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Showing 2 results for Climatic Variables
Volume 2, Issue 4 (12-2014)
Abstract
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.
Mona Ghorbanian, Azadeh Karimi-Malati, Mahdi Jalaeian, Mahmood Fazeli Sangani,
Volume 9, Issue 4 (12-2023)
Abstract
Risk assessment is utilized to prioritize preventive measures based on the probability of dispersal success of pests. A main part of the risk assessment procedure is to determine the effects of environmental variables on the current and potential geographical distributions. In the present study, the spatial distribution of the Mediterranean pine engraver, Orthotomicus erosus (Wollaston), was mapped and predicted using MaxEnt. Presence records of O. erosus (north, northeast, west and centre of Iran), environmental and topographic variables, with the lowest correlations among themselves and the highest effects on the pest distribution were used. A total of 76 presence records of O. erosus were collected. The results of the distribution prediction modelling revealed that the northern part of Iran and the areas along the Zagros are the most suitable habitats for this species. Examining environmental variable importance on the distribution of O. erosus showed that the variables related to temperature and precipitation had more contribution in the MaxEnt model, respectively than the altitude. Furthermore, the high accuracy of the model (0.928) indicated that the MaxEnt had an acceptable performance for the prediction of O. erosus distribution. These findings would provide primary and critical information about the potential distribution of O. erosus in Iran, which could be effective for the stable population regulation of this destructive pest.
