Bedrock has a signifcant role in vegetation growth by regulating physical and chemical properties of soils (Hamh et al. 2014) and has a substantial infuence on soil erosion processes (Milodowski et al. 2015). It is the source of mineral nutrients and infuences soil texture characteristics controlling the water and nutrient retention capacity, but can also present a supply of heavy metals that have an adverse infuence on plant growth (Jiang et al. 2020). Soil texture in forest soils determines soil water and aeration, both important for tree growth and microbial processes (Gomez-Guarrerro and Doane 2018). Soil degradation includes higher bulk density and lower hydraulic conductivity and extensive nutrient losses in soils (Hajabbasi et al. 1997). Loss of porosity leads to infltration reduction, loss of soil volume, and enhances soil erosion. However, these effects might be happening at the same time and causal (Poff 1996). Similar is true for textural properties. Soils with high silt, low clay, and low organic matter content are generally considered to be more erodible. However, this is not straightforward and particle size distribution has to be considered in relation to other soil physical and chemical properties (Wischmeier and Mannering 1969).

Altieri et al. (2018) have experimentally shown that soil erosion is not a substantial problem in well-managed forests and minimal values of soil loss were reported in areas with high canopy cover and biomass. However, some authors indicate that new silvicultural treatments should be planned with care, since, as established by earlier studies, loss of forest cover, either due to deforestation or climate change, can impose a serious problem with long-term consequences. If the topsoil layer is disturbed due to natural or human-induced causes, such as wildfre, harvesting, and prescription burning, erosion rates can substantially rise. Relationship between soil disturbance and soil productivity is a complex interconnection among soil physical properties, nutrient cycling, and climate. The disturbance effect depends on soil local characteristics and microclimate, so mitigation solutions have to be sitespecifc (Elliot et al. 1996).

## *8.4.4 Forest Damages*

Forest disturbances are, in many cases, inseparably related to climate change (Dale et al. 2000, 2001; Reyer et al. 2017; Seidl et al. 2017). Disturbances, human-induced and naturally caused mostly by wind, insects, fungi, fres, droughts, heatwaves, and their interactions, shape the forest ecosystems in terms of species composition, structure, and processes. Proactive disturbance-risk management should encompass adaptive silvicultural measures, being a part of the adaptive forest management, which enable using some strategies to counteract the effects of climate change resulting in forest disturbances. These possible actions should be undertaken considering uncertainties about climate change impacts on forests and their reactions (Lindner et al. 2014). The potential silvicultural disturbance-prevention measures include (1) the use of more climate-adapted tree species or their genotypes (Kauppi et al. 2018; Thurm et al. 2018), the introduction of economic alternatives to main

species (Deuffc et al. 2020), management to facilitate the establishment of species outside of historical natural ranges and genomics-based assisted migration in reforestation (transformation) (Hagerman and Pelai 2018); (2) application of more diversifed species composition of forests (mixtures of conifers with broadleaves, shade-tolerant with intolerant species, more drought-resistant with less-resistant species) involving also conversion from single-species to multispecies stands where site conditions permit (Kerr et al. 2010; Jactel et al. 2017), this allows to distribute silvicultural risk to many tree species in a stand; (3) managing for and/or increasing resilience (Hagerman and Pelai 2018); (4) more frequent and intensive thinnings (selective or differentiation) and shorter and/or diversifed rotation length (Jactel et al. 2009; Silva et al. 2018; Deuffc et al. 2020); (5) shaping the diversifed age structure of forests (uneven-aged/selection structure) (Schütz 2002; O'Hara 2014; Deuffc et al. 2020); (6) increasing stand stability and decreasing stand density (Knoke et al. 2008; Deuffc et al. 2020); (7) fre-smart landscape management techniques (Kauppi et al. 2018; Lindner et al. 2020). In addition, the realization of the concepts of close-to-nature silviculture (Schütz 1999; Brang et al. 2014; O'Hara 2014) and/or continuous cover forestry (Mason et al. 1999; Pukkala and Gadov 2012) seems to enhance adaptation to climate change and, to some extent, mitigate its effects on forests (Fig. 8.1).

**Fig. 8.1** Forest damages caused by the windstorm Xynthia (2010) in la Val d'Aran (NE, Spain). (Photo: Álvaro Aunós)

## *8.4.5 Increment and Felling*

In the case of close-to-nature mountain mixed and uneven-aged forests, comprised of species combination such as silver fr (*Abies alba* Mill.), Norway spruce (*Picea abies* (L.) Karst.) and European beech (*Fagus sylvatica* L.), all silvicultural operations attempt to achieve growth sustainability from one cutting cycle to the next and continuous forest cover for preventing soil erosion. To this end, the single and/or group selection (plenter) system can be used in mountain regions across Europe (Schütz 2001a). In the selection forest, the mixture of trees of different sizes (diameter at breast height and height), ages, and species, growing together in a small area (<0.1 ha) (Schütz 2001a; Bončina 2011a; O'Hara 2014), results in much more steady course of growth, in comparison to one species dominated even-aged stands, at both tree and stand level (Fig. 8.2). The higher resilience of stand growth to silviculturally induced density reductions in mixed, uneven-aged mountain forests can be observed as in this case, trees in the medium and lower canopy layers can compensate (buffer) for losses in the upper layer and vice versa (Mitscherlich 1952; Assmann 1970).

In the structural stable mountain forests (Fig. 8.3), the equilibrium state is achieved when standing volume remains relatively constant from one cutting cycle to the next; in the other words, the harvest volume equals increment. Therefore, the value of periodic volume increment may serve as an additional important parameter to consider, when regulating the long-term development of mixed, uneven-aged

**Fig. 8.2** Tree level and stand level growth pattern in two contrasting silvicultural systems: simple even-aged forests (black line) and complex uneven-aged forests (grey line), managed by a clearcutting and selection system, respectively. *In the frst case, the growth (*e.g.*, tree diameter left and stand volume increment right) follows the unimodal curve and changes more rapidly (up and down) over the time with a clear pick during the optimal developmental phase, to decreases, however, to zero at the time of the initiation of subsequent forest generation by clearcuttings or shelterwood cuttings with short regeneration period (10–20 years). In the selection forest, the combination of trees of many sizes, age classes, and species buffers the changes in the growth pattern and thus a steadier increment course can be observed.* (Adapted from Schütz (2001a) and Pretzsch et al. (2015) (after Assmann 1970) in case of a tree and stand level, respectively)

**Fig. 8.3** The vertical and horizontal structural stable close-to-nature mountain mixed and unevenaged stand, comprised of silver fr (Abies alba Mill.), European beech (Fagus sylvatica L.) and Norway spruce (Picea abies (L.) Karst.), as well as other minor tree species, managed by selection (plenter) system on the long-term experimental plot in the Zagnansk Forest District (Poland)

mountain forests. Schütz (2001a) described the plenter structure as being maintained through continuous control of the growing stock (standing volume); a growing stock over the equilibrium would lead to reduced regeneration and recruitment into smaller diameter classes, whereas levels of growing stock below the equilibrium would reduce total increment and the quality of trees as well as to overpromote the natural regeneration and recruitment rate. However, in some cases such as the current stand diameter structure deviates signifcantly from the equilibrium curve (e.g., when stands previously were managed by uniform or irregular shelterwood cuttings), the transformation by applying heavy structural differentiation thinning is recommended, to reduce mainly the density in the middle diameter at breast height classes and, therefore, as a consequence, also the stand productivity.

Finally, if the proportion of more light-demanding tree species in the stand is required, the irregular shelterwood system, emulating the natural gap dynamic pattern, would be also recommended in the scope of climate-smart silviculture. The main difference between selection and irregular shelterwood systems lies in an emphasis on individual trees in the former case versu. cohorts of trees in the latter (Schütz et al. 2016). Moreover, the irregular shelterwood system gives a free hand to the manager. On the one hand, it is possible to create larger openings by clearcutting (e.g., up to 0.5 ha) when regeneration of more light-demanding tree species (larch, pine, oak) is required, and on the other hand, the shelter or group and single selection cuttings may be applied for intermediate (sycamore, spruce, elm) and more shade-tolerant tree species (lime and beech) as well (cf. Schütz 2001a; Raymond et al. 2009). During the long regeneration period (e.g., 40–50 years), the volume increment of regeneration and overstorey add up. Thus, compared with an age-class forest, the total volume increment's oscillations are much less distinct (cf. Fig. 8.2). The more multilayered a stand and the more horizontally diverse it is, the higher is its growth resilience to natural and silvicultural interferences (Pretzsch et al. 2015).

## *8.4.6 Tree Species Composition*

In production forests, the diversity of tree species composition positively affects other indices of biodiversity and shows close relationships with multiple ecosystem services (e.g., Gamfeldt et al. 2013; Bravo-Oviedo et al. 2014; Almeida et al. 2018). However, in the case of provisioning services, the forest development stage is also of great importance (Zeller and Pretzsch 2019).

None of the single tree species in a forest is able to safeguard a provision of the full set of ecosystem services. On the other hand, the provision of some services can be impossible, since they might be negatively correlated with each other. Therefore, in order of satisfying the society demands regarding multiple ecosystem services the production forests should be managed considering use of the various tree species. No doubt that tree species diversity positively infuences ecosystem functioning, but in some cases, probably the effect of species identity is stronger compared with diversity (Nadrowski et al. 2010). If the dominating tree species is badly chosen, then changing it back to the former one might reverse the negative outcomes for biodiversity, production, and recreational values, as well as on stand vulnerability to a wind, frost, and drought damage, as well as on risks of pathogen or insect outbreak (Felton et al. 2019).

Tree species diversity of temperate mountain forests is much lower if compared to the tree species diversity in forests of lower vegetation belts (i.e., planar-hilly, sub-montane). Therefore, management options regarding tree species are much broader in lower areas. For the adaptation of mountain forests to climate change, it is highly important (1) to maintain/increase genetic variation in the species, (2) to increase structural diversity (Brang et al. 2014), and (3) to assure that all "natural" tree species of mountain forests are present in a forest stand. However, quite often, European mountain forests contain mainly three tree species – Norway spruce, silver fr, and European beech. Especially, recruitment of silver fr into these forests is often restricted or even prevented due to browsing pressure (e.g., Ficko et al. 2011; Simončič et al. 2019), which noticeably decreases adaptation capacity of forests to climate change. The additional characteristics if compared to the forests in lower

elevations are that in mountain forests, many minor tree species (e.g., *Sorbus aucuparia*, *Salix* sp.) cannot compete or are economically less important for forest managers/owners, while some other with possible high economic value (i.e., *Ulmus glabra*, *Fraxinus excelsior*) suffer from diseases. Therefore, tree species from genus *Acer*, *Larix*, and *Pinus* gain higher importance for the adaptation of mountain forests to climate change.

There is increasing evidence that tree species mixtures positively infuence forest functionality. Forest stands with tree species with different functional traits enhance forest ftness in the face of climate change as they include different "strategies" concerning plant establishment and competitiveness (Jactel et al. 2017). Moreover, in many cases, species-rich forests with high functional diversity are more productive than less diverse forests (Pretzsch et al. 2010). In stands where light demanding and shade-tolerant, canopy and understory or deep-rooting, and shallow-rooting species are combined, resources such as light, water, and nutrients can be spatially and temporarily used differently and thus more effciently. Such forests are more resistant to various abiotic disturbance events, such as drought, fres, or storms (Bravo-Oviedo et al. 2014; Knoke et al. 2008; Schütz et al. 2006; Spellmann et al. 2011; Lebourgeois et al. 2013), and more resilient once a disturbance has occurred (Jactel et al. 2009, 2017). With an increasing number of functionally different species, the probability increases that some of these species can resist external disturbances or changing environmental conditions (i.e., the ecological insurance concept, according to Yachi and Loreau 1999). Examples are the bark beetle *Ips typographus* that attacks Norway spruce (*Picea abies*), but not broad-leaved species or silver fr (*Abies alba*) (Wermelinger 2004), or the ash dieback (*Hymenoscyphus pseudoalbidus*) affecting exclusively *Fraxinus excelsior* (Kjær et al. 2012). In addition to functional diversity, the redundancy of species increases the probability that one species can take over the role of another species that does not survive (Walker et al. 1999; Messier et al. 2019).

