Desert
Volume:26 Issue: 2, Summer -Autumn 2021

High temperatures, low average rainfall, drought, and high evapotranspiration are limiting factors in arid lands. Therefore, when constructing landscapes (green spaces) in these regions, strategies should be developed to mitigate these climatic influences. One practical strategy is utilizing different types of mulches on the surface of the soil. This study was conducted as a randomized complete block design experiment with four replications during 2014 and 2015 to examine the performance of organic and inorganic mulches as non-living mulches and ground cover plants as living mulches. Ground cover plants were Carpobrotus sp., Potentilla reptans, Vinca minor, Frankenia sp. and a mixed turfgrass. Non-living mulches were turfgrass clippings, wood chips, sawdust, gravel, rubble and scoria (volcanic rock). Bare soil was used as the control treatment. The results demonstrated the application of mulches could modify soil temperature at 5 and 15 cm depths in different seasons of the year. The living mulches especially Carpobrotus sp. and turfgrass reduced the temperature more than the non-living mulches. The soil covered with sawdust and wood chips preserved soil moisture content over the soil covered with other types of mulches. It would appear the selected mulches could decrease the irrigation intervals through increased water holding capacity of the soil. The outcomes of this research could assist landscape managers operating in extreme climate conditions of arid and semi-arid regions to advance the management of soil moisture and temperatures with the objective to improve sustainability.

Salt stress is a major agro-environmental constraint on crop productivity. In this study, the effect of different levels of salinity stress (0,25,50,75, and 100mM NaCl) on the accumulation of some ions in two salt-tolerant and susceptible onion cultivars (Esfahan and Behbahan cultivars, respectively) was investigated in 2017. The research was done by a factorial experiment based on a completely randomized design with three replications. The results showed that salinity increased Na and Cl contents and also decreased K content in the leaf and root in both cultivars. However, Na and Cl contents in the leaf and root of the susceptible cultivar were significantly higher than those in the tolerant cultivar, while the K value was less. In both cultivars, the Cl content in the leaf and root decreased with increasing salinity. However, the amount of Ca in the tolerant cultivar was higher than that in the leaves and roots of the susceptible cultivar. Salinity only significantly reduced Mg in the leaves. The amount of phosphate decreased at low salinity levels and increased as salinity increased. Yield injury index was in significantly negative correlation with K,Ca, K/Na, and Ca/Na ratios and in significantly positive correlation with Na and Cl in the leaves and roots. The results indicated the salt-tolerant cultivar plays a role in reducing the Na and Cl uptake, as well as increasing the absorption and transfer of K and Ca to the leaves. Therefore, it could cause low yield injury under the salinity conditions compared with the susceptible cultivar.

Soil compactibility can be quantified using different indices such as maximum dry bulk density (BDmax) and critical water content (θcritical) in a compaction test. The objective of this study was to determine soil properties influencing soil compactibility by evaluate pedotranfer functions (PTFs) with respect to their accuracy and usefulness for the prediction of BDmax and θcritical using linear regression and ANN methods. 100 soil samples were collected from arable and virgin lands in southeast Iran. Primary particle size distribution, CaSO4, CaCO3, organic matter (OM) contents and natural bulk density were used as predictors. Two PTFs were developed using linear multiple stepwise regression: a PTF that estimates BDmax using clay and sand contents and natural bulk density as predictors (R2 = 0.45), the other one for the estimation of θcritical using clay and CaSO4 contents as predictors (R2 = 0.51). Furthermore, an attempt was made to construct PTFs for the prediction of the BDmax and θcritical using ANNs. High prediction efficiencies were achieved using the ANN models. Generally, when all of the easily-available soil properties were included as predictors, much more accurate estimates were obtained by the ANN models for the θcritical and BDmax as compared with the linear regression method. Sensitivity analysis showed that the most important variable in BDmax prediction using ANNs is the BDnatural followed by sand and clay, CaCO3 and CaSO4 contents. The θcritical had the highest sensitivity to clay content and the lowest sensitivity to OM content in the studied soils.

