فهرست مطالب امید کرمی

The occurrence of fires is one of the important factors that determine the different characteristics of many terrestrial ecosystems. For a long time, fires have severely affected forest areas, and sometimes their negative effects remain for several years after the occurrence of the fire, so that the state of vegetation does not return to its previous state. The aim of this study is to model the restoration of vegetation in Zagros forests (Ilam province) following fire.

We used various climatic and environmental data as independent variables (vegetation at the time of fire (NDVI+1), burn severity index, temperature and precipitation anomaly, average temperature, annual precipitation, slope, aspect, and elevation) and NDVI +5 as dependent variable for the modeling (using random forest, decision tree and gradient boosting) the vegetation recovery following fire. Landsat satellite images were used to prepare indices indicating vegetation density status and burn severity, and after preprocessing the images, these indices were prepared by spectral ratio. Climatic variables (precipitation, average temperature, minimum temperature and maximum temperature) were also estimated according to the regression relationships between these variables and the elevation in the study area. Finally, three machine learning algorithms, including decision tree, random forest, and gradient boosting, were used for modeling, and also the accuracy of these models were evaluated.

The results showed that among the various variables investigated, the annual precipitation, average annual temperature, normalized vegetation difference index (NDVI) and burn intensity index at the time of fire were the most important factors affecting the vegetation restoration post fire in these forests. The precipitation and temperature were the most important factors affecting the restoration among the mentioned factors. Also, the results showed that among the different models, the gradient boosting algorithm with R2 = 0.66 models vegetation restoration better than other models. In this model, the climatic factors were the most important in the vegetation recovery.

According the relationships between the NDVI and other studied factors and the results of the modeling; it is possible to explain the effective role of climate factors in the vegetation restoration in the study area.

Understanding the dynamics and spatial distribution of plant species is an important strategy to conserve biodiversity. Modeling the distribution of plant species is one of the important methods in this field, which uses appropriate indicators to identify the relationships of different environmental variables and evaluate the habitat suitability for a species. In this study, in order to identify suitable areas for the presence of Iranian oak, which is one of the most important tree species in the Zagros forests in Iran, the model of maximum entropy (MaxEnt) was used. 16 environmental variables including topographic, climatic, and soil variables were used as independent variables and occurrences of Iranian oak were used as response variables. In order to evaluate the model, the area under the curve (AUC) was used. Jackknife method was used to determine and evaluate the importance of environmental variables. The results of this study showed that the MaxEnt model had a high efficiency with AUC: 0.98 and the mean annual temperature, elevation, and precipitation in the wettest quarter are more important. In addition, aspect and NDVI were the least important in model construction. In this study, the suitability map of Iranian oak in the study area was prepared, which can be a reliable source for managers in planning to protect and rehabilitate deforested forests in the study area.

Land use change is one of key factors in global environmental change, which affects a wide range of environmental characteristics and natural resources (processes and functions of ecosystems and climate systems, water quality, land and air resources). Excessive destruction and exploitation of forests and pastures, inadequate cultivation patterns, land degradation due to population growth and lack of proper management of natural environments have endangered nature and destructed habitats. Planning in this respect demands a clear understanding of how the land should be used and the type of activity done in each part of it in order to obtain accurate information about different communities and terrestrial phenomena. Also, it is difficult to access information to evaluate land degradation and land use change on both global and regional scale. One of the most important ways to determine land use change is satellite imagery. Because protected areas play an important role and are the core of biodiversity conservation, their management and conservation require further field research. Therefore, having information about land use and its changes over time is one of the important issues in planning and policy-making in this region. Therefore, the present study was conducted to predict and evaluate the rate of natural land degradation by emphasizing land use change in the Dinarkoh protected area.

Dinarkoh forest protected area is one of the mountainous areas of Ilam province. This study collected the required information about the study area and similar studies using library and field studies. Then, satellite images were extracted for data analysis and software methods were used to process them. In this way, after examining the geometric and atmospheric errors in the images used, using the maximum probability method, a map of land use classes related to the period 2001-2020 was created. Then, using two post-classification comparison methods, the difference in vegetation index (NDVI) was used to detect and study land use changes in the study period.

