مجله بوم شناسی کاربردی
پیاپی 2 (پاییز و زمستان 1391)

Effective river ecosystem management requires that the existing hydrologic regime be characterized in terms of the natural hydrologic regime and the degree to which the human-altered regime differs from natural conditions. This is known as Range of Variation Approach (RVA) and can be used for variation of stream flow, range of variation and appraisal of dam impacts on riparian zones. In this paper, we used 31 hydrologic parameters, classified into five groups, monthly flow indices, extreme flow indices, timing indices, high-flow and low-flow indices, and rate of change, to assess hydrologic regime alteration in downstream of Karkheh dam. For this, purpose the hydrologic parameters of Pay-Pol hydrometric station have been taken. into consideration. As the Riparian ecosystems are highly dependent on and sensitive to variation in the hydrological cycle, the focus of this study was the 50-meter buffer of the Karkheh River. To examine the impacts caused by the variation of hydrologic regime, we tested if this variation and 8 different landscape metrics in the study area are correlated. The results showed that variation of hydrologic regime had a significant impact on the landscape structure of riparian zone in Karkheh downstream and caused isolation in landscape pattern of the woodland cover. Therefore, landscape structure in Karkheh downstream is highly correlated to hydrologic processes of upstream of the river. It can be concluded that an effective water management strategy is keeping safe the ecological condition and integrity of the riparian zone of Karkheh. This happens when all the hydrologic parameters are in the natural range of variation as they were before dam construction.

Due to the increasing industrial activities in many tropical and subtropical coastal areas, social concerns in relation to the impact of anthropogenic activities on mangrove forests have been increased. Surface mangrove sediments (0–10 cm) from three mangrove forests in Bushehr, northern Persian Gulf were sampled for metal analysis in April 2009. The concentrations ranged (in µg g-1 dry weight)as fallows: 1795-30240 Al, 6425-51530 Fe, 0.6-3.45 Cd, 14.1-98.28 Cu, 14.1-204.54 Ni, 34.15-191.6 Pb, 57.38-825.26 V, and 44.91–306.15 Zn. The overall average concentrations of above metals exceed the primary standard criteria but meet the secondary standard criteria of the Chinese National Standard of Marine Sediment Quality and United State Environmental Protection Agency (USEPA) Standard. Among them, three mangrove sites in Bushehr, Bidekhun and Basatin were contaminated with heavy metals. Bidekhun is nearest mangrove to the South Pars gas complex, and Basatin is located in neighborhood. In addition, the disturbing of current water in Basatin creek with bridge construction has caused the increase of metal concentrations within this site.

The relationship between plant species and environmental factors has always been a central issue in plant ecology. With rising power of statistical techniques, geo-statistics and geographic information systems (GIS), the development of predictive habitat distribution models of organisms has rapidly increased in ecology. This study aimed to evaluate the ability of Logistic Regression Tree model to create potential habitat map of Astragalus verus. This species produces Tragacanth and has economic value. A stratified- random sampling was applied to 100 sites (50 presence- 50 absence) of given species, and produced environmental and edaphic factors maps by using Kriging and Inverse Distance Weighting methods in the ArcGIS software for the whole study area. Relationships between species occurrence and environmental factors were determined by Logistic Regression Tree model and extended to the whole study area. The results indicated species occurrence has strong correlation with environmental factors such as mean daily temperature and clay, EC and organic carbon content of the soil. Species occurrence showed direct relationship with mean daily temperature and clay and organic carbon, and inverse relationship with EC. Model accuracy was evaluated both by Cohen’s kappa statistics (κ) and by area under Receiver Operating Characteristics curve based on independent test data set. Their values (kappa=0.9, Auc of ROC=0.96) indicated the high power of LRT to create potential habitat map on local scales. This model, therefore, can be applied to recognize potential sites for rangeland reclamation projects.

