Ali Mirhosseini; Younes Asri; Mohammad Abolghasemi
Volume 27, Issue 2 , June 2020, , Pages 192-203
Abstract
The Bahadoran Kalmand protected area with an area of 255000 hectares is located at about 30 km Yazd township and in the southeastern township of Mehriz with geographical coordinates of 31° 00¢ to 31° 40¢ North latitude and 54° 15¢ to 55° 20¢ East longitude. The ...
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The Bahadoran Kalmand protected area with an area of 255000 hectares is located at about 30 km Yazd township and in the southeastern township of Mehriz with geographical coordinates of 31° 00¢ to 31° 40¢ North latitude and 54° 15¢ to 55° 20¢ East longitude. The vegetation cover was studied using the physiognomic-floristic method. Some soil characteristics were evaluated based on conventional methods and data were analyzed by Principal Component Analysis (PCA) method. The results showed that there was a special relationship between different plant communities and soil characteristics. The most important factors in separating these plant communities were electrical conductivity, acidity, texture, organic carbon, and sodium adsorption ratio. In general, in regard to habitat conditions, each plant community has different ecological needs and tolerance range with environmental factors and soil characteristics.
Mojtaba Pakparvar; Morteza Abtahi
Volume 8, Issue 4 , September 2019, , Pages 93-122
Jalil Farzadmehr; Hamed Sangooni; Hamid Rouhani
Volume 26, Issue 1 , June 2019, , Pages 18-28
Abstract
In order to investigate the relationship between the distribution of plant communities and environmental factors in Bidokht area, a physiognomic-floristic approach was used. The appropriate area of sampling plot and sample size were determined by the minimal area method and statistical ...
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In order to investigate the relationship between the distribution of plant communities and environmental factors in Bidokht area, a physiognomic-floristic approach was used. The appropriate area of sampling plot and sample size were determined by the minimal area method and statistical approach, respectively. In each plot, the number of plant species and their canopy cover were determined and vegetation mapping was conducted. In each of the plant communities, six soil profiles were drilled and soil samples (composite) were taken from 0 to 100 cm depth. After transferring to the laboratory, parameters of soil texture, lime, pH, electrical conductivity, organic matter, sulfate, calcium, phosphorus, potassium and nitrogen were measured. Information layers were also provided for altitude, slope and aspect of the study area. In order to determine the factors influencing vegetation distribution, PCA-ORD software was used to analyze the principal components (PCA). The results showed that there was a relationship between the factors studied and distribution of vegetation (four rangeland types). The results of principal component analysis showed that the most important environmental characteristics affecting distribution of plant communities in the region were clay, sand, organic matter, electrical conductivity, and potassium (PCA first axis).
Mohsen Yousefi; leila kashi zenouzi
Volume 22, Issue 2 , August 2015, , Pages 240-250
Abstract
The aim of this study was to determine some factors affecting dust storms phenomenon using different methods. In order to determine the best-input combination, variable reduction techniques such as factor analysis (maximum likelihood, principal component analysis), Gama test, and multivariate forward ...
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The aim of this study was to determine some factors affecting dust storms phenomenon using different methods. In order to determine the best-input combination, variable reduction techniques such as factor analysis (maximum likelihood, principal component analysis), Gama test, and multivariate forward regression analysis were used. Each of these methods presented different combinations used by feedforward neural network model, with Levenberg–Marquardt algorithm and multivariate forward regression with R²=0.87 and RMSE=0.04 was selected as the best suitable combination of neural network model. In addition, monthly and seasonal data were applied by neural network using the best-input combination, and the simulation of dust storm phenomenon was done in summer and spring during the months of April, May, June, July, August and September with a higher correlation coefficient and lower mean square error, due to the good distribution of the dust storm data. The results showed that based on these methods used in this study, dominant wind speed, horizontal visibility, continuity and average of wind speed were the most important factors affecting dust storm phenomenon in Yazd province.
