Natural disturbance regimes as a guide for sustainable forest management in Europe

Abstract

In Europe, forest management has controlled forest dynamics to sustain commodity production over multiple centuries. Yet over‐regulation for growth and yield diminishes resilience to environmental stress as well as threatens biodiversity, leading to increasing forest susceptibility to an array of disturbances. These trends have stimulated interest in alternative management systems, including natural dynamics silviculture (NDS). NDS aims to emulate natural disturbance dynamics at stand and landscape scales through silvicultural manipulations of forest structure and landscape patterns. We adapted a “Comparability Index” (CI) to assess convergence/divergence between natural disturbances and forest management effects. We extended the original CI concept based on disturbance size and frequency by adding the residual structure of canopy trees after a disturbance as a third dimension. We populated the model by compiling data on natural disturbance dynamics and management from 13 countries in Europe, covering four major forest types (i.e., spruce, beech, oak, and pine‐dominated forests). We found that natural disturbances are highly variable in size, frequency, and residual structure, but European forest management fails to encompass this complexity. Silviculture in Europe is skewed toward even‐aged systems, used predominately (72.9% of management) across the countries assessed. The residual structure proved crucial in the comparison of natural disturbances and silvicultural systems. CI indicated the highest congruence between uneven‐aged silvicultural systems and key natural disturbance attributes. Even so, uneven‐aged practices emulated only a portion of the complexity associated with natural disturbance effects. The remaining silvicultural systems perform poorly in terms of retention compared to tree survivorship after natural disturbances. We suggest that NDS can enrich Europe's portfolio of management systems, for example where wood production is not the primary objective. NDS is especially relevant to forests managed for habitat quality, risk reduction, and a variety of ecosystem services. We suggest a holistic approach integrating NDS with more conventional practices.

Full text

Aszalós Réka (Orcid ID: 0000-0002-4268-0775)
Thom Dominik (Orcid ID: 0000-0001-8091-6075)
Hlásny Tomáš (Orcid ID: 0000-0001-9771-7435)
Kovács Bence (Orcid ID: 0000-0002-8045-8489)
Müller Jörg C. (Orcid ID: 0000-0002-1409-1586)
Journal: Ecological Applications
Manuscript type: Article
Title: Natural disturbance regimes as a guide for sustainable forest management in Europe
Réka Aszalós1, Dominik Thom2,3,4, Tuomas Aakala5, Per Angelstam6,7, Guntis Brūmelis8, László
Gálhidy9, Georg Gratzer10, Tomáš Hlásny11, Klaus Katzensteiner10, Bence Kovács1, Thomas
Knoke12, Laurent Larrieu13, Renzo Motta14, Jörg Müller15,16, Péter Ódor1, Dušan Roženbergar17,
Yoan Paillet18, Diana Pitar19, Tibor Standovár20, Miroslav Svoboda11, Jerzy Szwagrzyk21, Philipp
Toscani22, William S. Keeton3,23,*
1 Centre for Ecological Research, Institute of Ecology and Botany, Vácrátót, H-2163, Hungary
2 Ecosystem Dynamics and Forest Management Group, School of Life Sciences, Technical
University of Munich, 85354 Freising, Germany
3 Gund Institute for Environment, University of Vermont, Burlington, VT 05405, USA
4 Institute of Silviculture, Department of Forest- and Soil Sciences, University of Natural
Resources and Life Sciences (BOKU), 1190 Vienna, Austria
5 School of Forest Sciences, University of Eastern Finland, FI-80101 Joensuu, Finland
6 School for Forest Management, Faculty of Forest Sciences, Swedish University of Agricultural
Sciences, 73921, Skinnskatteberg, Sweden
7 Department of Forestry and Wildlife Management, Inland Norway University of Applied
Sciences, N-2480 Koppang, Norway
8 Faculty of Biology, University of Latvia, Riga, LV-1004, Latvia
9 WWF Hungary, Budapest, H-1141, Hungary
10 University of Natural Resources and Life Sciences, Vienna (BOKU), 1180 Wien, Ausztria
11 Czech University of Life Sciences in Prague, Faculty of Forestry and Wood Sciences, 165 00,
Praha 6 – Suchdol, Czech Republic
12 Institute of Forest Management, School of Life Sciences, Technical University of Munich,
85354 Freising, Germany
13 Univ. Toulouse, INRAE, UMR DYNAFOR, Castanet-Tolosan, France & CNPF-CRPF
Occitanie, Tarbes, France
14 Department of Agriculture, Forestry and Food Sciences (DISAFA), University of Turin, 1095
Grugliasco (TO), Italy
15 Field Station Fabrikschleichach, Biocenter, University of Würzburg, 96181 Rauhenebrach,
Germany
16 Bavarian Forest National Park, 94481 Grafenau, Germany
This article has been accepted for publication and undergone full peer review but has not been
through the copyediting, typesetting, pagination and proofreading process which may lead to
differences between this version and the Version of Record. Please cite this article as doi:
10.1002/eap.2596
This article is protected by copyright. All rights reserved.

17 Department of Forestry and Renewable Forest Resources, University of Ljubljana, 1000
Ljubljana
18 Univ. Grenoble, Alpes, INRAE, BP76, 38402 Saint-Martin-D’Hères, France
19 National Institute for Research and Development in Forestry “Marin Dracea”, 77190
Voluntari, Ilfov, Romania
20 Department of Plant Systematics, Ecology and Theoretical Biology, ELTE Eötvös Loránd
University, H-1117, Budapest, Hungary
21 University of Agriculture in Krakow, Department of Forest Biodiversity, 31-425 Krakow,
Poland
22 Institute of Agricultural and Forestry Economics, University of Natural Resources and Life
Sciences (BOKU), Vienna, A-1180 Vienna, Austria
23 Rubenstein School of Environment and Natural Resources, University of Vermont, Burlington,
VT 05405, USA
* Corresponding author: William S. Keeton. Email: william.keeton@uvm.edu
Manuscript received 1 July 2021; revised 13 November 2021; accepted 1 December 2021
Handling Editor: Luc Barbaro
Open Research: Data (Aszalós 2021) are available from the Open Science Framework repository
at https://osf.io/t468c/

ABSTRACT
In Europe, forest management has controlled forest dynamics to sustain commodity production
over multiple centuries. Yet over-regulation for growth and yield diminishes resilience to
environmental stress as well as threatens biodiversity, leading to increasing forest susceptibility
to an array of disturbances. These trends have stimulated interest in alternative management
systems, including natural dynamics silviculture (NDS). NDS aims to emulate natural
disturbance dynamics at stand and landscape scales through silvicultural manipulations of forest
structure and landscape patterns. We adapted a “Comparability Index” (CI) to assess
convergence/divergence between natural disturbances and forest management effects. We
extended the original CI concept based on disturbance size and frequency by adding the residual
structure of canopy trees after a disturbance as a third dimension. We populated the model by
compiling data on natural disturbance dynamics and management from 13 countries in Europe,
covering four major forest types (i.e., spruce, beech, oak, and pine-dominated forests).
We found that natural disturbances are highly variable in size, frequency, and residual structure,
but European forest management fails to encompass this complexity. Silviculture in Europe is
skewed towards even-aged systems, used predominately (72.9% of management) across the
countries assessed. The residual structure proved crucial in the comparison of natural
disturbances and silvicultural systems. CI indicated the highest congruence between uneven-aged
silvicultural systems and key natural disturbance attributes. Even so, uneven-aged practices
emulated only a portion of the complexity associated with natural disturbance effects. The
remaining silvicultural systems perform poorly in terms of retention as compared to tree
survivorship after natural disturbances. We suggest that NDS can enrich Europe’s portfolio of
management systems, for example where wood production is not the primary objective. NDS is