Development of roads through protected areas and ecological sensitive regions can have catastrophic effects on wildlife. In Iran, road construction in sensitive habitats and protected areas has been expanding during the past decades. This study focuses on the ecological impacts of Isfahan’s west ringway, which passes through Ghamishloo wildlife refuge, I.U.C.N category IV, in Isfahan Province. The key affected species of the study area goitered gazelle (Gazella subgutturosa subgutterosa), was considered for impact analysis. We used HEP (Habitat Evaluation Procedure) as a habitat-based impact assessment methodology which considers habitat quality and quantity. Habitat quality was measured as habitat suitability index for the species. By literature review and field observations (293 presence points), five effective variables in habitat suitability including vegetation cover, slope, elevation, distance to water and distance to road were identified, and habitat units (HUs) were derived from multiplying the HSI for goitered gazelle by the species habitat area at two times (before and after road construction). The results showed that due to the presence of the ringway, 7710 HUs for goitered gazelle have been lost. In addition, we used landscape ecology approach for quantifying landscape pattern change due to road construction and landscape metrics including NP (Number of Patches), MNN (Mean Nearest Neighbor) and CONTAG (Contagion). Our results provided quantitative data on habitat loss and landscape fragmentation in Ghamishloo wildlife refuge and indicated negative impacts of the ringway on goitered gazelle populations by restricting their movement between habitat patches in this region, which presents a concern for the conservation of this vulnerable species.

In applied studies, identification and study of vegetation, for management and protection of natural ecosystems, are very important. This study was carried out in Vezg forest with an area of 308 hectares located in southeast of Yasouj city. The purpose of this study was to classify ecological species groups and survey their relation to soil physic-chemical properties and physiographic attributes. For this purpose, the field data were obtained using 52 sample plots (15m×30m) in a systematic random grid. In each sample plot, the cover percentage of tree, shrub and grass species type were recorded, by using Braun-Blanquet method. The TWINSPAN method and Canonical Correspondence Analysis (CCA) were used for the definition of ecological species groups and determintion of the relationship between ecological species groups and environmental properties. Results showed that, there were four ecological species groups in the study area. The First group included: Anchusa italic-Quercus brantii, the second group: Heteranthelium piliferum-Avena clauda, the third group: Teucrium polium and the fourth group: Salvia reautreana. The first group was in an area, where there was a higher percentage of Persian oak litter. The second group was located in site a with higher grass cover than the site of other groups in the area. The third and fourth groups, were located in the higher elevation and steep points. Results of CCA showed that soil properties were not in significant relation with ecological species groups. But, the relationships of ecological species groups with other environmental factors such as litter, altitude, grass cover and slope were significant. So, we can conclude that these properties are effective in the separation and distribution of ecological groups.

Regarding high economic and conservative values of Zagros forests, and livelihood dependency of local people these recourses, determination of sites with higher conservation index can help us to maintain biodiversity of these forests more efficiently. Therefore, 49 plots with 450 m2 in area accompanied by 1, 10 and 45 m2 subplots were taken as systematic random design in research forests of Yasouj University. The number of species in each plot and subplot was recorded. The conservation values for different physiographic regions of forest were calculated using integrative parameters such as the number of species per plot, number of rare species per plot, number of tree species per plot, Jaccards similarity coefficient and slope of species-log(area). Comparing the conservation index in different physiographic sites revealed that the areas located in the north, hills and lower altitudes can be considered for in situ conservation due to higher number of trees, rare species and total plant species, species-log (area) slope and lower amount of Jaccard similarity coefficient. But, vegetative sites located in lower slopes and south, because of lower conservation index, can be used for other multipurpose forestry activities. Using this index for different forest areas can be potentially conducted for better conservation and management of Zagros forests.

There is no doubt that climatic factors are one of significant parameters in occurrence of natural fires in forest and range ecosystems. The goal of this study was a monthly-based prediction of the occurrence of the natural fires using artificial neural networks in Izeh, north-west of Khuzestan province. The natural fire occurrence data including date of the occurrence, the burned area and number of the fire occurrence was obtained from Izeh Natural Resources Office. The findings indicated that the algorithm of multiple layer perceptron and hyperbolic function were efficient in exploring the relationship between climatic factors and the natural fire occurrence. The networks with two hidden layers and 15 neurons have revealed high accuracy in prediction of the natural fires occurrence. Moreover, for prediction step FMSE(Final Mean Square) was recorded 0.0038. While for testing step, coefficient of variation, MSE(Mean Square), and NMSE(Normal Mean Square) were equal to 0.99, 0.073, and 0.018, respectively. For validation step, the trained network has indicated a high determination coefficient (r2=0.98) between the observed and predicted values. It should be mentioned that the present approach in this study could achieve an artificial neural network with medium performance (r2=0.58) between climate data and the burned area of the natural fire.