سحر حیدری مستعلی

In this research, the continuity of land landscape was analyzed from the perspective of land landscape metrics (10 indicators) and graph theory indicators (12 indicators). First the correlation between correlation indices and water quality parameters was performed using Spearman and Pearson correlation coefficient and then with the help of stepwise linear regression method and through power, exponential and logarithmic regression models and using Akaike coefficient, the best model was chosen. The results showed that there was a significant negative correlation with water quality parameters between the land quality measures of CONIG and FRAC and the length of the corridor and most of the continuity indices of graph theory. Also, the highest coefficient of explanation or R2 belonged to CO3 models with a coefficient of explanation of 0.818, water flow with a coefficient of explanation of 0.733, Ca with a coefficient of explanation of 0.772 and TDS with a coefficient of explanation of 0.704. Almost all selected models are nonlinear models. Significant correlation of land feature continuity indicators, especially graph theory continuity indicators and corridor length with water quality indicators, shows the effect of structural features of land landscape on water quality in watersheds.

The arid and semi-arid areas in the south of Varamin city are one of the areas that are prioritized for the implementation of tourism development and conservation programs due to soil erosion conditions, excess livestock grazing and destruction of pastures and vegetation. Therefore, the purpose of this research is a comprehensive evaluation of the ecological conditions to evaluate the environmental potential of recreation in this area. For this purpose, first, soil and vegetation samples were taken from sample plots from all three areas of Dolat Abad, Shokar Abad and Fakhr Abad in Varamin, and the required data and maps were prepared. Soil samples were collected and important soil parameters were determined in each sample and maps of these parameters were prepared. Then, the evaluation of the environmental potential of tourism was done by the method of intersecting ecological maps. For this purpose, the mapping of ecological factors, including slope, aspect, height, density of vegetation, precipitation, and temperature, as well as soil texture, was done. They were classified and coded according to the degree of desirability for wide recreation and then superimposed, and finally, the 1st and 2nd grade capacity classes and the unfavorable classes were created from the combination of these layers. In terms of totality and summation of ecological factors affecting the potential of tourism, Shakarabad region has more potential than the other two regions of Fakhrabad and Daulatabad. In general, what has caused the difference and superiority of tourism in Shakarabad region compared with the other two regions is the soil factor, which has caused the development of tourism in Shakarabad region to be higher than the other two regions. Another important factor is the land use and the proximity of this area to the desert protected area, which itself provides a high potential in the Shakarabad region for the development of outdoor recreation. The results of this research showed that by combining the multi-criteria evaluation method and the geographic information system and considering all the ecological factors, the real potential of outdoor recreation in forest areas and reserves can be determined.

Biodiversity is an important structural feature of dynamic and complex forest ecosystems. One of the most challenging and important issues in assessing the structure of forest ecosystems is understanding the relationship between biodiversity and environmental factors. Hyrcanian Forests are considered a biodiversity hotspot in the world and have special and unique features that have led to an emphasis and importance of biodiversity conservation in these forests. The aim of this study was to investigate the effect of biotic and abiotic factors on the diversity and richness of tree species in Hyrcanian Forests from the west of Gilan province to the east of Golestan province. For this purpose, using 655 fixed sample plots (0.1 hectare), the diversity of trees in 3 provinces in the northern Iran from east to west of the Caspian Sea was analyzed. A combination of non-parametric models including random forest (RF) and support vector machine (SVM) and linear regression models were used to investigate the relationship between tree diversity and biotic and abiotic factors. Biotic and abiotic variables included the number of trees per hectare, diameter, respectively. Basal area (BA), Basal Area in Largest tree (BAL), slope, aspect and elevation. Evaluation statistics including the coefficient of determination, RMSE and percentage RMSE error showed that the random forest model was the best model to determine the relationship between biodiversity and environmental factors and has suitable accuracy for determining biodiversity changes in the northern forests of Iran.

Urban green space has a very important role in the sustainability of the city. Green space per capita is one of the main factors to planning and management of a city. In this study, green space per capita estimation of Khomein city was investigated.

Satellite imagery was used to measure green space and parks per capita. For this purpose, using Sentinel-2 imagery, land use map was developed in four classes including: Bare lands, habitat, urban parks and farmlands. The urban park layer was extracted and combined to the four district of Khomein city layer. Then, the green space per capita of each area was calculated.