especially relevant to forests managed for habitat quality, risk reduction, and a variety of
ecosystem services. We suggest a holistic approach integrating natural dynamics silviculture
with more conventional practices.
Key words: clearcut, close-to-nature forestry, deadwood, emulation of natural dynamics, even-
aged, forest management, natural disturbance, natural dynamics silviculture, residual structure,
retention, severity, uneven-aged
1. INTRODUCTION
Growth, composition, structure, and age class distributions of the vast majority of European
forests are tightly regulated under a variety of production driven, even-aged and continuous
cover systems aimed at supplying industrial raw materials (Schelhaas et al. 2018, Puettman et al.
2008). However, maximizing growth and yield often diminishes resilience to environmental
stressors (Farrell et al. 2000, Thomson et al. 2009, Sommerfeld et al. 2021) leading to increasing
susceptibility to an array of human and natural disturbances (Cardinale et al. 2012). It may also
lead to declines in many elements of biodiversity (Hobson and Schieck 1999, Brunet et al. 2010,
Drapeau et al. 2016), like species dependent on forest cover continuity, deadwood, and large
trees. Examples of such species include bryophytes, lichens, fungi, and saproxylic beetles
(Müller et al. 2007, Paillet et al. 2010, Brunet et al. 2010, Roth et al. 2019). Moreover, forest
operations decreased the share of old European forests (Vilén et al. 2012, Sabatini et al. 2018)
and modified their natural structure, composition, and dynamics for centuries, reducing their
overall naturalness in several parts of Europe (Wallenius et al. 2010a, Brumelis et al. 2011).
Forest scientists in many regions around the world have therefore proposed innovative ways of

managing forests both for a greater variety of services and biodiversity, and for enhanced
resilience and adaptive capacity to global change (Bengtsson et al. 2000, Gustafsson et al. 2012;
Mori and Kitagawa 2014, Fahey et al. 2018, Kuuluvainen et al. 2021). For example, there is
growing interest in the development of forest management techniques designed to approximate
the structural and compositional dynamics of “natural” (or less human-influenced) ecosystems
(Angelstam 1998, Keeton 2007, Kuuluvainen and Grenfell 2012, Puettmann et al. 2015). Here
we use the term “natural dynamics silviculture” to refer to these approaches, recognizing this as
part of a larger trend towards “ecological silviculture” as described by Franklin et al. (2018) and
others (e.g. Palik and D’Amato 2017, Keeton et al. 2018). In Europe, there has long been interest
in ecological or multi-functional forest management approaches (Bengtsson et al. 2000, Diaci et
al. 2006, Wolfslehner and Seidl 2010, Kraus and Krumm 2013, Brang et al. 2014, Pretzsch et al.
2017). Natural dynamics silviculture has the objective of emulating natural disturbance dynamics
to better approximate the environmental conditions in which these organisms have evolved
(Angelstam 1996, Aplet and Keeton 1999, Bengtsson et al. 2000, Franklin et al. 2007, Keeton
2007). In some cases, ecosystem services, such as carbon storage and hydrologic regulation
(Ford and Keeton 2017), or wildlife habitat and improved risk management (Huuskonen et al.
2021) may be a co-benefit. A further goal is to enhance resilience to global change (through
adaptive capacity) by providing a broader array of plant functional traits and functional
complexity in managed forests (Messier et al. 2013, Thom et al. 2019, 2020). This is in contrast
to the narrow range of traits and functional diversity representation offered by intensive forest
management practices, such as short rotation, even-aged forestry, which simplify and
homogenize forest stands and landscapes (Fahey et al. 2018). Natural dynamics silviculture is
not intended to fully mimic natural disturbances; rather it is an approach advocated for its utility

in building complexity of habitat conditions, seral community diversity, and ecosystem service
provisioning into managed forests (North and Keeton 2008; Angelstam 1996), recognizing that
there can be tradeoffs among multiple objectives (see, for example, Sabatini et al. 2019).
Besides economic and logistic reasons, a major barrier to implementing natural dynamics
silviculture has been the lack of comprehensive understanding of the ranges of variability
(whether historic, contemporary, or future) in natural disturbance regimes, including frequencies,
spatial attributes, and severities (Kulakowski et al. 2017). Moreover, the distribution,
composition, and dynamics of European forest landscapes have been fundamentally altered by
millennia of human influence (Kaplan et al. 2009, Keeton et al. 2013, Pretzsch et al. 2017,
Angelstam et al. 2021). Consequently, finding reference forests in which to observe baseline
disturbance dynamics is needed, but also highly challenging, since only small fragments of
primary or old-growth forests remain in most places (Szwagrzyk and Gazda 2007, Mikoláš et al.
2019). The proportion of remnant old-growth (primary) forests is only 0.7% of the forest cover
in Europe (without Russia), with montane beech forests overrepresented relative to other forest
types (Sabatini et al. 2018). However, in recent decades great progress has been made in
describing the disturbance regimes of European forests, by applying long-term observational data
(e.g. Thom et al. 2013, Nagel et al. 2017a), statistical (Seidl et al. 2014), and
dendrochronological data analysis (Nagel et al. 2014, Čada et al. 2020), literature review
(Kuuluvainen and Aakala 2011, Thom and Seidl 2016, Kulakowski et al. 2017), conceptual
approach (White and Jentsch 2001, Kulakowski et al. 2017), as well as analysis of remote
sensing data (Senf and Seidl 2020). Our study advances the science by comparing such literature
derived data on disturbance dynamics with a comprehensive database on forest management
effects across 13 countries. The analysis encompasses four of the major European forest

categories, including those dominated by Norway spruce (Picea abies (L.) H. Karst.), Scots pine
(Pinus sylvestris L.), European beech, (Fagus sylvatica L.), and oak (Quercus robur Pall., Q.
petrea (Matt.) Liebl., Q. pubescens Brot., Q. cerris L.). Without the Mediterranean forest types,
oak forests include mesophytic and thermophilous deciduous oak dominated forests (EEA 2006,
pp. 28).
1.1 Comparing natural disturbance dynamics to forest management
A consistent comparative framework is needed to analyze how ecologically important attributes
of forests managed using conventional systems may differ from those associated with natural
disturbances regimes, such as the structural and stand development dynamics of primary and
long-time unmanaged forests. We explore this potential by assembling data on pan-European
forest disturbances and management effects. We use those data to adapt for Europe the
“Comparability Index” (CI) first proposed by Seymour et al. (2002) in North America and later
modified by North and Keeton (2008). The CI plots the relative frequencies and sizes of
dominant disturbance types – such as gap forming, intermediate and high severity events –
against the frequencies and scales of regeneration harvesting methods, such as clearcutting or
selection systems. Using the current version of the index, silviculturists can determine how to
adjust harvesting regimes to better approximate natural disturbance dynamics in terms of spatial
scale and frequency.
In this study we expand the CI framework by adding a third dimension that characterizes the
residual structure of forest stands (see, for example, Turner et al. 1998). The third axis
represents percent survival (post natural disturbance) or retention (post-harvesting) of canopy
trees, and is thus comparable to the inverse of disturbance severity. This results in a 3-

dimensional framework showing ranges of variability both for natural disturbance dynamics and
forest management systems, based on the shared parameters of spatial extent, frequency, and
residual structure. A similar framework was employed for boreal forests in Canada (Bergeron et
al. 2002). With this innovation, the framework now provides a comprehensive basis for assessing
the congruence between forest management and natural disturbances in both temperate and
boreal European forest ecosystems.
1.2 Understanding variability in disturbance regimes
We synthesized research on disturbance dynamics obtained from both a survey of expert
knowledge on the forest management of 13 European countries and a literature review on the
natural disturbance regime of European forests. For example, relevant research has utilized (i)
stand level structural observations of remnant old-growth stands (Korpel 1995, Standovár and
Kenderes 2003, Schütz et al. 2016, Jaloviar et al. 2017, Aakala 2018), (ii) dendrochronological
studies (Splechtna et al. 2005, Svoboda et al. 2012, Nagel et al. 2014, Čada et al. 2020), and (iii)
historical and remote sensing studies (Aszalós et al. 2012, Nagel et al. 2017a, Senf and Seidl
2018). There are many studies in the first group (i), describing composition and structure or
short-term dynamics in old-growth forests, based on repeated measurements, but these have
yielded only limited information on long-term and landscape scale dynamics.
Dendrochronological studies (ii) have longer (e.g. multiple centuries) time-frames, but explore
primarily stand-level processes; while the third group (iii) includes areas with forests under
strong human influences. Therefore, in our study, we relied on expert knowledge to synthesize
and triangulate data from multiple types of natural disturbance studies and for all four of the
major forest categories.

