علوم مراتع
سال:1392 | دوره: | شماره: |تعداد مقالات:8

Rangelands are important for plant productivity, livestock production, wildlife, conservation of soil and water resources, and etc. One of the main problem of rangeland is that has not been used based on its potential that leads to more degradation of rangelands. The purpose of this study was to evaluate the range management capability of Badreh region in Ilam province, Iran, using ANP (Analytic Network Process) and GIS (Geographic Information Systems) techniques. For this regard, firstly, the network of effective factors in evaluation was designed. Four clusters including vegetation cover, topography, pedology, and geology were divided into number of sub-criteria. For determining the relations among these clusters and sub-criteria, a number of questionnaires distributed among the experts and used to obtain their judgments about the relative importance of each criterion in rangeland capability. In the next step, based on the limited super matrixes the final weight of nodes was calculated. The weights of nodes in evaluating process were extracted by calculating the geometric mean of the questionnaire weights, as well. After determining the weights of nodes, they were transformed to data layers. Finally, ecological capability map for range management was provided using WLC (Weight Linear Combination) technique in GIS. The results showed that 3.00, 21.76, 58.46, 16.79 percent of the study area had very good (or excellent) condition (as first class), good condition (second class), fair condition (third class), and poor condition (fourth class) for capability of range management, respectively.

One of the influential tools concerning the rangeland and vegetation sciences is the technology of remote sensing and satellite data. Satellite data have played essential roles in preparing the needed information for studying the vegetation. Vegetation has been widely recognized as one of the best indicators for determining the land conditions. Using vegetation indices is one of the techniques of remote sensing to study the vegetation. The purpose of this research is to study the vegetation indices and also provide an appropriate mathematical model for estimating the vegetation fraction using the mentioned indicators. In this research, different vegetation indices were calculated by Landsat TM (2006) satellite images in order to evaluate their capability to estimate the vegetation in the arid regions. At the outset, vegetation fraction was measured using the sample quadrates and then the measured data were compared with the values of digital numbers for the site pixels. Multiple regression analysis was utilized for the actual values and parameters to select the validation and optimization models. Indices which have been calculated include MSR, DVI, TRVI, SARVI, SR, RDVI, DVI, NDVI, SAVI, ARVI and MSAVI. The results showed that the model in which ARVI was used had the highest accuracy (R2=0.86) and therefore, it was chosen as the most suitable model for the estimation of vegetation fraction in the study area. One accomplishment of the above results is to suggest some mathematical equations with those indices to estimate the amount of vegetation. These results provide a strong foundation for the use of some vegetation indices for assessing the vegetation cover in central Iran.

Subalpine rangeland as a rara avis ecosystem is very important because of ecological features. Consistency and resistance of this ecosystem is so frangible and its natural equilibrium is instable due to the effects of biotic and abiotic factors. The landslide as one of negative consequences in upland area is seen in Masoleh watershed (north of Iran). This study has investigated the roles of biotic factors playing in the occurrence of the landslides in Masoleh rangeland. Hence, two sites such as exclosure and grazing areas were analyzed and compared. The plot size was 1m2 and totally, 128 plots were obtained by minimal area method and statistical formula approach, respectively. The rangeland conditions were measured by six-factor method. Clipping and weighing method was used to determine the grazing capacity. In order to do the landslide zonation, the landslide index was employed. Results showed that there were significant differences between species densities and soil conservation factors in both exclosure and grazing areas. There might bemore than 1.2 overstocking in the grazing area. The rangeland conditions‟ classes and distance from fold, effective biotic factors, geologic formation, soil texture and effective abiotic factors were the most influential factors on the landslide occurrence in subalpine ecosystem of Masoleh. Regarding results of current research, the exclosure can protect the soil from the landslide through increasing the perennial and endemic species. Decreasing livestock and regulating the animal entrance and egress to reach the suitable circumstances of vegetation covers and pull up the landslide occurrence are recommended in this area.

The major aim of processing satellite images is to prepare topical and effective maps. The selection of appropriate classification methods plays an important role. Among various methods existing for image classification, artificial neural network method is of high accuracy. In present study, TM images of 1987, and ETM+images of 2000 and 2006 were analyzed using artificial fuzzy ARTMAP neural network within Mehrgan region, Kermanshah province, Iran, with an area of 5957 ha changes in range cover state in this basin during 3 periods of time from 1987 to 2000 and 2000 to 2006 were examined. In this study, initially, Land sat data for intended years were corrected geometrically and radiometric ally. Next, different land use classes were defined and training samples obtained via field visits. The obtained results show that, over time period of 1987-2000, the extent of low-density rangeland and farmland in study region had been increased by 89.09 and 321.08 ha, respectively, while good rangeland and fair rangeland faced a declining trend of 358.29 ha and 48.89 ha. Also, during time period of 2000-2006, the extent of poor rangeland and farmland within study region has increased by 64.98 and 727.12 ha, respectively, while good rangeland and fair rangeland faced a declining trend of 144.01 ha and 648.1 ha. Accuracy of vegetation maps resulting from satellite data classification using algorithm of artificial fuzzy ARTMAP neural network was 90.97% and 94% for TM (1987) images and ETM+ (2000, 2006) respectively which indicates high accuracy of ARTMAP algorithms for classifying satellite. Therefore, this study proves high efficiency and potential of artificial fuzzy ARTMAP neural network for classification of remote sensing images.

