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Primary forests are critical for forest biodiversity and provide key ecosystem services. In Europe, these forests are particularly scarce and it is unclear whether they are sufficiently protected. Here we aim to: (a) understand whether extant primary forests are representative of the range of naturally occurring forest types, (b) identify forest types which host enough primary forest under strict protection to meet conservation targets and (c) highlight areas where restoration is needed and feasible. We combined a unique geodatabase of primary forests with maps of forest cover, potential natural vegetation, biogeographic regions and protected areas to quantify the proportion of extant primary forest across Europe's forest types and to identify gaps in protection. Using spatial predictions of primary forest locations to account for underreporting of primary forests, we then highlighted areas where restoration could complement protection. We found a substantial bias in primary forest distribution across forest types. Of the 54 forest types we assessed, six had no primary forest at all, and in two‐thirds of forest types, less than 1% of forest was primary. Even if generally protected, only ten forest types had more than half of their primary forests strictly protected. Protecting all documented primary forests requires expanding the protected area networks by 1,132 km2 (19,194 km2 when including also predicted primary forests). Encouragingly, large areas of non‐primary forest existed inside protected areas for most types, thus presenting restoration opportunities. Europe's primary forests are in a perilous state, as also acknowledged by EU's “Biodiversity Strategy for 2030.” Yet, there are considerable opportunities for ensuring better protection and restoring primary forest structure, composition and functioning, at least partially. We advocate integrated policy reforms that explicitly account for the irreplaceable nature of primary forests and ramp up protection and restoration efforts alike.
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Diversity and Distributions. 2020;26:1646–
Received: 26 March 2020 
  Revised: 30 July 2020 
  Accepted: 18 August 2020
DOI: 10.1111/ddi.13158
Protection gaps and restoration opportunities for primary
forests in Europe
Francesco M. Sabatini1,2,3 | William S. Keeton4| Marcus Lindner5|
Miroslav Svoboda6| Pieter J. Verkerk7| Jürgen Bauhus8| Helge Bruelheide1,2 |
Sabina Burrascano9| Nicolas Debaive10| Inês Duarte11| Matteo Garbarino12 |
Nikolaos Grigoriadis13| Fabio Lombardi14 | Martin Mikoláš6,15| Peter Meyer16 |
Renzo Motta12| Gintautas Mozgeris17 | Leónia Nunes11,18 | Péter Ódor19 |
Momchil Panayotov20| Alejandro Ruete21 | Bojan Simovski22 |
Jonas Stillhard23| Johan Svensson24 | Jerzy Szwagrzyk25| Olli-Pekka Tikkanen26|
Kris Vandekerkhove27 | Roman Volosyanchuk28| Tomas Vrska29|
Tzvetan Zlatanov30 | Tobias Kuemmerle3,31
1Institut für Biologie, Martin-Luther-Universität Halle-Wittenberg, Halle, Germany
2German Centre for Integrative Biodiversity Research (iDiv), Halle-Jena-Leipzig, Germany
3Geography Department, Humboldt-Universität zu Berlin, Berlin, Germany
4Rubenstein School of Environment and Natural Resources, University of Vermont, Burlington, V T, USA
5Resilience Programme, European Forest Institute, Bonn, Germany
6Faculty of Forestry and Wood Sciences, Czech University of Life Sciences Prague, Praha 6 – Suchdol, Czech Republic
7European Forest Institute, Joensuu, Finland
8Faculty of Environment and Natural Resources, University of Freiburg, Freiburg, Germany
9Department of Environmental Biology, Sapienza University of Rome, Rome, Italy
10Réserves Naturelles de France, Dijon Cedex, France
11Centre for Applied Ecolog y “Professor Baeta Neves” (CEABN), InBIO, School of Agriculture, University of Lisbon, Lisbon, Portugal
12Department of Agricultural, Forest and Food Sciences (DISAFA), University of Torino, Grugliasco, Italy
13Forest Research Institute Thessaloniki, Thessaloniki, Greece
14Department of Agraria, Mediterranean University of Reggio Calabria – Feo Di Vito, Reggio Calabria, Italy
15PRALES, Rosina, Slovakia
16Northwest German Forest Research Institute, Göttingen, Germany
17Agriculture Academy, Institute of Forest Management and Wood Science, Vytautas Magnus University, Akademija, Lithuania
18CITAB, Centre of the Research and Technology of Agro-Environmental and Biological Science, University of Trás-os-Montes and Alto Douro, Vila Real,
19Centre for Ecological Research Institute of Ecology and Botany, Vácrátót, Hungary
20University of Forestr y, Sofia, Bulgaria
21Greensway AB, Uppsala, Sweden
22Hans Em Faculty of Forest Sciences, L andscape Architecture and Environmental Engineering, Depar tment of Botany and Dendrology, Ss. Cyril and Methodius
University in Skopje, Skopje, Nor th Macedonia
23Forest Resources and Management, Swiss Federal Institute for Forest, Snow and Landscape Research WSL, Birmensdorf, Swit zerland
24Department of Wildlife, Fish and Environmental Studies, Swedish University of Agricultural Sciences, Umeå, Sweden
25Department of Forest Biodiversity, Universit y of Agriculture in Krakow, Krakow, Poland
This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium,
provided the original work is properly cited.
