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Analysis of the spatial and temporal trends of precipitation and temperature are pertinent for future development and sustainable management of water resources in a given region. In this paper, we present a study concerning the climatic behavior of two principal observables Variables, viz. monthly temperature (maximum and minimum) and mean precipitations obtained from the measurements carried out in 60 Iranian meteorological stations for 40 years from 1969 to 2008. The Mann-Kendall test was used to detect the significant trends.Results showed that during summer and autumn, the precipitation had a negative trend (at 5% significant level) in the south-eastern parts of Iran and this trend is less during spring, but no special trend was observed in winter. The minimum and the maximum temperatures did not have any particular trend in winter. Spring was accompanied by an increase in positive trend in the maximum temperatures in the south-west and north-east, while the minimum temperature only limited in the south-west parts. Positive and negative trends of the minimum temperature were very dispersed during the summer. The maximum temperatures had a negative trend in the north-west and no positive trend was observed at 5% significant level. During autumn, the temperatures indices had positive and negative trends with a wide range of dispersion.

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Site-selection for schools in large cities such as Tehran is a complicated problem. A multiplicity of effective factors in locating schools and increase of urban living problems in Iarge cities manifests the necessity of the use of effective, advanced, and computerized methods for this purpose. The main objectives of this research to evaluate the pattern of spatial distribution of primary schools and to identify the bereaved zones of primary school and to them in the region 6 of Tehran. Attribute data were collected and stored using the available documents, and local data were collected and digitized using linear and digitizing maps in several layers. For each layer buffers were specified, then by giving weights for each buffer zone and their combination, spatial positions of the existing schools were analyzed. Finally, the optimum sites for establishment of new schools were proposed. Results of this research showed that the majority of educational buildings of primary schools are not located in suitable sites, and their sites do not conform with site-selection standards. The results of this research also showed that the use of GIS can be very useful for ananlysis and selection of schools sites.

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The seasonal abundance patterns of the cotton aphid, Aphis gossypii Glover, in cotton fields at Gorgan in northern Iran were studied during two growing seasons of 2002 and 2003. The spatial distribution of different developmental stages and morphs of the aphid was described by fitting data to Poisson (random) and negative binomial (aggregated) dis-tributions, and calculating the dispersion indices. A sequential sampling plan was also de-veloped using the fixed-precision method of Green for estimating the density of the adult, nymph and total population. The first aphid colonies appeared on plants during late June and early July and peaked in early September when cotton plants were at the boll matu-ration and opening stages. Aphid populations, especially nymphs and apterous females, were aggregated during most of the growing season and negative binomial models fit data sets better than the Poisson series. The percentage fit for alate morphs showed a slight tendency to the Poisson distribution. With respect to sampling cost or required sample size, the developed fixed-precision sequential sampling plans showed an acceptable per-formance for estimating aphid density at the precision level of D= 0.25. The optimum sample size was flexible and depended upon the aphid density and desired level of preci-sion, and generally ranged from 10 to 513 and 62 to 3,206 at the precision levels of 0.25 and 0.10, respectively. The sequential sampling plans developed could be recommended to estimate the aphid density in integrated pest management programs.

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The population density and spatial distribution pattern of Empoasca decipiens Paoli were etermined in Tehran area, Iran, during 2004-2005 on four species of common bean Phaseolus vulgaris (L.) var. Talash, lima bean P. lunatus (L.) Savi ex Hassk. var. Sadaf, rice bean P. calcaratus Roxb. var. Goli and cowpea Vigna sinensis (L.) var. Parastoo. The higher and lower mean population densities of E. decipiens per leaf were observed on Parastoo cowpea (18.85 in 2004 and 29.94 in 2005) and Talash common bean (1.08 in 2004 and 0.37 in 2005), respectively. Spatial distribution pattern of E. decipiens was described on these four bean species using variance to mean ratios, Taylor's power aw coefficients and Iwao's patchiness regression methods. The spatial distribution pattern of this pest in most cases as aggregated and in a few cases random. In 2004, collected data were in a better fitting with aylor's model in comparison with Iwao's model on Talash common beans (r2= 0.879) as well as on Goli rice bean (r2= 0.967). Iwao's model explained the distribution data of 2004 and 2005 on Sadaf lima beans (r2= 0.746 and 0.906, respectively) more appropriately than Taylor's model (r2= 0.541 and 0.828, espectively). It is concluded that bean species influence the population density and spatial istribution pattern of E. decipiens. Spatial distribution parameters can be employed to develop a sampling program and to estimate the population density of this pest.