There are multiple sources of spatial variability in European disturbance processes (Senf and
Seidl 2018, 2020), differing among categories and biomes (Thom and Seidl 2016). For instance,
historically, fire played a greater role in boreal forests as compared to European temperate
systems. It was typically infrequent and high severity in Norway spruce stands, and frequent but
of low to mixed severity in Scots pine stands (Angelstam 1998, Niklasson and Granström 2000,
Aakala 2018). However, in all types, residual live trees, both dispersed and aggregated in
patches, typically persisted post-fire (Berglund and Kuuluvainen 2021). Wind disturbances are
also a dominant structuring process across all European forests, though varying greatly in
intensity and frequency, for example exhibiting periods when high intensity wind storms are of
greater prevalence (Zielonka et al. 2009; Svoboda et al. 2012, Čada et al. 2016). Recent research
on the role of intermediate severity disturbances suggests a much broader range of variability in
the resulting stand age class structure and tree demography than previously recognized for
European forests (Nagel et al. 2014, Svoboda et al. 2014, Trotsiuk et al. 2014, Janda et al. 2017).
For example, in central Europe multi-aged (i.e. multi-cohort) stands originating from partial
disturbances and subsequent pulse tree recruitment are common in some primary conifer forests
(Mikoláš et al. 2017).
Thus, contrary to dominant even-aged management practices, natural dynamics silviculture aims
to manage for a range of structures, including multi-aged or multi-cohort forest structures
(O’Hara 1998). These are more analogous to the stand structures created by periodic partial
mortality events and associated pulses of tree recruitment (Meigs et al. 2017). Large, infrequent
disturbances are also a component of European natural disturbance regimes, but are more
challenging to accommodate as a management objective (Turner et al. 1998). The comparative

framework we propose synthesizes the current knowledge of these ranges of variability,
presenting a basis for consistent comparisons against forest management.
In this paper, we explore the central research question; namely, what is the congruence between
the silvicultural systems and natural disturbances in Europe? The study addresses several related
objectives. These include understanding how congruence/divergence relationships are influenced
by adding residual structure as a third axis to the Comparability Index and how does management
differ from the natural disturbance regimes for different forest categories. Finally, we discuss how
management approaches could be modified, where desirable, to more closely emulate natural
disturbances.
We hypothesize that contemporary forest management in Europe exhibits very low congruence
with past and present natural disturbances. We also hypothesize that by adding the third axis
(residual structure), the divergence between natural disturbances and silvicultural systems will
increase, and that this divergence will vary by biome and by forest category.
2. METHODS
2.1 Scope of the Study
The geographical scope of this study spans the boreal and temperate forest regions of Europe.
We excluded the Mediterranean zone because of the greater variability and fragmentation of the
region’s extant forests and fundamental differences in forest history and contemporary
management. We addressed four broad forest categories, dominated by four focal species;
namely Norway spruce, Scots pine, European beech and main European oak species (Quercus
robur, Q. petrea, Q. pubescens, Q. cerris). The classification criterion for this typing required
that the dominant tree species exceeded 50% of the mixture ratio. Where a tree species other than

the four focal species was dominant, or where (e.g. in mixed species stands) no single species
exceeded 50% of the mixture ratio, forests were assigned to the “other” category. The four focal
forest categories encompass the most common forest types in the boreal and temperate zones of
Europe (comp. EEA 2006, pp. 28, forest type categories 1-8), and represent different ranges
along the disturbance continuum. Our study compared human and natural disturbances both in
aggregate for all studied forests continent-wide, and individually within each of the four focal
forest category, quantitatively for the former and qualitatively for the latter.
2.2 Compiling the dataset
2.2.1 National forest management data
To assess European forest management practices, we selected 13 target countries, representing
boreal and temperate ecoregions in Europe (Fig 1), and asked forest experts of each country to
complete a standardized questionnaire (Appendix S1). The questionnaire (Q) addressed four
groups of questions which concerned: 1) silvicultural systems used in a given country; 2) the
ratio and land area under different silvicultural systems as well as forests with no management or
managed primarily for non-timber objectives (“non-timber and unmanaged” henceforward); 3)
the area and proportion of the four forest categories and their typical management methods; and
4) harvest size, rotation period, and residual structure (live tree retention) for these silvicultural
systems.
Our classification of silvicultural systems encompasses four main categories of forest
management (Table 1): A) even-aged forest management methods, such as uniform shelterwood
and uniform clearcutting systems; B) uneven-aged (continuous cover) and multi-aged forest
management methods, represented by a variety of selection and irregular shelterwood systems

(see Raymond et al. 2009); C) regular coppice and coppice with standards; and D) no
management or management primarily for non-timber objectives (i.e. EU MCPFE categories 1.1,
1.2, 1.3, see Parviainen and Frank 2006).
The survey excluded “other wooded lands” (see definition in FAO 2000) and non-productive
forests (defined as annual increment < 1 m3/ha/yr). Short-rotation systems with final felling at
stand ages of 40 years or less, usually intensively managed plantations, are considered as forests
in some of the investigated countries (France, Slovakia, Hungary, Latvia), but not so in others
(Austria, Italy), where they are instead classified as agroforestry, and thus were excluded from
the analysis. For consistency, we harmonized the silvicultural terminology across country-
specific data. The area and area proportion of the four forest categories dominated by the
selected four tree species, and their typical management methods were also assessed by the
questionnaire. Forests not covered by these four categories were assigned to an “other” category.
The intervention sizes for the different silvicultural systems were defined as the area of the final
harvest in the case of shelterwood-, clearcutting-, and coppice systems (Cat. A1, A2, C1, C2, see
Table 1 for categories). Intervention size in the case of uneven-aged systems (Cat. B) was
defined as the size of the canopy openings created by the intervention of the single-tree-, group-
or multicohort selection system. This was necessary to compare forestry practices with their
natural analogues.
Harvest frequency was based on rotation period in the case of even-aged (Cat. A) and coppice
forest management systems (Cat. C), and with entry cycles for uneven-aged systems (Cat. B).
Residual structure (i.e. survivorship or retention) was defined as the percentage of living woody
biomass volume (m3) post-harvest compared to the pre-harvest volume left on a 1 ha site after
the final cutting operation for even-aged management systems (clearcutting system, shelterwood

system), or after the regular entry period (uneven-aged forestry). Intermediate treatments, such as
thinnings, were not considered in the determination of harvest frequency and residual structure.
Multiple data sources were used by the national experts to complete the questionnaire. Sources
included national forest inventories, national silvicultural guidelines, ministry reports, data
archived by national research institutes, scientific papers, state forest service statistics, original
datasets maintained by survey participants, and expert opinion (see Appendix S2).
2.2.2 Natural disturbance attributes of European forests
Our analysis was based on variables describing the spatial extent, frequency, and residual
structure (inverse of severity) of natural disturbance events in Europe. We compiled data from,
(i) long-term studies of primary and old-growth forests (see Sabatini et al. 2018 for definitions),
(ii) dendrochronological studies, and (iii) other studies defining the ranges of variability in
disturbance dynamics for the four forest categories (Appendix S3, Table 2). To define the
attributes of natural disturbances at landscape scale, the experts used information from studies
investigating many of the largest and most intact old-growth forests remaining in Europe,
including Perućica forest reserve in Bosnia-Hercegovina (Nagel et al. 2014), primary forests in
northern Finland (Aakala 2018), unmanaged boreal forests in Fennoskandinavia including
Russian Karelia (Kuuluvainen and Aakala 2011), old-growth forests of the Carpathians (Čada et
al. 2020, Frankovič et al. 2021), the Parangalitsa Reserve in Bulgaria (Panayotov et al. 2011),
and forest reserves in the European Russia (Aakala et al. 2011, Ryzhkova et al. 2020).
Based on the classification of Kuuluvainen and Aakala (2011), we grouped natural disturbance
types into four categories; 1) high-severity disturbances, like major windstorms or forest fires, 2)
intermediate severity disturbances that result in a partial removal of canopy, like microbursts, ice

