| تعداد نشریات | 286 |
| تعداد نشریات سازمان | 84 |
| تعداد شماره‌ها | 3,032 |
| تعداد مقالات | 33,934 |
| تعداد مشاهده مقاله | 45,322,000 |
| تعداد دریافت فایل اصل مقاله | 64,298,393 |
استفاده از روشهای تجزیه‌وتحلیل بقا در ارزیابی اثرات خصوصیات فرد، توده و محیط بر زمان بقا بلندمازو در برابر بیمار ذغالی | ||
| تحقیقات حمایت و حفاظت جنگلها و مراتع ایران | ||
| مقاله 5، دوره 15، شماره 1 - شماره پیاپی 29، شهریور 1396، صفحه 53-66 اصل مقاله (440.67 K) | ||
| نوع مقاله: مقاله پژوهشی | ||
| شناسه دیجیتال (DOI): 10.22092/ijfrpr.2017.113333 | ||
| نویسندگان | ||
| جلیل کرمی1؛ محمد رضا کاووسی2؛ منوچهر بابانژاد3 | ||
| 1دانشجوی دکتری جنگل‌شناسی و اکولوژی جنگل (پاتولوژی جنگل)، دانشکده علوم جنگل، دانشگاه علوم کشاورزی و منابع طبیعی گرگان، گلستان، ایران | ||
| 2عضو هیات علمی دانشگاه علوم کشاورزی و منابع طبیعی گرگان | ||
| 3دانشیار، گروه آمار، دانشکده آمار، دانشگاه گلستان، گلستان، ایران | ||
| چکیده | ||
| بیماری ذغالی با عاملmediterranea Biscogniauxia یکی از بیماریهای مهم و مؤثر در خشکیدگی درختان بلوط است که در سال 1388 در استان گلستان گزارش گردید. این تحقیق باهدف ارزیابی اثرات خصوصیات درخت، توده و محیط بر زمان بقا (سالم ماندن) بلندمازو، در پارک جنگلی قرق انجام شد. بنابراین 192 اصله درخت بلندمازو با متوسط قطر برابرسینه 9/50 سانتیمتر در پنج دوره شش‌ماهه از مهر 1392 تا مهر 1394 در این مطالعه وارد شدند. از آزمون لگ رتبهای و رگرسیون کاکس به ترتیب برای برآورد میانگین زمان بقای درختان و بررسی عوامل مؤثر بر آن استفاده شد. نتایج حاصل از آزمون لگ رتبهای بیشترین (7/100 ماه) و کمترین (2/40 ماه) میانگین زمان بقا را بهترتیب در مرحله رویشی تیرک و پیردار برآورد کرد. همچنین درختان بلوط با فاصله کمتر از 10 و بیشتر از 200 متر از جاده به ترتیب کمترین (7/51 ماه) و بیشترین (6/109 ماه) زمان بقا را داشتند. بااین‌وجود براساس تجزیه رگرسیون کاکس، در بین متغیرهای مورد بررسی تنها متغیرهای فاصله از جاده و محدوده پراکنش برمیزان بقا درختان بلندمازو مؤثر بودند. با برآورد میزان بقای درختان و عوامل مؤثر بر آن، میتوان روشهای پیشگیری جهت مدیریت و کاهش نرخ بیماری ارائه کرد. استفاده از روشهای تجزیه‌وتحلیل بقا در اپیدمیولوژی بیماریهای درختان جنگلی، این توانایی را به کارشناسان خواهد داد تا درک بهتر و صحیحتری از چگونگی روند بیماریها به دست آورند. | ||
| کلیدواژه‌ها | ||
| بلوط بلندمازو؛ بیماری ذغالی؛ تحلیل بقا؛ مدل کاکس | ||
| عنوان مقاله [English] | ||
| Application of survival analysis methods to assess the effects of individual characteristics, habitat and environment on survival time of oak charcoal against the charcoal disease | ||
| نویسندگان [English] | ||
| J. Karami1؛ M. R. Kavosi2؛ M. Babanezhad3 | ||
| چکیده [English] | ||
| Charcoal disease (Biscogniauxia mediterranea) was reported in Golestan province as one of the major diseases affecting oak decline in 2011. Therefore, this study was aimed to evaluate the influence of tree characteristics, stand and site on the infection risk in oak trees in the Qoroq forest park. In this study, 192 oak trees with the average diameter of 50.9± 16.5 cm at breast height were recorded, so that the health status of the trees was evaluated in five semiannual courses from October 2013 to October 2015. Log-rank test and Cox regression analysis were used to estimate the mean survival time of the trees and the affecting factors, respectively. The Log-rank test demonstrated the highest (100.7 months) and lowest (40.2 months) mean survival time at the vegetative stage in small pole and mature trees, respectively. Oak trees at a distance of less than 10 and more than 200 meters from the road showed the lowest (51.7 months) and the highest (109.6 months) mean survival time, respectively. Nevertheless, according to the Cox regression analysis, among the variables examined only the distance from the road and distribution range had significant effects on the survival rate of oak trees. Estimation of the survival rate and the affecting factors in oak trees could be used in prevention methods to manage and decrease the charcoal disease rate particularly in Qoroq forest park. Using the survival analysis methods in epidemiological studies of the forest tree diseases, the experts will have the better and more accurate understanding on the diseases progress. | ||
| کلیدواژه‌ها [English] | ||
| Quercus castaneifolia, Charcoal Disease, Survival analysis, Cox model | ||
| مراجع | ||
|
Akaike, H., 1974. A new look at the statistical model identification. IEEE Transactions on Automatic Control, 19: 716–23.