It is assumed that in the future also mountain forest ecosystems are severely affected by water shortage (Collin 2020). The admixture of broadleaved tree species in conifer stands can have positive effects on soil water availability, thus reducing water stress for the trees. There is evidence that interception losses are higher in pure conifer stands with Scots pine and Norway spruce compared to broadleaved or mixed stands with European beech (Barbier et al. 2009; Berger et al. 2009). In a study in northeastern Germany, Müller (2009) analyzed seepage rates in mixtures of Scots pine with European beech compared to pure Scots pine stands. The higher seepage in mixed stands is due to reduced interception losses and a higher stemfow on broadleaved trees compared to pine. Moreover, in pure (pine) stands, dense ground vegetation layers of the grass *Calamagrostis* lead to a further reduction of the soil water content (Müller and Bolte 2009).

Other complementarity effects with respect to water supply of species mixtures are reported, such as hydraulic redistribution or the different stomatal behavior of the trees. Thus, water availability in mixed stands can be positively infuenced, although many effects are observed at the drier end of the gradients and are not yet quantifed (Grossiord et al. 2014; Bauhus et al. 2017).

## *8.4.7 Regeneration*

One of the most important practices to increase species richness is the choice of regeneration cut or the silvicultural system, respectively. Here, the future species composition of the forest can actively be changed by replacing tree species and/or tree individuals sensitive to climate change with trees of native or introduced species and/or species' provenances that are potentially better adapted to future climate conditions (called active adaptation; Martín-Alcón et al. 2016; Bolte et al. 2009). Examples for this strategy are the ongoing conversion of pure Norway spruce stands into mixed stands or silvicultural measures aiming at replacing species such as Norway spruce by other species of comparable economic value (e.g., Douglas fr). In Germany, the Bavarian State Department of Environment, Health and Consumer Protection published a regional climate program in November 2007 that includes an example for the application of the "active adaptation" concepts on species level. It is planned to convert about 200,000 ha of pure Norway spruce forests by 2030 in areas where a high risk of drought damage is assumed to less sensitive mixed forests, predominantly with European beech and oak (Stmelf 2018).

The concomitant natural establishment of diverse species can be controlled by creating large variations in light conditions, allowing both light-demanding and shade-tolerant species to regenerate (e.g., group selection or irregular shelterwood in combination with strip cuts). In young growth originating from natural regeneration, enrichment planting is a valuable practice to introduce additional species. Once young trees are established, species richness can be maintained by appropriate tending measures, such as precommercial thinning or thinning. Especially rare species or species with low competitiveness, in particular, if they are adapted to a warmer and drier climate, have to be released in this case (Brang et al. 2008). Finally, the successful establishment of species-rich stands depends very much on the control of ungulates (Gill 1992; Götmark et al. 2005; Ameztegui and Coll 2015). To achieve the optimal adaptive effect of species mixtures, large monospecifc patches should be avoided as well as very intimate mixtures, which usually require high tending investments. Forest conversion encompasses the use of the many native (mostly broadleaved) tree species, and selected exotic tree species, respectively. From tree species trials and recent dendroecological analyses, we know that rare native species and non-native tree species can increase forest resilience in a landscape (Kunz et al. 2018; Vitali et al. 2017). Furthermore, provenances of native tree species from warmer regions of the species' distribution range could enrich forest diversity in mountainous regions. Especially these rear-edge populations (Hampe and Petit 2005) of native species often show desired adaptation traits, such as higher drought stress tolerance compared to provenances from the core distribution area of a species.

In the early stage of conversion, an interesting option to diversify forest stands is currently discussed in Germany. Some authors have recommended integrating early successional species, which seem to be more adapted to the drier site conditions into

regular stand management in the tree species portfolio (Lüpke 2009). Early successional species quickly cover bare regeneration sites. They recover nutrients, which otherwise would likely be lost and are valuable elements for enhancing biodiversity (nurse crops). Moreover, there is growing evidence to abandon the practice of a merely local provenance choice. Assisted migration, the planned translocation of provenances and species beyond their natural occurrence range, has the potential to ensure that provenances or species are adapted enough to cope with the future warmer climate in the fnal stage of their development cycle. At the same time, stands must be robust enough to get along with still harsh climatic conditions in the establishment phase when they are young plants. Already well-developed recommendations for assisted migration transfer distances have been developed for Douglas fr in the Northwest USA (Sáenz-Romero et al. 2016).

## *8.4.8 Naturalness*

The concept of naturalness has been broadly used in forestry. The naturalness of forest stands can be assessed by different indicators (e.g., Brumelis et al. 2011; Winter 2012); tree species composition is one of the most important. The naturalness of tree species composition for a given forest site is estimated by comparison between current tree species composition and the natural tree species composition of forest stand, which is a part of potential natural vegetation. Due to climate change, natural vegetation may change over several decades (e.g., Hickler et al. 2012).

The analyses of forest stands in the Dinaric mountain areas (Bončina et al. 2017) showed that the alteration of the natural tree species composition of forest stands is primarily the result of forest management and past land-use, conditioned either by topography or accessibility of forests. The portion of Norway spruce increased due to past forest management. A higher level of alteration of natural tree species composition of mountain forests signifcantly increases the susceptibility of forest stands to natural disturbances – mainly windthrows and insect outbreaks. Therefore, sanitary felling can be a few times larger than in stands with natural tree species composition (e.g., Pasztor et al. 2015; Bončina et al. 2017).

In general, for the introduction of new, exotic tree species and provenances, it is suggested to follow the order: (1) species that are already adapted on a larger scale in the planting region and tested non-autochthonous provenances, then (2) new species with knowledge on their behavior but no adaptation yet, and fnally (3) completely new species (Spathelf and Bolte 2020). Currently, only a few forest owners have started to plant nonnative tree species other than Douglas fr, red oak, and grand fr on a larger scale. Nevertheless, around 10–20 "new" species are in the search of forest research institutes across Europe. Existing trials with non-native species are currently evaluated and new trials established (de Avila and Albrecht 2017; Brang et al. 2016; Metzger et al. 2012).

## *8.4.9 Introduced Tree Species*

Tree species have been deliberately moved by humans for as long as humans have been cultivating land for food, fuel, and fber. Indeed, it is highly probable that tree species were inadvertently moved by our hunter-gatherer ancestors, just as other primates do today (Chapman 1989). Long before the development of countries with borders and associated concepts, such as nativeness, immigration, introduction, or invasiveness, humans travelled and traded and the only considerations were what thrived where, and what value it had as a product. For trees, the main considerations would have been fruit and nut production, foliage and bark for animal fodder, frewood potential, and use as a building material.

As concepts of forest management developed, the choice of tree species for timber production has become increasingly sophisticated. It may even be that tree species selection was the frst conscious silvicultural decision? Originally it is probable that some native tree species were preferred by foresters; for example, oak has long been advocated in Britain for ship-building (Evelyn 1664; Fisher 1763). Where one tree species is favored, others inevitably decline in abundance. In the past, when there was no concept of genetic diversity or origin, although native tree species might have been selected for planting, the seed itself might have been introduced from another country.

It is diffcult to trace the widespread use of nonnative (also known as exotic or introduced) species in plantation forestry, but it is always likely to have been most prevalent in countries like the UK with low native tree species richness. For example, at least one introduced tree species, European larch (*Larix decidua*), has been being planted in the UK since the mid eighteenth century when medals and cash prizes were awarded to those who planted most trees by the Royal Society for the Encouragement of the Arts. In their frst full transactions published in 1783, the summary of the activities since the inauguration in 1754 showed that a sum of 50 £ had been paid alongside the award of 45 gold and 14 silver medals for the "encouragement of planting to raise Timber" from a list of trees, including oak, but also larch (Anon 1783). Larch would have been included on the list, because softwood timber was considered best for ship's masts and the UK has only three native conifers, juniper (*Juniperus communis*), yew (*Taxus baccata*), and Scots pine (*Pinus sylvestris*), of which only one, Scots pine, can grow suffciently straight and tall to be used as a ship's mast.

In the early nineteenth century, the great plant hunters, such as David Douglas, sent new coniferous tree species back to Britain, from the Pacifc North-West, where the climate is similar to the Atlantic North-West of Europe. It was soon noted how fast and straight these species, particularly Sitka spruce (*Picea sitchensis*) and, of course, Douglas fr (*Pseudotsuga menziesii*) (Savill 1991) grew. Consequently, they were soon widely planted, not only in the UK but on suitable sites throughout northwestern Europe. Sitka spruce now comprises more than a quarter of all forest trees in the UK (Forestry Statistics 2019).

In recent years, the recognition of the role of trees, woods, and forests in combating climate breakdown has led to an appreciation that introduced tree species may have a role to play in climate mitigation. Specifcally, if introduced trees grow faster than native species, they are considered to sequester carbon faster in the forest via net photosynthesis. This means that they have faster biomass accumulation to provide a carbon substitution beneft from the forest sooner (as wood fuel, or by replacing building materials, such as concrete and steel that have higher carbon footprints). Whether faster-growing trees or more frequent harvests of biomass provide better climate mitigation as timber density, not just volume needs to be quantifed, carbon transfer via roots into the mycorrhizae and soil needs to be measured and the effects of more frequent harvests on soil disturbance need to be included.

The concept of planting introduced tree species as a silvicultural treatment for improving forest stand adaptation to climate breakdown is novel. It has been recognized that long-lived, slow to reproduce, heavy seeded plants, including many native tree species, are unable to rapidly adapt to climate change by moving or adapting, so increased tree mortality and associated forest dieback is projected to occur in many regions over the twenty-frst century (Field et al. 2014). Consequently, although the native tree species in a given country may be adapted to survive the current pests, diseases, and abiotic threats they face, they may not be resistant and resilient to future threats. As tree species in certain locations may be adapted to climatic conditions that are similar to the ones predicted to be faced in others, it can be argued that to maintain a forest structure, for commercial timber production and other ecosystem services, but also as a habitat/ecosystem for biodiversity, the introduction of tree species likely to thrive in the future climate is justifed (Forestry Commission 2020).

The novel argument for the introduced tree species, as a silvicultural treatment to help forests adapt to climate breakdown and thus maintain the delivery of ecosystem services, including climate mitigation, is controversial. However, a CSF approach means putting climate adaptation and mitigation frst among multiple sustainable forest management objectives and all options need to be considered (Bowditch et al. 2020). Research into the effectiveness of this approach is needed and indicators need to be developed to guide if, how, and where this is viable. For example, in commercial plantation forestry with introduced tree species, it is not a great issue to introduce others. However, in the current plantations of native species, it may need more careful consideration. In our most pristine native woodlands, introduced tree species may be viewed as too damaging to their integrity.

## *8.4.10 Deadwood*

In forest ecosystems, deadwood infuences the nutrient and water cycling, humus formation, carbon storage, fre frequency, natural regeneration and represents a crucial component of forest ecosystems for maintaining and improving forest biodiversity. Decaying wood, such as logs, snags and stumps, as well as rot holes, dead limbs and roots, heart rot and hollowing in living ancient or veteran trees, all of them are habitats for the specifc species of fungi, fora, and fauna (Humphrey et al.

2004). Thus, the deadwood volume narrowly meant as the coarse woody debris (CWD), that is, logs and snags, has been selected as the main Pan-European SFM indicator regarding biodiversity, and it is also one of 15 main indicators of biodiversity as proposed by European Environmental Agency (Humphrey et al. 2004; Merganičová et al. 2012)., However, the ancient and veteran trees in all forests also are of key importance for rare and threatened saproxylic species, but, unfortunately, they arenot used for biodiversity monitoring (Humphrey et al. 2004).

Deadwood constitutes habitats for many species of cryptogams, such as bryophytes, lichens, and fungi (Humphrey et al. 2002; Lonsdale et al. 2008; Stokland and Larson 2011; Persiani et al. 2015; Preikša et al. 2015), invertebrates like saproxylic beetles (Martikainen et al. 2000; Franc 2007; Müller et al. 2008; Lassauce et al. 2011), as well as amphibians, birds, and mammals (Merganičová et al. 2012).

Wood-decaying fungi are essential for the functioning of forest ecosystems. They provide habitat for many other deadwood-dependent organisms and enable the regeneration of forests. There are plenty of examples of enhanced survival of seedlings of various forest tree species (mainly conifers) occurring on decaying deadwood (Lonsdale et al. 2008). To support the decaying fungi species of varying requirements, a wide range of CWD of different sizes and stages of decay is necessary (Lonsdale et al. 2008).

