The aim of this study was to construct a nationwide stand age model by using National Forest Inventory (NFI) data and nationwide airborne laser scanning (ALS) data. In plantation forestry, age is usually known. While this is not the case in boreal managed forests, age is still seldom predicted in forest management inventories. Measuring age accurately in situ is also very laborious. On the other hand, tree age is one of the accurately measured sample tree attributes in NFI field data. Many countries also have a nationwide coverage of airborne laser scanning (ALS) data. In this study, we merged these data sources and constructed a nationwide, area-based model for stand age.

While constructing the model, we omitted old forests from the data, since the correlation between ALS height metrics and stand age diminished at stands with age > 100 years. Additionally, the effect of growth conditions was considerable, so we also utilized different geographical and NFI variables such as site fertility and soil type in the modeling. The resultant nationwide model for the stand age of managed forests yielded a root mean square error (RMSE) of about 14 years. The model could be improved further by additional forest structure variables, but such information may not be available in practice.

The results showed that the prediction of stand age by ALS, geographical and NFI information was challenging, but still possible with moderate success. This study is an example of the joint use of NFI and nationwide ALS data and re-use of NFI data in research.

The occurrence of aspen trees increases the conservation value of mature conifer dominated forests. Aspens typically occur as scattered individuals among major tree species, and therefore the inventory of aspens is challenging.

We characterized aspen populations in a boreal nature reserve using diameter distribution, spatial pattern, and forest attributes: volume, number of aspens, number of large aspen stems and basal area median diameter. The data were collected from three separate forest stands in Koli National Park, eastern Finland. At each site, we measured breast height diameter and coordinates of each aspen. The comparison of inventory methods of aspens within the three stands was based on simulations with mapped field data. We mimicked stand level inventory by locating varying numbers of fixed area circular plots both systematically and randomly within the stands. Additionally, we also tested if the use of airborne laser scanning (ALS) data as auxiliary information would improve the accuracy of the stand level inventory by applying the probability proportional to size sampling to assist the selection of field plot locations.

The results showed that aspens were always clustered, and the diameter distributions indicated different stand structures in the three investigated forest stands. The reliability of the volume and number of large aspen trees varied from relative root mean square error figures above 50% with fewer sample plots (5–10) to values of 25%–50% with 10 or more sample plots. Stand level inventory estimates were also able to detect spatial pattern and the shape of the diameter distribution. In addition, ALS-based auxiliary information could be useful in guiding the inventories, but caution should be used when applying the ALS-supported inventory technique.

This study characterized European aspen populations for the purposes of monitoring and management of boreal conservation areas. Our results suggest that if the number of sample plots is adequate, i.e. 10 or more stand level inventory will provide accurate enough forest attributes estimates in conservation areas (minimum accuracy requirement of RMSE% is 20%–50%). Even for the more ecologically valuable attributes, such as diameter distribution, spatial pattern and large aspens, the estimates are acceptable for conservation purposes.