© 2020 The Authors. Diversity and Distributions published by John Wiley & Sons Ltd.
26School of Forest Sciences, University of Eastern Finland, Joensuu, Finland
27Research Institute for Nature and Forest (INBO), Geraardsbergen, Belgium
28NGO "Ecosphere" – Koshyts'ka, Uzhhorod, Ukraine
29Silva Tarouca Research Institute, Brno, Czech Republic
30Institute of Biodiversity and Ecosystem Research, Bulgarian Academy of Sciences, Sofia, Bulgaria
31Integrative Research Institute on Transformation in Human-Environment Systems, Humboldt-Universität zu Berlin, Berlin, Germany
Francesco M. Sabatini, Institut für
Biologie, Martin-Luther-Universität Halle-
Wittenberg, Am Kirchtor 1, 06108 Halle,
Funding information
European Commission, Grant/Award
Number: 658876; Portuguese Foundation
for Science and Technology, Grant/
Award Number: UID/AGR/04033/2019;
Naturvårdsverket, Grant/Award Number:
NV-03 5 01-15
Aims: Primary forests are critical for forest biodiversity and provide key ecosystem
services. In Europe, these forests are particularly scarce and it is unclear whether they
are sufficiently protected. Here we aim to: (a) understand whether extant primary
forests are representative of the range of naturally occurring forest types, (b) iden-
tify forest types which host enough primary forest under strict protection to meet
conservation targets and (c) highlight areas where restoration is needed and feasible.
Location: Europe.
Methods: We combined a unique geodatabase of primary forests with maps of for-
est cover, potential natural vegetation, biogeographic regions and protected areas
to quantify the proportion of extant primary forest across Europe's forest types and
to identify gaps in protection. Using spatial predictions of primary forest locations
to account for underreporting of primary forests, we then highlighted areas where
restoration could complement protection.
Results: We found a substantial bias in primary forest distribution across forest types.
Of the 54 forest types we assessed, six had no primary forest at all, and in two-
thirds of forest types, less than 1% of forest was primary. Even if generally protected,
only ten forest types had more than half of their primary forests strictly protected.
Protecting all documented primary forests requires expanding the protected area
networks by 1,132 km2 (19,194 km2 when including also predicted primary forests).
Encouragingly, large areas of non-primary forest existed inside protected areas for
most types, thus presenting restoration opportunities.
Main conclusion: Europe's primary forests are in a perilous state, as also acknowledged
by EU's “Biodiversity Strategy for 2030.” Yet, there are considerable opportunities for
ensuring better protection and restoring primary forest structure, composition and
functioning, at least partially. We advocate integrated policy reforms that explicitly
account for the irreplaceable nature of primary forests and ramp up protection and
restoration efforts alike.