All types of deadwood are a substrate for the development of rare cryptogam species. The intermediate decay stages are extremely important for fungi, while bryophytes or lichens do not show such a clear preference. The highest number of cryptogam species is found on the deadwood of Common ash, English oak, and Norway spruce, while deadwood of other tree species hosts less than half cryptogam species (Preikša et al. 2015).

Throughout Europe, saproxylic beetle species have been identifed as the most threatened community of invertebrates (Davies et al. 2008). Species richness in saproxylic beetles has a signifcant positive correlation with the main deadwood variables (Martikainen et al. 2000). It depends not only on deadwood amount, but also on other microhabitat factors, such as the richness of wood-inhabiting fungi, and, for the threatened saproxylic beetles – on the frequency of *Fomes fomentarius* (Müller et al. 2008).

Natural variation of deadwood niches – including decay stages, snag sizes, tree cavities, and wood-decaying fungi species – must be maintained to effciently preserve the whole saproxylic beetle fauna. To better assess the quantitative relationships between deadwood and biodiversity of saproxylic beetles, apart from the deadwood volume, deadwood type or decay stage should also be considered (Lassauce et al. 2011).

Pieces of evidence have shown that climate change will speed up tree growth and accumulation ending up in a higher stock of deadwood available *in situ* (Mazziotta et al. 2014). However, due to increased decomposition rates, the time the deadwood stock is available for deadwood-associated species will diminish and the carbon stored in deadwood will return to the carbon cycle faster (Büntgen et al. 2019). Disturbances from fre, insects, and pathogens, in particular, are likely to increase in a warming world (Seidl et al. 2017), which could markedly modify the distribution

of deadwood across the forested landscapes in time and space. Under such circumstances, it is going to become increasingly challengeable to manage deadwood in a sustainable way. Some authors recommend that the structure and dynamics of oldgrowth forests are used as a reference system for managed forests (Jandl et al. 2019). Based on modelling results, it was found that continuous cover forestry, based on emulating natural disturbances and leaving 10% of stands uncut with no deadwood extraction, will result in greater dendrobiotic birds habitat quality per unit of current volume increment under climate change (ARANGE 2020). However, it is not clear whether the carbon sink function will decrease or even stop when the forests get into a steady-state of carbon sequestration in biomass and soil organic matter and of carbon loss due to decomposition of deadwood debris and soil organic matter (Desai et al. 2005; Pukkala 2017). In all cases, forest owners should be fexible and prepared to diversify the silvicultural systems across forested landscapes. They will need to follow natural disturbances in a way that will guarantee the presence of enough deadwood to adequately address the various trade-offs between wood biomass production for carbon sequestration, on the one hand, and forest protective functions, on the other.

Forest management should mimic the natural stand dynamics, increasing the number of dead trees and the diversifcation of the vertical and horizontal tree layers, considering the good potential for restoring and increasing the diversity of saproxylic communities and their associated ecological functions. For monitoring the ecological sustainability of forest management, we must focus on threatened species (Müller et al. 2008).

For strategies to increase deadwood amount in managed forests, the best results will be achieved in areas close to existing reserves or other important habitats (Müller et al. 2008). Research into deadwood dynamics carried out in unmanaged forest ecosystems (Christensen et al. 2005; Persiani et al. 2015) has proved useful as a reference tool to implement rehabilitation criteria in sustainable management, to maintain and increase biodiversity and other ecosystem services provided by managed forests.

Sanitary cuttings, carried out mainly to avoid outbreaks of insect pest populations or to reduce risk of forest fres, are another measures leading to severe restriction of the capacity of managed forest ecosystems to provide habitats for saproxylic species (Humphrey et al. 2004). Since healthy, resistant, and resilient managed forest should, partly, consist of diseased or injured trees (Szwagrzyk 2020), their retention until natural death would allow accumulation of deadwood of various types and sizes, and representing all tree species that grow in a forest, that would create niches for all deadwood depending species.

To improve the status of the deadwood-depending organisms, the managed forests should maintain a long-term continuous provision of greater amounts of dead and decaying wood microhabitats that deadwood-depending organisms require for their survival (Christensen et al. 2005; Davies et al. 2008; Lonsdale et al. 2008). However, no simple deadwood stocking recommendations can be applied, due to the inherent complexity of all the stand, site, and management factors that drive deadwood dynamics (Persiani et al. 2015).

## *8.4.11 Genetic Resources*

Since the advent of the population genetic studies based on molecular markers, it has been postulated that long-term survival and adaptation of species and populations to the changing environment strongly depends on the high genetic variation accumulated in the gene stock of populations over historical times (van Dam 2002). Natural forest tree populations tend to maintain a high level of genetic diversity along with the distribution range because of the high outcrossing rate, the long life span of individuals that besides preserving their highly heterogeneous genomes can fx benefcial alleles for a longer period (Petit and Hampe 2006). Several acting forces on population-level, however, can shape the uniform distribution of the genetic variation especially at the range periphery of the species where gene fow usually decreases or the environment reaches the tolerance limit of populations. Genetic drift and inbreeding acting at the range margins can cause differentiation by changing the frequency distribution of alleles and selecting population-specifc alleles (Hampe and Petit 2005). These selected alleles might be benefcial in the local adaptation on the range margins, but can be also harmful forcing populations to counteract against their fxation (balancing selection). Differences between central versus peripheral populations and the role of the benefcial alleles helping population adaptation have been much discussed in different studies (Gibson et al. 2009; Logana et al. 2019).

Natural or human-induced fragmentation in species' distribution area can increase the effect of marginality and can cause isolation within the species' range, not only at the range periphery. Fragmentation increases genetic divergence and will promote the overall structuring of populations. If gene fow becomes limited among the fragmented sites, the long-lasting drift and inbreeding end up in pauperization of the gene stock causing a higher rate of homozygous individuals. Homozygote excess usually produces limited resilience and lower ftness, impeding population adaptation to the changing environment (Mátyás 2002; Allendorf et al. 2013). All these processes are strongly affecting populations in the time of the ongoing climate change that has an unpredictable impact on the structure of the ecosystems and populations therein.

Forest trees having a large genome and preserving a considerable amount of genetic variation are expected to have high resilience. Moreover, the high phenotypic plasticity allows them to withstand even large environmental fuctuations during their lifetime. However, researchers have expressed their concerns also. Tree species with long generation time due to the long-life span of individuals might be unable to react to the fast changes experienced due to the ongoing climate change. These events are too rapid relative to the tree's age and populations may not have adequate time to adapt or to disperse and colonize the newly available habitats. As many species are unlikely to migrate fast enough to track the rapidly changing climate in the future, their standing adaptive variation will likely play an increasingly important role in their response (Jump and Peñuelas 2005; Mátyás and Kramer 2016).

Studies have shown that the effect of climate change acts strongly at the species' ecological limits, as tolerance to climatic extremes is genetically determined. For example, European beech populations at the lower xeric limit of the species' distribution are more exposed to the impacts of climate change; hence, the decline of population in these territories has been anticipated (Mátyás and Kramer 2016). In turn, more recent studies have shown that beech, currently dominating lower elevations in mountain sites, has a high potential to advance to higher altitudes, where it can perform better in mixed stands than in monospecifc stands (Pretzsch et al. 2020c).

Since the frst utilization of forests ecosystems, humans intentionally or unconsciously have altered the gene pool of forest tree species (Buiteveld et al. 2007). The decrease in forest area size, habitat degradation, change in species composition, forest plantations, or tree breeding, all these, have infuenced natural gene stock of forest communities. Most European forests are also affected by historical forest management and despite the intention of the last decades, to preserve sustainable silviculture, the long history in forestry has left strong imprints in the genetic makeup of forest tree species.

Genetic studies in forest tree populations using a large stock of genetic markers make it possible to reveal all these historical processes, to evaluate the composition and quality of the forest gene stock, and foresight future ability of communities to adapt to changing environmental conditions.

To mitigate the effects of the changing climate in forest ecosystems and to conduct CSF primarily, it is important to have deep insights into the genetic constitution of species and their populations. High levels of "standing genetic diversity" in populations is a prerequisite for species to face fast environmental changes as selection and fxation of new adaptive mutations take a comparatively longer time. In contrast to new adaptive mutations, standing variation most probably has already passed through a "selective flter" and might have been formerly tested by selection in past environments (Barrett and Schluter 2008). Selection of the new alleles in tree species with their long-life span needs comparatively more time; thus, lack of adaptation may end in the decline of the functional traits.

Former case studies on the phenotypic variation of forest trees, experiments in provenance trials beginning from the early 1970s, and many common garden experiments provided a large source of data helping in understanding the adaptive behavior of species. Although these were not designed to monitor the effects of climate change, they still provide insights into the aspects of the genetic variation and of the adaptive response to species to the acting environmental forces. A more recent study by use of feld trials and modelling tools tried to determine the extent to which four widespread forest tree species in Europe (Norway spruce, Scots pine, European beech and sessile oak) may be affected by the climatic change (Mátyás and Kramer 2016).

To explore the impacts of environmental change on the adaptive potential of trees, functional phenotypic traits need to be assigned to allele composition. This is not always unequivocal as for many traits, there is still limited knowledge, likely

because they are regulated by multilocus systems. Thus, a genome-wide scanning of the changes in population genetic diversity based on neutral markers represents another but a more conservative approach (Kramer et al. 2010). However, an increasing number of projects mapping complete genomes of mountain forest tree species (Mosca et al. 2019) and the development of gene-specifc primers makes it already possible to identify nucleotide diversity in genes and candidates responsible for the adaptive variation.

To grant forest tree populations the ability to keep an adequate level of genetic diversity, to maintain viability, and to support long-term evolutionary potential, genetic aspects should be embedded in the forest management (Buiteveld et al. 2007). Forest ecosystems will only persist if genetic variation and allele composition of trees are maintained at a high level and this especially holds in view of the environmental changes. Therefore, studies on the genetic makeup of species and populations should be performed before starting the planning of any forest management activity. Moreover, selection and conservation of multiple genetic resources should be also in the focus.

A case study on the genetic variation of pure beech stands along species' distribution range was initiated within CLIMO (COST Action, CA15226). The novelty of this work is the coupling of the genetic data with other empirical measurements within the considered study plots. Dominant trees from 12 study plots were subjected to molecular evaluation based on six nuclear microsatellite markers. The overall high genetic variation of the stands was correlated to local climate variables. Among the genetic indices, the number of alleles and Shannon genetic diversity were shown to be highly correlated with daily temperature and the frequency of frost days (Höhn et al. 2021).

## *8.4.12 Threatened Forest Species*

Because of the extensive studies that had been carried out for years, species diversity turned out to be the easiest aspect to implement among the main biodiversity components (Kraus and Krumm 2013). Species diversity remains a keystone, and the loss of species is the most recognizable form of biodiversity decline.

European Red List of Trees identifes those species that are threatened with extinction at the European level to inform about actions needed to improve their conservation status (Rivers et al. 2019). The list summarizes the results for the assessment of all known native European trees, a total of 454 species, of which 265 (over 58%) are endemic to continental Europe. In common with vascular plants (Bilz et al. 2011), some of the highest levels of endemism are found in the main mountain chains, such as the Alps, Pyrenees, Carpathians, Apennines, Dinaric Mts., and others. The mountain areas also represent the richest centers in Europe (Rivers et al. 2019).

Overall, 191 (42%) European tree species have been assessed as having a high risk of extinction, that is, assessed as critically endangered, endangered, or vulnerable. A further 13 tree species are assessed as almost meeting the criteria for a threatened category, while 216 of them are considered of not being of conservation concern (Rivers et al. 2019).

Each country may produce its national red lists (most often containing more species than in the European red list), which assess the risk of species' extinction within the country borders. The species considered of not being under threat in the European scale locally can be seen as critically endangered or vulnerable. Thus, several countries have developed management or action plans for various species and have legislation in place to protect certain species legally. Some examples of successful initiatives include the Regional Programme of Conservation and Restitution of *Sorbus torminalis* in Poland (Zwierzyński and Bednorz 2012), and the *Zelkova* global action plan (Kozlowski and Gratzfeld 2013).

