فهرست مطالب anoosheh kafash

Little is known about altitudinal distribution of lizards in Iran. In the present study we studied distribution pattern of members of family Lacertidae along the eleveatinal gradient in Iran. To determine environmental drivers of distribution pattern of 48 lizard species, all known valid members of family Lacertidae, along elevational gradient in Iran. Firstly, we classified Iran digital elevation model (DEM) based on 100m intervals, that resulted in 56 altitudinal bands and number of species in each band was recorded. Secondly, we extracted mean value of following variables; altitude, slop, area, solar radiation index (SRI), normalized differences vegetation index (NDVI), annual precipitation, precipitation of wettest month, precipitation of driest month precipitation, precipitation of wettest quarter, precipitation of driest quarter, and precipitation of warmest quarter, and using VIF measure correlated variables were removed. Finally, we performed a multiple regression and found that area and precipitation of warmest quarter are the most important drivers of distribution pattern of family Lacertidae along elevational gradient in Iran. General distribution pattern of family Lacertidae was unimodal and maximum number of species living from 1475 m to 1675 m.

Modeling potential distributions in order to find unidentified populations of rare and endangered species in inaccessible areas is a promising tool for conservation biologists. Mountain viper (Montivipera spp.) comprises M. raddei raddei, M. latifii, M. r. albicornuta, and M. Kuhrangica, which are patchily distributed throughout Alborz and Zagros Mountain Ranges of Iran. Identifying unrecorded populations of these species within the already established distribution range is critical in conservation action planning such as corridor design and protected area establishment as well as genetic management of the species. In this study, with an aim to predict the occurrence of unidentified mountain viper populations, we used the Ensemble method as well as four modeling algorithms including Maximum Entropy (Maxent), Artificial Neural Networks (ANN), Support Vector Machine (SVM), and Generalized Linear Modeling (GLM). Locality points were collected for mountain vipers from western Iran and large-scale habitat variables related to topography, climate, and land use/cover were used in the modeling. Results indicated that temperature in the warmest month, precipitation in the driest month, and slope were the most important predictors of mountain viper presence in suitable habitats. Among the four modeling algorithms, Maxent (AUC= 0.97) and SVM (AUC= 0.85) showed the highest and the lowest predictive powers, respectively. Pooling the results of the modeling methods, we found that possibility of finding new populations of mountain vipers is highest in Dalakhani (Amrolah and Bistoun) ÑÂæ in Kermanshah province, Chehel-cheshmeh and Hezarkanian in Kordestan province, Oramanat at the border of the two aforementioned provinces, and Almubolagh and Garin in western and southern Hamedan province respectively. Currently, 31.6 percent of the suitable habitats identified in our models are represented within the network of national protected areas. Establishment of new protected areas in suitable locations identified in our models can complement the current system of protected areas for conservation of mountain vipers, especially the endemic species. We also determined the effects of climate change on the extent and suitability of mountain viper habitats in the past (Last Glacial Maximum, 21000 years ago) and the future (the year 2070) using 19 climatic variables. Considering the recent and predicted rates of global warming, our climatic models point to a continuous contraction of suitable habitats for mountain vipers from the past to the year 2070. This thought-provoking finding warns that the negative effects of climate change on biodiversity and specifically in our study, endemic mountain vipers.