biodiversity conservation, conservation priorities, gap analysis, old-growth forest, primary
forest, protected areas, protection gap, restoration opportunities, strict protection, virgin
Primary forests continue to disappear worldwide (FAO, 2016; Mackey
et al., 2015; Watson et al., 2016, 2018), even in regions where for-
ests are expanding (Potapov et al., 2017; Song et al., 2018). Their loss
is deeply concerning since primary forests are an irreplaceable part
of our natural heritage (Watson et al., 2018) and are critical for con-
serving forest biodiversity (Di Marco, Ferrier, Harwood, Hoskins, &
Watson, 2019; Dvořák et al., 2017; Gibson et al., 2011). Primary for-
ests provide important ecosystem services, such as carbon storage
and riparian functionality (Ford & Keeton, 2017; Warren, Keeton,
Bechtold, & Kraft, 2019; Watson et al., 2018). And while they have
long been known to harbour high levels of biodiversity, particularly
for certain taxa such as bryophytes, fungi, lichens and saproxylic
beetles (Eckelt et al., 2018; Paillet et al., 2010; Watson et al., 2018),
recent research has shown that primary forests frequently also have
high functional trait diversity, which contributes to the resilience of
ecosystem service outputs to global change (Messier, Puettmann,
& Coates, 2013; Thom et al., 2019). Finally, where forest extent has
declined or forests have been heavily altered from historic baselines,
primary forests are also an important reference for guiding resto-
ration and adapting to global change (Kuuluvainen, 2002; Parviainen,
Bücking, Vandekerkhove, Schuck, & Päivinen, 2000).
Primary forests are naturally regenerated forests composed of
native species, where signs of past human use are minimal and eco-
logical processes, such as natural disturbances, operate dynamically
and with little impairment by anthropogenic influences (Barton &
Keeton, 2018; CBD, 2006; FAO, 2015). Globally, about one-third of
all forests can be considered primary, but most are located in re-
mote areas in the tropics, boreal zones or mountain regions (Potapov
et al., 2017). By contrast, primary forests are scarce in the sub-trop-
ical and temperate zones (Sabatini et al., 2018; Watson et al., 2016).
In Europe, millennia of land use deeply transformed the forested
landscapes (Kaplan, Krumhardt, & Zimmermann, 2009), so that very
few forests remain with minimal signs of human use (<4% of forest
area; FO REST EUROPE , 2015b). Yet, it is un cle ar wh eth er th ese rem-
nants are representative of the range of natural forest types found
in Europe (Sabatini et al., 2018), and whether they are effectively
Where primary forests still exist, ensuring that a sufficiently
large area is adequately protected should be the first priority from
a conservation perspective. Yet, there is a lack of consensus on how
much primary forest should be protected for safeguarding biodi-
versity (Lõhmus, Kohv, Palo, & Viilma, 2004; Mair et al., 2018; Noss
et al., 2012; Parviainen et al., 2000; Visconti et al., 2019). For in-
stance, the Aichi target #11 of the Convention of Biological Diversity
requires 17% of terrestrial land to be conserved in ecologically rep-
resentative systems of protected areas (CBD, 2010). In its National
Strategy on Biological Diversity, Germany committed to protecting
at least 5% of forested areas in wilderness areas (Schumacher, Finck,
Riecken, & Klein, 2018). Yet, most international agreements (CBD,
2010; European Commission, 1992; UN General Assembly, 2015)
do not explicitly refer to primary forest, which adds uncertainty
to conservation objectives (Chiarucci & Piovesan, 2019; Mackey
et al., 2015; Watson et al., 2018). Only recently the EU commission
released a new “Biodiversity Strategy for 2030,” which emphasizes
the need to define, map, monitor and strictly protect all of the EU's
remaining primary and old-growth forests (European Commission,
2020). Until this strategy comes into force, however, many pri-
mary forests remain unprotected (Mikoláš et al., 2019; Sabatini
et al., 2018), and it is unclear in which forest types such protection
gaps are largest.
Where protection does exist, it should be sufficiently strict to
avoid primary forest degradation. Many protected areas allow for
human activities (e.g. salvage logging) that could jeopardize natural
forest dynamics, such as successional recovery from natural dis-
turbance and carryover of biological legacies (Mikoláš et al., 2019;
Thorn et al., 2018). Such activities should thus be banned from pri-
mary forests, if the goal is to allow these forests to develop naturally.