Green space per capita survey using remote sensing approach shows a severe shortage of urban green space in this city, especially zone 3 in the southeast of the city with 1.66 m2 per capita, meanwhile, this zone had the lowest value among all zones. In this city, green space has an inappropriate distribution and the highest green space per capita value was 3.43 in zone 1. Zones 2 and 4 had an average of 3.22 and 3.27 m2, respectively.

the results show that the green space per capita of the city is very low compared to the standards and requires special attention of decision makers to increase and expand the green space in the city. So in the near future, a comprehensive analysis of the green space and the reasons for this shortage should be addressed.

Lack of up-to-date, documented and scientific information on the current situation (area and distribution) of Zanjan poplar plantation is one of the main problems of wood production managers for planning and management of wood supply in the province and the country. In this study, Sentinel-2 satellite data with spatial resolution of 10 m in spectral bands were used and the ground truth map of existing poplar fields with 600 points was plotted in all cities and villages from field surveys. From the beginning to the end of the poplar growing season (first half of March to December 2018), at least 6 time periods of 30 to 40 days were used in the SVM classifier. Post-test and calibration of SVM model based on the phenology of poplar genus and field samples were extracted, populated area distribution map of province was extracted. The results showed that the total area of ​​poplar areas is 2744 hectares which covers 0.12% of total area of ​​Zanjan province. One percent of the total polygons were randomly selected for field control and after field control, the overall mapping error was obtained and calculated. In this study, the exact location and area of ​​poplar mills were estimated with acceptable accuracy (96%). So that using extracted information (distribution map of poplars of the province) can provide studies on comprehensive planning of poplars and sustainable management of wood production from the poplars of the province.

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.

Determining and comparing biodiversity in different forest communities is important for accurate identification and forest management. The purpose of this study is an investigation the status of tree species diversity in three forest areas: Gorazbon district of Noushahr Kheyrod forest, Ashkateh Chal of Sefarood Ramsar forest and Haft Khal Neka forest. Species diversity of fixed plots was calculated by Margalf and Manhink (as species richness index), Simson and Shannon-Wiener (as heterogenity index), and Pielou and Hip (as evenness indices) indices. In all of 10R fixed plots, the DBH of alive trees was recorded. Statistically comparisons were done by one-way ANOVA and Duncan test. The results showed that all indices have significant differences at confidence level of 95%. The maximum and minimum of species richness were seen at Kheyroud and Neka forest, respectively. Also, Simpson and Shannon Wiener diversity indices are also maximum at the Kheyroud and minimum in the Neka forest. Ramsar forest has the most uniformity, then Kheyroud forest. The results show that the status of woody species diversity in Kheyroud forest is better than other forest areas in this study. The Neka forest, specially, has poor condition in terms of biodiversity indicators.

Proper distribution of urban green space is one of the most important issues in urban planning and especially in management of urban green space. In other words, the physical expansion of cities destroys surrounding natural environments and arable lands. It also results in fundamental changes in ecological structure and functionof urban landscape, along with gradual changesin spatial structure and patterns of this landscape (Wang et al., 2008). Since ecosystem processes depends on its structure, landscape metrics have been accepted as a very useful tool for expressing the structure of urban green space and its human-causedchanges (Hessburg et al., 2013).There has always been discussion onacceptable per capita green space or changes in green space over time and place. Iranian cities are no exception in this regard, thougheven a city enjoying a high ratio of green space per capita may still lack enough green space per capita in some districts. This suggests the necessity of investigating various measures and avoiding studies limited to per capita green space and urban forestry. (Botequilha and Ahren, 2002). If as an ecological structure,green space is proportional to populationcomposition and distribution, ecological performance and land use type of an urban area, it can have important ecological functions. Since most studies on urban green space have primarily focused onfinding a proper location, calculating appropriate per capita green space and introducing suitable species for green space, investigatingthe spatial distribution of urban green spaceseems to be of great importance. Therefore, the present study seeks to investigate the spatial pattern and distribution of public green space in Khomein using a landscape approach.

