تهیه نقشه خشکیدگی بلوط ایرانی (Quercus brantii Lindl.) با استفاده از روش زمین‌آمار در دشت ‌برم استان فارس

نوع مقاله: علمی- پژوهشی

نویسندگان

1 دانشجوی دکتری جنگل‌داری، دانشکده منابع ‌طبیعی، دانشگاه تهران

2 استاد، گروه جنگل‌داری و اقتصاد جنگل، دانشکده منابع طبیعی

چکیده

این پژوهش به‌منظور تهیه نقشه خشکیدگی بلوط ایرانی (Quercus brantii Lindl.)، تجزیه ‌و تحلیل و تشریح پراکنش مکانی درختان و توده‌های خشکیده بلوط با استفاده از روش زمین‌آمار و رسم نقشه‌های پهنه‌بندی خشکیدگی، احتمال و خطا در منطقه دشت‌برم استان فارس انجام شد. داده‌ها در قطعه‌نمونه‌هایی مستطیلی‌شکل به‌ مساحت 1200 متر مربع (40×30 متر) براساس شبکه‌ای به ابعاد 500×500 متر با روش منظم- تصادفی جمع‌آوری شد. واریوگرام‌های تجربی ناهمسان‌گرد با استفاده از روش‌های مختلف زمین‌آماری رسم شد. نتایج ارزیابی متقابل نشان داد که روش کریجینگ معمولی با مدل کروی بهترین برازش را به داده‌ها داشت. نقشه خشکیدگی در طبقه‌های کمتر از 10، 10 تا 25، 25 تا 60 و بیشتر از60 درصد ترسیم شد. بیشترین سطح به طبقه 25 تا 60 درصد با 3827 هکتار و کمترین سطح به طبقه کمتر از 10 درصد با 260 هکتار تعلق داشت. در نقشه احتمال خشکیدگی مشاهده شد که احتمال این‌که خشکیدگی بیشتر از 60 درصد باشد، در بیشتر سطح در محدوده کمتر از 25 درصد بود و در سطح کمی از محدوده بین 50 تا 75 درصد واقع شده بود. پژوهش پیش‌رو نشان داد که با استفاده از زمین‌آمار (کریجینگ) می‌توان تغییرات مکانی، خطای برآورد و احتمال پیش‌بینی خشکیدگی درختان بلوط زاگرس را در قالب نقشه ارایه داد و کانون‌های خشکیدگی (آفت و بیماری) را شناسایی کرد.

کلیدواژه‌ها


عنوان مقاله [English]

Mapping Brant's oak (Quercus brantii Lindl.) mortality using geostatistical methods in Dasht-e Barm, Fars province

نویسندگان [English]

  • Shahram Ahmadi 1
  • Ghavamoddin Zahedi Amiri 2
  • Mohammad Reza Marvie Mohadjer 2
1 Ph.D. Student Forestry, Faculty of Natural Resources, University of Tehran
2 Prof., Department of Forestry and Forest Economics, Faculty of Natural Resources, University of Tehran
چکیده [English]

This research was conducted to study the spatial distribution of Brant's oak (Quercus brantii Lindl.) mortality using geostatistical prediction and mapping approaches in Dashte-e Barm, Fars province. Field sampling was performed based on a 500m×500m systematic random grid and 1200 m2 rectangular forest plots. Different geostatistical methods were used for plotting anisotropic empirical semivariogram and surface creation. Results of cross validation showed that ordinary kriging with spherical model achieved superior results. The models were used for wall-to-wall prediction maps with four classes, including <10%, 10-25%, 25-60% and >60% mortality. The 25-60%, mortality class occupied the largest area (3827 ha), whereas the <10% class covered the smallest portion of the study area (260 ha). In addition, the probability of mortality was spatially mapped, in which the probability of > 60% tree mortality across the entire study site was shown to be less than 25%. This research concluded that Geostatistical kriging methods could be applied to predict and map missing tree mortality values in forest stands. Our analysis suggests that these methods can be used to generate prediction and probability maps in zagros oak stands for overarching goals such as forest mortality, pest and disease managements.

کلیدواژه‌ها [English]

  • Geostatistic
  • mortality
  • Oak
  • Spatial variation
  • Zagros

- Akhavan, R., Sagheb-Talebi, Kh., Zenner, E.K. and Safavimanesh, F., 2012. Spatial patterns in different forest development stages of an intact old-growth oriental beech forest in the Caspian region of Iran. European Journal of Forest Research, 131(5): 1355-1366.

- Anonymous, 2006. Sub-Manual on Forest Vegetation Monitoring in EANET. Network Center for EANET, Acid Deposition and Oxidant Research Center, Japan, 128p.

- Anonymous, 2015. Fars Meteorological Bureau Online Data. Available at: http://www.farsmet.ir/Default.aspx

- Babish, G., 2006. Geostatistics Without Tears: A Practical Guide to Surface Interpolation, Geostatistics, Variograms and Kriging. Environment Canada, Gatineau, Quebec, 117p.

