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مدلسازی پراکنش راش در جنگلهای کرانرودی با استفاده از مدل HOF | ||
| تحقیقات جنگل و صنوبر ایران | ||
| مقاله 13، دوره 23، شماره 4، دی 1394، صفحه 707-718 اصل مقاله (333.58 K) | ||
| نوع مقاله: علمی- پژوهشی | ||
| شناسه دیجیتال (DOI): 10.22092/ijfpr.2015.106591 | ||
| نویسندگان | ||
| محمدنقی عادل* 1؛ حسن پوربابایی2؛ سیدجلیل علوی3؛ علی صالحی4 | ||
| 1دانشجوی دکتری علوم جنگل (اکولوژی)، دانشکده منابع طبیعی، دانشگاه گیلان | ||
| 2استاد، گروه جنگلداری، دانشکده منابع طبیعی، دانشگاه گیلان | ||
| 3استادیار، گروه جنگلداری، دانشکده منابع طبیعی و علوم دریایی، دانشگاه تربیت مدرس | ||
| 4دانشیار، گروه جنگلداری، دانشکده منابع طبیعی، دانشگاه گیلان | ||
| چکیده | ||
| هدف پژوهش پیشرو مدل سازی پراکنش راش و تعیین مقدار بهینه و دامنه بردباری آن در جنگلهای کرانرودی حاشیه رودخانه صفارود رامسر بود. بدین منظور، از خطنمونه های عمود بر جریان آب در هر دو طرف رودخانه برای جمع آوری داده ها استفاده شد. طول هر خطنمونه 200 متر و فاصله بین خطنمونه ها نیز 200 متر انتخاب شد. در هر خطنمونه از پنج کوادرات 400 مترمربعی با فواصل 50 متری در پنج نقطه صفر، 50، 100، 150 و 200 متر استفاده شد و در آنها تعداد درختان راش با قطر برابر سینه بیشتر از 7/5 سانتیمتر اندازه گیری شد. در هر قطعهنمونه از سه نقطه از عمق صفر تا 30 سانتیمتر نمونه خاک برداشت شد و برای تعیین خصوصیات آن به آزمایشگاه منتقل شد. درمجموع، از 44 خطنمونه و 220 کوادرات برای جمع آوری داده ها استفاده شد. برای بررسی پاسخ راش به عوامل خاکی از مدل HOF توسعهیافته و تعیین بهترین مدل از معیار اطلاعات آکائیک تصحیح شده (AICc) استفاده شد. در هر یک از پنج فاصله، مدلی که کمترین مقدار AICc را در میان مدل های هفتگانه داشت، بهعنوان بهترین مدل انتخاب شد. محاسبات با استفاده از بسته eHOF در نرم افزار R ver. 3.1.3 انجام شد. نتایج نشان داد که تنها 27/5 درصد از مدل های به دستآمده دارای توزیع نرمال بودند، درحالیکه 72/5 درصد از مدل های به دستآمده از مدل های خطی یا نامتقارن تبعیت می کردند. مدل های VI و VII در هیچ یک از پاسخ ها مشاهده نشد. پیشنهاد میشود در آینده مطالعات بیشتری درمورد جنگلهای کرانرودی و همچنین استفاده از مدل HOF انجام شود. | ||
| کلیدواژهها | ||
| دامنه بردباری؛ صفارود رامسر؛ مدل توسعهیافته eHOF؛ مدلسازی؛ مقدار بهینه | ||
| عنوان مقاله [English] | ||
| Modeling distribution of oriental beech (Fagus orientalis Lipsky) trees in riparian forest by HOF model | ||
| نویسندگان [English] | ||
| Mohammad Naghi Adel1؛ Hasan Pourbabaei2؛ Seyyed Jalil Alavi3؛ Ali Salehi4 | ||
| 1Ph.D. Student of Forest Sciences (Ecology), Faculty of Natural Resources, University of Guilan | ||
| 2Prof., of Forestry, Natural Resources Faculty, University of Guilan | ||
| 3Assistant Prof., Natural Resources and Marine Sciences Faculty, Tarbiat Modares University | ||
| 4Associate Prof., of Forestry, Natural Resources Faculty, University of Guilan | ||
| چکیده [English] | ||
| We modeled the distribution of oriental beech (FagusorientalisLipsky) stands to determine optimum ecological amplitude range along riparian forests of RamsarSafaroud riverside in Mazandaran province. Data were collected on transects which were perpendicular to the water flow on both river sides. Each transect was 200 m in length, with a 200 m distance between transects. On each transect five 400 m2 quadrats were laid in 50 m intervals. At each sampling location the number of beech individuals with a diameter at breast height (DBH) > 7.5 cm were recorded. In addition three soil samples per plot were taken from the upper 30 cm depth. Totally 44 transects and 220 quadrats were sampled. An extended HOF model implemented in eHOF package in R was applied to assess the response of beech to soil variables, and the corrected Akaike's information criterion (AICc) was used for model selection based on models associated with the lowest AICc values. The results showed that only 27.5% of the models obtained a symmetric normal response curve (model IV), whereas 72.5% of models showed linear and asymmetric (i.e. I to V) curves. However, the VI and VII models were observed in none of the results. We assessed the HOF models to be of high potentials to be further employed in similarly-structured riparian forests. | ||
