| تعداد نشریات | 282 |
| تعداد نشریات سازمان | 80 |
| تعداد شمارهها | 3,208 |
| تعداد مقالات | 35,560 |
| تعداد مشاهده مقاله | 53,002,291 |
| تعداد دریافت فایل اصل مقاله | 92,287,802 |
کاربرد سیستم های تخصص محور در طبقه بندی پوشش گیاهی | ||
| تحقیقات جنگل و صنوبر ایران | ||
| مقاله 3، دوره 29، شماره 3 - شماره پیاپی 85، مهر 1400، صفحه 214-229 اصل مقاله (380.78 K) | ||
| نوع مقاله: علمی- پژوهشی | ||
| شناسه دیجیتال (DOI): 10.22092/ijfpr.2021.354945.2004 | ||
| نویسندگان | ||
| پری کرمی کردعلیوند1؛ امید اسماعیل زاده* 2 | ||
| 1دانشجوی دکتری جنگلداری، گروه علوم و مهندسی جنگل، دانشکده منابع طبیعی و علوم دریایی، دانشگاه تربیتمدرس، نور، ایران | ||
| 2نویسنده مسئول، استادیار، گروه علوم و مهندسی جنگل، دانشکده منابع طبیعی و علوم دریایی، دانشگاه تربیتمدرس، نور، ایران | ||
| چکیده | ||
| در پژوهش پیشرو کارایی دو سیستم تخصصمحور طبقهبندی پوشش گیاهی در بازیابی جوامع گیاهی سرخدار (Taxus baccata L.) در جنگلهای هیرکانی مرکزی و شرقی ارزیابی شد. برای این منظور، ابتدا جوامع گیاهی با استفاده از تحلیل گونههای معرف دوطرفه (TWINSPAN) و براساس اطلاعات ترکیب پوشش گیاهی 408 رلوه 400 متر مربعی طبقهبندی شدند. سپس، گونههای معرف هریک از جوامع گیاهی مذکور با بهرهگیری از نتایج تلفیقی سه شاخص تعلقهفی، نسبت پایایی و نسبت تاجپوشش کل تعیین شدند. جوامع گیاهی اولیه پس از سنتر بهروش جدولی براون- بلانکه در قالب پنج جامعه گیاهی سرخدار معرفی شدند. همچنین، با استفاده از دو رویکرد مختلف شامل گروهگونه عملکردی (در روش تخصصمحور تلفیقی) و گروهگونه جامعهشناختی (در روش تخصصمحور ترکیب گونههای معرف)، رلوهها به هریک از پنج جامعه مذکور تخصیص یافتند. براساس نتایج بهدستآمده، همه رلوهها در روش تخصصمحور تلفیقی به گروههای هدف اختصاص یافته بودند و انطباق صددرصد را با جوامع گیاهی پنجگانه سرخدار نشان دادند، درحالیکه در روش ترکیب گونههای معرف، 87 رلوه به هیچکدام از این جوامع تعلق نداشتند یا به بیشتر از یک جامعه اختصاص یافتند. مقدار انطباق نتایج این روش با جوامع گیاهی ازپیشطبقهبندیشده سرخدار، 7/78 درصد ارزیابی شد. بهطورکلی، نتایج پژوهش پیشرو تصریح میکند که باتوجهبه اهمیت ثبات و انعطافپذیری سیستمهای طبقهبندی پوشش گیاهی و اختصاص صحیح یک رلوه به جامعه هدف، استفاده از روش تخصصمحور تلفیقی نسبت به روش ترکیب گونههای معرف در طبقهبندی خودکار جوامع گیاهی ارجحیت دارد. | ||
| کلیدواژهها | ||
| طبقهبندی خودکار؛ گروه گونه عملکردی؛ گروه گونه جامعهشناختی؛ گونه معرف؛ تخصیص | ||
| عنوان مقاله [English] | ||
| Application of expert systems in vegetation classification | ||
| نویسندگان [English] | ||
| P. Karami‑Kordalivand1؛ O. Esmailzadeh2 | ||
| 1PhD. Student of Forestry, Department of Forest Science and Engineering, Faculty of Natural Resources and Marine Sciences, Tarbiat Modares University, Noor, Iran | ||
| 2Corresponding author, Assistant Prof., Department of Forest Science and Engineering, Faculty of Natural Resources and Marine Sciences, Tarbiat Modares University, Noor, Iran | ||
| چکیده [English] | ||
| The aim of this study was to evaluate the efficiency of two expert systems in automatic classification of pre-defined yew (Taxus baccata L.) communities in the central and eastern of the Hyrcanian forests. Therefore, initial plant communities were recognized using Two-Way Indicator Species Analysis (TWINSPAN) based on floristic data of 408 relevés with 400 m2 areas each. To determine representative species, the integrative results of Phi-coefficient index, constancy ratio, and the ratio of average cover were used. Five plant communities were introduced after transferring the initial communities to the Braun-Blanquet synthesis table. The assignment of relevés into the fifth yew associations were done by functional and sociological species groups as two different automatic algorithms of expert system for vegetation classification. The results showed that all relevés in the expert system based on functional species groups were correctly assigned to the target groups. This method was in 100% agreement with the existing yew syntaxa. However, 87 relevés were not assigned to any of the five pre-defined yew associations, or they were assigned to more than one unit in the Cocktail method, which showed 78.7% agreement with the previously yew syntaxa. Finally, our results illustrate that application of expert system based on functional species groups is preferred to sociological species groups in automatically plant community classification due to the importance of consistency and flexibility of vegetation classifications and the correct assignment of relevés to the target units. | ||