Soil moisture (SM) acts like an impressive factor in hydrological process, agricultural productivity and monitoring of dangerous outcomes of climate change. The main purpose of this study was to monitoring and pattern recognition of spatial and temporal variation of SMAP soil moisture in five subcatchment of Simineh-Zarrineh catchment in north west of Iran from 2015 to 2017. Precipitation data of thirty-five meteorological stations and 287 soil moisture points derived from the SMAP were used to monitoring SM variations in the time scale. Result indicated that the SM variations are subject to precipitation variations throughout the monthly scale in the catchment. In all seasons of the period SM decreased from north to south of the catchment also on the contrary, east to west does not follow up such a constant pattern. Oscillation SM patterns in this time period were completely coordinated by precipitation pattern. The determination coefficient between monthly SMAP soil moisture and precipitation for each sub-catchment was 0.9, 0.83, 0.7, 0.84 and 0.71 for Bokan, Saqqez, Takab, Saeinqaleh and Miandoab sub-catchment, respectively. Spatial variability of standard deviation for SM values was used to find the amount of deviation from the average value during dry and wet seasons. Result reveal that in seasonal scale northwest (0.067 to 0.069 cm3.cm3) and east parts (0.057 to 0.061 cm3.cm3) of study area have higher values of the SM standard deviations in autumn. Results demonstrated that high value of standard deviation was observed in autumn season because of irregular precipitation events and fluctuation of temperature.

Tourism is one of the most diverse economic activities in the world. Desert ecosystems are now considered as one of the important natural tourist attractions due to their unique ecological potential and socio-economic capabilities and values, attractions, and unique features. Lut desert has also attracted the attention of many tourists around the world as a tourist destination. This is while, tourism development in the Lut desert cannot be easy due to its natural fragility. Therefore, the current research aimed to prioritize the impacts of tourism development in the Lut desert by integrating the driver-pressure-state-impact-response (DPSIR) model and TOPSIS technique in order to formulate management strategies. The values of severity and importance of each of the identified impacts were prioritized using the TOPSIS technique and according to experts’ opinions. The results showed that the decline of culture and customs (0.80) and the indicators of cultural and social dichotomy (0.31) were the most important impacts. Land use change for the sake of infrastructural development (0.27), and activation the government diplomacy (0.26) were the next most important priorities. Tourism development in the Lut desert has positive and negative impacts, so in order to develop tourism with minimal damages to nature (ecotourism), it is necessary for the planners and managers to consider the relevant policies. Finally, this article proposed strategies which help accurate and wise development of tourism, such as codified educational programs to the tourist and host community, planning and appropriate land use management for infrastructural development.

Soil classification is useful to better understand and manage soils. The objective of the present research was to compare the capability of Soil Taxonomy (2014) and WRB (2015) systems to describe and classify soils in Lut Desert. Marginal and central parts of Lut with typical aridic/thermic and extreme aridic/hyperthermic soil moisture/temperature regimes were selected. Twelve representative pedons on alluvial fan, plain, rock pediment, Gandom Beryan lava plateau, and playa were described and sampled. Results of the study clearly showed that the WRB system was more capable to reflect soil forming processes. However, it is recommended that anhydritic qualifier to Solonchaks, Solonetz, and Gypsisols; aquatic qualifier to Solonchaks and Solonetz; and abruptic, leptic, and paralithic qualifiers to Solonchaks be added. The ST system has not been successful in expressing soil forming processes because this classification system considers only two great groups for saline soils and gives priority to Salids in comparison to the other suborders of Aridisols. That is why Petrosalids, Gypsisalids, Natrisalids, and Argisalids great groups and Anhydritic Natrisalids, Anhydritic Argisalids, Anhydritic gypsisalids, Anhydritic Petrosalids, Calcic Natrisalids, Calcic Argisalids, Calcic Gypsisalids, Natric Petrosalids, Natric Haplosalids, Natric Gypsisalids, Petrogypsic Petrosalids, and Epipetrosalic Aquisalids subgroups are suggested to be added to Soil Taxonomy system. Meanwhile, definition of anhydritic horizon, considering textural difference in strongly contrasting particle size classes of family level, and aquic conditions in playa were among the strong points of Soil Taxonomy. It is also suggested to remove (or adopt) colour (Hue) requirement of anhydritic horizon in ST system.

