2. Bussmann, R.W., Batsatsashvili, K., Kikvidze, Z., Ghorbani, A., Khajoei Nasab, F., Paniagua-Zambrana, N.Y., Khutsishvili, M., Maisaia, I., Sikharulidze, S., Tchelidze, D. (2020). Rosa canina L., Rosa pimpinellifolia Boiss. Rosaceae. (eds.), Ethnobotany of the Mountain Regions of Far Eastern Europe, Ethnobotany of Mountain Regions, https://doi.org/10.1007/978-3-030-28940-9_118 [DOI:10.1007/978-3-030-28940-9_118.]

3. Daneshkhah, M., Kafi, M., Nikbakht, A., Mirjalili, M.H. (2007). Effect of different levels of nitrogen and potassium on yield indicators and oil of Rosa damascene from Barzok of Kashan. Journal of Horticultural Science and Technology, 8(2), 83-90. (In Persian)

4. Elith, J., Phillips, S.J., Hastie, T., Dudík, M., Chee, Y.E., Yates, C.J. (2011). A statistical explanation of MaxEnt for ecologists. Diversity and Distributions, 17, 43-57. [DOI:10.1111/j.1472-4642.2010.00725.x]

5. Ercisli, S. (2007). Chemical composition of fruits in some rose (Rosa spp.) species. Food Chemistry, 104, 1379- 1384 [DOI:10.1016/j.foodchem.2007.01.053]

6. Fielding, A.H., Haworth, P.F. (1995). Testing the generality of bird‐habitat models. Conservation Biology, 9 (6), 1466-1481. [DOI:10.1046/j.1523-1739.1995.09061466.x]

7. Fois, M., Cuena-Lombraña, A., Fenu, G., Bacchetta, G. (2018). Using species distribution models at local scale to guide the search of poorly known species: Review, methodological issues and future directions. Ecological Modeling, 385, 124-132. [DOI:10.1016/j.ecolmodel.2018.07.018]

8. Ghorbani, A. (2005). Studies on pharmaceutical ethnobotany in the region of Turkmen Sahra, North of Iran (Part1): general results. Journal of Ethnopharmacology, 102, 58-68. [DOI:10.1016/j.jep.2005.05.035]

9. Heubes, J., Schmidt, M., Stuch, B., García Márquez, J.R., Wittig, R., Zizka, G., Thiombiano, A., Sinsin, B., Schaldach, R., Hahn, K. (2013). The projected impact of climate and land use change on plant diversity: An example from West Africa. Journal of Arid Environment, 96, 48-54. [DOI:10.1016/j.jaridenv.2013.04.008]

10. Javanmard, M., Asadi-Gharneh, H.A., Nikneshan, P. (2017). Characterization of biochemical traits of dog rose (Rosa canina L.) ecotypes in the central part of Iran. Natural Product Research, 32(14):1738-1743. [DOI:10.1080/14786419.2017.1396591]

11. Kabata-Pendias, A. (2011). Trace Elements in Soils and Plants, CRC Press, Boca Raton, FL, USA. [DOI:10.1201/b10158]

12. Khalasi Ahwazi, L., Zare Chahouki, M.A., Hosseini, S.Z. (2015). Modeling geographic distribution of Artemisia sieberi and Artemisia aucheri using presence-only modelling methods (MaxEnt & ENFA). Journal of Renewable Natural Resources Research, 6(1), 57-74. (In Persian)

13. Khalighifar, A. (2015). Detect potential habitat of Rheum ribes L. in the Esfahan province using MaxEnt and Garp. Thesis of graduate student. Department of natural resources, Esfahan University of Technology. (In Persian)

14. Kelly, A.E., Goulden, M.L. (2008). Rapid shifts in plant distribution with recent climate change. PNAS, 105 (33), 11823-11826 [DOI:10.1073/pnas.0802891105]

15. Kumar, S., Stohlgren, T.J. (2009). Maxent modeling for predicting suitable habitat for threatened and endangered tree Canacomyrica monticolain New Caledonia. Journal of Ecology and the Natural Environment, 1(4), 094-098.

