Ecosystem modelling

The carbon cycle of natural terrestrial ecosystems has been estimated with two models – Land ecosystem model JSBACH and semi-empirical stand flux model PREBAS. The models differ in how they describe photosynthesis and account for land ecosystem types and land area. Neither of the models include explicitly the impact of nitrogen on the photosynthetic capacity.

Land ecosystem model JSBACH

JSBACH accounts for the exchange of water and carbon dioxide between natural terrestrial surfaces and the atmosphere [1]. It is part of the earth system model of the Max Planck institute [2]. JSBACH describes the biogeophysical processes that regulate the balances of water and carbon dioxide. The storage of water and carbon into the ecosystem as well as their release to the atmosphere are regulated by the climatic variables.

In addition to the magnitude of the ecosystem stocks and the climatic state, the net exchange rate of the quantities depends on the properties of the ecosystem. In JSBACH the vegetation is divided into functional types with separable characteristic properties. The areal distribution of the plant functional types is set according to the current situation in Finland. The Finnish soil carbon model Yasso07 [3], [4], [5] have been implemented to JSBACH to account for the fate of carbon in the soil storages.

Prior to the runs with the climate scenario data the ecosystem and soil carbon stocks have been first set to an equilibrium with the preindustrial atmospheric carbon content and then the carbon stocks have been further developed with increasing atmospheric carbon content and current climate. The JSBACH impact estimates in Climate guide only include the natural ecosystems while cultivated fractions are excluded from the visualizations. The results are given per total land area.

Stand flux model PREBAS

PREBAS is a forest model system developed at the University of Helsinki, with the objective of making future projections of a given forest stand with known initial state under alternative management options. In order to allow for applications over large geographical areas accounting for observed forest properties and management options, the model was constructed to be as simple as possible in structure, yet based on biologically sound assumptions. The model is based on carbon fluxes and stocks between the atmosphere and the forest ecosystem. The system is modular, such that modules can be used either independently or linked, where the carbon fluxes determine the linkages.

PREBAS estimates canopy photosynthesis and evapotranspiration from daily environmental drivers and stand properties (module PRELES) [6], [7]. It computes stand growth model based on carbon acquisition and allocation in trees (module CROBAS) [8], [9]. The model has been further combined with the Finnish soil carbon model Yasso07 [3]. All modules have been independently tested and calibrated against data from eddy flux stations, forest experiments and inventories, and soil processes.

For the Climateguide.fi simulations we used multisource inventory data of 2013 from the Finnish Natural Resources institute to initialise the simulations. Because our focus was on climate impacts rather than management, we considered each simulated 30-year period as if starting from the same initial state. During the 30 years, we assumed that 60% of commercial forest area was managed using current management recommendations while no management was done in the rest. The forest data resolution is 16 x 16 m2 which was first used to classify the forest on the basis of factors like species, site type, mean height and volume. The simulations were done for each subclass in grid cells of size 8 x 8 km2 which was the resolution of the climate data. The results are presented as averages in these 8 x 8 km2 grid cells per area of 8 km block. The results are presented both per unit land area.

Soil carbon model Yasso07

The soil carbon model Yasso07 describes the release of carbon dioxide as a consequence of leaf litter decomposition [3], [4], [5]. The model assumes that different types of carbon compounds in the soil decompose at different speeds. In addition to the air temperature, the decomposition speed is affected by moisture in the soil, for example. The model calculates the changes in the stock of soil organic carbon and the amount of carbon dioxide released from the soil over a specific period of time. The Yasso model is used for the greenhouse gas calculations in Finland and some other countries. In addition, the model is widely used in research [10].

 

1.11.2017 (The article has been updated in MONIMET project funded by LIFE+ programme.)

References

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  2. Giorgetta, M. A., Jungclaus, J., Reick, C. H., Legutke, S., Bader, J., Böttinger, M., Brovkin, V., Crueger, T., Esch, M., Fieg, K., Glushak, K., Gayler, V., Haak, H., Hollweg, H.-D., Ilyina, T., Kinne, S., Kornblueh, L., Matei, D., Mauritsen, T., Mikolajewicz, U., Mueller, W., Notz, D., Pithan, F., Raddatz, T., Rast, S., Redler, R., Roeckner, E., Schmidt, H., Schnur, R., Segschneider, J., Six, K. D., Stockhause, M., Timmreck, C., Wegner, J., Widmann, H., Wieners, K.-H., Claussen, M., Marotzke, J. & Stevens, B. 2013. Climate and carbon cycle changes from 1850 to 2100 in MPI-ESM simulations for the Coupled Model Intercomparison Project phase 5, Journal of Advances in Modeling Earth Systems, Volume 5, Issue 3: 572–597. http://doi.org/10.1002/jame.20038
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  4. Tuomi, M., Laiho, R., Repo, A. & Liski, J. 2011. Wood decomposition model for boreal forests. Ecological Modelling, Volume 222, Issue 3: 709–718. http://doi.org/10.1016/j.ecolmodel.2010.10.025
  5. Goll, D. S., Brovkin, V., Liski, J., Raddatz, T., Thum, T. & Todd-Brown, K. E. O. 2015. Strong dependence of CO2 emissions from anthropogenic land cover change on initial land cover and soil carbon parametrization. Global Biogeochemical Cycles, 29, 1511–1523. https://doi.org/10.1002/2014GB004988
  6. Peltoniemi M., Pulkkinen M., Aurela M., Pumpanen J., Kolari P. & Mäkelä A., 2015. A semi-empirical model of boreal forest gross primary production, evapotranspiration, and soil water – calibration and sensitivity analysis. Boreal Environment Research, Volume 20, Number 2: 151–171. http://www.borenv.net/BER/pdfs/ber20/ber20-151.pdf
  7. Minunno, F., Peltoniemi, M., Launiainen, S., Aurela, M., Lindroth, A., Lohila, A., Mammarella, I., Minkkinen, K., Mäkelä, A., 2016. Calibration and validation of a semi-empirical flux ecosystem model for coniferous forests in the Boreal region. Ecological Modelling, Volume 341: 37–52. http://doi.org/10.1016/j.ecolmodel.2016.09.020
  8. Mäkelä, A. 1997. A carbon balance model of growth and self-pruning in trees based on structural relationships. Forest Science, Volume 43, Number 1: 7–-24. http://www.ingentaconnect.com/content/saf/fs/1997/00000043/00000001/art00004
  9. Valentine, H. T. & Mäkelä, A. 2005. Bridging process-based and empirical approaches to modeling tree growth. Tree Physiology, Volume 25, Issue 7:769–779. http://doi.org/10.1093/treephys/25.7.769
  10. Finnish meteorological institute. 9.2.2017. Soil carbon model - Yasso. [Refered 4.7.2017.] http://en.ilmatieteenlaitos.fi/yasso

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