The results of evaluating the accuracy of the map obtained from the classification with the maximum probability algorithm on TM and OLI images showed that the accuracy of each of the TM and OLI classified images in the supervised classification method with the maximum probability method is high and acceptable. Considering the overall accuracy of 92.09% in TM image classification and 92.66% in OLI image, it can be said that these two images can prepare the desired area map at any time and can be used to identify changes. The results showed that factors such as similarity of the reflection of some lands which causes an inaccurate segregation of classes reduce the accuracy and are classified as a source of error. Therefore, in general, it can be said that according to the accuracy obtained from TM and OLI images, these two sensors can detect changes. The results showed that forest exploitation and a sharp increase in the population of villages and cities and their need for housing and economic factors have reduced the level of forest. Comparison of the classification maps obtained from the methods used in this research with the ground reality map showed that these methods have different accuracy in identifying areas of change and non-change. The results of satellite image processing showed that in 2001, compared to 2020, more than 6000 ha of forest lands in the region during the 19-year period have been converted into non-forest lands such as agriculture and rangeland, which indicates poor protection of the region.

The results showed that 8000 ha lands in the study area in terms of NDVI index had a decrease in vegetation cover, which indicates the trend of degradation in the region and the need for more serious conservation measures.

Today, the use of modeling methods to predict and modeling of regeneration for different species in forest conservation and management plans is increasing. It is possible to predict the condition and density of forests in the future by forest regeneration modeling and based on that, adopted different management scenarios.

With regard to importance of the subject, in this study the regeneration rate of oak species in a part of oak forests of Manesht and Qalarang protected area-Illam province was estimated using artificial neural network (ANN) and environmental variables such as primary topographic properties, secondary topography, soil physical properties, soil chemical properties and forest structural characteristics as independent variables. For this purpose, various functions and models were evaluated. After sampling, 70% of the, oak regeneration samples was used as training samples to implement the ANN model and the remaining 30% of the data was used to evaluate the model results. Finally, the sensitivity of the oak regeneration model was analyzed.

The results showed that the artificial neural network with error standard error equal to 0.99 was able to estimate the oak regeneration in the study area. The results of sensitivity analysis showed that the highest R2 is related to the model with all input variables, which indicates the positive effect of all input parameters to the model, so that by removing each of the input variables, the accuracy of the model in predicting oak regeneration decreases. However, the results also showed that forest structural and soil chemical characteristics are the most important factors affecting oak regeneration in the study area. The least effect on oak regeneration in the prepared model are secondary topographic variables, which although had a positive role in predicting the regeneration. However, the effect of these variables was less than other variables. The results showed that about 21% of the study area has less than 100 regenerations per hectare. Also, more than 12% of the study area has more than 1200 regenerations per hectare.

In general, the simultaneous use of all primary and secondary topographic features, soil and forest structural characteristics increase the accuracy of regeneration modeling of Zagros oak forests. On the other hand, ANN due to its flexibility, allows the selection of the various variables according to the study area conditions and the available information, as a result, it increases the accuracy of modeling.

Drought stress is one of the most important limiting factors in the expansion and regeneration of plants in the agricultural systems and natural environment, which the best way to deal with it is to introduce cultivars resistant to stress. For this purpose, by experimenting in the 2015 -2016 cropping year, the response of 5 cultivars of chickpea including 3 Kabuli cultivars (Arman, Azad and ILC482) and 2 Desi cultivars (Pirooz and Kaka) to drought stress resistance under 5 levels of water potential (0, -3, -6, -9 and -12 times), using 6000 polyethylene glycol in the laboratory in a factorial design in a completely randomized design with 3 replications. Cultivars were evaluated in field conditions in the form of a randomized complete block design with 4 replications at the research site of the Kurdistan Agricultural Research Center. The results showed that there are significant relationships between the characteristics measured in laboratory and field conditions. Among the studied cultivars, only Desi cultivars showed good germination potentials in (-9) and (-12) times. Therefore, in terms of drought stress tolerance at the germination stage, they had a significant advantage over Kabuli cultivars. In reducing the potential from zero to (-6) times, the greatest difference was seen in all traits. The highest number of days to flowering, day to maturity and the number of seeds per plant belonged to Kaka cultivar and the highest grain yield belonged to Arman cultivar. Cluster analysis revealed the similarity of Kabuli cultivars and their genetic distance from Desi cultivars.

