فهرست مطالب bahman jabbarian amiri

The forests of the Caspian region are one of the most important forest resources in Iran, but what is seen as a large gap in research is the need to pay attention to the structural dimensions, especially to maintain the structural connectivity of these forests. The aim of this study was to assess and compare the indicators of forest landscape in the Caspian Sea watersheds. At first, the forest layer was extracted from the land cover map and 25 large watersheds were selected to study and compare the connectivity indicators. The connectivity of the terrestrial landscape was analyzed using landscaping metrics and graph theory indicators, by Fragstats and Conefor softwares respectively. Finally, by standardizing the calculated connectivity indicators, a final connectivity score was obtained for each watershed. The results showed that the indicators of forest patches connectivity in the whole Caspian catchment are very low, so that 80% of the watersheds are in the category of very low and low connectivity. Watershed 9 (Sardabroud, Shalmnroud) and 7 (Chalous) are in a very unfavorable situation, and only two watersheds of 14 (Chalav, Panjab) and 4 (Pasikhan), in the area of Chalav and Punjab, in the Haraz River, and the Shakharz, Pesikhan rivers, are in a better situation in terms of connectivity indicators. Considering the importance of preserving the structure and connectivity of forest patches, the results of this study show the need for special attention to the management and restoration programs of these forests.

In the present study, in order to model the environmental impacts using landscape metrics; Guilan province was divided into 183 impact unit, and the Land Degradation Model was applied. In the next step, using the measures of (Related circumscribing circle, Perimeter-area ratio, Shape index, Fractal dimension index & Contiguity index) which were calculated by Fragststs, five models were developed based on stepwise modeling approach. Following from that, Akaike information criterion was applied to determine the most appropriate model. The results of this study showed that 39.78% of Guilan province is located in sensitive and susceptible areas. The highest physiological density was observed in Siahkal county. Regression models indicated that the amount of environmental degradation can be predicted using the weighted average of measures related to the landscape structure metrics: rcc (r2 = 0.437, p ≤ 0.05), contig (r2 = 0.615, p ≤ 0.05), frac (r2 = 0.505, p ≤ 0.05), shp (r2 = 0.499, p ≤ 0.05) and (r2 = 0.672, p ≤ 0.05). The most appropriate model, which was determined by AIC, was the model for the Perimeter-area ratio, and it had a good model validation result. Our findings revealed that applying the landscape metrics would be able to use for assessing the environmental impacts. In turn, it would decrease the degree of subjectivity in the landscape degradation model, as well. On the other hand, the use of landscape metrics, which can be easily and quickly calculated through land use or land cover maps, will greatly eliminate the need for extensive field work. Accordingly, using land degradation model will be more easily implemented in a much shorter time and at a lower cost to evaluate the environmental impacts.

Due to the negative effects of built up area temperature on energy consumption and human welfare, it is important to mitigate these negative effects by controlling the spatial pattern of green cover and its cooling effect. Therefore, in order to reveal the type and shape of relationship between landscape spatial patterns with land surface temperature (LST) in Rasht, the statistical modeling approach and landscape metrics were used. Land use- land cover and LST mapping were performed using Landsat sensor imagery classification and finally calculated landscape metrics of entered into the modeling process. Validation results showed that although all four linear, logarithmic, exponential and power regression models have good performance in predicting LST through land cover metrics, the highest performance was related to power model. In addition, this models indicate LST is strongly correlated with near distance to green patch and near distance to water patch metrics.

