Aim, design and settings of the study
The main aim of the study is to quantify development of forest resources in the Czech Republic for the set of four scenarios of likely development, all including adaptive forest management. The quantification concerns carbon budget with a focus on changes in individual ecosystem carbon pools according to the adopted IPCC methodologies (IPCC 2006, 2019) as used for the national GHG emission inventories under UNFCCC. Additionally, key indicators of forest resources are analyzed – specifically the changes in tree species composition and volume/age structure. The spatial domain of the study is the cadastral forest land of the Czech Republic (2 604 kha as of 2018), with a spatial resolution of the NUTS3 regional units (n = 14, Table 3; Fig. 11).
Modeling tool CBM-CFS3
This study uses a specifically calibrated modeling tool called Carbon Budget Model of the Canadian Forest Sector (CBM-CFS3 v. 1.2, here also denoted as CBM;[10, 11]). CBM represents a flexible modelling framework that has also been applied for forest ecosystem analyses and carbon-accounting purposes in other European countries [12, 13]. Pilli et al. [17] prepared an extensive database of model parameters and biomass equations applicable to European conditions, which was also used as a basis for this country-specific application. CBM is an inventory based, yield-data driven model that simulates the stand- and landscape-level carbon (C) dynamics of above- and below-ground biomass, and dead organic matter (DOM) including soil [11]. In its spatial representation beyond single stands, it can be flexibly set up to represent administrative and climate regions. CBM uses in total 21 carbon pools, which are linked to IPCC carbon pools as shown in Table 1 and in the conceptual diagram in Fig. 10.
Table 1
IPCC carbon pools and their equivalents in CBM
(adapted from Kurz et al. 2009). *Merchantable size wood limit uses the Czech standard of min. 7 cm in diameter.
IPCC carbon pool | Pool name in CBM-CFS3 | Description |
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Living Biomass | | |
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Aboveground biomass | Merchantable stemwood and bark | Live stemwood of merchantable size* plus bark |
Other wood and bark | Live branches, stumps and small trees including bark |
Foliage | Live foliage |
Belowground biomass | Coarse roots | Live roots, 5 mm and larger diameter |
Fine roots | Live roots, less than 5 mm diameter |
Dead organic matter | | |
Deadwood | Snag stems DOM | Dead standing stemwood of merchantable size incl. bark |
Snag branches DOM | Dead branches, stumps and small trees |
Medium DOM | Coarse woody debris on the ground |
Belowground fast DOM | Dead coarse roots (diam. 5 mm and more) in mineral soil |
Litter | Aboveground fast DOM | Fine and small woody debris and dead coarse (submerch. size) roots in the forest floor |
Aboveground fast DOM | F, H and O horizons |
Aboveground very fast DOM | L horizon incl. foliar litter and dead fine roots (< 5 mm diam.) |
Soil | | |
Soil organic matter | Belowground very fast DOM | Dead fine roots (< 5 mm diam.) in the mineral soil |
Belowground slow DOM | Humified organic matter in the mineral soil |
To use CBM-CFS3 in the Czech national circumstances, the European Archive Database as prepared by the Joint Research Centre [17] was modified to include the locally applicable biomass allometry functions for beech, pine, spruce, oak and birch [41–46]. The calibration process was based on the sample based landscape inventory data [47] and CBM procedure as described by [48]. The fitting procedure and applicable species-specific parameters are described in [18].
The model was initialized using the national data on the Czech forest resources as of 2018 (Table 5) using the centralized database of Forest Management Plans (FMP) administered centrally by Forest Management Institute (FMI), Brandýs n. Labem. These data included information on growing stock volume by age classes and tree species categorized in seven groups representing forest types (Table 5) and 14 regional (NUTS3) spatial units (Table 3, Fig. 11). Net (current) annual increment (NAI) applicable to forest types and their productivity as of 2018 was also provided by FMI based on the national Growth and yield tables [49]. CBM uses merchantable volume data over age to simulate growth. The entire CBM growth concept is described in detail by Kurz et al. [11] and Pilli et al. [12], and its national application described in [18]. Turnover rates and transfer to DOM carbon pools are based on the values published for CBM in the European CBM-specific database [17], with stem biomass mortality derived from the Czech NFI [50]. The information on biomass turnover, designated DOM pools and litter transfer rates as applied in CBM is provided in [18].