| کلیدواژهها [English] | ||
| Assignment, automatic classification, functional species group, indicator species, sociological species group | ||
| مراجع | ||
|
- Asadi, H., Esmailzadeh, O., De Cáceres, M. and Hosseini, S.M., 2021. The assignment of relevés to pre-existing vegetation units: a comparison of approaches using species fidelity. Annals of Forest Science, 78(1): 13. - Asadi, H., Esmailzadeh, O., Hosseini, S.M., Asri, Y. and Zare, H., 2016. Application of Cocktail method in vegetation classification. Taxonomy and Biosystematics, 28(8): 21-38 (In Persian). - Boublík, K., 2010. Formalized classification of the vegetation of Abies alba-dominated forests in the Czech Republic. Biologia, 65(5): 822-831. - Bruelheide, H. and Chytrý, M., 2000. Towards unification of national vegetation classifications: A comparison of two methods for analysis of large data sets. Journal of Vegetation Science, 11(2): 295-306. - Bruelheide, H., 1997. Using formal logic to classify vegetation. Folia Geobotanica, 32(1): 41-46. - Bruelheide, H., 2016. Cocktail clustering–a new hierarchical agglomerative algorithm for extracting species groups in vegetation databases. Journal of Vegetation Science, 27(6): 1297-1307. - Černá, L. and Chytrý, M., 2005. Supervised classification of plant communities with artificial neural networks. Journal of Vegetation Science, 16(4): 407-414. - Chytrý, M. and Tichý, L., 2018. National vegetation classification of the Czech Republic: a summary of the approach. Phytocoenologia, 48(2): 121-131. - Chytrý, M., 2007. Vegetation of the Czech Republic: 1. Grassland and Heathland Vegetation. Academia, Prague, Czech, 528p (In Czech). - Chytrý, M., Tichý, L., Holt, J. and Botta‐Dukát, Z., 2002. Determination of diagnostic species with statistical fidelity measures. Journal of Vegetation science, 13(1): 79-90. - Çoban, S. and Willner, W., 2019. Numerical classification of the forest vegetation in the Western Euxine Region of Turkey. Phytocoenologia, 49(1): 71-106. - De Cáceres, M., Font, X., Vicente, P. and Oliva, F., 2009. Numerical reproduction of traditional classifications and automatic vegetation identification. Journal of Vegetation Science, 20(4): 620-628. - Douda, J., 2008. Formalized classification of the vegetation of alder carr and floodplain forests in the Czech Republic. Preslia, 80(2): 199-224. - Esmailzadeh, O., Darvand, R. and Asadi, H., 2018. Assessing of similarity indices for the assignment of the plots to the plant communities of an existing phytosociological classification. Journal of Plant Research, 30(4): 732-744 (In Persian). - Esmailzadeh, O., Hosseini, S.M., Asadi, H., Ghadiripour, P. and Ahmadi, A., 2012. Plant biodiversity in relation to physiographical factors in Afratakhteh Yew (Taxus baccata L.) Habitat, NE Iran. Journal of Plant Biology, 4(12): 1-12 (In Persian). - Fischer, H.S, 2015. On the combination of species cover values from different vegetation layers. Applied Vegetation Science, 18(1): 169-170. - Gholizadeh, H., Naqinezhad, A. and Chytrý, M., 2020. Classification of the Hyrcanian forest vegetation, northern Iran. Applied Vegetation Science, 23(1): 107-126. - Hastie, T., Tibshirani, R. and Friedman, J., 2009. The Elements of Statistical Learning: Data Mining, Inference, and Prediction, Second Edition. Springer, New York, NY, 745p. - Haveman, R. and Janssen, J.A.M., 2008. The analysis of long-term changes in plant communities using large databases: The effect of stratified resampling. Journal of Vegetation Science, 19(3): 