Streamlining and better precision are two cornerstones needed to make forestry even more sustainable, and to further extend the use of the timber raw material. Urban Nilsson, professor at SLU, is involved in two projects that promote precisely this.
Urban Nilsson, Swedish University of Agricultural Sciences (SLU).
One project is about improved thinning planning, another is developing a new and improved growth model, where climate is taken into account in a way that has not been done before.
– The growth models we have today are based on how the forest has grown historically. It is a fantastic tool based on test areas dating from the beginning of the 20th century. But with today’s changed – and changing – environment, they quickly become obsolete, says Urban Nilsson. Since the models are based on historical statistical relationships, they become incorrect as the temperature rises, and the ground conditions change.
Martin Goude, Swedish University of Agricultural Sciences (SLU).
What Urban Nilsson and doctoral student Martin Goude have done, is to introduce climate variables into the growth models.
– In the models, we included the ability of the trees to utilise the light that is used during growth. The link between light and growth depends on the temperature and the water supply of the trees. This means that we can calculate the growth of the forest and see how it might change depending on how temperature and precipitation change, says Martin Goude.
The growth model can be linked to climate forecasts from SMHI, which means it can calculate growth with much greater accuracy and probability.
The models shows the growth of spruce and pine forests using light, temperature and water supply. Illustration: Martin Goude.
The second project, “Thinning Forecast”, is a digital tool for detailed thinning planning. One use is to develop the decision support for the forest owner and advisor, so favourable decisions about the time for thinning can be made.
– It is easier for us to see the consequences of thinning now or in a few years time, considering withdrawal volume, finances and risk of storm damage, for example. Magnus Petersson, head of forest management and entrepreneurial development at Södra, gives this example.
The tool uses nationally collected laser data to identify thinning needs. It also allows for more detailed instructions for harvester drivers.
– You often have stocks as a whole unit, but the truth is that there can be incredible differences within them. However, using laser data we can thin based on pixels of 20×20 meters, says Urban Nilsson.
Magnus Petersson, Södra
Magnus Petersson sees great gains for operational forestry.
– Today’s thinning templates are based on the assumption that a stock is homogeneous, so that the harvest is also the same over the entire area. In practice, there is great variation in base area, number of trunks and tree species, even in well-managed forests. So, providing the harvester with decision support that actually takes into account the variation in the stock is valuable.