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Bionomics of Aphis gossypii Glover and its predators Coccinella septempunctata L. and Hippodamia variegata Goeze were studied in Varamin (Tehran Province) during 11th May to 5th October 2006 on eggplant crop, with the interaction (density dependence) between the aphid and either of the predators determined. The reliable sample size (number of leaves) with a maximum variation of 6.73% was about 56. The index of dispersion, regression models (Taylor and Iwao), Morisita’s index as well as Lloyd’s mean crowding to mean were employed to estimate the spatial distribution pattern of the insects. The results indicated that the highest population densities of A. gossypii, C. septempunctata and H. variegata occurred in 8th June (11.62 per leaf), 17th August (0.36 per leaf) and 3rd August (2.11 per leaf), respectively. The index of dispersion, regression models (Taylor and Iwao), Morisita’s index and Lloyd’s mean crowding to mean showed aggregated distribution for all species. The linear regression model between prey and predators’ population densities showed a density independent predation by C. septempunctata and H. variegata on A. gossypii. This study indicated that spatial distribution parameters of the cotton aphid and its natural enemies can be employed to outline a sampling program and to estimate the population densities of these insects for use in integrated pest management programs.

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Study of the spatial distribution of a pest and its natural enemies provides better decision tool for integrated pest management. The spatial distribution and seasonal activity of Panonychus ulmi (Koch) and its predator Zetzellia mali (Ewing) were studied in an apple orchard in Khoramdareh (Zanjan Province, Iran) during 2007. The interaction (density dependence) between the prey and its predator was determined. For P. ulmi RV (relative variation) and reliable sample size were calculated with 25 percent variation from primary sampling at 18.8% and 59 leaves, respectively. The distribution pattern of both species was analyzed using nine statistical formulae: Taylor’s power law, Iwao’s patchiness regression, index of dispersion, Morisita’s coefficient of dispersion, Lloyd’s mean crowding, David and Moore's index, Cole's index of dispersion, Green's index and coefficient of 'K' (coefficient of aggregation). The results indicated that the highest population density of P. ulmi and Z. mali were on 11 August (23.92 per leaf) and 11 September (8.2 per leaf), respectively. The slopes of Taylor's power law and Iwao's patchiness regression methods were 1.82 and 2.18 for prey and 1.39 and 1.92 for predator, respectively. These slopes had significant difference from one, indicating aggregated spatial distribution in prey and predator. The index of dispersion (ID) showed that the spatial distribution of P. ulmi in apple orchards was aggregated but it showed random distribution for Z. mali. The Morisita’s coefficient, Lloyd’s mean crowding and Green's index showed an aggregated distribution for both species. The regressions between population densities of P. ulmi and Z. mali indicated a density independent reaction of predator to the prey. The effect of temperature and humidity on the prey and predator populations was estimated. Spatial distribution parameters of the prey and predator can be used in integrated pest management programs.

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Population density and spatial distribution of Thrips tabaci Lindeman on seven soybean varieties (Williams, Tellar, Sahar, Dpx, L17, Sari and Zane) and one genotype (Ks3494) were studied in Tehran region, during 2007. The highest population density of the thrips per leaf was recorded on Dpx and on Ks3494 (0.810.05 and 0.800.05, respectively). The lowest population density was observed on L17 and Tellar (0.620.04 and 0.640.03, respectively). To estimate the spatial distribution pattern of this pest, data were analyzed through index of dispersion, Lloyd's mean crowding, Morisita's index as well as through regression models (Taylor and Iwao). The index of dispersion and Lloyd's mean crowding indicated an aggregated pattern for the spatial distribution of this insect in all the varieties and the genotype of soybean. Spatial distribution of T. tabaci using Morisita's index was aggregated in most of the sampling dates. In Taylor's model, regression between log S2 and log m was not significant for Dpx varieties (P> 0.05), but the b values of Taylor's power law on Zane, Sahar, Williams and Tellar varieties exceeded 1, indicating aggregated distribution. However, the other varieties had a b value equal to 1, indicating random distribution. Iwao's patchiness regression indicated that the spatial distribution of T. tabaci on Sari, Zane, Williams and Tellar varieties as well as on Ks3494 genotype was aggregated, but on the rest of varieties the pattern was of a random one. It is concluded that soybean varieties affect the population density and spatial distribution of T. tabaci. Spatial distribution parameters of this species can be employed to outline a sampling program as well as to estimate the population density of T. tabaci.

