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Publikasjoner

NIBIOs ansatte publiserer flere hundre vitenskapelige artikler og forskningsrapporter hvert år. Her finner du referanser og lenker til publikasjoner og andre forsknings- og formidlingsaktiviteter. Samlingen oppdateres løpende med både nytt og historisk materiale. For mer informasjon om NIBIOs publikasjoner, besøk NIBIOs bibliotek.

2019

Sammendrag

The Jena Soil Model (JSM) is a multi-layer mechanistic soil biogeochemistry model with explicit representations of vertical transport, mineral sorption, and microbial control on decomposition rates. Reaction rates are further modified by temperature and moisture. While temperature determines the maximum reaction velocity (Vmax), moisture reduces this rate nonlinearly if either the diffusion of substrate is restricted (at low soil moisture) or oxygen availability for microbes is limited (at wet conditions). This moisture control on soil organic matter formation and decomposition is represented with the Dual Arrhenius Michaelis-Menten (DAMM) model concept (Davidson et al. 2012) and influences the reaction rates of microbial depolymerisation of litter and microbial residue pools as well as DOC (dissolved organic matter) uptake. Sorption of DOM and microbial residues to mineral surfaces is moisture dependent through a Langmuir sorption approach. We will validate the carbon cycle representation of moisture control on soil organic matter decomposition in JSM by comparing simulations with measured carbon stocks and respiration rates from different ecosystems ranging from boreal upland forests and wetlands to Mediterranean savannas. The modular structure of JSM will allow us to investigate the effect of moisture control on each decomposition step (depolymerisation, microbial uptake and growth, and OC sorption) separately.

Sammendrag

The role of soil moisture on organic matter decomposition remains poorly understood and underrepresented in coupled global climate models. Traditionally, organic matter decomposition is represented as simple first- or second order kinetics in such models, using mostly empirical functions for temperature and moisture controls, and without considering microbial interactions. We use the Dual Michaelis-Menten (DAMM) model (Davidson et al. 2012) to simulate simultaneous temperature and moisture controls on decomposition rates. Microbial controls on decomposition in relation to changes in soil moisture and temperature are implicitly simulated with DAMM: Soil moisture affects the available substrate (SOC) and oxygen available for decomposition and reduces the maximal, temperature driven decomposition rate (Vmax). We apply the DAMM model on vertically resolved data from the most recent coupled model intercomparison project (CMIP5) and gridded global SOC values (SoilGrids). We study the potential decomposition rates for a historic period (1976 - 2006) and a period under the RCP8.5 climate change scenario (2070-2099) for 5 soil layers up to 1m depth. Our key finding is that the inclusion of soil moisture controls has diverging effects on both the speed and direction of projected decomposition rates, compared to a temperature-only approach. The majority of these changes are driven by soil moisture through substrate limitation, rather than oxygen diffusion limitation. In deeper soil layers, oxygen diffusion limitation plays a stronger role. Our study highlights the need for inclusion of soil moisture interactions in coupled global climate models. Our findings could be particularly important for boreal soils, which store a major fraction of Earth’s SOC stocks and where temperature increases and soil moisture changes are expected to be largest.