Planning and selection suitable industrial zones locations for safe and sustainable use of land are as the basis for land use planning and approach to sustainable development. Therefore, considering these location and geographical positions with environmental characterize that determine distribution and regional balance and maximum use of environment capabilities could mitigate degradation impact of industries on environment. In this study, to assess conformity of industrial in Ardabil province, Fuzzy Multi Criteria Decision Making model and to improve development and land use planning, 16 criteria such as topography, slope, residential areas, road access, airport access, surface water, groundwater deep, current land use, geology, fault, vegetation, electrical facilities, soil, protected areas, distance from wells, vegetation density was used. FDANP hybrid model developed to locate areas of industrial in Ardabil province. The modeling results indicate importance of river criteria and then land use in industrial areas. Verify conformity of current industries in region with suitable area in Ardabil province indicates that only 3 percent of areas in region are matched on land use planning and spatial planning approach and 97 percent in areas are in unsuitable for industrial development. Therefore, the principles of land use planning and sustainable development be considered in industrial planning on region in future to proper operation of optimal space and reduce impact agents on environmental, until the most optimal mode of all environmental, economic social and sustainable development be ensured.

Land degradation modeling is one of the environmental impact assessment methods that quantitatively represent the effects of human activities. The purpose of applying this model is identifying vulnerability factors and destruction of ecosystems, to prevent further destruction by other project and also to show feasibility of future development to decision markers.

first The study area was partitioned into 94 cells, 1600 ha each and then Fourteen degradation factors were identified along with their intensity using land use map, field observations and expert views. So the determination of ecological susceptibility and physiological density was determined and all cells were classified to 4 categories: recommended for development, zones that require reconstruction, protection and cells hadn't development potential based on fuzzy theory.

The results show that from 94 cells, 22 cells (23.40% of the total area) require reconstruction, 37 cells (39.36% of total area) have no development potential, and 35 cells (37.22% of total area) are recommended for development. 

The effects of destructive activities (which are mainly destructive effects of tourism activities) in the region are obvious, so that destructive activities such as land use change and river pollution to the region on the one hand. They are the main causes of destruction of the 94 cell, 21 cell due to faults and 16 cell due to being in the Binalood protected area, have no development potential. 35 cell are recommended for development in first to third priorities, these cells are in low physiological density area and 22 cell due to high physiological density and severity destructive agents has a high degradation coefficient and need to be reconstructed, and therefore any future development in this area, should be excluded.

Land use/ land cover of watersheds has great impacts on water quality of rivers. The water quality of rivers can be degraded due to changes in the land use/land cover patterns within watersheds as human activities increase. In this study, to determine the relationship between te impacts, which are induced by change in land use/ land cover on water quality, the relationship between land use and water quality variables has been examined. The effects of land use/land cover changes were investigated in different buffer zones. Using geographic information system (GIS) and spatial analysis, 39 watersheds were selected within the southern Caspian Sea Sub-basin, and then the relationship between water quality variables and land use/ land cover classes, in different river buffer zones varying between 30 to 120 meters with 30 m incremental intervals, were examined by Spearman correlation test and multiple linear regression. Due to the fact that two or more independent variables may affect the dependent variable, multiple regression modeling approach was used. The results showed that integrated land use data in intermediate areas could provide the most reliable model for predicting chlorine (R2 = 0.813) and sodium (R2 = 0.77). In addition, in riparian areas with 30 meter, SAR, K, Na, Cl, pH, EC, TDS, Mg, Ca, HCO3 variables had the highest correlation coefficient with their surrounding land use/land cover.

Land degradation modeling is one of the environmental impact assessment methods that quantitatively represents the effects of human activities. The purpose of applying this model is to identify the destruction factors and susceptibility degree in ecosystems in order to prevent further destruction by other projects and to show the feasibility of future development to decision markers. The study area was firstly partitioned into 94 cells (1600 ha) and then 14 degradation factors along with their intensity were identified using land use map, field observations and expert views. Ecological susceptibility and physiological density were then determined and all cells were classified into four categories as recommended for development, required for reconstruction, required for protection and cells with no development potential based on fuzzy theory. The results show that 22 cells (23.40% of the total area) out of 94 cells require reconstruction, 37 cells (39.36% of total area) have no development potential, and 35 cells (37.22% of total area) are recommended for development.  The effects of destructive activities in this region (that is mainly due to the detrimental effects of tourism activities) were evident, so that the destructive activities such as change in land use and land cover, on the one hand, and waste and rivers pollution, on the other hand, were found as the main causes of destruction in the region. Out of 94 cells, 21 cells and 16 cells had no development potential due to faults and due to being in Binalood protected area respectively. 35 cells are recommended for development in first to third priorities; these cells are in low physiological density area. 22 cells, due to high physiological density and severity of the destructive agents, have a high degradation coefficient and need to be reconstructed, and therefore should be excluded from any future development.