Reza Yari; Hosein Azarnivand; Mohammad Ali Zare Chahouki; Jalil Farzadmehr; Firoozeh Moghimi Nejad
Volume 21, Issue 2 , August 2014, , Pages 247-259
Abstract
This research was aimed to evaluate the environmental factors affecting the distribution of vegetation in Sarchah Amari ranglands, Birjand. After field visits, five vegetation types were selected based on physiognomy method and soil and vegetation sampling was done in key area of each vegetation ...
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This research was aimed to evaluate the environmental factors affecting the distribution of vegetation in Sarchah Amari ranglands, Birjand. After field visits, five vegetation types were selected based on physiognomy method and soil and vegetation sampling was done in key area of each vegetation type along the transect and within square plots with systematic-random method. Depending on the type and distribution of plant species, the plot size was calculated to be 1.3 and 16 m2 and 45 plots were established in each vegetation type along transects. The percentage of vegetation cover was measured in all plots but soil sampling was done in the first and last plots of each transect at soil depths of 0-30 and 30-80 cm. Soil characteristics including soil texture, percentage of lime, saturated moisture, gypsum, pH, electrical conductivity, sodium, calcium, potassium, magnesium, chlorine and topographic features including slope, aspect and altitude above sea level were measured. Soil and vegetation data were analyzed by PCA and ANOVA. The results of PCA showed that among the environmental factors, EC, the percentage of sand, slope, gypsum, organic matter and the soluble sodium were the most important environmental factors affecting the distribution of vegetation. Overall, these factors could explain 89.73% of the vegetation distribution. The results of ordination (PCA) showed that 70.74% and 18.63% of vegetation distribution were explained by the first and second axes, respectively. The first axis variables included the percentage of sand, electrical conductivity (EC), percentage of gypsum, sodium and the organic matter of first depth. According to the algebraic sign of variables, the distribution of vegetation was positively correlated with the percentage of sand while it showed a negative correlation with electrical conductivity (EC), gypsum, sodium and organic matter in first depth. The second axis variables of the ordination diagram included the percentage of slope and organic matter of second depth and according to the algebraic sign of variables, the distribution of vegetation had a negative correlation with the percentage of slope and soil organic matter of second depth.
Reza Yari; Hosean Azarnivand; Mahammad ali Zare Chahouki; Jalil Farzadmehr
Volume 19, Issue 1 , June 2012, , Pages 95-107
Abstract
In this study, the relationship between species diversity and environmental factors in the pastures in the Sarchah Amari ranglands of Birjand was investigate. For this purpose, after classification of vegetation types through physiognomy method, sampling from vegetation and environmental factors were ...
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In this study, the relationship between species diversity and environmental factors in the pastures in the Sarchah Amari ranglands of Birjand was investigate. For this purpose, after classification of vegetation types through physiognomy method, sampling from vegetation and environmental factors were accomplished in the key area of each vegetation type by random-systematic sampling. Plot size and the number of plots were respectively determined by minimal area and statistical methods. Afterward, in the key area of each vegetation type, three 300 m transects were established and 15 plots with 20 m intervals were located along each transect. Sampling of vegetation was carried out in all plots while soil samples were taken at the beginning and end of each transect from two depths of 0-30 and 30-80 cm. The list of plant species and canopy cover percentage were recorded in each plot. Percentage of soil gravel, clay, silt, sand, moisture saturation, pH, lime, organic matter, gypsum, electrical conductivity and soluble salts (sodium, potassium, chloride and magnesium) and topographic features (slope, aspect and altitude) were measured. For data analysis, species richness and evenness were calculated using different diversity indices (Simpson and Shannon -Wiener index of heterogeneity, Kamargov and Smith- Wilson as the homogeneity index). To determine the most important factors influencing variations of species diversity, principal components analysis was used. The results showed that electrical conductivity, gypsum, organic matter, slope, and sand were the most effective factors on diversity in the study area.
Asghar Farajollahi; Mohammad ali Zare Chahouki; Hosein Azarnivand; Reza Yari; BahraM Gholinejad
Volume 19, Issue 1 , June 2012, , Pages 108-119
Abstract
In this study, the relationship between environmental factors and distribution of plant communities in rangelands of Bijar protected region was investigated. Vegetation types were determined by using physiononmy method. Plot size was determined with minimal area method and after primary sampling the ...
