JOURNAL OF RANGELAND SCIENCE
Year:2016 | Volume:6 | Issue:4|Papers Count:8

According to the fundamental goal of remote sensing technology, the image classification of desired sensors can be introduced as the most important part of satellite image interpretation. There exist various algorithms in relation to the supervised land use classification that the most pertinent one should be determined. Therefore, this study has been conducted to determine the best and most suitable method of supervised classification for preparing the land use maps involving no grazing, heavy and moderate grazing rangelands, ploughed rangelands for harvesting licorice roots and dry land and fallow lands in Baft, Kerman province, Iran. After being assured of accuracy and lack of geometric and radiometric errors, the images of Landsat and ETM+sensors achieved on 3 July 2014 have been used. A variety of algorithms involving Mahalanobis distance, Minimum distance, Parallelepiped, Neural network, Binary encoding and Maximum likelihood was investigated based on field data which were obtained simultaneously. These algorithms were compared with respect to error matrix indices, Kappa coefficient, total accuracy, user accuracy and producer accuracy of maps using ENVI 4, 5. The results indicated that the Maximum likelihood algorithm with Kappa coefficient and total accuracy of map estimated as 0.969 and 97.77% were regarded as the best supervised classification algorithm in order to prepare the land use maps. Mahalanobis distance algorithm had a low ability for recognizing two types of dry land and fallow land uses concerning the extracted maps. According to the findings, various land use maps as rangelands under three grazing intensities and ploughed rangelands to harvest the licorice roots provided by the means of algorithms related to neural networks were not of sufficient accuracy. The highest Kappa coefficient of Neural network algorithms was estimated as 0.5 and attributed to the algorithm of multilayer perceptron neural network with the logistic activation function and one hidden layer.

Hydrological response of a watershed is a comprehensive symbol of environmental conditions and characteristics of the basin. Vegetation is one of the main factors in water resources status, erosion, and sediment of a watershed. Rangelands of Golestan province, Iran due to the geographical location, climate, and destruction of these resources as well as drastic land use changes from forests, and rangelands to agricultural lands have a high potential of run-off. Therefore, in the present study in order to determine the best management of the rangelands, we developed a rangeland improvement model using the Soil and Water Assessment Tool (SWAT) in the Gorganroud Watershed, Golestan, Iran. Calibration and validation of model were performed using Sequential Uncertainty Fitting Program (SUFI-2) in the eco-hydrological model of SWAT. Simulating the run-off in the studied hydrometric stations, the results showed that this model performed well for the study area (P-factor 0.6-0.9; R-factor 0.85-1.5). As well, four range improvement scenarios (mechanical, biological, biomechanical and livestock grazing management) were defined in this study. On average, by applying mechanical, biological, biomechanical, and grazing management scenarios, runoff was reduced to 13.5%, 11%, 20.7% and 12.5%, respectively in comparison with the actual runoff. According to the obtained results, the biomechanical scenario was identified as the best one in reducing the runoff and water conserve in poor and moderate rangelands.

One of the effective ways for reducing atmospheric CO2 is carbon sequestration by plants and soils. Rangelands with an expanded area have a great potential for Carbon (C) Stocks. In this study, C stocks in three treatments including natural rangelands (NR), Pit- seeding by Agropyrum elongatum (PS) and abandoned dry farming (ADF) were examined in Kardeh basin Mashhad, Iran in 2013. In each treatment, ten transects and in each transect, ten plots were established. Percentages of vegetation cover, litter, rock and soil were recorded in each plot. Aerial and root biomasses of dominant species were sampled by the clipping and weighing method. Litters in each plot were collected and weighed, too. Carbon content of biomass and litter were measured by combustion method using Electric Combustion Furnace. Ten soil samples were taken along each transect at two depths of 0-25 and 25-50 cm. The soil organic carbon percent was determined by the Walkley–Black method. Data analysis was performed by one-way analysis of variance (ANOVA) and means were compared using Duncan test. Results showed significant differences between treatments for total C stocks (soil+biomass+litter). NR and ADF management with the average values of 535.32 and 177.14 (t.ha-1) had the highest and lowest C stocks, respectively. Among the components of the ecosystem, soil had a main role in C sequestration followed by above biomass, roots and litters. PS management had the highest C stocks in plant biomass and litter but its soil C stocks were significantly lower than NR. Perennial grasses, bushes and perennial forbs were dominant in PS and NR management that play the most important role in plant C stocks. In conclusion, proper management of natural rangelands and more attention to vegetation and soil conservation may lead to store a considerable amount of C stocks in these lands.

Maharloo Lake is one of the salty lakes located in the southeast of Fars province, Iran. Presence of salt domes has a significant role in its salinity. Magnesium-sodium chloride and sodium sulfate are dominant salts of the lake. Due to the drying up of lake, widespread lands surrounding the area are exposed to secondary salinity. It seems necessary to investigate the changes to find salinity level in order to predict the changes of vegetation and its margin uses. The purpose of the study was to evaluate the spectral indices derived from the images of Landsat8 sensors in detection of salty levels of the Maharloo Lake. In this study, Landsat8 imagery was used to obtain salinity indicators in the salt lake. Fourteen salinity indices have been calculated using the ENVI. The results showed that the indices of BI, SI, SI1, SI2, SI3, VSSI, YSI and SR could detect the area covered by salt crust on the lake and then, isolate and separate it from the rest of reflection spectrum. However, MSI and NDBI indicators were unsuccessful in detection of salt crust. NDVI and COSRI indicators used in plant detection could not detect the salt crust and just identified the typical vegetation. Finally, I2 and NDSI indicators also partially with low accuracy succeeded to detect some salinity areas and had no satisfactory performance.