Forest management can negatively affect several taxa by reducing the number of natural attributes, such as microhabitats bearing trees, deadwood quantity, and its diversity (Lafond et al. 2015). However, the opposite happens: for example, in European beech forests, no loss in vascular plant species restricted to forests occurred over the past 250 years despite forest management (Schulze et al. 2016). On the other hand, some feld studies highlight a positive effect of forest management on the diversity of such taxa, as bird species related to open spaces and species of the understory vegetation (Lafond et al. 2015).

In uneven-aged forests, large tree retention has a positive effect on several structure and biodiversity indicators. In particular, it seems effcient to compensate for the negative impacts of increased harvesting intensity by limiting the decrease in tree sizes diversity. Through the analysis of compensating effects, it has been revealed the existence of possible ecological intensifcation pathways, that is, the possibility to increase management intensity while maintaining biodiversity through the promotion of nature-based management principles, that is, gap creation and retention measures (Lafond et al. 2015).

Nowadays, climate change represents an important driver of species extinction, the importance of which is increasing, when acting in synergy with habitat destruction and fragmentation. Climate change will cause many tree species to lose a part of their current habitat but will also enable them to colonize new habitats (e.g., del Río et al. 2018). As natural migration is often slow, forest managers are examining the option of assisted migration (Martín-Alcón et al. 2016; Gömöry et al. 2020). A main premise of SFM is that silviculture based on patterns and processes found in old-growth forests will maintain the provision of important habitats for biodiversity (Schütz et al. 2016). Although in some parts of Europe is implemented "close-tonature management" (Schütz 1999; Brang et al. 2014; O'Hara 2016), the resulting forests lack the diversity in composition and structure of forest ecosystems that are driven by natural succession and dynamics so characteristic to old-growth forests (Kraus and Krumm 2013).

## *8.4.13 Protective Forests (Soil, Water, and Other Ecosystem Functions)*

Protective forests as one of SFM indicators are presented here in the broader context, that is, including all FRA 2020 categories as described in Global Forest Resources Assessment (FAO 2020) for European countries, except Russian Federation and Turkey. Thus, apart from protective forests primarily designated for protection of soil and water, Table 8.2 contains data on areas primarily designated for other forest ecosystem functions, such as conservation of biodiversity, social services, and of multiple use. Such an approach enables a general understanding of the role of forest in maintaining also other forest functions.

Any undisturbed forest has a capacity to effectively sustain the maintenance of biological diversity and protection of soil and water, since these capacities/functions are integrated with natural processes ongoing in forest ecosystems. Forest functions as such, refect a forest ecosystem capacity of sustaining expected people's demands, while forest ecosystem services account for the provision of requested benefts (Lesiński 2012). These benefts are of the basic value for peoples' welfare.

Forests primarily designated for various management objectives (FAO 2020), with exception of production, occur in as many as 30 out of 36 countries and they all together cover 42.55% of the total forest area in Europe (Table 8.2). The representativeness of the above FRA 2020 categories in individual countries and their average share in the total forest area in Europe are as follows:

In 12 countries' data in the matter, production has not been at all mentioned as one of primarily designated forest management objectives, and in six of them, forests have not been designated for any other objective, either. The latter have been described either as other, none, or unknown (Table 8.2).

When it comes to distinguishing forest functions, two main approaches might be considered – the zoning approach and the integration approach (Bončina 2011b). The zoning approach takes place mainly in scarcely populated countries/ regions, large forest areas, or mountain ranges (Lesiński 2012). Protective forests are typical examples of such an approach. In Europe, they cover large areas in the mountains of Switzerland, Austria, Romania, Moldova, and Norway (Table 8.2). The integrated approach suits much better in densely populated countries/regions (Lesiński 2012). Integration approach results in multifunctionality that is achieved by combining various objectives at a larger scale. France, Belgium, Netherlands, and Spain are very good examples of implementing such an approach (Table 8.2).

8 Climate-Smart Silviculture in Mountain Regions

Order of countries by Multiple use (descending) and by Other/None/Unknown (ascending)Source: Reports for individual European countries; FAO (2020)

290

**Table 8.2**

Protective forests are forests that have as their primary function to prevent soil erosion, to preserve water resources and protect infrastructure, people and/or their assets against the impact of natural hazards. The main tool used by these forests are standing trees, which act as obstacles to downslope mass movements such as rock falls, snow avalanches, erosion, landslides, debris fows, and foods. The protective effect of these forests is ensured only if the silvicultural system used and any natural disturbances that occur leave a suffcient amount of forest cover (Brang et al. 2006). Thus, the continuous cover approach maintaining unevenaged tree-stands seems to be the best solution (Mason et al. 1999; Pukkala and Gadov 2012).

## *8.4.14 Slenderness Coeffcient*

The slenderness coeffcient (H/D ratio) is commonly used in studies of the resilience of trees and forest stands to the destructive activity of wind and snow (Abetz 1976; Burschel and Huss 1997). This is a synthetic indicator describing the shape of the tree trunk (the stem taper, the opposite of slenderness). The slenderness coeffcient is calculated by dividing the height (H) by the diameter at breast height (D). The higher the diameter at breast height of a tree with the same height (lower H/D values), the stronger the force necessary to bend the trunk. A low slenderness coeffcient is found for a longer crown, lower center of mass, and better-developed root system due to the large space for growth. Free growth of the crown facilitates the increase of growth of the diameter at breast height and the increase of the stem taper (Petty and Worrell 1981). Expansion of the space for the growth of the crown also limits their asymmetric development (Petty and Swain 1985; Valinger et al. 1994), with trees with regular crowns less susceptible to leaning or swinging (e.g., due to an asymmetric snow load). A torsional moment is also observed less frequently. The tree roots in a loose stand tend to be better anchored in the soil, leading to increased resilience to tree damages (Nielsen 1995). Peltola et al. (1997) explain that with a low slenderness coeffcient, snow is dislodged from the tree crowns by gusts of wind, and these two damaging factors do not accumulate.

In some of the publications, the authors use the slenderness coeffcient as a measure of tree/stand stability. They formulate conclusions and assessments concerning the rules of tending stands, assuming that lower H/D values will result in higher resistance to the wind (snow) (Wang et al. 1998; Wilson and Oliver 2000; Castedo-Dorado et al. 2009; Vacchiano et al. 2013; Meng et al. 2017). A different methodological approach is the creation of models allowing the prediction of the fact or probability of wind damage emergence. In these models, the slenderness coeffcient is one of the many variables. An analysis of effciency, measures of ft, prediction, and classifcation capacity of these models indicates that the slenderness coeffcient, as a single variable, is frequently of relatively limited value as an explanatory variable. The studies by Pukkala et al. (2016) show the slenderness coeffcient as useful, but only in interaction with specifc basal area and diameter at breast height values. In the work by Martín-Alcón et al. (2010), the slenderness coeffcient infuenced the prediction of the percentage of damaged trees in a stand, but only when divided by the basal area. Slenderness alone is not a good indicator of tree stand stability, one also requires a factor indicating mutual tree support within a forest stand (Schütz et al. 2006; Schelhaas et al. 2007; Martín-Alcón et al. 2010). The work by Albrecht et al. (2012) concludes that a variable tree height should be used in conjunction with H/D. The usability of the slenderness coeffcient as a predictive measure was also critically assessed in studies covering historic data. Oliveira (1987) and Schütz et al. (2006) also do not recommend the usage of the H/D ratio as a single variable to predict resistance to wind damage. In the work of Díaz-Yáñez et al. (2017), the best prediction models use the slenderness coeffcient to clarify the probability of damage at less than 10%. Tree height covered the majority of the probability of damage emergence.

Due to the common usage of the slenderness coeffcient as the measure (indicator) of resistance against wind damage, many authors indicate its desired/critical values. In Germany, Abetz (1987) recommended a slenderness factor of ca. 80 as suitable for Norway spruce. Burschel and Huss (1997) suggest the following value scale for coniferous species: very unstable (H/D > 100), unstable (H/D 80–100), stable (H/D < 80), alone trees (H/D < 45). The values given by other authors are similar (Johann 1981; Cremer et al. 1982; Rottmann 1986; Becquey and Riou-Nivert 1987; Lohmander and Helles 1987; Peltola et al. 1997; Wilson and Oliver 2000). Summarizing their research, Wilson and Oliver (2000) conclude that there is no single H/D value guaranteeing stability. It depends on the wind strength. We are not able to eliminate the hazard of wind, and a lower H/D value leads to a reduction in value or production costs (pruning). Skrzyszewski (1993) concluded that promotion of trees (European spruce) with a low slenderness coeffcient (below 80) during thinning leads to the emergence of tree stands with trees that have branches extending low over the ground, with a large share of ingrown knots and showing a very tapered stem and broad rings, resulting in low mechanical strength and reduced wood durability in coniferous species. Safe strategies are sparser planting spacing and/or high-intensity cuttings at a young age (sapling and pole stage), and in neglected forest stands – very low-intensity cuttings during many entries. An alternative may be growing all-age (selection) stands (Dobbertin 2002; Griess and Knoke 2011; Jaworski 2013; Hanewinkel et al. 2014; Pukkala et al. 2016).

The slenderness coeffcient is the result (effect, derivative) of a specifc vertical structure of a stand, its age (height), and density as well as the silvicultural treatments executed in the past. The quoted publications indicate that the slenderness coeffcient should be analyzed in association with other variables (site conditions, soil humidity, exposure, slope, altitude and age as well as the height of neighboring tree stands).

## **8.5 Silvicultural Treatments Improving Stand Mitigation**

## *8.5.1 Growing Stock*

Keeping the average growing stock low is mentioned as one of the principles for climate change adaptation in forest management (Brang et al. 2014). This might be especially true in the case when forest fres cause stand damages, which is typical for Mediterranean forests. However, the high growing stock of forest stands can increase damage susceptibility also in mountain areas, especially in the case of wind throws or insect attacks, and much less for ice or snow breaks (Jalkanen and Mattila 2000; Klopčič et al. 2009).

At present, the average growing stock in European forests is 163 m3 /ha, ranging from 10 m3 /ha in Iceland to 352 m3 /ha in Switzerland (Forest Europe 2015). During the last decades, the rate of annual felling to wood volume increment has been relatively stable and remained under 80% for most countries in Europe.  However, the ratio of harvesting to increment is assumed to increase in the nearest future since the demand for woody biomass as a renewable energy source is expected to increase (Forest Europe 2015). On the other hand, the higher growing stock as well the age of forest stands may increase the occurrence and the severity of insect outbreaks in forests prone to the pest damages (Pasztor et al. 2015). The crucial issue is to keep the average value of growing stock on a certain level allowing to control trade-offs between climate change mitigation actions focused on growing stock increase (increase carbon stores) and adaptation potentials focused on wood harvesting enabling to create multilayer and uneven-aged stands (D'Amato et al. 2011). For example, Pretzsch et al. (2014) and Schütz (2003) suggest to strive to achieve the average growing stock amounted to 300–400 m3 /ha on fertile site conditions and 250–350 m3 /ha in medium site conditions in mountain mixedspecies forests.

## *8.5.2 Carbon Stock (Soil)*

Soils are the largest carbon pools of most of the mountain forest ecosystems and are more stable and less exposed to sudden fuctuations than trees (Scharlemann et al. 2014; Achat et al. 2015). Nevertheless, forest management can affect soil organic carbon (SOC) stock and accumulation rate (Mayer et al. 2020; Tonon et al. 2011). The extent to which different silvicultural systems, harvest intensities (percentage of original biomass), frequency, modality (tree stem or whole tree collection), and the degree of mechanization might impact SOC is still debated due to the huge number of external factors (climate, species composition, litter quality, type of soil, and relative clay content) involved in the ecosystem response (Hoover 2011). In this context, although conficting results can be found in literature, often linked to the different timescale of the experiments, some general indications can be provided to maximize the SOC stock of mountain forests. First, all forest management strategies with a positive effect on the ecosystem's net primary productivity have to be considered as putative strategies to increase SOC accumulation through the increased production of leaf, root, and woody litter. An example is a conversion of pure to mixed forest in central Europe (Aguirre et al. 2019; Pretzsch et al. 2020b; Torresan et al. 2020) with evident positive effects in terms of productivity and resilience to climate changes. Recent evidence shows that intensive forest harvest, based on the collection of tree stems and logging residues, has a deleterious effect on SOC content resulting in a consistent and lasting loss of carbon that affects both the surface and mineral soil layers, suggesting that residues management is one of crucial aspect to take into account in the context of the CSF (Achat et al. 2015). On the other hand, it has been shown that traditional forest harvest has a temporary effect limited to the forest foor without any serious impact on the mineral deeper soil layers (Achat et al. 2015; Mayer et al. 2020).

