| تعداد نشریات | 282 |
| تعداد نشریات سازمان | 80 |
| تعداد شمارهها | 3,219 |
| تعداد مقالات | 35,690 |
| تعداد مشاهده مقاله | 53,573,830 |
| تعداد دریافت فایل اصل مقاله | 92,853,368 |
پیشبینی رویشگاه آویشن Thymus kotschyanus بر اساس عوامل محیطی با مدلسازی رگرسیون لجستیک(مطالعه موردی: دولانیه، پیرانشهر) | ||
| تحقیقات مرتع و بیابان ایران | ||
| دوره 33، شماره 2، تیر 1405، صفحه 191-200 | ||
| نوع مقاله: مقاله پژوهشی | ||
| شناسه دیجیتال (DOI): 10.22092/ijrdr.2026.135838 | ||
| نویسندگان | ||
| سمیه سوری1؛ شهریار دشتی* 2؛ یوسف اجنی3؛ اسماعیل کریمی4؛ الهام نوری5 | ||
| 1دانشجوی اکولوژی گیاهان زراعی، گروه مهندسی تولید و ژنتیک گیاهی، دانشکده کشاورزی، دانشگاه مراغه، آذربایجان شرقی، ایران | ||
| 2استادیار گروه مهندسی تولید و ژنتیک گیاهی، دانشکده کشاورزی، دانشگاه مراغه | ||
| 3استادیار پژوهشی،مؤسسه تحقیقات جنگلها و مراتع کشور، سازمان تحقیقات، آموزش و ترویج کشاورزی، تهران، ایران | ||
| 4استادیار، گروه مهندسی تولید و ژنتیک گیاهی، دانشکده کشاورزی، دانشگاه مراغه، آذربایجان شرقی، ایران | ||
| 5کارشناس محقق ،مؤسسه تحقیقات جنگلها و مراتع کشور، سازمان تحقیقات، آموزش و ترویج کشاورزی، تهران، ایران | ||
| چکیده | ||
| چکیده سابقه و هدف عوامل محیطی میتواند تأثیر زیادی بر پراکنش گونههای گیاهی داشته باشد. پیشبینی رویشگاه گونهها نیازمند شناخت این اثرات است. آویشن از مهمترین جنسهای خانواده نعناعیان با ۲۱۵ گونه است که بهطور گسترده در جهان، خصوصاً منطقه مدیترانه، پراکنش دارد. هدف پژوهش حاضر پیشبینی رویشگاه گونه Thymus kotschyanus با استفاده از مدل رگرسیون لجستیک و روشهای درونیابی در منطقه دولانیه شهرستان پیرانشهر است. مواد و روشها متغیرهای توپوگرافی شامل ارتفاع از سطح دریا، درصد شیب و جهت شیب از مدل ارتفاع رقومی (DEM) منطقه و پارامترهای اقلیمی شامل متوسط درجه حرارت و بارندگی برای ایستگاه سینوپتیک دولانیه استخراج شد. تعداد 94 نقطهی حضور و عدم حضور گونه آویشن بهصورت سیستماتیک تصادفی نمونهبرداری شد. برای بررسی رابطه بین حضور گونه و عوامل محیطی از روش رگرسیون لجستیک دوتایی در نرمافزار SPSS استفاده شد. تغییرات مکانی احتمال حضور گونه نیز با استفاده از روشهای درونیابی قطعی و زمینآماری بررسی شد نتایج نتایج نشان داد احتمال حضور آویشن با متغیرهای عرض جغرافیایی، جهت شیب، عرض برگ، درصد کربن آلی خاک، کربنات کلسیم، مس، متوسط بارندگی ماهانه و سالانه، درصد شن و رس رابطه معکوسی دارند. درحالیکه متغیرهای شیب، طول برگ، ارتفاع گیاه، هدایت الکتریکی، pH، روی، آهن و متوسط دما با احتمال حضور آویشن رابطه مستقیمی دارند. احتمال حضور آویشن در مناطق خشک و نیمهخشک با شیب مناسب افزایش مییابد. توزیع مکانی احتمال حضور نشان داد شرق منطقه بیشترین احتمال حضور آویشن را دارد و از شرق به سمت جنوب غرب کاهش مییابد. در بیشتر مناطق احتمال حضور کمتر از 25/0 است و در بخشهای کوچکی احتمال حضور نزدیک به یک است. نتیجهگیری با توجه به نتایج بهدستآمده از مدلهای رگرسیونی که نشاندهنده تأثیر معنادار عوامل محیطی مانند ارتفاع، شیب، جهت جغرافیایی و بارش بر پراکنش گونه آویشن T. kotschyanus در مراتع منطقه است، میتوان از این مدلها بهعنوان ابزار مؤثری برای شناسایی رویشگاه و ترسیم حدود جغرافیایی پراکنش اینگونه استفاده کرد. بهویژه با توجه به افزایش حضور آویشن در شرق منطقه و کاهش محسوس آن در جنوب غرب، نتایج این پژوهش میتواند مبنای علمی مناسبی برای تدوین برنامههای مدیریتی چرا و توسعه کشت آویشن متناسب باقابلیتهای طبیعی هر ناحیه فراهم آورد و به حفاظت و بهرهبرداری پایدار ازاینگونه ارزشمند کمک نماید. | ||
| کلیدواژهها | ||
| بومشناسی؛ بومسازگانهای پایدار؛ مدلسازی رویشگاه؛ مدلهای رگرسیونی؛ مدیریت مرتع | ||
| عنوان مقاله [English] | ||
| Habitat Prediction of Thymus kotschyanus Based on Environmental Factors Using Logistic Regression and Interpolation (Case Study: Dolanieh Habitat in Piranshahr County) | ||
| نویسندگان [English] | ||
| Somayyeh Souri1؛ Shahryar Dashti2؛ Yousef Ajani3؛ Esmaeil Karimi4؛ Elham Noori5 | ||
