Combining multiple statistical methods to evaluate the performance of 
process-based vegetation models across three forest stands

Horemans, J. A.; Henrot, A.; Delire, C.; Kollas, C.; Lasch-Born, P.; Reyer, C.; Suckow, F.; François, L.; Ceulemans, R.

doi:10.1515/forj-2017-0025

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Combining multiple statistical methods to evaluate the performance of process-based vegetation models across three forest stands

Authors

Horemans, J. A.
Potsdam Institute for Climate Impact Research and Cooperation Partners;

Henrot, A.
Potsdam Institute for Climate Impact Research and Cooperation Partners;

Delire, C.
Potsdam Institute for Climate Impact Research and Cooperation Partners;

Kollas, C.
Potsdam Institute for Climate Impact Research and Cooperation Partners;

Lasch-Born, P.
Potsdam Institute for Climate Impact Research and Cooperation Partners;

Reyer, C.
Potsdam Institute for Climate Impact Research and Cooperation Partners;

Suckow, F.
Potsdam Institute for Climate Impact Research and Cooperation Partners;

François, L.
Potsdam Institute for Climate Impact Research and Cooperation Partners;

Ceulemans, R.
Potsdam Institute for Climate Impact Research and Cooperation Partners;

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Citation

Horemans, J. A., Henrot, A., Delire, C., Kollas, C., Lasch-Born, P., Reyer, C., Suckow, F., François, L., Ceulemans, R. (2017): Combining multiple statistical methods to evaluate the performance of process-based vegetation models across three forest stands. - Central European Forestry Journal, 63, 4, 153-172.
https://doi.org/10.1515/forj-2017-0025

Cite as: https://publications.pik-potsdam.de/pubman/item/item_21942

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