The transition from the traditional age class forestry to the continuous cover forestry toward the conversion of even-aged to irregular or uneven-aged forests is a further indication that emerged from the literature as a potential option with a positive long-term effect on soil and forest carbon storage (Seidl et al. 2008). This structural change can be reached through the application of selective harvesting, such as single-tree selection or small-group selection cutting. However, this transition is not possible everywhere as it requires local technical skills, suitable climate conditions to support natural regeneration under the typical uneven-aged forest microclimate, and a fexible timber market. In agreement with the ECCP-Working Group on Forest Sink (2003), 30 million hectares of forests at the European level could be converted to continuous cover forestry with an important carbon gain at the regional level. Where social, technical, or ecological reasons make the conversion to the continuous cover forestry inapplicable, the elongation of the rotation period of even-aged forest can be considered as a possible strategy to promote carbon sequestration. Indeed, the time that the system needs to recover to the pre-disturbance SOC content can largely vary according to climate, soil conditions, and magnitude of the perturbation. Therefore, the rotation period in even-aged forestry should be at least longer than the recovery time. An additional point supporting the elongation of the rotation period is the evidence that forest ecosystems are far to be carbon-saturated, since several old-growth forests are still accumulating carbon in the different compartment, soil included, at different altitudinal and latitudinal belts with an important accumulation rate (Gunn et al. 2014; Schrumpf et al. 2014; Vedrova et al. 2018; Badalamenti et al. 2019; Keeton 2019).

## *8.5.3 Roundwood (Timber Products)*

One of the main effective measures to mitigate climate change is to retrieve carbon from the atmosphere and store it as long as possible in roundwood as a timber product resulting from the stand management expected by society (Kauppi et al. 2018). The roundwood timber can be used for many purposes in building construction and human everyday life. The best climate change mitigation effect is achieved when the wood is converted into long-lived products and where the same wood unit is used in several, successive product cycles (Jandl et al. 2018). Wood production belongs to the component of the CSF concept concerning mitigation related to sustainably increasing forest productivity and income and relies on using wood resources sustainably to substitute nonrenewable, carbon-intensive materials (Nabuurs et al. 2017; Verkerk et al. 2020). To produce the best quality and suffcient amount of different assortments of roundwood timber, many different optimal silvicultural measures depending on the species composition, site conditions, and societal expectations can be implemented. The most important silvicultural treatments are thinnings, both precommercial and commercial, which systematically applied in the stand can lead to the rotation age with high-quality crop trees. Some economic analyses have shown that properly made precommercial thinning often is the most rewarding long-term investment that can be made during the silvicultural prescription throughout a stand's life (Smith et al. 1997). The various methods of commercial thinning focused on the production of best timber products at the end of rotation are undertaken in Europe. The common thinning rule is the selective promotion of the best trees (taking into account vitality, social position, quality, stability) in the stand using the procedure based on Assmann concept (1961) of maintaining stand basal area allowing to maintain the growth at the level of at least 95% of the maximum periodic annual volume increment. Other models of thinnings are mostly adapted to the main tree species in the stand and their selection is also determined by the fnal production objective (target timber assortments) of stand management. Here we are presenting some examples of particular methods applied in stands consisting of main tree species: *Pinus sylvestris* stands – thinning leading to construction timber and/or valuable wood (Burschel and Huss 1997); *Picea abies* stands – the selection of thinning procedure based on the stand age, method of stand formation, origin, and stability (Burschel and Huss 1997); Abetz's model (1975) of thinning with a selection of a certain number of future best trees; *Abies alba* stands – selection of the best crop trees and selective thinning (Korpel 1975), differentiation thinning leading to the forest with selection structure (Schütz 1989; Korpel and Saniga 1993); *Quercus* stands – three methods to produce veneer, valuable, and sawn timber (Burschel and Huss 1997); *Fagus sylvatica* stands – selective thinning (Burschel and Huss 1997), qualitative group thinning (Kato and Mülder 1983; Röhring et al. 2006), thinning procedures by Freist and Altherr (Burschel and Huss 1997). However, most of them were developed in the period when climate change was not an important issue, so they need to be modifed according to the current state of knowledge and predicted climate change effect on timber production.

## **8.6 Application of Simulation Models for Development, Testing, and Improving Silvicultural Prescriptions**

## *8.6.1 The Role of Models in Forest Science and Practice*

Under changing environmental conditions, models become particularly important as they may provide information about the effcacy regarding the mitigation and adaptation potential of new silvicultural measures, which are so far not at all or not suffciently covered by experiments.

For instance, experiments addressing the effects of thinning in mixed stands or the transition from even-aged monocultures to uneven-aged mixed stands are still rare; so, the potential of mixing and transitioning on the resistance, resilience, or recovery under drought stress may be explored by model scenarios.

The main role of models is the integration of existing knowledge for better understanding and regulation of well-analyzed ecosystems under stable conditions; however, in the view of unknown future development, their contribution to exploring future management strategies by scenario analyses gains an increasing importance. Ecophysiologically based models derive the system behavior from mechanistic relationships but often lack an interface to silvicultural management. Management models statistically refect the tree stand growth observed on experimental and inventory plots, cover the practical relevant dendrometric variables but are less fexible regarding changing growing conditions. By deriving relationships between growth and water supply with ecophysiological models, statistically modelling such relationships and integrating them into management models pros and cons of both model approaches may be combined as shown by Schwaiger et al. (2018a, b).

Silvicultural prescriptions can serve as guidelines for tree and stand regulation. Their development starts with a participative target development (Pretzsch et al. 2008). Their quantitative development is based on expert knowledge, existing experimental plots, and inventory data and is also often based on scenario analyses with models. Models may reveal which treatment variants match the best with the ecosystem functions and services aimed at by the defned target state. In this case, models are used as virtual experiments for testing the long-term consequences of various treatment options. By comparing the model outcome with the target, the most promising and stable variants may be selected and formulated as easy-to-apply rules for use in forest practice.

## *8.6.2 Models as a Substitute for Missing Experiments*

Strong stand density reductions, thinning in mixtures, transitioning from even-aged monocultures to uneven-aged mixed stands, gap cuts, or inner edges may be caused by silvicultural measures of mitigation or adaptation to drought and climate change. The effects of such measures on the long-term are unclear, as respective long-term experiments are hardly available (Pretzsch et al. 2020a).

However, spatially explicit individual tree models, parameterized based on longterm experiments with distant-dependent prognosis algorithms, are suitable for assessing the reactions of such silvicultural measures. Especially models that are based on basic rules such as allometric principles, self-thinning lines, density competition relationships, or dose–response functions for quantifcation of the relationships between growth and environmental conditions may be helpful. They interpolate or extrapolate beyond the range of stand and structure conditions covered by the parameterization data sets.

Starting with defned stands and environmental conditions, various treatment options may be tested by simulation runs. Link functions to various ecosystem services enable the assessment of the long-term consequences of various treatment options and their match with the target settings by management. The treatment options that meet the best the various criteria of the defned target are an appropriate basis for further development of practical guidelines.

Certainly, additional aspects, for example, of forest utilization, wood quality, and ecological and socioeconomic impact, need to be considered; however, the effects of the silvicultural measures on the natural production represent an essential pillar and step in the process of guideline development.

## *8.6.3 Models as Decision Support in the Case of an Unclear Future Development*

In the last few decades, forest science and forestry were faced with the environmental impact on forest ecosystems such as acid rain, increasing atmospheric ozone concentration, and eutrophic deposition as well as climate change. There is hardly any previous experience from experiments or monitoring on how forestry may mitigate or adapt to such environmental changes. Chamber experiments are restricted to small trees and feld experiments are costly and very long-lasting; they are important but not suffcient to quickly provide forest management with recommendations for decision making under environmental stress.

Model predictions and model scenarios are often the only alternatives for getting decision support, but their results should be interpreted and applied with due care for the following reasons: Mechanistic models that are based on general relationships between environmental conditions and ecophysiological processes. As they are hardly parameterized for the special stress conditions, they may provide false estimations of the stress reactions, acclimation, and adaptation reactions of forest ecosystems (Bréda et al. 2006). Statistical models that apply the "space for time" approach and derive the temporal reactions on different environmental conditions from the plant's reactions along spatial gradients may underestimate the time trees need to adapt to or recover from exposition to stress events. Individual tree models that estimate the tree's growth response on tree size and competition within the stands may be parametrized for even-aged stands where most trees have a similar history. If their functions are used to predict tree growth in mixtures, in heterogeneous stands or regeneration phases with gaps and edge trees, there may be false estimations as the trees are no longer growing similarly but have much more diverse courses of growth than in monospecifc and even-aged stands. Thus, their growth courses can hardly be predicted just from their present size and competition. More information about past development, for example, about the inner and outer traits, may be necessary for appropriate predictions. Improved models are on the way (Sievänen et al. 2000; Pretzsch et al. 2002; Rötzer et al. 2012) and may be used for silvicultural scenario development for mitigation and adaptation measures (Hilmers et al. 2020).

## *8.6.4 Model Scenarios to Fathom Out the Potential of Adapting Forest Stands to Climate Change by Silvicultural Measures*

Model scenario calculations may help to better adapt forest ecosystems to environmental changes and stress. We see mainly fve lines of models' applications for the development of climate-smart silvicultural measures.

tem services. Of special interest are the effects of a transition to continuous cover forestry regarding the reduction of damages and growth losses by wind and storm, bark beetle, and drought stress.

(v) Reduction of the rotation length or introduction of midrotation mixture may reduce risks and increase productivity due to adaptation to the species-specifc growth rhythms and damage susceptibilities and temporary tree species mixing.

In all cases, model scenarios may serve as a substitute or completion of information derived from experiments or observations.

## *8.6.5 Example of the Application of Models for the Development of Silvicultural Guidelines*

Since early medieval times, mixed mountain forests of Norway spruce, silver fr, and European beech have been replaced by Norway spruce monocultures for wood supply of the salt works in Southern Germany (Hilmers et al. 2020). The resulting nonnatural and unstable secondary Norway spruce monocultures suffered various damages by snow and wind in the last decades. In addition, they are strongly affected by drought stress events and continuous climate warming (Pretzsch et al. 2020b).

To increase the stability of these historically destabilized and presently endangered forests, alternative management concepts are being intensively discussed and introduced. A promising option to restore the stability of these ecosystems is their transformation from pure Norway spruce stands into site-appropriate, sustainable, and stable mixed mountain forests of mainly Norway spruce, silver fr, European beech, and sycamore maple.

However, there are hardly any practical examples for such silvicultural transformations. As way out we used the stand growth simulator SILVA to develop and assess the results of various transformation scenarios. We also analyzed any tradeoffs between the pros and cons of various scenarios and the resulting success criteria (Hilmers et al. 2020). Here we show the results of the test of seven different transformation scenarios (e.g., slit-coupes, shelterwood and gap-coupes, strip clearcutting, do-nothing). We report their impact on the fve evaluation criteria forest stand growth, economical results, carbon store, stand stability, and biodiversity.

Some of the results are visualized in Fig. 8.4. In essence, we found out that the scenarios applying gap or slit-coupes resulted in the most benefcial overall utility values regarding the fve evaluation criteria. We could also show the best way to transform destabilized forests to sustainable and stable ecosystems. In this way, guidelines for restauration and transformation can be developed, compared, and ranked regarding their achievement, even if respective model stands are scarce or missing. A precondition is the availability of simulation tools that are based on basic principles of tree and stand dynamics and thus can realistically simulate also treatment options and development scenarios that were not used for the model parameterization (Pretzsch et al. 2008).