16. Lemke, D., Hulme, P.E., Brown, J.A., Tadesse, W. (2011). Distribution modelling of Japanese honeysuckle (Lonicera japonica) invasion in the Cumberland Plateau and Mountain Region, USA. Journal of Forest Ecology and Management, 262(2), 139-149. [DOI:10.1016/j.foreco.2011.03.014]

17. Leus, L., Laere, K.V., Riek, J.D., Huylenbroeck, J.V. (2018). Rose. J. Van Huylenbroeck (ed.), Ornamental Crops, Handbook of Plant Breeding 11, Springer International Publishing AG, part of Springer Nature, https://doi.org/10.1007/978-3-319-90698-0_27 [DOI:10.1007/978-3-319-90698-0_27.]

18. Marschner, H. (1995). Mineral Nutrition of Higher Plants, 2nd ed. Cambridge, UK: Academic Press.

19. Manimaran, P., Rajasekar, P., Rameshkumar, D., Jaison, M. (2017). Role of nutrients in plant growth and flower quality of rose: A review. International Journal of Chemical Studies, 5(6), 1734-1737.

20. Mirzadeh Vaghefi, S.S., Jalili, A., Jamzad, Z. (2020). Native plants with ornamental potential for planting in urban green space of Tehran. Flower and Ornamental Plants, 4(2), 131-142. (In Persian) [DOI:10.29252/flowerjournal.4.2.131]

21. Momeni damaneh, J., Esmaeilpour, Y., Gholami, H., Farashi, A. (2022). Prediction of potential habitat of Astracantha gossypina (Fisch). Using the maximum entropy model in regional scale. Journal of Plant Ecosystem Conservation, 9(19), 217-236. (In Persian)

22. Mosaddegh M, Naghibi F, Moazzeni H, Pirani A, Esmaeili S. (2012). Ethnobotanical survey of herbal remedies traditionally used in Kohghiluyeh va Boyer Ahmad province of Iran. Journal of Ethnopharmacology, 141, 80-95. [DOI:10.1016/j.jep.2012.02.004]

23. Mousazade, M., Ghanbarian, G., Pourghasemi, H.R., Safaeian, R., Cerdà, A. (2019). MaxEnt data mining technique and its comparison with a bivariate statistical model for predicting the potential distribution of Astragalus Fasciculifolius Boiss. in Fars, Iran. Sustainability, 11, 3452. [DOI:10.3390/su11123452]

24. Neina, D. (2019). The Role of Soil pH in Plant Nutrition and Soil Remediation. Applied and Environmental Soil Science, 2019, 5794869. doi.org/10.1155/2019/5794869 [DOI:10.1155/2019/5794869]

25. Pehlivan, M., Mohammed, F.S., Sevindik, M., Akgul, H. (2018). Antioxidant and oxidant potential of Rosa canina. Eurasian Journal of Forest Science, 6(4), 22-25. [DOI:10.31195/ejejfs.475286]

26. Phillips, S.J., Dudík, M. (2008). Modeling of species distributions with Maxent: New extensions and a comprehensive evaluation. Ecography, 31, 161-175. [DOI:10.1111/j.0906-7590.2008.5203.x]

27. Phillips, S.J., Anderson, R.P., Schapire, R.E., (2006). Maximum entropy modeling of species geographic distributions. Ecological Modelling, 190, 231-259. [DOI:10.1016/j.ecolmodel.2005.03.026]

28. Qin, A., Liu, B., Guo, Q., Bussmann, R.W., Ma, F., Jian, Z., Pei, S. (2017). Maxent modeling for predicting impacts of climate change on the potential distribution of Thuja sutchuenensis Franch., an extremely endangered conifer from southwestern China. Global Ecology & Conservation, 10, 139-146. [DOI:10.1016/j.gecco.2017.02.004]

29. Rahimian Boogar, A., Salehi, H., Pourghasemi, H.R., Blaschke, T. (2019). Predicting Habitat Suitability and Conserving Juniperus spp. Habitat Using SVM and Maximum Entropy Machine Learning Techniques. Water, 11, 2049, doi:10.3390/w11102049. [DOI:10.3390/w11102049]

30. Sajid, A.H., Rudra, R.P., Parkin, G. (2013). Systematic evaluation of kriging and inverse distance weighting methods for spatial analysis of soil bulk density. Canadian Biosystems Engineering, 55, 1-13. [DOI:10.7451/CBE.2013.55.1]

31. Selahvarzian, A., Alizadeh, A., Baharvand, P.A., Eldahshan, O.A., Rasoulian, B. (2018). Medicinal Properties of Rosa canina L. Herbal Medicines Journal, 3(2), 77-84.