Study area The study area, Khomein, is bounded by agricultural lands and gardens in its northeast, west, and partly in its south. Only the main area of urban texture is located on barren lands (Abbasi et al., 1986). The study area includes four districts of Khomeinin which the pattern of green space distribution isinvestigated. Methods Sentinel-2 images were used in the present study. Satellite images were processed and then, their geographical effects were extracted inthe first step of classification. Different indices were defined for each patch of the image and using supervised method, images were classified into four classes of agricultural lands, barren lands, urban parks and residential areas in accordance with the training data. Visual method was used to improve classification results. In this method, classification results are matched with the imagesand possible errors are rectified. Google Earth was used to evaluate the accuracy of results obtained from classification of satellite images. In the next step,the base map of the present study was produced and then, the layer containing urban parkswas integrated with the layers prepared for four districts of Khomein. It should be noted that the present study focuses on urban parks prepared by the municipality for public use and does not include other urban green spaceareas such as the green belt or private gardens, etc. To study the spatial distribution of green space, measures of land cover were calculated and analyzed in each of the four districts. Geographic Information System (GIS) and Landscape Measurement Analysis Program (FRAGSTATS) were among the tools used to calculate and measure landusein the present study. Landscape metrics used in the present study included: Landscape Shape Index (LSI) which measures the area of ​​the largest patch in a class divided by the total area of ​​that landscape (multiplied by 100 to convert to percent) Euclidean Nearest Neighbor distance (ENN) which is the average distance between patches in a class. Meter is used as the standard unit of measurement for this index. Perimeter /Area Ratio (PARA) which is the ratio of the perimeter of ​​the patch (m) to its area (m2). This measure lacks a specific unit and for PARA> 0 it is without a limit. Number of Patches (NP) equals the number of patchesof the corresponding patch type (class). Shape Index:sum of patches’ perimeter divided by the square root of the area of ​​the patch (ha) for each class (class surface) or the entire patch (land surface). This index iscalculated for circle standard (polygon), or square standard (grid) and divided by the number of patches. Largest Patch Index (LPI) which measures the area of ​​the largest patch in a class divided by the total area of ​​the landscape (multiplied by 100 to convert to percent) Mean Patch Size (MPS) which measures the average size of a patchin the landscape.  

District 3 ranked highest and district 1 ranked lowest in ENN indexindicating that ​​urban green space patches in this district were closer together, while green space patches in the third district were limited and far apart from each other. Regarding LPI index, the second district ranked thehighest and the third district ranked the lowest indicating that the largest urban parks in this districtwere much smaller than other districts. Other district had a relatively acceptable statusin this respect. In MPS index, district 2 with 697 patches ranked highest and district 1 with ​​564 patches ranked lowest indicating that average green space patches in district 1 were smaller. This was also confirmed by maps prepared based on other metrics.Regarding the LSI index, district 1 ranked highest and district 2 ranked lowest, while districts 3 and 4 had a similar status in this measure. The first district had the highest number of patches (NP), while the third district had the lowest NP. The highestPARA ratio was observed in District 1, and the lowestin District 4, while districts 3 and 2 ranked near the middle. In Landscape shape index which increases with the heterogeneity of patches,district 1 (with 13.12) ranked highest and District 3(6.64) ranked lowestwhiledistricts 2 and 4 ranked near the middle.This indicates the heterogeneous shape of green space patches in district 1, while showing that patches of green space in district 3 are very simple and homogeneous.Finally it should be noted that calculating landscape metrics for the four districts ofKhomein indicated a very low per capita green space in this city and also absence of a proper and equitable spatial distribution.  

Calculatinglandscape metrics in the four districts of Khomeinindicated thatcompared to other districts, district 1, located in the southern part of the city, has a more desirable status in indices such as PARA, LSI, NP, and ENN. At the same time, district 3, located in the southeastern part of the city, has the least appropriate status regarding these metrics indicating the necessity of a comprehensive analysis of green space areas in this district in near future. Urban managers and planners need to focus on this district and its green space, and if possible find appropriate sites for future green space areas in this district.Although the status of districts 2 and 4, located in the west and north of the cityrespectively, were not very desirable, theyranked higher than districts 3in NP, LPI, and MPS. Using GIS in combination with satellite imagery, and land use metrics provided an innovative way to study the gradual spatial changes in urban green space. Results of landscape metrics analysis indicated an unbalanced distribution of land use in the four urban districts in this study.