Rainfall-runoff hydrological models are important tools in water resources projects. Generally, performance of this group of models is dependent on the proper selection of parameters. Accordingly, several methods have been developed to estimate hydrological parameters. The present study aimed to compare the performance of conceptual hydrologic models such as TANK, SIMHYD and AWBM which benefit from the indirect model parameters estimation approach in discharge simulation of Babolroud watershed, Mazandaran province, Iran. The automatic calibration process of these models was designed using genetic evolutionary search algorithm and objective functions (NSE and RMSE) as error thresholds determinants. Hence, meteorological and hydrological data consist of temperature, evapotranspiration, precipitation and discharge (in daily scale) were gathered from authorities. Input data was also divided into warm-up, train and test steps after preliminary validation and recovery. Based on the results, NSE metric introduced TANK model as the best simulator respectively for train and test step (0.59 to 0.72). Depends on RMSE metric, SIMHYD (0.83) and TANK (0.15) models were introduced as the best simulator respectively for train and test step either. According to the catchment flow signatures, general simulation of low-flow (excluding the Model TANK), mean-flow and high-flow were conducted with acceptable agreement. While simulation of the flow duration curve slope which represents an intensity of changes (excluding TANK model in train step), did not provide acceptable results. Given the weaknesses and strengths of the proposed models, they can be used as an acceptable simulator in water resources management especially in terms of ungauged basins, after preliminary verification in different climatic conditions.

The aim of this study is to determine the status of forest spatial disturbance in Golestan National Park using remote sensing and landscape metrics. Detailed forest/non-forest map was prepared by on-screen digitizing method using Landsat 8 data. After determining the optimal area of gridding, the studied area was divided into 550 hexagonal zones with the area of 100 hectares each one. Spatial distribution, connectivity and composition of non-forest patches in each zone were measured using 12 spatial metrics (MESH, NP, PD, ENN-MN, LPI, FRAC-MN, CONTIG_MN, SPLIT, AREA-MN, DIVISION, PLAND and SHAPE-MN). After standardization of metrics values, principal component analysis was also performed in order to determine the effective metrics in disturbance and their associate weight in the spatial disturbance model. Afterwards, based on the prepared model, the disturbance index map was prepared and classified in four classes of disturbance including 1) without disturbance, 2) low disturbance 3) medium disturbance and 4) high disturbance. The results showed that the mentioned classes cover 48.53, 16.15, 19.90 and 15.41 percentage of the studied area, respectively. With the approach that used in this study, the disturbances map of the under management forest areas can be prepared periodically and used as one of its monitoring tools.

Modeling of the relationship between physical characteristics of a catchment and water quality parameters plays a significant role in unified watershed management. In addition, in the process of modeling there is always an inevitable level of uncertainty caused by error in the input data, parameters and the structure of the model. Therefore, quantifying the uncertainty in the output of the model in order to reach certain forecasts in modeling is essential. In this research, water quality data, land use/cover, land suitability map and geological map of hydrometric stations located in the western part of the Caspian Sea were used. The modeling was done using Multiple Linear Regression Stepwise Method, while the model uncertainty analysis was examined using Monte Carlo simulation. Based on the results of the correlation and regression analyses, it could be concluded that all these parameters have a strong positive correlation with a variety of human activities such as agriculture and urban development. This indicated that an increase in agricultural land or a decline in forest areas will ultimately lead to a decline in water quality. The results of the Monte Carlo simulation shows that although some models have high R-squared values, the possibility of generation of negative outputs (Pr