| کلیدواژهها [English] | ||
| Safaroud forest of Ramsar, amplitude, modeling, extended eHOF model, optimum value | ||
| مراجع | ||
|
- Alavi, S.J., Zahedi Amiri, G., Rahmani, R., Marvie Mohajer, M.R., Muys, B. and Fathi, J., 2012. Extracting ecological optimum and amplitude of Fagus orientalis along environmental gradients in Kheyrud forest, Nowshahr. Journal of Natural Environmental, 64 (4): 399-415 (In Persian). - Alavi, S.J., Zahedi Amiri, G., Rahmani, R., Marvie Mohajer, M.R., Muys, B. and Nouri, Z., 2013. Investigation on the response of Fagus orientalis Lipsky to some environmental variables using beta function and its comparison with Gaussian function (Case study: Kheyrud forest research station). Iranian Journal of Forest, 5(2): 161-171 (In Persian). - Ali Ehyaei, M. and Behbehani Zade, A.A., 1993. Methods of soil chemical analysis. Soil and Water Research Institute of Agricultural Extension and Education. Vol.1, 128p. (In Persian). - Anonymous, 1984. Procedures for collecting soil samples and methods of analysis for soil survey. Soil Survey Staff, Soil Survey Investigations Rep. No. 1. USDA-SCS Agricultural Handbook, 436p. - Anonymous, 2010. Safaroud forest management plan. Forests, Rangeland and Watershed Management Organization, Natural Resources Office-Nowshahr, 311p. - Anonymous, 2015. R: A language and environment for statistical computing. R Core Team, R Foundation for Statistical Computing, Vienna, Austria. URL http://www.R-project.org/. - Austin, M.P., 1999. A silent clash of paradigms: some inconsistencies in community ecology. Oikos, 86: 170-178. - Austin, M.P., 2002. Case studies of the use of environmental gradients in vegetation and fauna modelling: theory and practice in Australia and New Zealand. In: Scott, J.M., Heglund, P.J., Samson, F., Haufler, J., Morrison, M., Raphael, M., Wall, B. (Eds.), Predicting Species Occurrences: Issues of Accuracy and Scale. Island Press, Covelo, CA, pp. 73-82. - Bremner, J.M., 1996. Nitrogen-total. Methods of soil analysis. In Sparks, D.L. (Ed), Published by: Soil Science Society of America, Inc. American Society of Agronomy, Inc. Madison, Wisconsin, USA. 1309p. - Budke, J.C., Jarenkow, J.A. and de Oliveira-Filho, A.T., 2007. Relationships between tree component structure, topography and soils of a riverside forest, Rio Botucaraı, Southern Brazil. Plant Ecology, 189: 187–200. - Cramer, W. and Hytteborn, H., 1987. The separation of fluctuation and long-term change in vegetation dynamics of a rising sea shore. Vegetatio, 69: 157- 168. - Dirnbock, T., Dullinger, S. and Grabherr, G., 2003. A regional impact assessment of climate and land-use change on alpine vegetation. Journal of Biogeography, 30: 401–417. - Engler, R., Guisan, A. and Rechsteiner, L., 2004. An improved approach for predicting the distribution of rare and endangered species from occurrence and pseudoabsence data. Journal of Applied Ecology, 41: 263-274. - Everson, D.A. and Boucher, D.H., 1998. Tree species-richness and topographic complexity along the riparian edge of the Potomac River. Forest Ecology and Management, 109: 305-314. - Franklin, J., McCullough, P. and Gray, C., 2000. Terrain variables used for predictive mapping of vegetation communities in southern California. In: Wilson, J.P., Gallant, J.C. (Eds) Terrain Analysis: Principles and Applications. Wiley. 