**Fig. 8.4** The development of silvicultural guidelines by model scenario calculations comprises the (**a** and **b**) initial state and aim of the modelling exercise, (**c**) defnition of the standing stock for the model scenarios (above) and the resulting growth (below), (**d**) the multicriteria overview of the long-term consequences of various options regarding ecological, economical, and socioeconomic criteria, (**e**) simplifed silvicultural guidelines for practical application. (After Hilmers et al. 2020) **a and b visualizes the objective, that is, the transition from even-aged monospecifc Norway spruce stands to uneven-aged mixed-species stands of mainly Norway spruce, silver fr, and European beech**

## *8.6.6 From Models for Regulation and Optimization to Guidelines for Silvicultural Steering*

We showed that model-based scenario analysis may contribute to deriving an appropriate silvicultural option. For this purpose, various treatment variants may be implemented algorithmically in a growth model, for example, various tree numbermean tree height guidelines (N-h-curves) for steering the stand development over time. For each of *i* = 1 … *n* treatment options, the stand development can be simulated, and the result may be compared with the target state. The very treatment options that show the best approximation of the stand to the defned target may be of special interest as a suitable guideline for practical application. The derivation is often based on a combination of a normative, experimental, and simulation approach and also includes ecological and socioeconomic criteria.

The involvement of a scenario analysis requires a quantitative formulation of a set of treatment options and fnally provides a quantitatively based treatment option that might be used for target-oriented silvicultural steering in practice.

This model-based derivation of a silvicultural treatment guideline represents a regulation process (Fig. 8.5). By defnition (Berg and Kuhlmann 1993), regulation means that a development is controlled by the initial conditions, the time exogen variables and that the rules can be modifed by a feedback between the current development and the applied rules (closed-loop-control).

The application of this once derived curve for stand treatment represents steering. Steering means that system development is controlled just by the initial conditions, the time exogen variables, and static rules (open-loop control). In this case, once derived and prescribed rules (e.g., guideline curve or threshold), provide the setpoint for stand characteristic (e.g., density, mixing proportion, number of future crop trees) to which the stand is adjusted by silvicultural interventions in defned intervals. In the case of steering, there is no feedback between the stand development and the once fxed guideline. The application of a given silvicultural treatment in forest practice, that is, the thinning of a stand based on a defned N-h curve, represents steering.

#### **Fig. 8.4** (continued)

**c shows the stand volume of the remaining stand in m3 ha−<sup>1</sup> (above) and the mean stand periodic annual volume increment in m3 ha−<sup>1</sup> year−<sup>1</sup> (below) resulting from 30 simulations of the following variants: DN, do-nothing scenario; G, Gap-coupes with the planting of beech and fr; SH1, shelterwood-coupes with natural regeneration; SH2, shelterwood-coupes with the planting of fr and beech; SL1, slit-coupes with natural regeneration; SL2, slit-coupes with the planting of fr and beech; SC, strip clear-cutting with natural regeneration**

**d shows radar charts of the evaluation of multiple criteria. FG, forest growth; NPV, net present value; C, carbon sequestration; S, stability; NS, number of species. The scaled results of the respective factors of each criterion are shown. Results were scaled between 0 and 1. Results evaluated with 1 represent the best scenario in comparison to the other scenarios. Categories rated 0 show the worst scenario. DN, do-nothing scenario; G, Gap-coupes with the planting of beech and fr; SH1, shelterwood-coupes with natural regeneration; SH2, shelterwood-coupes with the planting of fr and beech; SL1, slit-coupes with natural regeneration; SL2, slit-coupes with the planting of fr and beech; SC, strip clear-cutting with natural regeneration**

**e represents the main aspect of the derived silvicultural guideline, the target standing stock for stands growing under different site conditions**

**Fig. 8.5** Regulation (**a**) vs. steering (**b**) of systems after Berg and Kuhlmann (1993). (**a**) The effects of silvicultural treatments on stand development may be simulated by a model. The stand development can be compared with the management objective, and the repeated modifcation of the treatment and simulation generates a set of scenarios with some of them appropriate for reaching a defned management objective. The feedback between the simulated stand development and the treatment option makes this process a regulation. (**b**) A derived silvicultural treatment may be applied as a silviculture guideline for stand management. As there is no feedback between stand development and guideline characteristics, this process is called steering

## **References**

(eds) Mountains of Northern Europe: conservation, management, people and nature. TSO Scotland, Edinburgh

Jaworski A (2013) Hodowla lasu. Pielęgnowanie lasu. PWRiL, Warszawa, p 359

Zeller L, Pretzsch H (2019) Effect of forest structure on stand productivity in Central European forests depends on developmental stage and tree species diversity. For Ecol Manag 34:193–204 Zwierzyński J, Bednorz L (2012) Regional Programme of Conservation and Restitution of Sorbus torminalis in the Territory of the Regional Directorate of the State Forests in Piła in 2010-2013. Nauka Przyroda Technologie, 6,3,#42

**Open Access** This chapter is licensed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

The images or other third party material in this chapter are included in the chapter's Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the chapter's Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder.

# **Chapter 9 Smart Harvest Operations and Timber Processing for Improved Forest Management**

#### **G. Picchi, J. Sandak, S. Grigolato, P. Panzacchi, and R. Tognetti**

**Abstract** Climate-smart forestry can be regarded as the evolution of traditional silviculture. As such, it must rely on smart harvesting equipment and techniques for a reliable and effective application. The introduction of sensors and digital information technologies in forest inventories, operation planning, and work execution enables the achievement of the desired results and provides a range of additional opportunities and data. The latter may help to better understand the results of management options on forest health, timber quality, and many other applications. The introduction of intelligent forest machines may multiply the benefcial effect of digital data gathered for forest monitoring and management, resulting in forest harvesting operations being more sustainable in terms of costs and environment. The interaction can be pushed even further by including the timber processing industry, which assesses physical and chemical characteristics of wood with sensors to optimize the transformation process. With the support of an item-

G. Picchi (\*)

J. Sandak InnoRenew CoE, Izola, Slovenia e-mail<EMAIL_ADDRESS>
S. Grigolato Department of Land, Environment, Agriculture and Forestry, Università degli Studi di Padova, Legnaro, PD, Italy e-mail<EMAIL_ADDRESS>
P. Panzacchi Department of Biosciences and Territory, Università degli Studi del Molise, Pesche, Italy

Faculty of Science and Technology, Free University of Bolzano-Bozen, Bolzano, Italy

R. Tognetti Dipartimento di Agricoltura, Ambiente e Alimenti, Università degli Studi del Molise, Campobasso, Italy e-mail<EMAIL_ADDRESS>
Institute of Bioeconomy of the National Research Council (CNR-IBE), Sesto Fiorentino, Italy e-mail<EMAIL_ADDRESS>
level traceability system, the same data could provide a formidable contribution to CSF. The "memory" of wood could support scientists to understand the response of trees to climate-induced stresses and to design accordingly an adaptive silviculture, contributing to forest resilience in the face of future changes due to human-induced climate alteration.

## **Acronyms**

## **9.1 Climate-Smart Forestry and Forest Operations**

Climate change is altering the ecological equilibrium of our planet. Forests are among the most affected ecosystems due to the increasing damages caused directly or indirectly by rising temperatures, such as droughts, wildfres, and pest attacks. On the other hand, in the Land Use, Land Use Change and Forestry sector (LULUCF), forests are considered a key tool in tackling greenhouse gases (GHG) concentration in the atmosphere. In this regard, there is an open debate concerning the most appropriate use and management of forests. Some researchers consider a priority the carbon sequestration capacity of forest ecosystems, suggesting a focus on the accumulation of carbon in forest biomass and soils. This would be achieved with a specifc management approach and reduction of timber harvests (Holtsmark 2012). The concern over timber extraction is not only related to illegal logging but also regarding the production of forest biomass for energy (Searchinger et al. 2018). Nevertheless, while illegal logging and deforestation are unanimously regarded as a threat, several authors consider that under appropriate management and regulations, timber and biomass extraction may contribute positively to an overall net carbon control (Kauppi et al. 2018; Favero et al. 2020), e.g., through substitution of fossil fuel-based products.

In this frame, the productive functions of forests are essential to guarantee an effective contribution to GHG mitigation. In fact, they provide renewable materials and fuels (substituting fossil-derived alternatives), food, as well as other non-wood forest products, whose importance may sometimes offset the role of woody materials (Sheppard et al. 2020). The production of goods with direct economic value is essential to support local communities and rural development. This in turn ensures forest management and preservation is economically and technically feasible. For instance, by allowing the presence of local inhabitants, which represent both the workforce and the main users/monitors of forests.

A possible answer to this complex scenario is provided by climate-smart forestry (CSF) (Yousefpour et al. 2018). This is a comprehensive approach, addressing the goals of Sustainable Forest Management (SFM) and the threat of climate change by enabling both forests and society to transform, adapt to, and mitigate climateinduced changes (Bowditch et al. 2020).

The previous and following chapters of this book describe in detail the concept of CSF as well as the solutions envisaged for its application and the tools used for forest monitoring. The present chapter focuses on the contribution that forest operations and, in a broader vision, the whole timber supply chain can provide to CSF application. This contribution can be summarized by two main roles:

Even if they stem from the same activities, these two roles can be easily differentiated when considered as part of CSF. In fact, the former is the application in practice of the management strategies, acting "passively" while implementing the guidelines and instructions elaborated by CSF models. The latter, instead, is an active contribution to the development of such models. In fact, the data produced and stored all along the timber supply chain can be used to better understand forest dynamics and improve the very models previously mentioned, closing the loop.

*Active forest management* is based on the use of specifc technologies and techniques. These can be combined to achieve both processes effciency, social benefts, and minimal environmental impact, implementing the concept of sustainable forest operations (SFO) as introduced by Marchi et al. (2018). SFO deployed in the frame of an adaptive silviculture is a crucial tool to enhance the resilience of forests and to achieve the following goals:

In order to secure a fast and effective implementation of SFO guidelines, sensing and digital technologies are necessary to plan, manage, and execute forest works, creating a link between SFO and precision forestry (PF). The latter can be defned as the application in forestry of geospatial information and remotely sensed data for planning silvicultural operations at the level of stand, sub-stand, or even individual trees (Holopainen et al. 2014). For instance, planning may identify broad restricted areas, as may be the case of riparian vegetation surrounding water bodies enclosed in the forest (e.g., ponds or creeks), but with individual-tree detail level, it can address the protection of individual trees (e.g., trees hosting nests of protected birds' species) as well as meet the precise requirement of nature conservation instances.

*Production of data at plot and tree level* is one of the distinctive requirements of CSF, which relies on the availability and elaboration of data (including the territorial scale). As described in the chapters of this book, this is essential for understanding the dynamics of forest growth and health and its responses to climate change and to draw models that support management hypotheses. Data is provided by a number of sources, ranging from satellite images to sessile sensors fxed on trees, varying greatly in territorial and time scale. Forest equipment is already an additional source of data, but the potential of machines as carriers of sensors for forest monitoring is still largely unexpressed. Furthermore, the whole timber supply chain, including the highly detailed sensors deployed by the timber transformation industry (e.g., sawmills), provides extremely valuable and accurate data regarding wood development and characteristics. This data could narrate the "memory of wood," relating the stresses and growing conditions experienced in the last decades (or centuries) by an enormous dataset of trees. For this purpose, an effective tracing system from stump to mill is necessary as well as the capacity to store and manage properly a high volume of data.

## **9.2 Timber Supply Chains and CSF: The Stat of the Art**

This section details the practical application of PF in planning and management of forest harvesting. It describes the present sources of data and their commercial application for feet control and for estimate of timber and biomass yield. Additionally, it discusses the developments expected in the near future and the main research lines currently known. All the information or data infrastructure is also considered from the point of view of CSF, and the potential synergies between commercial operations and forest monitoring activities are highlighted.

## *9.2.1 From Forest Inventories to the Virtual Forest*

At present, forest inventories (FI) are the most common application of precision forestry. For this purpose, visible (red/green/blue, RGB) or hyperspectral images are the main data source, collected from airborne sensors installed on different carriers, such as satellites (long distance), airplanes (medium distance), and unmanned aerial vehicles (UAVs) for short distances (White et al. 2016). Forest inventories are generally integrated with thematic maps, such as soil layers, forest treatments, tree species composition, and any relevant information reported. A detailed forest inventory plays a key role in the management of the forest as well as in its economic valorization (which may aim at producing an income for the owner or simply to cover the costs of the necessary management operations, depending on the function assigned to the forest stand). For this purpose, it includes not only quantitative values, such as timber volume, age distribution, and structure of the forest stand, but also qualitative fgures, such as health and fertility of the stands composing the forest.