32. Silva, L.D., Costa, H., de Azevedo, E.B., Medeiros, V., Alves, M., Elias, R.B., Silva, L. (2017). Modelling Native and Invasive Woody Species: A Comparison of ENFA and MaxEnt Applied to the Azorean Forest. In Modeling, Dynamics, Optimization and Bioeconomics II, Proceedings in Mathematics & Statistics, Pinto, A.A., Zilberman, D., Eds., Springer: Berlin, Germany, 195, 415-444. [DOI:10.1007/978-3-319-55236-1_20]

33. Soti, P.G., Jayachandran, K., Koptur, S., Volin, J.C. (2015). Effect of soil pH on growth, nutrient uptake, and mycorrhizal colonization in exotic invasive Lygodium microphyllum. Plant Ecology, 216, 989-998 [DOI:10.1007/s11258-015-0484-6]

34. Tesfamariam, B.G., Gessesse, B., Melgani, F. (2022). MaxEnt-based modeling of suitable habitat for rehabilitation of Podocarpus forest at landscape-scale. Environmental Systems Research, 11(4), 1-12. [DOI:10.1186/s40068-022-00248-6]

35. Thorn, J.S., Nijman, V., Smith, D., Nekaris, K.A.I. (2009). Ecological niche modelling as a technique for assessing threats and setting conservation priorities for Asian slow lorises (Primates: Nycticebus). Diversity and Distributions, 15(2), 289-298. [DOI:10.1111/j.1472-4642.2008.00535.x]

36. Tunçay, T., Bayramin, I., Atalay, F., Ünver, I. (2016). Assessment of inverse distance weighting (IDW) interpolation on spatial variability of selected soil properties in the Cukurova plain. Journal of Agricultural Sciences, 22, 377-384. [DOI:10.15832/ankutbd.257726]

37. Vukosavljeva, M., J. Zhang, J., Esselink, G.D., van't Westende, W.P.C., Cox, P., Visser, R.G.F., Arens, P., Smulders, M.J.M. (2013). Genetic diversity and differentiation in roses: A garden rose perspective. Scientia Horticulturae, 162(23), 320-332. [DOI:10.1016/j.scienta.2013.08.015]

38. Yang, X.Q., Kushwaha, S.P.S., Saran, S., Xu, J., Roy, P.S. (2013). Maxent modeling for predicting the potential distribution of medicinal plant, Justicia adhatoda L. in Lesser Himalayan foothills. Ecologycal Engineering, 51, 83-87. [DOI:10.1016/j.ecoleng.2012.12.004]

39. Zarabi, M., Haghdadi, R., Yousefi, H. (2017). Habitat utility modeling of organic (wild) pistachios (Pistacia Vera) using Maximum Entropy Method (MaxEnt) in Sarakhs Forest Area (Gonbadli in khorasan Province). Iranian Journal of Ecohydrology, 4(3), 817-824. (In Persian)

40. Zare Chahouki, M.A., Abbasi, M. (2018). Habitat prediction model medicinal species of Rheum ribes L. with Maximum Entropy model in Chahtorsh rangeland of the Yazd province. Journal of Range and Watershed Management, 71(2), 379-391. (In Persian)

41. Zhang, K., Zhang, Y., Zhou, C., Meng, J., Sun, J., Zhou, T., Tao, J. (2019). Impact of climate factors on future distributions of Paeonia ostii across China estimated by MaxEnt. Ecological Informatics, 50, 62-67. [DOI:10.1016/j.ecoinf.2019.01.004]

