sarı (2018) also stated that the Eastern Black Sea Region is a leopard habitat, and there is a settled leopard population in this region. Furthermore, using the MaxEnt program, Zimmermann et al. (2007) identified suitable habitats for the leopard in the Caucasus ecological region, suggesting that this region is potentially suitable for the leopard and that research should be intensified on the eastern borders of Türkiye. Predicted suitable habitats produced using the same program in this research was found to be consistent with the results reported by Zimmerman et al. (2007). Some studies have determined potentially suitable habitats for the leopard using ENM, noting that these areas are at least as important as the existing ones (Zimmermann et al. 2007; Swanepoel et al. 2012; Mondal et al. 2012). However, this model is based on the ecological values of the areas where more species are found. In fact, the results obtained using the program in this study did not reveal all of the available habitats for the leopard in Türkiye. For example, the habitats that the results suggest are suitable for the leopard in Türkiye, such as Çoruh Valley, Çemçe-Madur mountain range, mountainous areas between Lake Van and Hakkari, and the areas ranging from Erzincan-Sivas-Tokat to Sinop forests –in reality-, do not contain any suitable habitats, which render the results of the program somewhat inaccurate. Also, although there is no record of the Anatolian leopard in the Thrace region, the program has shown these areas as suitable habitats by evaluating the climate data.
Presence-only data are useful and can be used to model the same ecological relationships as presence-absence data, provided that biases can be dealt with. Finally, although MaxEnt can predict suitable habitats, it may be less robust in predicting how specific environmental variables influence habitat suitability (Elith et al. 2010; Swanepel et al. 2012).
Climate change often makes environments hotter and drier (IPCC 2014; Ebrahimi et al. 2017). Drought reduces prey availability, which is an important factor for leopards choosing a territory (Carbone and Gittleman 2002; Hebblewhite et al. 2011; Farhadinia et al. 2015; Ebrahimi et al. 2017); it is therefore necessary to take prey distribution into account when modelling potential habitats for the leopard in Türkiye.
Addressing the needs of human beings without defining and preserving the habitats of leopards threatens the latter’s survival, and this has important downstream effects on biodiversity. Leopards are timid animals that lead solitary lives, are mostly active at night (they are nocturnal) in large areas, and are difficult to study scientifically; subsequently, there is little data on their population and habitats in Türkiye. Therefore, although ENM may generate important results when determining potentially suitable habitats, it is clear that this model cannot yield accurate results without