Determination of the carbon budget of a pasture: effect of system boundaries and flux uncertainties

Abstract

Abstract. Carbon (C) sequestration in the soil is considered as a potential important mechanism to mitigate greenhouse gas (GHG) emissions of the agricultural sector. It can be quantified by the net ecosystem carbon budget (NECB) describing the change of soil C as the sum of all relevant import and export fluxes. NECB was investigated here in detail for an intensively grazed dairy pasture in Switzerland. Two budget approaches with different system boundaries were applied: NECB tot for system boundaries including the grazing cows and NECB past for system boundaries excluding the cows. CO 2 and CH 4 exchange induced by soil/vegetation processes as well as direct emissions by the animals were derived from eddy covariance measurements. Other C fluxes were either measured (milk yield, concentrate feeding) or derived based on animal performance data (intake, excreta). For the investigated year, both approaches resulted in a small near-neutral C budget: NECB tot −27 ± 62 and NECB past 23 ± 76 g C m −2 yr −1 . The considerable uncertainties, depending on the approach, were mainly due to errors in the CO 2 exchange or in the animal-related fluxes. The comparison of the NECB results with the annual exchange of other GHG revealed CH 4 emissions from the cows to be the major contributor in terms of CO 2 equivalents, but with much lower uncertainty compared to NECB. Although only 1 year of data limit the representativeness of the carbon budget results, they demonstrate the important contribution of the non-CO 2 fluxes depending on the chosen system boundaries and the effect of their propagated uncertainty in an exemplary way. The simultaneous application and comparison of both NECB approaches provides a useful consistency check for the carbon budget determination and can help to identify and eliminate systematic errors.

Modeling Carbon and Water Fluxes of Managed Grasslands: Comparing Flux Variability and Net Carbon Budgets between Grazed and Mowed Systems

“…Over the study period, the site experienced large variations in temperature, moisture availability, and radiation, which are controlling factors of the exchange rates between the atmosphere and grasslands of CO 2 [87][88][89][90] and water fluxes [91]. In addition, grazing and cutting dramatically alter the way managed grassland ecosystems respond to climate drivers by the sharp removal of large amounts of live biomass [36,92,93] and thus strongly affect the seasonal and inter-annual variabilities of gas exchanges and the annual carbon budgets of the farm/paddock [22,79,94].…”

“…In this study, we showed that the direct effect of grazing (i.e., the reduction of photosynthesizing biomass [22]) was properly captured in EC data but that the indirect effect (i.e., grazing animals' respiration [22]) was not captured by EC systems because of the stochastic position of cows and shifts in the flux footprint area. To fully understand why grazers' respiration is not accounted for and to find a way to correct EC data for this bias, using a biochemical, process-based ecosystem model incorporating management practices, like CenW, alongside dairy cows positioning devices and detailed flux footprint information, could be necessary [79,94].…”

Herd position habits can bias net CO2 ecosystem exchange estimates in free range grazed pastures

“…representative way suggesting that there were no correlations between the animal positions and the 109 wind direction. However, this result is site specific and such observations has yet to be verified for 110 continuously grazed pastures (Felber et al, 2016a). In those sites the animals are allowed to move 111 freely in the pasture so that, if cattle are more likely to remain grouped in specific areas of the pasture 112 such as shade areas or near water/feed supplies, which is very probable, NEE tot would be biased in a 113 way and to an extent that depends on the position of these specific areas relative to the footprint.…”

“…He proposed to filter out the fluxes from paddocks affected by cattle respiration, compute 95 NEE past , and account for the biomass ingested by the animals as C exports and the animal excretions as 96 C imports, thereby considering cattle to be external to the system. More recently, several studies also 97 identified this problem and adapted their methodology to exclude grazer respiration and thus, compute 98 NEE past (Felber et al, 2016a;Hunt et al, 2016;Rutledge et al, 2017aRutledge et al, , 2017b. Kirschbaum et al, 99 (2015) also highlighted the need to filter fluxes in the presence of high stocking density in the 100 footprint in order to obtain good agreement between modelled and measured CO 2 fluxes in a 101 rotationally grazed pasture.…”

“…In short rotation grazing sites, the 598 regrowth can be considered negligible, making the computation of C intake easier and more reliable 599 (Skinner, 2008). Another option to compute C intake is to estimate the energy requirements of the 600 animals for maintenance, activity, and grazing and convert this energy into dry matter intake (and then 601 C intake ) (IPCC, 2006) or, for dairy cows, using equations based on milk yields and the lactation week of 602 the cows, as proposed by Felber et al (2016a). 603 5 Conclusions and recommendations 604 The results of this study highlight the necessity to carefully check if cow respiration is measured in a 605 representative way by the EC system when dealing with grazed pastures.…”