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How to not miss the forests for the trees: Implementing a dynamic forest harvest model in a global multisector dynamics model under alternative scenarios.

Presentation Date
Wednesday, December 13, 2023 at 2:10pm - Wednesday, December 13, 2023 at 6:30pm
Location
MC - Poster Hall A-C - South
Authors

Author

Abstract

Various studies have found that forest management can be an effective strategy for carbon management. Forests are also an important economic resource since they are a source for supply of roundwood and wood fuel. In some regions of the world, forests are also increasingly being cleared to make more land available for agriculture. These factors make effectively representing forest management decisions such as planting and harvesting important. Here, we implement a dynamic forest harvest model in a global state of the art multi sector dynamics model, namely the Global Change Analysis Model (GCAM). We implement a forest harvest model which is based on the age vintages for stands of trees. This new model generates rotation ages for forest harvest that are responsive to changes in wood prices. Furthermore, the forest sector in GCAM competes for investment with other types of land use in each future time step based on harvest profit. We find that with the new forest harvest model the current global wood demand in GCAM can be met with less loss of forest cover (approx. 500 thous km2) through effective management of vintages. We find that deforestation is a much higher risk to forest cover (especially old growth and secondary re-growth forests) especially in regions where food demand is expected to rise. Under climate forcing scenarios where terrestrial carbon is assigned a carbon price (which typically promotes increased afforestation), we find that old growth and secondary re-growth forests can be protected through adjusting rotation ages of harvested forests. Also, under climate forcing scenarios, we find that new plantations can cover up to 38% of all forests globally by the end of the century (i.e. 2100) as compared to 7% under a business as usual scenario.

Funding Program Area(s)