Nebkha and the plant that creates it together form a system. nebkha formation parameters have a significant effect on the transfer rate of aeolian deposits. Adequate information on nebkha will help plan more accurately and efficiently and better manage wind erosion-prone lands to identify appropriate wind erosion programs and deal with this phenomenon. This study aimed to compare regression methods and artificial neural networks to investigate the relationship between the quantitative characteristics of Tamarix and Seidlitzia Rosmarinus plant species and quantitative parameters of nebkha. The regression methods used in this study include PCR, PLS, and OLS. In this study, the plant characteristics used are plant height, length, width, and type, and morphometric characteristics include nebkha length, height, slope, and width. The number of sampling points was 80 selected randomly from nebkha in Khour va Biabanak County. 70% of the data was used for training the network and 30% for validation. According to the results of this study, the highest R2 between nebkha length and Seidlitzia Rosmarinus plant characteristics is related to the OLS method with 0.8, followed by nebkha area and width. R2 levels in the neural network were lower, i.e., 0.76. In the case of the Tamarix species, the highest R2, i.e., 0.797, is related to the characteristics of the plant with nebkha length, followed by nebkha area and width. This value is 0.78 in the neural network method. Moreover, the evaluation results of different predictive models showed that the OLS model is superior to other models.

Soil salinity and alkalinity are among the most important soil degradation processes, especially in arid and semi-arid regions. The purpose of this study is to evaluate spectral indicators as well as use the data of the EM38 for identifying saline soils and spatial changes. The study area is Ghahavand plain that is located in Hamedan Province. In this study, Landsat 8 satellite data were used. Soil sampling of 37 points was performed and 86 points were read using an electromagnetic induction device. Using protomorphic units based on visual interpretation of OLI 543 false-color composite image and field observations, a total of 9 homogeneous units were identified in the region using these units as training regions for supervised classification. The results showed that the detection of soil salinity in the visible spectrum (blue, green, and red band) is feasible. The bands 5, 6, and 7 can be useful in differentiating salty white crust lands from salty gray crust lands. In the reflective bands, the white and smooth crust exhibits the highest reflectance. The results of classification accuracy showed that the highest total accuracy was 90.0 and the kappa coefficient was 80.45 when bands 1, 2, 3, 4, 5, 6, 7, 10, and 11 were used and shallow and abandoned plowed lands had the least accuracy. Also, the final model of salinity estimation showed that SI6 and SI11 indicators and electromagnetic induction vertical measurements (EMv) are the most suitable variables for estimating salinity spatial changes.

Barley is one the most widely cultivated crop in marginal environments which is often exposed to abiotic stresses. It seems that genetic diversity in adaptive characters is the key factor for adaptation to diverse environments. In this research diversity of 500 landraces of Hordeum vulgare, in barley germplasm collection of National Plant Gene Bank of Iran (NPGBI) collected from various climatic zones were evaluated for morphological and phenological traits. The experiment was held in the research field of Seed and Plant Improvement Institute, Karaj, Iran. Traits were measured based on guidelines of Bioversity International. One-way analysis of variance indicated that, traits were significantly different between winter, facultative and spring growth types. Based on mean comparison, winter type landraces had longer growth phase (higher values in days to spike emergence and flowering). Winter and facultative landraces had more values in plant height (88.92 and 86.76 cm respectively) and Grain yield was higher in winter barley landraces. The results of multivariate analysis indicated that two-row landraces had higher kernel weight and spike length than six-row landraces, which seems to be a moderator of adverse environmental factors on yield production. The grain yield in two-row and six-row barley was not significantly different. The results in this study indicated that two-row barley landraces were generally spring type and six-row landraces had a winter type. Xerothermic coefficient of two-row barley landraces was significantly lower than six-row types, therefore it can be assumed that six-row landraces were mostly from hot and dry areas.

The standard yield stability used to measure changes is the potential yield and actual yield of a genotype in different environments. The aim of this research was to evaluate the genotype and environment interaction (GE) and detecting the sustainable genotypes in rapeseed. Also, this study aimed to determine genotypes with stable grain yield using parameters of equivalence (Wi), regression coefficient (bi), deviations mean square (S2di) and coefficient of variation (CV), (first model), and AMMI model analysis (second model). For this pupose, a field experiments was carried out with 14 winter rapeseed genotypes for two consecutive years in two different irrigation and rainfed. The expriment was performmed in a randomized complete block design with three replications per the environment. Combined analysis of variance showed that difference between the genotype-environment interaction was significant. positive correlation and significant parameters of Wi and S2di showed that both of these parameters can be used independently. According to the AMMI model, the genotypes Geronimo and ARC2 had the highest stability with a high average yield. These genotypes can be used in future breeding programs.