heating differs between microbial groups (Table 2), intense fires can result in changes in the microbial community diversity and structure (Goberna et al., 2012). For instance, it is known that soil heating increases the predominance of soil bacteria while reducing the fungal abundance (Fultz et al., 2016; Rutigliano et al., 2007). In a review by Taudière et al. (2017), negative effects of prescribed fires on ectomycorrhizal (ECM) fungal richness are reported, but the authors acknowledge that further studies are necessary to understand how this practice could impact ECM fungal diversity. Furthermore, Tomao et al. (2020) shows that there is not much consistency in the literature on the effect of prescribed burning on fungal species diversity. What seems clear is that shifts in fungal community composition occurs (Oliver et al., 2015; Reazin et al., 2016), and that the recovery of the pre-burning community can take more than a decade (Hart et al., 2018; Oliver et al., 2015). These community changes could have potential consequences at a functional level and on the C and nutrient cycling. Then, the recovery of soil microbial functions, such as the capacity to degrade compounds of different biochemical characteristics, may depend on the capacity of plant communities to regrow and provide different organic compounds through root turnover and exudation (Garcia-Pausas et al., 2022).

### 7.1.2. Impact of fire management on soil C stock and fluxes

Even in low intensity burns, the losses of ecosystem C and N can be significant (Certini, 2005; Homann et al., 2011). Although most of the studies agree unequivocally that untreated stands release more emissions to the atmosphere during a wildfire than treated stands (Restaino and Peterson, 2013), when considering the emissions derived from treatments, the relative effectiveness of fuel treatments in mitigating C losses is less clear, and highly variable (Restaino and Peterson, 2013: -33 Mg C ha⁻¹ to +3 Mg C ha⁻¹). For instance, in *Picea abies* forests of Finland, CO₂ efflux during the two years after clear-cutting and burning of slash was comparatively lower than the clear-cut only stand (difference ~10.1 Mg C ha⁻¹), but the total amount of CO₂ released was higher due to the immediate CO₂ emissions during burning (~28.0 Mg C ha⁻¹, Kulmala et al., 2014). Furthermore, a sink capacity of CH₄ is reduced during at least the first year after burning (Virkkula et al., 2014). In the long-term, however, the decay of logging residuals at the clear-cut stand may reduce the differences between clear-cutting with and without burning of slash (Table 1).

As litter and soil organic layers contain an important proportion of surface C stocks, the consumption of ground fuels during a prescribed burning can represent the largest fraction of emissions caused by fire management. Consequently, in ecosystems with deep organic horizons (e.g. boreal forests, peatlands) prescribed burning can negatively impact C storage (Pellegrini et al., 2022). In a meta-analysis on temperate forests, Nave et al. (2011) indicated that prescribed burning caused, on average, 46% and 35% reductions of the forest floor C and N stocks, respectively.

Depending on the temperatures reached, fires can also potentially alter the physical, chemical, and biological properties of the uppermost mineral horizons, which may affect key processes of the C cycling (Alcañiz et al., 2018; Certini, 2005). However, the heat transfer to the soil surface and into the soil is an uncertainty in modelling fire impact on soil processes (Table 1). The amount, characteristics and arrangement of fuels determines the proportion of released energy by fire that impacts forest floor and mineral layers. Thus, under slash piles soil temperature can reach more than 100°C at 10 cm depth, and even more intense and longer-lasting heating can occur in soils under wood piles (200-300°C) (Busse et al., 2013), causing stronger C and nutrient losses, soil physical alterations, and mortality of faunal and microbial communities. The heat transfer into organic and mineral layers during the burning of shredded debris is higher than during the burning of standing understory. In both managements, intense heating of mineral soil is generally restricted to the 2-5 cm soil depth, and diminishes steeply with depth (Cawson et al., 2016). Soil moisture limits temperature increase during a

fire (Busse et al., 2005); therefore, burning when organic and mineral soils are moist is outlined in the prescription guidance to prevent soil impacts (Table 1).

Overall, fire could eventually affect both C inputs to and outputs from the soil. Understory burning alters the quantity or quality of the organic matter inputs through shifts in plant community composition, abundance and vigour, which in turn may affect the microbial activity and organic matter mineralisation. However, mid-term changes in soil C and N after low-to-medium intensity prescribed burnings seem to be more related to plant community dynamics than to the direct effects of fire (Martí-Roura et al., 2011). Although litterfall increases during the first months after a prescribed burning (Espinosa et al., 2018), recovery of the forest floor mass to pre-fire stocks could take several years. For instance, in *Pinus ponderosa* forests of Oregon (US), Busse and Gerrard (2020) recorded faster rates of litter mass accumulation in burned than in unburned sites, but the recovery of organic horizons to pre-burning levels took about 15-20 years. Increase of litter N content, at least in places with a high frequency of burning, may contribute to litter decomposition (Ficken and Wright, 2017) and slow down the recovery of C stocks in organic horizons.

Despite the growing consensus among researchers and managers concerning the benefits of fire as a management tool for ecosystem issues such as wildfire hazard reduction, forest productivity, and biodiversity conservation of endangered species, the benefits of this practice for key soil components and functions are less obvious. Compared to the reduced and transient effects of low-intensity prescribed burns, burning shredded debris or slash piles have greater potential to negatively impact soil C stocks. In these cases, burning when organic and mineral soils are moist is mandatory to reduce soil C emissions. Minimizing soil C emissions during burning together with soil organic matter stabilization processes triggered by fire supports fire management as a smart forest tool to mitigate the effects of stand-replacing wildfires and enhancing forest biodiversity. We have extensive knowledge about the effects of fire management on soil physical and biogeochemical variables such as C and nutrient dynamics (e.g., Alcañiz et al., 2018; Martí-Roura et al., 2014, 2011 and references there-in), but less understanding about the cumulative effects of repeated burnings on soil functions. Thus, more knowledge is needed on a mechanistic understanding of plant and soil biota-mediated responses to different fire intensities and recurrences to avoid negative impacts on soils (Table 1).

### 7.1.3. Impact of fire management on soil C stability

Short-term organic C stock reduction after fire can be compensated in the long term by multiple transformations that increase the stability of organic matter and potentially buffer C emissions due to heterotrophic respiration (Pellegrini et al., 2021). Fire can alter the stability of soil organic matter by changing its physical protection and its biochemical quality. Partially charred organic material may have different biochemical quality than uncharred organic matter, altering their decomposition dynamics (Martí-Roura et al., 2014; Pellegrini et al., 2021). On the other hand, the rapid rise of soil temperature even under low intensity fires cause structural degradation of soil aggregates due to the steam pressure when there is a rapid vapourisation of soil pore water (Albalasmeh et al., 2013; Jian et al., 2018). This leads to a loss of C by microbial mineralisation of previously physically protected organic matter (Jian et al., 2018), and may also compromise the capacity of soils to stabilise new organic matter inputs. Structural degradation can also occur in the case of high intensity fires, if the organic matter that binds aggregates is burnt (Alcañiz et al., 2018).

On average, about 5% of the burned biomass is converted to pyrogenic C (PyC) (DeLuca et al., 2020), which is considered a stable form of C resistant to microbial degradation (Singh et al., 2012 but see Ghosal et al. 2016). In a data synthesis, DeLuca et al. (2020) found no significant differences in the amount of PyC produced by wildfires and prescribed fires (2.2±1.7 Mg ha⁻¹), with less variability observed in prescribed fires due to their usual low fire intensity. PyC not only represents a form of
heating differs between microbial groups (Table 2), intense fires can result in changes in the microbial community diversity and structure (Goberna et al., 2012). For instance, it is known that soil heating increases the predominance of soil bacteria while reducing the fungal abundance (Fultz et al., 2016; Rutigliano et al., 2007). In a review by Taudière et al. (2017), negative effects of prescribed fires on ectomycorrhizal (ECM) fungal richness are reported, but the authors acknowledge that further studies are necessary to understand how this practice could impact ECM fungal diversity. Furthermore, Tomao et al. (2020) shows that there is not much consistency in the literature on the effect of prescribed burning on fungal species diversity. What seems clear is that shifts in fungal community composition occurs (Oliver et al., 2015; Reazin et al., 2016), and that the recovery of the pre-burning community can take more than a decade (Hart et al., 2018; Oliver et al., 2015). These community changes could have potential consequences at a functional level and on the C and nutrient cycling. Then, the recovery of soil microbial functions, such as the capacity to degrade compounds of different biochemical characteristics, may depend on the capacity of plant communities to regrow and provide different organic compounds through root turnover and exudation (Garcia-Pausas et al., 2022).

### 7.1.2. Impact of fire management on soil C stock and fluxes

Even in low intensity burns, the losses of ecosystem C and N can be significant (Certini, 2005; Homann et al., 2011). Although most of the studies agree unequivocally that untreated stands release more emissions to the atmosphere during a wildfire than treated stands (Restaino and Peterson, 2013), when considering the emissions derived from treatments, the relative effectiveness of fuel treatments in mitigating C losses is less clear, and highly variable (Restaino and Peterson, 2013: -33 Mg C ha⁻¹ to +3 Mg C ha⁻¹). For instance, in *Picea abies* forests of Finland, CO₂ efflux during the two years after clear-cutting and burning of slash was comparatively lower than the clear-cut only stand (difference ~10.1 Mg C ha⁻¹), but the total amount of CO₂ released was higher due to the immediate CO₂ emissions during burning (~28.0 Mg C ha⁻¹, Kulmala et al., 2014). Furthermore, a sink capacity of CH₄ is reduced during at least the first year after burning (Virkkula et al., 2014). In the long-term, however, the decay of logging residuals at the clear-cut stand may reduce the differences between clear-cutting with and without burning of slash (Table 1).