Investigating the soil and vegetation characteristics of forest provides basic and essential information on the management process of forests. Therefore, due to the importance of the subject,  this study is to investigate the distribution of different soil parameters and vegetation diversity in a part of oak forests of Ilam province using geostatistics methods. In so doing, at first, 100 plot centers were identified in a systematic random method with a network by 100 × 200 m2 dimensions. Three samples were selected  around  the center of each plot at a depth of 20 cm. In each plot, 4 samples of 1 m2 were used for vegetation sampling.  After calculating different parameters, the spatial structure of the parameters investigated, the estimated accuracy was calculated, and finally the spatial distribution map of the various parameters was papered. The results showed that there is a spatial dependency between the characteristics of the soil as well as diversity, richness and uniformity in the studied area and the distribution map of these parameters provided with proper accuracy. In addition, the results of the comparison between the two protected and unprotected areas showed that there was a significant difference between the two regions in relation to the different variables.

The aim of this study was to predict and investigate land use change trends in Manasht - ghalarang protected area in Ilam province using Landsat satellite imagery (L5 TM-1984, L5TM-1999, L8 OLA-2014). After geometric and atmospheric correction on satellite images, four land uses including agriculture, garden, pasture and forest were identified in the study area. For classification of satellite images used the comparison of maximum likelihood (MLC) and k nearest neighbor (KNN) methods, and for identifying user changes from post-classification comparison methods, the difference of vegetation index (NDVI) and principal component analysis (PCA) were used. Prediction of land use changes in 2024 was performed using the automated fusion cell and Markov chain model. The classification of images used with the MLC method is higher than KNN method. According to the classification results, during the period 1984–2014, decreases in rangelands and forests and increase in gardens and agricultural were observed. In the comparative method after classification most changes happened in period of 1984-1999 were related to forest conversion to agriculture, while in period of 1999-2014 were to forest to pasture. Forecasts of changes for 2024 showed that agricultural land-uses increased by 1.10%, garden by 0.52% and rangelands and forests decreased by 0.76% and 0.86 %, respectively. Based on the results, the use of Landsat images in combination with the Markov model in modeling land use change, had high accuracy and can be effective in decision-making and management of the region.

The first and most important issue in forest drought management is knowledge of the location and severity of forest decline. In this regard, we used geostatistics and artificial neural network methods to map the dieback intensity of oak forests in the  Ilam province, Iran. We used a systematic random sampling with a 250 × 200 m grid to establish 100 plots, each covering 1200 m2. The percentage of the declined trees in each plot was measured and recorded. Also, a composite soil sample was extracted from the center and the four corners of each plot in order to determine their physical and chemical properties. After examining the normality of the data, the dieback intensity map was made using interpolation methods and the artificial neural network. The results showed  that the best method for dieback intensity estimation was the artificial neural network with an accuracy of 85 %, by using the multilayer perceptron algorithm. Oak decline was found to be mainly related to the slope, soil moisture, soil organic content and soil bulk density.

In recent years, oak decline phenomenon has caused severe damages in Zagros forests. To deal with and managed this crisis, prior to any action, having accurate information about the status and distribution area of this phenomena is necessary. Using satellite data is one of methods to achieve information on the extent and severity of die back. For this purpose, map of oak decline severity was prepared in four levels for some parts of Ilam forests using Worldview-2 satellite data. Maximum likelihood, naive bayes, K-nearest neighbors and artificial neural network classification algorithm were used. The results showed that among different classification methods, the results of artificial neural network classification algorithm had most overall accuracy with 72.83%. Moreover, our results confirmed that the Worldview-2 satellite data can illustrate the severity of oak decline.

Today, with the increasing attention of economic policy makers to economic development and growth, and less attention to the effects of this growth and development, we are witnessing the destruction of environmental goods. One reason for the lack of attention to environmental issues is the lack of awareness of their actual value. So, environmental studies can be helpful. In this study, we want to determine the factors affecting the willingness to pay for visitors of Nazhvan Park which is located near the Zayandehrood River. Results from 313 questionnaires were completed from visitors and estimating Logit model shows that the offer price variable at 1%, sex and numbers of visits variables were significant at the 10% level. Finally, the average willingness to pay for recreational use of the Nazhvan Park visitors, was calculated to 1530 Rials. Given that women are more willing to pay, so building the parks for ladies in the city has economic justification. This means that costs of keeping the park can be met from visitors. Numbers of visits variable is significant and has positive impact on willingness to pay. So, improving transportation system for better access to the Park can increases non market valuation of Nazhvan Park and visitor's satisfaction.