Mining activities and associated metal smelting industries with massive soil displacement and the manipulation of natural ecosystems have Great effects on their surroundings, including the accumulation of heavy metals in the soil. Due to the transfer of metals from the plant as the first ecosystem food chain the amount of bioavailability of metals and their accumulation in plants is important to control and manage pollution in these areas. In this study, the concentration of soluble elements in soil and plant around the Khotun Abad copper smelter (Al, As, Ba, Cr, Cu, Fe, Mg, Mn, Mo, Ni, Pb, Rb, S, Si, Sr, Zn), And the accumulation and transfer of these elements in the plant Astragalus sp. was investigated, Using transfer factor. Analysis of variance (ANOVA) was performed on mean concentrations of metals followed by Duncan’s multiple range test. Correlation of elements with Pearson correlation coefficient was investigated. The results showed that the highest metal concentrations were Mn and Fe concentrations in the stem (2324.72 and 2024.30 mg / kg respectively). Both nickel and chromium had the lowest concentration in the soil, which was not detectable. Based on the data obtained, the average concentrations of soluble elements in the analyzed soil samples were: S>Mg>Si>Al>Sr>Mn>Cu>Zn> Pb>Fe>Rb>As> Ba> Mo Also, the average concentration of Al, As, Ba, Cr, Mn, Mo, Cu, S and Sr in the root> stem> soil And the mean concentration of Fe, Mg, Ni, Pb, Rb, Si, Zn in the root> root of stem. The elements of Zn, Si, Rb, Pb, Ni, Mg, Fe and Ba with a transfer factor have more than 1 have ability to transfer from root to stem and accumulate in the aerial parts of Astragalus sp. The highest and lowest transfer factors were respectively Si (2.11 mg / kg) and Al (0.38 mg / kg) respectively. Also, there is a strong correlation coefficient (P value

To meet flow requirement of streams, it is necessary to allocate some part of stream flow to own stream, aiming to ensure stability of aquatic life. The underlying reason for it is that utilizing the ecosystems and ecological services such as water supply of streams should not endanger their ecological potential in having a sustainable life. The main objectives of environmental flows for all major rivers and streams applying three rainfall-runoff modeling, hydrologic approach, and indicators hydrologic alteration, and comparing the find outs. Base flow approach is based on the idea that the driest month-mean flow is sufficient for aquatic life except the aquatic life needs additional flow for their spawning and reproduction. To conduct the base flow approach, tank model, has been applied. In flow duration method, flow data of a given river or stream is analyzed in order to estimate the discharge value relate the stream flow amount to the percentage probability that the daily flow will be exceeded over a long-term base period without regard to the sequence of the flow events. Findings of the present study suggest that in this catchment tank model results are reliable, as their Nash-sutcliff criteria measure higher than 0.5. The results indicated that according to the environmental flow estimation of Flow duration curve method, environmental flows is 0.191 m3/s in the study area.

Growth and development of tourism, create economic, social, cultural and environmental impact in the host environment. Tourism in Torghabeh –Shandiz county due to the proximity to the metropolis in the city of Mashhad, benefiting from favorable weather and a beautiful landscape and pristine, in recent years has been growing strongly. So this study examines the consequences of tourism development has been done in this city that for this purpose degradation model was used. First the study area was partitioned into 94 cells, 1600 ha each and then Fourteen degradation factors were identified along with their intensity using land use map, field observations and expert views. So the determination of ecological susceptibility and Physiological density was determined and al cells were classified 3 categories: recommended for development, zones that require reconstruction, and cells hadn't development potential based on fuzzy theory.
So that destructive activity such as change and shed waste and rivers pollution in the region, are the main causes of destruction. Of the 94 cell, 21 cell due to faults and 16 cell due to being in the Binalood protected area, have no development potential. 46 cell are recommended for development in first to third priorities, these cells are in low physiological density area and 11 cell due to high physiological density and severity destructive agents has a high degradation coefficient and need to be reconstructed, and therefore any future development in this area, should be excluded.