As litter and soil organic layers contain an important proportion of surface C stocks, the consumption of ground fuels during a prescribed burning can represent the largest fraction of emissions caused by fire management. Consequently, in ecosystems with deep organic horizons (e.g. boreal forests, peatlands) prescribed burning can negatively impact C storage (Pellegrini et al., 2022). In a meta-analysis on temperate forests, Nave et al. (2011) indicated that prescribed burning caused, on average, 46% and 35% reductions of the forest floor C and N stocks, respectively.

Depending on the temperatures reached, fires can also potentially alter the physical, chemical, and biological properties of the uppermost mineral horizons, which may affect key processes of the C cycling (Alcañiz et al., 2018; Certini, 2005). However, the heat transfer to the soil surface and into the soil is an uncertainty in modelling fire impact on soil processes (Table 1). The amount, characteristics and arrangement of fuels determines the proportion of released energy by fire that impacts forest floor and mineral layers. Thus, under slash piles soil temperature can reach more than 100°C at 10 cm depth, and even more intense and longer-lasting heating can occur in soils under wood piles (200-300°C) (Busse et al., 2013), causing stronger C and nutrient losses, soil physical alterations, and mortality of faunal and microbial communities. The heat transfer into organic and mineral layers during the burning of shredded debris is higher than during the burning of standing understory. In both managements, intense heating of mineral soil is generally restricted to the 2-5 cm soil depth, and diminishes steeply with depth (Cawson et al., 2016). Soil moisture limits temperature increase during a

fire (Busse et al., 2005); therefore, burning when organic and mineral soils are moist is outlined in the prescription guidance to prevent soil impacts (Table 1).

Overall, fire could eventually affect both C inputs to and outputs from the soil. Understory burning alters the quantity or quality of the organic matter inputs through shifts in plant community composition, abundance and vigour, which in turn may affect the microbial activity and organic matter mineralisation. However, mid-term changes in soil C and N after low-to-medium intensity prescribed burnings seem to be more related to plant community dynamics than to the direct effects of fire (Martí-Roura et al., 2011). Although litterfall increases during the first months after a prescribed burning (Espinosa et al., 2018), recovery of the forest floor mass to pre-fire stocks could take several years. For instance, in *Pinus ponderosa* forests of Oregon (US), Busse and Gerrard (2020) recorded faster rates of litter mass accumulation in burned than in unburned sites, but the recovery of organic horizons to pre-burning levels took about 15-20 years. Increase of litter N content, at least in places with a high frequency of burning, may contribute to litter decomposition (Ficken and Wright, 2017) and slow down the recovery of C stocks in organic horizons.

Despite the growing consensus among researchers and managers concerning the benefits of fire as a management tool for ecosystem issues such as wildfire hazard reduction, forest productivity, and biodiversity conservation of endangered species, the benefits of this practice for key soil components and functions are less obvious. Compared to the reduced and transient effects of low-intensity prescribed burns, burning shredded debris or slash piles have greater potential to negatively impact soil C stocks. In these cases, burning when organic and mineral soils are moist is mandatory to reduce soil C emissions. Minimizing soil C emissions during burning together with soil organic matter stabilization processes triggered by fire supports fire management as a smart forest tool to mitigate the effects of stand-replacing wildfires and enhancing forest biodiversity. We have extensive knowledge about the effects of fire management on soil physical and biogeochemical variables such as C and nutrient dynamics (e.g., Alcañiz et al., 2018; Martí-Roura et al., 2014, 2011 and references there-in), but less understanding about the cumulative effects of repeated burnings on soil functions. Thus, more knowledge is needed on a mechanistic understanding of plant and soil biota-mediated responses to different fire intensities and recurrences to avoid negative impacts on soils (Table 1).

### 7.1.3. Impact of fire management on soil C stability

Short-term organic C stock reduction after fire can be compensated in the long term by multiple transformations that increase the stability of organic matter and potentially buffer C emissions due to heterotrophic respiration (Pellegrini et al., 2021). Fire can alter the stability of soil organic matter by changing its physical protection and its biochemical quality. Partially charred organic material may have different biochemical quality than uncharred organic matter, altering their decomposition dynamics (Martí-Roura et al., 2014; Pellegrini et al., 2021). On the other hand, the rapid rise of soil temperature even under low intensity fires cause structural degradation of soil aggregates due to the steam pressure when there is a rapid vapourisation of soil pore water (Albalasmeh et al., 2013; Jian et al., 2018). This leads to a loss of C by microbial mineralisation of previously physically protected organic matter (Jian et al., 2018), and may also compromise the capacity of soils to stabilise new organic matter inputs. Structural degradation can also occur in the case of high intensity fires, if the organic matter that binds aggregates is burnt (Alcañiz et al., 2018).

On average, about 5% of the burned biomass is converted to pyrogenic C (PyC) (DeLuca et al., 2020), which is considered a stable form of C resistant to microbial degradation (Singh et al., 2012 but see Ghosal et al. 2016). In a data synthesis, DeLuca et al. (2020) found no significant differences in the amount of PyC produced by wildfires and prescribed fires (2.2±1.7 Mg ha⁻¹), with less variability observed in prescribed fires due to their usual low fire intensity. PyC not only represents a form of
long-term C storage, but also alters microbial processes and nutrient cycling (Pingree and DeLuca, 2017) and can adsorb organic compounds (i.e., exudates, microbial byproducts or other products derived from litter decomposition) (Gundale and DeLuca, 2006). The presence of PyC reduces the amount of soluble organic matter and increases its aromaticity (Hobley et al., 2019). However, the increase in SOM recalcitrance in the long term after a fire is not always related to an increased proportion of aromatic C, but could also be related to an increased abundance of condensed forms (Rovira et al., 2012). This increased biochemical recalcitrance may reduce the microbiological activity and nutrient cycling in soils. For instance, Speratti et al. (2018) showed that the addition of PyC (biochar) to forest soils reduced the mineralisation of native organic matter (negative priming). How relevant the interactions between fire intensity, soil characteristics and microorganisms' dynamics are for soil organic matter stabilization remains unclear (Table 1).

## 7.2. Modelling of post-fire C dynamics

Although several models have been applied to predict post-wildfire erosion (Wittenberg and Pereira, 2021), to our knowledge, no specific models have been developed to simulate post-fire soil physicochemical and microbial dynamics (Table 1). In the short-term, soil modelling should consider the effects of heating on soil communities and their recovery capacity. Forest fires cause a notable reduction in the microbial biomass in the top 10 cm soil (Wang et al., 2012). The magnitude of the effect mostly depends on the maximum temperature reached and the duration that temperatures exceed the lethal threshold, which depends on the fuel distribution and on soil water content. Soil water is volatilized under high temperature, and the vapor kills soil biota. At a similar temperature, mortality is greater in a humid soil than in a dry soil (Barreiro et al., 2020). Models should also account for the sudden increase of available nutrients, which may reduce microbial activity (Treseder, 2008), and the release of labile organic matter (Choromanska and DeLuca, 2002), which may prime the mineralisation of labile and recalcitrant organic pools in the uppermost mineral soil layers. Under intense fire, models should consider the pace at which soil functioning recovers, which in part is likely to depend on the recovery of litter inputs and vegetation regrowth (Garcia-Pausas et al., 2022). To our knowledge no specific simulation routines exist to account for the short-term impacts of fire on soil dynamics. In the mid- and long-term, as long as litterfall and vegetation recover, the dynamics of soil C can be modelled with some of the currently applied soil models, taking into account the effects of the reduction of soil organic layers caused by fire on the dynamics of uppermost soil layers.

# 8. Biodiversity management

## 8.1. Effects of biodiversity management on soil carbon stocks and GHG fluxes

### 8.1.1. *Rationale for biodiversity management*

Protection of key habitats or establishment of forest conservation areas that have high biodiversity value are major methods applied to maintain forest biodiversity. At forest stand scale, characteristics that enhance biodiversity include presence of old trees and broadleaf tree species, and availability of different categories of dead wood (Felton et al., 2016). Retention forestry, which creates these characteristics, suggests that forest stands are only partially cut, leaving single trees or groups of trees that age and die on site. Thus, the retention increases the forest dead wood C pool, but decreases the production of merchantable timber (Nunery and Keeton, 2010; Roberge et al., 2015; Santaniello et al., 2017). On the other hand, retention trees have positive impact on diversity of mycorrhiza, which determine the capacity of seedlings to take up water and nutrients (Korkama et al., 2006; Sterkenburg et al., 2019).

### 8.1.2. Impact of biodiversity management on soil C stock

Protection of key habitats or establishment of forest conservation areas that have high biodiversity value can have a positive impact on forest C stocks at the stand level. Old-growth forest conservation results in greater C stock in soils than does extensive and intensive forest management (Ameray et al., 2021), but measured differences in the soil C stocks between managed and unmanaged forests can be small or negligible partly due to differences in the site history and lower fertility level of the set-aside forest (Tamminen and Ilvesniemi, 2012).

The overall impact of tree retention on soil C stock has not been quantified. In general, retention increases input of coarse woody debris to the forest floor. Furthermore, it is known that fungi inhabiting wood in advanced decay stages transfer N from soil to dead wood (Mäkipää et al., 2017), which decreases the amount of N in the organic layer and can likely decrease the organic layer decomposition rate. On the other hand, retention of broadleaf species may increase decomposition, since as compared to conifers, broadleaf species generally have higher soil biological activity and decomposition rates, although these tree species effects are also mediated by site properties (Augusto et al., 2015).

Restoration of degraded ecosystems may provide co-benefits for climate change mitigation and biodiversity, e.g., C stock of dead wood and habitat availability for saprophytic species. However, restoration of boreal peatlands with positive biodiversity impacts may be an inefficient method to mitigate climate change (Juutinen et al. 2020). Peatland restoration is discussed in Chapter 6 and fire management in Chapter 7.

