2University of Helsinki, Helsinki, Finland. Martyn Futter 1*, Syed Ashraful Alam 2, Roland Baatz 3, Jaana Bäck 2, Eugenio Díaz-Pinés 4, Thomas Dirnböck 5, Martin Forsius 6, Lauren Gillespie 4, Hjalmar Laudon 7, Michael Mirtl 8, Christian Poppe 8, Marcus Schaub 9, Ute Skiba 10, Harry Veervecken 8, James Weldon 1ġSwedish University of Agricultural Sciences, Uppsala, Sweden. This study implies that a large sample size and frequent CH flux measurements are necessary for comparison with ecosystem scale fluxes of N2O by EC, and that Bayesian statistics are an appropriate method for estimating realistic means and ranges of uncertainty for CH flux data sets.ġ5 Leveraging Research Infrastructure Co-Location to Quantify Biogeochemical, Ecological and Social Constraints on Landscape-Scale Carbon Sequestration Annual cumulative fluxes by EC at a rate of 3.35 kg N ha -1 were higher than CH using the arithmetic at a rate of 2.98 kg N ha -1, and the Bayesian method at a rate of 3.13 kg N h ha -1, which quantified emission factors of 1.46 %, 1.30 % and 1.36 %, respectively. Where n ≤ 5, the Bayesian method produced large, asymmetrical uncertainties due to the difficulty of fitting an arithmetic mean from a log-normally distributed data set with few flux measurements. N2O fluxes measured by CH and EC were most comparable when flux measurements were > 115 N2O -N µg m-2 hr -1, and EC and CH measurements showed spatial and temporal alignment when CH n ≥ 15. In addition to commonly used arithmetic statistics, daily mean CH emissions were also calculated using Bayesian statistics to explicitly account for the log-normal distribution of the dataset. We assessed the variability of N2O emissions in space and time using both static chambers (CH) and eddy covariance (EC) techniques, measured at a temperate grassland site under a fertilizer management (calcium ammonium nitrate ) in 2019. Terrestrial ecosystems : A.1 GHG Fluxes at ecosystem level: Soil and Woody-tissue Rachael Murphy 1,2*, Karl Richards 1, Dominika Krol 1, Amanuel Gebrmichael 1, Luis Lopez-Sangil 1, James Rambaud 1, Gary Lanigan 1, Matthew Saunders 2ġTeagasc Research Johnstown Castle, Wexford, Ireland. Bayesian T-test showed that there was a high probability that the regions were different, with 95% credible intervals.ġ4 Assessing nitrous oxide emissions in time and space with minimal uncertainty using static chambers and eddy covariance from a temperate grassland Our results showed that there is great variability in pCO2 which was higher during spring in CCS and CC while GT had great variability in autumn-winter due to Tehuanos winds, which are inertial winds that cruise from the Gulf of Mexico to the Pacific (GT) every year in November to March. Therefore, this research aimed to describe the variation of pCO2 in this area during almost two decades. Databases from NOAA, GLODAP, LDEO, and SOCAT. We used databases with information on sea surface temperature, salinity, and the partial pressure of CO2 (pCO2) from 1993 to 2018. The study area had three regions according to their oceanographic features California Current System (CCS 22.5-34°N), Cabo Corrientes (CC 16.5-22.5° N), and Gulf of Tehuantepec (GT 9-16.5° N). The Pacific off Mexico is an extensive area in which diverse processes occur at different spatiotemporal scales, such as coastal upwelling and the confluence of different water masses, which causes great uniqueness to each region comprising the area. Marine and aquatic carbon cycling : B.2 The value chain of (surface) ocean CO2 measurements 2Centro Interdisciplinario de Investigación para el Desarrollo Integral Regional (CIIDIR Unidad Sinaloa), Guasave, Mexico Luz de Lourdes Aurora Coronado-Álvarez 1*, José Martín Hernández-Ayón 1, Orión Norzagaray-López 1, Leticia Espinosa-Carreón 2ġInstituto de Investigaciones Oceanológicas de la Universidad Autónoma de Baja California, Ensenada, Mexico. 13 Spatiotemporal variability of the pCO2 in the Pacific off Mexico
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