Adaptive models for managing forests and nature under climate change

The inherent uncertainty related to the outcomes of climate change effects on forests, agriculture, grasslands and many natural habitats is a major challenge for decision-making both in intensively managed forests as well as the management and protection of natural habitats and the environmental services humanity derive from them.

 

It is important to understand that not only classic productive functions of forests and landscape will be subject to uncertainty and potentially dramatic changes. Also several important environmental services from forest and nature areas may be subject to dramatic changes, resulting in significant welfare changes.

 

This calls for improved decision making models and information, which explicitly takes into account uncertainty as well as the welfare economic value of environmental services.

 

The methodologies that need to be brought together are those of eco-system modelling, operations analysis, the theory of decision making under uncertainty and the economic valuation of environmental services.

 

The main scientific objectives are:

 

1. To develop adaptive decision making models, which allow (optimal) adjustments and changes in forest and nature management as the future unfolds and we learn more about the effects on eco-systems and decision options
2. To include and model the role of endogenous risk in decision making, i.e. the fact that management practises may affect the vulnerability of eco-systems to climatic changes?
3. To understand the links between climate change, land-use and ecosystem services, including their valuation and inclusion as a basis for decision making.

Adaptation studies are offer research opportunities in the methods needed to study climate change and the handling of its inherent and significant uncertainty. Studies on the effects of climate change on environmental service provision are crucial for an improved understanding of the costs of not adapting properly to climate change.

 

Contact: Professor J. Bo Larsen ()