Reza Omidipour; Ataollah Ebrahimi; Pejman Tahmasebi; Marzban Faramarzi
Abstract
Vegetation canopy cover (VCC) and Above-Ground Phytomass (AGP) are the most important indicators of rangeland ecosystem’s structure and function, therefore their accurate evaluation and monitoring is vital for ecosystem welfare. Vegetation indices, are essential tools for assessing and monitoring ...
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Vegetation canopy cover (VCC) and Above-Ground Phytomass (AGP) are the most important indicators of rangeland ecosystem’s structure and function, therefore their accurate evaluation and monitoring is vital for ecosystem welfare. Vegetation indices, are essential tools for assessing and monitoring VCC and AGP which have not been addressed under different managerial conditions, so far. In the present study, the effect of long-term grazing and enclosure (26-year) on the relationship between the VCC and AGP with vegetation indices were evaluated in the Sabzkouh protected area of ChaharmahalVaBkhtiari province using Landsat-8 images. VCC and AGP were evaluated in both grazed and enclosed area by 10 plots of 30*30-m in each of which three quadrates of 2×2 square meters were applied (totally 60 quadrates) in the June, 2016. The results indicate significant differences between grazed and enclosed areas in terms of VCC (57% and 46 respectively) and AGP (with 1656 and 1011 kg per hectare, respectively). The soil adjusted vegetation indices show a more significant prediction of VCC in enclosed and grazed areas (TSAVI1=0.828 and PVI3=0.884, respectively). The PVI2 index showed appropriate results for estimating AGP in both enclosed (R2=0.726) and grazed (R2=0.698) areas. The improved performance of these indies is mainly due to the adjustment of soil effects. Our results suggest that grazing caused a significant effect on the relationship between VCC and AGP with vegetation indices due to feasible changes in vegetation structure or composition. Therefore, using different indices is necessary to study and monitor different rangelands under management strategies.
Reza midipour; Reza Erfanzadeh; Marzban Faramarzi
Abstract
Intensive livestock grazing is one of the most important destructive factors in rangelands that leads to decrease of diversity and causes disappearance of sensitive plants. On the other hand, considering the scales in assessment of diversity is very importance to study the variability of plant diversity ...
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Intensive livestock grazing is one of the most important destructive factors in rangelands that leads to decrease of diversity and causes disappearance of sensitive plants. On the other hand, considering the scales in assessment of diversity is very importance to study the variability of plant diversity patterns in different scales. Therefore, current study aimed to investigate the impact of livestock grazing on diversity components in different scales using additive partitioning methods in western country rangelands in the Ilam province. Sampling was carried out in 40 plots of 4m2 in 8 rangeland sites including 4 exclosures and 4 grazing sites. Based on additive partitioning diversity methods, the total diversity was partitioned into additively components within and among samples. The results showed that diversity among sites (β2) had the highest contribution of total diversity that indicated the importance of this scale for conservation practices, and it was due to the variation of composition between sites. In addition, the results represented that exclosure in the semi-arid areas can increase diversity at plot scale, while in the regional scales (diversity among sites or β2) livestock grazing leads to increase in diversity. Therefore, exclosure of rangelands does not necessarily lead to increase in diversity. Also, long terms exclosure can lead to increase evenness that resulting in increasing competition among plants, therefore it could decrease plant diversity.
Kamran Karimi; Gholamreza Zehtabian; Marzban Faramarzi; Hassan Khosravi
Abstract
Remote sensing is a key technology for assessing expansion and rate of land cover changes that awareness of these changes as the basic information has a special importance for various programs. In this study, land use changes were examined over the past 24 years, and the feasibility of predicting ...
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Remote sensing is a key technology for assessing expansion and rate of land cover changes that awareness of these changes as the basic information has a special importance for various programs. In this study, land use changes were examined over the past 24 years, and the feasibility of predicting it in the future was evaluated by using the Markov chain model of the Abbas Plain. Landsat TM, ETM+, and OLI satellite images for the years 1968, 2003 and 2013, respectively; along with topographic and vegetation maps of the study region were used in this research. The images for three periods were classified into five land-use classes of rangeland, agricultural land (irrigated and rain-fed)), residential land, riverbed and barren and hilly land. According to the results, agricultural land is the most dynamic land-use class in the study area and its area has followed an upward trend during the period 1968 – 2003, so that 4337 ha (7.12%) has been added to this land-use class during this period. The trend of rangeland use change has had a descending trend during the period 1968 – 2003, so that has caused its area to be decreased by 3.19% (6573.6 ha) during this period. The results obtained from Markov chain analysis in the period 1968-2003, for model calibration; the maps for the years 1968 and 2003, and its matrix for predicating land use changes of the year 2023 indicate the Kappa coefficient equal to 80 percent. Based on the obtained results, in the year 2023, 49.1 and 10.1 percent of the study region are comprised of agricultural land and rangeland, respectively.