| 1Ph.D Student, Department of Plant production and Genetics. Faculty of Agriculture, University of Maragheh, East Azarbaijan, Iran | ||
| 2Assistant Professor, Department of Plant Production Engineering and Genetics, Faculty of Agriculture, University of Maragheh | ||
| 33- Assistant Prof., Botany Division, Research Institute of Forests and Rangelands, Agricultural Research Education and Extension Organization (AREEO), Tehran, Iran | ||
| 4Assistant Professor, Department of Plant Production and Genetics, Faculty of Agriculture, University of Maragheh, East Azarbaijan | ||
| 5Researcher, Forests, Research Division, Research Institute of Forests and Rangelands, Agricultural Research Education and Extension Organization (AREEO), Tehran, Iran | ||
| چکیده [English] | ||
| Abstract Background and Objectives Environmental factors can significantly influence the distribution of plant species. Predicting suitable habitats for species requires a thorough understanding of these influences. Thymus is one of the most important genera in the Lamiaceae family, comprising over 215 species widely distributed across the world, particularly in the Mediterranean region. The present study aims to predict the habitat suitability of Thymus kotschyanus using logistic regression modeling and spatial interpolation methods in the Dolaniyeh region of Piranshahr County. Materials and Methods Topographic variables including elevation, slope, and aspect were derived from the region’s Digital Elevation Model (DEM), while climatic parameters such as average temperature and precipitation were obtained from the Dolanaya synoptic station. A total of 94 presence and absence points of Thymus kotschyanus were systematically and randomly sampled. Binary logistic regression was used in SPSS software to evaluate the relationship between species presence and environmental factors. Spatial variation in habitat suitability was assessed using deterministic and geostatistical interpolation techniques. Results The results indicated that the probability of T. kotschyanus presence had a negative relationship with variables such as latitude, slope aspect, leaf width, soil organic carbon, calcium carbonate, copper, and mean monthly and annual precipitation, as well as sand and clay content. In contrast, variables such as slope, leaf length, plant height, electrical conductivity, pH, zinc, iron, and average temperature showed a positive relationship with the probability of species presence. The likelihood of Thymus presence increases in arid and semi-arid areas with suitable slopes. Spatial distribution mapping revealed that the eastern part of the study area had the highest probability of presence, which gradually decreased toward the southwest. In most parts of the region, the probability of presence was below 0.25, while in a few localized areas, it approached 1.00. Conclusion Based on the results of the regression models, which showed significant effects of environmental variables such as elevation, slope, aspect, and precipitation on the distribution of T. kotschyanus in the study area, these models can serve as effective tools for identifying potential habitats and mapping the species’ geographic range. Considering the increased presence in the eastern region and a notable decline in the southwest, the findings of this study provide a scientific foundation for grazing management strategies and cultivation planning of T. kotschyanus tailored to the ecological capacity of different zones, contributing to the sustainable utilization and conservation