1. Introduction
The changing climate, increasing biomass demand, requests for wetland restoration, biodiversity conservation and the need for enhancing the carbon sink in forests, lead to an increasing need for alternative forest management models (aFMM). There is a clear need to consider aFMMs that aim at increasing forest multifunctionality while preserving wood production [
1]. In particular, within the framework of the ALTERFOR project (Alternative models and robust decision-making for future forest management,
https://alterfor-project.eu/), a number of aFMMs have been tested in specific case studies in eight European member states and in Turkey [
2,
3]. The aFMMs designed in the ALTERFOR project can be aggregated in the following categories: (high productive) clearcut, shelterwood, selective logging, EU habitats (a combination of clearcut forest management with set-aside patches of forest with high biodiversity value), set-aside and combination of the first three listed aFMMs with tree species changes. In this study, we consider these aFMMs from the point of view of the impact on the wood removals (harvest) and the forest carbon sink.
The actual forest management in Europe varies a lot depending on region, tree species, site productivity, forest owner, etc. [
4]. The high production clearcut forest management applies relatively short rotations, maximizing mean annual increment [
5,
6]. Usually, forests in Europe are not managed with the maximum intensity [
7]; on average, about 31% of forests are managed intensively and very intensively for wood production [
8]. Therefore, the transition of forest with longer rotation to shorter rotation when the objective is to maximize mean annual increment (MAI) leads to an increase in wood removals and a decrease in standing biomass; in contrast, the transition to set-aside management interrupts wood removals and increases the forest biomass accumulation [
6]. Selective logging (or continuous cover forestry) is a non-intensive forest management model (FMM) as only single trees that have reached a certain threshold, e.g., stem diameter at breast height (Dbh), are harvested. Under the “EU habitats” forest management high-biodiversity forest patches stay onsite continuously, thus, less forest area is harvested when compared to the forest under clearcut forest management. Transition from clearcut forest management to selective logging forest management or “EU habitats” management leads to an increase in standing forest biomass and a decrease in wood removals [
6,
9]. Under the shelterwood forest management, the forest is regularly harvested as under the clearcut forest management, however, a share of the forest is left onsite for natural regeneration and protection of the regrowth. Thus, shelterwood logging is an intermediate model between clearcut and continuous cover forest management, as the total biomass is removed in two or more successive stages. Compared to clearcut logging, shelterwood logging is better suited for regenerating some tree species while providing higher biodiversity [
10,
11,
12,
13] and soil protection, due to the increasing forest biomass and decreasing wood removals since a share of forest stand is left onsite for longer time [
14].
As a part of implementing the Paris Agreement, the European Union (EU) set rules for accounting the greenhouse gas emissions and removals from forest land. According to these rules, for each European Member State, the average emissions from forest land in 2021–2025 (compliance period 1, CP1) and in 2026–2030 (compliance period 2, CP2) will be compared to a projected reference level (FRL) [
15]. The FRL is estimated by modelling forest development under fixed forest management practices, based on those observed in 2000–2009 (the reference period, RP) [
16]. As a result, forest management emissions that occur from pure continuation of RP forest management practices are not taken into account [
17]. This approach aims to account only for the impacts of real changes to forest management and the cancelling out of the foreseen decrease in forest sink that is purely due to aging of forests [
18]. The FRL estimation criteria allow for different assumptions on the FRL projection, such as flexibility in starting year of projection and determination of the forest management practices within RP to be applied for the projection, and assumptions regarding future climate change [
16]. Different assumptions may result in variation of the combined FRLs of EU27+UK by approximately 100 Mt CO
2/year [
19].