520 p. - Guisan, A. and Zimmermann, N.E., 2000. Predictive habitat distribution models in ecology. Ecological Modeling, 135: 147-186. - Habibi Kaseb, H., 1964. Study of soil texture effect on growth of beech. Journal of Natural Resources, 31: 60-70 (In Persian). - Harris, E., 2002. Goodbye to Beech? Farewell to Fagus? Quarterly Journal of Forestry, 96(2): 97-98. - Huisman, J., Olff, H. and Fresco, L.F.M., 1993. A hierarchical set of models for species response analysis. Journal of Vegetation Science, 4: 37-46. - Jansen, F. and Oksanen, J., 2013. How to model species responses along ecological gradients–Huisman-Olff-Fresco models revisited. Journal of Vegetation Science, 24 (6): 1108-1117. - Jansen, F. and Oksanen, J., 2015. Package ‘eHOF’. Extended hierarchical logistic regression (Huisman-Olff-Fresco Models). http://www.r-project.org/ - John, R., Dalling, J.W., Harms, K.E., Yavitt, J.B., Stallard, R.F., Mirabello, M., Hubbell, S.P., Valencia, R., Navarrete, H., Vallejo, M. and Foster, R.B., 2007. Soil nutrients influence spatial distributions of tropical tree species. Proceedings of the National Academy of Sciences of the United States of America, 104: 864–869. - Jokar Sarhangi, A., Amir Ahmadi, A. and Soleyman, H., 2007. Landslide hazard zonation in Safaroud River basin using GIS. Geography and Regional Development, 9: 79-92. - Kalusova, V., Le Duc, M.G., Gilbert, J.C., Lawson, C.S., Gowing, D.J.G. and Marrs Rob, H., 2009. Determining the important environmental variables controlling plant species community composition in mesotrophic grasslands in Great Britain. Applied Vegetation Science, 12: 459-471. - Lawesson, J.E. and Oksanen, J., 2002. Niche characteristics of Danish woody species derived from coenoclines. Journal of Vegetation Science, 13: 279-290. - Mäkipää, R., 1999. Response patterns of Vaccinium myrtillus and V. vitis-idaea along nutrient gradients in boreal forest. Journal of Vegetation Science, 10: 17-26. - Naiman, R.J., Décamps, H. and McClain, H.E., 2005. Riparia Ecology, Conservation, and Management of Streamside Communities. Elsevier Press, 446p. - Oksanen, J. and Minchin, P.R., 2002. Continuum theory revisited: what shape are species responses along ecological gradients? Ecological Modeling, 157: 119-129. - Olden, J.D. and Jackson, D.A., 2002. A comparison of statistical approaches for modeling fish species distributions. Freshwater Biology, 47: 1976-1995. - Olsen, S.R., Cole, C.V., Watanabe, F.S. and Dean, L.A., 1954. Estimation of Available Phosphorus in Soils by Extraction with Sodium Bicarbonate. U. S. Department of Agriculture, No. 939, 24p. - Pakeman, R.J., Reid, C.L, Lennon, J.J. and Kent, M., 2009. Possible interactions between environmental factors in determining species optima. Journal of Vegetation Science, 19: 201-208. - Sakio, H. and Tamura, T., 2008. Ecology of Riparian Forests in Japan. Disturbance, Life History, and Regeneration. Springer Press, 335p. - Santika, T. and Hutchinson, M.F., 2009. The effect of species response form on species distribution model prediction and inference. Ecological Modelling, 220: 2365–2379. - Scott, J.M., Heglund, P.J., Samson, F., Haufler, J., Morrison, M., Raphael, M. and Wall, B., 2002. Predicting Species Occurrences: Issues of Accuracy and Scale. Island Press, Covelo, CA, 868p. - Shahoei, S.S., 2006. The nature and properties of soils (translation). Kurdistan University, 900p. - Stokes, K., Ward, K. and Colloff, M., 2010. Alterations in flood frequency increase exotic and native species richness of understorey vegetation in a temperate floodplain eucalypt forest. Plant Ecology, 211: 219-233. - Uğurlu, E. and Oldeland, J., 2012. Species response curves of oak species along climatic gradients in Turkey. International Journal of Biometeorology, 56: 85–93. - Wei, X.Z., Jiang, M.X., Huang, H.D., Yang, J.Y. and Yu, J., 2010. Relationships between environment and mountain riparian plant communities associated with two rare tertiary-relict tree species, Euptelea pleiospermum (Eupteleaceae) and Cercidiphyllum japonicum (Cercidiphyllaceae). Flora, 205: 841–852. - Zarrinkafsh, M.K., 2002. Forestry soil. Interaction of soil and plants regarding ecological factors forests ecosystems. Research Institute of Forests and Rangelands, 361p. | ||
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