A multi-hazard evaluation of climate change impacts on forests in Finland using impact response surfaces

We developed a new approach to climate change impact and adaptation analysis at regional level in Finland in close collaboration with stakeholders (Carter & Fronzek 2022, Fronzek et al. 2022). It advances methods of analysis by applying impact models across sectors within a standard analytical framework for representing three aspects of relevance for policy: (i) sensitivity: examining the sensitivity of the sectors to changing climate by constructing impact response surface of relevant indicators; (ii) urgency: estimating risks of approaching or exceeding key thresholds of impact under alternative scenarios as a basis for determining urgency of response; and (iii) response: determining the effectiveness of potential adaptation and mitigation responses.

The approach is demonstrated by evaluating multi-hazards to ecosystems with risk indicators of drought, fire and pest outbreaks estimated with the process-based forest growth model PREBAS. Forest productivity for locations in Finland was simulated for systematic perturbations in temperature and precipitation, and results were plotted as impact response surfaces (IRS) that depict the model sensitivity to changes in climate in a scenario-neutral manner. IRSs were overlaid with probabilistic projections of climate change to estimate likelihoods of exceeding critical impact thresholds.

Our results indicate that more severe climate change and rising CO₂ levels increase growth and carbon uptake, but also the risk of disturbances. The net biome exchange is strongly related to harvest levels, but combined effects of climate change and forest management are complex and vary regionally. Our impact response surface approach helps to stress-test and improve sector-based models and provides a framework for model intercomparison. It can also be used, for example, to study multi-hazard impacts.

References:

Carter T.R. and S. Fronzek (2022) A model-based response surface approach for evaluating climate change risks and adaptation urgency. In: Kondrup C. et al. (eds) Climate Adaptation Modelling, Springer Climate. Springer, Cham., p. 67-75, doi:10.1007/978-3-030-86211-4_9

Fronzek, S., Y. Honda, A. Ito, J.P. Nunes, N. Pirttioja, J. Räisänen, K. Takahashi, E. Terämä, M. Yoshikawa and T.R. Carter (2022) Estimating impact likelihoods from probabilistic projections of climate and socio-economic change using impact response surfaces. Climate Risk Management 38, 100466, doi:10.1016/j.crm.2022.100466