Document Type : Research Article
Authors
Yasouj university
Abstract
Introduction: Due to fossil fuels overuse, land use change, global population growth and the development of industrial activity to meet the welfare and demands of the global community, global climate has undergone gradual, but drastic, changes in the post-industrial revolution era mainly manifested in the rise of mean temperature, more frequent extreme climatic events like floods, hails, tropical storms, heat and cold waves, rising sea level, polar ice melting, droughts and etc. Climate change is a mix of dominant and lasting atmospheric characteristics of a geographic area over time and is often based on such variables as temperature, precipitation, humidity, wind, solar radiation, and number of sunny days, sea level temperature, and the thickness of ice layers at sea. Climate of a region is dedictated by a set of these factors in the long run, as well as other local characteristics such as the length of growing season and the intensity of floods whose change influences how people live and harm different sectors including agriculture and environment. Present study aimed to explore the impact of climate change on total agronomical production in 10 agro-ecological zones of Iran.
Materials and Methods: Present study employed panel data econometrics to explore the impact of climate change (mean precipitation, temperature, evapotranspiration rate, relative humidity, wind speed) on total agronomical production over the 1985-2015 periods. The panel data set included the observations related to multiple sectors and have been collected at different times. Panel data has been used when it is impossible to use just time series data or cross-sectional data. They contain more information in addition they are more diverse and have less multicollinearity between variables, so they are more efficient. In analysis of the combined data firstly should consider a certain section (e.g. country, region or province) and then focus on the attributes of the variables related to all N sections over a certain period, T. The number of data is not required to be equal over the sections (unbalanced panel model) and it is also possible to have variables that are constant in a certain section over the studied time period. In a panel data model, the variables are measured sequentially both among the sections of the statistical population and over time. In panel data, before proceeding to model estimation, we should firstly recognize whether panel or pool model is appropriate for the estimation and statistical inference. To do this, we first integrate whole data as pool to estimate the model and calculate the sum of residual squares. Then, the model is estimated as a panel model with different y-intercepts for a certain section and the residual squares are again summed. Finally, F-statistic is applied as the following equation to test the constructed model. The data were collected from Iran Meteorological Organization and Ministry of Jihad-e Agriculture. After checking the stationarity of the data, panel model with random effects has been estimated.
Results and Discussion: The results showed that total agronomical production has been influenced by temperature, evapotranspiration, and wind speed at 0.05 level and precipitation at 0.10 level. The impacts of global warming can be currently observed across the world. Agricultural sector is especially vulnerable to climate change so the rise in average seasonal temperature would shorten the growth period of most crops, causing the loss of their yields. Climate changes, such as the change in temperature, precipitation, pest and disease outbreaks adversely influence food production systems, decrease harvest and jeopardize food security. As predicted for Iran, it is expected that occurrence of climate change – which is characterized by rainfall decline, rise in temperature, and increase in the occurrence of extreme weather conditions – have harmful consequences for the agronomical production.
Conclusion: Climate change imposes remarkable economic costs on agronomical producers. The producers may have to either stop growing these crops or adapt to climate change as far as possible. In most cases, it is not economically feasible for producers to apply adaptive methods and the majority of their life aspects are potentially influenced. According to the results, it is recommended to use water pricing policies in agricultural sector that motivate farmers to use modern irrigation technologies and low irrigation-resistant cultivars, alter planting pattern towards crops with higher water use efficiency, therefore plan for and grant financial facilities, such as crop insurance, in order to prepare agronomical farmers for climate change.
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