|Publication Type||Journal Article|
|Year of Publication||2011|
|Authors||Jamali, H, Jamali, H, Livesley, SJ, Dawes, TZ, Cook, GD, Assoc Prof Hutley, LB, Arndt, SK|
|Journal||Agricultural and Forest Meteorology|
|Keywords||Diurnal CH4 flux, Mound temperature, Mound water content, savanna, Seasonal CH4 flux, Termites|
Termites are estimated to contribute between <5 and 19% of the global methane (CH4) emissions. These estimates have large uncertainties because of the limited number of field-based studies and species studied, as well as issues of diurnal and seasonal variations. We measured CH4 fluxes from four common mound-building termite species (Microcerotermes nervosus, M. serratus, Tumulitermes pastinator and Amitermes darwini) diurnally and seasonally in tropical savannas in the Northern Territory, Australia. Our results showed that there were significant diel and seasonal variations of CH4 emissions from termite mounds and we observed large species specific differences. On a diurnal basis, CH4 fluxes were least at the coolest time of the day (∼07.00 h) and greatest at the warmest (∼15.00 h) for all species for both wet and dry seasons. We observed a strong and significant positive correlation between CH4 flux and mound temperature for all species. A mound excavation experiment demonstrated that the positive temperature effect on CH4 emissions was not related to termite movement in and out of a mound but probably a direct effect of temperature on methanogenesis in the termite gut. Fluxes in the wet season were 5–26-fold greater than those in the dry season. A multiple stepwise regression model including mound temperature and mound water content described 70–99% of the seasonal variations in CH4 fluxes for different species. CH4 fluxes from M. nervosus, which was the most abundant mound-building termite species at our sites, had significantly lower fluxes than the other three species measured. Our data demonstrate that CH4 flux estimates could result in large under- or over-estimation of CH4 emissions from termites if the diurnal, seasonal and species specific variations are not accounted for, especially when flux data are extrapolated to landscape scales.