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In this study, the relationship between environmental factors and distribution of plant communities in rangelands of Bijar protected region was investigated. Vegetation types were determined by using physiononmy method. Plot size was determined with minimal area method and after primary sampling the number of plots was determined by statistical method. In each vegetation type, sampling was done along four transects of 300 m length. 15 plots of 1m2 were established along each transect at 20 meter intervals. The type and the amount of existing species and the percentage of vegetation cover were determined in each plot. In each community, 6 profiles were dug within sampling unit. Soil samples were taken from 0-20 and 20-100 cm according to the boundary of separated horizons and type of existing plant species in study area. physiographic features including altitude, slope and aspect were measured and among soil properties, clay, silt, sand, lime, pH, EC, organic mater and gravel were measured. After collecting data, the Principal Component Analysis (PCA) was used to determine relationship between vegetation cover and environmental factors by PC-ORD software. The results indicated that there were relationships between measured factors and distribution of vegetation. Texture, gravel, lime, altitude and slope had the most influence on distribution of plant communities.
Asghar Kohandel; Hossein Arzani; Morteza Hosseini Tavassol
Volume 17, Issue 4 , November 2011, , Pages 518-526
Abstract
Different grazing intensities change the chemical and physical properties of soil and plant composition of rangelands. Accordingly, effect of livestock grazing intensities on soil and vegetation characteristics were investigated in the southeastern of Hashtgerd using Principal Component Analysis. Principal ...
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Different grazing intensities change the chemical and physical properties of soil and plant composition of rangelands. Accordingly, effect of livestock grazing intensities on soil and vegetation characteristics were investigated in the southeastern of Hashtgerd using Principal Component Analysis. Principal Component Analysis is a statistical method for defining new variables based on a linear combination of original variables. Three 5-ha areas were selected in the study area under treatments of no, moderate, high and continuous grazing intensities. Afterward, vegetation and important physical and chemical soil characteristics including moisture, specific gravity, soil porosity, infiltration, mechanical resistance, nitrogen, phosphor, potassium, pH, EC, soil texture and organic matter were measured in three grazing treatments for two years (2004 and 2005). According to the results, increase of grazing intensity increased forbs while grasses and shrubs decreased. Among soil properities, soil porosity and Mechanical resistance decreasid and pH, EC and K had the highest relationship with grazing intensity.
Farhad Zolfaghari; Ahmad Pahlevanravi; Akbar Fakhireh; Mitra Jabari
Volume 17, Issue 3 , October 2010, , Pages 431-444
Abstract
Agh Toghe basin is in the central part of Marave Tapeh located in the east of Golestan province. In this research, study area was investigated based on Braun-Blanquet to identify plant communities. Afterward, relationship between environmental factors particularly slope, elevation, vegetation cover and ...
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Agh Toghe basin is in the central part of Marave Tapeh located in the east of Golestan province. In this research, study area was investigated based on Braun-Blanquet to identify plant communities. Afterward, relationship between environmental factors particularly slope, elevation, vegetation cover and soil properties including sand, silt, clay, acidity, electrical conductivity, and organic matter were determined using Principal Component Analysis (PCA). .Data collecting was carried out through establishing 103 quadrates based upon minimal area method in different vegetation types. A matrix of vegetation and soil characteristics was prepared and ordination was applied by PCA. The results showed that the most important factors in separation of vegetation types were as follows: elevation, slope, carbon percentage, sand, silt, clay and acidity.
Saleh Arekhi; yaghoub Niyazi
Volume 17, Issue 1 , September 2010, , Pages 74-93
Abstract
Presently, unplanned changes of land use have become a major problem. Most land use changes occur without a clear and logical planning with little attention to their environment impacts.Since that landuse change occurring over large areas, remote sensing technology is an essential and useful tool for ...