An experiment was conducted under completely randomized design to study the effect of different levels of probiotic (500 and 1000g/feed for 1st phase (25 days) i.e. 35-60 days and at the levels of probiotic (250 and 500g/feed) as 2nd phase (50 days) i.e. 60-110 days. 90 rock partridges (35 day old) were randomly distributed into three treatments and five replicates (6 birds in each replicate) with feed and water ad libitum for 75 days. During experimental period, performance, gut microflora, gut morphology and carcass characteristics of rock partridges were studied. At the end of experiment, two birds were selected from each replicate randomly and slaughtered to study the gut microflora, gut morphology and carcass traits. The experimental diets were as follows: 1= Basal diets (without feed additives), 2= Diet suppl. with probiotic 500g/t feed, 3= Diet included with probiotic 1000g/t feed, 4= Diet contains probiotic 250g/t feed and 5= Diet included with probiotic 500g/t feed. The results indicated that, during 1st phase (25d), the higher and the lower daily feed intake were significantly observed in diets containing probiotic at 1000g/t feed and control groups respectively (p

Recently, forest decline has outburst in Zagros forests, west of Iran. Consequently, we aimed considering dried trees and their spatial patterns as well as spatial structure at Bioreh forests in Ilam province, west of Iran. For this purpose, we selected and fully inventoried a 96 ha infected forest. The interested attributes were tree species, diameter at breast height (DBH), crown diameter, origin and number of sprout in coppice trees as well as Cartesian coordinates of dried trees with drying intensity more than 50 percent. For spatial point pattern analysis and spatial structure of interested attributes, O- ring statistics and variogram analysis were used, respectively. Results showed that the density of dried trees was 10 N/ha which more comprised of coppice trees, while high frequency percentage of drying was observed in large diameter classes. The spatial pattern of dried trees was determined as cluster up to 15 m, which implied that dried trees created patches with 4500 m2 surface area. No spatial structure were found for three interested attributes (DBH, crown diameter and number of sprout) which implied that there was no similarity among infected trees. These results can be used as an instruction to manage infected stands based on their spatial characteristics.

Lighvan Chay River in East Azerbaijan province named as one of the important tourism zone of the province because of its many natural places for leisure, entertainment and recreational opportunities like field trips and camping. Environmental goods and services are more open access public goods. Lack of awareness of the actual value of the environment is one of the important factors of ignoring the environmental issues and causes environmental deteoration. Therefore, the issue of estimating the environmental value can be helpful to policy-makers and practitioners involved in the conservation and management of natural resources. The aim of this research is to estimate the conservation value of the Lighvan Chay River with the use of contingent valuation method and Double–Bounded Dichotomous Choice (DDC). Results from 149 questionnaires were completed from visitors (in the summer of 2012). Estimating logit model shows that the price offer variable at 1%, marital status and satisfaction of utilities variables were significant at the 5% level and numbers of visits variables was significant at the 10% level. The offered bid variable has marginal effect -0.00004 shows that an increase a unit of bid makes 0.00003 unit decrease in WTP. In this paper willings to pay to protect the area was calculated $2 per month per person by using Shazam 10. Since the average family size was 4.22, so average willings to pay of each family per month was $1.9340. Finally, Mean willingness to pay for each family per year, was calculated $1. Therefore, the formation of the association to preserve the area is recommended. However, according to the positive effect of numbers of visits variable, to facilitate the area’s accessibility by improving road networks is recommended.

