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Extended Abstract Background: Sustainable management and fundamental planning of forest resources require efficient and high-quality information about the current and future states of forests. Investigating the current and future states of forest stands, describing the structure of the forest stand, and the response of the stand to tending operations are among the capabilities of statistical distributions in forest management. Frequency distribution modeling is the distribution of people in a population in different classes. Since natural phenomena include continuous and discrete types, their distribution will also be different and diverse. The use of statistical distributions in the forest has a long history, and some researchers have considered its history as long as two centuries. Zagros forests, as one of the most important vegetation areas of Iran, have a special importance from the socioeconomic and ecological points of view. The dominant species of these forests is the Iranian oak (Quercus brantii Lindl). According to geographical and environmental conditions, this species has various habitats in the vegetation zone of the middle Zagros. It is expected that this species has different probability distribution functions in different habitats. Therefore, the probability distribution functions of the characteristic height in habitats with different vegetative structures of Iranian oak in the forests of Khorramabad city were investigated in this research to select the best models in different habitats. This study also seeks to provide useful information on the authority of forest managers and planners to preserve and improve these valuable forests. Methods: To carry out this research, two areas with different structures, including coppice with standard (Sefidkoh area) and standard with coppice (Qala-Gol area) were determined in the forests of Khorram Abad city through numerous excursions in the forest. A forest stand with an area of approximately 3 ha was selected in each of these areas. This forest stand was chosen in such a way to represent the forests of the region. The subsoil was semi-deep and north direction in the Qala-Gol forest stand at an altitude of 1850 m above sea level and with an average slope of 20%. In the SefidKoh forest stand, the subsoil was semi-deep and located in the north direction at an altitude of 1900 m from sea level with an average slope of 30%. In each of these two selected forest stands, the height of all Iranian oak trees, with a height of > 1.5 m, was counted 100%. In total, the heights of 458 and 348 Iranian oak trees were measured in the two SefidKoh and Qala-Gol regions, respectively. A TruPulse 360 laser device was used to measure the height of trees. To investigate the distribution of height classes, the most widely used continuous probability distribution models in biological research were used due to the continuousness of the height variable, including two-parameter Weibull, two-parameter gamma, normal, log-normal, beta, and Johnson. The goodness of fit of the data was also examined using the Anderson-Darling test, which has a higher power than other tests. Easy Fit 5.6 software was used to analyze all data and draw graphs. Results: The statistical errors were 4.45% and 2.82% in the Sefidkoh and Qala-Gol regions, respectively. The average height of trees was 6.76 m in the Sefidkoh region (between 1.8 and 18 m) compared to that of 7.54 m (between 1.53 and 14.04 m) measured in the Qala-Gol area. The values of skewness and Kurtosis were positive in the two forest areas, with higher values in the Sefidkouh region than in the Qala-Gol area, indicating the concentration of data in lower-height classes in the Sefidkouh region. The results of Anderson-Darling's goodness of fit test in the Sefidkoh area (coppice with standard) showed that the most suitable probability distribution functions (with a 5% error level) for modeling the distribution of trees in height classes were Johnson sb and beta, respectively. In the Qala-Gol region (standard with coppice), the most appropriate distribution functions were identified as beta and normal, respectively. Conclusion: The results of this research show that the forest has an uneven-aged structure in the areas where the oak forest has a coppice with standard form, according to the form of distribution (decreasing distribution). In contrast, the forest has moved toward a single-stemmed and even-aged forest in areas where the forest form is standard with coppice. This is mainly caused by the destruction through grazing, the cutting of branches for livestock and fuel consumption, and the indiscriminate use of byproducts that have occurred in this region. In the Sefidkoh region, the effects of destruction and less human intervention were observed at the regional level in field observations. According to the shape of the distributions obtained in the two sites, the vegetative forms of the trees affected the distribution functions of their heights, which can provide useful information for managers, planners, and researchers to maintain and control these valuable forests.

