Carbon cycle and natural vegetation/Data uncertainties limitations

Component is implemented in:

LPJmL model (version IMAGE-LPJmL 3) Components: Carbon cycle and natural vegetation Crops and grass Water

Related IMAGE components

Agriculture and land use Atmospheric composition and climate Carbon, vegetation, agriculture and water Ecosystem services Land cover and land use

Models/Databases

HYDE database

Key publications

Müller et al., 2016a Sitch et al., 2003

References

FAO et al., 2009 Heyder et al., 2011 Schaphoff et al., 2013 Vetter et al., 2008

Flowchart Carbon cycle and natural vegetation. See also the Input/Output Table on the introduction page.

Data, uncertainty and limitations

Data

The LPJmL model uses the FAO harmonised world soil map, to provide information on soil texture and hydraulic properties (FAO et al., 2009). Climate input data come from the IMAGE climate model. Comparison of carbon stocks and fluxes with IPCC estimates shows these estimates are well within the uncertainty range. The modelled distribution of plant functional types has been found to compare well to other data sources.

Uncertainties

Although the terrestrial biosphere plays a key role in the global carbon cycle, it is also subject to considerable uncertainty. Current carbon fluxes are highly uncertain because they cannot be observed directly on a large scale, and vary considerably in time and space. Thus, all available estimates of global carbon pools and fluxes are model-based.

For the future dynamics of the terrestrial carbon cycle, additional uncertainty arises from physiological and ecological processes and interactions, which change rapidly under changing environmental conditions. As a dynamic global vegetation model, LPJmL can simulate carbon dynamics under internally computed vegetation shifts that occur in response to climate change, the impacts of land-use change, water availability and CO₂ fertilisation (Heyder et al., 2011). The most uncertain parameters in future dynamics are the combined effect of temperature and precipitation change on soil respiration, and the effect of CO₂ fertilisation. An uncertainty range for how the terrestrial biosphere may react to climate change scenarios is presented above.

Limitations

Permafrost modules have been developed to improve assessment of future climate change impacts on the carbon balance (Schaphoff et al., 2013). Impacts of weather extremes can be assessed, provided they are represented in the climate input data (e.g., heat waves, dry spells). However, only few data are available on the effects of weather extremes on the carbon balance to enable evaluation of the model’s capability in this respect. Simulation results from LPJmL calculation are within current estimates (Vetter et al., 2008). A key limitation of LPJmL 4.0 which is part of IMAGE 3.2 is that it does not yet include nutrient flows, specifically nitrogen. A recent LPJmL version does include the nitrogen which substantially improves crop yield estimates especially in relation to CO₂ fertilisation (von Bloh et al., 2018).