In order to study the chemical clogging and its effect on hydraulic performance of trickle irrigation system, four treatments includes compensating emitters (Netafim and Micro-Flapper), non-compensating emitters (Mehr and Goldani), three treatment of flow rates that includes 8, 4 and 2 lph (liters per hour) were selected and tested using Karoun river’s water in No. 1 research farm of Shahid Chamran University of Ahvaz. The experiment was conducted in a Completely Randomized Block Design (CRBD) and irrigation was performed in 31 times with irrigation frequency for two days, at pressure of 1.5 bar. The results showed that decreasing of flow rate of Micro-Flapper emitter with 8 and 4 LPH flows is higher than the other treatments and this decreasing is significante at the five percent. Also the Micro-Flapper emitter with 2 lph flows has the lowest decreasing of flow rate. Based on field observations, herniation of silicon diaphragm that used in Micro-Flapper emitters with 8 and 4 lph flows is the main reason for the reduction of flow rate and high values of CV, qvar and qd. So in this particular case the Chemical sediment did not impose a major effect. Turbulent regime of water at the outlet is the reason of resistance against the chemical clogging in the Micro-Flapper emitter with 2 lph flows. In Netafim emitter with 8 and 4 lph, despite having the significant clogging in five percent signification level have a minimal values of CV, qvar and qd and high values of EU and CU. In this experiments, the treatment which had the lowest coefficient of manufacturing Variation, was accounted to it the lowest coefficient of variation of flow rate and the highest Emission Uniformity of variation. In most treatments during the Irrigation, values of CV, qvar and qd increased and values of EU and CU decreased. According to the results presented, the Goldani emitter with 8 gph flows is rated and selected as the top emitter in both terms of resistance against the chemical clogging and hydraulic performance parameters than other emitters.

Stresses caused by recent droughts and fine dust lead to physiological weakness of oak trees as the insect outbreaks and pathogens lead to oak tree decline in the Zagros forests. To evaluate the effect of physiographic factors (terrain relief)، forest cover density and soil on the amount and distribution of dead standing oak trees، a logistic regression model was used. An area of 540 ha of oak forests in the Bivareh region from Malekshahi country in Ilam province was selected. Global positioning system was used for recording all dead standing oak trees. Then، using the recorded points of dead standing trees and digital elevation model، different required maps of the study area like distribution map of dead standing oak trees، elevation classes map، aspect and slope percentage maps، forest density map and soil map were developed. In order to understand the relationship of each factor with dead standing oak trees a logistic regression model was used، with the maps of aforementioned factors as independent variables and the map of location of dead standing oak trees as the dependent variable. The results showed that with increasing altitude in the western and southern aspects، increasing forest cover density and in areas with shallow soils and steep terrain the amount and distribution of dead standing oak trees were increased. Finally، based on the current position map of dead standing oak trees، the effects of independent variable probability maps of dead standing oak trees for the future was produced.

Determination of land capability for optimal use of land to prevent land degradation and improper use of lands is an effective step towards sustainable development strategy. Regarding the importance of subject, in this study in first; ecological potential for usual land uses in Iran (forestry, ecotourism, agriculture, range management, residential areas development and conservation) in Babolrood basin was evaluated using Analytical Hierarchy Process (AHP) and Geographic Information System (GIS). Then land uses were ranked using MOLA technique and land use planning map of study area was created. The results showed that 59.49 percent of the area was allocated to forestry and 21.82, 17.73, 0.05, 0.106 and 0.804 percent of the area were allocated to ecotourism, agriculture, range management, residential areas development and conservation respectively.

Recognition equal units and segregation them and upshot planning per units most basic method for management forest units. Aim this study presentation and comparison classification and regression tree (CART) and random forest (RF) algorithm for forest type mapping using ASTER satellite data in district one didactic and research forest's darabkola. In start using inventory network 500* 350 m, take number 150 sample plat in over district. After accomplish Geometric correction and reduce atmospheric effect on image processing bands rationing, create general vegetation indices, principal component analysis and tesslatcap index. After extraction spectrum values relevant by sample plats fabric and processing bands, classification values other pixel accomplish using investigating algorithms. Evaluation accuracy results classification accomplish by some sample plat that not participate in process classification. The result showed preparation map using RF with overall accuracy 66% and kappa coefficient 0.57 than classification and regression tree with overall accuracy 58% and kappa coefficient 0.49 has superior accuracy. Totality result showed using above algorithm may increased accuracy forest type map.