Identifying upgrading gaps (i.e. protected areas requiring an upgrade
to strict protection) is therefore a second major priority to safeguard
primary forests in the long-term.
Finally, given the overall very small area still covered by primary
forest for most forest types, even protecting these areas entirely is
likely insufficient for meeting biodiversity targets for many forest
types (Keenelyside, Dudley, Cairns, Hall, & Stolton, 2012). Where
the area of extant primary forest is too low, promoting the devel-
opment of primary forest structure, composition and functioning in
non-primary (e.g. secondary and managed forests) forests is crucial.
Depending on the context and starting conditions (e.g. connectiv-
ity, presence of keystone species), restoration could happen either
passively (e.g. setting aside forest and discontinuing forest man-
agement, salvage logging or disturbance suppression) or actively
(e.g. removing non-native species, translocating species, restor-
ing natural hydrological conditions or promoting the development
of key structural elements, such as deadwood or veteran trees;
Keenelyside et al., 2012; Mazziotta et al., 2016; Mikoláš et al., 2019;
Schnitzler, 2014). Still, restoring conditions closer to those found in
primary forests faces many challenges, not the least of which is the
long timeframes involved. Where primary forests are scarce, lack
of regeneration material may impede restoration of compositional
diversity. Climate change adds uncertainty, as it is unclear where
species may thrive in the future (Cernansky, 2018). Yet, it provides
an additional argument for forest restoration, because increas-
ing the structural and compositional diversity of forests improves
their resistance and resilience to climate change effects (Barton &
Keeton, 2018; Betts, Phalan, Frey, Rousseau, & Yang, 2018; Mair
et al., 2018). Identifying where restoration gaps exist (i.e. areas
where restoring primary forests is needed and feasible) is therefore
a third conservation priority.
Building on a unique and comprehensive spatial database of
documented primary forests in Europe (Sabatini et al., 2018), as
well as on country-level statistics of primary forests (FOREST
EUROPE, 2015b), here we address three questions:
1. Are remaining primary forests representative of Europe's bio-
geographic diversity and forest types?
2. Which forest types have a sufficient proportion of primary forest
under strict protection and which forest types would meet differ-
ent conservation targets?
3. Where would primary forest restoration efforts best complement
protection to reach long-term conservation targets?
Compared to our previous work (Sabatini et al., 2018), which
focused on understanding the spatial determinants underlying the
current distribution of known primary forests, this study advances
existing knowledge on primary forests by (a) systematically assessing
their extent and distribution in relation to biogeographical regions
and forest types in Europe and (b) comprehensively characterizing
and mapping different conservation gaps. By identifying protection
and restoration gaps and priorities, in particular, we contribute to the
scientific knowledge urgently needed for developing an integrated
strateg y for protecting and restoring forest s with primary character-
istics across Europe's landscapes, as called for in the framework of
the new “EU Biodiversity Strategy for 2030” (European Commission,
2.1 | Input data
As acknowledged by the Convention of Biological Diversity, the
term “primary forest” has a different connotation in Europe com-
pared to the rest of the world. It refers to forests which have never
been completely cleared, at least throughout historical times, even
if traditional human disturbances (e.g. coppicing, burning, partial
logging) may have occurred (CBD, 2006). In line with the Food and
Agricultural Organization (FAO, 2015), here we consider a forest
as primary” where the signs of former human impacts, if any, are
strongly blurred due to decades (at least 60–80 years) without for-
estry operations (Buchwald, 2005). We do not imply, therefore, that
these forests were never cleared nor disturbed by humans.
We used a novel database of primary forests in Europe, excluding
Russia (Sab ati ni et al., 2018). This ma p aggreg ate s and harm oni ze s in-
formation derived from existing local-to-regional maps and datasets,
scientific literature and original data from forest experts. In total, the
map includes 1.4 Mha of primary forest across 32 European coun-
tries and represents a comprehensive, spatially explicit database on
known primary forests in Europe (Sabatini et al., 2018).
To assess the distribution of Europe's total forested area, we used
a high-resolution (25 m) map of forest cover (Kempeneers, Sedano,
Seebach, Strobl, & San-Miguel-Ayanz, 2011), which we aggregated
at 250-m resolution (pixel size = 6.25 ha) for computational reasons.
