Understanding the factors affecting the CO 2 emission from agricultural practices is crucial for global warming.A study was performed in an apricot orchard field in the experimental farm of the Harran University,South...Understanding the factors affecting the CO 2 emission from agricultural practices is crucial for global warming.A study was performed in an apricot orchard field in the experimental farm of the Harran University,Southeast Turkey,to i) quantify weekly and seasonal variations of the CO 2 emissions from a Vertisol under apricot orchard;ii) evaluate the difference in CO 2 emission between the area under trees and rows;and iii) assess the relationships between the amounts of CO 2 emissions and environmental parameters for better use and management of the soils from the view point of carbon balance and flux in a semi-arid environment under drip irrigation.Soil CO 2 emission measurements were performed during May 2008 and May 2010,from both under tree crowns (CO 2-UC) and between tree rows (CO 2-BR),on a weekly basis in southeast Turkey with a semi-arid climate.CO 2 emissions were statistically correlated with weather and soil parameters such as air temperature,relative humidity,rainfall,soil water content,and soil temperature at various depths from 5 to 100 cm.The weekly emissions ranged from 82 to 1 110 kg CO 2 ha 1 week 1 and from 96 to 782 kg CO 2 ha 1 week 1 in CO 2-UC and CO 2-BR,respectively.Increase in CO 2 emission in the second year was due to increases in mean air and soil temperatures.The weekly and monthly cumulative CO 2 emissions were positively correlated with the air and soil temperatures.Multiple linear regression analysis explained 35% and 83% variations in average weekly and monthly CO 2 emissions,by using meteorological data.Including the interaction effects of meteorological parameters in regression equations nearly doubled the variance explained by the regression models.According to stepwise regression analysis,soil and air temperatures were found to have the most significant impact on the temporal variability of the soil CO 2 emission.展开更多
基金Supported by the Harran Universitesi Bilimsel Ara stirma Projeleri Komisyonu (HBAK),Turkey (No. 799)
文摘Understanding the factors affecting the CO 2 emission from agricultural practices is crucial for global warming.A study was performed in an apricot orchard field in the experimental farm of the Harran University,Southeast Turkey,to i) quantify weekly and seasonal variations of the CO 2 emissions from a Vertisol under apricot orchard;ii) evaluate the difference in CO 2 emission between the area under trees and rows;and iii) assess the relationships between the amounts of CO 2 emissions and environmental parameters for better use and management of the soils from the view point of carbon balance and flux in a semi-arid environment under drip irrigation.Soil CO 2 emission measurements were performed during May 2008 and May 2010,from both under tree crowns (CO 2-UC) and between tree rows (CO 2-BR),on a weekly basis in southeast Turkey with a semi-arid climate.CO 2 emissions were statistically correlated with weather and soil parameters such as air temperature,relative humidity,rainfall,soil water content,and soil temperature at various depths from 5 to 100 cm.The weekly emissions ranged from 82 to 1 110 kg CO 2 ha 1 week 1 and from 96 to 782 kg CO 2 ha 1 week 1 in CO 2-UC and CO 2-BR,respectively.Increase in CO 2 emission in the second year was due to increases in mean air and soil temperatures.The weekly and monthly cumulative CO 2 emissions were positively correlated with the air and soil temperatures.Multiple linear regression analysis explained 35% and 83% variations in average weekly and monthly CO 2 emissions,by using meteorological data.Including the interaction effects of meteorological parameters in regression equations nearly doubled the variance explained by the regression models.According to stepwise regression analysis,soil and air temperatures were found to have the most significant impact on the temporal variability of the soil CO 2 emission.