A number of studies have investigated the effects of implementing aFMMs at different scales. In particular, Schwaiger et al. (2019) [
6] studied stakeholder specific landscape-level forest management scenarios (set-aside, multifunctional and wood production oriented) applied in two forest sites, a less productive and a more productive one, in Germany. The studies were carried out under the condition that the whole forest is managed under the same landscape level concept in each scenario. While this implied considerable differentiation at the stand level, it might be summed up as follows: the multifunctional oriented FMM was characterized by diameter-target harvesting and increasing representation of broadleaved tree species, while the wood production oriented FMM was characterized by increment maximization with conifer monocultures, including the increase in conifer area shares at the expense of broadleaf species. Application of the set-aside FMM led, as expected, to an increase in growing biomass stock in both areas. The multifunctional-oriented FMM resulted in a larger average growing stock than the production oriented FMM in the more productive area, while the effect was opposite in the less productive area. In contrast to the multifunctional management, the production forest scenario resulted in strong oscillations of the harvested timber amounts. This is due to the uneven initial age class distribution at the investigated sites which does not become balanced in the production scenario.
Hynynen et al. (2019) [
20] compared growth rate response of even-aged and uneven-aged Norway spruce stands, located in southern Finland, to different cuttings. Even-aged stands were thinned from below while uneven-aged stands were logged selectively. The observation period lasted for about 20 years. The authors concluded that in the conditions of southern Finland the even-aged forest management most likely produces more wood in a long term than uneven-aged forest management, and the growth rate of even-aged stands is likely to be higher than the growth rate of uneven-aged stands.
In 2020, Eggers et al. [
21] studied four stakeholder defined scenarios of a large representative forest landscape in Sweden. The scenarios comprised different shares of alternative forest management models: forest reserves, even-aged and uneven-aged management and retention patches. Even-aged forestry with the application of clearcut and shelterwood logging resulted in the largest mean annual harvest, mean annual growth and the least growing stock and low net present value (the sum of future net cash flows discounted to the present). Continuous cover forestry with selective logging resulted in about a 20% lower mean annual harvest and mean annual growth, higher growing stock compared to the even-aged forestry and the largest net present value. The combination of clearcut, shelterwood and selective logging resulted in a slightly lower mean annual harvest, mean annual growth and a higher growing stock than the even-aged forestry, while the net present value was the same. Retention patches that were treated with selection fellings yielded the lowest mean annual harvest, net present value and the largest growing stock compared to the other cases, showing a mean annual growth slightly lower than in the continuous cover forestry.
Vauhkonen and Packalen (2019) [
9] studied scenarios of large-scale forest transition to alternative forest management in Finland. They considered a number of scenarios of transition of different shares of forests from even-aged forest management to continuous cover forest management and set-aside management. They found that carbon sequestration, wood removals and harvesting costs depend on the forest type and the share of forest area treated with the alternative FMMs. Transition of forests with low conservation value to the FMM implying continuous cover forestry and set-aside areas resulted in the highest accumulation of carbon stock, a considerable decrease in harvest removals and a moderate increase in harvesting costs. Transition of forests with low conservation value to the FMM implying continuous cover forest management, as well as transition of forests with a high conservation value to the continuous cover forestry (with or without set-aside areas) resulted in a moderate accumulation of carbon stock. Transition to the continuous cover forestry with the establishment of set-aside areas decreases the harvest removals considerably, while the effect of the transition to the continuous cover forestry alone causes more moderate effects. If the uneven-aged FMM is adopted on a large scale, but wood demand remains the same, the harvesting costs with the selective logging becomes considerably higher than with the clearcut (as in even-aged FMM).
However, the effect of large-scale implementation of aFMMs in the whole ALTERFOR region (EU27+UK and Turkey) on wood removals and net forest carbon sink in comparison to the respective FRL levels in CP1 and CP2 has not yet been studied. Therefore, the objective of this study is to estimate the effects of large-scale uptake of the aFMMs, studied in the ALTERFOR project, on forest harvest and forest carbon sink in 2021–2025 and 2026–2030 considering that the proposed aFMMs are expanded to most of the suitable areas in EU27+UK and Turkey. In particular, our results are compared to projections modelling the FRL estimates for EU27+UK (and hypothetical FRL projections for Turkey), thus providing insights into possible opportunities for the EU member states under the new land use, land use change and forestry (LULUCF) regulation. We performed our simulations under the condition that the different countries should still match the harvest levels estimated for their FRLs as closely as possible.
