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1

Space partitioning among two sympatric species, sand cat (Felis margarita) and Ruppell’s fox (Vulpes rueppellii), in a desert landscape in Central Iran

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Akbari Feizabadi H., Naderi M., Ashrafi S., Hemami M. R.
Polish Journal of Ecology
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2018
|
tom 66
|
nr 2
This study evaluates and compares habitat preferences and spatial niche breadth and overlap between two sympatrically occurring species, the sand cat (Felis margarita) and Rüppell's fox (Vulpes rueppellii), in a desert landscape of central Iran. A field survey from 2014 to 2016 was conducted to collect occurrence points for the two species as well as to identify their structural characteristics of used habitats in the occurrences points. Jacobs' index as a measure of habitat preference, Shannon and Levins' indices as measures of niche breadth, MacArthur, Levins and Pianka's indices as measures of niche overlap were calculated and interpreted. The results of this study showed that the sand cats are specifically restricted to sand dune and sabulous habitat type, whereas Rüppell's foxes have wider ecological amplitude. Sand cats only prefers sand dunes while Rüppell's foxes were found to prefer foothills, badlands, and sand dunes. Rüppell's foxes therefore had a wider niche breadth compared to the sand cats. The asymmetric MacArthur and Levins indices yielded a higher value of niche overlap for the sand cats compared to Rüppell's foxes, while the symmetric Pianka's measure of niche overlap was relatively high for both species. Such habitat preference and niche segregation between the two species may be a result of their feeding habits or the physical protective structure of their habitats attributes.
2

Predicting the potential invasive range of raccoon in the world

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Farashi A., Naderi M., Safavian S.
Polish Journal of Ecology
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2016
|
tom 64
|
nr 4
Invasive alien species are considered to be one of the most important causes for the extinction and the reason for diminishing of the wild native species. Considering that nowadays the raccoon (Procyon lotor, Linnaeus 1758) is found in several European and Asian countries where it can amplification its ranges remarkably, but it is actually native to North and Central America. Here, we use the Maxent model to generate a preliminary map of the potential distribution of the raccoon around the world and enumerate its relative risk of invasion across all countries. In a study, MaxEnt predicted a significantly large area as the eco-climatically suitable habitat for the raccoon in the world. The predicted habitats are consistent with the wide-ranging habitat associations of the raccoon in its well-established sites. The results identified the hotspots of the raccoon invasion and indicated the possible dispersal pathways. Results also showed that both precipitation and temperature variables were strongly correlated with the raccoon distribution and the species would be absent in cold environments with average sub-zero temperatures.
3

Fat dormouse (Glis glis L.) distribution modeling in the Hyrcanian relict forests of Northern Iran

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Naderi M., Kaboli M., Ahmadi M., Krystufek B.
Polish Journal of Ecology
|
2016
|
tom 64
|
nr 1
The fat dormouse (Glis glis L.) is a small arboreal and extreme habitat specialist mammal that is tightly linked to the deciduous mixed forests dominated by Beech (Fagus orientalis) and oaks (Quercus sp.). Despite its status in Iran as a least concern species, dormice face high risk of extinction in some parts of Europe. The unique life history and large scale distribution of the species in the Palearctic region made it as an ideal model species. This habitat specialist rodent is particularly sensitive to size and connectivity of the forest patches. The fat dormouse shows very deep molecular and morphological divergence in its eastern most parts of its global distribution, in the Hyrcanian refugium of the Northern Iran. Therefore modeling its distributional range can leads to identify biodiversity hotspots and planning conservation activities. The meteorological data, land cover types, topographical variables and geo-referenced points representing geographical locations of the fat dormouse populations (latitude/longitude) in the study area were used as the primary MaxEnt model input data. The predictive accuracy of the Fat Dormouse ecological niche model was significant (training accuracy of 93.3%). This approach successfully identified the areas of the fat dormouse presence across the study area. The result suggests that the maximum entropy modeling approach can be implemented in the next step towards the development of new tools for monitoring the habitat fragmentation and identifying biodiversity hotspots.
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