storms, and moderate bark beetle outbreaks, 3) low severity disturbances that result in spatially
diffuse mortality, like low severity fires, windstorms, ice storms, mild bark beetle outbreaks and
4) low severity disturbances that result in aggregated tree mortality, such as “gap dynamics”
driven by tree mortality at fine scales of small groups of trees or a single large tree (< 200 m2).
Finally, ranges for size, frequency, and severity parameters were attributed to these categories on
the basis of the literature review (Appendix S3). This compilation of the European disturbance
literature was then used to estimate the dimensions of the four disturbance types.
2.3 Data Analysis
We compared boreal and temperate natural forest disturbances in Europe with the silvicultural
systems applied in the 13 target countries. First, we calculated ratios and areas by forest biome
(temperate and boreal) and by forest category for the silvicultural systems presented in Table 1
from the raw database of national data (Data S1: [Forest Management Database] in Aszalós
2021). Three countries represented the boreal zone: Sweden, Finland, and Latvia. Though Latvia
belongs to the transitional hemiboreal zone (Ahti et al. 1968), it was classified as a boreal
country in this study on the basis of forest type and management similarities.
Second, we designed a 3D figure for visualization purposes, and populated it with the data
obtained from our forest management survey and natural disturbance literature review. The
figure’s three axes compare the three variables disturbance size, frequency, and residual
structure. For each silvicultural system, we obtained country-level averages of the given
silvicultural system. Then, we visualized the volume (within the 3D figure) of natural
disturbance types and silvicultural systems by drawing ellipsoids with the outer bounds
concurring with the data ranges. To facilitate the derivation and interpretation of the CI, we used

the same approach to populate three 2D figures presenting size and frequency, size and residual
structure, and frequency and residual structure (sensu Seymour et al. 2002). The 3D and 2D
figures were visualized in R (R Core Team 2020) using the rgl (Murdoch 2020) and the car
packages (Fox et al. 2012), respectively (Data S2: [R_Code.r], [management_data.cvs] in
Aszalós 2021).
We obtained the Comparability Line (CL) by fitting a linear regression through the centroids of
the four natural disturbance types. Subsequently, we derived the relative distance (i.e., the CI) of
each disturbance attribute for each silvicultural system comparing the centroids of silvicultural
systems with the CL. For example, a CI of 0.2 indicates a 20% similarity between a silvicultural
system attribute and a natural disturbance attribute (e.g., harvest and disturbance size). In total,
this approach resulted in six comparisons: size relative to frequency, size relative to residual
structure, frequency relative to size, frequency relative to residual structure, residual structure
relative to size, and residual structure relative to frequency. The average through all six
comparability indices constitutes the overall difference of a silvicultural system from the natural
disturbance regime.
3. RESULTS
3.1 Silvicultural systems used in European forests and in the four focal forest
categories
The total forest cover of the 13 target countries without the Mediterranean forests and short-
rotation systems is approximately 109 million hectares (1 hectare area is equal to 10.000 m2), see
Fig. 2. According to the national forest management data we examined (Data S1: [Forest
Management Database] in Aszalós 2021), the forested area of the three boreal countries

(Sweden, Finland and Latvia) accounts for 44% of this total, and the 10 temperate countries
encompass the remaining 56%.
Our results show that use of silvicultural systems in Europe is skewed disproportionately towards
even-aged systems. Even-aged silvicultural systems (Cat. A, see Table 1 for categories)
dominate (72.9%) across all the target countries (Fig. 2). More than half of the investigated
forests are managed by uniform clearcutting systems (51.9%, Cat. A2), and approximately 21%
by uniform shelterwood systems (Cat. A1). Uneven-aged systems, by comparison, are employed
to a far lesser degree. In our dataset 9.7% of forests are managed using uneven-aged systems
(Cat. B), whereas coppice systems (Cat. C) are applied to 9.1% of forests. Only 8.3% of the
forest included within the scope of our study is unmanaged or managed primarily for non-timber
objectives (Cat. D), such as management for biodiversity (Fig. 2, Appendix S4).
There is a marked difference between boreal and temperate countries (Fig 2, Appendix S5).
Clearcutting systems (Cat. A2) are employed across 86.7% of forests in the boreal zone, which
are predominantly coniferous. For the three boreal countries included in our dataset (Finland,
Latvia, and Sweden), all other management methods represent minor components. Uneven-aged
management is applied on only 4.2% of forests, whereas 8.7% belong to the non-timber and
unmanaged category in the boreal zone. In contrast, in the temperate zone shelterwood (Cat. A1),
uneven-aged (Cat. B), and coppice systems (Cat. C) are applied over larger proportions of the
forest area, i.e. 37.4%, 14.1%, and 16.4% of all forests, respectively (Fig. 2, Appendix S4).
Within the temperate biome, however, dominant silvicultural systems vary by country. For
example, coppice and uneven-aged systems are more prevalent in France and Italy; shelterwood
systems are more common in Slovakia and Romania. Finally, in Czech Republic, Germany,
Poland, Austria, and Hungary, clearcutting and/or uniform shelterwood systems are more widely

represented. The majority of Slovenian forests are managed by irregular shelterwood systems
(Appendix S5).
In Norway spruce and Scots pine dominated forests, the primary management system is even-
aged with clearcutting system, applied to 68.9% and 78.1% of the area of all 13 countries
respectively (Table 2). Less than one fifth of these two focal forest categories is managed by
uniform shelterwood systems across all of the 13 target countries. In temperate Norway spruce
dominated stands, even-aged methods have the highest representation (75.3%), but uneven-aged
methods, such as single-tree and group selection, are also common (24.7%) (Table 2). The
majority of European beech and oak dominated forests are managed with uniform shelterwood
systems (67.7% and 48.9% respectively), indicating that natural regeneration (advanced
regeneration) and subsequent release through overstory removal are the typical silvicultural
techniques applied to these forest categories. Beech dominated forests have a fairly high ratio of
uneven-aged management for all the 13 counties in the temperate forest countries, nearly 20% of
beech forests in our dataset are managed with selection methods on both scales. One-third of
temperate oak dominated forests are managed with a variety of coppice systems (Table 2,
Appendix S6).
3.2 Characteristics of natural disturbances in European forests
The literature review revealed that disturbance sizes, frequencies and severities in European
temperate and boreal forests are highly variable across space and time (Table 3). Small,
aggregated canopy openings, where gap size usually does not exceed 200 m2 (Mountford 2001,
Kuuluvainen and Aakala 2011) are common throughout the region, typically removing less than
20% of the canopy (Nagel et al. 2014, Hobi et al. 2015). Individual low severity diffuse

disturbances affect larger spatial extents, such as the low severity fires typical in boreal Scots
pine forests and low severity ice storms in temperate Europe (Angelstam and Kuuluvainen 2004,
Kenderes et al. 2007, Kuuluvainen and Aakala 2011). In such events, the total area of scattered
canopy openings, tree mortality, and tree damage for an event may range from 200 m2 to 100 ha
even if locally the proportion of canopy disturbed remains low. Rotation periods for low severity,
diffuse disturbances can be relatively short, often ranging between 10-100 years (Sannikov and
Goldammer 1996). Intermediate severity wind and ice storms, having rotation periods of
approximately 100-500 years (Nagel et al. 2014, 2017a), generate a diverse mosaic with 25-75%
canopy loss (Nagel et al. 2014, Čada et al. 2020) suggesting a very broad range of variability.
Disturbance patches resulting from intermediate severity disturbances are irregularly structured
(i.e. often having variable residual tree survivorship densities and patterns) and range in size
from 200 m2 up to 100 ha (Kuuluvainen and Aakala 2011, Kameniar et al. 2021, Frankovič et al.
2021). High severity events are rare, returning at intervals usually of more than 300-500 years
(Aakala 2018, Nagel et al. 2014). However, severe disturbances in mountain ecosystems, like in
the conifer forests of the Carpathians, can have rotation periods as short as 174 years (Čada et al.
2016). The size of such disturbance areas varies widely, ranging from 1 to 1000 ha (Kuuluvainen
and Aakala 2011).
3.3 Congruence of silvicultural systems with natural disturbances
Silvicultural systems differed clearly from natural disturbances with regard to the evaluated
attributes; size, frequency, and residual structure (Table 4, Table 5, Fig. 3, Fig. 4 Fig. 5). With an
average CI of 0.07 (7% congruence), clearcutting and uniform shelterwood systems had the
lowest congruence with natural disturbances, followed by coppice systems (on average 13 %).