- Anton-Fernandez, C., 2008. Towards greater accuracy in individual-tree mortality regression, PhD thesis, Michigan Technological University.
- Baguskas, S. A., Peterson, S. H., Bookhagen, B., Still, C. J., 2014. Evaluating spatial patterns of drought-induced tree mortality in a coastal California pine forest. Forest Ecology and Management, 315: 43–53.
- Condeso, T. E., Meentemeyer, R. K., 2007a. The effects of landscape heterogeneity on the emerging forest disease sudden oak death. Journal of Ecology, 95 (2): 364–375.
- Condeso, T. E., Meenteyer, R. K., 2007b. Effects of landscape heterogeneity on the emerging forest disease sudden oak death.Journal of Ecology, 95: 364–375.
- Contrerasa, M. A., Affleck, D., Chung, W., 2011. Evaluating tree competition indices as predictors of basal area increment in western Montana forests. Forest Ecology and Management, 262: 1939–1949.
- Costa, A., Pereira, H., Madeira, M., 2010. Analysis of spatial patterns of oak decline in cork oak woodlands in Mediterranean conditions. Annals of Forest Science, 67 (2): 204-209.
- Cox, D. R., 1972. Regression models and life-table. (With discussion). Journal of Royal Statistical Society, 34: 187-220.
- Cox, D. R., Oakes, D., 1984. analysis of Survival Data, Chapman and Hall, London, 208p.
- Davidson, J. M., Patterson, H. A., Wickland, A. C., Fichtner, E. J., Rizzo, D. M., 2011. Forest type influences transmission of Phytophthora ramorum in California oak woodlands. Phytopathology, 101: 492–501.
- Fierke, M. K., Kelley, B., Stephen, F. M., 2007. Site and stand variables influencing red oak borer, Enaphalodes rufulus (Coleoptera: Cerambycidae), population densities and tree mortality. Forest Ecology and Management, 247: 227–236.
- Flewelling, J., Monserud, R. A., 2002. Comparing methods for modeling tree mortality. In: Crookston, N. L., Havis, R. N. (Eds.), Second Forest Vegetation Simulator Conference. RMRS-P-25. USDA Forest Service, Rocky Mountain Research Station, Fort Collins, 169–177.
- Gadow, K., Kotze, H., 2014. Tree survival and maximum density of planted forests – Observations from South African spacing studies. Forest Ecosystems, 1:21.
- Jules, E. S., Carroll, A. L., Garcia, A. M., Steenbock, C. M., Kauffman, M. J., 2014. Host heterogeneity influences the impact of a non–native disease invasion on populations of a foundation tree species. Ecosphere, 5 (9): 1-17.
- Karami, J., Kavosi, M. R., Bbanezhad, M ., 2015a. Assessing the relationship between some environmental variables and spread of charcoal disease on chestnut-leaved oak (Quercus castaneifolia CA Mey), Iranian Journal of Forest and Range Protection Research, 13(1): 34-45 (In Persian).- Karami, J., Kavosi, M. R., Bbanezhad, M., 2015b. Description of the symptoms and the evaluation of the co-occurrence of different severity of charcoal disease in Quercus castaneifolia, Journal of Natural Ecosystems of Iran, 6 (3):1-14 (In Persian).-Karami, J., Kavosi, M. R., Bbanezhad, M., 2016. Assessment of relationship between host characteristics with the severity and occurrence of charcoal disease in oak forests of Golestan. Iranian Journal of Forest, 8 (2): 195-207 (In Persian).- Karami, J., Kavosi, M. R., Bbanezhad, M., 2017. Epidemiology of oak decline: Spatial Analysis of oak decline dynamics in a Golestan oak forest (Case study: Qoroq Park Forest). Forest and Wood Products, 69 (4): 777-788 (In Persian).
