| Article ID | Journal | Published Year | Pages | File Type |
|---|---|---|---|---|
| 4374930 | Ecological Informatics | 2013 | 8 Pages |
•Geostatistics and maximum entropy model are very effective at determining habitat distribution for different species.•In addition to using climatic and topographic data which have been used in most of the previous researches in the field of ecological modelling, soil data improve the predictive ability for habitat distribution mapping of plant species.•The results of Maxent modeling provided key information about the environmental tolerances of the Artemisia species in the study area that can be used for protecting susceptible habitats from future invasion and impacts of climate change.
Predicting potential habitats of endemic species is a suitable method for biodiversity conservation and rehabilitation of rangeland ecosystems. The present study was conducted to estimate the geographic distribution of Artemisia sieberi (A. sieberi) and Artemisia aucheri (A. aucheri), find the most important environmental predictor variables and seek for similarities and differences in habitat preferences between the two species for Poshtkouh rangelands in Central Iran. Maps of environmental variables were created by means of geographic information system (GIS) and geostatistics. Then predictive distribution maps of both species were produced using the maximum entropy modeling technique (Maxent) and presence-only data. Model accuracy is evaluated by using the area under the curve (AUC). Lime1, gravel1, lime 2 and elevation most significantly affect habitat distribution of A. aucheri, while habitat distribution of A. sieberi is affected by elevation, lime1, am1, lime2, and om2. For both species, elevation has an influence on their potential distributions. However, A. aucheri depends more on elevation, and consequently climate in comparison to A. sieberi. Finally, it is revealed that the potential distribution of A. aucheri is limited mostly to mountainous landscapes while A. sieberi is present in wide ranges of environmental conditions.
