Seasonal and diurnal dynamics of soil respiration fluxes in two typical forests on the semiarid Loess Plateau of China: Temperature sensitivities of autotrophs and heterotrophs and analyses of integrated driving factors

Partitioning of total soil respiration (RT) into autotrophic (RA) and heterotrophic (RH) components was undertaken in two typical (natural and artificial) forests on the temperate, semiarid Loess Plateau of China, to determine and compare temperature sensitivities between the two components. The natural secondary forest was dominated by oak (Quercus liaotungensis) while the artificial forest was a plantation of black locust (Robinia pseudoacacia). Soil CO2 efflux and different abiotic and biotic factors were measured during dormant and growing seasons. Temperature sensitivities of soil respiration components were investigated using the Q10 function at diurnal and seasonal scales. The temperature sensitivities of autotrophic (RA) and heterotrophic (RH) respiration varied with the time scales (daily, seasonal, or annual) of the investigation, and were affected by other biological and environmental factors. The largest contribution of RA to RT was 46% in the oak forest and 60% in the black locust plantation during the growing season. During the dormant season it was as low as 12% in the oak forest and 6% in the black locust plantation. The Q10 of RA for the black locust plantation was higher than for the oak forest during the growing season, but was lower during the dormant season. The Q10 of RA in both forests was higher than that of RH at both diurnal and seasonal scales. Multiple regression analyses suggested that photosynthesis is an important parameter in soil respiration studies and that a multiple-factor model may be more suitable during the annual periods.

► Temperature sensitivity expressed by Q10 for RA and RH varied with time scales.
► The Q10 of RA was higher than that of RH in two different forest types.
► The Q10 of RA for black locust exceeded that for oak stand only in growing season.
► Multiple factors may be used in modeling respiration at the annual time scale.