2017]; the substantial carbon sinks forests provide are therefore potentially at risk. Hence, it is vital to quantify the effects of disturbances on the carbon balance and growth of forests to evaluate forest management options and their potential role in climate change mitigation.
The aim of this project is therefore to develop a set of disturbance modules for selected agents – wind, snow and root rot – and implement them in the climate- and management-sensitive growth model PREBAS to be applicable to the whole of Finland. The modules take into account stand characteristics, forest management and climate change effects on growth, as well as direct effects of climate change as well as management on disturbance agents.
Empirical wind and snow modules
▶ Empirical wind and snow disturbance modules are developed based on risk models under development at the Natural Resources Institute Finland (Luke) [Suvanto et al. 2019, 2020]. These models consider a range of external abiotic variables, and will be implemented in the PREBAS framework to consider model stand and management variables. As the models do not consider the intensity of disturbances, a combination of NFI data and recordings of management responses to wind and snow disturbances from the Finnish Forest Centre is used to quantify impacts and management reactions.
Process-based wind module
▶ The empirical wind risk model will be extended with the process-based HWIND wind disturbance model [Peltola et al. 1999, Honkaniemi et al. 2017], which will allow for a more precise estimation of the effects of climate change on wind susceptibility due to changes in the soil frost period, and hence tree anchorage. In addition, the module will supply an interface to the effects of root rot on wind susceptibility. HWIND will be adapted by predicting wind disturbance for a set of stand configurations, and a regression model of the predicted susceptibility will be implemented in PREBAS. The possibility ofa hybrid model combining the empirical and process-based approaches will be explored.
Hybrid root rot module
▶ The general risk of root rot infection will be based on an empirical model currently under development at Luke [Honkaniemi et al. in preparation]. Infection development will be simulated using the process-based root rot model Hmodel [Honkaniemi et al. 2017]; harvests and wind and snow disturbances will be considered potential points of entry for infections. Feedbacks to PREBAS and other disturbance modules will include growth reductions, timber devaluation and decreased resistance to wind.
Seidl, R., Thom, D., Kautz, M., Martin-Benito, D., Peltoniemi, M., Vacchiano, G., Wild, J., Ascoli, D., Petr, M., Honkaniemi, J., Lexer, M.J., Trotsiuk, V., Mairota, P., Svoboda, M., Fabrika, M., Nagel, T.A., Reyer, C.P.O., 2017. Forest disturbances under climate change. Nature Climate Change 7, 395–402.
Suvanto, S., Peltoniemi, M., Tuominen, S., Strandström, M., & Lehtonen, A. 2019. High-resolution mapping of forest vulnerability to wind for disturbance-aware forestry. Forest Ecology and Management, 453, 117619.
Suvanto S., Lehtonen A., Nevalainen S., Lehtonen I., Viiri H., Strandström M., & Peltoniemi, M. 2020. Mapping forest sensitivity to snow disturbances in Finland. Preprint. bioRxiv 2020.12.23.424139.
Peltola, H., Kellomäki, S., & Väisänen, H. 1999. A mechanistic model for assessing the risk of wind and snow damage to single trees and stands of Scots pine, Norway spruce, and birch. Canadian Journal of Forest Research, 29, 647–661.
Honkaniemi, J., Lehtonen, M., Väisänen, H., & Peltola, H. 2017. Effects of wood decay by Heterobasidion annosum on the vulnerability of Norway spruce stands to wind damage: a mechanistic modelling approach. Canadian Journal of Forest Research, 47(6), 777–787.
Honkaniemi, J., Henttonen, H., Lehtonen, A. & Peltoniemi, M. (in preparation). The effects of historical land-use and forest management on root rot abundance in Finland. Manuscript under preparation.