Document Type : Research Paper

Authors

1 Professor, Department of Reclamation of Arid and Mountainous Regions, Natural Resources Faculty, University of Tehran, Tehran, Iran

2 Former M.Sc. in Range Management, Department of Reclamation of Arid and Mountainous Regions, Natural Resources Faculty, University of Tehran, Iran

3 Professor, Department of Reclamation of Arid and Mountainous Regions, Natural Resources Faculty, University of Tehran, Iran

Abstract

     The study was performed with the aim of modeling the distribution habitats of Eshtehard rangelands using Maximum Entropy Method and determining the factors affecting each habitat. Vegetation and environmental data including soil characteristics and topography were collected. The initial map was prepared based on slope, elevation and direction maps and satellite images. At each site, three transects with a length of 750 m were established, two transects along the most important environmental gradients and one transect perpendicular to them. A number of 45 plots along each transect was placed at a distance of 50 meters. The size of plot sampling was determined to be two square meters according to the type and distribution of plant species with minimal area method. Soil profiles were dug at the beginning and end of each transect. Sampling was done from the depths of 0-20 cm and 20-80 cm. The list of species and the percentage of vegetation in each plot were determined. For each sampling unit, the latitude and longitude data, slope, direction, and elevation were also determined. Then the desired characteristics were measured in the laboratory. GIS and Geostatistics methods were used to map the environmental variables. The species distribution models were produced using the species presence data and Maximum Entropy Method (Maxent). The Kappa coefficient index and the area under the curve (AUC) were used to evaluate the accuracy of the distribution maps. The agreements of actual and predicted maps for Pteropyrum olivieri was well (K=0/7) and it was acceptable for Halocnemum strobilaceum, Salsola richteri‏-Artemisia sieberi, Artemisia sieberi, Artemisia sieberiStipa barbata (K=0/66, 0/64, 0/57, 0/66).

Keywords

-  Abdollahi J. and Naderi, H., 2011. Soil and topographical variation influencing the growing factors of Artemisia sieberi in steppic rangeland, Nodoushan-Yazd. Watershed Management Research (Pajouhesh&Sazandegi), 97: 52-62.
-  Abd El-Ghani, M. M. and Amer, W. M., 2003. Soil-Vegetation Relationships in a Coastal Desert Plain of Soutern Sinai, Egypt. Journal of Arid Environments, 55: 607-628.
-  Baldvin, R. A., 2009. Use of Maximum Entropy in Wildlife Research. Journal of Entropy, 1: 854-866.
-  Evangelista, Ph., Kumar, S., Stohlgren, T. J., Jarnevich, C. S., Crall, A. W., Norman, J. B. and Barnett, DT., 2008. Modelling invasion for a habitat generalist and a specialist plant species. Journal of Divers Distributions, 14:808-817.
-  Elith, J., Graham, C. H. and Anderson, R.P., 2006. Novel methods improve prediction of species’distributions from occurrence data. Journal of Ecography. 29: 129- 151.
-  Hosseini, S. Z., Kappas, M., ZareChahouki, M. A., Gerold, G., Erasmia, S. and RafieiEmama, A., 2013. Modelling potential habitats for Artemisia sieberi and Artemisia aucheri in Poshtkouh area, central Iran using the maximum entropy model and geostatistics, Journal of Ecological Informatics, 18: 61-68.
-  KhalasiAhwazi, L., ZareChahouki, M. A., Azarnivand, H. and SoltaniGardFaramarzi, M., 2011. Desirable habitat modeling of Eurotiaceratoides (L.) CAM Using ecological niche factor analysis (ENFA) in North East Semnan ranges. Journal of Range Management, 4: 373-362.
-  Mbatudde, M., Mwanjololo, M., KyomugishaKakudidi, E. and Dalitz, H., 2012. Modelling the potential distribution of endangered Prunusafricana(Hook.f.)Kalkm in East Africa. African Journal Ecology, 50: 393–403.
-  Mostafa, A. and Zaghloul, M., 1996. Environment and Vegetation in the Montane Saint Catherine. Journal of Arid Environment, 34: 331-349.
-  Pearson, R. G., Raxworthy, C. J., Nakamura, M. and Peterson, A.T., 2007. Predicting species' distributions from small numbers of occurrence records: A test case using cryptic geckos in Madagascar. Journal of Biogeography, 34: 102- 117.
-  Peterson, A.T. and Shaw, J., 2003. Lutzomyia vectors for cutaneous leishmaniasis in southern Brazil: ecological niche models, predicted geographic distribution, and climate change effects. Int. Journal of Parasitol, 33: 919-931.
-  Qu, X. X., Huang, Z. Y., Baskin, J. M. and Baskin, C.C., 2008. Effect of Temperature, Light and salinity on seed and Germination and Radicle Growth of the geographically widespread Halophyte shrub Halocnemum strobilaceum, Annals of botany, 101(2): 293-299.
-  Vessella, F. and Schirone, B., 2013. Predicting potential distribution of Quercussuber in Italy based on ecological niche models: Conservation insights and reforestation involvements Forest Ecology and Management: 304, 150–161.
-  Yang, X. Q., Kushwaha, S. P. S., Saran. S., Xu, J. and Roy, P. S., 2013. Maxent modeling for predicting the potential distribution of medicinal plant, Justicia adhatoda L. in Lesser Himalayan foothills. Journal of Ecological Engineering, 51: 83–87.
-  ZareChahouki, M. A., Azarnivand, H., Jafari, M. and Tavili, A., 2010. Multivariate Statistical Methods as a Tool for Model-Based Prediction of Vegetation Types, Russian Journal of Ecology, 41(1): 84-94.
-  ZareChahouki, M. A., PirySahragard, H. and Azarnivand, H., 2013. Habitat distribution modeling of some halophyte plant species using Maximum Entropy Method (Maxent) in HozeSoltan rangelands of Qum Province. Journal of Rangeland, 7(3): 212-221.
-  ZareChahouki, M. A. and Esfanjani, J., 2015. Predicting potential distribution of plant species by modeling techniques in southern rangelands of Golestan, Iran. Journal of Range Management and Agroforestry, 36(1): 66-71.