42. Abrha, H., Birhane, E., Hagos, H., Manaye, A. (2018) Predicting suitable habitats of endangered Juniperus procera tree under climate change in Northern Ethiopia. Journal of Sustainable Forestry, 37(8), 842-853. [DOI:10.1080/10549811.2018.1494000]

43. Bussmann, R.W., Batsatsashvili, K., Kikvidze, Z., Ghorbani, A., Khajoei Nasab, F., Paniagua-Zambrana, N.Y., Khutsishvili, M., Maisaia, I., Sikharulidze, S., Tchelidze, D. (2020). Rosa canina L., Rosa pimpinellifolia Boiss. Rosaceae. (eds.), Ethnobotany of the Mountain Regions of Far Eastern Europe, Ethnobotany of Mountain Regions, https://doi.org/10.1007/978-3-030-28940-9_118 [DOI:10.1007/978-3-030-28940-9_118.]

44. Daneshkhah, M., Kafi, M., Nikbakht, A., Mirjalili, M.H. (2007). Effect of different levels of nitrogen and potassium on yield indicators and oil of Rosa damascene from Barzok of Kashan. Journal of Horticultural Science and Technology, 8(2), 83-90. (In Persian)

45. Elith, J., Phillips, S.J., Hastie, T., Dudík, M., Chee, Y.E., Yates, C.J. (2011). A statistical explanation of MaxEnt for ecologists. Diversity and Distributions, 17, 43-57. [DOI:10.1111/j.1472-4642.2010.00725.x]

46. Ercisli, S. (2007). Chemical composition of fruits in some rose (Rosa spp.) species. Food Chemistry, 104, 1379- 1384 [DOI:10.1016/j.foodchem.2007.01.053]

47. Fielding, A.H., Haworth, P.F. (1995). Testing the generality of bird‐habitat models. Conservation Biology, 9 (6), 1466-1481. [DOI:10.1046/j.1523-1739.1995.09061466.x]

48. Fois, M., Cuena-Lombraña, A., Fenu, G., Bacchetta, G. (2018). Using species distribution models at local scale to guide the search of poorly known species: Review, methodological issues and future directions. Ecological Modeling, 385, 124-132. [DOI:10.1016/j.ecolmodel.2018.07.018]

49. Ghorbani, A. (2005). Studies on pharmaceutical ethnobotany in the region of Turkmen Sahra, North of Iran (Part1): general results. Journal of Ethnopharmacology, 102, 58-68. [DOI:10.1016/j.jep.2005.05.035]

50. Heubes, J., Schmidt, M., Stuch, B., García Márquez, J.R., Wittig, R., Zizka, G., Thiombiano, A., Sinsin, B., Schaldach, R., Hahn, K. (2013). The projected impact of climate and land use change on plant diversity: An example from West Africa. Journal of Arid Environment, 96, 48-54. [DOI:10.1016/j.jaridenv.2013.04.008]

51. Javanmard, M., Asadi-Gharneh, H.A., Nikneshan, P. (2017). Characterization of biochemical traits of dog rose (Rosa canina L.) ecotypes in the central part of Iran. Natural Product Research, 32(14):1738-1743. [DOI:10.1080/14786419.2017.1396591]

52. Kabata-Pendias, A. (2011). Trace Elements in Soils and Plants, CRC Press, Boca Raton, FL, USA. [DOI:10.1201/b10158]

53. Khalasi Ahwazi, L., Zare Chahouki, M.A., Hosseini, S.Z. (2015). Modeling geographic distribution of Artemisia sieberi and Artemisia aucheri using presence-only modelling methods (MaxEnt & ENFA). Journal of Renewable Natural Resources Research, 6(1), 57-74. (In Persian)

54. Khalighifar, A. (2015). Detect potential habitat of Rheum ribes L. in the Esfahan province using MaxEnt and Garp. Thesis of graduate student. Department of natural resources, Esfahan University of Technology. (In Persian)

55. Kelly, A.E., Goulden, M.L. (2008). Rapid shifts in plant distribution with recent climate change. PNAS, 105 (33), 11823-11826 [DOI:10.1073/pnas.0802891105]

56. Kumar, S., Stohlgren, T.J. (2009). Maxent modeling for predicting suitable habitat for threatened and endangered tree Canacomyrica monticolain New Caledonia. Journal of Ecology and the Natural Environment, 1(4), 094-098.

