This assessment was part of project Baltic ForBio funded by the Interreg Baltic Sea Region Programme ( https://www.slu.se/en/departments/forest-economics/forskning/research-projects/baltic-forbio/). The project was carried out in 2017-2020.

The harvesting potentials in Finland were calculated for the following assortments:

• Stemwood for energy from 1st thinnings, pine

• Stemwood for energy from 1st thinnings, spruce

• Stemwood for energy from 1st thinnings, broadleaved

• Stemwood for energy from 1st thinnings (smaller than pulpwood-sized trees), pine

• Stemwood for energy from 1st thinnings (smaller than pulpwood-sized trees), spruce

• Stemwood for energy from 1st thinnings (smaller than pulpwood-sized trees), broadleaved

• Logging residues, pine

• Logging residues, spruce

• Logging residues, deciduos

• Stumps, pine

• Stumps, spruce.

1.1 Decision support system used in assessment

Regional energywood potentials were calculated with MELA forest planning tool (Siitonen et al. 1996; Hirvelä et al. 2017).

1.2 References and further reading

Anttila P., Muinonen E., Laitila J. 2013. Nostoalueen kannoista jää viidennes maahan. [One fifth of the stumps on a stump harvesting area stays in the ground]. BioEnergia 3: 10–11.

Anttila P., Nivala V., Salminen O., Hurskainen M., Kärki J., Lindroos T.J. & Asikainen A. 2018. Re-gional balance of forest chip supply and demand in Finland in 2030. Silva Fennica vol. 52 no. 2 article id 9902. 20 p. https://doi.org/10.14214/sf.9902

Hakkila, P. 1978. Pienpuun korjuu polttoaineeksi. Summary: Harvesting small-sized wood for fuel. Folia Forestalia 342. 38 p.

Hirvelä, H., Härkönen, K., Lempinen, R., Salminen, O. 2017. MELA2016 Reference Manual. Natural Resources Institute Finland (Luke). 547 p.

Hynynen, J., Ojansuu, R., Hökkä, H., Siipilehto, J., Salminen, H. & Haapala, P. 2002. Models for predicting stand development in MELA System. Metsäntutkimuslaitoksen tiedonantoja 835. 116 p.

Koistinen A., Luiro J., Vanhatalo K. 2016. Metsänhoidon suositukset energiapuun korjuuseen, työopas. [Guidelines for sustainable harvesting of energy wood]. Metsäkustannus Oy, Helsinki. ISBN 978-952-5632-35-4. 74 p.

Mäkisara, K., Katila, M., Peräsaari, J. 2019: The Multi-Source National Forest Inventory of Finland - methods and results 2015.

Muinonen E., Anttila P., Heinonen J., Mustonen J. 2013. Estimating the bioenergy potential of forest chips from final fellings in Central Finland based on biomass maps and spatially explicit constraints. Silva Fennica 47(4) article 1022. https://doi.org/10.14214/sf.1022.

Natural Resources Institute Finland. 2019. Industrial roundwood removals by region. Available at: http://stat.luke.fi/en/industrial-roundwood-removals-by-region. Accessed 22 Nov 2019.

Ruotsalainen, M. 2007. Hyvän metsänhoidon suositukset turvemaille. Metsätalouden kehittämiskeskus Tapio julkaisusarja 26. Metsäkustannus Oy, Helsinki. 51 p. ISBN 978-952-5694-16-1, ISSN 1239-6117.

Siitonen M, Härkönen K, Hirvelä H, Jämsä J, Kilpeläinen H, Salminen O et al. 1996. MELA Handbook. 622. 951-40-1543-6.

Äijälä, O., Kuusinen, M. & Koistinen, A. (eds.). 2010. Hyvän metsänhoidon suositukset: energiapuun korjuu ja kasvatus. Metsätalouden kehittämiskeskus Tapion julkaisusarja 30. 56 p. ISBN 978-952-5694-59-8, ISSN 1239-6117.

Äijälä, O., Koistinen, A., Sved, J., Vanhatalo, K. & Väisänen, P. (eds). 2014. Metsänhoidon suositukset. Metsätalouden kehittämiskeskus Tapion julkaisuja. 180 p. ISBN 978-952-6612-32-4.

2. Output considered in assessment

Valid for scenario: Maximum sustainable removal

Main output

☒Small-diameter trees

☒Stemwood for energy

☒Logging residues

☒Stumps

☐Bark

☐Pulpwood

☐Saw logs

Additional information

Stemwood for energy from 1st thinnings. Part of this potential consists of trees smaller than pulpwood size. This part is reported as Small-diameter trees.