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Presently, unplanned changes of land use have become a major problem. Most land use changes occur without a clear and logical planning with little attention to their environment impacts.Since that landuse change occurring over large areas, remote sensing technology is an essential and useful tool for landuse change detection. In this study,after applying geometric and radiometric correction on landsat images of TM(1988) and ETM+(2001) ,five techniques of change detection have been used in 80470 hectare in the region of Daresher,Ilam province. These change detection techniques included Image regression, NDVI differencing, Principal component analysis (PCA(, Tasselled cap (KT) and post-classification comparison. In all these techniques, following standarizing maps,change direction has been determined.The accuracy of the results obtained by each technique was evaluated by comparison with post-classification method through Kappa coefficient calculation. According to the results, NDVI differencing and PC2 differencing showed the largest accuracy with Kappa coefficients of 0.667 and 0.655, respectively.However, Different change detection algorithms have their own merits and no single approach is optimal and applicable to all cases. In practice, several change detection techniques should be used to implement change detection, whose results are then compared to identify the best approach through visual or quantitative assessment.
Kian Nadjafi–Tireh–Shabankareh; Adel Jalili; Nemat.. Khorasani; Ziba Jam zad; Uones Asri
Volume 15, Issue 2 , January 2008, , Pages 179-199
Abstract
The Genu Protected Area encompasses Kuh–e–Genu, a single and isolated mountain rising above the Persian Gulf Coastal plain. The Genu Protected Area is located in Hormozgan province, 30 km north west of BandarAbbas between latitudes (27°18′50″-27°29′16″ ...
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The Genu Protected Area encompasses Kuh–e–Genu, a single and isolated mountain rising above the Persian Gulf Coastal plain. The Genu Protected Area is located in Hormozgan province, 30 km north west of BandarAbbas between latitudes (27°18′50″-27°29′16″ N) and longitudes (55° 57′30″-56°18′4″E), at about 70 to 2347m above sea level. It covers an area of about43000 hectares. The main aim of this research is to identify relationship between plant associations and environmental factors. In this investigation the relationship between environmental factors and establishment and expansion of plant associations was carried out. The each plant association, 38 ecological factors including different soil characteristics such as soil texture, lime, saturation moisture, gypsum, acidity, electrical conductivity, soluble ions (Na+, K+, N, P, Mg2+, Ca2+, CL-, CO32-, HCO3- , SO42-) in two depth, elevation and slope of habitat were determined too. Multivariate method (Principal component analysis) was used to analyze the collected data. A matrix of vegetation and environmental factors was prepared and the ordination was done by the PCA using PC-ORD software. The results show that the measured environmental variables affected the plant association distribution pattern. The most important factors that have influenced plant associations separation are as follows: electrical conductivity, elevation, moisture saturation, organic matter, lime, K+, Na+, SO42-, Ca2+, CL-, Mg2+ and slope of habitat, respectively. The multivariate analysis expression, the effects of the complicated environmental variables on the plants in a simpler way and introduce the most important factors. As a general, each plant association depends on habitat conditions, ecological needs and tolerance shows a significant relation with environmental factors especially some soil properties.
Ammar Rafiei Emam; Kazem Alavi panah
Volume 13, Issue 1 , February 2006, , Pages 1-9
Abstract
Remote sensing plays a considerable role on detection of natural resources features by its multi spectral means. Three decades works of remote sensing scientists have resulted in presentation of several vegetation indices, for soil how ever there are not many examples. TM spectral ratioing have been ...
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Remote sensing plays a considerable role on detection of natural resources features by its multi spectral means. Three decades works of remote sensing scientists have resulted in presentation of several vegetation indices, for soil how ever there are not many examples. TM spectral ratioing have been employed in this study to overcome problem of detection of soil variation. To reach the point spectral ratioing of TM (18 May 1998) was used. Data used in this study were: a) 3 first principle component, b) spectral ratioing of reflectance bands, c) spectral ratioing of Thermal band and d) original bands of TM. Results show that distinction of different soil in possible by PC3 on the basis of soil moisture variation. So, more researches in various regions for more studies in this subject are advised.