Plants produce thousands of primary and secondary metabolites including volatile compounds at various developmental stages throughout their life cycle during flowering, ripening, and maturation. Lavandin known for its volatile compounds is a small aromatic shrub cultivated worldwide for the essential oil. Lavandin essential oil composition is greatly influenced by the environmental and genetic factors. The essential oils from the leaves and flowers of the plant are widely used to enhance the flavor of foods as well as cosmetic and pharmaceutical industries. In order to study the environmental factors regarding the essential oil and antibacterial activity of Lavandin, four populations were collected (Jowkar, Khoramabad, Alashtar and Aligoodarz) in Lorestan province, Iran in May 2014. The hydro-distillated essential oil was analyzed using GC and GC/MS. Results indicated that there were significant differences among the various populations for the main constituents in the essential oils. Analyses revealed 32 compounds constituting 91.63–97.2% of the essential oils. The main constituents were 1, 8-cineole (44.8 to 31.64%), borneol (26.14 to 18.47%), and camphor (14 to 8.41%). According to the results, there was a significant correlation between borneol and altitude (r=−0.95). Antibacterial data were analyzed using one-way analysis of variance. The essential oils of Lavandin indicated good inhibitory activities against four bacteria, especially against Salmonella typhi with the inhibition zones of 19−23 mm. It was concluded that there was a high variation for the essential oil composition among the populations of Lavandin. In addition, the essential oil of Lavandula × intermedia has a good potential source of natural products for being used in food industry.

In dry lands, semi-circular bund has been considered as a management practice used to restore the ecological revival in terms of vegetation enrichment and soil amelioration. This study was conducted to investigate the effects of semi-circular bunds on vegetation cover and some soil properties in Koteh rangeland, Sistan and Baloochestan province, Iran (2014). Adjacent to the semi-circular bund area, a rangeland area without semi-circular bunds was selected as the control site. Vegetation sampling was done using 5×5 m2 plots and soil samples were taken from the depth of 0–30 cm. Vegetation and soil data were analyzed using T test. In total, 16 species from 7 families and 13 genera were observed. Results showed that semi-circular bunds exhibited more vegetation cover, plant production and density. The minimum values of production and vegetation coverwere related to the control site. The highest and lowest richness and diversity of species were measured in the semi-circular bunds area and the control site, respectively. The pH level was significantly higher in the soils of semi-circular bunds area as compared to the control site (P<0.05). However, the level of soil EC followed an opposite pattern. Results showed that the amounts of organic carbon, nitrogen, potassium, phosphorus and calcium carbonate increased significantly in the semi-circular bunds as compared to the control site (P<0.05). The semi-circular bunds area had more amounts of clay and silt and the least values were measured in the control site. In total, the results of the study showed that building the semi-circular bund had positive effects on vegetation cover and soil properties in the rangelands of study area.

The vegetation cover and rangeland production are the most important factors to determine the proper planning system for effective utilization and management of rangelands. In this research, the effect of climatic factors (temperature and rainfall) were studied on vegetation cover and forage production of four species (Festuca ovina, Bromus tomentellus, Dactylis glomerata and Agropyron trichophorum) during 2002-2006 and in 2013 in a semi-steppe area in Polur rangeland, Mazandaran Province, Iran. The climatic factors were annual rainfall, growing season rainfall, growing season plus previous year rainfall, growing season rainfall of March, annual mean temperature and growing season temperature. For this purpose, some plots with a systematic distribution were selected. The vegetation cover and forage production were measured. The relationships between vegetation indices and climatic factors were assessed for each species using stepwise regression. The results demonstrated that the plant species had responded to rainfall and temperature fluctuations. However, the responses were different in various species. Among the important climatic factors, the growing season rainfall of March was the most effective index for B. tomentellus and A. trichophorum vegetation cover and forage production as well as on D. glomerata vegetation cover. The forage production of F ovina was influenced by the growing season plus the previous year rainfall. According to the results, the forage production and vegetation cover of these grass species could be estimated based on rainfall data. Therefore, with the knowledge of the effects of rainfall year fluctuations on vegetation indices over a long period, it is possible to make the necessary predictions for optimizing the management of rangelands.

Strong benefits of species diversity have been demonstrated in mixed cropping on rangelands. In order to determine the best composition of mixed cropping of alfalfa (Medicago sativa) with three cool season grass species (Agropyron elongatum, Agropyron desertorum and Festuca arundinacea), on yield and quality traits, an experiment was conducted during two years (2009 and 2010) in Bojnourd, Iran. The used experimental design was a split plot based on randomized complete block design with three replications. Main factor was different compositions of alfalfa and grasses and sub factor were two intercropping methods (Mixed intercropping and Row intercropping). Dry matter (DM) yield, Land Equivalent Ratio (LER) and quality traits including Crude Protein (CP), Water Soluble Carbohydrates (WSC), Dry Matter Digestibility (DMD) and Acid Detergent Fiber (ADF) were determined. Results showed that the effects of treatments were significant for all of traits. The highest DM yield was obtained in mixed intercropping ratio of alfalfa 25%+A.elongatum 75% (2317 kg.ha-1) that increased 23.3% compared with alfalfa monoculture treatment. The effects of cropping method were significant for all of traits. The highest CP was obtained by mixed intercropping of alfalfa 75%+Festuca 25% (14.51%). In conclusion, mixed intercropping of alfalfa and Festuca arundinacea produced moderate DM yield coupled with higher quality traits. Whereas, mixed intercropping of alfalfa and A. elongatum produced highest DM yield but lower forage quality.