The ClimateForest project is a collaboration between multiple partners. It has received funding from the EU, Interreg Aurora, and the Regional Council of Lapland. Our objective is to develop new forest damaging agent prevention tools and risk management methods to support and ensure livelihood in Aurora regions in relation to forests.
Introduction
The forest damaging agents negatively affect many of the ecosystem services that forests provide, including climate regulation, production of renewable raw materials, and other provisioning, regulating, cultural, and supporting ecosystem services. Climate change-related disturbances are already impacting forest growth dramatically in parts of Europe, like the Aurora region, and these problems are estimated to increase and expand northwards. Because Aurora areas are projected to experience more dramatic temperature increases than lower latitudes, these areas will probably face more severe effects of climate change.
Project objective
The overall objective of this project is to develop new forest damaging agent prevention tools and risk management methods to support and ensure livelihood in Aurora regions in relation to forests. By decreasing the effect of damaging agents and developing new methods, the region’s economy and vitality are improved. New RDI cooperation in the forestry sector will be created and new know-how is shared. The project will generate new knowledge for short- and long-term activities to enhance living conditions in the Aurora region and contribute to sustainable ecological, social, and economic development.
impact
More sophisticated risk assessment methods can help us anticipate the occurrence and magnitude of forest disturbances under cold and Nordic conditions of the Aurora region. Current risk management methods also need to be refined to implement correct management methods. Forest owners, decision-makers, and other groups involved in forest tending need accurate information on how to manage their forests. Information about possible future climates is crucial for optimal decision-making and adaptive forest management at the stand and landscape level.