Uneven-aged systems were most similar to natural disturbances (on average 53 %) among all
silvicultural systems investigated.
Altogether, silvicultural systems occupied a much smaller portion of the 3D attribute space than
natural disturbances, indicating a much lower variability (Fig. 3). High and intermediate severity
disturbances had a particularly high volume, followed by diffuse low severity disturbance. Only
the volume of aggregated low severity disturbances occupied a 3D space similarly small as each
individual silvicultural system.
Ellipsoids – representing the attribute space occupied by a given disturbance type or silvicultural
system relative to the three axes – for clearcutting and uniform shelterwood systems had large
overlapping zones (Fig 3, Fig. 4 a,b,c). The mean harvest sizes of these systems (2.8, 3.7 ha
respectively, Table 4, Fig. 5) were intermediate between the mean size of low severity
aggregated and diffuse natural disturbances, however their rotation periods were shorter (100
years).
The 2D plots added more detail to the relationship between natural disturbance and silvicultural
systems (Fig. 4). The size-frequency plot (Fig. 4 a) showed an overlap of the ellipsoids of
uneven-aged systems and low severity aggregated disturbance, indicating that uneven-aged
systems are partly within the range of low severity aggregated disturbance. Coppice systems,
and, to some degree even-aged silviculture systems, overlapped with low severity diffuse
disturbance (Fig. 4 A). We found the highest congruence between uneven-aged forestry and
natural disturbance for size relative to frequency, and frequency relative to size with CIs of 0.5
and 0.79 (i.e., 50% and 79%, respectively, see Table 5). Congruence values of other silvicultural
systems ranged from 0.1 to 0.4 with natural disturbance. Lowest CI values (i.e., the largest
divergence) were detected for frequency relative to residual structure and size relative to residual

structure (Table 5, Fig 4 b, c). In particular, CI values for even-aged and coppice systems were
only 0.01 or smaller. Further, these silvicultural systems diverged strongly from natural
disturbance comparing residual structure relative to size and residual structure relative to
frequency (Fig 4 b, c) with CIs of 0.03 and 0.06, respectively. In contrast, with CIs of 0.7-0.8
uneven-aged systems were considerably more similar to natural disturbances in the same
pairwise comparisons.
The even-aged management systems overlapped with coppice systems in terms of size relative to
residual structure. Ellipsoids of uneven-aged systems were detached from the three other
silvicultural systems on each plot, but were often close to, or overlapping with, low severity
aggregated natural disturbances (Fig. 3, Fig. 4 A, B, C).
4. DISCUSSION
4.1 Significance of the residual structure axis
Based on our findings, the majority of European forests are managed outside the range of their
respective natural disturbance regimes, showing low congruence with past and present natural
disturbances. For more than two centuries, European foresters have controlled tree mortality
processes, growth and yield, and stand health based on a well-developed science. In this school
of thought, management was focused on excluding natural disturbances and producing
predictable outcomes. Acknowledging this tradition, we propose that there is an opportunity to
expand Europe’s portfolio of management options to diversify habitats, seral patch mosaics, and
service provisioning. While previous studies have described natural disturbance regimes
according to their size, frequency, and severity ranges (Turner et al. 1998, Bergeron et al 2002),
this study is among the first to populate this framework with field-based data for forest

management and literature derived data for natural disturbances. The expanded framework
employed in our study defines the critical third axis, residual structure, expressed as the
proportion residual canopy structure (i.e. tree survivorship) left on a site following harvest or
disturbance. Adding this third axis to the forest disturbance conceptual model significantly
improved the basis for comparison and proved critical in understanding incongruences with
forest management. Silvicultural systems in Europe typically retain very low densities of diverse
biological legacies, such as residual live, dead, and downed trees, either dispersed or aggregated
(Paillet et al. 2015, Vítková et al. 2018). This is generally true for the selection systems as well –
deadwood and old, large living trees are removed (Keren and Diaci 2018). Our model
incorporated only residual living trees – but even this resulted in high divergence from natural
dynamics.
The Comparability Index (CI) was initially proposed by Seymour et al. (2002) as a useful
benchmark for what they and others (e.g. Franklin et al. 2007) termed “natural disturbance-based
silviculture”. Using the CI, Seymour et al. (2002) postulated that a Picea spp. plantation
managed on harvest rotations of 50 years and using 20-ha clearcuts would be outside the range of
variability for natural disturbances. And thus, in scenarios such as this one, cumulative
ecological impacts over multiple rotations and at landscape scales are unlikely to be analogous to
natural disturbance effects. Our findings show that forest management effects in Europe partly
overlap with the range of variability of low intensity diffuse disturbances on the frequency-size
attribute space. However, relative to residual structure (the third axis) there is a large divergence,
as low intensity diffuse disturbances usually result in only 10-25% mortality of the tree canopy.
North and Keeton (2008) modified Seymour et al.’s (2002) model by adding a hypothesized
intermediate disturbance regime and suggested a third evaluation criterion, which is the amount

or density of “biological legacies”. Our study has applied and further developed the CI index –
populated with data spanning the full range of natural disturbances in Europe, including
intermediate disturbances. We calculated the overall congruence of silvicultural systems and
natural disturbances relative to all three attribute dimensions, using the CL through the European
forest disturbance regimes as reference line. Using the expanded index, forest managers can
determine the congruence/divergence of a given harvesting regime relative to natural disturbance
dynamics.
4.2 Uneven-aged silvicultural systems are the closest to Comparability Line of natural
disturbances
The vast majority of the 109 million ha of temperate and boreal forests included in this study are
managed under even-aged systems, having only 7% congruence with natural disturbances on
average. Uneven-aged systems had the highest CI values, with 53% similarity to natural
disturbances, but this silvicultural system constitutes only approximately 10% of all human
management of the investigated forest land. Looking at the big picture the 3-dimensional
ellipsoid for uneven-aged forest systems occupied an attribute space close to the ellipsoids for
natural disturbances, whereas the three other silvicultural systems were located well outside the
range of natural disturbances. Clearcutting and uniform shelterwood systems had the lowest CI
in almost all comparisons, coppice systems were intermediate, and uneven-aged systems had the
highest CI values in all paired comparisons. Using only axes for size and frequency, and
disregarding structural complexity, the similarity of even-aged and coppice systems with natural
disturbances was markedly higher. Management systems using 50-100 years rotations and few
hectare harvest blocks have overlapping size and frequency attributes as compared to low

severity diffuse and intermediate severity disturbances. However, these natural disturbances
always have much higher residual structure (25-90%) than management systems leaving only a
few residual trees. On the other hand, high severity disturbances can exhibit low residual
structure (0-25% canopy survivorship) similar to even-aged and coppice systems. Still, the
frequency of high severity natural disturbances is smaller by one order of magnitude than that of
the rotation of silvicultural practices. Consequently, both size and frequency attributes for
clearcutting, shelterwood, and coppice systems exhibited large departure with the residual
structure axis included, with CI values dropping to only 0.01 or less congruence with natural
disturbances.
This analysis clearly shows that Europe’s natural disturbances have great complexity and
variability across the multiple dimensions of spatial extent, frequency, and severity leading to
variation in structural complexity. By contrast, management in most European forests
perpetuates a landscape-scale condition incorporating little of this diversity (Angelstam 1996).
Although uneven-aged forestry showed the highest congruence with natural disturbances on the
basis of the three observed attributes, it does not emulate or fully encompass the great
complexity of all natural disturbance effects. For example, where a disturbance regime of a forest
type is characterized by intermediate and/or high severity disturbances, multi-cohort and/or
variable retention systems would more closely emulate disturbance effects (Meigs and Keeton
2018; Kameniar et al. 2021), than uneven-aged systems using single tree or group selection
methods. Other important features of forests with natural dynamics are also often missing in
intensively managed uneven-aged forest stands – such as biological legacies or irregular
structure within silvicultural gaps, presence of large, older trees, and diverse types, sizes and
decay-stages of deadwood, both standing and downed (Keren and Diaci 2018).