Since this map does not cover some Eastern European countries (e.g.
Ukraine, Belarus or Moldova), we integrated it with data on frac-
tional tree cover (original resolution 30 m) from the Global Forest
Watch (Hansen et al., 2013), which we also aggregated to a reso-
lution of 250 m. Percentage forest (or tree) cover estimated using
these two data sources had a good match in overlapping areas (i.e.
Poland, Slovakia and Romania), with Pearson's r correlation esti-
mated over 1,000 random points (with a 5 km minimum distance
between points) of 0.87 (p < .001). For our analysis, we defined
each 6.25 ha pixel as forest when forest\tree cover was >40%. This
threshold discriminates between open and closed forests as defined
by FAO (FAO, 2018).
We derived a map of forest types following a multi-step proce-
dure. We started with the map of the potential natural vegetation of
Europe (BfN, 2003), which reports potential zonal and azonal veg-
etation that would occur after a successional process undisturbed
by humans. Next, we cross-linked the >700 legend classes from this
map to the 13 forest categories (plantations excluded) defined by
the European Environmental Agency (EEA, 2006), as in Table S1.
By aggregating classes belonging to the same category, we could
then create a map with the potential distribution of forest catego-
ries in the absence of human disturbance. We then masked the map
of potential forest categories with the forest-cover map to quan-
tify the actual amount of forest area in each category (Figure S1).
Disaggregating categories across Europe's biogeographical regions
(BfN, 2003) yielded 54 forest types, defined as the combination be-
tween forest category and biogeographical region.
2.2 | Accounting for reporting gaps
To account for underreporting of primary forests data, we created a
composite dataset complementing different data sources. For each
country, we calculated the difference between the fraction of forests
contained in the map of primary forests (Sabatini et al., 2018), and
the country area estimates of forest undisturbed by man (FOREST
EUROPE, 2015b). The latter data are based on national interpreta-
tions of forest undisturbed by man and typically derive from for-
est inventories or individual studies (FOREST EUROPE, 2015a). We
considered this difference as an estimate of the amount of primary
forest not yet mapped for each country (Table S2). We then assigned
a corresponding fraction of forested area to primary forest, based
on the likelihood that each 250 m grid cell contains primary forests.
To calculate this likelihood, we trained a spatially explicit boosted
regression tree (BRT) model relating the presence of primary forests
(response variable) to a set of 15 non-collinear (Pearson's r < 0.7)
biophysical, socio-economic and historical land use predictors
(Table S3). This model is conceptually equivalent to the one pre-
sented in Sabatini et al. (2018), but downscaled to a 250 m resolu-
tion. Since spatial clustering might lead to inaccurate models (Phillips
et al., 2009), we rarefied primary forest presence points based on a
5 × 5-km grid. We selected 37,060 pseudo-absence points (i.e. ten
times the number of presences after rarefaction), stratified to con-
trol for the unequal sampling intensity across different European
countries or administrative regions. We set a learning rate of 0.02,
a tree complexity of 5 and a bag fraction of 0.7. We used the gbm.
step routine provided by the R dismo package (Hijmans, Phillips,
Leathwick, & Elith, 2011) to determine the optimal number of trees
(n = 1,650). We also reported the relative importance of each pre-
dictor, that is, the number of times that a variable was selected for
splitting in the BRT model, weighted by the squared improvement to
the model averaged over all trees (Elith et al., 2006) and produced
partial dependency plots for the most important predictors.
2.3 | Representativeness of primary forests
To evaluate the representativeness of primary forest distribution
along environmental gradients, we compared the probability–density
distributions between the forested area of Europe, and the database
of documented primary forests (Sabatini et al., 2018), separately for
each biogeographical region. For this analysis, we used only the da-
tabase of documented primary forests (i.e. not the composite dataset
outlined above). We considered five environmental variables: elevation
(NA S A , 20 06), year l y solar ra d iatio n (N A SA , 20 0 6), gr ow i n g degre e da y s
(>5°C) (Hijmans, Cameron, Parra, Jones, & Jarvis, 2005), water availa-
bility (i.e. the ratio of actual over potential evapotranspiration, referred
to as Pries tley–Taylor alpha coeff icient in Trabu cco & Zomer, 2010) and
suitability to agricultural crops (Zabel, Putzenlechner, & Mauser, 2014).