4. Discussion
4.1. Impact of the Introduction of the aFMMs on the Harvest and Net Forest Sink
The changing of an FMM in a certain part of the forest impacts the local harvest in the year of the aFMM introduction and may change the average harvest over a longer period. If the aFMM was introduced in a large territory, the wood removal in the country or region is affected and should be compensated by the adaptation of FMM parameters in other places within the region, in order to still satisfy the total wood demand. In the case of switching from the clearcut to the shelterwood logging aFMM, the removals are reduced in the year of the aFMM introduction, because a share of the forest stand, which would be harvested in the case of the clearcut aFMM, is left onsite for regeneration. Therefore, in the years when shelters are removed, the total harvest can be larger when compared to the clearcut FMM [
14]. Carbon sequestration in forest biomass is greater than in the forests treated with clearcut logging, because a number of older trees are present onsite in the shelters. In the case of switching from the clearcut to the EU habitat aFMM, the removals are reduced in the year of the aFMM introduction and, in the long run, the carbon sequestration in forest biomass is larger because a share of the forest stand, which would have been removed in the case of the clearcut aFMM, is left onsite for biodiversity protection [
39]. In the case of switching from the clearcut to the selective logging aFMM, the removals are reduced in the year of the aFMM introduction and, in the long run, the carbon sequestration in forest biomass is larger. In the case of switching from the clearcut to the set-aside aFMM, the removals are reduced in the year of the aFMM introduction as well as in the long run because the logging is not carried out. The dynamics of the wood removals and the carbon sink is in line with the study by Vauhkonen and Packalen (2019) [
9], Eggers et al. (2020) [
21] and the high-productive case from Schwaiger et al. (2019) [
6].
The multifunction scenario in the northern region can be compared to the MUCL (multi-use conservation landscapes) scenario with 20% share of continuous forest cover and set-aside forest management (
p = 20%) from the study by Vauhkonen and Packalen (2019) [
9] for Finland, while the balanced scenario can be compared to the MUL (multi-use landscapes) scenario with 15% share of continuous forest cover forest management (
p = 15%) and the production scenario to the MUL scenario (
p = 5–10%). In our study, similar to [
9], the increase in the share of the set-aside and continuous cover forest management leads to accumulation of forest biomass and a decrease in harvest removals.
The changing of tree species does not affect the amount of wood removals in CP1 and CP2 sharply, as the new species are introduced gradually and will reach the harvesting thresholds after CP2. However, in the longer period, the FMM parameters will be adapted to the properties of the new tree species (e.g., harvesting Dbh threshold is 40–45 cm for spruce but 60 cm for beech in the CSA in Bavaria,
Table 1; the rotation length maximizing MAI depends on the shape of the growth curve) that affects the harvest. The share of coniferous and non-coniferous roundwood will change as well, which in the long run can impact the wood processing industry [
40].
4.2. aFMM Scenarios Minimizing the Reduction in Harvest and Maximizing the Increase in Sink
From the point of view of minimizing the reduction in roundwood harvest compared to the BAU-only, the production or balanced scenarios are the preferable ones. In most cases, the immediate introduction of aFMMs had a greater impact on harvest during CP1, while the gradual introduction of aFMMs had a greater impact in CP2. The impact varies from a slight increase in wood removals (0.3%) in the central-east region to a slight decrease, up to 1.1%, in the other regions.
From the point of view of maximizing the enhancement of the sink in forest biomass in CP1 and CP2, the multifunction or set-aside scenarios of aFMM allocation with immediate introduction of the aFMM had the largest effect in all regions (from 5% in the southern to 35% in the central-west region). The gradual introduction of aFMMs reduced the effect by approximately 40% in CP1 and by 20% in CP2 (
Table 5). Taking into account the correlation between wood harvest and the carbon sink (i.e., combining information from
Table 5 and
Table 6), in the northern region and the allocation of aFMMs according to the multifunction scenario in the southern region, the multifunction or set-aside scenarios with gradual introduction of aFMMs are the preferable ones for maximizing the carbon sink.