In this research, which was done in Ramsar forests in Mazandaran province, the forest increment was estimated using artificial neural network and compared with the actual increment of the forest which was directly measured in 20 sample plots of 1 hectare in 2002 and 2012. The annual volume growth of beech was 4.52 and 4.35 m3 in hectare for direct inventory and estimation by artificial neural networks. Then regression analysis was performed to compare the results, stepwise, and the best models were selected. After selecting the best model for forecasting growth, the sensitivity analysis of inputs was investigated.The results showed that the neural network with relatively good accuracy can estimate the annual growth and cutting. The value of R2, RMSE and MAE were 0.75, 17 and 13.6 (for 20 sample plot of one hectare) respectively in the multi-layer perceptron network. Results also showed that the MLP neural network had the highest accuracy in predicting and estimation. In the analysis of multiple linear regression, the coefficients of detection were 0.610 and 0.679, respectively, and RMSE was 1.5 and 1.42, respectively, for the first and second models respectively. The volume at the beginning of the period and the diameter at breast height had the greatest impact on the amount of wood produced. Comparison of the models showed the use of neural network can predict the growth rate with proper accuracy.

Understanding the ecological niche of the different species is essential in many ecological issues.  Ecological niches of species are one of the important factors in the tree species distribution pattern and for all species, it can be detected by examining distribution of species distribution. Ecological nest models often help to understand more ecosystems. These models are applicable in predicting ecosystem stability and sustainability ratios and ecosystems.

In order to determine the selective pressure of different species, the indicators of the equilibrium level of selected nests, the dominant level of selected nests and the crisis level of selected nests were used and 41.5 hectares of Khirud research and educational forest were fully surveyed (100%). Then, characteristics such as diameter equal to the chest of the trees were measured and using selective nesting indices, the selected pressure and nesting levels of beech, oak, hornbeam and alder species were measured.

The values of the selective pressure were measured for the species on the Fagus orientalis 66.419, Quercus persica 3. 313, Carpinus orientalis 261. 28, Alnus 36. 962 and tilia begonifolia 9. 39 respectively. The final results showed that Carpinus orientalis wasat a Dominates niche level, the Fagus orientalis and Alnus was in the balance niche level and the Quercus persica was in intermediate between balance and critical level and also tilia begonifolia was in the critical niche levels.

The Carpinus species were at the dominant level of selective pressure, the Tilla species were at the equilibrium level and the Quercus species were at the equilibrium level of the crisis nest. The results of this study showed that selective strain quantification is an important factor in determining the current status of endangered species.

There are important species of beech and hornbeam In the Hyrcanian forests. Due to the economic and ecological importance of beech as well as the frequency of mixed beech-sufficient information about the structure and the level of beech and hornbeam and their associated species which will be used by Forest managers. Also in this study, for the first time in the study area, correlation analysis and regression analysis between biodiversity indices and independent environmental variables were performed which are essential steps in forest planning and management.

For this purpose, the indices of biodiversity (Shannon Weiner and Simpson Index) were measured individually in each habitat and then they were compared with each other. In addition, the correlation and regression of these indices with 16 eco-physiographic factors Including seasonal light, average air temperature, high altitude from the nearest drained point, topographic shafts, relative humidity, wind speed, reflection and radiation levels representing the environmental conditions of the region was obtained. Among them, only four factors had a significant correlation with biodiversity index. These factors are air temperature near the surface of the Earth, topographic wetness index, wind speed, and total solar radiation energy in each habitat. Also, t-test was performed to investigate the significant differences between biodiversity indices between the two habitats.

The results showed that both Biodiversity indices were higher in Hornbeam habitat than Rash habitat. The correlation coefficient of the environmental variables mentioned in the Shannon diversity index in each habitat indicated that the correlation coefficients of the variables with the variability index in the hornbeam habitat were higher than the rash except for the correlation coefficient related to the total solar energy variation in the Beech habitat which was higher than beech, with a negative slope indicating the nature of the friendliest shade of beech species compared to hornbeam.

the higher Shannon species diversity and Simpson uniformity index in beech habitat, confirms the tendency for this species to be mixed with its non-homogeneous trees and high competition at this stage of the sequence in beech habitat. In fact, the mass distribution of beech is a factor in the high competition and, consequently, a low index of uniformity. The results of this study showed that biodiversity indices were higher in hornbeam than in beech, which could be due to various reasons. In fact, determining biodiversity indices in forest communities firstly and then, examining and determining environmental factors affecting the biodiversity of tree species, as well as comparing important forest habitats and communities from the perspective of these factors for management purposes. Forests are important and essential.

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.