A further technology with great potential and consolidated application in forest sector is the laser imaging detection and ranging (LiDAR), which has proven particularly effective in large-scale inventories, integrating data elaborated from RGB sensors (Matasci et al. 2018) and multispectral sensors (Puliti et al. 2020). Compared to the latter source of data, LiDAR provides a more reliable 3D information (Noordermeer et al. 2019) and allows a better estimate of the growing stock and the relative value of the harvestable roundwood (Peuhkurinen 2011). The assessment of the quantity and market value of growing stock can be further enhanced thanks to the application of terrestrial laser scanner (TLS). This can integrate both traditional inventories and aerial surveys, returning a detailed inventory including number of trees, shape and taper of stems, crow insertion, and other parameters not detectable with aerial, above-crown sensing (Mengesha et al. 2015). For instance, by integrating RGB images taken from UAVs with TLS scanning, Pichler et al. (2017) increased the effective volume estimation of the trees in the stand from below 80% for the aerial data to over 94% of the combined dataset. This proves the potential of merging data originated from different sensors and integrated with other digital information sources such as topographic or thematic maps (e.g., pedological layers) and traditional forest inventories. Such multisensor data fusion leads to the generation of a digital model of the studied object (Mitchell 2012), in this case the forest. This can be defned as the "virtual forest" (Rossmann et al. 2009), which gathers accurate, consistent, and readily available information regarding the real forest. This information is used to better plan and manage commercial forest operations. Some examples may be given by forest road and skid trail planning and georeferencing (Đuka et al. 2017). The virtual forest and the related database are both generated for and paid by forest management and harvest operations. Yet, from the point of view of CSF, they can be regarded as an excellent and massive data collection infrastructure. In fact, the availability of such an integrated network of sensors can provide stand-specifc information extremely useful to monitor the forest physiology and health parameters (see also Chap. 10 of this book: Tognetti et al. 2021).

## *9.2.2 Multipurpose Forest Operation Planning*

Cost optimization remains the foremost aim (and driver) of forest operation planning. Yet, forest operation plans are also the main tool used to balance forest growth and extraction of woody products, to minimize impact on soil and water resources and to guarantee the conservation of biodiversity.

Over time, the common timber-oriented planning approach has introduced an increasing number of targets, such as minimizing the damages to the remaining standing trees (still a timber-oriented goal). The development of a multi-target forest operation plan is a complex task, which requires more data regarding the forest and a higher capacity to elaborate and interconnect this information. For this purpose, the digital database of the virtual forest (VF) is the perfect source of data, which is not only related to standing trees but also to other descriptors of the forest. For instance, LiDAR data is also used to detail the terrain features through the digital surface model (DSM) and the digital terrain model (DTM). These are used to derive the canopy high model (CHM) but provide also relevant information regarding terrain and soil characteristics such as roughness, slope and, with the integration of sampling plots, bearing capacity (Pirotti et al. 2012).

The high-resolution 3D data of the VF combined with multi-spectrum satellite data collected in frequent time series is a key element to optimize planning of forest operations. It allows to minimize the transit for forest machines and to set predefned skidding trails (Sterenczak and Moskalik 2015) and cable layout (Bont and Heinimann 2012) that increase effciency of the operations, reducing costs per cubic meter of timber extracted. As an example, Fig. 9.1 shows a GIS analysis to evaluate alternative forwarder paths in an Alpine environment by considering variables I) slope and roughness of the terrain and II) the density of the forest stand. The variables were determined from LiDAR data: in particular, the digital terrain model (DTM) (a), the canopy height model (CHM) (b), the terrain roughness (c), and the cost surface normalizing and summarizing the previous data (d).

**Fig. 9.1** Example of timber hauling operation planning based on digital data. (Credits: Marco Pellegrin, Project NewFor)

Based on the mobility parameters of a medium-size forwarder, two different paths were generated: the ecological path (maximum uphill slope 30% and maximum downhill slope 43%) and the maximum path (maximum uphill slope 35% and maximum downhill slope 67% and a maximum lateral inclination of 4%), a path considering the maximum mobility limits of the machine. In both cases, the maximum lateral inclination was supposed to be 4%. The generated paths were then compared with the real paths of the machine driven by an expert operator.

Thanks to the high detail of the data, plans can get to a tree-level resolution and evaluate the interaction among trees at stand level and the trees' group dynamics (Pirotti et al. 2012; Lindberg and Holmgren 2017). This creates a link with the climate-smart silvicultural prescriptions described in Chap. 8 of this book (Pach et al. 2021) and strengthens the connection that may (and should) exist between the timber supply chains and CSF aims. Examples of this interaction can be provided by forest operation plans tailored to include the priority of habitats conservation, to tackle the spread of forest pests, and to consider the hydrological effect of logging extraction (Blagojević et al. 2019; Görgens et al. 2020). The reduction of soil damage due to forest operation can take advantage from the use of high-resolution data as reported by (Niemi et al. 2017; Salmivaara et al. 2018). Minimizing soil damage is one of the most important targets for the sustainability of forest operation to preserve soil fertility and forest regeneration and to reduce the rate of soil erosion (Cambi et al. 2015; Venanzi et al. 2019), for instance, by developing detailed wetindex and terrain mobility maps (Murphy et al. 2008; Mattila and Tokola 2019). Additionally, in the last two decades, water quality preservation has been introduced as a relevant factor in the planning of forest operations (Keleş and Baskent 2011). This is particularly relevant in mountain areas where the need to maintain wood production while preserving water quality coexists, maximizing the ecosystem services provided by the forest (Ovando and Speich 2020).

The higher complexity of multi-target planning calls for more powerful systems of data interpretation and modeling of forest dynamics. In fact, the more factors and goals are included, the higher will be the effort to develop decision tools. Analytic hierarchy process (AHP) techniques, as well as machine learning fuzzy algorithms, are increasingly deployed for such elaborations. The evaluation of the effects of forest operations in the forest environment can be even more complex when climate change effect is considered (Keenan 2015) with the related nonlinear alterations. On a world scale, climate change is infuencing in different ways the operating methods connected to forest harvesting and wood transportation, as well as in the choice of silvicultural addresses and landscape conservation. Consequently, the forest management planning, which includes also the planning of forest operations, needs to be supported by more complex approaches with the introduction of nonlinear approaches and heuristic techniques (Bettinger and Boston 2017). The challenge is to accomplish complex planning, addressing all the risks faced by the forest and all the benefts provided by the same forests such as soil protection, carbon storage, biodiversity, water supply, and non-wood forest products (Matthies et al. 2019).

## *9.2.3 Sensors on Forest Machines*

The appropriate implementation of the forest operation plans based on the FI (or the VF) requires logging machinery or forest teams equipped with geopositioning sensors (at least) and an appropriate interface with the FI (Holopainen et al. 2014). This is even more important when there is an upgrade to the virtual forest and its larger content of digital information. Most modern machines, such as harvesters and forwarders, can already beneft from a digital FI, for instance, with a better organization of harvesting of marked trees or forwarding piled logs along predefned paths. This is possible thanks to the presence onboard of global navigation satellite system (GNSS) receivers, which provide suffcient accuracy on fat terrain, particularly on areas with limited vegetation cover, such as clear-cuts (Valbuena et al. 2012). Digital FIs at present are generally deployed to guide machines through optimal paths to follow. These are elaborated according to predefned criteria, such as minimum cost, minimum impact on soil or standing trees, or a compromise among these (Piragnolo et al. 2019). In optimal cases, where geopositioning is highly reliable and accurate, this application can be stretched to the level of a single tree to cut, implementing a virtual tree marking performed directly on the digital inventory.

This information can be further refned with the information of the exact position of the processing head or the logs grapple (boom's tip) with respect to the machine, leading in optimal conditions to a sub-metric precision in recording the position of the standing tree or the pile of logs (Lindroos et al. 2015). These machines can also feed the virtual forest with additional data collected by the onboard sensors. At present, the parameters measured are the diameters and length of the logs produced by the harvester: values needed to calculate the felled and processed volume (Eriksson and Lindroos 2014). These are generally used for invoicing timber produced and delivered but can also provide a detailed insight of the quantity of roundwood produced in the harvested plot (Rossit et al. 2019) and draw a balance between net annual increment and harvesting of a given forested area. Furthermore, by segregating the assortments, at least in main classes (e.g., pulp-wood vs. industrial timber), it is possible to estimate several characteristics of the harvested trees (Lu et al. 2018) and, possibly in the near future, even to develop forest yield maps (Olivera and Visser 2016).

An additional sensor, which is increasingly installed on forest machines, is the timber crane weighing load cell. It quantifes the exact masses of timber and biomass extracted by forest operations (Laurila and Lauhanen 2012). Currently, this information is used to better plan and link the different operations of the biofuel supply chain (extraction, drying, comminution and transport). It can also contribute to drawing a more precise balance between forest growth and woody products extraction (Fig. 9.2).

Finally, among the last sensors installed in forest machinery, we can report the deployment of cameras used for the automatic detection of stem damage on the trees left in the stand during harvesting. The elaboration of digital pictures, by means of logistic regression models in image processing, allows the operators to identify the damaged (debarked) trees, counting their number and ranking the level of damage (Palander et al. 2019). The system was designed to estimate timber value losses over time and the forest areas potentially susceptible to bark diseases due to damage intensity. A different elaboration of the same dataset of images could return

**Fig. 9.2** Modern forest machines feature as a standard georeferencing sensor and wireless data transmission system (1) and encoders (in case of processor heads – 2). Additionally, accurate crane positioning systems (3) and grapple load cells (4) are increasingly used

additional services, for instance, for monitoring phenology, composition, tree cover, and biodiversity of the forest plots, where the machines transit, integrating with remote-sensing data products (see Chap. 11 of this book: Torresan et al. 2021) (Table 9.1).

Clearly, as already discussed, the maximum potential of the data provided by forest machines relies on the possibility to integrate it with other data sources, returning highly detailed estimates of stand characteristics (Barth and Holmgren 2013). Under this perspective, the potential of forest machines, as a carrier of sensors, and its capacity to interact with the virtual forest are still largely unexploited and can provide important benefts both to the effciency of the supply chain and forest monitoring.

## **9.3 Marking and Tracking Systems in Forestry**

Following the example of precision agriculture and precision farming (Mavridou et al. 2019), the evolution of onboard sensors and communication systems in forest machines has gradually made it possible to measure valuable parameters for each

**Table 9.1** Main sensors currently installed on forest machines relevant for precision forestry (current) and CSF (potential) applications

produced item, such as logs and wood chips. This has promoted the development of technologies capable of automatically linking, such information to individual timber products, relating each item to its dimensions (returning volume and assortment) and to the position of the machine during the operations. Forest companies are increasingly interested in these systems, since an effective marking (tagging) system of timber products provides both track and trace services, which may signifcantly reduce the costs of timber production and management:

In addition to the direct economic savings, the availability of technologies for tree marking and timber product traceability would be a powerful tool for sustainable forest management disclosing or enhancing the following services:

Tracking systems are common in industrial applications, but to automatically identify single logs throughout the forest supply chain is a challenging task. In timber supply chains, several handling operations may be involved (such as skidding, loading, piling, etc.), causing mechanical impacts and frictions. The capacity of tags or marks to remain attached to the logs is further hindered by the exposure to weather factors, such as rain, frost, and sunlight exposure. These factors, together with the presence of mud, dust, or resins and with the very variable conditions of natural illumination, may challenge readability of ID codes in the case of visual systems. Additionally, the tracking service should be based on unique codes (physical ID number) linked with an ID code stored in a database, allowing it to retrieve the attributes associated with each timber item. A further requirement is that the system must be reliable and relatively inexpensive, allowing to mark the ID of trees and logs without incurring in signifcant productivity losses for the forest operations. Finally, the stored information must be retrieved automatically at predefned steps of the chain supply with remote systems featuring reading ranges above 1 m (Korten and Kaul 2008).

## *9.3.1 Current Marking Systems*

At present, several simple marking and tracing systems are used in forest management and timber production activities. This is the case in most of the Alpine region, where trees selected for felling are manually marked with log brand hummers in the frame of close-to-nature silviculture (Fig.9.3). In the simplest case, the tool is used to debark a spot of the trunk, creating a mark easily detectable by the chain saw operators. The forester uses the brand, featuring a personal and unique shape, to mark the stump of the tree and certify the selection made. This makes it possible to identify any tree felled other than the selected ones and detect illegal or unauthorized logging.

Due to their low cost and relative robustness in identifying trees intended for timber production, log brands as well as paper or plastic tags are used by a large number of forest companies worldwide to mark trees in the forest but also logs at sorting yards (Murphy et al. 2012; Kaakkurivaara 2019).