Extended Abstract Introduction and Objective: The forests of Zagros, as the most extensive and at the same time as the most damaged forests of the country, have been affected by the extensive decline of oak trees in recent years, and in this sense, they are in a critical conditions. Decline of oak trees is described as a wide and complex phenomenon that causes a decrease in growth and physiological weakness followed by the attack of pathogenic agents. As sustainability of these forests is now facing a serious problem, proper management strategies are required to deal with the decline phenomenon, before these valuable ecosystems are completely destroyed. The implementation of such strategies necessitates collecting basic information, including map of the decline distribution and the extent of the lost biomass of trees as a result of decay. The purpose of this study is to estimate the amount of biomass on the above-ground in dead oak trees as a result of the decline of Zagros forests, which was carried out in the forests of Dadabad region of Lorestan province. Material and Methods: The present study was conducted in Dadabad forests located in the southwest of Khorramabad, Lorestan, Iran. To achieve this purpose, 40 dried trees were randomly selected and biometric parameters including diameter at knee height, diameter at breast height, as well as height and crown diameter were measured. Different parts of the tree were fragmented, dried, and weighed. Using regression analysis, the biomass of different parts was modeled against the independent variables of diameter at knee height, diameter at breast height, crown height, and diameter. Finally, at the area of 32 hectares of the forest stand, a 100% inventory was conducted, and different characteristics of all Iranian oak trees were measured. Results: The results of the research declared that strong relationships can be established to estimate the biomass of Iranian oak trees. The result of fitting linear and non-linear models to estimate the biomass of this tree species showed that if the average diameter of the tree crown was used as an independent variable, the more suitable model was the power model with an explanation coefficient of 0.857. Also, the validity results of the model or the value of RMSE% for the obtained equation was 9.082%. The total biomass in the study area was 389.994 tons, of which 39.54%, i.e. 154.226 tons, of the area's biomass was lost under decline phenomenon. Conclusion: The results indicated that in the comparison between linear and non-linear regression models, the best model for estimating the biomass of this species was the power model based on the average diameter of the crown with R2=0.857. In general, using the average diameter of the crown as an estimator variable for the Iranian oak species can suggest a better and more appropriate assessment of the above-ground biomass of these trees.

Oak decline has been observed periodically in the different parts of the world. We conducted this study to evaluate the project control in this phenomenon. In this paper, the project control methods have proposed to be useful tools to deal with oak decline. The aim of the study is twofold: (i) define and schedule a set of activities and determine times for those activities in the Control of Forest Decline Project (CFDP) using the Project Evaluation and Review Technique (PERT) method; (ii) apply the Critical Path Method (CPM) within the context on how to reduce the project time by increasing operating costs and crashing the activities. In crisis management, "golden time" is defined for doing activities and controlling the crisis, which has a greater role than other times. The analysis confirmed that the problem of forest decline is an ecological problem and its root lies in participatory management with the local community. We also found that the time crashing is not economically efficient to the CFDP except for two activities: public information and stakeholder analysis.

Carbon sequestration through trees is one of the most important strategies to mitigate the carbon emission. The present study was conducted in Khorramabad Agricultural Orchard as randomized complete block design. In each experimental unit, three five-year-old trees were investigated in two groups and 12 poplar colonies or cultivars in three replications. Duncan multiple range test was used to find the mean comparison of the treatments and T test was applied to observe the differences between two groups. The results showed that there is a significant difference in the increment rate and amount of carbon sequestration in the two poplar groups (P

During the last decades, the decrement of forest areas has come to attention in regional and global scales. This research aims to investigate the forest changes using satellite imagery, Artificial Neural Network and Markov chain in Bastam area, Lorestan province. Land use maps for the years 1364, 1379, and 1394 were prepared using the Maximum Likelihood Classification and Landsat TM and OLI Sensors. Land use changes modeling was done, using LCM model based on Artificial Neural Network and 7 effective variables include altitude, proximity of the residential areas, slope, direction, proximity of the roads, proximity of the river and land use map. The land use map for the year 1394 was predicted using the Markov chain modeling method. To evaluate the accuracy of the results, the error matrix was formed between the predicted map and the ground reality map for this year. The results of the first period showed that the highest increase in the agricultural area and the largest reduction in the forest area were 380 and 425 hectares respectively. In addition, the variables of altitude and proximity of residential areas with the Cramer correlation coefficient of 0.47 and 0.43 respectively, had the most effect on land use changes and forest degradation. Finally, the comparison of modeling and reality maps of 1394 showed the Kappa coefficient of 0.89, which indicates the proper performance of the LCM model in predicting land use changes.