Development impact assessments before decision making and projects implementing and development plan, leads to identification, prediction, reduction or offset the negative effects of the projects. Quality of impact assessment reports can assist to make a better decision about environmental issues and impact assessment effectiveness. For review of the reports on European countries is used the "Lee N & Colley" method .This method has four level or general sections which each of the sections is divided to some categories and subcategories. In this article "Lee N & Colley" method has been used for reports assessment. In Iran, to evaluation the quality of impact assessment reports has been considered six sections. In this research, 50 reports from different provinces and various projects including linear and polygonal were evaluated by experts. The results showed that quality of 76% from assessments reports was favorable and satisfactory (very good, good, and fair). Description of Project had the highest percentage of satisfaction about 84 %. Monitoring of the environment and management had the lowest quality and satisfaction. Therefore with assessment of different parts of impact assessments reports, you can recognize their strengths and weaknesses and in the future In the future, impact assessments carried out more carefully and effectively.

Lack of sufficient attention to animal and plant species that are within the scope of projects, can cause irreparable consequences. Impacts of development on the environment through impact assessment report, an important way to maintain the survival of these valuable biological resources. One of the important sectors in the procurement process and environmental assessment projects, studies of wildlife. Therefore, this study aimed to determine the quality of the studies to identify weaknesses and problem wildlife impact assessment reports have been investigated. This study selected 50 reports since 1376 until 1390 during the period of 15 years the environmental assessment process based on the method of Lee and Colley (1992) to determine the quality of life studies conducted in the evaluation reports. The criteria are set at different levels in various parts of the assessment reports and the hierarchy is evaluated. In this study for discussing wildlife 7 sections are determined and the quality of wildlife in 50 assessment reports in four levels is evaluated. According to the results, 36 % of reports in studies of wildlife have good quality, 52% average quality and 7% are poor and very poor in quality.

Climatological parameters are among the most important ecological capability evaluation criterias, on other hand, climate changes which has intensified in the past decades and has the consequences such as; increases in climatic threshold phenomena like occurrence of horrific floodings, destructive hurricanes, abnormal and sudden colds and heats, untimely rainfalls and heavy snows, widespread droughts and etc., has shown the necessity of studding the impacts of climate change on various parts of economy and social more than before. But due to low spatial and temporal resolution of global climate models, regional experts must increase the resolution of this model's data using downscaling methods. This study has evaluated the power and precision of LARS-WG model in climatic data generating and future climate forecasting for Guilan province of Iran. Accordingly the daily data collected from synoptic stations in Guilan, with a minimum of 15 years of daily data, between 1995 to 2009 has been used. The parameters used included; rainfall, minimum temperature, maximum temperature and solar radiation. The results show that, the highest calculated value of Mean Absolute Error (MAE) for rainfall modeled data was 14.48 in Astara station, and the highest bias calculated value for rainfall parameter was -4.35 and in Astara station too. The model precision for modeling the minimum and maximum temperature was desired for modeling this parameters, and the highest MAE and bias values for minimum temperature were 0.17 and 0.065 in sequence and both in Anzali station. Also, the highest MAE and bias calculated values of maximum temperature were 0.26 and 0.23 in sequence and both in Rasht station. And in LARS-WG precision in modeling the solar radiation parameter, the Rasht station had the highest calculated MAE and bias values, with the amount of 0.31 and 0.08 in sequence. Results analysis show that the LARS-WG model, has the proper power and precision for climate modeling and data generating in Guilan province of Iran.