## 8.2. Modelling effects of biodiversity management on soil C and GHG fluxes

Forest conservation can be accounted for in forest ecosystem and soil models, which derive soil C stock changes from stand growth and soil edaphic and climatic conditions (e.g., Mäkipää et al. 2011). The changes in the dead wood and soil C stocks can be modelled with some of the currently applied soil models (e.g., YASSO07, Tuomi et al. 2011; CEN-TURY, Parton et al. 1987; ROMUL, Chertov et al. 2001), but these models do not fully account for changes in soil biological activity (Table 1). Modelling of the peatland hydrology restoration is discussed in chapter 6.2. and modelling of post-fire soil carbon dynamics in chapter 7.3.

# 9. Synthesis

The soil is the largest C pool in the forest (FAO, 2020) and potentially a large sink or source of GHGs (e.g., Ameray et al., 2021) that is affected by forest management decisions. In this review, we identified some highly likely impacts of commonly applied forest management practices on soil C stock or GHG emissions, and also potential impacts with high uncertainty and knowledge gaps (Table 2). We identified several management practices that can contribute to climate change mitigation by increasing soil C stock (e.g. transition from broadleaved to coniferous trees or mixed-stands, and N fertilization of boreal forest on mineral soil) or by reducing soil C loss or GHG emissions (e.g. sustainable fire management and elevated water level on peatland forests) (Table 2). On the other hand, soil carbon losses may be accelerated by intensive thinning regimes and harvesting practices (e.g. intensive stand thinning on mineral soils sites, whole tree harvesting and short rotation length), which are followed by mechanical site preparation that may accelerate soil C losses. In general, the direction of soil C and GHG emissions change due to various management practices can be derived from current knowledge, but further experimental studies, long-term monitoring and scenario modelling are needed to quantify and upscale the rate and magnitude of change (Table 2).

Forests are complex and dynamic ecosystems, where the responses of soil GHG fluxes to management often diverge from the responses of tree stand. This emphasizes the importance of soil measurements and development of soil models applicable to target ecosystems where
long-term C storage, but also alters microbial processes and nutrient cycling (Pingree and DeLuca, 2017) and can adsorb organic compounds (i.e., exudates, microbial byproducts or other products derived from litter decomposition) (Gundale and DeLuca, 2006). The presence of PyC reduces the amount of soluble organic matter and increases its aromaticity (Hobley et al., 2019). However, the increase in SOM recalcitrance in the long term after a fire is not always related to an increased proportion of aromatic C, but could also be related to an increased abundance of condensed forms (Rovira et al., 2012). This increased biochemical recalcitrance may reduce the microbiological activity and nutrient cycling in soils. For instance, Speratti et al. (2018) showed that the addition of PyC (biochar) to forest soils reduced the mineralisation of native organic matter (negative priming). How relevant the interactions between fire intensity, soil characteristics and microorganisms' dynamics are for soil organic matter stabilization remains unclear (Table 1).

## 7.2. Modelling of post-fire C dynamics

Although several models have been applied to predict post-wildfire erosion (Wittenberg and Pereira, 2021), to our knowledge, no specific models have been developed to simulate post-fire soil physicochemical and microbial dynamics (Table 1). In the short-term, soil modelling should consider the effects of heating on soil communities and their recovery capacity. Forest fires cause a notable reduction in the microbial biomass in the top 10 cm soil (Wang et al., 2012). The magnitude of the effect mostly depends on the maximum temperature reached and the duration that temperatures exceed the lethal threshold, which depends on the fuel distribution and on soil water content. Soil water is volatilized under high temperature, and the vapor kills soil biota. At a similar temperature, mortality is greater in a humid soil than in a dry soil (Barreiro et al., 2020). Models should also account for the sudden increase of available nutrients, which may reduce microbial activity (Treseder, 2008), and the release of labile organic matter (Choromanska and DeLuca, 2002), which may prime the mineralisation of labile and recalcitrant organic pools in the uppermost mineral soil layers. Under intense fire, models should consider the pace at which soil functioning recovers, which in part is likely to depend on the recovery of litter inputs and vegetation regrowth (Garcia-Pausas et al., 2022). To our knowledge no specific simulation routines exist to account for the short-term impacts of fire on soil dynamics. In the mid- and long-term, as long as litterfall and vegetation recover, the dynamics of soil C can be modelled with some of the currently applied soil models, taking into account the effects of the reduction of soil organic layers caused by fire on the dynamics of uppermost soil layers.

# 8. Biodiversity management

## 8.1. Effects of biodiversity management on soil carbon stocks and GHG fluxes

### 8.1.1. *Rationale for biodiversity management*

Protection of key habitats or establishment of forest conservation areas that have high biodiversity value are major methods applied to maintain forest biodiversity. At forest stand scale, characteristics that enhance biodiversity include presence of old trees and broadleaf tree species, and availability of different categories of dead wood (Felton et al., 2016). Retention forestry, which creates these characteristics, suggests that forest stands are only partially cut, leaving single trees or groups of trees that age and die on site. Thus, the retention increases the forest dead wood C pool, but decreases the production of merchantable timber (Nunery and Keeton, 2010; Roberge et al., 2015; Santaniello et al., 2017). On the other hand, retention trees have positive impact on diversity of mycorrhiza, which determine the capacity of seedlings to take up water and nutrients (Korkama et al., 2006; Sterkenburg et al., 2019).

### 8.1.2. Impact of biodiversity management on soil C stock

Protection of key habitats or establishment of forest conservation areas that have high biodiversity value can have a positive impact on forest C stocks at the stand level. Old-growth forest conservation results in greater C stock in soils than does extensive and intensive forest management (Ameray et al., 2021), but measured differences in the soil C stocks between managed and unmanaged forests can be small or negligible partly due to differences in the site history and lower fertility level of the set-aside forest (Tamminen and Ilvesniemi, 2012).

The overall impact of tree retention on soil C stock has not been quantified. In general, retention increases input of coarse woody debris to the forest floor. Furthermore, it is known that fungi inhabiting wood in advanced decay stages transfer N from soil to dead wood (Mäkipää et al., 2017), which decreases the amount of N in the organic layer and can likely decrease the organic layer decomposition rate. On the other hand, retention of broadleaf species may increase decomposition, since as compared to conifers, broadleaf species generally have higher soil biological activity and decomposition rates, although these tree species effects are also mediated by site properties (Augusto et al., 2015).

Restoration of degraded ecosystems may provide co-benefits for climate change mitigation and biodiversity, e.g., C stock of dead wood and habitat availability for saprophytic species. However, restoration of boreal peatlands with positive biodiversity impacts may be an inefficient method to mitigate climate change (Juutinen et al. 2020). Peatland restoration is discussed in Chapter 6 and fire management in Chapter 7.

## 8.2. Modelling effects of biodiversity management on soil C and GHG fluxes

Forest conservation can be accounted for in forest ecosystem and soil models, which derive soil C stock changes from stand growth and soil edaphic and climatic conditions (e.g., Mäkipää et al. 2011). The changes in the dead wood and soil C stocks can be modelled with some of the currently applied soil models (e.g., YASSO07, Tuomi et al. 2011; CEN-TURY, Parton et al. 1987; ROMUL, Chertov et al. 2001), but these models do not fully account for changes in soil biological activity (Table 1). Modelling of the peatland hydrology restoration is discussed in chapter 6.2. and modelling of post-fire soil carbon dynamics in chapter 7.3.

# 9. Synthesis

The soil is the largest C pool in the forest (FAO, 2020) and potentially a large sink or source of GHGs (e.g., Ameray et al., 2021) that is affected by forest management decisions. In this review, we identified some highly likely impacts of commonly applied forest management practices on soil C stock or GHG emissions, and also potential impacts with high uncertainty and knowledge gaps (Table 2). We identified several management practices that can contribute to climate change mitigation by increasing soil C stock (e.g. transition from broadleaved to coniferous trees or mixed-stands, and N fertilization of boreal forest on mineral soil) or by reducing soil C loss or GHG emissions (e.g. sustainable fire management and elevated water level on peatland forests) (Table 2). On the other hand, soil carbon losses may be accelerated by intensive thinning regimes and harvesting practices (e.g. intensive stand thinning on mineral soils sites, whole tree harvesting and short rotation length), which are followed by mechanical site preparation that may accelerate soil C losses. In general, the direction of soil C and GHG emissions change due to various management practices can be derived from current knowledge, but further experimental studies, long-term monitoring and scenario modelling are needed to quantify and upscale the rate and magnitude of change (Table 2).

Forests are complex and dynamic ecosystems, where the responses of soil GHG fluxes to management often diverge from the responses of tree stand. This emphasizes the importance of soil measurements and development of soil models applicable to target ecosystems where
climate change mitigation potential is evaluated or mitigation measures are planned. Incomplete or biased information may lead to inefficient climate policy and non-optimal use of resources. For instance, drainage of forested peatlands can enhance the C sequestration of growing stock in a Norway spruce dominated stands, but the continuous GHG emissions of nutrient-rich peat soils are larger than the temporary C sink of the tree stand in the long term (over a rotation period or longer) (Ahtikoski et al., 2022; Shanin et al., 2021). Furthermore, reported high CO₂ and N₂O emissions after clear-cutting of the drained fertile peatland sites indicate that more sustainable management regimes are needed, such as continuous cover forestry as an alternative to rotation forestry (Korkiakoski et al. 2019; Nieminen et al. 2018). Since the direction of change in the soil carbon stock can be opposite to that of trees, at least in short term, assessment of the forest C sink that considers only trees is incomplete and likely to be invalid and we strongly recommend moving towards comprehensive GHG inventories, forest monitoring methods and scenario analyses that quantify the total GHG balance of the forest including the forest soils. Thus, further improvements in forest inventories/forest soil surveys, soil models and data analysis are needed. Reliable soil models, GHG scenario tools and monitoring methods will contribute to the design and evaluation of climate policy targets in the EU and globally (National Inventory Report (NIR) European Union 2021; Forsell et al., 2018).