4.3 Congruence of natural disturbance and management of the four focal forest
categories
Interest in natural dynamics silviculture has taken root in many regions globally as foresters seek
management alternatives that better integrate biodiversity and non-timber objectives. Similarly,
in Europe the merits of intensive forest management, such as high yield, even-aged forestry
practices, have been the subject of debate (Bollmann and Braunisch 2013; Schulze et al. 2014).
Points of contention include tradeoffs among economic efficiency, hydrologic regulation, abiotic
disturbance risks, susceptibility to insects and pathogens, carbon uptake and storage, and habitat
provisioning (Mikoláš et al. 2014, Burrascano et al. 2016). In this context, comparison with
natural disturbance analogues is particularly informative, for instance in developing forest
management approaches that integrate competing objectives (Franklin et al. 2018; Schall et al.
2020). Knoke et al. (2020) showed that continuous cover forest management also can be an
effective strategy for meeting economic objectives, for example if risk-avoidance is an important
strategic consideration.
We found that even-aged management with clearcut regeneration harvesting is the most
prevalent system in the boreal zone of Europe, yet resulted in very low congruence with natural
dynamics. Primary or unmanaged boreal Norway spruce forests are dominated by finely-scaled,
low severity aggregated gap openings, together with less frequent intermediate severity
disturbance events (Caron et al. 2009, Aakala et al. 2009, Szewczyk et al. 2011, Aakala et al.
2011, Khakimulina et al. 2016). Boreal Scots pine stands also experience mixed-severity fire
disturbances, leaving irregular age-class structures and high amounts of deadwood in variably
distributed spatial patterns (Niklasson and Granström 2000, Wallenius et al. 2010b, Aakala 2018,

Ryzhkova et al. 2020). Natural disturbance effects contrast starkly with the clear-felling regime
most commonly practiced in boreal pine and spruce dominated forest types. Clear-felling results
in mosaics of 2-10 hectare stands that are predominately even-aged at the patch scale, harvested
on 60-90 year rotations, and have extremely low volumes and densities of post-harvest residual
structure (i.e. biological legacies) (Angelstam and Manton 2021).
The temperate zone of Europe has a more diverse portfolio of harvest regimes, and consequently
the congruence with natural disturbances greatly varies among both countries and forest types.
Forests dominated by Scots pine, of which more than half are in Poland, are predominantly
managed by clearcutting systems. Regional studies from the Carpathians, Rila Mountains
(Bulgaria), and Bohemia (Czech Republic) suggest that mixed-severity disturbance regimes with
wide variation of low to high disturbance severities historically operated in temperate mountain
spruce forests (Panayotov et al. 2011, Szewczyk et al. 2011, Svoboda et al. 2014, Trotsiuk et al.
2014, Čada et al. 2016, Janda et al. 2017, Frankovič et al. 2021). We showed that this variability
is not emulated by contemporary forest management. Nevertheless, in this study, almost 25% of
temperate Norway spruce dominated stands are managed by uneven-aged systems, which
suggests that the management of this forest category has the largest congruence with natural
disturbances among the four forest categories we evaluated. On the other hand, Norway spruce
has been planted widely outside its natural distribution in temperate Europe (Spiecker 2003,
Caudullo et al. 2016). These stands are highly susceptible to windthrow and bark beetle
outbreaks, which are significantly amplified by climate change. Foresters have responded by
salvaging or “sanitary cutting” thousands of hectares of beetle or wind disturbed forests in recent
decades (Schelhaas et al. 2003, Thom et al. 2013, Seidl et al. 2014, Hlásny et al. 2019), although
this is not always profitable (Knoke et al. 2021).

Beech dominated forests are usually managed with uniform shelterwood systems, but on 20%
uneven-aged silviculture is applied, thus emulating more closely the pattern created by the low
severity aggregated disturbances (gap dynamics) associated with naturally dynamic beech forests
(Emborg et al. 2000, Standovár and Kenderes 2003, Piovesan et al. 2005, Kral et al. 2014,
Frankovič et al. 2021). However, intermediate and mixed severity disturbances are also common
in beech-dominated forests (Splechtna et al. 2005, Nagel et al. 2014, 2017a; Frankovič et al.
2021), and these are not well emulated by contemporary harvesting systems in Europe. Natural
dynamics of oak forests in Europe are difficult to separate from anthropogenic influences, as the
latter have shaped the oak-zone landscapes since pre-historic times (Vera 2000, Bobiec et al.
2018, 2019).
Lacking robust natural reference stands and landscapes, researchers have only a limited
understanding of natural regeneration and stand dynamics in European oak forests (Kohler et al.
2020). Light demanding oak species (Quercus pubescens, Q. robur, Q. petrea) require open
habitats resulting from poor site productivity or strong human/natural disturbances that enhance
natural regeneration (“oakspace”, see Bobiec et al. 2018, 2019). In contrast to their natural
regeneration strategy, much of the contemporary oak management employs closed coppice and
high forest (originated from seed or planted seedlings) systems which have very low congruence
with natural dynamics for this forest type.
4.4 Natural dynamics silviculture
The comparative framework and index presented in this paper are intended as a tool to encourage
development of multifunctional landscapes by applying “natural dynamics silviculture”,
complemented by a variety of retention forestry approaches (see, for example, Mori and

Kitagawa 2014; Puettmann et al. 2015, Gustafsson et al. 2020). Interest in ecologically-oriented
forest management has increased dramatically in recent decades both in North America and in
Europe (Angelstam 1998, Bengtsson et al. 2000, Kuuluvainen 2002, Franklin et al. 2002,
Lindenmayer et al. 2006, Bauhus et al. 2009, Krumm et al. 2020; Čada et al. 2020, Kuuluvainen
et al. 2021), but there are key differences. In North America, ecological forest management
increasingly looks to baselines provided by primary (i.e. never cleared by humans) forests,
comparing forest dynamics driven by natural disturbances (e.g. wind, fire, insects, floods) with
the impacts of different forest harvesting approaches (Franklin et al. 2002, Keeton 2007, Fahey
et al. 2018, Keeton et al. 2018, Thom and Keeton 2019). In Europe interest in ecological forestry
is also high (e.g. Bauhus et al. 2009, Pretzsch et al. 2017), but the common European
approaches, variably termed “close-to-nature,” “Plenterwald”, or “Pro Silva” are quite different,
being primarily modifications of conventional selection systems (Johann 2006, Brang et al.
2014). They are used for either conversion cutting in spruce plantations – promoting replacement
by native mixed species or deciduous forest types – or as uneven-aged management (e.g. the
“Plenterwald” and “Dauerwald” systems) in European beech and Silver fir-European beech
forests, and other temperate deciduous or mixed species forest types. Close-to-nature silviculture,
as commonly practiced, only partially replicates natural disturbance effects (Diaci 2006, Schütz
et al. 2016) by providing a mosaic of structurally variable patches as well as tree age class
diversity at the aggregate or stand scale. However, it rarely maintains irregular age-class
structure or retention trees within patches and often neglects the dead wood (both standing and
downed) component of structural complexity, despite its inevitable importance in biodiversity
maintenance (Gossner et al. 2013, Larrieu et al. 2014, Roth et al. 2019). In parts of Central
Europe deliberate efforts have been made to emulate consequences of natural processes observed

in old-growth stands (Kraus and Krumm 2013, Schütz et al. 2016, Roth et al. 2019), such as
retention of downed woody debris, habitat trees and other structures (Johann 2006). For example,
research in old-growth forest reserves has supported the development of flexible irregular
shelterwood system in Slovenia, by defining unique combinations of forest sites, stands, and
social environments (see Diaci 2006, Boncina 2011). In the boreal forests, experimental work
has been initiated to assess the feasibility and benefits of natural dynamics silviculture, including
explicit dead wood goals (Koivula et al. 2014).The potential to incorporate a broader range of
dynamics and structures – including old and habitat or “veteran” trees, standing deadwood, and
downed trees, based on research on natural disturbance effects – is true both for European even-
aged and continuous cover forest management (Pommerening and Murphy 2004, Kern et al.
2017, Nagel et al. 2017b).
Simplification and homogenization of European forests, for example through the widespread
planting of mono-specific Picea abies plantations across formerly diverse landscapes and on
former beech and other tree sites and through the coppicing system in the Mediterranean forests,
is a well-documented phenomenon (Angelstam 1998, Björse and Bradshaw 1998, Tērauds et al.
2011, Keeton et al. 2013). This practice, implemented over centuries, has contributed to the high
susceptibility of some European forests to spruce bark beetle (Ips typographus) outbreaks
(Hlásny et al. 2021) as well as forest dieback associated with fungal pathogens, such as root rots
(e.g. Armillaria sp., Heterobasidion parviporum, H. annosum, see Peri et al. 1990, Arhipova et
al. 2011). Also as a result of homogenization and bias toward mature cohorts, European forests
may be more vulnerable to increased disturbance intensity and frequency associated with climate
change (Långström et al 2009, Seidl et al. 2014), leading to interest in management to restore
greater heterogeneity in forest composition at landscape scales (Angelstam and Kuuluvainen