Forecast period for the biomass supply assessment

Start year: 2015

End year: 2044

Results presented for period 2025-2034

3. Description of scenarios included in the assessments

Maximum sustainable removal

The maximum sustainable removal is defined by maximizing the net present value with 4% discount rate subject to non-declining periodic total roundwood removals, energy wood removals and net incomes, further the saw log removals have to remain at least at the level of the first period. There are no sustainability constraints concerning tree species, cutting methods, age classes or the growth/drain -ratio in order to efficiently utilize the dynamics of forest structure. Energy wood removal can consist of stems, cutting residues, stumps and roots. According to the scenario the total annual harvesting potential of industrial roundwood is 80.7 mill. m3 (over bark) for period 2025-2034. In 2018 removals of industrial roundwood in Finland totaled 68.9 mill. m3 (Natural Resources… 2019).

4. Forest data characteristics

Level of detail on forest description

☒High

☐Medium

☐Low

NFI data with many and detailed variables down to tree parts.

Sample plot based

☒Yes

☐No

NFI sample plot data from 2013-2017.

Stand based

☐Yes

☒No

Grid based

☒Yes

☐No

Multi-Source NFI data from 2015 (Mäkisara et al. 2019) utilized when distributing regional potentials to 1 km2 resolution.

5. Forest available for wood supply:

Total forest area

defined as in: FAO. 2012. FRA 2015, Terms and Definitions. Forest Resources Assessment Working Paper 180. 36 p. Available at: http://www.fao.org/3/ap862e/ap862e00.pdf.

Forest and scrub land 22 812 000 ha

Forest land 20 278 000 ha and scrub land 2 534 000 ha

Forest area not available for wood supply

Forest and scrub land 2 979 000 ha

Forest land 1 849 000 ha and scrub land 1 130 000 ha

Partly available for wood supply

Forest and scrub land 2 553 000 ha (includes in FAWS, below)

Forest land 1 149 000 ha and scrub land 1 404 000 ha.

Forest Available for wood supply (FAWS)

Forest and scrub land 19 833 000 ha

Forest land 18 429 000 ha and scrub land 1 404 000 ha

In MELA calculations all the scrub land belonging to the FAWS belongs to the category “Partly available for wood supply”, but there are no logging events on scrub land regardless or the category.

6. Temporal allocation of fellings

Valid for scenario: Maximum sustainable removal

Allocation method

☐Optimization based without even flow constraints

☒Optimization based with even flow constraints

☐Rule based with no harvest target

☐Rule based with static harvest target

☐Rule based with dynamic harvest target

See item 3 above (max NPV with 4 % discount rate).

7. Forest management

Valid for scenario: Maximum sustainable removal

Representation of forest management

☐Rule based

☒Optimization

☐Implicit

Treatments, among of the optimization makes the selections, are based on management guidelines (e.g. Äijälä etc 2014)

7.2 General assumptions on forest management

Valid for scenario: Maximum sustainable removal

☒Complies with current legal requirements

☐Complies with certification

☒Represents current practices

☐None of the above

☐ No information available

Forest management follows science-based guidelines of sustainable forest management (Ruotsalainen 2007, Äijälä et al. 2010, Äijälä et al. 2014).

7.3 Detailed assumptions on natural processes and forest management

Valid for scenario: Maximum sustainable removal

Natural processes ☒Tree growth

☒Tree decay

☒Tree death

☐Other?

Tree-level models (e.g. Hynynen et al., 2002).

Silvicultural system

☒Even-aged

☐Uneven-aged

Click here to enter text.

Regeneration method

☒Artificial

☒Natural

Regeneration species

☐Current distribution

☒Changed distribution

Optimal distribution may differ from the current one.

Genetically improved plant material

☐Yes

☒No

Cleaning

☒Yes

☐No

Thinning

☒Yes

☐No

Fertilization

☐Yes

☒No

7.4 Detailed constraints on biomass supply

Volume or area left on site at final felling

☒Yes

☐No

5 m3/ha retained trees are left in final fellings. Final fellings can be carried out only on FAWS with no restrictions for wood supply.

Constraints for residues extraction

☒Yes

☐No

☐N/A

Retention of 30% of logging residues onsite (Koistinen et al. 2016)

Constraints for stump extraction

☒Yes

☐No

☐N/A

Retention of 16–18% of stump biomass (Muinonen et al. 2013; Anttila et al. 2013)

8. External factors

Valid for scenario: Maximum sustainable removal

External factors besides forest management having effect on outcomes

Economy

☐Yes

☒No

Climate change

☐Yes

☒No

Calamities

☐Yes

☒No

Other external

☐Yes

☒No