We considered elevation as a proxy for forest accessibility. Yearly solar
radiation provides a quantitative estimation of topography-related
productivity at a given latitude. We preferred growing degree days
over mean annual temperature since it better represents the growing
conditions during the vegetative season. Similarly, we assumed the
ratio of actual over potential evapotranspiration to provide a better
representation of water availability compared to mean annual precipi-
tation. Finally, we used suitability to agricultural crops to account for
site productivity and land use competition.
To account for collinearity in the environmental data, we also com-
pared the distribution of forested area in Europe to that of primary
forest using a principal component analysis (PCA). After scaling each
variable to zero mean and unit standard deviation, we ran a PCA of
all the forested 250 m pixels of Europe. We then tested whether the
density estimates of the distributions of forested area pixels and pri-
mary forest pixels in the PCA space originated from the same (multi-
variate) distribution. We estimated the probability-density func tions in
the PCA space using a kernel density estimation and then compared
these between forested and primary forest pixels using a squared dis-
crepancy measure. As this comparison test is non-parametric and as-
ymptotically normal, it does not require any subjective decisions, nor
the usual resampling techniques to compute p-values. We used the
function kde.test in the R package ks (Duong, Goud, & Schauer, 2012).
To explore whether primary forests are representative of
Europe's forest types, we first attributed each primary forest pixel
to its respective forest type using the map of potential forest types
described above. We did this because compositional data were only
available for a subset of primary forests. This approach assumes,
therefore, that all primary forests belong to their respective poten-
tial forest type. For each forest type, we then calculated: (a) the cur-
rent extent of all forest, (b) the extent of primary forest and (c) the
fraction of forest in primary conditions. We limited the analysis to
forest types with a potential extent >1,000 km2 and ran this compar-
ison both using the primary forest database (documented primary
forests only) and the composite dataset.
2.4 | Quantifying protection, upgrading and
restoration gaps
Given the lack of consensus on how much primar y forest should be
conserved in Europe, we considered three alternative conservation
targets: 17% (according to the Aichi target #11; CBD, 2010), 10% and
5% of forest area in primary st ate. We deemed there to be a protection
gap for a given forest type when insufficient amounts of primary for-
ests were within protected areas to meet conservation targets, but
only when additional primary forests for those forest types occurred
outside protected areas. Similarly, we identified upgrading gaps for
those forest types where primary forests are formally protected, but
not yet included within strictly protected areas. We considered strict
protection (= IUCN category I and II) to be the only protection level
sufficient to ensure long-term conservation of primary forests, since
in some European countries forest management (e.g. partial cutting,
salvage logging) is allowed even in protected areas with lower protec-
tion level (e.g. Natura 2000 areas). Finally, we indicated as restoration
gaps those situations when not enough primary forest exists, so that
restoration is required to reach a conservation target.
To quantify these three conservation gaps, we calculated the
share of primary forest under different protection levels for each for-
est type. We used spatial information on protected areas from the
World Database on Protected Areas (UNEP-WCMC, & IUCN, 2019).
We conservatively considered those protected areas where the IUCN
category was not specif ied (e.g. Natur a 20 00 areas) as bei ng protecte d,
but not strictly. This yielded, for each forest type, the area and share
of primary forest currently unprotected (protection gaps) or outside
strictly protected areas (upgrading gaps). Similarly, we quantified the
area and share of forested land that would have to undergo restoration
to meet a given conservation target (re storation gaps) as the dif ference
between a conservation area target and the current amount of primar y
forests for that forest type. For visualization purposes, we used tree-
map graphs (Tennekes, 2017), where we show the 17%, 10% or 5%
forest area having the highest conservation status (two levels: primary,
non-primary) and protection status (three levels: strict—IUCN protec-
tion category I and II, other—IUCN categories III-VI, and no protection)
for each forest type. We ran this analysis both using our database of
documented primary forests and the composite dataset, which ac-
counts for underreporting of primary forest data.
