Overstory and Understory CO2 and Energy Fluxes of a Black Spruce Forest in Interior Alaska

Abstract:

Eddy covariance techniques were used to quantify understory contributions to carbon and energy balances, and to evaluate the environmental responses of the overstory and understory at a black spruce forest in interior Alaska. Net ecosystem productivity (NEP), gross primary productivity (GPP), ecosystem respiration (RE), sensible heat flux (H), and latent heat flux (LE) were estimated for the ecosystem (subscripted by ‘eco’), canopy (subscripted by ‘cano’) and forest floor (subscripted by ‘floor’) based on canopy gap fraction and footprint analyses for 3 years, 2011 - 2013. Fluxes per unit land surface area of black spruce overstory (subscripted by ‘b’) and that of understory (subscripted by ‘u’) were also evaluated their ecophysiological responses to micrometeorological environments. Overall, NEP_floor, GPP_floor, RE_floor and LE_floor represented 60 (37, growing season in parenthesis) %, 47 (51) %, 47 (54) %, and 75 (76) % of NEP_eco, GPP_eco, RE_eco, and LE_eco, respectively with the average canopy gap fraction of 0.52 (± 0.073 SD). The year, 2013 was characterized by high air temperature and vapor pressure deficit (VPD) during the growing season. The high temperature and VPD particularly reduced understory NEP and their growth inferred by low green excessive index (GEI), which was correlated to GPP_u more strongly than GPP_b. LE_u linearly increased with vapor pressure deficit (VPD) whereas LE_b was insensitive to VPD. Future warming and drying expected in the boreal forest will increase understory evapotranspiration disproportionately to that of black spruce and likely decrease the production of the current understory community.

Acknowledgments This study was supported by the Japan Aerospace Exploration Agency (JAXA) and the JAMSTEC-IARC Collaboration Study, with funding provided by the Japan Agency for Marine-Earth Science and Technology (JAMSTEC) to the International Arctic Research Center (IARC). The Polar Geospatial Center, University of Minnesota provided the Quick Bird Image as a support for the NSF grand number 1107524. HI acknowledges J. H. Matthes for helping the footprint algorism, R. Hirata, D. McGuire, and E. Euskirchen for fruitful discussion, and Y. Harazono and H. Nagano for providing parts of meteorological data. We thank N. Bauer for editing.