2004). Improved understanding of baseline disturbance dynamics – from both studies of
reference stands as well as dendrochronological reconstructions – could guide this endeavor
(Bauhus et al. 2009, Paillet et al. 2010; Čada et al 2020).
4.5 Limitation and perspectives of the study
Human presence and influence on forest ecosystems has been continuous since the last ice age,
and became decisive from the Neolithic period onwards (i.e. -6000 y) in Europe (Angelstam et
al. 2021). Hence the structure, composition, and natural dynamics of European forests have been
fundamentally altered across millennia (Kaplan et al. 2009). This particularly concerns certain
forest types, like oak dominated forests at lower elevations. Other forest types survived in a
limited number of primary forest stands and landscapes, often in places with low accessibility
(Sabatini et al. 2018). These remnants provided only limited capacity to reconstruct historical
ranges of variability, particularly for landscape-scale processes. Consequently, reconstructing or
inferring baseline disturbance dynamics is fraught with uncertainty, though dendrochronological
approaches (Aakala et al. 2011, Svoboda et al. 2012, Nagel et al. 2014, Schurman et al. 2018,
Čada et al. 2020; Frankovič et al. 2021) and retrospective modeling are proving increasingly
robust. The CI presented here must be applied within this context, acknowledging human
influences on our estimation of natural disturbance regime characteristics.
Disturbance regimes are changing rapidly (White and Jentsch 2001, Turner 2010). Recent studies
indicate a significant increase in disturbance rates across Europe’s natural and managed forests
(Schelhaas et al., 2003, Seidl et al. 2014). However, it remains unknown how they will change
exactly in the future and how they will be affected by climate change. The strong yet complex
linkage between natural and human processes are already shaping the forested landscapes of

Europe (Senf and Seidl 2020), making the separation of human and natural dynamics very
challenging.
Further research could strengthen the CI by incorporating information (by forest type and local
content) on the amount and quality of deadwood, density of large trees, density and diversity of
tree-related microhabitats on habitat trees, intensity of the given management method, proportion
of admixing species, and use of natural or artificial regeneration. For example, while uneven-
aged systems had the highest CI values on the basis of the three observed attributes, addition of
dead wood and large tree attributes, specifically, might lower these values, as retention of these
structure is not commonly practiced in Europe.
This framework must acknowledge the alteration of disturbance regimes caused by centuries of
human influence as well as shifting boundary conditions associated with climate change (Seidl et
al. 2014, Kulakowski et al. 2017, Thom et al. 2017, Senf and Seidl 2020). It must also consider
the broad range of forest management approaches and harvesting intensities in Europe, varying
by region, forest type, ownership and subsidy programs, local conditions and accessibility,
importance of non-timber services, and other factors (Schelhaas et al. 2018). Application of
portfolios of diversified forest management approaches need to be considered across tree, stand,
and landscape scales, and be adapted to differing forest ownerships (Lazdinis et al. 2019,
Angelstam et al. 2020). Consideration of these factors can help forest practitioners to down-scale
and operationalize the comparability framework we propose.
4.6. Management implications
We present this conceptual model to help inform forest management practices designed to more
closely emulate natural disturbance effects, and in so doing provide a broader range of

ecosystem goods, services, and habitats compared to conventional practices (Mönkkönen et al.
2014, Eyvindson et al. 2018, Huuskonen et al. 2021). The CL and CI, which helps to compare
natural and human disturbances, highlights the importance of understanding the three main
attributes of disturbances: size, frequency, and severity. These must be considered jointly, both
for understanding natural disturbance baselines and for developing and testing ecologically-
based, sustainable forest management practices in Europe. With downscaling to incorporate
information on more proximate disturbance effects and habitat relationships (e.g. key elements of
stand structure and patch configuration emulated through retention forestry), the CI provides a
useful tool for planning and assessing biodiversity outcomes in managed forests, complementing
other approaches (see, for example, Thom and Keeton 2020, Mikoláš et al. 2021).
Natural disturbances create a much broader range of variability for all three attributes as
compared to human disturbances. Forest practitioners could approximate the Comparability Line
at any point of the continuum represented by the ranges of variability for the three attributes.
However, to apply the entire range of disturbance processes to a landscape heavily altered by
millennia of land-use history will be challenging. For example, intermediate and mixed-severity
disturbances play a formative structuring role in many European forest types (Svoboda et al.
2014, Trotsiuk et al. 2014, Khakimulina et al. 2016, Nagel et al. 2017a, Aakala 2018, Čada et al.
2020). The emulation of intermediate and mixed-severity disturbances, with broad range of age
classes and high level of biological legacy will require a fundamental change in forest practices.
Advances in multi-cohort and retention silvicultural practices in North America, shifting away
from even-aged management and derived from efforts to emulate natural disturbance regimes,
may prove informative in this regard (Harvey et al. 2002, North and Keeton 2008, Long 2009).
The forestry community’s perceptions of the role of natural disturbances are also vital (Nagel et

al. 2017b). Foresters will need to feel comfortable emulating certain aspects of natural
disturbance effects, such as deliberately creating (or retaining following natural disturbances)
variability in residual structure, both live and dead, without defaulting always to sanitary cutting
(Diaci et al. 2017). In the case of coarse-scaled interventions (larger than 10 ha), the rarely used
irregular shelterwood method and retention forestry systems would have much higher similarity
to intermediate severity disturbances. Irregular shelterwood systems keep relatively high residual
structures after the interventions, but their use is extremely low in European silviculture as a
proportion (< 3%) of overall management based on our data (Data S1: [Forest Management
Database] in Aszalós 2021). Instead of changing the predominant even-aged management regime
to just one type of silviculture, we and others recommend broader diversification of
management regimes (Schall et al. 2018, Nolet et al. 2018), adapted to both ecological and social
systems (Angelstam et al. 2020). A combination of uneven-aged selection and irregular
shelterwood systems with even-aged clearcutting and uniform shelterwood system – with high
level of remaining biological legacies – could promote landscape-scale diversity of seral stages,
stand structures and biodiversity (see Mönkkönen et al. 2014, Schall et al. 2018).
Natural dynamics silviculture must incorporate deadwood management and tree retention
(including large and habitat trees) to decrease the divergence from natural disturbances by
increasing the amount and type of biological legacies (Larrieu et al. 2014, Krumm et al. 2020).
Compared to naturally dynamic forests the amount of deadwood is low in European forests
(Guby and Dobbertin 1996, Lombardi et al. 2008, Bölöni et al. 2017, Vítková et al. 2018, Puletti
et al. 2019). According to the national reported values, total deadwood ranges between 2.3 and
28 m3/ha (Forest Europe, 2020), and the mean for the EU countries is 16 m3/ha (Puletti et al.
2019), much lower than the recommended threshold values (see Müller and Bütler 2010).

However, effective deadwood management should not only increase the amount and size, but
also manipulate the position, arrangement, and decay stages of retained trees (Vítková et al.
2018), since deadwood diversity is pivotal for many taxa (see e.g. Ódor et al. 2006, Fritz et al.
2008, Gossner et al. 2013, Bouget et al. 2013). As climate change intensifies bark beetle
outbreaks, deadwood management, tree retention, and disturbance-based forestry should be
harmonized with bark beetle management strategies in forests most susceptible to bark beetles
(Hlásny et al. 2019, Hlásny et al. 2021).
ACKNOWLEDGMENTS
This research and related multilateral scientific exchanges were supported by grants from the
Trust for Mutual Understanding (W.S. Keeton, P.I.), the USDA McIntire-Stennis Forest
Research Program (W.S Keeton, P.I.), and EU founded LIFE project (LIFE 4 Oak Forests, R.
Aszalós, P.I.). The authors are grateful to the United States Department of State, Fulbright
Scholars Program, for funding the bi-lateral exchanges of the lead authors (R. Aszalós and W.S.
Keeton) that led directly to development of this paper.
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Table 1. Classification and the definition of the silvicultural systems
Category
Silvicultural system
Definition
A
Even-aged silvicultural
systems
Even-aged management
A1
Even-aged forest
management with
uniform shelterwood
system
Regeneration is usually natural. Interventions are
intermediate thinnings and subsequent cuttings. New
seedlings are established before the mature trees are fully
removed. Final cut after a certain target diameter or age has
been reached. The size of the final cut is usually between 0.5
ha and 10 ha.
A2
Uniform clearcutting
system (rotation time is >
40 years)
Regeneration is usually artificial (planted). Interventions are
intermediate thinnings. Clearcut after a certain target
diameter or age has been reached. The size of the clearcut is
usually between 0.5 ha and 10 ha.
B
Uneven-aged silvicultural
systems (continuous
cover forestry)
Selection cutting based usually on target diameter
distribution. Predominantly trees of large dimensions are cut
B1
Single tree selection
Scattered individual trees of multiple age classes are
harvested
B2
Group selection
Small to medium sized openings created by the removal of
several adjacent trees, gap size is typically under 0.3 ha
B3
Multi-cohort (irregular
shelterwood) system
Multi-aged forestry, permanent retention with ≥10% basal
area
C1
Coppice systems
Woodlands regenerated asexually from stump sprouts on
harvested crop trees
C2
Coppice with standards
systems
Two distinct elements: a lower storey treated as coppice; and
an upper storey of scattered older tree individuals (standards)
treated as high forest
D
Non-timber and
unmanaged forests
No forest management, or management primarily for non-
timber objectives, such as protection forest (against erosion,
avalanche, etc.), conservation-oriented management,
management for biodiversity, non-productive forests, forests
with no defined rotation time, abandoned forests, set-asides.