355-362. - Hennekens, S.M. and Schaminée, J.H.J., 2001. TURBOVEG, a comprehensive data base management system for vegetation data. Journal of Vegetation Science, 12(4): 589-591. - Hill, M.O., 1979. TWINSPAN—a FORTRAN program for arranging multivariate data in an ordered two-way table by classification of the individuals and attributes. Cornell University, Ithaca, NY, 90p. - Hosseinzadeh, S. and Esmailzadeh, O., 2017. Floristic study of Buxus hyrcana stands in the Western forests of Haraz district, Amol. Iranian Journal of Applied Ecology, 6(1): 1-13 (In Persian). - Karami‑Kordalivand, P., Esmailzadeh, O., Willner, W., Noroozi, J., and Alavi, S.J., 2021. Classification of forest communities (co‑)dominated by Taxus baccata in the Hyrcanian forests (northern Iran) and their comparison with southern Europe. European Journal of Forest Research, 140(2): 463-476. - Kočí, M., Chytrý, M. and Tichý, L., 2003. Formalized reproduction of an expert-based phytosociological classification: A case study of subalpine tall-forb vegetation. Journal of Vegetation Science, 14(4): 601-610. - Kuželová, I. and Chytrý, M., 2004. Interspecific associations in phytosociological data sets: how do they change between local and regional scale? Plant Ecology, 173(2): 247-257. - Landucci, F., Tichý, L., Šumberová, K. and Chytrý, M., 2015. Formalized classification of species-poor vegetation: A proposal of a consistent protocol for aquatic vegetation. Journal of Vegetation Science, 26(4): 791-803. - Liao, S.H., 2005. Expert system methodologies and applications—a decade review from 1995 to 2004. Expert Systems with Applications, 28(1): 93-103. - McLeod, R., Jr., 1998. Management Information System, 7th Edition. Prentice Hall, Upper Saddle River, NJ, 655p. - Noble, I.R., 1987. The role of expert systems in vegetation science. Vegetatio, 69(1): 115-121. - Novák, P., Willner, W., Zukal, D., Kollár, J., Roleček, J., Świerkosz, K., ... and Chytrý, M., 2020. Oak-hornbeam forests of central Europe: a formalized classification and syntaxonomic revision. Preslia, 92(1): 1-34. - Rechinger, K.H. (Ed.), 1963-2015. Flora Iranica, Vols. 1-181. Akademische Druck und Verlagsanstalt, Verlag des Naturhistorischen Museum Wien, Graz and Wien, Austria. - Saberi, B.G., Esmailzadeh, O. and Asadi, H., 2021. Evaluating the different indicator species analysis in the classification of plant communities. Iranian Jornal of Forest, 12(4): 541-555 (In Persian). - Tichý, L. and Chytrý, M., 2006. Statistical determination of diagnostic species for site groups of unequal size. Journal of Vegetation Science, 17(6): 809-818. - Tichý, L., 2002. JUICE, software for vegetation classification. Journal of Vegetation Science, 13(3): 451-453. - Tichý, L., Chytrý, M. and Landucci, F., 2019. GRIMP: A machine-learning method for improving groups of discriminating species in expert systems for vegetation classification. Journal of Vegetation Science, 30(1): 5-17. - Turban, E., Aronson, J.E. and Liang, T.P., 2004. Decision Support Systems and Intelligent Systems, 7th Edition. Prentice Hall, Upper Saddle River, NJ, 936p. - van Tongeren, O., Gremmen, N. and Hennekens, S., 2008. Assignment of relevés to pre-defined classes by supervised clustering of plant communities using a new composite index. Journal of Vegetation Science, 19(4): 525-536. - Willner, W., 2011. Unambiguous assignment of relevés to vegetation units: The example of the Festuco-Brometea and Trifolio-Geranietea sanguinei. Tuexenia, 31: 271-282. - Willner, W., Jiménez-Alfaro, B., Agrillo, E., Biurrun, I., Campos, J.A., Čarni, A., ... and Chytrý, M., 2017. Classification of European beech forests: a Gordian Knot? Applied Vegetation Science, 20(3): 494-512. - Willner, W., Tichý, L. and Chytrý, M., 2009. Effects of different fidelity measures and contexts on the determination of diagnostic species. Journal of Vegetation Science, 20(1): 130-137. | ||
|
آمار تعداد مشاهده مقاله: 961 تعداد دریافت فایل اصل مقاله: 584 |
||