Effects of forest management practices are not yet widely integrated into scenario analyses that support climate and forest policy, since forest management affects soil processes in multiple ways, effects in different conditions are not well quantified, and many have not yet been included in the modelling frameworks (Fig. 1, Table 1). In general, the management effects that change biomass production and litter quantity and quality are represented by soil models. Changes in environmental conditions such as soil temperature and moisture are sometimes represented in soil models, and depend on relevant and representative measurements that describe the effects of various management interventions (Table 1). The climate change mitigation potential of forest soils, as estimated by modelling approaches, depends on stand biomass driven effects (such as quantity and quality of litter input) and climate factors that affect the decomposition rate. Thus, management practices that change tree species composition, volume of the growing stock or natural mortality can be accounted for when litter input to the soil is estimated. However, forest C modelling based on the biomass change without consideration of soil characteristics cannot account for loss of nutrients in removed biomass and feedbacks that reduced nutrient availability have on the future growth of trees (e.g. Palosuo et al., 2008). Dynamic biomass production without considering the feedback of changing soil properties may be biased, as variation in forest growth and productivity is determined by soil conditions, such as soil fertility and water content; therefore any changes in these conditions may affect the future C sink of vegetation (Mäkipää et al., 2015; Shanin et al., 2016).

The dynamic changes of soil preparation or management, which can directly modify soil temperature, moisture, nutrient balance, microbial processes, erosion, hydrology and oxygen concentration, are not explicitly represented in the models (Table 1). For example, models like Yasso07 (Tuomi et al., 2011) and CENTURY (Parton et al., 1987) are used for the analyses of forest C sinks and applied in national GHG inventories (IPCC 2019) but exclude effects of forest management, although some more comprehensive ecosystem models include them. For example, SUSI (Laurén et al., 2021) and ORCHIDEE (Chang et al., 2013; Levis et al., 2012; Wu et al., 2016) can simulate impacts of management on hydrology, soil temperature, and soil C cycling for peatlands and croplands, respectively. Terrestrial biosphere models including landscape scale models have historically been developed to understand and make predictions for undisturbed ecosystems, with land management representation added later. As a result, estimation of land

management effects on soil C, nutrient and water cycles are often based on few studies (Levis et al., 2012; Zhou et al., 2021) and primarily considers the ways in which various land management practices modify existing processes rather than adding new processes. Parsimonious soil C models with less input data requirements e.g., Yasso and CENTURY as formulated in Sierra et al., (2012) are more spatially applicable e.g., on regional and global scale than more complex models which contain more site-specific parameters and are computationally demanding. However, complex models account for more processes affecting the decomposition and soil C stabilization, thus including interactions between soil properties, microbiota, nutrients, and management. In general, soil C stabilization processes, e.g. organic-mineral interactions, microbial decomposition, or the chemical complexity or organic compounds, are not included in the current models and require further measurements and new generation models. The most challenging task in modelling is to integrate management effects that change soil microbial communities and their functioning. Here further understanding on the variation of microbial community structure and functional roles of fungi and bacteria are needed. We emphasize that both measurements from empirical studies and modelling supported by development of theory need to work together, and incorporating more processes in modelling may enhance our ability to reliably predict the future.

We need to develop and efficiently implement more ambitious mitigation and adaptation to tackle climate change and the unforeseen risks that changing conditions introduce to ecosystems, provision of ecosystem services and human wellbeing. Since soil is a large C stock, it is essential to understand effects of planned management practices on soil processes and to avoid risks of turning soil from a C and GHG sink to a source. Meanwhile, supply of sustainably produced timber and other ecosystem services need to be maintained. This review explores the potential of soil management practices to mitigate climate change, as well as the current capacity of modelling and scenario analysis tools to support planning of forest operations and climate policy. We stress that current models and analysis frameworks do not fully account for the relevant soil processes described in this review and encourage the parsimonious development of multiple models and analysis frameworks to support the estimation and optimization of soil GHG balance for climate policy.

## Declaration of Competing Interest

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

## Data availability

This is review article and published peer reviewed articles are used as a data in this study

## Acknowledgements

This review has been supported by the grant Holistic management practices, modelling and monitoring for European forest soils – HoliSoils (EU Horizon 2020 Grant Agreement No 101000289) and the Academy of Finland Fellow project (330136, B. Adamczyk). In addition to the HoliSoils consortium partners, Dr. Abramoff contributed on this study and her work was supported by the United States Department of Energy, Office of Science, Office of Biological and Environmental Research. Oak Ridge National Laboratory is managed by UT-Battelle, LLC, for the United States Department of Energy under contract DE-AC05-00OR22725.
climate change mitigation potential is evaluated or mitigation measures are planned. Incomplete or biased information may lead to inefficient climate policy and non-optimal use of resources. For instance, drainage of forested peatlands can enhance the C sequestration of growing stock in a Norway spruce dominated stands, but the continuous GHG emissions of nutrient-rich peat soils are larger than the temporary C sink of the tree stand in the long term (over a rotation period or longer) (Ahtikoski et al., 2022; Shanin et al., 2021). Furthermore, reported high CO₂ and N₂O emissions after clear-cutting of the drained fertile peatland sites indicate that more sustainable management regimes are needed, such as continuous cover forestry as an alternative to rotation forestry (Korkiakoski et al. 2019; Nieminen et al. 2018). Since the direction of change in the soil carbon stock can be opposite to that of trees, at least in short term, assessment of the forest C sink that considers only trees is incomplete and likely to be invalid and we strongly recommend moving towards comprehensive GHG inventories, forest monitoring methods and scenario analyses that quantify the total GHG balance of the forest including the forest soils. Thus, further improvements in forest inventories/forest soil surveys, soil models and data analysis are needed. Reliable soil models, GHG scenario tools and monitoring methods will contribute to the design and evaluation of climate policy targets in the EU and globally (National Inventory Report (NIR) European Union 2021; Forsell et al., 2018).

Effects of forest management practices are not yet widely integrated into scenario analyses that support climate and forest policy, since forest management affects soil processes in multiple ways, effects in different conditions are not well quantified, and many have not yet been included in the modelling frameworks (Fig. 1, Table 1). In general, the management effects that change biomass production and litter quantity and quality are represented by soil models. Changes in environmental conditions such as soil temperature and moisture are sometimes represented in soil models, and depend on relevant and representative measurements that describe the effects of various management interventions (Table 1). The climate change mitigation potential of forest soils, as estimated by modelling approaches, depends on stand biomass driven effects (such as quantity and quality of litter input) and climate factors that affect the decomposition rate. Thus, management practices that change tree species composition, volume of the growing stock or natural mortality can be accounted for when litter input to the soil is estimated. However, forest C modelling based on the biomass change without consideration of soil characteristics cannot account for loss of nutrients in removed biomass and feedbacks that reduced nutrient availability have on the future growth of trees (e.g. Palosuo et al., 2008). Dynamic biomass production without considering the feedback of changing soil properties may be biased, as variation in forest growth and productivity is determined by soil conditions, such as soil fertility and water content; therefore any changes in these conditions may affect the future C sink of vegetation (Mäkipää et al., 2015; Shanin et al., 2016).

The dynamic changes of soil preparation or management, which can directly modify soil temperature, moisture, nutrient balance, microbial processes, erosion, hydrology and oxygen concentration, are not explicitly represented in the models (Table 1). For example, models like Yasso07 (Tuomi et al., 2011) and CENTURY (Parton et al., 1987) are used for the analyses of forest C sinks and applied in national GHG inventories (IPCC 2019) but exclude effects of forest management, although some more comprehensive ecosystem models include them. For example, SUSI (Laurén et al., 2021) and ORCHIDEE (Chang et al., 2013; Levis et al., 2012; Wu et al., 2016) can simulate impacts of management on hydrology, soil temperature, and soil C cycling for peatlands and croplands, respectively. Terrestrial biosphere models including landscape scale models have historically been developed to understand and make predictions for undisturbed ecosystems, with land management representation added later. As a result, estimation of land

management effects on soil C, nutrient and water cycles are often based on few studies (Levis et al., 2012; Zhou et al., 2021) and primarily considers the ways in which various land management practices modify existing processes rather than adding new processes. Parsimonious soil C models with less input data requirements e.g., Yasso and CENTURY as formulated in Sierra et al., (2012) are more spatially applicable e.g., on regional and global scale than more complex models which contain more site-specific parameters and are computationally demanding. However, complex models account for more processes affecting the decomposition and soil C stabilization, thus including interactions between soil properties, microbiota, nutrients, and management. In general, soil C stabilization processes, e.g. organic-mineral interactions, microbial decomposition, or the chemical complexity or organic compounds, are not included in the current models and require further measurements and new generation models. The most challenging task in modelling is to integrate management effects that change soil microbial communities and their functioning. Here further understanding on the variation of microbial community structure and functional roles of fungi and bacteria are needed. We emphasize that both measurements from empirical studies and modelling supported by development of theory need to work together, and incorporating more processes in modelling may enhance our ability to reliably predict the future.

We need to develop and efficiently implement more ambitious mitigation and adaptation to tackle climate change and the unforeseen risks that changing conditions introduce to ecosystems, provision of ecosystem services and human wellbeing. Since soil is a large C stock, it is essential to understand effects of planned management practices on soil processes and to avoid risks of turning soil from a C and GHG sink to a source. Meanwhile, supply of sustainably produced timber and other ecosystem services need to be maintained. This review explores the potential of soil management practices to mitigate climate change, as well as the current capacity of modelling and scenario analysis tools to support planning of forest operations and climate policy. We stress that current models and analysis frameworks do not fully account for the relevant soil processes described in this review and encourage the parsimonious development of multiple models and analysis frameworks to support the estimation and optimization of soil GHG balance for climate policy.