of this valuable medicinal species. Abstract Background and Objectives Environmental factors can significantly influence the distribution of plant species. Predicting suitable habitats for species requires a thorough understanding of these influences. Thymus is one of the most important genera in the Lamiaceae family, comprising over 215 species widely distributed across the world, particularly in the Mediterranean region. The present study aims to predict the habitat suitability of Thymus kotschyanus using logistic regression modeling and spatial interpolation methods in the Dolaniyeh region of Piranshahr County. Materials and Methods Topographic variables including elevation, slope, and aspect were derived from the region’s Digital Elevation Model (DEM), while climatic parameters such as average temperature and precipitation were obtained from the Dolanaya synoptic station. A total of 94 presence and absence points of Thymus kotschyanus were systematically and randomly sampled. Binary logistic regression was used in SPSS software to evaluate the relationship between species presence and environmental factors. Spatial variation in habitat suitability was assessed using deterministic and geostatistical interpolation techniques. Results The results indicated that the probability of T. kotschyanus presence had a negative relationship with variables such as latitude, slope aspect, leaf width, soil organic carbon, calcium carbonate, copper, and mean monthly and annual precipitation, as well as sand and clay content. In contrast, variables such as slope, leaf length, plant height, electrical conductivity, pH, zinc, iron, and average temperature showed a positive relationship with the probability of species presence. The likelihood of Thymus presence increases in arid and semi-arid areas with suitable slopes. Spatial distribution mapping revealed that the eastern part of the study area had the highest probability of presence, which gradually decreased toward the southwest. In most parts of the region, the probability of presence was below 0.25, while in a few localized areas, it approached 1.00. Conclusion Based on the results of the regression models, which showed significant effects of environmental variables such as elevation, slope, aspect, and precipitation on the distribution of T. kotschyanus in the study area, these models can serve as effective tools for identifying potential habitats and mapping the species’ geographic range. Considering the increased presence in the eastern region and a notable decline in the southwest, the findings of this study provide a scientific foundation for grazing management strategies and cultivation planning of T. kotschyanus tailored to the ecological capacity of different zones, contributing to the sustainable utilization and conservation of this valuable medicinal species. | ||
| کلیدواژهها [English] | ||
| Ecology, Habitat Modeling, Rangeland Management, Regression Models, Sustainable Ecosystems | ||
| مراجع | ||
|
Awasthi, N., Bhandari, S. K., and Khanal, Y. 2015. Does scientific forest management promote plant species diversity and regeneration in Sal (Shorea robusta) forest? A case study from Lumbini collaborative forest, Rupandehi, Nepal. Banko Janakari, 25(1), 20-29. doi.org/10.3126/banko.v25i1.13468
Azimi Motem, F., Talai, R., Asiaizadeh, F., and Hoshiar, M. 2011. Introduction of flora, biological forms and geographical distribution of plant species in the forested and protected area of Fandakhlu (Ardebil province). Taxonomy and biosystematics. 3(9), 75-90 [In Persian].