Ecotourism is a purpose-built journey to nature for recognition of natural and cultural history of environment without changing and destruction of ecosystems and environment; and creation of economical activities which leads to proper utilization of environmental resources and job creation for local societies. Evaluating the capacity of Khorram-Abad county for ecotourism is essential for achieving sustainable development in the region. For evaluation of ecotourism capability of the region، by using the Analytic Network Process (ANP) and geographic information system (GIS)، firstly، according to the conditions of the study area and experts knowledge، five clusters including climate، morphologic، geo-pedometery، environmental and socio- economy were considered that any cluster has many sub-criteria. The relations between these clusters and sub-criteria were determined. For determining the relations among these clusters and sub-criteria، a number of questionnaires distributed among the experts and used to obtain their judgments about the relative importance of each criterion in ecotourism capability. At the next step، based on the limited super matrixes، the final weight of nodes was calculated. The weights of nodes in evaluating process were extracted by calculating the geometric mean of the questionnaire weights as well. After determining the weights of nodes، they were transformed to data layers. Finally، capability map for ecotourism was provided using WLC (Weight Linear Combination) technique in GIS. The results showed that 7. 65 and 32. 93 percentages of the study area have excellent and good conditions respectively and 6. 85 percentages of the study area doesn''t have any ecotourism capability.

Undoubtedly, Khorram-Abad Country has been considered as one of the most beautiful, scenic and pleasant weather areas of Iran because of many natural, cultural, historical, etc attractions. Despite the great potential for ecotourism development in this country, it has not been implemented a good plan for ecotourism development in this area. This study intends to identify the effective criteria and sub-criteria in ecotourism evaluation with respect to the area conditions and suggest the suitable areas for ecotourism development. For this regard Geographic Information System (GIS) and Analytical Hierarchy Process (AHP) have been used. At the first step, effective criteria and sub-criteria in the evaluation process determined and the weight of each criterion and sub-criterion determined using the Delphi technique and expert's knowledge. Then, the required maps were prepared. After that, with the integration of maps and their corresponding weights the capability map for ecotourism was prepared. The results showed that 7.80, 60.75, 46.37 and 5.50 percent of the study area has excellent, good, moderate and poor potential respectively and 2.35 percent of the area is not suitable for ecotourism at all.

To determine the amount of dead standing trees in Zagros forest, a forest area (96 ha) of Bioreh catchment in Malekshahi city in Ilam province was selected. A hundred percent or complete inventory in study area was conducted. The results showed that near to 70% of all trees were sprout-origin and about 30% were seed-origin. While Quercus brantii var persica (92.8 %) and Cerategus sp (5.5%) had the highest abundance, Amygdalus sp., had the lowest amount of abundance compared to other species in the study area. The results also showed that the total percentage of standing deadwood was 11.15% which West and South facing aspects had the highest and East and North facing aspects had the lowest ratios of standing deadwoods. Amygdalus sp., Acer cinerascense and Quercus persica species had the most ratios of standing dead trees while Cerateagus sp., and Pistacia atlantica species had the lowest ratios of standing deadwoods. With increasing in diameter classes, the standing dead trees were increasing in the study area so that the ratio of deadwood in the diameter classes 4 and 6 was less than 10 % while in the diameter classes 84, 88, 92 and 112 the ratio of deadwoods was about 35, 100, 37, and 75% respectively. Furthermore, the percentage of standing deadwoods among seed-origin trees was more than sprout- origin trees. Base on the results, the regional drought and precipitation deficit in the last years was the most important factor in causing standing deadwoods.

Recreation planning is not only as a tools for enhancing of socio-economy levels of the people but because of its conservational functions can provide a dynamic conditions for conservation of natural resources. With respect to this point that the first step in recreation planning like planning for any activity is the evaluation of land potential for that activity. The aim of this study was to evaluate the potential of ecotourism of Babolrood watershed in Mazandaran province by using of analytical hierarchy process (AHP) and geographical information system (GIS). For this regard، firstly the most important effective criteria and sub-criteria in evaluating of the potential for recreation in the study area were determined by using prior researches، conditions of study area and expert knowledge. After that، some questionnaires were provided and between different experts were distributed. The weight of criteria in each questionnaire was calculated and then the averaged weights were estimated. With applying of AHP method and Expert Choice software the final weight for each criteria and sub-criteria was determined. After that، the needed maps for this evaluation were provided in GIS environment. At the end، with help of Weighted Linear Combination (WLC) technique the final potential map for the ecotourism development of region was provided. The results showed that 19/33 percent of study area has a high potential and 52/81 percent has a good potential for ecotourism. In addition، 23/19 percent has an average potential، 1/84 percent has a weak potential and 2/82 percent is not suitable for recreation land use.