Does Aiming for Long-Term Non-Decreasing Flow of Timber Secure Carbon Accumulation: A Lithuanian Forestry Case
Abstract
:1. Introduction
2. Materials and Methods
2.1. Study Area
2.2. Modelling the Development of Forests and Forestry
2.3. Accounting for Changing Climate Conditions
- (1)
- Reference, which assumed the continuation of climate change mitigation efforts in the EU as they were in 2016 and small efforts globally, resulting in strong climate change and a temperature increase of ca. 3.7 °C by 2100 compared to pre-industrial values. Globally, this was expected to increase timber and pulpwood harvests with relatively unchanged proportions and a medium level of logging residue extraction. In Lithuania, this scenario assumed the relatively largest increase of the yield of coniferous forests in Lithuania.
- (2)
- EU bioenergy, which assumed strong EU climate change mitigation efforts and medium efforts globally, therefore resulting in medium climate change and a temperature increase of ca. 2.5 °C by 2100 compared to pre-industrial values. Globally, this was considered to result in increasing pulpwood shares until 2050 and, after that, a strong increase of both timber and pulpwood harvests, with logging residues extraction, as for the reference scenario. The productivity of coniferous forests in Lithuania was projected to increase, however, less than under conditions of the reference scenario.
- (3)
- Global bioenergy, which assumed strong climate change mitigation, thus resulting in halted climate change with a temperature increase of ca. 1.5–2 °C by 2100 compared to pre-industrial values. This was characterised by high bioenergy demand increases, especially for the harvests of small-diameter pulpwood. All available residues were considered to be extracted for energy purposes. The productivity of coniferous stands was projected to increase, however, less so than under the EU bioenergy scenario.
2.4. Assessed Attributes Describing Forests and Timber Delivery
- Standing volume (m3/ha)—gross remaining wood volume of the living trees in the forest stands after harvest and mortality in the preceding decade.
- Area-weighted average age (years).
- Annual net wood volume increment per 1 ha (IV) of total forest stand area (m3/ha/year), estimated as:
- Volume of annually harvested timber per 1 ha of total forest stand area (m3/ha/year). The distribution of harvested timber by assortments (sawlogs, pulpwood, logs remaining in the forest and harvest residues) and their prices were taken from the state forestry statistics referring to the years from 2013 to 2018 [79]. To reduce the number of assortment categories, the pulpwood volume also included the volume of roundwood for particle board and firewood.
- Total area of forest stands, belonging to a specific age class (ha). As an age class, we assumed 10-year-long forest stand age intervals, i.e., the 1st age class ranging from 1 to 10 years, the 2nd age class from 11 to 20 and so on.
2.5. Assessing Carbon Sequestration
- (1)
- Carbon stocks in the forest, including the above- and belowground living tree biomass and deadwood (harvesting residues, stumps and dead roots). The methodology employed for assessing the carbon changes in biomass pools was based on Tier 1 gain-loss method described in the Intergovernmental Panel on Climate Change (IPCC) Guidelines for National Greenhouse Gas Inventories [55]. For that we estimated the above- and belowground biomass gains, losses due to harvest and mortality and transfer of carbon from biomass to harvest or deadwood pools. The aboveground biomass gains were estimated using the wood volume increment per 1 ha data and wood density, biomass to carbon conversion factor and biomass conversion factors from merchantable wood to total biomass adopted for gain-loss method [55]. Total biomass was achieved adjusting the aboveground biomass values using the values of relative share of root biomass in the total tree biomass. Conversion factors used were adopted for deciduous trees and conifers. Biomass losses due to harvest and mortality were derived using the volumes of harvested timber and mortality, available from the simulations. Deadwood carbon stocks included dead logs (harvest residue logs and mortality logs) and roots (including stumps) and they were calculated to decline with time using an exponential first-order decay function and half-life values for dead coarse roots and stumps and aboveground deadwood.