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Seasonal activity and spatial distribution of Eoteranychus frosti Mcgregor, Tydeus longisetosus (ElBagouy and Momen) and Zetzellia mali Ewing were studied during 9th July to 22th October 2006 in an unsprayed apple orchard, Maragheh region, Northwest of Iran. Also the density dependence interaction between preys and predator was assessed. To estimate the spatial distribution pattern of these species, data was analyzed through Iwao's patchiness regression, Taylor's power law, Morisita's coefficient, Lloyd's mean crowding and index of dispersion. Iwao’s patchiness regressions and Taylor’s power law showed a random and Morisita’s coefficient, Lloyd's mean crowding and index of dispersion revealed an aggregated distribution pattern for E. frosti, T. longisetosus and Z. mali. The results indicated that the peak density of E. frosti and T. longisetosus occurred in mid September and in late August (2.46 and 4.4 per leaf, respectively). Regarding their predator, the peak density (10.34) occurred in early July. The linear regression between prey and predator densities indicated a density independent predation by Z. mali.

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The population densities and spatial distribution patterns of Zetzellia pourmirzai Khanjani and Ueckermann and its preys Cenopalpus irani Dosse and Bryobia rubrioculus (Scheuten) were studied in a sprayed orchard in Kermanshah, a western province of Iran, from 31 May till 7 November, 2007. The interaction (density dependence) between the plant feeding mites and their predator was determined as well. Population density of the phytophagous mites and their predator were counted on 130 leaves (sampling unit) every 10 days. The mean population density of C. irani per leaf was significantly higher than that of the other mites. The population densities of C. irani, B. rubrioculus, and Z. pourmirzai were highest on 9 August (11.092 per leaf), 20 July (0.554 per leaf) and 30 July (1.385 per leaf), respectively. The index of dispersion, regression models (Taylor and Iwao), and Lloyd’s mean crowding to mean showed an aggregated distribution for all species. Some changes in the distribution from aggregated to random was indicated by Morisita’s index during different sampling dates. These changes showed that the spatial distribution of these mites can vary during the season. The smallest optimum sample sizes, calculated with Taylors' coefficients, were 20.806, 192.912, and 128.117 for C. irani, B. rubrioculus and Z. pourmirzai, respectively. Linear regression of predator to prey population densities showed a density-dependant predation by Z. pourmirzai on C. irani and on B. rubrioculus. In addition, a significant linear regression was obtained between temperature and the population fluctuations of these mites. The spatial distribution parameters of the tetranychoid mites and their predator could be used to improve sampling programs and to estimate the population densities of these mites and the efficacy of the predator being used in orchards IPM.

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Sustainable management of limited land and water resources is urgently needed to meet the increasing demand for food and to protect the environment. Land suitability analysis is a prerequisite in assessing and proposing sustainable land use alternatives for an area. Soil data are usually available at different levels of detail and stored in various forms, usually soil maps and/or soil observations. Soil data interpretation methods control the reliability of land suitability evaluation results. This has a serious effect on the reliability of the suitability maps, the subsequent land use decisions, and environmental modeling. This study examines the reliability of land suitability mapping using different methods of soil data interpretation – the average of land characteristics for field observations within soil map units (point-in-polygon) and spatial interpolation using field observations only (proximity to points). The degree of agreement between the two methods depends on the type of land utilization – rainfed barley (86%), open range (85%), improved range (75%), drip irrigated vegetables (69%), and drip irrigated trees (59%). This results from the difference in the limiting land characteristic that determines the suitability of each land utilization type and the pattern of spatial variation of each land characteristic in the field. Suitability maps for adaptable (indigenous) crops (such as barley and range crops), which require minimum farming inputs, are generally more accurate because they tolerate a wider range of variability. The interpolation method was more efficient in detecting the spatial distribution and extreme values of limiting land characteristics, resulting in more accurate suitability maps. Therefore, when detailed soil maps are not available, field observations could be used to derive suitability maps using an exact interpolation method.

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Designing the flexible investment strategies for maximizing returns under spatial variation and considering uncertainty in beef cattle investment decision-making are vital. Therefore, the objectives of the study were (i) To explore the real options and its values spatially for beef cattle investments in Turkey, and (ii) To evaluate the adequacy of government support for beef cattle investment spatially. Research data were collected from randomly selected 385 beef cattle farms by using questionnaires. The valuation of real options was assessed by using Binomial Valuation, Black-Scholes Method and Monte Carlo simulation. Tornado diagram was used for exploring sensitivity of decision variables for beef cattle investment. The results of the research showed that the classical Net Present Value (NPV) value was -200.82 thousand US $. The NPV values of the options of wait, expand, and input-output change for the beef cattle investment were US $102.37 thousand, 43.87 thousand, and 24.50 thousand, respectively. The research findings also showed that the value of real options and adequacy of government subsidies varied spatially. Based on the resuts of the sensitivity analysis, the most important variables affecting the investor's decision are carcass meat price, yield rate, capacity utilization rate, and fattening feed price, respectively. The research suggests that policy makers should consider the spatial distribution of investment subsidies and policies to the specific needs of different regions to increase efficiency of investment support policy.