- Kitahara, M., Hirata, K., 2012. Modeling Tree Mortality Using the Cox Proportional Hazards Model based on data derived from permanent plots of Cryptomeria japonica planted forest. Formth, 11:103–119.
- Klein, J. P., Moeschberger, M. L., 2003. Survival analysis: Techniques for censored and truncated data. Springer, New York , 353p.
- LI, J., Hong, Y., Thapa, R., Burkhart, H. E., 2015. Survival Analysis of Loblolly Pine Trees with spatially Correlated Random Effects. Journal of the American Statistical Association, 110: 486-502.
- Mack, R. N., Simberloff, D., Mark Lonsdale, W., Evans, H., Clout, M., Bazzaz, F. A., 2000. Biotic invasions: causes, epidemiology, global consequences, and control. Ecological Applications, 10 (3): 689–710.
- Meentemeyer, R .K., Cunniffe, N. J., Cook, A. R., Filipe, J. A. N., Hunter, R. D., Rizoo, D. M., Gilligan, C. A., 2011. Epidemiological modeling of invasion in heterogeneous landscapes: spread of sudden oak death in California (1990 –2030). Ecosphere, 2 (2): 1-24.
- Metz, M. R., Frangioso, K. M., Meentemeyer, R. K., Rizzo, D. M., 2011. Interacting disturbances: wildfire severity affected by stage of forest disease invasion. Ecological Applications, 21: 313–320.
- Mirabolfathy, M., 2012. Outbreak of charcoal disease on Quercus spp and Zelkova Carpinifolia trees in forests of Zagros and Alborz mountains in Iran. Journal of Plant Diseases, 49 (2): 257-263.
- Mirabolfathy, M., Groenewald, J. Z., Crous, P. W., 2011. The occurrence of charcoal disease caused by Biscogniauxia mediterranea on chestnut-leaved oak (Quercus castaneifolia) in the Golestan Forests of Iran. Plant Disease, 95 (7): 876-876.
- Porhooseinqoli, M. A., Hajizadeh, A., Abdi, A. R., Safaee, A., Moqimi Dahkoordi, B., Zali, M. R., 2006. Comparison of Cox regression and parametric models in survival analysis of patients with gastric cancer. Iranian Journal of Epidemiology, 3(2): 25-29 (In Persian).
- Rose, E. C., Hall, D. B., Shiver, B. D., Clutter, M. L., Borders, B., 2006. A multilevel 481 approach to individual tree survival prediction, Forest Science, 52 (1): 31–43.
- Shifley, S. R., Fan, Z., Kabrick, J. M., Jensen, R. G., 2006. Oak mortality risk factors and mortality estimation. Forest Ecology and Management, 229: 16–26.
- Sturrock, R. N., Frankel, S. J., Brown, A. V., Hennon, P. E., Kliejunas, J. T., Lewis, K. J., Worrall, J. J., Woods, A. J., 2011. Climate change and forest diseases. Plant Pathology, 60 (1): 133–149.
- Thapa, R., Burkhart, E. H., Li, J., Hong, Y., 2015. Modeling clustered survival times of Loblolly Pine with time-dependent covariates and shared frailties. Journal of Agricultural Biological and Environmental Statistics.
- Therneau, T., Grambsch, P., 2000. Modeling survival data: extending the cox model. New York, Springer-Verlag.
- Woodall, C. W., Grambsch, P. L., Thomas, W., Moser, W. K., 2005. Survival analysis for a large-scale forest health issue: Missouri oak decline. Environmental Monitoring and Assessment, 108: 295–307.
- Worboys, S. J., Gadek, P. A., 2004. Rainforest dieback: risks associated with roads and walking track access in the wet tropics world heritage area. School of Tropical Biology, James Cook University Cairns Campus and Cooperative Research Centre for Tropical Rainforest Ecology and Management. Rainforest Cooperative Research Centre, Cairns, 57p.
- Zens, M. S., Peart, D. R., 2003. Dealing with death data: individual hazard, mortality and bias. Trends in Ecology and Evolution, 18, 366–373. | ||
|
آمار تعداد مشاهده مقاله: 672 تعداد دریافت فایل اصل مقاله: 549 |
||