Determination of the Potential Habitat of Range Plant Species Using Maximum Entropy Method
الموضوعات :Fatemeh Palashi 1 , Hossein Piri Sahragard 2 , Majid Ajorlo 3
1 - Department of Rangeland and Watershed Management, Faculty of Water and Soil, University of Zabol, Iran
2 - Department of Rangeland and Watershed Management, Faculty of Water and Soil, University of Zabol, Iran
3 - Department of Rangeland and Watershed Management, Faculty of Water and Soil, University of Zabol, Iran
الکلمات المفتاحية: MaxEnt, Potential habitat, Jiroft rangelands, Plant distribution, Kappa index,
ملخص المقالة :
This study aimed to identify the most important physical variables affecting the distribution of four range plants species (Tamarix aphylla, Calligonum comosum, Prosopis spicigera and Salsola rigida) habitats and to prepare potential habitat map of the species using Maximum Entropy (MaxEnt) method in rangelands of Jiroft city, Kerman province, located in SE Iran. To this end, sampling of vegetation including species type and percent cover was conducted with randomized-systematic method in 2015. Sample size was determined as 60 plots with a quadrat size of 25-100 m2. For soil sampling, eight profiles were dug in each habitat and samples were taken at two depths, i.e., 0–30 and 30–60 cm. Results indicated that the classification accuracy of the model was acceptable and soil variables including EC, percentage of lime, organic matter, moisture content and texture had the greatest effect on the distribution of the studied plant species habitats. Correlations between the actual and predicted maps for Tamarix aphylla and Calligonum comosum habitats were at a very good level, Kappa = 0.81 and 0.79, respectively, for Prosopis spicigera habitat was at a good level, Kappa = 0.75, and finally for Salsola rigida was at a moderate level, Kappa = 0.53. These results indicate that the MaxEnt method can provide valuable information about the physical conditions of plant habitats in arid rangeland. Knowledge on physical characteristics of plant habitats can be useful in determination of potential habitats and rangeland improvement projects.
Ahqaqi, R., 2011. A study of some ecological properties of four scenic bodies in Yazd province. MSc thesis, Faculty of Natural Resources and Desert Study, Yazd University, 74p.
Ardestani, E. G., Tarkesh, M., Bassiri, M. and Vahabi, M. R., 2015. Potential habitat modeling for reintroduction of three native plant species in central Iran. Journal of Arid Land, 7: 381-390.
Arekhi, S., Heydari, M. and Pourbabaei, H., 2010. Vegetation-environmental relationships and ecological species groups of the Ilam oak forest landscape, Iran. Caspian Journal of Environmental Sciences, 8: 115-125.
Azarnivand, H., Joneidi Jafari, H., Nikoo, SH., Zare Chahouki, M. A. and Malekian, A. 2010. Study of effective ecological factors on distribution of vegetation types (Case study: Southern margin of Haj Aligholi Kavir, Damghan). Desert Journal, 15: 1-4.
Cohen, J. A., 1960. Coefficient of agreement for nominal scales. Educational and Psychological Measurement, 20: 37-46.
El-barasi, Y. M. and Barrani, M. W., 2012. Factors affecting natural vegetation on EL-Harouge Mountain, Central part of Libyan desert (Sahara). Bocconea, 24: 199-211.
Enright, N. J., Miller, B. P., and Akhter, R., 2005. Desertvegetation and vegetation-environmentrelationships in Kirthar National Park, Sindh.Pakistan. Journal of Arid Environment, 61: 397-418.
Evangelista, P. H., Kumar, S. and Stohlgren, T. J., 2008. Modelling invasion for a habitat generalist and a specialist plant species. Diversity and Distribution, 14: 808−817.
Guisan, A. and Thuiller W., 2005. Predicting species distribution: offering more than simple habitat models. Ecology Letters, 8: 993-1009.
Hirzel, A., and Guisan A., 2002. Which is the optimalsampling strategy for habitat suitability modelling.Ecological Modelling. 157: 331-341.
Hosseni, S. Z., Kappas. M., Zare Chahouki, M. A., Gerold, G., Erasmi, S. and Rafiei Emam, A., 2013. Modelling potential habitats for Artemisia sieberi and Artemisia aucheri in Poshtkouh area, Central Iran using the maximum entropy model and Geostatistics. Ecological Informatics, 18: 61-68.
Khalasi Ahvazi, L., Zare Chahouki, M. A. and Ghorbannezhad, F., 2012. Comparing Discriminant Analysis, Ecological Niche Factor Analysis and Logistic Regression methods for geographic distribution modelling of Eurotia ceratoides (L.) C. A. Mey. Journal of Rangeland Science, 3: 45-57.
Kumar, S. and Stohlgren, T. J., 2009. Maxent modeling for predicting suitable habitat for threatened and endangered tree Canacomyrica monticola in New Caledonia. Journal of Ecology and the Natural Environment, 1: 94-98.