The purpose of the study was to investigate the effects of some physiographic factors on competition index (CI) and fine root biomass (FRB) in coppice Persian oak trees (Quercus brantii Var. Persica), and also to determine the correlation between these factors and some characteristics of oak trees in forest of Ghalegol-Lorestan. Randomized blocks sampling method was used to determine the target trees in the site by circular sample plots (n=40). In addition to measuring the DBH of trees and their distance from neighbor trees for determining CI, fine root sampling was done at depth of 0-30 cm and at distance 1m, also in north and south sides of the target trees. The independent t-test showed that the aspect had a significant effect on CI, so that it was more in north-facing than the southern directions (p0.05). The independent t-test showed that aspect had a significant effect on FRB (p

As one of the most important understory evergreen species in Hyrcanian forests of Iran, information on the distribution of Box (Buxus Hyrcana Pojark.) are essential for both forest research and practice. Here, the capability of very high spatial resolution IKONOS satellite imagery acquired in leaf-off condition was tested for mapping Box distribution in a part of Khiboos-Anjili forest reserve in Mazandaran province. The IKONOS imagery was geometrically corrected with a georefrenced panchromatic Pleaides scene, which was orthorectified using 3D ground control points obtained using differential GPS (RMSE less than one pixel). Reference data samples from three classes of non-forested area, deciduous stands without Box understory and deciduous stands with Box understory were recorded using DGPS-supported field survey. By means of a number of vegetation indices, classes seperabilities were evaluated on main and synthetic image channels by partitioning 75% training area and transformed divergence. IKONOS image was classified using both main and best-selected bands and a number of nonparametric (Maximum Likelihood, Mahalonobis distance, Minimum distance to mean and Paralell piped) and parametric (Suport Vector Machine) classifiers. Then the classified images were assessed using 25 percent of unused sample points. Results of validation using the 25% left-out test data showed the highest performance by SVM algorithm compared to other algorithms, with overall accuracy and Kappa coefficient of 97.87% and 0.96, respectively. The results also showed the potential of IKONOS imagery from leaf-off season has to map Box trees in understory layer.

Stand structure and species diversity are two useful parameters for complex assessment of forest biodiversity, and provide important information for management and decision making for appropriate silvicultural system. For this purpose, five one ha plots were selected randomly in homogeneous ecological units of beech-hornbeam type in Nav-e Asalem, Gilan province. In order to determine complex structural diversity index (SI) in the studied forest type, uniform angle, mingling and DBH dimensions difference indicators were calculated. Also in order to determine density of trees, the nearest neighbors distance index was used. According to the results, the average value of nearest neighbors distance index was calculated to 5.58 meter. Mean uniform angle index was 0.52, which indicates clumped distribution of trees. Mean mingling index (0.45) indicates moderate mixture of the studied mixed stand. The amount of DBH dimensions difference index was 0.47, indicates moderate difference between trees diameter at breast height. The complex structural diversity index which presents three dimensions of structure, including diversity of spatial pattern, species diversity, and diversity of DBH dimensions) was calculated to 0.475. This value confirms a high level of tree diversity. The results of this study provide key information for management and maintaining of tree diversity in the studied mixed beech-hornbeam stand. Also with monitoring and management of tree diversity level we can reduce the negative impact of natural and human factors.

Using remote sensing data is an applied method to estimate above ground biomass. In this study, satellite radar data of ALOS-2, with the full polarization and the optical data of Sentinel-2, has been used to estimate the aboveground biomass in the Nav-e Asalem forests, Gilan province. The backscattering coefficients at different polarization, the texture measures and target decomposition features of SAR images, obtained original and synthetic bands from optical images in three different combinations of radar images, optical images and the composition of radar and optical images, as inputs to the Artificial Neural Network (ANN) and Multiple Linear Regression (MLR) models were used. In order to measure aboveground biomass, 149 sample plots were laid out. Evaluation of ANN and MLR models using R2 and RMSE statistics showed that in all cases the ANN was better performance to estimate the aboveground biomass than MLR. The best results showed that the ANN from combined optical and radar data with R2 and RMSE, 0.86 and 31.62 Mg/ha (15.34%), respectively, can be the best applied method to estimate the aboveground biomass. The results of radar images and optical separately, with the R2 and RMSE for the modeling of aboveground biomass have been shown, respectively, 0.57 and 49.17 Mg/ha (23.85%) by radar images and 0.7 and 39.53 Mg/ha (19.17%) by the optical images, superior modeling to estimate aboveground biomass represents by optical imaging. The overall and more accurate results to estimate of aboveground biomass have been shown when we used combined radar and optical images with the ANN model.

