Land use and season affect fluxes of CO2, CH4, CO, N2O, H2 and isotopic source signatures in Panama: evidence from nocturnal boundary layer profiles


E. Pendall, tel. +1 307 766 6293, fax +1 307 766 2851, e-mail:


Conversion of tropical rainforests to pastures and plantations is associated with changes in soil properties and biogeochemical cycling, with implications for carbon cycling and trace gas fluxes. The stable isotopic composition of ecosystem respiration (δ13CR and δ18OR) is used in inversion models to quantify regional patterns of CO2 sources and sinks, but models are limited by sparse measurements in tropical regions. We measured soil respiration rates, concentrations of CO2, CH4, CO, N2O and H2 and the isotopic composition of CO2, CH4 and H2 at four heights in the nocturnal boundary layer (NBL) above three common land-use types in central Panama, during dry and rainy seasons. Soil respiration rates were lowest in Plantation (average 3.4 μmol m−2 s−1), highest in Pasture (8.3 μmol m−2 s−1) and intermediate in Rainforest (5.2 μmol m−2 s−1). δ13CR closely reflected land use and increased during the dry season where C3 vegetation was present. δ18OR did not differ by land use but was lower during the rainy than the dry season. CO2 was correlated with other species in approximately half of the NBL profiles, allowing us to estimate trace gas fluxes that were generally within the range of literature values. The Rainforest soil was a sink for CH4 but emissions were observed in Pasture and Plantation, especially during the wet season. N2O emissions were higher in Pasture and Plantation than Rainforest, contrary to expectations. Soil H2 uptake was highest in Rainforest and was not observable in Pasture and Plantation during the wet season. We observed soil CO uptake during the dry season and emissions during the wet season across land-use types. This study demonstrated that strong impacts of land-use change on soil–atmosphere trace gas exchange can be detected in the NBL, and provides useful observational constraints for top-down and bottom-up biogeochemistry models.