The past and future carbon dynamics of forest ecosystems are controlled in the model by a set of prescribed management interventions and natural disturbances. Scheduling the timing of timber harvest (thinning, salvaging, final cut) for each species group is organized in the model input file and disturbance event tables, which define the minimum forest age and biomass for clearcut, minimum and maximum age for thinning and the thinning interval. The set of disturbances used here are described in Table 2, the corresponding transfer matrices are used identically as published in [18]. It should be understood that forestry uses planned interventions such as thinning and final cut (Dist. 2 and Dist. 4 in Table 2), as well as sanitary harvest interventions (Dist. 3a, Dist. 3b in Table 2). According to the forestry legislation of most Central-European countries, the latter must be prioritized on the account of the planned activities in case of calamities to minimize their environmental impact and limit spreading. Hence, the ratio of sanitary and planned harvest (Fig. 11) is a solid indicator of stability of forests and forest management.
Table 2
Description of the individual disturbance types that are entered in the input file, all in mass unit of carbon (t C) except Dist.6 and Dist. 8 that represent interventions defined by area (ha).
Disturbance type ID | Disturbance name | Description |
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Dist. 2 | Thinning | Commercial thinning of merchantable trees in age classes 2 to 5 (species-dependent) resulting in a 10%-30% reduction in biomass carbon. |
Dist. 3a | Salvage with clear-cut | Salvage clear-cut logging of 100% of merchantable trees on areas with both abiotic and biotic disturbance. A fraction of harvest residues may be burned. |
Dist. 3b | Salvage without clear-cut | Selective salvage logging of merchantable trees in small patches with abiotic and/or biotic disturbance that does not result in open clear-cuts. |
Dist. 4 | Clear-cut harvesting without salvage | Final commercial felling of merchantable trees, 5% of trees left aside as seed trees enhancing biodiversity. A small portion of harvest residues may be burned. |
Dist. 5 | Clear-cut with slash-burn | Logging of 85% of merchantable trees followed by the burning of slash. This disturbance is only used for the initialization of dead organic matter pools. |
Dist. 6 | 100% mortality | Death of standing trees due to drought and/or bark-beetle attack, representing transfer of living biomass to snag stemwood (in area units). |
Dist. 7 | 90% mortality | Harvest of snag stemwood after previous mortality of standing trees due to drought and/or bark-beetle attack. |
Dist. 8 | Afforestation | Afforestation of forest stands after the previous mortality of tree layer (in area units). |
Simulated domain
The simulated domain is the forest area in the Czech Republic with a NUTS3 regional resolution (Fig. 11). The total area of the country is 7 887 kha, the simulated domain equals totally 2 604 kha of forest land representing timberland (including the clearcut areas) according to the Czech national cadastral system as of 2018. The fraction of unstocked cadastral forest land (63.6 kha in 2018) is not included. The share of cadastral forest land at the country-level was 34%. All elaborated scenarios assume a constant forest area for the entire projection period 2018–2070, any afforestation and deforestation events representing a possible land use change are not considered. The list of the 14 NUTS3 regions and the key region-specific information is included in Table 3.
Table 3
List of NUTSu3 regions with basic information and scenario assumptions. *Forest cover share. **The region-specific end of disturbance episode is set for the pessimistic Red, Black, and Black with repetition scenarios. ***The spread of bark-beetle calamity since the last observation (2021) is considered for the Black and Black with repetition scenario.
NUTS3 name | Code | NUTS 3 area [kha] | Forest cover* [%] | Enhanced species** | Average altitude [m A.S.L.] | Pesimistic scenario assumptions |
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End of disturbance episode*** [year] | Calamity spread**** |
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Hl. m. Praha | CZ010 | 50 | 9.6 | Oak | 286 | 2037 | no |
Středočeský | CZ020 | 1093 | 26.9 | Oak | 414 | 2025 | yes |
Jihočeský | CZ031 | 1006 | 37.0 | Fir | 631 | 2030 | yes |
Plzeňský | CZ032 | 765 | 39.8 | Fir | 609 | 2035 | yes |
Karlovarský | CZ041 | 331 | 42.6 | Fir | 684 | 2023 | yes |
Ústecký | CZ042 | 534 | 29.7 | Oak | 516 | 2030 | yes |
Liberecký | CZ051 | 316 | 43.2 | Oak | 522 | 2036 | yes |
Královéhradecký | CZ052 | 476 | 30.6 | Oak | 548 | 2047 | yes |
Pardubický | CZ053 | 452 | 29.0 | Oak | 486 | 2033 | yes |
Vysočina | CZ063 | 680 | 30.0 | Fir | 574 | 2022 | no |
Jihomoravský | CZ064 | 719 | 26.8 | Oak | 378 | 2021 | no |
Olomoucký | CZ071 | 527 | 34.4 | Fir | 592 | 2032 | no |
Zlínský | CZ072 | 396 | 39.2 | Oak | 503 | 2031 | no |
Moravskoslezský | CZ080 | 543 | 34.7 | Fir | 591 | 2036 | no |
Management scenarios
Four adaptive forest management scenarios (Green, Red, Black, Black rep.) were developed to analyze potential alternatives for the ongoing bark-beetle calamity and the effects of implemented sanitary measures (Table 4). All scenarios adhere to the current national forest adaptation policy, which is applied with specific intensity to reduce and restructure vulnerable spruce-dominated stands. However, they differ in their projections regarding the end of the current disturbance episode, in harvesting regime for the subsequent decades until 2070, and, indirectly, in intensity of tree species change.
