Applied and empirical forest-management models focus on the periodically applied forest-management techniques. In addition to modelling the prevailing practices and thereby baseline, they are fundamental in computing the increased carbon sequestration due to the isolated carbon offset action.

These applied models suffer from the same general problems as the growth models (lack of long-term accuracy, trade-off between predictability and uncertainty etc.), but also from very specific ones. They introduce periodicity to the problem – every so often a forest management technique is applied (fertilizing/weeding/thinning…) and these are techniques are optimized again in the subsequent period. Therefore, their underling modelling error is compounded by optimization, again in particularly over very long horizons. Also, and crucially from carbon perspective, they generally do not account for technique’s indirect impact on carbon stocks or unintended releases. Therefore, Aurora Forealis must also consider how these applied modelling approaches need to be refined (our actual approach described in the section below under Tapio).