IRANIAN JOURNAL OF APPLIED ECOLOGY
Year:2019 | Volume:8 | Issue:3|Papers Count:6

Density and diversity of birds in two different forest zones, namely, Shasta Kalateh Protected Forest and Alangdareh Recreational Forest, were estimated and compared. Birds and environmental variables were recorded within 25 m radius in 100 sampling points. The first axis of Canonical Component Analysis segregated two main groups of birds. The first group consisted of Black Woodpecker, Great Spotted Woodpecker, Nuthatch, Blackbird, and Cettis Warbler; these had a positive correlation with logs less than 7 m in height, the degree of the decay of logs, the density of canopy cover, litter depth, and the percentage of grass cover in Shasta Kalateh Forest. The second group including Bullfinch, Hooded Crow, and Robin had a positive correlation with the number of trees with the dbh of 50-100 cm, the number of trees more than 15 m in height, the number of snags with 7-15 m in height, and the position of the canopy cover of snags in Alangdareh Forest Park. Also, according to the results of the analysis of similarity (ANOSIM) in the autumn and winter, there was a significant difference between Shasta Kalateh Forest and Alangdareh Forest (P=0. 001).

Forestry plans have been influential on tree species and planting in different ways, regulating tree species diversity. Investigation of the changes in tree species diversity and preservation livestock sustainability by using forestry inventory can be an appropriate tool for decision makers in management. Indicators such as the Shannon Wiener and Simpson indices can be used to study the variations in tree species diversity in the forest. In this research, the Watson series forestry inventory was used in 2004 and 2014. In the aforementioned years, 369 circular sampling plots were taken with an intensity of 3. 3% and using a 200 * 150 m inventory grid with GPS. The Simpson and Shannon Wiener indices were calculated in sampling plots pieces; then, Kriging ability was investigated using histogram, QQ plot, semivariogram and RMSE, and data normalization. The land maps of these indices were analyzed in 2004, 2014; also, their change detections were prepared. The results showed that during the 10-year period of the implementation of the forestry plan, the Simpson and Shannon Wiener species diversity indices were increased by 30%, and about 60% of the area remained unchanged; also, about 11% of the area had reduced species diversity.

The first and most important issue in forest drought management is knowledge of the location and severity of forest decline. In this regard, we used geostatistics and artificial neural network methods to map the dieback intensity of oak forests in the Ilam province, Iran. We used a systematic random sampling with a 250 × 200 m grid to establish 100 plots, each covering 1200 m2. The percentage of the declined trees in each plot was measured and recorded. Also, a composite soil sample was extracted from the center and the four corners of each plot in order to determine their physical and chemical properties. After examining the normality of the data, the dieback intensity map was made using interpolation methods and the artificial neural network. The results showed that the best method for dieback intensity estimation was the artificial neural network with an accuracy of 85 %, by using the multilayer perceptron algorithm. Oak decline was found to be mainly related to the slope, soil moisture, soil organic content and soil bulk density.

Continual access to precise information about the land use/land cover (LULC) changes of the Earth’ s surface is extremely important for any sustainable development program in which LULC serves as one of the major input criteria. In this study, a supervised classification was applied to three Landsat images collected in 1986, 1998and 2018, providing mangrove forests change data in the coastal area of the Bushehr province. The supervised classification results were further improved by employing image enhancement and visual interpretation. Visual interpretation was not only useful in increasing the classification accuracy of the Landsat images, but also in identifying the mangrove forest cover. Post-classification comparisons of the classified images of the mangrove forest area of the Assaluyeh habitat zone during a period from 1986 to 2018 indicated that the area of these lands had been increased by 68. 94 hectares, with a percentage change of 43. 85%, which was an increase of 1. 41% per year. These changes in the Deir habitat zone showed that the area of the land covered by the mangrove forest was 5. 25 hectares, with a percentage change of 0. 87. In the Mela Ganza habitat zone, the area of the land covered by the mangrove forest was 26. 82 hectares, with a percentage change of 6. 33, which was an increase in the annual rate of 0. 20.

Quantifying land use/land cover changes is essential to monitor and assess the ecological consequences of human disturbances. Ecological condition and water quality of wetlands are highly related to the landscape characteristics, including land use/land cover (LULC) types and their fractions in the upland and the surrounding landscape. The changing characteristics of LULC in Shadegan International Wetland, Khouzestan Province, Iran, were detected in this study by using the Landsat Satellite images of the years 2001, 2014, and 2017, which were classified using the Artificial Neural Network algorithm. Then by using Land Change Modeler (LCM) in the TerrSet IDRISI software, the future of LULC changes was simulated using six independent variables and the Markov chain method. The results of this study showed that from 2001 to 2017, about 48200 ha of the wetland water was increased and around 50000 ha of saline soils and vegetation area was decreased. However, since this water increase in the wetland was due to the entry of drainage and wastewater, particularly from sugarcane cultivation around the wetland, this increase could significantly alter the hydrology, the water quality of wetland and also, the plant species composition, as compared to historical conditions; mapping these changes requires further investigations and fine scale monitoring studies.

The distribution pattern of plants is an important characteristic of plant communities, being of critical importance in ecological studies and sampling plans. This study was designed to investigate the efficiency of different shapes and sizes of quadrants to delineate the spatial patterns of Astragalus verus Olivier by using dispersion indices. At Mayan Rangeland (Khorasan Razavi), a digital camera and R software were used to locate the coordinates of individual plants and to demarcate the boundary of the study area. We used plots of different shapes, square, wide rectangular and long rectangular, with the areas of 1, 2, 4, and 8 m2, for a total of 12 combinations of shapes and sizes. The distribution indices used included Green, Lioyd, Morisita, and the Standardized Index of Morisita. The results of the study showed that the standard Morisita's index and Morisita’ s index had the same distribution patterns in all shapes and sizes of plots. These two indices were not affected by plot size and shape in displaying the distribution pattern. The current study alsoshowed that Morisita’ s and standard Morisita’ s indices were more precise in comporison with Green and Lioyd indeces.