The Green scenario represents an optimistic development of the bark-beetle calamity, with a rapid decline and a stable annual harvest volume of approximately 17 Mm3 of merchantable wood under bark after the current disturbance episode ends. Conversely, the other scenarios (Red, Black, and Black rep.) take a more pessimistic approach, assuming a gradual and slower decline in the ongoing bark-beetle calamity, with an annual harvest volume of around 16 Mm3 once the current disturbance subsides.
Table 4
Summary of the tested forest management scenarios. *Removal target in Mm3 merchantable wood volume under bark; **region-specific spread of bark-beetle calamity with a 20% increase in sanitary logging compared to 2021 level; ***reoccurring calamity as of 2018/2019 every decade; ****additional biodiversity measure.
Scenarios | Description | Target removal [Mm3/yr]* | Spread of the recent calamity** | Calamity reoccurance *** | Preserving old trees **** |
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Green | Optimistic scenario with the rapid attenuation of the recent calamity Species change promoting fir and broadleaves. | 17 | No | No | Yes |
Red | Pessimistic scenario with a progressive decrease of the recent calamity until 2030. Species change promoting fir and broadleaves. | 16 | No | No | No |
Black | Pessimistic scenario with a slight spread of the recent calamity followed by its gradual decline until 2030. Species change promoting fir and broadleaves. | 16 | Yes | No | No |
Black rep. | Pessimistic scenario based on the Black, with a two-year calamity recurrence every 10 years. Species change promoting fir and broadleaves. | 16 | Yes | Yes | No |
The harvesting regimes in each scenario differ primarily in terms of salvage logging, which is based on the observed sanitary harvest [22] in the NUTS3 regions during the recent years from 2012 to 2021 (Fig. 11). The proportion of salvage logging has increased over time as a response to the advancing bark-beetle calamity and the decline of spruce forest stands. Once the calamity subsides, the harvest demand aligns with the sustainable logging potential, which is determined by the standing stock volume across different age classes and forest types (groups of tree species).During the period of ordinary planned management, the amount of sanitary logging does not exceed one-third of the total harvest. This proportion is consistent with the values observed prior to the current outbreak of the calamity. The aim is to maintain a balance between regular harvesting activities and the need for sanitary logging to address the impacts of the bark-beetle calamity.
The Green scenario is based on the observation that, as of 2021, that the calamity reached its maximum in most NUTS3 regions in 2020 or earlier, and a gradual decline in harvest intensities is observed in subsequent years. The histograms of harvest volumes at the NUTS3 regional resolution in Fig. 11 indicate that the current disturbance episode, respectively the harvest intensities, follow a normal distribution. Using the non-linear regression model, the parameters of normal distribution of the total harvest volumes for each NUTS3 region were estimated on the yearly data observed from 2012–2021 (Fig. 11). Subsequently, the total harvest volumes in regional resolution for the period of 2022–2030 were extrapolated based on the fitted curves. Next, the tree species and logging type composition of harvest demand in this part of projection period were determined by using exponential interpolation of the corresponding harvest shares between 2021 and 2031. From 2030 onwards, the harvest demand was determined according to the logging potential and sustainable harvest for individual tree species groups and NUTS3 regions at annual time step. Under this scenario, the guiding merchantable total annual harvest volume under this scenario is about 17 Mm3. Furthermore, as one of the widely advocated adaptive measures [51], old-growth forest stands, namely 120- and 140-year-old and older coniferous and broadleaved stands, will be left without sanitary logging and final cut after 2025.
The Red scenario assumes a continued decline of the vulnerable spruce stands following the current calamity, with a specific setting for the end of the disturbance episode according to the available spruce growing stock in each given NUTS3 region. During this part of projection period, the harvest demand is set according to the observed harvest intensities for a given disturbance type (Dist. 2, Dist. 3a, Dist. 3b and Dist. 4; Table 2), tree species group and NUTS3 region in 2021. Once the harvest limit of mature spruce stands is reached in each NUTS3 region, a transition to a sustainable harvest regime according to the logging potential for individual tree species groups is assumed. The assessed termination of the current bark-beetle calamity and the decline of spruce forest stands by the NUTS3 regions are provided in Table 3. Under this scenario, the guiding merchantable total annual harvest volume is about 16 Mm3.