The main pre-request of the forest management and planning program is the availability of quantitative and qualitative data from forest structure. Therefore, the forest inventory plays a vital role in the estimation of the current status and future planning. In this study, spatial pattern of trees in Gorazbon section of Kheyroud forest in northern Iran was simulated to compare the random systematic sampling and complete random systematic sampling method based on the full calipering method. By using the Arc GIS software, the spatial pattern of forest trees was simulated. Buffer function was used to calculate the random systematic sampling and complete random systematic sampling method based on the full calipering method. In order to compare random systematic sampling with full calipering single-sample, a t-test was used. The results showed that there was no significant difference between random systematic sampling and full calipering method to estimate the average diameter of Alnus, Fagus orientalis, and Tilia begonifolia. However, there was a significant difference between two methods in the estimation of average diameter of Carpinus orientalis and Quercus persica. The results of T-test revealed that there is no significant difference between Alnus and Tilia begonifolia but significant difference was observed between the trees of the Fagus orientalis, Carpinus orientalis, and Quercus persica. In addition, paired t-test was used to compare the random systematic sampling and complete random systematic sampling method. Results showed that there is no significant difference between random systematic sampling and complete random systematic sampling method.

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.

Hyrcania is a highly productive forest along the southern coast of the Caspian Sea (northern Iran). The forests are mostly uneven-aged, oriental beech (Fagus orientalis)-dominated hardwood mixtures. These forests often include the presence of Carpinus betulus, Alnus subcurdate, Acer velutinum, and several other tree species and shrubs. These forests are mostly broadleaved, but Taxus bacata and Cupressus spp. do appear on some specialized sites. These forests are home to about 80 different tree species and 50 shrub species. Hyrcanian forests have multiple ecological functions, such as provide for (i) the production of wood fiber and lumber, (ii) the protection of watersheds, including their water and soils, and (iii) the conservation of biodiversity.
The topic of biodiversity has become a primary focal point in deliberations of sustainability worldwide, as a result of the rampant decline and degradation of natural environments initiated by urbanization, unrestrained resource extraction, and wanton disregard for nature. Furthermore, global climate change broadens our need to incorporate significant amounts of knowledge on biodiversity and functionality in developing contemporary forest management plans, which is not always easy to achieve. In this chapter, we develop a computational framework that relates measures of tree diversity (based on actual field surveys) to modelled physical (abiotic) variables. Here, we calculate tree diversity using the Shannon-Weiner index; an index commonly used to characterize species diversity in plant communities by accounting for both species abundance and evenness.
The plot network in the Gorazbon section is designed on a rectangular grid (150 m × 200 m) and consists of 258 fixed-area circular plots of 0.1 ha each .Tree species richness was determined at each plot from basic tree species identification and tallying. Prominent tree species in plots include Fagus orientalis, Carpinus betulus, Acer velutinum, Acer campestre, Alnus subcordata, Quercus castaneifolia, Parrotia persica, Tillia begonifolia, and Ulmus glabra. Total number of plots available for the current analysis was 202; many of the unused plots had missing site information, including GPS (global positioning system) coordinates, preventing their geo-referencing.
Development of numerical surfaces
Fundamental to the spatial calculation of abiotic surfaces or their surrogates at mid-resolution is the DTM of the Gorazbon section. DTM-height data is derived from the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) 30-m resolution Global Digital Elevation Model v. 2 (GDEM; http://asterweb.jpl.nasa.gov/gdem.asp, last accessed on June 2014). Descriptions of the various abiotic and associated surfaces, including their proxies and their derivation, can be found in Table 1. Values of abiotic and proxy variables at forest-plot locations were summarised separately as averages of values falling within each individual 0.1-ha plot (Fig. 1b).
Relating plot-estimates of environmental variables to
Symbolic regression, or symbolic function identification, is used to determine from the list of independent variables in Table 1, which site variables are particularly crucial in explaining spatial variability in . Symbolic regression is a procedure founded on evolutionary computation in searching for algebraic equations, while reducing the difference between target values and values calculated with the equations generated with the procedure .Different from conventional regression techniques that determine parameters of known equations, no specific mathematical expression is needed as a starting point to the approach. Rather, primary expressions are formed by randomly combining primitive base functions of input variables (linear or otherwise) with algebraic operators. Equations retained by the procedure are those that replicate the target output data better than others; undesirable solutions are rejected. The procedure stops whenever the desired accuracy in data replication has been reached. In order to balance the relative contribution of each plot-estimate of in the development of a generalised expression of , -values were weighted as a function of the inverse of their occurrence (i.e., number of times it occurs) in the dataset. This was done to ensure that values that are not commonly observed (e.g., = 7 species per 0.1 ha plot) contribute as much to the explanation of as values that are more frequently observed (e.g., = 2-4 species per 0.1 ha plot).
This research examines the possible ecological controls on tree diversity in an unmanaged region of the Hyrcanian forests (i.e., the Kheyrud experimental forest). Key to the study are computer-generated abiotic surfaces and associated plot estimates of (i) growing-season-cumulated cloud-free solar radiation, (ii) seasonal air temperature, (iii) topographic wetness index (TWI) in representing soil water distribution, and (iv) wind velocity generated from simulation of fluid-flow dynamics in complex terrain (Fig. 1).
Fig. 1. Model-generated abiotic surfaces of (a) growing-season cumulated cloud-free solar radiation (MJ m-2), (b) mean seasonal air temperature (oC), (c) topographic wetness index (TWI; unitless), and (d) wind velocity within the study area (m s-1).
Plot-level estimates (Fig. 2) are used in the generation of a three-variable equation (eq. 1) of tree diversity by means of symbolic regression (Schmidt and Lipson, 2009):(1)
where W is the wind velocity (m s-1), S annually-cumulated cloud-free solar radiation (MJ m-2), and T mean annual air temperature near the ground surface (oC). In the regression process, diversity values are weighted according to TWI. Fig. 2. Spatial variation in plot-level estimates of tree species diversity; size of the circles coincides with level of species diversity based on a calculation of the Shannon-Weiner index; the large circles coincide with high index values (high species diversity with an upper value of 1.6), whereas small circles coincide to low values (low species diversity with a lower value of 0.1).
Localised topographic wetness index (TWI) is shown to be unimportant with explaining spatial patterns in tree diversity. The approach shows that plot-level estimates of W, S, and T in combination can explain roughly 70% of the spatial variation in tree diversity in the validation data (Fig. 3). Fig. 3. Plot-level estimates of the Shannon-Weiner index (blue circles) compared to modelled values (red line).
Concluding Remarks
The chapter develops the methodology, the results, and discussion regarding the research.
Reference
Schmidt, M., and Lipson, H. 2009. Distilling free-form natural laws from experimental data. Science, 324(5923): 81-85.

