مجله بوم شناسی کاربردی
پیاپی 34 (زمستان 1399)

Understanding effects of environment on the distribution of economic fish is a fundamental step in the ecosystem-based management and ultimately a standard approach in management policies. Bigeye tuna (Thunnus obesus) is one of the most important aquatic species harvested in the Indian Ocean. The present study investigated the association of different variables effecting the rate of catch and distribution of bigeye tune, using generalized additive model (GAM) and maximum entropy (MaxEnt) and satellite derived environmental variables in the Indian Ocean. Results highlighted the importance of temporal and spatial variables along with the eddy kinetic energy, sea level height, depth of 20°C isotherm and sea surface temperature on the distribution of the species. The most suitable habitat predicted by MaxEnt model was observed around the latitudes of 0 to 5 degrees of north and south, mainly in the western part of the Indian Ocean and longitude of 45 to 70 degrees east. Using satellite data, the present study determinied the important factors and suitable habitats for the species, which can be useful for Iranian fisheries managers to increase the fishing efficiency and implementing of ecosystem-based fisheries management in the shared exploited stocks of the Indian Ocean.

Addressing desertification, due to its multi-criteria nature, increasing development, extensive and long-term impacts on natural resources and human populations, is necessary to achieve sustainable development. Therefore, for optimal utilization of facilities and limited funds allocated to this issue, evaluation of current strategies, based on different criteria is essential to avoid wasting national funds, while achieving better results. The current study used Decision Making Trial and Evaluation Laboratory (DEMATEL) to rank desertification strategies in the context of Multi-Attribute Decision-Making (MADM) models. First, important and high-priority criteria and strategies were identified within the framework of MADM, using the Delphi method. Then, the final priority of strategies was determined using the DEMATEL method. Based on the obtained results, vegetation cover development and reclamation (A23), change of irrigation patterns and implementation of low water demand methods (A33), and livestock grazing control (A20) were recognized as the most important combating desertification strategies in the region. Therefore, it is suggested to consider the obtained results and ranking in control plans to reduce the effects of desertification and reclamation of destructed lands.

The Solanaceae family with 49 species of 10 genera is one of the important nutritional, economical, medicinal and ornamental families in which six genera of them are classified in the group of wild relatives. Predicting the effect of climate change on the distribution of plant species is important for their management and conservation. In this study, the effects of climate change on this family was investigated with a conservation approach, using Species Distribution Modeling (SDM). Future spatial distribution of this family was predicted by MaxEnt model under optimistic (RCP2.6) and pessimistic (RCP8.5) scenarios for the year 2050 and 2080 in R software. In general, the performance of the model for different species was good or excellent based on the area under the curve index (AUC ≥ 0.8), showing high statistical reliability of the distribution modeling. Predicting the distribution of all species in the face of climate change and under various future scenarios showed both decrease in the current original habitats and increase in new habitats. However, the ratio of the increase and decrease was different in various species. In Atropa acuminate, Solanum surratense, Datura stramonium, Hyoscyamus niger, Hyoscyamus reticulatus, Physalis alkekengi and Solanum dulcamara the ratio of decrease was more than increase, implying the negative effects of climate change on these species and may cause species extinction. However, the ratio of increase was more than decrease in Datura innoxia,Physalis divaricate,Solanum alatum and Withania somnifera, showing a positive effect and climate change may  cause species expansion.

During the marking operations planning in forest ecosystems, designing the canopy gap size (CGS) is not clearly possible and a marker can only be capable of calculating the expanded gap size (EGS) that will be created by cutting and felling trees. Therefore, the main goal of the current study was to provide a solution to this problem on the basis of accurate prediction for CGS, before applying selection methods, through developing regression models for predicting the CGS in Glandroud forests. On the basis of full inventory for measuring the area of canopy and expanded gaps using radial technique, calculating the species diversity indices and observations of physiographic units, the regression models were developed for estimating the CGS as the response in the research. The results showed that the site fraction occupied by expanded gaps has one hectare more than the fraction occupied by the canopy gaps. Furthermore, the results of correlation tests showed that the CGS had significant relationship with the Shannon diversity and species dominance indices. The results of analyses indicated that multiple linear regression log-transformed from the power function including EGS, correlated species diversity indices of gaps surrounding trees predicted the responses with statistically acceptable certainty and accuracy.

Mansourieh and Sharifieh are two recently dried wetlands in Khuzestan province, that have become important dust sources. This study was carried out in Sharifieh and Mansourieh wetlands to assess the vegetation condition and trend, following the implementation of water spreading and artificial recharge in recent years. To evaluate changes in vegetation, five transects of 100 meters, 50 meters apart, were established in the water spreading site in a random systematic manner, and data was collected from 30 permanent plots for six times between 2017-2019. Species richness and diversity indices were measured using the coverage percentage factor. The results obtained in Mansourieh showed a significant difference between the water spreading site and the non-irrigated site. Simpson and Shannon indices showed a gradual increase in species diversity following the implementation of flood spreading by means of Shahid Poursharifi Channel. Likewise, in Sharifieh wetland, Shannon and Simpson diversity indices improved in response to the enhancement of species richness and decreasing dominance (from two dominant species to over 20 species). In Sharifieh, we obtained a significant difference between the years 2017 and 2018 in terms of diversity indices. In general, the flood spreading areas will experience an improvement in native vegetation, which will be translated into reduced dusts storm frequency and severity.

The current study aimed to investigate changes in growth models of hornbeam (Carpinus betulus), as the most abundant species in Arasbaran forest, at different altitude ranges and aspects. Sampling was performed in one-hectare plots at the altitude range of 1200 to 1500 meters and hornbeam trees were measured on the diameter at the breast height (DBH), total height and the diameter of crown canopy. Data analysis was carried out by Nonlinear Regression Models and the best models were fitted based on maximum correlation coefficient, coefficient of determination, minimum standard error and Akaike coefficient for the relationship between diameter (independent variables), and height, basal area and the crown canopy (dependent variable). Results showed that there was a positive correlation between DBH, height, and basal area of trees (r = 0.994) but DBH and crown canopy had a negative correlation. In addition, there was a significant difference in height and crown canopy of the trees across altitudes and aspects. The results of nonlinear models revealed that Exponential Linear Model, Rational Model, Heat Capacity, Sinusoidal, Exponential Association 3, Gaussian, Natural Logarithm and Reciprocal Quadratic YD were the most important models. The hornbeam species follows different models at different altitudes and aspects (except in the northeast aspect which only showed a Rational Model at different altitudes). Nonlinear Regression Models performed reasonable in showing the relationship between tree characteristics including diameter-basal area and diameter-canopy cover. It is recommended to use such models for other species in the region with environmental factors to provide complementary results for more accurate management guidelines.