## Declaration of Competing Interest

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

## Data availability

This is review article and published peer reviewed articles are used as a data in this study

## Acknowledgements

This review has been supported by the grant Holistic management practices, modelling and monitoring for European forest soils – HoliSoils (EU Horizon 2020 Grant Agreement No 101000289) and the Academy of Finland Fellow project (330136, B. Adamczyk). In addition to the HoliSoils consortium partners, Dr. Abramoff contributed on this study and her work was supported by the United States Department of Energy, Office of Science, Office of Biological and Environmental Research. Oak Ridge National Laboratory is managed by UT-Battelle, LLC, for the United States Department of Energy under contract DE-AC05-00OR22725.
## Appendix A. Literature search on effects of different management practices on forest soil C and GHG fluxes.

<table><thead><tr><th>Management practice</th><th>Searching strings (used for title, abstract or keywords)</th><th>Databases</th><th>Number of studies screened</th><th>Number of studies included</th></tr></thead><tbody><tr><td>Stand thinning and harvesting practices</td><td>soil AND (carbon OR respiration) AND forest AND (thinning OR clear cut* OR logging OR harvest*)</td><td>Web of Science, Google Scholar</td><td>341</td><td>95</td></tr><tr><td>Tree species selection</td><td>(soil carbon OR soil organic carbon) AND (tree species OR tree species identity OR tree species diversity)</td><td>Google Scholar, JSTOR</td><td>57</td><td>41</td></tr><tr><td>Fire management</td><td>((Prescribed &amp; (fire* OR burn*)) OR (slash &amp; burn*)) &amp; Soil* &amp; Forest*.</td><td>Web of Science</td><td>165 (of which 30 were reviews and 6 were meta-analyses)</td><td>44</td></tr><tr><td>Nutrient management, incl. N fertilization, wood ash fertilization and liming</td><td>"nitrogen fertilization" OR "nitrogen addition" OR "wood ash fertilization" OR "wood ash addition" OR "liming" OR "limestone" (Title) and "forest*" (Title) and "soil*" (Title) and "carbon stock*" OR "carbon storage*" OR "organic matter decomposition" OR "organic matter mineralization" OR "enzyme*" OR "litter" OR "lignin" OR "soil respiration" OR "greenhouse gas" OR "greenhouse gas *flux*" OR "CO2" OR "carbon dioxide" OR "CH4" OR "methane" OR "N2O" OR "nitrous oxide" (Topic) and English (Language) and 2012.01.01-2022.12.31 (publication date)</td><td>Web of Science, Google Scholar, CAB,</td><td>N fertilization, wood ash and liming: 47</td><td>N fertilization, wood ash and liming: 47</td></tr><tr><td>Chemical agents</td><td>soil carbon AND forest AND (herbicide* OR pesticide* OR chemical agent*)</td><td>Google Scholar, JSTOR</td><td>22</td><td>12</td></tr><tr><td>Peatland hydrology and restoration</td><td>"peatland" OR "drained peatland" OR "forestry-drained peatland" OR "restored peatland" OR "drained peatland forest" with "hydrology management" OR "hydrology restoration" OR "rewetting" OR "water table management" OR "forest-to-bog"</td><td>Google Scholar</td><td>96</td><td>33</td></tr></tbody></table>

## References

Abramoff, R., Xu, X., Hartman, M., O'Brien, S., Feng, W., Davidson, E., Finzi, A., Moorhead, D., Schimel, J., Torn, M., Mayes, M.A., 2018. The Millennial model: in search of measurable pools and transformations for modeling soil carbon in the new century. Biogeochemistry 137, 51–71. https://doi.org/10.1007/s10533-017-0409-7.

Abramoff, R.Z., Davidson, E.A., Finzi, A.C., 2017. A parsimonious modular approach to building a mechanistic belowground carbon and nitrogen model. J. Geophys. Res. Biogeosciences 122, 2418–2434. https://doi.org/10.1002/2017JG003796.

Abramoff, R.Z., Guenet, B., Zhang, H., Georgiou, K., Xu, X., Viscarra Rossel, R.A., Yuan, W., Ciais, P., 2022. Improved global-scale predictions of soil carbon stocks with Millennial Version 2. Soil Biol. Biochem. 164, 108466 https://doi.org/10.1016/j.soilbio.2021.108466.

Achat, D.L., Deleuze, C., Landmann, G., Pousse, N., Ranger, J., Augusto, L., 2015. Quantifying consequences of removing harvesting residues on forest soils and tree growth – A meta-analysis. For. Ecol. Manag. 348, 124–141. https://doi.org/10.1016/j.foreco.2015.03.042.

Adamczyk, B., Adamczyk, S., Kukkola, M., Tamminen, P., Smolander, A., 2015. Logging residue harvest may decrease enzymatic activity of boreal forest soils. Soil Biol. Biochem. 82, 74–80. https://doi.org/10.1016/j.soilbio.2014.12.017.

Adamczyk, B., Sietiö, O.-M., Straková, P., Prommer, J., Wild, B., Hagner, M., Pihlatie, M., Fritze, H., Richter, A., Heinonsalo, J., 2019. Plant roots increase both decomposition and stable organic matter formation in boreal forest soil. Nat. Commun. 10, 3982. https://doi.org/10.1038/s41467-019-11993-1.

Agee, J.K., Skinner, C.N., 2005. Basic principles of forest fuel reduction treatments. For. Ecol. Manag., Relative Risk Assessments for Decision-Making Related To Uncharacteristic Wildfire 211, 83–96. https://doi.org/10.1016/j.foreco.2005.01.034.

Ågren, G.I., Bosatta, E., Magill, A.H., 2001. Combining theory and experiment to understand effects of inorganic nitrogen on litter decomposition. Oecologia 128, 94–98. https://doi.org/10.1007/s004420100646.

Ahtikoski, A., Rämö, J., Juutinen, A., Shanin, V., Mäkipää, R., 2022. Continuous Cover Forestry and Cost of Carbon Abatement on Mineral Soils and Peatlands. Front. Environ. Sci. 10 https://doi.org/10.3389/fenvs.2022.837878.

Akujärvi, A., Shvidenko, A., Pietsch, S.A., 2019. Modelling the impacts of intensifying forest management on carbon budget across a long latitudinal gradient in Europe. Environ. Res. Lett. 14, 034012 https://doi.org/10.1088/1748-9326/aaf766.

Albalasmeh, A.A., Berli, M., Shafer, D.S., Ghezzehei, T.A., 2013. Degradation of moist soil aggregates by rapid temperature rise under low intensity fire. Plant Soil 362, 335–344. https://doi.org/10.1007/s11104-012-1408-z.

Alcañiz, M., Outeiro, L., Francos, M., Úbeda, X., 2018. Effects of prescribed fires on soil properties: A review. Sci. Total Environ. 613–614, 944–957. https://doi.org/10.1016/j.scitotenv.2017.09.144.

Aldea, J., Bravo, F., Bravo-Oviedo, A., Ruiz-Peinado, R., Rodríguez, F., del Río, M., 2017. Thinning enhances the species-specific radial increment response to drought in Mediterranean pine-oak stands. Agric. For. Meteorol. 237–238, 371–383. https://doi.org/10.1016/j.agrformet.2017.02.009.

Ameray, A., Bergeron, Y., Valeria, O., Montoro Girona, M., Cavard, X., 2021. Forest Carbon Management: a Review of Silvicultural Practices and Management Strategies

Across Boreal, Temperate and Tropical Forests. Curr. For. Rep. 7, 245–266. https://doi.org/10.1007/s40725-021-00151-w.

Augusto, L., Bakker, M.R., Meredieu, C., 2008. Wood ash applications to temperate forest ecosystems—potential benefits and drawbacks. Plant Soil 306, 181–198. https://doi.org/10.1007/s11104-008-9570-z.

Augusto, L., Boca, A., 2022. Tree functional traits, forest biomass, and tree species diversity interact with site properties to drive forest soil carbon. Nat. Commun. 13, 1097. https://doi.org/10.1038/s41467-022-28748-0.

Augusto, L., De Schrijver, A., Vesterdal, L., Smolander, A., Prescott, C., Ranger, J., 2015. Influences of evergreen gymnosperm and deciduous angiosperm tree species on the functioning of temperate and boreal forests. Biol. Rev. 90, 444–466. https://doi.org/10.1111/brv.12119.

Banerjee, T., 2020. Impacts of Forest Thinning on Wildland Fire Behavior. Forests 11, 918. https://doi.org/10.3390/f11090918.

Bang-Andreasen, T., Nielsen, J.T., Voriskova, J., Heise, J., Rønn, R., Kjøller, R., Hansen, H.C.B., Jacobsen, C.S., 2017. Wood Ash Induced pH Changes Strongly Affect Soil Bacterial Numbers and Community Composition. Front. Microbiol. 8 https://doi.org/10.3389/fmicb.2017.01400.

Barreiro, A., Lombao, A., Martín, A., Cancelo-González, J., Carballas, T., Díaz-Raviña, M., 2020. Soil Heating at High Temperatures and Different Water Content: Effects on the Soil Microorganisms. Geosciences 10, 355. https://doi.org/10.3390/geosciences10090355.

Baskaran, P., Hyvönen, R., Berglund, S.L., Clemmensen, K.E., Ågren, G.I., Lindahl, B.D., Manzoni, S., 2017. Modelling the influence of ectomycorrhizal decomposition on plant nutrition and soil carbon sequestration in boreal forest ecosystems. New Phytol. 213, 1452–1465. https://doi.org/10.1111/nph.14213.