Monitoring forest structure, to understand many issues in ecology and forest management is essential. In general, the term "structure" emphasizes the combination of tree communities in terms of specific characteristics. Monitoring forest structure is essential for understanding many issues in ecology and forest management. Today, many indicators have been developed for assessing the position and biodiversity of the trees, which simplifies the structural analysis of the forest. The use of these indices in constant sample units facilitates population dynamics studies over time and makes it possible to monitor the diversity of the location, dimensions, diversity of trees and height of the trees. Due to the smallness of these indicators and the possibility of comparing a mass at two different times, these indicators are a useful tool for achieving sustainable forest management. Combination indexes, uniform angles, diameters and altitudes are among the most important indices in the analysis of forest spatial structure in static studies. These indicators are preferable to other methods because of their simplicity in calculations and balancing accuracy. In this research, using a randomized random method, a rectangular grid of 200 * 150 * meters was used to identify the Gorazbon of Kheyroud forest in the city of Noshahr. Then, in order to study the structure of the forest species (beech, oak, hornbeam, alder, apple, lambs, lambs, almonds, and durum wheat) over a period of ten years, the uniform angle index, Ming-Ling blending, close The largest neighbor and the index of differentiation of diameter and height of trees were used. According to The results, Average indexes uniform angle index, mixing Ming Ling, nearest neighbor and the diameter and height dominate the index, in the first period and the end of the monitoring period was calculated) 0/598 and 0/525, 0/582 and 5/645 and 5/35, 0/762 and 0/720, 0/5521 and 0/591 respectively This represents a cluster random distribution pattern, an optimal mix of diversity and high density and the average dispute between the diameter and height of neighboring trees then the reference tree. In order to compare species diversity, location, and size, paired t-test was used. Paired t-test results showed that there is no significant difference between these indices before and after the period of monitoring (ie, the ten-year period). Also, the results of t-pair test for each species were proved, that there is a significant difference between the indices of differentiation of hornbeam tree before and after the observation. But there was no significant difference between the other species before and after the observation. This is due to the dominance of hornbeam trees in neighboring trees

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.

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