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Shamsallah Asgari, Tayeb Razi, Mohamadreza Jafari, Ali Akbar Noroozi,
Volume 0, Issue 0 (3-1921)

Due to the importance of forests in natural and anthropogenic environment, the effects of meteorological drought on the dryness of oak forests in Ilam province were investigated. The main purpose of this study was to determine the relationship of Zagros forests with drought occurring in the area. The results of the Standard Precipitation Index (SPI) for the time periods showed that the most drought occurred in 2007, 2008, 2011, 2015 and 2016. Remote sensing data (MODIS images) were used to investigate the vegetation trend (NDVI) of trees during the period 2016–2016. The vegetation trend (NDVI) was significant over the period with the index drought index (SPI) with R2 = 0.9999. Ground harvesting of oak drying points and simulation using Landsat satellite imagery with 15 m pixel output from GIS software showed that 17894 hectares of area forests from 2000 to 2016 were dried and destroyed and prepared with oak forest and integrated layer. The output layers from the drought zoning were shown visually and the statistical analysis was performed in three 5-year time series. The results of these analyzes from 2002 to 2006 showed that the correlation coefficient between meteorological drought and oak drought 96.6% with a coefficient of determination R2 = 0.985, for the time series of 2007 to 2011 the correlation coefficient between scratches Meteorological and oak dryness of 95.4% with R2 = 0.980 and coefficient of correlation for meteorological drought and oak drought of 98.8% and R2 = 0.995 of coefficient respectively. Its fluctuations in time series show the intensity and duration of the drying up of oak forests in the region. According to the results of this study, it is predicted that if the drought goes through this process, 1118.4 hectares of oak forests in Ilam province will be dried and destroyed annually.
- Ahmad Hosseini, - Mostafa Khoshnevis, - Mohammad Reza Jafari, - Shamsolah Asgari,
Volume 0, Issue 0 (3-1921)

Old trees as the most important genetic reserves of the country have great importance and value in various aspects of ecology, forest restoration management, ecotourism and even history. In this research, after identification of the old trees in the forests of Ilam province, their morphological characteristics including DBH, trunk height, total height, crown length, min & max crown diameter, crown health, crown firmness, crown symmetry, Trunk health and trunk shape were examined. The selection of old trees was based on DBH criterion. After the forest survey, 43 old trees including 5 Petrocarya fraxinifolia, 5 Ulmus glabra, 11 Fraxinus rotundifolia, 3 Celtis caucasica, 4 Platanus orientalis, 4 Ficus carica, 7 Olea europea and 4 Cupressus sempervirens were identified. The results showed that among single-stranded trees, P. orientalis had the highest mean DBH, total height and trunk height, and among multi-stranded trees O. europea had the highest mean DBH. P. fraxinifolia and U. glabra had the highest mean of crown length and F. rotundifolia had the highest crown area. The highest percentage of single-trunks belonged to the P. fraxinifolia and C. caucasica. The highest percentage of healthy trunks belonged to C. sempervirens and O. europea and the highest percentage of healthy crowns belonged to P. fraxinifolia, U. glabra, C. caucasica, P. orientalis, O. europea and F. carica. The highest percentage of crown symmetry was belonged to C. caucasica and the highest percentage crown freshness was belonged to P. fraxinifolia, F. rotundifolia, C. caucasica, P. orientalis, O. europea and F. carica. Based on the desirable morphological characteristics of old trees, it is possible to grow and rebuild Zagros forests by producing resistant seedlings from their seeds.
Hengameh Shiravand, Shahriar Khaledi, Saeed Behzadi, Hojjat Allah Sanjabi,
Volume 20, Issue 57 (6-2020)

   Decline phenomenon is one of the most important reasons for the destruction and mortality of oak trees in Zagros forests due to the wide variety and diversity of the topography of its determination through track and field operations is not readily possible. Changes in an ecosystem are often gradual changes, but sometimes changes occur in an ecosystem in a short time. This change can cause a catastrophe in the ecosystem, which is difficult to identify. A proposed method for identifying a general change in time series is use the BFAST model, which, by analyzing the time series in the process, season, and residual components, identifies the changes in the time series and also repeatedly estimates the time and amount of the changes, and The path and amount of variation in this study, using this model and satellite images to monitor and evaluate the changes in coverage and decline of oak forests in Lorestan province during the statistical period (2000-2017). The results showed that more than 42804 hectares (1.5%) of the oak forests of the province were lost due to the decline phenomenon during the studied period. Also, according to the BFAST method, the trend diagram is a failover and their frequency variations are irregular. Comparison and study of different forest coverings also showed a decrease in NDVI, which indicates that the process of decreasing forest cover is inclusive. The study of autocorrelation and Kendal coefficient showed that there were significant changes and severity of failure (-0.7) in the area Study. The seasonal chart also has uneven and irregular variations due to changes in oak forests in the region. The results of this research can be used to study the changes in the coverage of oak forests in the area and management and the way to think about this phenomenon.

Mr Mohammad Safaei, Dr Hani Rezayan, Dr Parviz Zeaiean Firouzabadi, Dr Ali Asghar Torahi,
Volume 22, Issue 65 (6-2022)

Examining the effects of climate change on the oak spatial distribution, as the main species of Zagros forests and its ecological and economic values is of significant importance. Here, we used species distribution models for simulating current climatic suitability of oak and its potential changes in 2050 and 2070. For this purpose, five regression-based and machine learning approaches, four climatic variables related to temperature and precipitation and two optimistic (RCP 2.6) and pessimistic (RCP 8.5)  greenhouse-gas scenarios were used. The results of measuring the accuracy of models by AUC indicated the good performance of all algorithms and Random Forest achieved the highest accuracy (AUC = 0.95) among other methods. The results showed that in both time periods and under both scenarios, changes will occur in oak spatial distribution and the most severe one would be a 42.9 percent loss in the oak climatic suitability in 2070 under pessimistic scenario (RCP 8.5).

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