The analyses based on documented primary forest alone or on
the composite dataset are highly complementary. The former re-
turns a more accurate representation of protection and upgrading
gaps, but overestimates the amount of restoration gaps. The latter
generates better estimates of restoration gaps, but quantifies pro-
tection and up gra ding gaps less ac cur ately due to the unce r tai n loc a-
tion of undocumented (=predicted) primary forests. Therefore, we
presented the results of both analyses, but gave them different em-
phases depending on the specific conservation gap. For protection
and upgrading gaps, we presented the results based on documented
primary forest alone in the main text, and those based on the com-
posite dataset in the supplementary material. For restoration gaps,
we did the opposite.
2.5 | Mapping restoration opportunities
To pinpoint the most favourable areas where restoration could com-
plement protection to reach primary forest conservation targets
(17%, 10 or 5%), we mapped restoration opportunities. We selected
areas suitable for restoration by selecting forested areas with the
highest likelihood to contain primary forests, based on the BRT model
described above. Since our BRT model showed that socio-economic
(i.e. accessibility, population density) and land use (i.e. agricultural
suitability, wood increment) determinants were good predictors of
primary forest location, we interpreted areas with higher likelihood
of containing primary forest as areas having lower land use pressure
and thus greater suitability for primary forest restoration. We prior-
itized forests in protected areas, because we assume restoration has
lower opportunity costs and higher social acceptability there. We
mapped restoration gaps separately for each forest type, again using
both datasets (documented primary forests and composite). In the
first case, the areas with the highest likelihood of containing primary
forests were all considered as areas suitable for restoration. In the
second case, these areas were split between additional (predicted)
primary forest and forest suitable for restoration.
We visualized the output of these analyses in two ways. First,
we built a choropleth showing the share of forested pixels in need of
conservation action (i.e. protection, upgrading or restoration gaps)
at the level of first- or second-order (depending on country size)
administrative regions in Europe (Global Administrative Areas, 2012).
Second, we aggregated the results into hexagonal forest landscapes
(ca. 6,000 km2) and reported the biggest conservation gap per land-
scape, separately for each forest type. We ranked gaps as follows:
(a) unpr ote cted primary fo res t s (=protection gap), (b) primary forests
occurring in protected areas of IUCN category III or higher (=up-
grading gap), (c) areas favourable for restoration in protected areas
(=restoration gap) and (d) areas favourable for restoration outside
protected areas (=restoration + protection gap). These maps show
neither primary, nor non-primary forests in strictly protected areas,
as these areas do not require conservation actions.
3.1 | Biogeographical bias in primary forest
Primary forests encompassed remarkably well the variability in
climate (solar radiation, growing degree days—GDD 5°, water
FIGURE 1 Distribution of total and primary forest cover along main environmental gradients. The y-axis represents the proportion of
250 m pixels covered with either forest (blue), or primary forest (pink), so that the areas under the curves are equivalent. We only considered
those biogeographical regions with more than 10,000 km2 of total forested area. Dots and horizontal bars, respectively, represent the
mean and standard deviation of the distributions. Outliers (<2.5th and >97.5th percentiles) are not shown [Colour figure can be viewed at]
0.0 0.5 1.0 1.5
Solar Rad.
100 200 300 400
(No. Days)
40 60 80 100
Availability (%)
Suitability (%)
availability), topography (elevation) and soil productivity (agri-
cultural suitability) occurring in Europe's biogeographical regions
(Figure 1). However, there were some key differences between
the distribution of primary forests and total forest cover. Primary
forests were over-represented at high elevations (except for the
Alpine region) and at the low end of the solar radiation gradient in
the Alpine, Atlantic and Boreal biomes. They also occurred more
often where yearly solar radiation is low, that is, where topographi-
cal conditions are relatively unfavourable, such as on steep and/or
north-facing-slopes. Primary forests also occurred more frequently
in colder conditions (low GDD), where water availability is higher
(with the exception of the Alpine region), and on land less suitable
for agriculture, especially in the Alpine, Atlantic and Boreal biomes.