The purpose of this study was identifying rangeland development and restoration operations targets. This study was conducted in Hossein Abad Bazoft basin with 7162 ha area, located in south east of Farsan County, Chaharmahal and Bakhtiari Province, Iran. The basin has various land uses including rangeland, forest, irrigated farm and garden, dry farm, residential area and rock mass. In this study, during land surveying process, ecological carrying capacity was first calculated for the rangelands and forests ecosystem. After capability evaluation, with regard to keeping the current land use and avoiding from more land degradation, restoration programs were proposed. In this regard, required data layers including altitudinal classes, slope classes, aspect classes, rangeland condition and trend, climate, soil hydrologic groups, depth and texture of the soil, geology and geomorphology were overlaid using GIS 9.3 by intersect method, and 280 homogenous units were resulted. The results of homogenous unit characteristics assessment showed that the region fell respectively in the categories 1, 3, 6, 3 and 4 for conservation, rangeland, forest, agriculture and unauthorized agriculture capabilities.Finally, according to the characteristics of the achieved capabilities and defining required criteria to propose each executive program, we proposed the location and the kind of the executable restoration programs such as exclosure, hill seeding, converting the inefficient dry farms to forage plants cultivation and in forest quantitative and qualitative regeneration.

Grass pea (Lathyrus sativus L.) has a high potential for forage production in both rangelands and cultivated rainfed areas of Iran. It is well adapted to semi-arid areas of west and north of country where annual rainfall is 250–350 mm. To study the seed and Dry Matter (DM) yield and agronomic traits, six genotypes of Lathyrus sativus L. and two genotypes of Lathyrus inconspicuous L. were provided by Natural Resources Gene Bank and sown in a randomized block design with three replications in rainfed area of Borujerd, Iran during spring 2011 and 2012. Data recorded included stem number per plant, pods number per plant, seed weight per plant, Dry Matter (DM) yield, seed yield, straw yield, 100 grains weight, flowering date, pod emergence date, maturity date and harvest index over two years. Results showed that the genotype 1554 with average values of 9328 kg ha-1 DM yield and 3053 kg ha-1 seed yield could be introduced as a promising genotype for cultivation in rainfed area of Borujerd, Iran. It was concluded that selection for improved grass pea varieties in dry condition should focus on increased DM yield, and grain yield coupled with early flowering, more grains per pod, more pod per plant and heavy seeds

Soil erosion is a serious problem especially in northern parts of Iran. One the most important side effects on soil erosion may be the decline in qualities of soil refers to agricultural productivity. So it is very important to assess the soil erosion risk for the sustainable development of agriculture. This study outlines ways undertaken to provide a new tool to manage water erosion from physical and economical perspectives. Kashidar Watershed in north of Iran is used as a case study. The focus of this study is on exploring the economic and physical impacts of eight land use-based scenarios for water erosion management as well as conducting a trade-off analysis using the Multi-Criteria Decision Making (MCDM) technique. This involves developing a modeling system to assist decision makers in formulating scenarios, analyzing the impacts of these scenarios on water erosion, interpreting and suggesting appropriate scenarios for implementation in the area. This study was conducted with object of modeling and assessing soil erosion risk in Kashidar Watershed with the application of IMAGE\LDM. Rainfall erosivity index, relief index, soil erosivity index and land cover index were four basic factors used in IMAGE\LDM. Soil erosion risk can be divided into six groups. Furthermore, the spatial distribution characteristics were also analyzed with the application of GIS in the view of elevation, land use types. Among 8 scenarios for water erosion management, most appropriate ones that have minimum proportion of high water erosion hazard classes, maximum gross margin and minimum establishment cost were chosen as best scenarios.

Water resources suitability is one of the most important factors to sustainability utilization of natural potential by rangeland grazing suitability. To determine this factor in short time, low cost and high accuracy are most challenges of experts and ranchers. Using suitable technique for this subject can be sustainable utilization comprising from rangeland ecosystems according to its degradation and heavy grazing. This research was conducted in Boroujerd Sarab Sefid rangeland, Lorestan province, Iran from 2011 to 2012. Some factors such as slope, height and direction maps provided by using satellite images, basic information, analog and digitized maps such as; topographic and DEM (Digital Elevation Model). Also measurements of field were conducted by excursion and interview with herders to determine places of water resources such as permanent and temporary springs and permanent and temporary rivers too. Water resources area's map was prepared by using Arc GIS9.3 software with integration of digitized information and field data. At the end water resources suitability were determined by using three sub models such as quantity, quality and distance from water resources. Results show that all of 16 plant vegetation types were dropped in І and II classes of water resources suitability which didn't have any limitation according to quantity and quality and distance of animal husbandry and livestock. As a final conclusion this research shows that using RS and GIS could be useful to water resources suitability of rangeland ecosystems with low cost and high accuracy and speed, if consider standards and criteria of using GIS and RS.