Luoto, M. and Hjort J., 2005. Downscaling of coarse-grained geomorphological data. Earth Surface Processes and Landforms, 33: 75-89.
Maddahi Nezhad, S., 2015. Modeling the desirability of plant species habitat using MaxEnt method in Jiroft plain. MSC Thesis, Faculty of Water and Soil, University of Zabol, 64p. (In Persian).
Maltez–Mouro, S., Garcia, L.V., Maranon, T. and Freitas, H., 2005. The combined role of topography andoverstory tree composition in promoting edaphic and floristic variation in a Mediterranean forest. Ecological Research, 20: 668-677.
Mohtashamnia, S., Zahedi, GH. and Arzani, H., 2011. Multivariate analysis of rangeland vegetation in relation to edaphical and physiographical factors. Procedia Environmental Sciences, 7: 305-310.
Negga, H. E., 2007. Predictive Modelling of Amphibian Distribution Using Ecological Survey Data: a case study of Central Portugal, Master thesis, International Institute for Geo-Information Science and Earth Observation, Enschede, The Netherlands.
Phillips, S. J., Anderson, R. P. and Schapire R. E., 2006. Maximum entropy modeling of species geographic distributions. Ecological Modelling, 190: 231-259.
Phillips, S. J., Dudik, M. and Schapire, R. E., 2004. A maximum entropy approach to species distribution modeling. In: Proceedings of the 21st International Conference on Machine Learning, ACM Press, New York. 655-662.
Piri Sahragard, H. and Ajorlo, M., 2016. Predicting the distribution of plant species habitats using maximum entropy model (A case study in rangelands of western Taftan, Southeastern Iran). Soil and Environment, 35: 224-234.
Piri Sahragard, H. and Ajorlo, M., 2017. A comparison of logistic regression and maximum entropy for distribution modeling of range plant species (a case study in rangelands of western Taftan, southeastern Iran). Turkish Journal of Botany, 42: 28-38.
Piri Sahragard, H. and Zare Chahouki M.A., 2015. An evaluation of predictive habitat models performance of plant species in Hoze-i Soltan rangelands of Qom province. Ecological Modelling. 309 and 310: 64-71.
Piri Sahragard, H. and Zare Chahouki, M. A., 2016. Modeling of Artemisia sieberi Besser habitat distribution using Maximum Entropy Method in desert rangelands. Journal of Rangeland Science, 6(2): 93- 101.
Piri Sahragard, H., Ajorlo, M. and Karami, P., 2018. Modeling habitat suitability of range plant species using random forest method in arid mountainous rangelands. Journal of Mountain Science. 15(10), 1-13. https://doi.org/10.1007/s11629-018-4898-1.
Sokoti Oskuei, R., Mehdyan, M. H., Mahmodi, S. H. and Qahramani, A., 2007. Comparison of the efficiency of some Geostatistical methods for determination of spatial dispersion of soil salinity, A case study of Urmia plain. Research and development in agriculture and horticulture, 74: 90-98. (In Persian).
Sweet, J. A., 1988. Measuring the accuracy of a diagnostic systems. Science, 240: 1285-1293.
Tarkesh, M. and Jetshcke, G., 2012. Comparison of six correlative models in predictive vegetation mapping on a local scale. Environmental and Ecological Statistics, 19: 437-457.
Tatian M. R., Zabihi A., Tamartash, R. and Shabani, M., 2011. Determination of indicator species of some soil characteristics by ordination method in Kooh-e-Namak rangelands of Qom. Journal of Environmental Studies, 37(52):34-52. (In Persian).
Termansen, M., Mcclean, C. J, Preston, C. D. 2006. The use of genetic algorithms and Bayesian classification to model species distributions. Ecological Modelling, 192: 410–424.
Wu, J., Boucher, A. and Zhang, T., 2008. SGeMS code for pattern simulation of continuous and categorical variables: FILTERSIM. Computers & Geosciences, 34(12): 1863-1874.
Yalpanian, A. A., Karami, M., Shams Esfand Anad, B. and Makhfi, G., 2015. Assessment of Canis lupus gray wolf habitat in Khangrmans protected area of Hamedan Province using MaxEnt method. Quarterly of animal ecology, 7: 19-30.
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. Ecological Engineering, 51: 83-87.
Zare Chahouki, M. A. and Piri Sahragard, H., 2016. MaxEnt modelling for distribution of plant species habitats of rangelands (Iran). Polish Journal of Ecology, 64 (4): 453-467.
Zare Chahouki, 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: 84-94.
Zare Chahouki, M. A., Khalasi Ahvazi, L. and Azarnivand, H., 2012. Comparison of three modelingapproaches for predicting plant species distribution in mountainous scrubvegetation (Semnan rangelands, Iran). Polish Journal of Ecology, 60: 105-117.
