Temperature Response of Respiration Across the Heterogeneous Landscape of the Alaskan Arctic Tundra

Abstract

Predictions of the response of ecosystem respiration to warming in the Arctic are not well constrained, partly due to the considerable spatial heterogeneity of these permafrost-dominated areas. Accurate calculations of in situ temperature sensitivities of respiration (Q 10 ) are vital for the prediction of future Arctic emissions. To understand the impact of spatial heterogeneity on respiration rates and Q 10 , we compared respiration measured from automated chambers across the main local polygonized landscape forms (high and low centers, polygon rims, polygon troughs) to estimates from the flux-partitioned net ecosystem exchange collected in an adjacent eddy covariance tower. Microtopographic type appears to be the most important variable explaining the variability in respiration rates, and low-center polygons and polygon troughs show the greatest cumulative respiration rates, possibly linked to their deeper thaw depth and higher plant biomass. Regardless of the differences in absolute respiration rates, Q 10 is surprisingly similar across all microtopographic features, possibly indicating a similar temperature limitation to decomposition across the landscape. Q 10 was higher during the colder early summer and lower during the warmer peak growing season, consistent with an elevated temperature sensitivity under colder conditions. The respiration measured by the chambers and the estimates from the daytime flux-partitioned eddy covariance data were within uncertainties during early and peak seasons but overestimated respiration later in the growing season. Overall, this study suggests that it is possible to simplify estimates of the temperature sensitivity of respiration across heterogeneous landscapes but that seasonal changes in Q 10 should be incorporated into model simulations.

Influences of light and humidity on carbonyl sulfide-based estimates of photosynthesis

“…Ideally, COS would be used to validate other flux-partitioning methods and to assess assumed relations, such as the relation between respiration and temperature that is used to determine GPP NEE (28). Recent studies in a temperate deciduous forest and an Arctic tundra have found that the standard flux-partitioning technique typically overestimates daytime ecosystem respiration and thereby overestimates GPP (32, 33). Here we find that GPP COS-fit is 13% higher than GPP NEE .…”

Ecosystem Scale Implication of Soil CO2 Concentration Dynamics During Soil Freezing in Alaskan Arctic Tundra Ecosystems

“…, 1980; Wilkman et al. , 2018; Zona et al. , 2011).…”

“…The organic C content in the top 100 cm of these soils ranges from 37 to 139 kg m −3 (Bockheim et al, 2004), and soil bulk density of the organic layer in the study site is 0.06 g cm -3 on average (Lipson et al, 2013). Much of the study site is patterned ground with many polygons, producing microtopographical and hydrological heterogeneity, where polygon rims (BEC) are associated with a lower water table and drier conditions, and low-centered polygons centers (BES) and troughs have a higher water table and wetter conditions (Brown et al, 1980;Wilkman et al, 2018;Zona et al, 2011). As determined by 14 C dating, the soil age of the drained lake site of this study is classified as a "medium" age (50-300 YBP, Hinkel et al, 2003); within the drained lake, soil pH values range from 5.1 at the low center polygons to 4.5 at polygon rims (Hinkel et al, 2003;Lipson et al, 2012).…”

Improved ELMv1-ECA Simulations of Zero-Curtain Periods and Cold-season CH<sub>4</sub> and CO<sub>2</sub> Emissions at Alaskan Arctic Tundra Sites

“…Other studies demonstrated that Q10 varies with environmental conditions, ecosystem types, and soil texture (Meyer et al, 2018;Graf et al, 2011;Kim et al, 2019), showing 45 a large spatial heterogeneity with generally higher values in the high-latitudinal regions (Zhou et al, 2009). In addition, Wilkman et al (2018) reported a temporal heterogeneity in Q10 over the Alaskan Arctic Tundra and suggested a higher value (e.g., 2.45) for early summer (e.g., June) but lower value (e.g., 1.58 to 1.67) for the peak growing season (e.g., July).…”