The Black scenario envisions the further spread of the current calamity in the NUTS3 regions where sanitary logging has not yet reached its peak. For these regions, sanitary logging of spruce is increased by 20% (compared to 2021 levels) since 2022, continuing until the harvest limit of mature spruce stands is reached. Subsequently, the transition to a regime according to the logging potential is expected. For all the remaining NUTS3 regions, the harvest demand for the sustained calamity period is set as in the Red scenario, i.e., according to harvest volumes observed in 2021. The length of the current disturbance episode with the spread of calamity is similar to the time settings in the NUTS3 regions as in the Red scenario. Once the limit of mature spruce stands in each NUTS3 region is reached, a subsequent transition to a sustainable harvest regime according to the logging potential for individual tree species groups is assumed. Under this scenario, the guiding merchantable total annual harvest volume is about 16 Mm3.
Similar to Black scenario, the Black scenario with repetition (Black rep.) envisions the further spread of the current calamity in NUTS3 regions where the calamity has not yet culminated as of 2021. The harvest demand intensities over the length of the projection period, when the spread of bark-beetle calamity occurs, are set to be like in the Black scenario. Furthermore, two-year disturbance episodes with bark-beetle infestation of spruce stands occur regularly every 10 years from the end of the 2030s until the end of the projection period. The annual logging intensities of spruce stands during a two-year episode are set as average harvest volumes from 2018 and 2019. During the period between two-year calamities, the harvest of spruce stands takes place according to the logging potential. For other forest types, a transition to a regime according to the logging potential is assumed once the current calamity subsides. Compared to the Red and Black scenario, the planned harvest demand (Dist. 2 and Dist. 4) for other tree species (except fir) is increased by 10%, 15% and 20%, in the period of 2038–2047, 2048–2057 and 2058–2070, respectively.
All four scenarios include a species change as a key adaptation measure. The species change occurs when wood is harvested either by sanitary logging interventions (Dist. 3a, 3b; Table 2) or following the planned final cut (Dist. 4; Table 2). The species change associated with sanitary logging assumes a replacement of spruce with beech (20%), fir and oak (10% and/or 30% depending on elevation of the NUTS3 region as in Table 2), long-lived broadleaves (LLB, Table 5, 20%) and short-lived broadleaves (SLB, Table 5, 20%). The species change associated with planned final cut assumes that 50% of the spruce species area is replaced by fir (10%), beech (20%) and OLB (20%) species groups.
Table 5
Forest types used to categorize tree species and category of unprocessed dead standing spruce trees and clearcut areas. Excluded is the unstocked cadastral forest area (forest roads, nurseries etc.) representing a share additional 2.4% (63.6 kha). This makes the total cadastral forest area 2 673 kha in the country, of which timberland makes up 2 610 kha in 2018.
Forest type | Acronym | Main species | Area [kha] | Area share | Volume share |
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Spruce | SP | Picea abies (L.) Karst. | 1 293 | 49.6% | 59.5% |
Pine | PI | Pinus sylvestris L., Pinus nigra Arnold | 528 | 20.2% | 19.9% |
Beech | BE | Fagus sylvatica L. | 225 | 8.6% | 6.7% |
Oak | OA | Quercus petrae (Matt.) Liebl., Q. robur L. | 194 | 7.4% | 5.4% |
Long-lived broadleaves | LLB | Tilia cordata Mill., Tilia platyphyllos Scop., Fraxinus excelsior L., Acer pseudoplatanus L., Carpinus betulus L. | 159 | 6.1% | 4.0% |
Short-lived broadleaves | SLB | Betula pendula Roth., Alnus glutinosa (L.) Gaertn., Populus spp., Alnus incana (L.) Moench | 139 | 5.3% | 2.6% |
Fir | AA | Abies alba Mill., Pseudotsuga menziesii (Mirb.) Franco | 37 | 1.4% | 1.5% |
Clearcut area | - | Temporarily unforested area, e.g. after clear-cut. | 31 | 1.2% | - |
Spruce snag | SPx | Unprocessed standing dead spruce forest stand (dead due to drought stress and bark beetle) | 5 | 0.2% | 0.3% |
Total | | | 2 610 | 100% | 100% |
The specific forest type representing standing dead spruce stands (SPx, Table 5) that remain unprocessed after bark beetle infestation due to insufficient logging capacity, was treated exclusively for the recent period of 2018–2021 as follows. Aboveground biomass of dead merchantable stems transits to stem snag pool, while carbon in other biomass pools is converted to the respective DOM pools. The postponed harvest of unprocessed dead stands is carried out in the following year after the dieback. Specifically, 90% of the previous year's unprocessed merchantable volume is removed from the snag stemwood pool in the following year. The rest of unprocessed volume is left to decomposition. The unprocessed volumes were determined in the NUTS3 resolution based on the available national statistic [22] on unprocessed dead trees for 2018–2021.