Sustainable Forest Management (SFM) means management of forest resources that consideration the needs of the current generation without risking ability of future generations to attain their needs. Evaluation of SFM needs to design a feedback information system to monitoring of forest resources. In this research, sustainability indicators based on the SMART&D framework were prepared in Tange-Solak local area in Zagros forest, Iran. Based on this, 7 indicators of ecosystem features were provided for evaluation of SFM. Here, Sustainability Index (SI) was used in evaluating SFM via fuzzy membership function. The results reveal that, Forest SI was eventually obtained as 0.15. This number (0.15) was obtained from the Fuzzy approach used in this study for an SI value far lower for forest sustainability compared to the number 1 (maximum value). Keywords: Fuzzy logic, Criteria, indicators, Sustainability Index (SI)

To design an optimal plantation map for reforestation, a convenient and accurate method is required to analyze plant communities as well as to simulate the plantation map using the spatial pattern of natural trees. In this study, a new algorithm was designed to simulate a plantation map in Zagros forests. To accomplish this, ten hectares of intact stands located in 45 km south of Khorramabad city in Lorestan province was selected. A set of previously-developed algorithms were evaluated to design a new algorithm. The map extracted from the algorithm showed that the required conditions in drawing the map were met. In addition, an appropriate pattern of plantation in different areas can be reached by using the results of this algorithm. Since this study is the first study of its own in Iran, further investigations are required to remove the weak points. Therefore, it is suggested that the presumably existing weak points may be best removed by applying this algorithm in various regions, as well as by integrating effective indexes such as soil type, height from the sea level and physiographic factors. Being based on computer simulations, the results obtained here should be further experimented in different study sites within Zagros region, followed by a thorough evaluation of their plausibility under natural forest conditions.

Analysis of forest structure is essential for enhanced understanding of forest ecology and management. In this study, the spatial structure of the existing species in Perk district of Ghaleh Gol site in Lorestan Province was explored. To this end, a 32-hectare region was 100% surveyed. To investigate the spatial structure, we used a set of indices including the Clark and Evans, uniform angles, Shannon-Wiener, mingling, Crown canopy and Crown canopy differentiation indices. The results showed the average values of 0.8 and 0.47 for Clark and Evans and uniform angles indices, respectively. This indicated random and cluster distribution patterns. In addition, Mean values of 0.25 and 0.06 were returned by Shannon - Weiner and mingling indices. Due to the dominant Oak coverage within the study area, Blend Low Index was additionally calculated. The mean Crown Canopy Index of 0.5 turned out a canopy dominance of Quercus brantii, Acer cineracense, Crataegus sp. and Pyrus syriaca over Lonicera nomularifolia and Amygdalus sp.. Moreover, the Crown Canopy Differentiation Index was calculated to quantify the differences between the levels of crown canopy in adjacent trees. This returned a mean value of 0.48 for the entire trees, which reflects the difference between the tree canopy levels. The results showed that the study site is currently undergoing an inappropriate biodiversity for woody species which yet shows better conditions compared to similarly-structured stands in the region. As a conclusion, proper forest planning measures should be carried out to prevent the recently experienced consistent loss of biodiversity.

Manna oak (Quercus brantii) is the most important tree species in Zagross region of Iran that faces lack of natural regeneration by seed. Forest managers suggest reforestation by seeds or seedlings as the main silvicultural practice, in order to rehabilitate these sites. In spite of the importance of shade tolerance in reforestation or seedling production in nurseries, some species such as Mana oak have not been well characterized. A completely random experimental design with light factor at four levels (20%, 40%, 60%, and 100% of sunlight) was used to study morphological and growth response of Manna oak seedlings in the first growing year. There were two samplings i) 100 days after germination and ii) 190 days after germination, using 20 seedlings for each treatment. The results showed that at the lowest light radiation level (20% of full sunlight) height growth, slenderness coefficient, root/shoot biomass ratio, and mean of leaf area increased whreas collar diameter, shoot biomass, net assimilation rate, and relative growth rate decreased. Since, high relative growth rate implies high survival rate, so Manna oak can be considered as shade intolerant species that in nurseries with no humidity limitations has the most efficiency in full sunlight.