Berhongaray, G., Cotrufo, F.M., Janssens, I.A., Ceulemans, R., 2019. Below-ground carbon inputs contribute more than above-ground inputs to soil carbon accrual in a bioenergy poplar plantation. Plant Soil 434, 363–378. https://doi.org/10.1007/s11104-018-3850-z.

Björk, R.G., Ernfors, M., Sikström, U., Nilsson, M.B., Andersson, M.X., Rütting, T., Klemedtsson, L., 2010. Contrasting effects of wood ash application on microbial community structure, biomass and processes in drained forested peatlands. FEMS Microbiol. Ecol. 73, 550–562. https://doi.org/10.1111/j.1574-6941.2010.00911.x.

Blaško, R., Forsmark, B., Gundale, M.J., Lundmark, T., Nordin, A., 2020. Impacts of tree species identity and species mixing on ecosystem carbon and nitrogen stocks in a boreal forest. For. Ecol. Manag. 458, 117783 https://doi.org/10.1016/j.foreco.2019.117783.

Bonner, M.T.L., Castro, D., Schneider, A.N., Sundström, G., Hurry, V., Street, N.R., Näsholm, T., 2019. Why does nitrogen addition to forest soils inhibit decomposition? Soil Biol. Biochem. 137, 107570 https://doi.org/10.1016/j.soilbio.2019.107570.

Börn, M.L., Rønn, R., Ekelund, F., 2020. Is wood ash amendment a suitable mitigation strategy for N₂O emissions from soil? Sci. Total Environ. 713, 136581 https://doi.org/10.1016/j.scitotenv.2020.136581.

Bossio, D.A., Cook-Patton, S.C., Ellis, P.W., Fargione, J., Sanderman, J., Smith, P., Wood, S., Zomer, R.J., von Unger, M., Emmer, I.M., Griscom, B.W., 2020. The role of soil carbon in natural climate solutions. Nat. Sustain. 3, 391–398. https://doi.org/10.1038/s41893-020-0491-z.

Bradbury, N.J., Whitmore, A.P., Hart, P.B.S., Jenkinson, D.S., 1993. Modelling the fate of nitrogen in crop and soil in the years following application of ¹⁵N-labelled fertilizer
## Appendix A. Literature search on effects of different management practices on forest soil C and GHG fluxes.

<table><thead><tr><th>Management practice</th><th>Searching strings (used for title, abstract or keywords)</th><th>Databases</th><th>Number of studies screened</th><th>Number of studies included</th></tr></thead><tbody><tr><td>Stand thinning and harvesting practices</td><td>soil AND (carbon OR respiration) AND forest AND (thinning OR clear cut* OR logging OR harvest*)</td><td>Web of Science, Google Scholar</td><td>341</td><td>95</td></tr><tr><td>Tree species selection</td><td>(soil carbon OR soil organic carbon) AND (tree species OR tree species identity OR tree species diversity)</td><td>Google Scholar, JSTOR</td><td>57</td><td>41</td></tr><tr><td>Fire management</td><td>((Prescribed &amp; (fire* OR burn*)) OR (slash &amp; burn*)) &amp; Soil* &amp; Forest*.</td><td>Web of Science</td><td>165 (of which 30 were reviews and 6 were meta-analyses)</td><td>44</td></tr><tr><td>Nutrient management, incl. N fertilization, wood ash fertilization and liming</td><td>"nitrogen fertilization" OR "nitrogen addition" OR "wood ash fertilization" OR "wood ash addition" OR "liming" OR "limestone" (Title) and "forest*" (Title) and "soil*" (Title) and "carbon stock*" OR "carbon storage*" OR "organic matter decomposition" OR "organic matter mineralization" OR "enzyme*" OR "litter" OR "lignin" OR "soil respiration" OR "greenhouse gas" OR "greenhouse gas *flux*" OR "CO2" OR "carbon dioxide" OR "CH4" OR "methane" OR "N2O" OR "nitrous oxide" (Topic) and English (Language) and 2012.01.01-2022.12.31 (publication date)</td><td>Web of Science, Google Scholar, CAB,</td><td>N fertilization, wood ash and liming: 47</td><td>N fertilization, wood ash and liming: 47</td></tr><tr><td>Chemical agents</td><td>soil carbon AND forest AND (herbicide* OR pesticide* OR chemical agent*)</td><td>Google Scholar, JSTOR</td><td>22</td><td>12</td></tr><tr><td>Peatland hydrology and restoration</td><td>"peatland" OR "drained peatland" OR "forestry-drained peatland" OR "restored peatland" OR "drained peatland forest" with "hydrology management" OR "hydrology restoration" OR "rewetting" OR "water table management" OR "forest-to-bog"</td><td>Google Scholar</td><td>96</td><td>33</td></tr></tbody></table>

## References

Abramoff, R., Xu, X., Hartman, M., O'Brien, S., Feng, W., Davidson, E., Finzi, A., Moorhead, D., Schimel, J., Torn, M., Mayes, M.A., 2018. The Millennial model: in search of measurable pools and transformations for modeling soil carbon in the new century. Biogeochemistry 137, 51–71. https://doi.org/10.1007/s10533-017-0409-7.

Abramoff, R.Z., Davidson, E.A., Finzi, A.C., 2017. A parsimonious modular approach to building a mechanistic belowground carbon and nitrogen model. J. Geophys. Res. Biogeosciences 122, 2418–2434. https://doi.org/10.1002/2017JG003796.

Abramoff, R.Z., Guenet, B., Zhang, H., Georgiou, K., Xu, X., Viscarra Rossel, R.A., Yuan, W., Ciais, P., 2022. Improved global-scale predictions of soil carbon stocks with Millennial Version 2. Soil Biol. Biochem. 164, 108466 https://doi.org/10.1016/j.soilbio.2021.108466.

Achat, D.L., Deleuze, C., Landmann, G., Pousse, N., Ranger, J., Augusto, L., 2015. Quantifying consequences of removing harvesting residues on forest soils and tree growth – A meta-analysis. For. Ecol. Manag. 348, 124–141. https://doi.org/10.1016/j.foreco.2015.03.042.

Adamczyk, B., Adamczyk, S., Kukkola, M., Tamminen, P., Smolander, A., 2015. Logging residue harvest may decrease enzymatic activity of boreal forest soils. Soil Biol. Biochem. 82, 74–80. https://doi.org/10.1016/j.soilbio.2014.12.017.

Adamczyk, B., Sietiö, O.-M., Straková, P., Prommer, J., Wild, B., Hagner, M., Pihlatie, M., Fritze, H., Richter, A., Heinonsalo, J., 2019. Plant roots increase both decomposition and stable organic matter formation in boreal forest soil. Nat. Commun. 10, 3982. https://doi.org/10.1038/s41467-019-11993-1.

Agee, J.K., Skinner, C.N., 2005. Basic principles of forest fuel reduction treatments. For. Ecol. Manag., Relative Risk Assessments for Decision-Making Related To Uncharacteristic Wildfire 211, 83–96. https://doi.org/10.1016/j.foreco.2005.01.034.

Ågren, G.I., Bosatta, E., Magill, A.H., 2001. Combining theory and experiment to understand effects of inorganic nitrogen on litter decomposition. Oecologia 128, 94–98. https://doi.org/10.1007/s004420100646.

Ahtikoski, A., Rämö, J., Juutinen, A., Shanin, V., Mäkipää, R., 2022. Continuous Cover Forestry and Cost of Carbon Abatement on Mineral Soils and Peatlands. Front. Environ. Sci. 10 https://doi.org/10.3389/fenvs.2022.837878.

Akujärvi, A., Shvidenko, A., Pietsch, S.A., 2019. Modelling the impacts of intensifying forest management on carbon budget across a long latitudinal gradient in Europe. Environ. Res. Lett. 14, 034012 https://doi.org/10.1088/1748-9326/aaf766.

Albalasmeh, A.A., Berli, M., Shafer, D.S., Ghezzehei, T.A., 2013. Degradation of moist soil aggregates by rapid temperature rise under low intensity fire. Plant Soil 362, 335–344. https://doi.org/10.1007/s11104-012-1408-z.

Alcañiz, M., Outeiro, L., Francos, M., Úbeda, X., 2018. Effects of prescribed fires on soil properties: A review. Sci. Total Environ. 613–614, 944–957. https://doi.org/10.1016/j.scitotenv.2017.09.144.

Aldea, J., Bravo, F., Bravo-Oviedo, A., Ruiz-Peinado, R., Rodríguez, F., del Río, M., 2017. Thinning enhances the species-specific radial increment response to drought in Mediterranean pine-oak stands. Agric. For. Meteorol. 237–238, 371–383. https://doi.org/10.1016/j.agrformet.2017.02.009.

Ameray, A., Bergeron, Y., Valeria, O., Montoro Girona, M., Cavard, X., 2021. Forest Carbon Management: a Review of Silvicultural Practices and Management Strategies

Across Boreal, Temperate and Tropical Forests. Curr. For. Rep. 7, 245–266. https://doi.org/10.1007/s40725-021-00151-w.

Augusto, L., Bakker, M.R., Meredieu, C., 2008. Wood ash applications to temperate forest ecosystems—potential benefits and drawbacks. Plant Soil 306, 181–198. https://doi.org/10.1007/s11104-008-9570-z.

Augusto, L., Boca, A., 2022. Tree functional traits, forest biomass, and tree species diversity interact with site properties to drive forest soil carbon. Nat. Commun. 13, 1097. https://doi.org/10.1038/s41467-022-28748-0.