Human activities due to implementation of projects has caused significant concerns on biodiversity in human societies. Hence, assessing the environmental impacts of those projects has been considered as a tool to help environmental managers to prevent emergence of those adverse impacts in general and those impacts which are related to biodiversity, in particular. It is provided that all components of the environment including biodiversityto be considered and integrated into environmental impact assessment process properly.
The present study revealed that Iranian environmental impact assessment guidelines, which has been ratified in 1994 suffers lack of sufficient and effective approach in integrating biodiversity, as has been stated in UN Biodiversity Convention, in its environmental impact assessment process.
In our study, we have applied a quantitative evaluation approach to investigate the quality of 50 environmental impact statements out of more than 1171 which have been ratified by Iran Environmental Protection Agency standpoint of biodiversity. Having analyzed sample-based data, binomial test has been applied for deducting population-based inferences relying on our sampling-based data.
Findings of the present study have indicated that biodiversity-related concerns are properly not addressed in more than half of the environmental impact statements at significance level of 95%. Accordingly, more attention on the biodiversity-related concerns should be paid by EIA practitioners considering the significance of biodiversity in general and wildlife in particular in our national environmental impact assessment system.

Development of remote sensing (RS) and GIS techniques and that of landscape metrics in the late 1980s have caused to introduce a new dimension in the landscape ecology arena (the relationship between spatial patterns and ecological processes). However, scale dependence of some of landscape metrics and RS systems of different spatial resolution has resulted in particular attention into selection of an appropriate scale in the landscape ecology studies and correct interpretation of ecological processes. Hence, the present study has investigated the behaviors of some landscape metrics in relation to changes in scale. Accordingly, the effects of the scale (pixel size and extent) on those landscape metrics which indicate trends of vegetation cover class was discussed applying Landsat images in Isfahan city and its surrounding (an area of ​​960 thousand hectares). For this purpose, behavior of NP, PD, LSI, MPS, ED, MNN, MSI and TCAI have studied through changing the size from 30 m to 60, 120, 240 and 480 and extent from 300 ha to 600, 1200, 2400 and 4800. The results of this study indicated sensitivity of these metrics except TCAI in relation to the scale factor. This type of studies and attention to the spatial scale have indicated that it could play an important role in identifying the impacts of ecological processes, predicting the ecological functions (landscape modeling) and reducing the uncertainty in landscape ecology studies.

This study is designed، aiming to detect changes in the composition and configuration of landscape in Rasht township between 1989 and 2011. It has been conducted applying synoptic analysis. Hence، landscape maps have been generated from three TM satellite images at 1987، 1999 and 2011 applying hybrid classification method. Some composition and configuration-based metrics including NP، PD، LSI، LPI، SHDI، CONTAG، ED and PLAND were then calculated at two class and landscape levels and their changes is detected. The results indicated that، in general، the landscape has been more fragmented، more complex and irregular in shape، more disconnected in continuity of patches and more diversified in the term of land use/ land cover types. It was in spite of the differences between trend and gradient of changes in Rasht county landscape at two period of time (1987- 1999 and 1999- 2011). Moreover، the results revealed that sprawl of the manmade areas have caused increase in fragmentation، irregularity and complexity of agriculture patches and decrease in total area of agriculture class. Hence، an intense degradation of ecosystems might be resulted if the current trend continues in future in the study area.

Recent experiences on disregarding the environment and continuous development have caused human to conclude that the only way to protect nature in long-term is to pay attention to environmental abilities and limitations. One of the most actions taken in this regard in management and development planning is to determine ecosystem vulnerabilities. In this way، by identifying vulnerable and sensitive areas، one will be able to prevent developments beyond the ecological abilities. Torghabeh-Shandiz Township is one of the regions in Razavi Khorasan province that was under constant developments such as buildings، establishing new residential complexes (apartments and villas) during the recent years، mostly for tourism. The objective of this study is to determine and to classify the ecological vulnerability in this area using the “objective method”. For this، the region was transformed into 94 cells، 1600 ha each، and the vulnerability and classification of each cell were calculated based on different environmental gradients such as: slope، aspect، elevation، soil depth، vegetation density، climate، and geology. The results show that 19. 21% of the total area was vulnerable، 53. 35% sensitive، 18. 4 % susceptible، and 9. 28% of it was classified in resistant category

