Identifying suitable species compositions to mitigate economic risks under climate change

Abstract

European forestry has always faced high uncertainties, including those related to future wood prices and risk of forest damages. Climate change will most likely add further uncertainty, for example by altering growth patterns and tree mortality. To reduce the adverse effects of climate change on forest enterprises, a change in forest composition towards more climate-tolerant species is often recommended. However, this could lead to financial losses if the selected species are economically less attractive, whereas the actual consequences of climate change remain uncertain. An open question is therefore which tree species compositions are most efficient to balance risks and economic returns. The research presented here aims to identify forest management strategies that are economically robust in the face of market and climate risks. For this purpose we present a mechanistic simulation and modelling approach to optimize tree species compositions for example forest enterprises in Germany. This method combines portfolio theory with novel mathematical programming techniques. To quantify the effect of climate change we build on updated survival rates from potential analogue climates. The approach allows us to quantify the economic consequences of climate change when accounting for the buffering effect of tree species diversification and the adaptation of forest composition.