Bedunah, D. J., and Angerer, J. P. 2012. Rangeland degradation, poverty, and conflict: how can rangeland scientists contribute to effective responses and solutions? Rangeland Ecology and Management, 65(6), 606–612. DOI: 10.2307/41403054
Carter, M. R., Parton, W. J., Rowland, I. C., Schultz, J. E., and Steed, G. R. 1993. Simulation of soil organic carbon and nitrogen changes in cereal and pasture systems of southern Australia. Soil Research, 31(4), 481-491. doi.org/10.1071/sr9930481
Cimalova, S., and Z. Lososova., 2009. Arable weed vegetation of the northeastern part of the Czech Republic: effects of environmental factors on species composition. Plant Ecology, 203: 45–57. doi.org/10.1007/s11258-008-9503-1
Dieleman, C.M., Branfireun, B.A., McLaughlin, J.W. and Lindo, Z. 2015. Climate change drives a shift in peatland ecosystem plant community: implications for ecosystem function and stability. Global change biology, 21(1), 388-395. doi.org/10.1111/gcb.12643
Dormann, C. F., Elith, J., Bacher, S., Buchmann, C., Carl, G., Carré, G., ... and Lautenbach, S. 2013. Collinearity: a review of methods to deal with it and a simulation study evaluating their performance. Ecography, 36(1), 27–46. doi.org/10.1111/j.1600-0587.2012.07348.x
Eldridge, D. J., Delgado‐Baquerizo, M., Travers, S. K., Val, J., and Oliver, I. 2017. Do grazing intensity and herbivore type affect soil health? Insights from a semi‐arid productivity gradient. Journal of Applied Ecology, 54(3), 976-985. doi.org/10.1111/1365-2664.12834
El-Khalafy, M. M., El-Kenany, E. T., Al-Mokadem, A. Z., Shaltout, S. K., and Mahmoud, A. R. 2025. Habitat suitability modeling to improve conservation strategy of two highly-grazed endemic plant species in Saint Catherine Protectorate, Egypt. BMC Plant Biology, 25(1), 485. doi.org/10.1186/s12870-025-06401-4
Evangelista, P. H., Norman, J., Berhanu, L., Kumar, S., and Alley, N. 2008. Predicting habitat suitability for the endemic mountain nyala (Tragelaphus buxtoni) in Ethiopia. Wildlife Research, 35(5): 409-416. doi.org/10.1071/wr07173
Guisan, A., and Zimmermann, N. E. 2000. Predictive habitat distribution models in ecology. Ecological Modelling, 135(2–3), 147–186. doi.org/10.1016/s0304-3800(00)00354-9
Hamilton, A. C. 2004. Medicinal plants, conservation and livelihoods. Biodiversity and Conservation, 13(8), 1477–1517. doi.org/10.1023/b:bioc.0000021333.23413.42
Hosseini, N., Ghorbanpour, M., and Mostafavi, H. 2024. Habitat potential modelling and the effect of climate change on the current and future distribution of three Thymus species in Iran using MaxEnt. Scientific Reports, 14(1), 3641. doi.org/10.1038/s41598-024-53405-5
Humaida, N., Wahab, L., Saputra, M. H., Kurniawati, F., Atmaja, M. B., Pujiono, E., ... and Wahyuningtyas, R. S. 2025. Species distribution model and conservation of Mentaok (Wrightia javanica) in Indonesia. Jurnal Manajemen Hutan Tropika, 31(1), 1–11. doi.org/10.7226/jtfm.31.1.1
Ilunga Nguy, K. and D. Shebitz., 2019. Characterizing the spatial distribution of Eragrostis Curvula (Weeping Lovegrass) in New Jersey (United States of America) using logistic regression. Environments, 6(125): 1-14. doi.org/10.3390/environments6120125
Jamali, A. A., Hossein Jafari, S., and Zarekia, S. 2024. Habitat preference of bitter and sweet asafoetida plants, topographic, soil and climatic factors using remote sensing and statistics analysis. Journal of Earth System Science, 133(1), 1. doi.org/10.1007/s12040-023-02252-5
Jamzad, Z. 2008. Iranian thymes and spices. Publications of the Country Forests and Pastures Research Institute, Tehran, Iran. [In Persian]
Kaufmann, S., Hauck, M., Leuschner, C. 2017. Comparing the plant diversity of paired beech primeval and production forests: Management reduces cryptogam, but not vascular plant species richness. Forest Ecology and Management, 400, 58-67. doi.org/10.1016/j.foreco.2017.05.043
Kent, M. 2011. Vegetation description and data analysis: a practical approach. John Wiley and Sons. doi.org/10.2307/3451427
Lam, N. S. N. 1983. Spatial interpolation methods: a review. The American Cartographer, 10(2), 129–150. doi.org/10.1559/152304083783914958
Li, Y., Kong, D., Fu, Y., Sussman, M. R., and Wu, H. 2020. The effect of developmental and environmental factors on secondary metabolites in medicinal plants. Plant Physiology and Biochemistry, 148, 80-89. doi.org/10.1016/j.plaphy.2020.01.006
Lu, X., Kelsey, K. C., Yan, Y., Sun, J., Wang, X., Cheng, G., and Neff, J. C. 2017. Effects of grazing on ecosystem structure and function of alpine grasslands in Qinghai–Tibetan Plateau: a synthesis. Ecosphere, 8(1), e01656. doi.org/10.1002/ecs2.1656
Mesdaghi, M. 2005. Plant ecology. Ferdowsi University of Mashhad Press. 187. p. [In Persian]
McBride, P.D., Cusens, J., and Gillman, L.N. 2014. Revisiting spatial scale in the productivity – specie s richness relationship: fund amental issues and global change implications. AoB PLANTS, 1-12. doi.org/10.1093/aobpla/plu057
Mehrad, S. 2018. Rural Economic Development and Employment Generation Program of the Province's Counties. Publications of the West Azerbaijan Management and Planning Organization. 337. p. [In Persian]
Miller, J., 2005. Incorporating spatial dependence in predictive vegetation models: residual interpolation methods. The Professional Geographer, 57(2), 169-184. doi.org/10.1111/j.0033-0124.2005.00470.x
Motamedi, J., Shidai Kirkej, A., Ghasemi, F., Souri, M. 2017. Ecological, habitat and morphological characteristics of Ephedra procera C.A.Mey. in the mountainous pastures of Urmia; Plant Biology of Iran. 1(3). 1-20 [In Persian].