Augusto, L., De Schrijver, A., Vesterdal, L., Smolander, A., Prescott, C., Ranger, J., 2015. Influences of evergreen gymnosperm and deciduous angiosperm tree species on the functioning of temperate and boreal forests. Biol. Rev. 90, 444–466. https://doi.org/10.1111/brv.12119.

Banerjee, T., 2020. Impacts of Forest Thinning on Wildland Fire Behavior. Forests 11, 918. https://doi.org/10.3390/f11090918.

Bang-Andreasen, T., Nielsen, J.T., Voriskova, J., Heise, J., Rønn, R., Kjøller, R., Hansen, H.C.B., Jacobsen, C.S., 2017. Wood Ash Induced pH Changes Strongly Affect Soil Bacterial Numbers and Community Composition. Front. Microbiol. 8 https://doi.org/10.3389/fmicb.2017.01400.

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Bradford, J.B., Bell, D.M., 2017. A window of opportunity for climate-change adaptation: easing tree mortality by reducing forest basal area. Front. Ecol. Environ. 15, 11-17. https://doi.org/10.1002/fee.1445.

Bravo-Oviedo, A., Ruiz-Peinado, R., Modrego, P., Alonso, R., Montero, G., 2015. Forest thinning impact on carbon stock and soil condition in Southern European populations of P. sylvestris L. For. Ecol. Manag. 357, 259-267. https://doi.org/10.1016/j.foreco.2015.08.005.

Brumme, R., Beeze, F., 1992. Effects of liming and nitrogen fertilization on emissions of CO₂ and N₂O from a temperature forest. J. Geophys. Res. Atmospheres 97, 12851-12858. https://doi.org/10.1029/92JD01217.

Burgess, D., Baldock, J.A., Wetzell, S., Brand, D.G., 1995. Scarification, fertilization and herbicide treatment effects on planted conifers and soil fertility. Plant Soil 168 (169), 513-522. https://doi.org/10.1007/BF00029364.

Busse, M., Gerrard, R., 2020. Thinning and Burning Effects on Long-Term Litter Accumulation and Function in Young Ponderosa Pine Forests. For. Sci. 66, 761-769. https://doi.org/10.1093/forsci/fxa0018.

Busse, M.D., Hubbert, K.R., Fiddler, G.O., Shestak, C.J., Powers, R.F., Busse, M.D., Hubbert, K.R., Fiddler, G.O., Shestak, C.J., Powers, R.F., 2005. Lethal soil temperatures during burning of masticated forest residues. Int. J. Wildland Fire 14, 267-276. https://doi.org/10.1071/WF04062.

Busse, M.D., Shestak, C.J., Hubbert, K.R., Busse, M.D., Shestak, C.J., Hubbert, K.R., 2013. Soil heating during burning of forest slash piles and wood piles. Int. J. Wildland Fire 22, 786-796. https://doi.org/10.1071/WF12179.

Campbell, J., Alberti, G., Martin, J., Law, B.E., 2009. Carbon dynamics of a ponderosa pine plantation following a thinning treatment in the northern Sierra Nevada. For. Ecol. Manag. 257, 453-463. https://doi.org/10.1016/j.foreco.2008.09.021.

Casals, P., Rios, A.I., 2018. Burning intensity and low light availability reduce resprouting ability and vigor of Buxus sempervirens L. after clearing. Sci. Total Environ. 627, 403-416. https://doi.org/10.1016/j.scitotenv.2018.01.227.

Cawson, J.G., Nyman, P., Smith, H.G., Lane, P.N.J., Sheridan, G.J., 2016. How soil temperatures during prescribed burning affect soil water repellency, infiltration and erosion. Geoderma 278, 12-22. https://doi.org/10.1016/j.geoderma.2016.05.002.

Certini, G., 2005. Effects of fire on properties of forest soils: a review. Oecologia 143, 1-10. https://doi.org/10.1007/s00442-004-1788-8.

Chan, A.S.K., Steudler, P.A., Bowden, R.D., Gulledge, J., Cavanaugh, C.M., 2005. Consequences of nitrogen fertilization on soil methane consumption in a productive temperature deciduous forest. Soil Fertil. Soils 41, 182-189. https://doi.org/10.1007/s00374-004-0822-7.

Chang, J.F., Viovy, N., Vuichard, N., Ciais, P., Wang, T., Cozic, A., Lardy, R., Graux, A.-L., Klumpp, K., Martin, R., Soussana, J.-F., 2013. Incorporating grassland management in ORCHIDEE: model description and evaluation at 11 eddy-covariance sites in Europe. Geosci. Model Dev. 6, 2165-2181. https://doi.org/10.5194/gmd-6-2165-2013.

Chen, J., Luo, Y., van Groenigen, K.J., Hungate, B.A., Cao, J., Zhou, X., Wang, R., 2018. A keystone microbial enzyme for nitrogen control of soil carbon storage. Sci. Adv. 4, eaqa1689.

Cheng, X., Yu, M., Wu, T., 2013. Effect of Forest Structural Change on Carbon Storage in a Coastal Metasequoia glyptostroboides Stand. Sci. World J. 2013, e830509.

Chertov, O.G., Komarov, A.S., Nadporozhskaya, M., Bykhovets, S.S., Zudin, S.L., 2001. ROMUL — a model of forest soil organic matter dynamics as a substantial tool for forest ecosystem modeling. Ecol. Model. 138, 289-308. https://doi.org/10.1016/S0304-3800(00)00409-9.

Chiti, T., Perugini, L., Vespertino, D., Valentini, R., 2016. Effect of selective logging on soil organic carbon dynamics in tropical forests in central and western Africa. Plant Soil 399, 283-294. https://doi.org/10.1016/j.foreco.2016.05.015-2697.9.

Choromanska, U., DeLuca, T.H., 2002. Microbial activity and nitrogen mineralization in forest mineral soils following heating: evaluation of post-fire effects. Soil Bio. Biochem. 34, 263-271. https://doi.org/10.1016/S0038-0717(01)00180-8.

Clarke, N., Gunderson, P., Jönsson-Belyazid, U., Kjønaas, O.J., Pessin, T., Sigurdsson, B. D., Stupak, I., Vesterdal, L., 2015. Influence of different tree-harvesting intensities on forest soil carbon stocks in boreal and northern temperature forest ecosystems. For. Ecol. Manag. 351, 9-19. https://doi.org/10.1016/j.foreco.2015.04.034.

Clarke, N., Kiær, L.P., Janne Kjønaas, O., Bárcena, T.G., Vesterdal, L., Stupak, I., Finér, L., Jacobson, S., Armolaitis, K., Lazdina, D., Stefánsdóttir, H.M., Sigurdsson, B.D., 2021. Effects of intensive biomass harvesting on forest soils in the Nordic countries and the UK: A meta-analysis. For. Ecol. Manag. 482, 118877. https://doi.org/10.1016/j.foreco.2020.118877.

Clemmensen, K.E., Bahr, R., Ovaskainen, O., Dahlberg, A., Ekblad, A., Wallander, H., Stenlid, J., Finlay, R.D., Wardle, D.A., Lindahl, B.D., 2013. Roots and Associated Fungi Drive Long-Term Carbon Sequestration in Boreal Forest. Science 339, 1615-1618. https://doi.org/10.1126/science.1231923.

Coleman, K., Jenkinson, D.S., 1996. RothC-26.3 - A Model for the turnover of carbon in soil. In: Powlson, D.S., Smith, P., Smith, J.U. (Eds.), Evaluation of Soil Organic Matter Models, NATO ASI Series. Springer, Berlin, Heidelberg, pp. 237-246. https://doi.org/10.1007/978-3-642-61094-3_17.

Cotrufo, M.F., Soong, J.L., Horton, A.J., Campbell, E.E., Haddix, M.L., Wall, D.H., Parton, W.J., 2015. Formation of soil organic matter via biochemical and physical pathways of litter mass loss. Nat. Geosci. 8, 776-779. https://doi.org/10.1038/ngeo2520.

Cotrufo, M.F., Wallenstein, M.D., Boot, C.M., Denef, K., Paul, E., 2013. The Microbial Efficiency-Matrix Stabilization (MEMS) framework integrates plant litter decomposition with soil organic matter stabilization: do labile plant inputs form stable soil organic matter? Glob. Change Biol. 19, 988-995. https://doi.org/10.1111/gcb.12113.

Craine, J.M., Morrow, C., Fierer, N., 2007. Microbial nitrogen limitation increases decomposition. Ecology 88, 2105-2113. https://doi.org/10.1890/06-1847.1.

Creevy, A.L., Payne, R.J., Andersen, R., Rowson, J.G., 2020. Annual gaseous carbon budgets of forest-to-bog restoration sites are strongly determined by vegetation composition. Sci. Total Environ. 705, 135863 https://doi.org/10.1016/j.scitotenv.2019.135863.

Cruz-Paredes, C., Bang-Andreasen, T., Christensen, S., Ekelund, F., Froslév, T.G., Jacobsen, C.S., Johansen, J.L., Mortensen, L.H., Rønn, R., Vestergård, M., Kjøller, R., 2021. Bacteria Respond Stronger Than Fungi Across a Steep Wood Ash-Driven pH Gradient. Front. For. Glob. Change 4. https://doi.org/10.3389/ffgc.2021.781844.

Cruz-Paredes, C., Wallander, H., Kjøller, R., Rousk, J., 2017. Using community trait-distributions to assign microbial responses to pH changes and Cd in forest soils treated with wood ash. Soil Biol. Biochem. 112, 153-164. https://doi.org/10.1016/j.soilbio.2017.05.004.

Dalsgaard, L., Lange, H., Strand, L.T., Callesen, I., Borgen, S.K., Liski, J., Astrup, R., 2016. Underestimation of boreal forest soil carbon stocks related to soil classification and drainage. Can. J. For. Res. 46, 1413-1425. https://doi.org/10.1139/cjfr-2015-0466.

