Since CMI’s inception, the Carbon Science Group has worked on developing new tools to improve modeling of the carbon cycle. This year the Pacala and Sarmiento groups have developed new approaches to the impacts of drought and forest fires, as well as carbon cycling in the ocean.
Linking drought and tree mortality
Adam Wolf is developing models and observations that link the water cycle, and particularly drought, to the carbon cycle, particularly mortality. Wolf has developed a unique observation system that monitors the biosphere (including microclimate and tree physiology) and reports these data in real time over cellular networks using electronics designed in-house. These observations help constrain a key uncertainty in the model depiction of plant physiology, namely the sensitivity of leaf photosynthesis and evaporation to drought among diverse species. Together, this work aims to identify which species gain and which species lose in a changing climate, and what impacts these demographic shifts will have on the global carbon cycle.
Better depiction of fire in land models
Vegetation fire is a significant contributor of greenhouse gases and other compounds that affect the climate, especially in tropical nations. Sam Rabin and Elena Shevliakova are working on a model of vegetation fire that will simulate the amount of burning on different vegetation types around the world — especially on human-managed lands — for inclusion in a global climate and vegetation model. This separation of fire types, thus far unique in the fire modeling literature, will help the research community better understand how interventions might be undertaken to reduce the impact of fire on the climate. In 2012, the researchers helped develop and publish details of a method that revealed, based on maps of land cover and satellite-observed burned area, how the timing of fire activity within a year differs between agricultural and non-agricultural lands. Development of advanced methods that allow more accurate estimation of the amount of burning on cropland, pasture, and other lands is under way.
An improved model of bacterial cycling in the ocean
Sinking organic particles composed of detrital materials including dead phytoplankton and zooplankton fecal pellets are one of the main ways carbon is transported to the deep ocean as part of the biological pump. Most sinking particles are remineralized, transformed from organic carbon to CO2, in the mesopelagic zone (150 to 1000 m depth) due to the metabolic activity of heterotrophic bacteria. The Sarmiento group has developed a model to better understand the mechanisms connecting heterotrophic bacteria with these sinking particles in the mesopelagic zone. The 1-dimensional idealized model of a sinking particle includes free-living and attached heterotrophic bacteria, particulate and dissolved organic matter, extracellular enzyme, and hydrolysate. In the past year, a major development in the project has been to add quorum sensing, a signaling system used by bacteria to assess population density, to regulate extracellular enzyme production and particle detachment rates to the model. This new parameterization has dramatically improved the model predictions of carbon flux at the Bermuda Atlantic Time Series station, which is located in the North Atlantic subtropical gyre.
One of the benefits of this model is that it can be integrated with the dynamics of existing models, i.e. the Martin Curve and the ballast model, currently used in IPCC-class models to predict particle attenuation in the deep ocean. The ultimate goal of this project is to improve predictions of the effects of future climate change on carbon sequestration in the ocean.
Model development is nearing completion so the next phase will be to conduct sensitivity studies of key parameters and implement the model in geographic locations with different environmental characteristics.