Nabipour, Y., and Vatakhah, M. 2016. Comparison of Different Geostatistical Methods for Estimating Rainfall in Hajighoshan Watershed. Journal of Range and Watershed Managment, 69(2), 487-502. doi: 10.22059/jrwm.2016.61698. [In Persian]
Nateghi, S., Khodagholi, M., and Souri, M. 2024. Assessment of the effects of climate change on the habitat of important pasture species in Alborz province based on the climate prediction model. Iranian Journal of Range and Desert Research, 31(3), 271-285.
Nickavar, B., Mojab, F. and Dolat-Abadi, R. 2005. Analysis of the essential oils of two Thymus species from Iran. Food Chem, 90, 609–611. doi.org/10.1016/j.foodchem.2004.04.020
Olff, H. and M.E. Ritchie. 1998. Effects of herbivores on grassland plant diversity. Trends Ecol Evol, 13: 261–265. doi.org/10.1016/s0169-5347(98)01364-0
Perez-Harguindeguy, N., Díaz, S., and Garnier, E. Lavor el S, Poorter H, Jaureguiberry P, Bret-Harte MS, Cornwell WK, Craine JM, Gurvich DE, Urcelay C, Veneklaas EJ, Reich PB, Poorter L, Wright IJ, Ray P, Enrico L, Pausas JG, Vos AC de, Buchmann N, Funes G, Quétier F, Hodgson JG, Thompson K, Morgan HD, Steege H ter, Heijden A van der, Sack L, Blonder B, Poschlod P, Vaieretti MV, Conti G, Staver AC, Aquino S, Cornelissen JHC. 2013. New handbook for standardised measurement of plant functional traits worldwide. Australian Journal of Botany, 61, 167-234. doi.org/10.1071/bt12225
Piri Sahragard, H., Zare Chahoki, M. A., Azarnivand, H. (2013). Modeling the distribution of plant species in pastures west of Hoz Sultan in Qom province using logistic regression method, Martadari Journal. Gorgan University of Agricultural Sciences and Natural Resources, 1(1): 113-94. [In Persian]
Qaderi, M. M., Martel, A. B., and Strugnell, C. A. 2023. Environmental factors regulate plant secondary metabolites. Plants, 12(3), 447. doi.org/10.3390/plants12030447
Raziei, T. 2022. Climate of Iran according to Köppen-Geiger, Feddema, and UNEP climate classifications. Theoretical and Applied Climatology, 148(3), 1395–1416. doi.org/10.1007/s00704-022-03992-y
Shah, I. H., Manzoor, M. A., Jinhui, W., Li, X., Hameed, M. K., Rehaman, A., ... and Chang, L. 2024. Comprehensive review: Effects of climate change and greenhouse gases emission relevance to environmental stress on horticultural crops and management. Journal of Environmental Management, 351, 119978. doi.org/10.1016/j.jenvman.2023.119978
Sher, H., Aldosari, A., Ali, A., and de Boer, H. J. 2014. Economic benefits of high value medicinal plants to Pakistani communities: an analysis of current practice and potential. Journal of Ethnobiology and Ethnomedicine, 10(1), 1–16. doi.org/10.1186/1746-4269-10-71
Sims, J. T. 1995. Characteristics of animal wastes and waste-amended soils: an overview of the agricultural and environmental issues.