When comparing the impact of the aFMM introduction, we may highlight scenarios which cause a minimal reduction in wood removals and a large increase in the carbon sink. Such scenarios are optimal from both points of view, because this way, both the impact on the wood processing industry and the enhancement of the carbon sink in forest biomass are considered. Under these considerations, in the central-east region, the allocation of the aFMMs following the balanced or multifunction scenarios with immediate or gradual introduction of the aFMMs are the preferable ones (
Table 5). Meanwhile, the multifunction scenario is preferable in the central-west and northern regions. At the same time, the multifunction or set-aside scenarios are better performing in the southern region. In fact, the multifunction scenario shows good performance in all regions.
However, considering the correlation of the wood removals and the carbon sink in our study (
Table 6), a significant share of the sink increase was connected to reduction in wood removals. This can be observed in the central-west region, under the multifunction scenario with gradual introduction of aFMMs, and in the southern region, under the multifunction and set-aside scenarios with immediate introduction of aFMMs. Thus, the effect of management in these cases was secondary compared to the effect of reducing the harvest.
In general, the immediate introduction of the aFMMs resulted in over 1.5 times greater increase in the sink than the gradual introduction under CP1 and over 1.2 times under CP2. These results indicate that adopting aFMMs has potential to provide a possibility for EU member states to gain accounting credits under the LULUCF regulation. However, the decision of introducing the aFMMs should be taken fast to greater effect on the carbon sink in CP1 and CP2.
4.3. Caveats in This Study
The relatively small number of CSAs and their locations reduce the representativeness of the CSAs for larger regions, especially in NUT2 with high diversity like in the case of Portugal. Another dimension of the representativeness is the mapping of the NUTS2 where the CSAs are located in the other NUTS2 using a statistical similarity. Finally, we applied a computer model operating on a 0.5 × 0.5° grid (approximately 50 × 50 km) initialized with one prevailing tree species group in each grid cell and applying forest stand growth functions generalized for eight tree species groups. However, we can argue that the results of this study are likely to present a conservative estimate of the potential of the aFMMs because of a possible underestimation of the potentially suitable areas. The reason is that in the first stage, we chose only the “most similar” NUTS2 region according to the Mahalanobis index. However, there could be other NUTS2 regions, apart from those where the Mahalanobis scores are within the similarity range, which may include forests composed of tree species for which a particular aFMM is designed, or having productivities fitting some of the aFMMs. The rough spatial resolution of the model and the use of only one prevailing tree species group in each cell filtered out possible suitable locations for aFMMs that were targeted for some specific tree species. Besides that, within one selected NUTS2 region, there are a few aFMMs which can be applied equally in the same location. Another uncertainty is in the time of switching to an aFMM which can influence the harvest and the net forest carbon sink. Since the spatial allocation of aFMMs is not unique and the time of aFMM application is uncertain, we developed four different scenarios of spatial allocation and two different scenarios for the time of aFMM introduction.
The application of aFMMs resulted in a slight decrease in harvested wood, with a maximum of 1.1% in CP1 and 0.92% in CP2, contrasting to BAU-only FMMs (
Table 4 and
Table 5). The largest decrease in harvest occurred under the set-aside aFMM allocation scenario, followed by multifunction (0.84% in CP1 and 0.54% in CP2) and balanced (0.78% in CP1 and 0.52% in CP2), with the smallest decrease observed in the production scenario (0.67% in CP1 and 0.34% in CP2). However, we consider as baseline the harvest level resulting from the application of the FMMs as in the RP (according to the FRL definition). In reality, wood demand may be greater, for example, the EU Reference Scenario 2016 [
41] projects a harvest increase in EU27+UK by more than 15% in CP1 and CP2 (compared to about 7–8% increase in the current study). In the case of the larger wood demand, we expect a shortage of wood under set-aside scenarios, in particular in the northern region.
The future climate, atmospheric CO2 concentration and nitrogen deposition were not taken into account in this study. However, this should have a limited effect on the results within next 10 years. In addition, we did not consider in this study the contribution to the sink which can be obtained through harvested wood products. A change in management could have a possible impact on the share of different assortments being harvested and therefore on their different capacity of storing carbon over time, with a potential climate impact of the aFMMs. This aspect would need further explorations in the future.