- Biondi, F., Myers, D.E. and Avery, C.C., 1994. Geostatistically modeling stem size and increment in an old-growth forest. Canadian Journal of Forest Research, 24: 1354-1368.

- Fallah Shamsi, S.R., Erfanifard, S.Y., Negahban, M., Ahmadi, SH., Solaymani, H.,Moeinodin, M. and Ranjbar, E., 2012. Detecting distribution pattern of Core-borer beetle in Persian oak forest (Quercus brantii), Case study: Dasht-e-Barm, Fars, Shiraz. Proceedings of National Conference of Zagros Forests (Challenges, Opportunities and Threats). Shiraz, 24-25 May. 2012: 18-27 (In Persian).

- Grodzki, W., 2005. GIS, spatial ecology and research on forest protection: 7-14. In: Grodzki, W. (Ed.). GIS and Databases in the Forest Protection in Central Europe. Forest Research Institute, Warszawa, 93p.

-  Hlásny, T., Vizi, L., Turčáni, M., Koren, M., Kulla, L. and Sitkova, Z., 2009. Geostatistical simulation of bark beetle infestation for forest protection purposes. Journal of Forest Science, 55(11): 518-525.

- Jafarnia, SH. and Akbarinia, M., 2014. Investigation of spatial distribution of soil and water properties by use of Geostatistical in Mangrove forest of Qeshm Island. Iranian Journal of Forest and Poplar Research, 22: 673-686 (In Persian).

- Johnston, K., Sakala, M. and Wrightsell, J., 2001. Using ArcGIS Geostatistical Analyst. ESRI Press, Place Redlands, Canada, 300p.

- Klobucar, D. and Pernar, R., 2012. Geostatistical approach to spatial analysis of forest damage. Periodicum Biologorum, 114(1): 103-110.

- Köhl, M. and Gertner, G., 1997. Geostatistics in evaluating forest damage surveys: considerations on methods for describing spatial distributions. Forest Ecology and Management, 95: 131-140.

- Legendre, P. and Legendre, L., 1998. Numerical Ecology. Elsevier, London, 853p.

- Lorenz, M., Seidling, W., Mues, V., Becher, G. and Fischer, R., 2001. Forest condition in Europe results of the 2000 large-scale survey. Geneva: Federal Research Centre for Forestry and Forest Products (BFH). UN/ECE and EC, 103p.

 - Negron, J.F., Anhold, J.A. and Munson, A.S., 2001. Within-stand spatial distribution of tree mortality caused by the Douglas fir beetle (Coleoptera: Scolytidae). Environmental Entomology, 30(2): 215-224.

- Otto, L.F. and Schreiber, J., 2001. Spatial patterns of the distribution of trees infected by Ips typographus (L.) (Coleoptera, Scolytidae) in the National Park “Sächsische Schweiz” from 1996 to 2000. Journal of Forest Science (Special Issue 2), 47: 139-142.

- Rezaie, E., Akhavan, R., Soosani, J. and Pourhashemi, M., 2014. Efficiency of Kriging for estimation and mapping of crown cover and density of Zagros oak forests (Case study: Dadabad region, Khorramabad). Journal of Forest and Wood Products (Iranian Journal of Natural Resources), 67(3): 359-370.

- Ristaino, J.B. and Gumpertz, M.L., 2000. New frontiers in the study of dispersal and spatial analysis of epidemics caused by species in the genus Phytophthora. Annual Review of Phytopathology, 38: 541-576.

- Rossi, R.E., Mulla, D.J., Journel, A.G. and Franz, E.H., 1992. Geostatistical tools for modeling and interpreting ecological spatial dependence. Ecological Monographs, 62: 277-314.

- Sagheb Talebi, Kh., Sajedi, T. and Pourhashemi, M., 2014. Forests of Iran: A Treasure from the Past, A Hope for the Future. Springer, 152p.

- Taylor, S.L. and MacLean, D.A., 2007. Spatiotemporal patterns of mortality in declining balsam fir and spruce stands. Forest Ecology and Management, 253: 188-201.

- Turčáni, M. and Hlásny, T., 2007. Spatial distribution of four spruce bark beetles in northwestern Slovakia. Journal of Forest Science (Special Issue), 53: 45-52.

- Vieira, S.R., Pierre, L.H., Grego, C.R., Siqueira, G.M. and Dafonte, J.D., 2010. A Geostatistical analysis of Rubber tree growth characteristics and soil physical attributes: 255-264. In: Atkinson, P.M. and Lioyd, C.D. (Eds.). GeoENV VII - Geostatistics for Environmental Applications. Springer, Amsterdam, 419p.

- Webster, R. and Oliver, M.A., 2000. Geostatistics for Environmental Scientists. Wiley Press, USA, 271p.