Tsiafouli, M. A., Thébault, E., Sgardelis, S. P., De Ruiter, P. C., Van Der Putten, W. H., Birkhofer, K., ... and Hedlund, K. 2015. Intensive agriculture reduces soil biodiversity across Europe. Global Change Biology, 21(2), 973–985. doi.org/10.1111/gcb.12752
Walkley, A., Black, C.A., 1974. Critical examination of rapid method of determining organic carbon in soil. Soil Sci. 63, 251–264. doi.org/10.1097/00010694-194704000-00001
Wang, G., Wang, C., Guo, Z., Dai, L., Wu, Y., Liu, H., Li, Y., Chen, H., Zhang, Y., Zhao, Y. and Cheng, H., 2020. Integrating Maxent model and landscape ecology theory for studying spatiotemporal dynamics of habitat: Suggestions for conservation of endangered Red-crowned crane. Ecological Indicators, 116, 106472. doi.org/10.1016/j.ecolind.2020.106472
Yari, R., Heshmati, G., Rafiee, H. 2019. Potential of available species in Chhar-Bagh summer rangelands, For medicinal, industrial and edibility use, Golestan Province, Iran. 3(13):350-367 [In Persian].
Yates, C. J., Norton, D. A., and Hobbs, R. J. 2000. Grazing effects on plant cover, soil and microclimate in fragmented woodlands in south‐western Australia: implications for restoration. Austral Ecology, 25(1), 36-47. doi.org/10.1046/j.1442-9993.2000.01030.x
Ye, J., Ji, Y., Wang, J., Ma, X., and Gao, J. 2024. Climate factors dominate the elevational variation in grassland plant resource utilization strategies. Frontiers in Plant Science, 15, 1430027. doi.org/10.3389/fpls.2024.1430027
Yilmaz, H., O.Y. Yilmaz and Y.F. Akyuz, 2017. Determining the factors affecting the distribution of Muscari latifolium, an endemic plant of Turkey, and a mapping species distribution model. Ecology and Evolution, 7(4): 1112–1124. doi.org/10.1002/ece3.2766
Zare Chahouki, M. A., A. Abbaasi and H. Azarnivand, 2014. Spatial distribution modeling of Agropyron intermedium and Stipa barbata habitats logistic regression (case study: Middle Taleghan Rangelands). Journal of Plant Ecosystem Conservation, 2(4): 47-60. [In Persian]
Zare Chahouki, M. A., Abbasi, M., and Azarnivand, H. 2014. Habitat suitability modeling for Thymus kotschyanus using logistic regression and GIS in Qom Province, Iran. Iranian Journal of Medicinal and Aromatic Plants, 30(4), 540–552. doi.org/10.47176/ijae.14.2.15501
Zare Chahouki, M.A. and L. Khalasi Ahvazi., 2012. Predicting potential distributions of Zygophyllum eurypterum by three modeling techniques (ENFA, ANN and logistic) in North East of Semnan, Iran. Range Management and Agroforestry, 33(2): 123-128. [In Persian]
Zare M, Ghorbani A, Moameri M, Piri Sahragard H, Mostafazade R, Hosseini Z, Dadjou F., 2023. Effect of Environmental Factors on Habitat Prediction of Species Dorema ammoniacum D. DON. in Nadoushan Rangelands, Yazd Province. Range, 17(1): 81-66. doi.org/10.1038/s41598-024-61073-8
Zhan, T., Zhang, Z., Sun, J., Liu, M., Zhang, X., Peng, F., Tsunekawa, A., Zhou, H., Gou, X., and Fu, S. 2020. Meta-analysis demonstrating that moderate grazing can improve the soil quality across China's grassland ecosystems. Applied Soil Ecology, 147. doi.org/10.1016/j.apsoil.2019.103438
Zhang, Q., Buyantuev, A., Li, F. Y., Jiang, L., Niu, J., Ding, Y., ... & Ma, W. 2017. Functional dominance rather than taxonomic diversity and functional diversity mainly affects community aboveground biomass in the Inner Mongolia grassland. Ecology and evolution, 7(5), 1605-1615. doi.org/10.1002/ece3.2778 | ||
|
آمار تعداد مشاهده مقاله: 93 |
||