Upscaling soil-atmosphere CO2 and CH4 fluxes across a topographically complex forested landscape

Abstract

Upscaling soil-atmosphere greenhouse gas (GHG) fluxes across complex landscapes is a major challenge for environmental scientists and land managers. This study employs a quantile-based digital soil mapping approach for estimating the spatially continuous distributions (2 m spatial resolution) and uncertainties of seasonal mean mid-day soil CO2 and CH4 fluxes. This framework was parameterized using manual chamber measurements collected over two years within a temperate forested headwater watershed. Model accuracy was highest for early (r2 = 0.61) and late summer (r2 = 0.64) for CO2 and CH4 fluxes. Model uncertainty was generally lower for predicted CO2 fluxes than CH4 fluxes. Within the study area, predicted seasonal mean CO2 fluxes ranged from 0.17 to 0.58 μmol m−2 s−1 in winter, and 1.4 to 5.1 μmol m−2 s−1 in early summer. Predicted CH4 fluxes across the study area ranged from −0.52 to 0.02 nmol m−2 s−1 in winter, and −2.1 to 0.61 nmol m−2 s−1 in early and late summer. The models estimated a per hectare net GHG potential ranging from 0.44 to 4.7 kg CO2 eq. hr−1 in winter and early summer, with an estimated 0.4 to 1.5% of emissions offset by CH4 uptake. Flux predictions fell within ranges reported in other temperate forest systems. Soil CO2 fluxes were more sensitive to seasonal temperature changes than CH4 fluxes, with significant temperature relationships for soil CO2 emissions and CH4 uptake in pixels with high slope angles. In contrast, soil CH4 fluxes from flat low-lying areas near the stream network within the watershed were significantly correlated to seasonal precipitation. This study identified key challenges for modeling high spatial resolution soil CO2 and CH4 fluxes, and suggests a larger spatial heterogeneity and complexity of underlying processes that govern CH4 fluxes.