Table 2. Forested area or proportion by forest categories (as represented by dominant species)
and silvicultural system.
Forested area or
silvicultural system
Norway
spruce
Scots pine
European
beech
Oak species
Combined
totals
Forested area (hectares)
Area
24 994 098
33 494 125
8 615 899
11 003 675
78 107 797
Boreal
15 083 066
23 539 760
151 800
9 355
38 783 981
Temperate
9 911 032
9 954 365
8 464 099
10 994 320
39 323 816
Percent
A1 Shelterwood
19.1
17.1
67.7
44.5
27.2
Boreal
2.1
12.3
0.0
100.0
8.3
Temperate
45.1
28.5
68.9
44.4
45.8
A2 Clearcutting
68.9
78.1
5.3
13.7
58.1
Boreal
94.4
83.8
96.0
0.0
88.0
Temperate
30.2
64.6
3.7
13.7
28.6
B Uneven-aged
11.9
4.3
19.9
5.6
8.6
Boreal
3.5
3.9
4.0
0.0
3.7
Temperate
24.7
5.3
20.2
5.6
13.5
C Coppice
0.0
0.5
7.0
36.3
6.1
Boreal
0
0
0
0
0
Temperate
0
1.6
7.2
36.3
12.1

Table 3. Size, frequency, and residual structure data by natural disturbance category. Size means
the area affected by a single disturbance event, frequency the interval between such disturbance
events in years, while residual structure the percentage of residual living woody biomass volume
related to 1 ha area.
Disturbance type Size (m2)
Frequency
(years)
Residual
structure (%)
References
High severity 104 – 107 150-1000 0-25 Kuuluvainen and Aakala 2011,
Aakala 2018, Nagel et al. 2014
Intermediate
severity 200-106 100-500 25 -75
Nagel et al. 2014, 2017a
Kuuluvainen and Aakala 2011, Čada et al. 2020,
Frankovic at al 2021
Low severity,
diffuse effects 200-106 10-100 75-90
Angelstam and Kuuluvainen 2004,
Kenderes et al. 2007, Kuuluvainen and Aakala
2011, Thom et al. 2013
Low severity,
aggregated effects 20-200 1-10 80-85 Khakimulina et al. 2016, Mountford 2001,
Kuuluvainen and Aakala 2011, Hobi et al. 2015

Table 4. Average size, frequency, and residual structure for silvicultural systems and natural
disturbances of European forests.
System or disturbance
Size
(ha)
Frequency
(years)
Residual
structure (%)
Silvicultural system
A1 Uniform shelterwood systems
3.7
104.0
1.6
A2 Clearcutting systems
2.8
91.4
1.9
B Uneven-aged systems
0.1
8.4
78.7
C Coppice systems
3.2
48.0
1.7
Natural disturbance
High severity
500.5
575.0
12.5
Intermediate severity
50.0
300.0
52.5
Low severity, diffuse effects
50.0
55.0
82.5
Low severity, aggregated effects
0.01
5.5
82.5

Table 5. Comparability Index (CI) values, representing the congruence between silvicultural
systems and natural disturbances. As shown in Fig. 4, each attribute (size, frequency, and
residual structure) was assessed relative to another attribute to derive the CI values, measuring
the distance from the centroids to the Comparability Line (CL). The final row of the table
presents the average CI across all pairwise comparisons.
CI
A1
Shelterwood
A2
Clearcutting
B
Uneven-aged
C
Coppice
Size relative to frequency
0.11
0.11
0.50
0.26
Size relative to residual structure
<0.01
<0.01
0.11
<0.01
Frequency relative to size
0.20
0.20
0.79
0.40
Frequency relative to residual
structure
0.01
0.01
0.26
<0.01
Residual structure relative to size
0.03
0.04
0.70
0.03
Residual structure relative to
frequency
0.06
0.06
0.80
0.05
Average
0.07
0.07
0.53
0.13

Figure captions
Figure 1. Area and proportion of the forest categories (as represented by dominant species)
within the scope of this study in total (b), by country (a) and by biome (c).
Figure 2. Proportion of silvicultural systems used in the observed regions of Europe.
Figure 3. Three dimensional figure displaying size, frequency, and residual structure attributes of
silvicultural systems and natural disturbances in European boreal and temperate forests. Axes
were log+1 transformed.
Figure 4. Size, frequency, and residual structure attributes for natural disturbances and
silvicultural systems in Europe. Shown are: (a) size and frequency; (b) frequency and residual
structure; and (c) size and residual structure comparisons. Dots indicate the centroids of natural
disturbance types and silvicultural systems. The Comparability Line (CL) is based on the
centroids of all the natural disturbance types assessed. Axes were log+1 transformed.
Figure 5. Boxplots of (a) size, (b) frequency and (c) residual structure of silvicultural systems in
Europe. A1 = Shelterwood systems, A2 = Clearcut systems, B = Uneven-aged systems, C =
Coppice systems. Dots indicate the national averages of the given attribute. Intervention size is
the area of the final harvest in case of A1, A2 and C, and defined as the size of the canopy gaps
created by the intervention in case of B. Harvest frequency is the rotation period in the case of
A1, A2 and C and entry cycles for B. Residual structure is defined as the percentage of living
woody biomass volume (m3) post-harvest compared to the pre-harvest volume left on a 1 ha site.

FR
DE
SE
FI
LV
PL
CZ
AT
IT
HU
SK
RO
SI
1 million ha
Scale of the bars:
Norway spruce
Scots pine
Oak species
European beech
Other tree species
(c)
boreal temperate
Area (million ha)
20 10 2010
0
23.4 10.0
15.1 9.9
0.2 11.0
0.1 8.5
9.6 21.5
(b)
Area (million ha)
2010
030
33.4
25.0
11.2
8.6
31.1
(a)

Boreal forests - 48.4 million ha Temperate forests - 60.9 million ha
A1
0.4%
D
8.7%
A2
86.7%
B
4.2%
C
0.0%
A1
21%
D
8.3%
A2
51.9%
B
9.7%
C
9.1%
+
All investigated forests - 109.3 million ha
A1: Uniform shelterwood systems
A2: Clearcutting systems
B: Uneven-aged systems
C: Coppice systems
D: Non-timber and unmanaged
A1
37.4%
D
7.8%
A2
24.3%
B
14.1%
C
16.4%

Frequency (years
)
Residual
structure (%)
Size (ha)
High severity disturbance
Intermediate severity disturbance
Low severity disturbance (diffuse)
Low severity disturbance (aggregated)
Clearcutting systems
Coppice systems
Uneven-aged systems
Uniform shelterwood systems

(a) (b)
(c)
Frequency (years)
Size (ha)
Residual structure (%)
Residual structure (%)
1505 500
500
1505
2205 100
1
1205 100
2
Size (ha)
500
1505
Frequency (years)
500
1505
High severity disturbance
Intermediate severity disturbance
Low severity disturbance (diffuse)
Low severity disturbance (aggregated)
Clearcutting systems
Coppice systems
Uneven-aged systems
Uniform shelterwood systems

Size (ha)
0.0 2.5 5.0 7.5 10.0
A1 A2 B C+D
Management
(a)
050 100
A1 A2 B C+D
Management
Frequency (years)
(b)
025 60 75
A1 A2 B C+D
Management
Residual structure (%)
(c)