The main objective of this research is to investigate the potential combination of Sentinel-2A and ALOS-2 PALSAR-2 (Advanced Land Observing Satellite -2 Phased Array type L-band Synthetic Aperture Radar-2) imagery for improving the accuracy of the Aboveground Biomass (AGB) measurement. According to the current literature, this kind of investigation has rarely been conducted. The Hyrcanian forest area (Iran) is selected as the case study. For this purpose, a total of 149 sample plots for the study area were documented through fieldwork. Using the imagery, three datasets were generated including the Sentinel-2A dataset, the ALOS-2 PALSAR-2 dataset, and the combination of the Sentinel-2A dataset and the ALOS-2 PALSAR-2 dataset (Sentinel-ALOS). Because the accuracy of the AGB estimation is dependent on the method used, in this research, four machine learning techniques were selected and compared, namely Random Forests (RF), Support Vector Regression (SVR), Multi-Layer Perceptron Neural Networks (MPL Neural Nets), and Gaussian Processes (GP). The performance of these AGB models was assessed using the coefficient of determination (R2), the root-mean-square error (RMSE), and the mean absolute error (MAE). The results showed that the AGB models derived from the combination of the Sentinel-2A and the ALOS-2 PALSAR-2 data had the highest accuracy, followed by models using the Sentinel-2A dataset and the ALOS-2 PALSAR-2 dataset. Among the four machine learning models, the SVR model (R2 = 0.73, RMSE = 38.68, and MAE = 32.28) had the highest prediction accuracy, followed by the GP model (R2 = 0.69, RMSE = 40.11, and MAE = 33.69), the RF model (R2 = 0.62, RMSE = 43.13, and MAE = 35.83), and the MPL Neural Nets model (R2 = 0.44, RMSE = 64.33, and MAE = 53.74). Overall, the Sentinel-2A imagery provides a reasonable result while the ALOS-2 PALSAR-2 imagery provides a poor result of the forest AGB estimation. The combination of the Sentinel-2A imagery and the ALOS-2 PALSAR-2 imagery improved the estimation accuracy of AGB compared to that of the Sentinel-2A imagery only.

In this study, some forest biometric parameters were studied to evaluate the decline severity in Tang-e Solak forest area in Kohgiluyeh and Boyerahmad province. Hundred plots of one hectare each were used. The Fierke method was used to evaluate the decline severity. In this method, crown condition classes (CCC) and Basal Emergence hole Classes (BEC) are divided into 6 groups. Finally Rapid Estimation Index (REI) was calculated by aggregating CCC and BEC. REI was then classified into tree classes for determining the dieback severity. The result of this study showed that 88% of broad-leaved trees are in weak severity, while only 12% include medium severity of decline.

Visualization is one of the best methods to represent data from natural environments. In this research, the variation of the forest cover was visualized at a part of Zagros forests (741 hectare) using aerial photographs and satellite images. Geometric correction and relief displacement was done on 1997 aerial photographs. Aerial photographs of 1955 and 1969 were corrected by approximate image correction method using georefrenced images. Forest boundaries were determined on all of the images by visual interpretation techniques, However classification of 1997 aerial photographs and satellite image were done automatically using Maximum likelihood classifier. Aerial photographs of 1955 and 1969 were classified by dot grid. Shadow index was specified by determining the accurate canopy amount on 74 random trees and compare them with data deduction from images. Likewise, field data were collected using 141 circular 1200m sample plots in a systematic random grid (100m×300m). With preparation of essential data, visualizations were done on different scale in the 3DNature software. Results indicated the notable reduce of forest area (37%) since 50 years ago. Maximum amount of canopy drop (45%) have been occurred from 1955 to 1969. Canopy percent on forest region indicate ascending trend (+15%) from 1969 to 1997 and lightly descending trend from 1997 to 2003.