57. Lemke, D., Hulme, P.E., Brown, J.A., Tadesse, W. (2011). Distribution modelling of Japanese honeysuckle (Lonicera japonica) invasion in the Cumberland Plateau and Mountain Region, USA. Journal of Forest Ecology and Management, 262(2), 139-149. [DOI:10.1016/j.foreco.2011.03.014]

58. Leus, L., Laere, K.V., Riek, J.D., Huylenbroeck, J.V. (2018). Rose. J. Van Huylenbroeck (ed.), Ornamental Crops, Handbook of Plant Breeding 11, Springer International Publishing AG, part of Springer Nature, https://doi.org/10.1007/978-3-319-90698-0_27 [DOI:10.1007/978-3-319-90698-0_27.]

59. Marschner, H. (1995). Mineral Nutrition of Higher Plants, 2nd ed. Cambridge, UK: Academic Press.

60. Manimaran, P., Rajasekar, P., Rameshkumar, D., Jaison, M. (2017). Role of nutrients in plant growth and flower quality of rose: A review. International Journal of Chemical Studies, 5(6), 1734-1737.

61. Mirzadeh Vaghefi, S.S., Jalili, A., Jamzad, Z. (2020). Native plants with ornamental potential for planting in urban green space of Tehran. Flower and Ornamental Plants, 4(2), 131-142. (In Persian) [DOI:10.29252/flowerjournal.4.2.131]

62. Momeni damaneh, J., Esmaeilpour, Y., Gholami, H., Farashi, A. (2022). Prediction of potential habitat of Astracantha gossypina (Fisch). Using the maximum entropy model in regional scale. Journal of Plant Ecosystem Conservation, 9(19), 217-236. (In Persian)

63. Mosaddegh M, Naghibi F, Moazzeni H, Pirani A, Esmaeili S. (2012). Ethnobotanical survey of herbal remedies traditionally used in Kohghiluyeh va Boyer Ahmad province of Iran. Journal of Ethnopharmacology, 141, 80-95. [DOI:10.1016/j.jep.2012.02.004]

64. Mousazade, M., Ghanbarian, G., Pourghasemi, H.R., Safaeian, R., Cerdà, A. (2019). MaxEnt data mining technique and its comparison with a bivariate statistical model for predicting the potential distribution of Astragalus Fasciculifolius Boiss. in Fars, Iran. Sustainability, 11, 3452. [DOI:10.3390/su11123452]

65. Neina, D. (2019). The Role of Soil pH in Plant Nutrition and Soil Remediation. Applied and Environmental Soil Science, 2019, 5794869. doi.org/10.1155/2019/5794869 [DOI:10.1155/2019/5794869]

66. Pehlivan, M., Mohammed, F.S., Sevindik, M., Akgul, H. (2018). Antioxidant and oxidant potential of Rosa canina. Eurasian Journal of Forest Science, 6(4), 22-25. [DOI:10.31195/ejejfs.475286]

67. Phillips, S.J., Dudík, M. (2008). Modeling of species distributions with Maxent: New extensions and a comprehensive evaluation. Ecography, 31, 161-175. [DOI:10.1111/j.0906-7590.2008.5203.x]

68. Phillips, S.J., Anderson, R.P., Schapire, R.E., (2006). Maximum entropy modeling of species geographic distributions. Ecological Modelling, 190, 231-259. [DOI:10.1016/j.ecolmodel.2005.03.026]

69. Qin, A., Liu, B., Guo, Q., Bussmann, R.W., Ma, F., Jian, Z., Pei, S. (2017). Maxent modeling for predicting impacts of climate change on the potential distribution of Thuja sutchuenensis Franch., an extremely endangered conifer from southwestern China. Global Ecology & Conservation, 10, 139-146. [DOI:10.1016/j.gecco.2017.02.004]

70. Rahimian Boogar, A., Salehi, H., Pourghasemi, H.R., Blaschke, T. (2019). Predicting Habitat Suitability and Conserving Juniperus spp. Habitat Using SVM and Maximum Entropy Machine Learning Techniques. Water, 11, 2049, doi:10.3390/w11102049. [DOI:10.3390/w11102049]