D'Amato, A.W., Bradford, J.B., Fraver, S., Palik, B.J., 2013. Effects of thinning on drought vulnerability and climate response in north temperate forest ecosystems. Ecol. Appl. 23, 1735-1742. https://doi.org/10.1890/13-0677.1.

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Feng, J., He, K., Zhang, Q., Han, M., Zhu, B., 2022. Changes in plant inputs alter soil carbon and microbial communities in forest ecosystems. Glob. Change Biol. 28, 3426-3440. https://doi.org/10.1111/gcb.16107.

Fernandes, P.M., Davies, G.M., Ascoli, D., Fernández, C., Moreira, F., Rigolot, E., Stoof, C. R., Vega, J.A., Molina, D., 2013. Prescribed burning in southern Europe: developing
to winter wheat. J. Agric. Sci. 121, 363-379. https://doi.org/10.1017/S0021859600085567.

Bradford, J.B., Bell, D.M., 2017. A window of opportunity for climate-change adaptation: easing tree mortality by reducing forest basal area. Front. Ecol. Environ. 15, 11-17. https://doi.org/10.1002/fee.1445.

Bravo-Oviedo, A., Ruiz-Peinado, R., Modrego, P., Alonso, R., Montero, G., 2015. Forest thinning impact on carbon stock and soil condition in Southern European populations of P. sylvestris L. For. Ecol. Manag. 357, 259-267. https://doi.org/10.1016/j.foreco.2015.08.005.

Brumme, R., Beeze, F., 1992. Effects of liming and nitrogen fertilization on emissions of CO₂ and N₂O from a temperature forest. J. Geophys. Res. Atmospheres 97, 12851-12858. https://doi.org/10.1029/92JD01217.

Burgess, D., Baldock, J.A., Wetzell, S., Brand, D.G., 1995. Scarification, fertilization and herbicide treatment effects on planted conifers and soil fertility. Plant Soil 168 (169), 513-522. https://doi.org/10.1007/BF00029364.

Busse, M., Gerrard, R., 2020. Thinning and Burning Effects on Long-Term Litter Accumulation and Function in Young Ponderosa Pine Forests. For. Sci. 66, 761-769. https://doi.org/10.1093/forsci/fxa0018.

Busse, M.D., Hubbert, K.R., Fiddler, G.O., Shestak, C.J., Powers, R.F., Busse, M.D., Hubbert, K.R., Fiddler, G.O., Shestak, C.J., Powers, R.F., 2005. Lethal soil temperatures during burning of masticated forest residues. Int. J. Wildland Fire 14, 267-276. https://doi.org/10.1071/WF04062.

Busse, M.D., Shestak, C.J., Hubbert, K.R., Busse, M.D., Shestak, C.J., Hubbert, K.R., 2013. Soil heating during burning of forest slash piles and wood piles. Int. J. Wildland Fire 22, 786-796. https://doi.org/10.1071/WF12179.

Campbell, J., Alberti, G., Martin, J., Law, B.E., 2009. Carbon dynamics of a ponderosa pine plantation following a thinning treatment in the northern Sierra Nevada. For. Ecol. Manag. 257, 453-463. https://doi.org/10.1016/j.foreco.2008.09.021.

Casals, P., Rios, A.I., 2018. Burning intensity and low light availability reduce resprouting ability and vigor of Buxus sempervirens L. after clearing. Sci. Total Environ. 627, 403-416. https://doi.org/10.1016/j.scitotenv.2018.01.227.

Cawson, J.G., Nyman, P., Smith, H.G., Lane, P.N.J., Sheridan, G.J., 2016. How soil temperatures during prescribed burning affect soil water repellency, infiltration and erosion. Geoderma 278, 12-22. https://doi.org/10.1016/j.geoderma.2016.05.002.

Certini, G., 2005. Effects of fire on properties of forest soils: a review. Oecologia 143, 1-10. https://doi.org/10.1007/s00442-004-1788-8.

Chan, A.S.K., Steudler, P.A., Bowden, R.D., Gulledge, J., Cavanaugh, C.M., 2005. Consequences of nitrogen fertilization on soil methane consumption in a productive temperature deciduous forest. Soil Fertil. Soils 41, 182-189. https://doi.org/10.1007/s00374-004-0822-7.

Chang, J.F., Viovy, N., Vuichard, N., Ciais, P., Wang, T., Cozic, A., Lardy, R., Graux, A.-L., Klumpp, K., Martin, R., Soussana, J.-F., 2013. Incorporating grassland management in ORCHIDEE: model description and evaluation at 11 eddy-covariance sites in Europe. Geosci. Model Dev. 6, 2165-2181. https://doi.org/10.5194/gmd-6-2165-2013.

Chen, J., Luo, Y., van Groenigen, K.J., Hungate, B.A., Cao, J., Zhou, X., Wang, R., 2018. A keystone microbial enzyme for nitrogen control of soil carbon storage. Sci. Adv. 4, eaqa1689.

Cheng, X., Yu, M., Wu, T., 2013. Effect of Forest Structural Change on Carbon Storage in a Coastal Metasequoia glyptostrobooides Stand. Sci. World J. 2013, e830509.

Chertov, O.G., Komarov, A.S., Nadporozhskaya, M., Bykhovets, S.S., Zudin, S.L., 2001. ROMUL — a model of forest soil organic matter dynamics as a substantial tool for forest ecosystem modeling. Ecol. Model. 138, 289-308. https://doi.org/10.1016/S0304-3800(00)00409-9.

Chiti, T., Perugini, L., Vespertino, D., Valentini, R., 2016. Effect of selective logging on soil organic carbon dynamics in tropical forests in central and western Africa. Plant Soil 399, 283-294. https://doi.org/10.1016/j.foreco.2016.05.015-2697.9.

Choromanska, U., DeLuca, T.H., 2002. Microbial activity and nitrogen mineralization in forest mineral soils following heating: evaluation of post-fire effects. Soil Bio. Biochem. 34, 263-271. https://doi.org/10.1016/S0038-0717(01)00180-8.

Clarke, N., Gunderson, P., Jönsson-Belyazid, U., Kjønaas, O.J., Pessin, T., Sigurdsson, B. D., Stupak, I., Vesterdal, L., 2015. Influence of different tree-harvesting intensities on forest soil carbon stocks in boreal and northern temperature forest ecosystems. For. Ecol. Manag. 351, 9-19. https://doi.org/10.1016/j.foreco.2015.04.034.

Clarke, N., Kiær, L.P., Janne Kjønaas, O., Bárcena, T.G., Vesterdal, L., Stupak, I., Finér, L., Jacobson, S., Armolaitis, K., Lazdina, D., Stefánsdóttir, H.M., Sigurdsson, B.D., 2021. Effects of intensive biomass harvesting on forest soils in the Nordic countries and the UK: A meta-analysis. For. Ecol. Manag. 482, 118877. https://doi.org/10.1016/j.foreco.2020.118877.

Clemmensen, K.E., Bahr, R., Ovaskainen, O., Dahlberg, A., Ekblad, A., Wallander, H., Stenlid, J., Finlay, R.D., Wardle, D.A., Lindahl, B.D., 2013. Roots and Associated Fungi Drive Long-Term Carbon Sequestration in Boreal Forest. Science 339, 1615-1618. https://doi.org/10.1126/science.1231923.

Coleman, K., Jenkinson, D.S., 1996. RothC-26.3 - A Model for the turnover of carbon in soil. In: Powlson, D.S., Smith, P., Smith, J.U. (Eds.), Evaluation of Soil Organic Matter Models, NATO ASI Series. Springer, Berlin, Heidelberg, pp. 237-246. https://doi.org/10.1007/978-3-642-61094-3_17.

Cotrufo, M.F., Soong, J.L., Horton, A.J., Campbell, E.E., Haddix, M.L., Wall, D.H., Parton, W.J., 2015. Formation of soil organic matter via biochemical and physical pathways of litter mass loss. Nat. Geosci. 8, 776-779. https://doi.org/10.1038/ngeo2520.

Cotrufo, M.F., Wallenstein, M.D., Boot, C.M., Denef, K., Paul, E., 2013. The Microbial Efficiency-Matrix Stabilization (MEMS) framework integrates plant litter decomposition with soil organic matter stabilization: do labile plant inputs form stable soil organic matter? Glob. Change Biol. 19, 988-995. https://doi.org/10.1111/gcb.12113.

Craine, J.M., Morrow, C., Fierer, N., 2007. Microbial nitrogen limitation increases decomposition. Ecology 88, 2105-2113. https://doi.org/10.1890/06-1847.1.

Creevy, A.L., Payne, R.J., Andersen, R., Rowson, J.G., 2020. Annual gaseous carbon budgets of forest-to-bog restoration sites are strongly determined by vegetation composition. Sci. Total Environ. 705, 135863 https://doi.org/10.1016/j.scitotenv.2019.135863.

Cruz-Paredes, C., Bang-Andreasen, T., Christensen, S., Ekelund, F., Froslav, T.G., Jacobsen, C.S., Johansen, J.L., Mortensen, L.H., Rønn, R., Vestergård, M., Kjøller, R., 2021. Bacteria Respond Stronger Than Fungi Across a Steep Wood Ash-Driven pH Gradient. Front. For. Glob. Change 4. https://doi.org/10.3389/ffgc.2021.781844.

Cruz-Paredes, C., Wallander, H., Kjøller, R., Rousk, J., 2017. Using community trait-distributions to assign microbial responses to pH changes and Cd in forest soils treated with wood ash. Soil Biol. Biochem. 112, 153-164. https://doi.org/10.1016/j.soilbio.2017.05.004.

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