Urban growth has been an important social and economic phenomenon that affects severely on function of ecological systems. Hence، understanding and analyzing the spatial patterns of urban growth using remote sensing، GIS and landscape metrics can play a fundamental role in urban land use management and planning and subsequently reduction in environmental problems and challenges among them. Therefore، in present study we examined urban growth in Sari city and its surrounding. For this purpose، satellite images of 1992، 1998، 2002 and 2009 of the study area was processed to generate land use\ cover maps. Accordingly، different types of urban growth have been quantified using post classification method (map overlay)، applying a set of landscape metrics at class level including PD، MPS، ED، LPI and ENN and developing R metric at patch level applying ArcGIS 9. 3. The results show that، urban development is associated with the growth of old patches in the study area. While the outlying growth type became the dominant pattern، the infilling growth decreased over the entire study period.

Livestock predation by wolf is one of the most frequent sources of conflict between human and wildlife and one of the reasons for species extinction throughout the world. Recent documented reports about the wolf attacks on livestock in Hamedan province is an example of the occurrence of such conflicts. This study aimed to identify risky areas for wolves’ attacks on livestock and determination of environmental factors affecting these conflicts with maximum entropy modeling method using MAXENT software. The results showed that the most important factor is land use variable in study area. In making of map of high-risk areas، livestock density and distance from the river other effective factors are as well. According to obtained predictions، Bahar and Kaboodarahang are facing with the highest possibility of wolf attacks. Results of this study could be use as a useful tool for implementation of conservation activities for mitigation of wolf-livestock conflicts in high risk areas of Hamedan province.

Sensitive coastal areas are fragile ecosystems affected by geographic features and in the same time settlements were developed around these areas due to their ecological capability. Coastal ecosystems due to their countless benefits are very important for protection. Hence، this paper attempts to determine the sensitivity of coastal ecosystem to disturbances in Hormozgan Province. We reviewed 22 international and national studies to notice identification criteria for determination the coastal sensitive areas. We used 6 criteria and 29 indicators to select these regions. Exclusiveness and wilderness were the most important coefficients while industrial dependency had the lowest priority among the indicators. Moreover، 10 ecosystems were studied to determine importance and priority of sensitivity of ecosystems in the study area in shore and coastal zone. According to the results، mangroves in seashore besides protected coastal area are of the most important sensitive regions. Zoning of sensitive ecosystems shows that the most extent areas are the least sensitive ones in the coastal zone. Few areas are in the highly sensitive in the vicinity of Bandarlenge city. 6. 96% of Very high sensitive parts are in southwest of Bandarlenge city that overlap with Seraj and Harra Protected Areas.

Deforestation in the past decades has risen. So، the proper development of human activities in forests requires the environmental limitations to be considered during forests management process. One of the appropriate measures is the determination of ecological vulnerability. In the present study، Patom District of Kheyrud Forest was classified based on the ecological sustainability، using Object- Oriented Vulnerability Method. The results showed that 26% of the study area is located in middle sensitive class، 46% in sensitive class and 28% in very sensitive class. Overall، we infer that Patom District of Kheyrud Forest has the high ecological vulnerability that it should be considered by forest managers.

Fire destroys major area of forests and rangelands in the world. Izhe، located in Khozestan province، is one of these area that was changed by this natural phenomena. The aim of this study is to determine the most important climatic factors on forest fire and its development by regression model analysis. Numbers and area of the forest fire as well as weather data for a three years period (2009-2011) were applied for this value. The results of Spearman correlation test showed that minimum and maximum temperature had a positive correlation with the burn area of the forests. The minimum and Mean of relative moisture suggested a negative correlation with forest fires. Moreover، the maximum and medium of temperature had positive correlation with forest fires.