Articles | Volume 9, issue 11
Geosci. Model Dev., 9, 4169–4183, 2016
Geosci. Model Dev., 9, 4169–4183, 2016

Model evaluation paper 22 Nov 2016

Model evaluation paper | 22 Nov 2016

Forest soil carbon stock estimates in a nationwide inventory: evaluating performance of the ROMULv and Yasso07 models in Finland

Aleksi Lehtonen1, Tapio Linkosalo1, Mikko Peltoniemi1, Risto Sievänen1, Raisa Mäkipää1, Pekka Tamminen1, Maija Salemaa1, Tiina Nieminen1, Boris Ťupek1, Juha Heikkinen1, and Alexander Komarov2,† Aleksi Lehtonen et al.
  • 1Natural Resources Institute Finland, Natural resources and bioproduction, (LUKE), P.O. Box 2, 00791 Helsinki, Finland
  • 2Institute of Physicochemical and Biological Problems in Soil Science of the Russian Academy of Sciences, 142290 Institutskaya ul., 2, Pushchino, Moscow, Russian Federation
  • deceased

Abstract. Dynamic soil models are needed for estimating impact of weather and climate change on soil carbon stocks and fluxes. Here, we evaluate performance of Yasso07 and ROMULv models against forest soil carbon stock measurements. More specifically, we ask if litter quantity, litter quality and weather data are sufficient drivers for soil carbon stock estimation. We also test whether inclusion of soil water holding capacity improves reliability of modelled soil carbon stock estimates. Litter input of trees was estimated from stem volume maps provided by the National Forest Inventory, while understorey vegetation was estimated using new biomass models. The litter production rates of trees were based on earlier research, while for understorey biomass they were estimated from measured data. We applied Yasso07 and ROMULv models across Finland and ran those models into steady state; thereafter, measured soil carbon stocks were compared with model estimates. We found that the role of understorey litter input was underestimated when the Yasso07 model was parameterised, especially in northern Finland. We also found that the inclusion of soil water holding capacity in the ROMULv model improved predictions, especially in southern Finland. Our simulations and measurements show that models using only litter quality, litter quantity and weather data underestimate soil carbon stock in southern Finland, and this underestimation is due to omission of the impact of droughts to the decomposition of organic layers. Our results also imply that the ecosystem modelling community and greenhouse gas inventories should improve understorey litter estimation in the northern latitudes.

Short summary
It is known that Earth system models have challenges to predict correct levels of soil carbon stocks. Quantification of those stocks is a prerequisite for reliable prediction of future carbon exchange between biosphere and atmosphere. Here, we tested Yasso07 and ROMULv soil carbon models against empirical data from Finland. We found that both the role of understorey vegetation and the impact of drought to decomposition should be incorporated into soil models to have realistic soil carbon stocks.