- (2)
- Wood usage and wood products. The carbon stock changes were based on the carbon stored in wood products coming from timber harvesting during each simulation step. The calculations were implemented using an exponential first-order decay model (function) and half-life values for HWP semi-finished products. HWP stock changes were estimated for each semi-finished wood category and using data on wood product inputs and historical HWP data for initial values of carbon stocks in semi-finished wood products. The wood inflow from the harvest into semi-finished woods products was based on harvest residue loss, wood used for production of energy and harvested timber by assortment (available from the simulations), taking into consideration wood getting lost during processing and the shares of assortments allocation to semi-finished product categories.
- (3)
- CO2 emissions savings due to energy substitution and product substitution. Displacement factors (DF) were used to estimate the emission savings. In our study, we considered three basic fossil fuels being replaced and the displacement factor (for calculating substitution of fossil C-emissions) for energetic wood use was based on average values for gas (0.19), oil (0.26), and coal (0.36).
3. Results
3.1. Standing Volume, Age and Timber Harvesting in Lithuanian Forests during the Next Century
3.2. Carbon Stock Changes in Lithuanian Forests during the Next Century
4. Discussion
4.1. Sustainability of Timber Deliveries from Lithuanian Forests during the Next Century
4.2. Carbon Stock Changes in Lithuanian Forests if Current Forest Management Practices Are Continued
4.3. Proposals for Carbon Accounting Policies
5. Conclusions
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
Appendix A
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Parameter Name | Value |
---|---|
Conversion factor of one biomass mass unit to one carbon mass unit | 0.5 |
Conversion factor from aboveground merchantable broadleaf wood to total aboveground biomass (from m3 into tons) | 0.8 |
Conversion factor from aboveground merchantable conifer wood to total aboveground biomass (from m3 into tons) | 0.7 |
Wood density of deciduous trees (t/m3) | 0.47 |
Wood density of conifers (t/m3) | 0.41 |
Relative share of deciduous root biomass in total tree biomass | 0.19 |
Relative share of coniferous root biomass in total tree biomass | 0.26 |
Relative share of stump volume in the harvest residues’ volume | 0.5 |
Relative share of stumps in aboveground mortality tree volume | 0.1 |
Half lifetime of dead coarse roots and stumps | 17.5 |
Half lifetime of aboveground deadwood | 12.5 |
Relative loss factor from above- and belowground deadwood pools | 0.15 |
Relative amount of deadwood (related to remaining growing stock), used for initialization of deadwood stocks | 0.1 |
Relative share of the harvested biomass getting lost during processing | 0.5 |
Relative share of sawlogs being used for production of energy | 0.39 |
Relative share of pulpwood being processed into wood-based products | 0.56 |
Relative share of pulpwood being used for energy production | 0.04 |
Relative share of harvest residues not remaining in the forest, but being used for energy provision or other short-life purposes | 0.3 |
Initial value of carbon stocks in semi-finished wood products for sawlogs (tC/ha) | 3.96332865 |
Initial value of carbon stocks in semi-finished wood products for wood-based products (tC/ha) | 1.12310721 |
Initial value of carbon stocks in semi-finished wood products for paper/pulp (tC/ha) | 0.00428203 |
Half lifetime of paper | 2 |
Half lifetime of sawn wood | 35 |
Half lifetime of wood-based products | 25 |
Displacement factor (for calculating substitution of fossil C-emissions) for energetic wood use | 0.27 |
Product displacement factor for wood-based products | 0.47 |
Product displacement factor for sawn wood | 0.54 |
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Mozgeris, G.; Kazanavičiūtė, V.; Juknelienė, D. Does Aiming for Long-Term Non-Decreasing Flow of Timber Secure Carbon Accumulation: A Lithuanian Forestry Case. Sustainability 2021, 13, 2778. https://doi.org/10.3390/su13052778
Mozgeris G, Kazanavičiūtė V, Juknelienė D. Does Aiming for Long-Term Non-Decreasing Flow of Timber Secure Carbon Accumulation: A Lithuanian Forestry Case. Sustainability. 2021; 13(5):2778. https://doi.org/10.3390/su13052778
Chicago/Turabian StyleMozgeris, Gintautas, Vaiva Kazanavičiūtė, and Daiva Juknelienė. 2021. "Does Aiming for Long-Term Non-Decreasing Flow of Timber Secure Carbon Accumulation: A Lithuanian Forestry Case" Sustainability 13, no. 5: 2778. https://doi.org/10.3390/su13052778