مجله بوم شناسی کاربردی
پیاپی 16 (تابستان 1395)

This study aimed to compare plant species diversity indices (diversity and richness) and some physico-chemical properties of soil among forest, ecotone and rangeland habitats. Vegetation sampling was done randomly at each habitat. One dominant community was selected in each habitat and one key area was distinguished in each community and 8×1m2 plots were randomly established in each key area. In each plot, the list of existing plants and cover percentage for each species were determined and soil samples were taken from depths of 0-10 cm. The Shannon-Wiener and Simpson diversity indices and Margalef and Menhinic richness indices were estimated using PAST software. Physical and chemical characteristics of the soil were compared at three sites by analysis of variance (One Way ANOVA). The results showed that the lowest and highest values of all species diversity and richness were occurred in forest and ecotone habitats, respectively. Bulk density, sand and pH value of soil were significantly the highest in the rangeland. The percentage of clay and organic carbon in forest habitat were higher than the two other habitats. This study revealed the importance of ecotone in preserving the diversity and species richness.

The relationship between plant species and climatic factors has always been an important subject in plant ecology and the use of multivariate statistical methods might be effective in detecting the relationship between climatic factors and the distribution of plant species. In the present study, climatic characteristics of Astragalus gossypinus Fisher producing tragacanth stretched in a relatively vast area in Isfahan province (approximatley seven percent of natural habitat of Isfahan province) to shed lights on determinant climatic factors on distribution of this species were investigated. In this study, 56 climatic variables were evaluated in the months of January, March, and July in the annual interval and to reduce the number of variables and determine the most important factors. Factor analysis was applied using principal components analysis. The results showed that four factors, namely cooling temperature-humidity, precipitation-storm, cloudiness, and windiness account for 39.05%, 32.77%, 11.44%, and 8.63%, and totally 91.88% of the variance of the data, respectively. Also, the cooling temperature-humidity factor has the greatest impact on presence of this species, therefor, in areas where this species can be seen, the cooling temperature-humidity factor is positive and vice versa.

In this study the effect of crude oil (0 to 20% w/w), one of the main pollutants of current age, on physiological characteristics of Prosopis juliflora, Acacia victoria, Ziziphus spina-chrisi and Robinia pseudoacacia in seed and seedling stages based on a completely randomized design with 10 replications in each experimental unit has been studied. The results revealed that germination rate of Prosopis and Acacia was not affected by the pollutant, but the germination reduced in Ziziphus with more than 6 percent pollutant and 4% pollution led to full inhibition in Robinia. The ED50 based on radicle growth for Acacia, Prosopis, Ziziphus and Robinia was 6.9, 3.2, 3.6 and 2.7%, respectively. In seedling stage green leaf percentage, chlorophyll concentration, and efficiency of photosystem II decreased by increasing contamination. Increasing oil concentration stopped seedling growth of Robinia and reduced stem length in Acacia and Prosopis, but no significant difference was observed in the root length. The increase of oil pollution up to more than three percentages was associated with increased growth of shoot and root in Ziziphus. The difference in response pattern of different species to crude oil enables us to select species based on a variety of objects from bio monitoring to phytoremediation.

Integrated watershed management is considered as a new principle for development planning and management of water and soil resources emphasizing on socio-economic characteristics of the region to sustainable livelihoods without vulnerability for plants and the residents of an area. This research, in line with the objectives of integrated management, has been carried out for modelling and evaluating the effects of ecological, socio-economic consequences resulting from the implementation of the proposed management plans on the vegetation changes with a focus on the problems in Simindasht catchment, located in Semnan and Tehran Provinces. After standardization of indices by distance method and weighing them, the scenarios were prioritized using multi-criteria decision-making technique. Trade-off analysis of the results indicates that in the integrated management of Simindasht catchment more than one single management solution, covering all aspects of the system can be recommended in different weighting approaches. The approach used herein, considering the results of different models and comparing the results, is an efficient tool to represent the watershed system as a whole and to facilitate decision making for integrated watershed management.

Leaf area index (LAI) is a key variable in primary production and carbon cycling in ecosystems. It is used as an important predictor to explain the processes of forest ecology, forest management, and remote sensing studies. Most of the remote sensing instruments such as LAI-2000 and Fisheye photography are based on three-dimensional space and they consider the geometry of the crown to estimate LAI. The aim of this study was to investigate the relationship between spectral behaviour of Quercus persica and Pistacia atlantica with two-dimensional and three-dimensional LAI. To estimate LAI, a box (0.5× 0.5× 0.5 meters) was placed in the four directions of the crown and all the leaves were harvested. In situ spectral measurements of leaves were done with ASD Fieldspec spectroradiometer. The results of partial least squares regression to model LAI form spectral data of Quercus persica showed maximum regression coefficient at visible and near infrared wavelengths for both LAI3D and LAI2D. The coefficient of determination (R2) between the measured and estimated LAI2D and LAI3D values for Quercus persica was 0.16 and 0.23 respectively, and for Pistacia atlantica was 0.15 and to 0.42, respectively. Generally, LAI3D showed better relationship with spectral reflectance for both species.

Knowledge of species’ habitat needs is considered as one of the requirements of wildlife management. We studied seasonal habitat suitability and habitat associations of wild goat (Capra aegagrus) in Kolah-Qazi National Park, one of its typical habitats in central Asia, using Maximum Entropy approach. The study area was confined to mountainous areas as the potential habitat of the wild goat. Elevation, distance to water sources, distance to human settlements, and distance to guard patrol roads were recognised as the most important variables determining habitat suitability of the species. The extent of suitable habitats was maximum in spring (3882.25 ha) and the least in summer (1362.5 ha). The AUC values of MaxEnt revealed acceptable to good efficiency (AUC ≥0.7). The obtained results may have implications for conservation of the wild goat in similar habitats across its distribution range.

The sensitivity of landscape metrics to the scale effect is one of the most challenging issues in landscape ecology and quantification of land use spatial patterns. In this study, fractal dimension was employed to assess the effect of scale on the sensitivity of landscape metric in the north of Iran (around Sari) as the case study. Land use/ cover maps were derived from Landsat-8 (OLI sensor) image processing and its spatial scale was downgraded to 30, 60, 120, 150, 200, 250, and 300 by cell-center method. After that, landscape-level metrics were quantified. Finally, linear regressions were formed for the every metric based on the logarithmic transformation and the Coefficient of Determination and Fractal Dimension were computed as well. The coefficient of determination for all measures of diversity was zero and for other measures in two general categories: high sensitivity (R- redundant) and without sensitivity (N- no effect). Results acquired from the two indicators were perfectly delineated the sensitivity of landscape metrics to the scale effect (Coefficient of Determination) as well as the direction and magnitude of the landscape metrics (Fractal dimension).