Color marking is another very common system, thanks to its fast and practical application. Along with manual marking, color spray enables automated marking. This is done by processor heads equipped with spray nozzles, which quickly mark the processed logs with a combination of up to three colors (Fig. 9.4). The system is generally used to segregate assortments differentiated by length and diameter classes (e.g., pulpwood vs industrial timber), as measured by the onboard sensors

**Fig. 9.3** Brand hammer used to mark trees. Note the area debarked with the sharp part of the tool and in the back of it the shape of the brand. Painting and yellow tags were part of a test and would not be used in common tree marking together with brand hammer

**Fig. 9.4** On the left, a timber processor crosscutting a tree. Just after this operation, it is possible to mark the cut section with colors. On the right, a processor head equipped with color spray: the blue color tank is visible

simplifying the operations of hauling and piling per assortment. The solution is effective, but it requires visual identifcation and interpretation by an operator at each step of the process and carries no single-item properties.

In timber supply chains featuring assortments with high unitary value, it is quite common to individually mark each log. Traditionally, this operation is performed manually, and the characteristics to be associated with the log are measured and reported manually in a database. Log brands cannot be used for this purpose, as they cannot defne a unique ID for each log. Thus, volume, quality class (based on visual evaluation), species, and forest lot of provenance are associated with a unique alphanumeric code printed on a plastic tag fxed on the log. This information is used to track the log along the logistic process and as a reference for purchasing and invoicing of the timber products. Nevertheless, in spite of their low investment cost, manual-based tracking systems are not suffcient to cope with the recent developments in forest equipment technology.

## *9.3.2 Optical Marking Systems*

When using paper or plastic tags, all the process is manual, as well as the recording of codes at the different steps of the supply chain (e.g., delivery at the yard of the end user). This leads to possible errors while reading or noting the codes, but most of all, it is a time-consuming operation, which may signifcantly increase the cost of the fnal assortments (Kaakkurivaara 2019). In the attempt to facilitate its use, some producers print on the plastic tags both the alphanumeric code and a barcode, or just the latter which can be acquired with manual optical readers.

Several types of barcodes are in use worldwide, but the most common types are:

Barcodes are relatively inexpensive as can be printed on any support, usually paper or plastic tags, and applied to the timber products. This technology requires visual connection for code acquisition with smartphones or portable devices, and effective reading can be hindered by inappropriate light conditions or presence of mud and dirt on the barcode. Furthermore, tags can be removed or damaged during handling and transport operations. This last inconvenience can be overcome printing the barcode directly on the wood surface. Spraying ID codes on wood boards is a common tracking system in industrial sawmills and has been successfully tested in forest operations by installing spray nozzles on the chain saw bar of a processor head (Möller et al. 2011). This solution allows to mark the crosscut section of each log with a special barcode while processing and without productivity losses (Figs. 9.5 and 9.6). Clearly, the system has several challenges, among which is the readability of a code printed on the relatively rough surface of a log crosscut with chain saw. Readability can be improved with the addition of microtaggants. These are microscopic particles to be mixed with the paint used for spraying. Being composed by different layers artifcially designed, microtaggants provide a unique numeric code (visible with microscopic analysis), which prevents falsifcation and that may include materials that enhance readability when exposed to UV or laser light sources.

**Fig. 9.5** On the left, logs recently hauled marked with plastic tags (orange). On the right, two models of plastic tags with numerical and UPC barcode

**Fig. 9.6** Example of UPC barcode on plastic tags (left) and a QR code (right)

**Fig. 9.7** The coded brands punched in the solid wood on the left carry an information carried as a unique ID for the log as simplifed on the center and right. (Source www.otmetka.com)

A further development of the barcoding concept in timber industry is provided by the Swedish company Otmetka, which developed a dedicated solution for visually marking single logs. The system, called Woodpecker, is constituted by 12 hammer brands, which are punched into the wood by the harvester head. The hammers can independently rotate, and each position represents an alphanumeric value, generating a unique 12-digit code that identifes the timber item, assigning it an ID that allows retrieving its attributes in the associated database. The marks are impressed in the butt end of the log and can be read with optical technology and software elaboration at the sawmilling facility (Fig. 9.7). Also, this technology has been tested successfully on processor heads, leading to a fast and effective tagging of logs.

Another promising technology for timber tracking is biometrics fngerprinting (Murphy et al. 2012). This technology is based on the identifcation of the unique characteristics of each log end section (or crosscut section), identifed through the analysis of digital images. The system is better suited for industrial, indoor applications due to the more controlled reading conditions (stable light, fxed angle, and distance of reading), but the implementation on processor heads has been conceived in order to secure a tracking service of single logs from the stump to the mill (Schraml et al. 2015). Biometric fngerprinting requires high-quality images of the log ends to discriminate logs. Common cameras providing images in the visible spectra can be deployed, but sensors operating in the hyperspectral and NIRs proved more effective (Schraml et al. 2020). Clearly, the fle size of images would be too large to transfer it from the forest to a server and store it in a large database (e.g., storing data for all the logs produced annually by a company). The frst elaboration can identify the key identity characteristics of the log end and store the information in much lighter vector fles, which can be effectively transferred in a reference database (Fig. 9.8). Deployment of biometrics from stump to mill would provide useful data for the industry, for instance, sorting early in the supply chain the timber assortments, but with slight adjustments of the image analysis software, it would also provide relevant CSF information regarding health and development of the felled trees. Biometric fngerprinting technology is not yet at a commercial stage, but its fast development is expected to soon open a wide range of applications and services to the timber supply chain, forest management, and CSF.

In general terms, all optical systems share the same advantages and drawbacks:

Pros

Cons

**Fig. 9.8** Biometrics fngerprinting is based on the elaboration of visible and measurable characteristics of the log end, compressed in vector-format information. (Credit: Rudolf Schraml)

## *9.3.3 Radio Frequency Identifcation (RFID)*

Another promising technology for tracking timber products is provided by the radio frequency identifcation (RFID), based on the capacity to transmit information via electromagnetic waves. A typical RFID system is based on a reader connected to one or more antennas emitting an interrogating signal. The signal is received by tags attached to the item. Tags consist of a transponder and a chip and can be active (with an inner power source) or passive. The latter requires the energy provided by the interrogating wave to return a signal. By EPC standard, the signal returns the identity of the tag, stored in the 12-byte memory of the chip. Disposable, passive RFID tags are preferred in timber supply chains due to their low unitary cost, even if they can store less memory and feature a lower reading distance compared to active tags (Björk et al. 2011). RFID can operate at different frequencies, ranging from low (LF), high (HF), to ultrahigh (UHF). The latter allows effective reading ranges of several meters in operative conditions with passive tags (Tzoulis et al. 2014; Kaakkurivaara and Kaakkurivaara 2019). RFID tags had been successfully used to transfer throughout the sequence of forest operations the valuable information provided by inventory data elaboration, such as bucking instructions for maximum value recovery (Picchi et al. 2015).

Among the main advantages of RFID tags in forestry applications, there is the possibility to perform fast and effective bulk reading (e.g., a whole truckload passing through a mill's gate). Furthermore, they can be used both to mark standing trees (Picchi 2020) and processed logs. Therefore, RFID technology can provide a complete service of timber traceability, which may be a powerful tool in the frame of a chain of custody service, guaranteeing the sustainable production of timber products from the forest to the sawmill and up to the end user (Appelhanz et al. 2015).

Regarding the drawbacks, currently (year 2020) the unitary cost of disposable UHF-RFID tags is relatively high. For custom-made tags, it ranges around 0.6–0.27 €, respectively, for batches of 5000 and 100,000 units (Picchi 2020). Furthermore, mills could be unenthusiastic to deal with tags made of plastic and metal, even if their overall mass is about 1 g. A possible solution could be the use of pulp-neutral material for the shell and radio-refecting ink for the transponder, even if this would surely increase the cost of tags and probably reduce their performance (Fig. 9.9, Table 9.2).

Pros

Cons

**Fig. 9.9** On the left, an UHF RFID tag used to mark a standing tree, on the right an UHF RFID applied by the processor head after crosscutting

**Table 9.2** Suitability of tracking technologies to applications in forestry and timber supply chains

## **9.4 Timber Industry as a Source of Data for CSF**

As mentioned in the previous section, the availability of a reliable tracking service discloses several new opportunities in timber supply chains. Among the most promising applications can be found the synergy between tracking technology and timber grading systems based on fast and nondestructive sensors. At present, these sensors fnd little application in forest operations: timber assortments can be sorted with machine support (e.g., using the StanForD data and dedicated software in the harvest machine), but quality grading of the logs is performed only visually. Nevertheless, this is a costly and time-demanding operation, which is potentially biased by the subjective judgment of the expert evaluator.

Once in the industry, a large set of sensors is used to precisely quantify the volume of the logs delivered and its quality. Additionally, an increasing number of sensors or analytical techniques are used to optimize the following steps of product transformation in the sawmill or pulp mill. According to Gergel et al. (2019), the sawmilling optimization made possible by a detailed knowledge of the properties and defects of single logs leads to an increased value recovery of 15% and 23%, respectively, for conifer and broadleaf timber. The same authors also highlighted how the status and quality of the standing trees prior to harvest plays a role of the utmost importance in the effciency and economic balance of the timber supply chain. Nevertheless, in real practice, just empirical sorting models are used for inventorying trees according to their economic value. These return the share of predefned timber assortments with an intrinsic inaccuracy due to the impossibility of detecting internal wood defects from external features. A wide range of sensors could contribute to provide this service early in the supply chain. Their potential is maximum when different sensors work in synergy, contributing to generate a wide and comprehensive picture of the timber quality, for instance, integrating stem shape characteristics as returned by a TLS system (e.g., taper, straightness, crown insertion, etc.) with internal properties as detected by optical sensors on the felled trees (e.g., rot, decay, eccentricity, etc.). In the short term, the fusion of such data provides a more detailed defnition of quality of single logs. In the long term, optically sensed characteristics may be used to tune the models interpreting 3D data provided by laser technology, gradually but constantly decreasing the gap between estimated properties and actual characteristics of the assortments. The very same data and approach can also disclose the "memory" of timber, being this the result of the growing conditions that the tree endured along its life. Widening the scope of the data analysis and the inputs of the models, it will be possible to support CSF studies and forecasts by relating the captured wood characteristics with the physiology of the trees and their response to the past stresses.

A recent trend in timber characterization is to deploy sensors as early as possible in the timber supply chain. Although application of timber quality gauges in forest machinery is mostly at the experimental stage, it arises great interest from the industry, since quality determination early in the supply chain would allow a great reduction of procurement costs by delivering just the desired quality to each end user, optimizing the logistics and further increasing the proftability of the industrial transformation. At the same time, the application of sensors for timber quality along the timber production process would bring additional benefts also to CSF applications, providing more data and with higher level of detail.

In addition to UAVs, forest technologies for monitoring tree processes include sensor networks deployed on the tree stems or embedded in the soil layers. The proliferation of these technologies generates a fow of data, which needs to be appropriately investigated through machine learning for automating or responding to disturbance events. The digitalization of forest stands allows forests to operate as technological platforms so that trees function as technical instruments informed by data that are meant to enable precision forestry and practices oriented toward high timber quality.

## *9.4.1 Wood Properties Relevant for CSF*

The industrial conversion of timber highly relies on the intrinsic characteristics and technical properties of this resource, which may be advantageous (or not) depending on the downstream process applied. The set of properties defning the quality of wood must be determined against the industrial requirements, local policy, and environmental constraints to assess its market value.

In a theoretical approach, a healthy tree results in production of the "perfect wood" defned here as a bioresource without wood defects. Perfect wood corresponds to the cylinder with a pith positioned in its geometrical center and containing regular concentric structures corresponding to yearly rings. In practice, perfect wood does not exist and always includes some defects. Here, the "defect" is considered as an undesired imperfection of the regular wood tissues that is a result of diverse stresses and factors affecting tree growth and the morphological constitution of the plant. Such natural features may be highly undesirable, downgrading the industrial value of timber. An example could be a knot that is an imprint of the branch positioned in the trunk. Branches cause the presence of knots that deviate the fber direction, having a tremendous effect on the mechanical properties of timber, as well as tree stability.

#### **<IP_ADDRESS> Tree-Ring Structure**