Reza Tamartash; Mohammad reza Tatian; Haniyeh Andarz chamani; Seyyed Hassan Zali; Seyedeh Mohadeseh Ehsani
Abstract
Invasive species are globally endangered for ecosystems, and ecologists are increasingly concerned about them. Pteridium aquilinum is one of the most invasive species widely distributed in the world. This study investigated the phytochemical of Pteridium aquilinum species in ...
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Invasive species are globally endangered for ecosystems, and ecologists are increasingly concerned about them. Pteridium aquilinum is one of the most invasive species widely distributed in the world. This study investigated the phytochemical of Pteridium aquilinum species in different altitude gradients. So, random sampling was performed from vegetation and soil in three altitudes (0-700, 700-1400 and 1400-2100 meters) with three replications for both growth and reproduction stages. In the growth stage, the composition of Linalool was the highest value (1.09) in the altitude of 0-700m. During the reproductive stage, Sabinene and –α Thujene had the highest values in the altitude of 0-700m with 0.15 and 0.13%, respectively. The amount of oil in the growth stage is more than the reproductive stage, so it can be concluded that the growth stage will have a significant effect on the amount of oil compounds.
Seyedeh Mohadeseh Ehsani; Reza Tamartash; Gholamali Heshmati; Esmaeil Sheidai Karkaj
Abstract
This study aimed to evaluate the efficiency of the LFA method to predict the species diversity indices. Sampling was carried out using 140 plots of 1 m2 along 14 transects based on a randomly-systematic design and so, the final index of soil infiltration, nutrient cycle and soil stability was calculated. ...
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This study aimed to evaluate the efficiency of the LFA method to predict the species diversity indices. Sampling was carried out using 140 plots of 1 m2 along 14 transects based on a randomly-systematic design and so, the final index of soil infiltration, nutrient cycle and soil stability was calculated. Also, the cluster analysis was applied to determine the similarity between the variability indices, soil surface parameters and final indices by using PAST software. The results showed that at the level of 1percentage (P≤0.01), the Shannon diversity and Simpson indices were predicted by altitude from the sea level and nutrient cycle parameters, respectively and, richness index were predicted by these two parameters. It seems that the LFA method can create the final indices by considering and scoring some of the surface parameters of the soil (eleventh indices) and these indices can finally display the ecosystem's performance finally display the ecosystem's performance.