71. Sajid, A.H., Rudra, R.P., Parkin, G. (2013). Systematic evaluation of kriging and inverse distance weighting methods for spatial analysis of soil bulk density. Canadian Biosystems Engineering, 55, 1-13. [DOI:10.7451/CBE.2013.55.1]

72. Selahvarzian, A., Alizadeh, A., Baharvand, P.A., Eldahshan, O.A., Rasoulian, B. (2018). Medicinal Properties of Rosa canina L. Herbal Medicines Journal, 3(2), 77-84.

73. Silva, L.D., Costa, H., de Azevedo, E.B., Medeiros, V., Alves, M., Elias, R.B., Silva, L. (2017). Modelling Native and Invasive Woody Species: A Comparison of ENFA and MaxEnt Applied to the Azorean Forest. In Modeling, Dynamics, Optimization and Bioeconomics II, Proceedings in Mathematics & Statistics, Pinto, A.A., Zilberman, D., Eds., Springer: Berlin, Germany, 195, 415-444. [DOI:10.1007/978-3-319-55236-1_20]

74. Soti, P.G., Jayachandran, K., Koptur, S., Volin, J.C. (2015). Effect of soil pH on growth, nutrient uptake, and mycorrhizal colonization in exotic invasive Lygodium microphyllum. Plant Ecology, 216, 989-998 [DOI:10.1007/s11258-015-0484-6]

75. Tesfamariam, B.G., Gessesse, B., Melgani, F. (2022). MaxEnt-based modeling of suitable habitat for rehabilitation of Podocarpus forest at landscape-scale. Environmental Systems Research, 11(4), 1-12. [DOI:10.1186/s40068-022-00248-6]

76. Thorn, J.S., Nijman, V., Smith, D., Nekaris, K.A.I. (2009). Ecological niche modelling as a technique for assessing threats and setting conservation priorities for Asian slow lorises (Primates: Nycticebus). Diversity and Distributions, 15(2), 289-298. [DOI:10.1111/j.1472-4642.2008.00535.x]

77. Tunçay, T., Bayramin, I., Atalay, F., Ünver, I. (2016). Assessment of inverse distance weighting (IDW) interpolation on spatial variability of selected soil properties in the Cukurova plain. Journal of Agricultural Sciences, 22, 377-384. [DOI:10.15832/ankutbd.257726]

78. Vukosavljeva, M., J. Zhang, J., Esselink, G.D., van't Westende, W.P.C., Cox, P., Visser, R.G.F., Arens, P., Smulders, M.J.M. (2013). Genetic diversity and differentiation in roses: A garden rose perspective. Scientia Horticulturae, 162(23), 320-332. [DOI:10.1016/j.scienta.2013.08.015]

79. Yang, X.Q., Kushwaha, S.P.S., Saran, S., Xu, J., Roy, P.S. (2013). Maxent modeling for predicting the potential distribution of medicinal plant, Justicia adhatoda L. in Lesser Himalayan foothills. Ecologycal Engineering, 51, 83-87. [DOI:10.1016/j.ecoleng.2012.12.004]

80. Zarabi, M., Haghdadi, R., Yousefi, H. (2017). Habitat utility modeling of organic (wild) pistachios (Pistacia Vera) using Maximum Entropy Method (MaxEnt) in Sarakhs Forest Area (Gonbadli in khorasan Province). Iranian Journal of Ecohydrology, 4(3), 817-824. (In Persian)

81. Zare Chahouki, M.A., Abbasi, M. (2018). Habitat prediction model medicinal species of Rheum ribes L. with Maximum Entropy model in Chahtorsh rangeland of the Yazd province. Journal of Range and Watershed Management, 71(2), 379-391. (In Persian)

82. Zhang, K., Zhang, Y., Zhou, C., Meng, J., Sun, J., Zhou, T., Tao, J. (2019). Impact of climate factors on future distributions of Paeonia ostii across China estimated by MaxEnt. Ecological Informatics, 50, 62-67. [DOI:10.1016/j.ecoinf.2019.01.004]