عنوان مقاله [English]
Introduction: The increasing global consensus built on empirical evidence, expresses that the world, is facing a threat from climate change. As a result, this can affect the agricultural sector through its productivity changes and so influence food security in the world. This can be more intuitive for countries that are dependent on agriculture. Agriculture is an important sector in Iran that provides 12 percent of gross domestic production (GDP) and 21.2 percent of employment. In this country, annual crops as an important agricultural production have 12.2 million hectare cultivation areas. They are grouped into vegetables, cereals, beans, industrials crops, forage crops and cucurbits. The shares of planted aria for these groups vary in different country's regions due to cultivation conditions differences including climatic variables. This indicates the importance of studying the climatic variable effects on these shares. Therefore, this study is aimed to assess the effect of climatic variables such as temperature, participation, humidity and wind speed on land allocation between annual crop groups in Iran's counties. This can provide useful information about the effects of climatic variable on crop shares. To achieve the purpose, using statistical methods and specifically the fractional multinomial logit model is considered. This study is benefited from advantages such as using of fractional multinomial logit model, comprehensiveness and choosing the whole country as a case study and the specific crops grouping way that distinguishes it's from the other related studies in the country.
Materials and Methods: Because the shares (fractions) of annual crop cultivation area for each county(observation) are limited values that vary between 0 and 1 and the sum of them is one, using of fractional models, is considered. In these models the dependant variables vary between 0 and 1, and each observation has several fractions that their summation is one. Papke and Wooldridge (1996) introduced the fractional logit and probit models that have a tow fraction for each observation. After them, Sivakumar & Bhat (2002) introduced the multinomial fractional logit model that can include more than two fractions for each observation. These models use quasi-likelihood methods for estimation of parameters and their standard errors. For estimation of the fractional multinomial logit model, this study uses Iran's 336 counties agricultural and weather information. Annual agricultural crops information is taken from the agricultural ministry and weather information is taken from the national meteorology organization. In this regard, the crops planted area shares and weather information in 1391 are used to explain the shares of annual crops planted area shares in 1392.
Results and Discussion: Since the weather information was on monthly scale, estimation of different models with annual crop shares variables and annualy and seasonally, Weather variables (their average, standard errors and coefficient of variation) was considered for choosing the best model based on Akaike information criterion and Bayesian information criterion. Comparing the models showed that the model with annual weather variables averages is the best. So in the next step, using the model, the marginal effects were estimated. According to the result, increasing temperature has created concerns in all fields, including the agricultural sector, affects cereals and beans productions as two important sources of food in the world. It increases the planted area share of cereals and decreases the cultivation area share of beans. The participation affects all groups' cultivation area shares except cucurbits. That is the effect of cereals planted area and its share is stronger, one centigrade degree increasing of temperature increase the share of cereals cultivation area 0.02 percent. Humidity percent influences vegetables and industrial crops planted area shares and increase them. Wind speed respectively decreases and increases industrial crops and cereals cultivation area shares. According to the results also, conventional farming patterns and other agricultural system’s rules such as crop rotation in each area has important effects on the farmers' decisions on land allocations.
Conclusion: Based on the above results we can conclude that along with the climate changing, the annuals crops cultivation area shares and thus the amount of their production will be affected in the future. This shows the importance of using accurate methods to predict the possible values of climate variables in country's regions under different scenarios for next years. Because in this way, we can predict potential changes in the future annual crops productions and compare potential production and population food needs. This can determine the gaps between potential production and potential consumption in the future. In this regard, decreasing of agricultural sector problems in the face of climate change in the next decades would be possible by providing appropriate policies and procedures. One appropriate procedure is producing of resistant varieties of climate change results such as rising temperatures. This can define as one of the objectives of agricultural research centers. Considering that this research has studied the land allocation between annual crops, it is suggested to researchers that consider studying of other agriculture's sectors productions such as livestock and Fruit in the next research.