The tendenc y towards high elevation, cold an d wet conditions with
low yea rly solar radiation was also visible after accounting for colline ar-
ity between variables and comparing the distribution of primary and
total forest in the multivariate environmental space defined by a princi-
pal component analysis (PCA; Figure 2). The two multivariate distribu-
tions were significantly (z = 383,805, p < .001) different according to
a kernel density based on global two-sample comparison test (Duong
et al., 2012) referring to the first four principal components (97.3% of
variation explained). This difference was also significant when consid-
ering each biogeographical region separately (Figure S2).
We found a substantial geographic bias in the distribution of
primary forests across forest types, both when using the compos-
ite dataset and our primary forest database only. The composite
dataset contains information on 3.5 Mha of primary forest (1.4 Mha
from Sabatini et al. (2018), and 2.1 Mha predicted). The model un-
derlying the composite dataset had a relatively high cross-validated
area under the curve (AUC, mean ± SD range 0.86 ± 0.007) and
correlation between observed and predicted primary forest likeli-
hood (rcv = 0.63 ± 0.007). After controlling for spatial sorting bias
(Hijmans, 2012), AUC reduced to 0.65 and rcv to 0.29. The most im-
portant explanatory variables were forest growing stock (relative
influence 12.1%), population density (10.7%), forest cover in 1,850
(9.6%) and accessibility (8.3%). Specifically, the model stresses that
primary forests are more likely to occur in less productive areas
where current and historical anthropogenic pressure is low. Indeed,
the likelihood of a pixel containing primary forest was higher where
growing stock and human population density were lower, and for-
est cover in 1,850 AD was higher. The relationship with accessibility
was more complex: primary forest likelihood increased for increas-
ing travel time from major cities up to a certain threshold and then
decreased abruptly (Figure S3).
Based on th e compos i t e da t aset , fo r only on e fo rest ty pe (no n - r i v-
erine alder, birch and aspen forest in the boreal biome), primary for-
est accounted for more than 17% of total forested area (Figure 3).
Of the remaining forest types, only one had a proportion of primary
forest >5%, and 13 forest types had a share of primary forest of
1%–5%. Another 33 forest types had between 0.01% and 1% of for-
est in primary state. For 13 of these, primary forest covered less
than 1,000 ha. No remaining primary forests were documented, or
predicted to exist, for the remaining six forest types, most of which
were located in the Atlantic and Alpine biomes (Figure 3). All these
results changed only marginally when considering our original data-
base of documented primary forests only (Figure S4). The number of
forest types having a relatively high proportion of primary forests
(1%–5%) decreased to seven, while those having little (0.01%–1%)
primary forest increased to 37. No primary forest was found in nine
forest types (Figure S4).
3.2 | Protection, upgrading and restoration gaps
When considering only our database of documented primary forests,
protection gaps were not particularly widespread across Europe's
FIGURE 2 Distribution of (a) all European forests, (b) primary
forests and (c) differences between the proportions of the two in
the multidimensional environmental space. The graphs are based on
a principal component analysis (PCA) based on elevation, growing
degree days (GDD 5°C), water availability, yearly solar radiation and
agricultural suitability. The first two principal components account
for 47.4% and 26.7% of the overall variation, respectively [Colour
figure can be viewed at]
forest types. For only three forest types were there more than 80%
of remaining primary forests located outside protected areas, while
in an additional six forest types the proportion of unprotected pri-
mary forest was greater than 20% (Table S4; Figure S5). The situation
was considerably less favourable for primary forest protection when
basing the analysis on the composite dataset (Figure S6). In this case,
la r ge prot e c tion gap s (>80% of primary forest unprotected) occurred
in about one fourth of the forest types we considered (n = 12) and in
eight additional forest types, this proportion ranged between 50%
and 80% (Figure S6). Protecting all documented primary forests in
Europe would require expanding the current protected area net-
works by 1,132 km2. This area increased to 19,194 km2 when con-
sidering also undocumented (=predicted) primary forests (Table 1),
although this figure should be seen as an upper bound due to the
uncertain location of undocumented primary forests.
Upgrading gaps were very common, although for some countries
the IUCN category of protected areas is not consistently specified
(UNEP-WCMC, & IUCN, 2019). When considering documented pri-
mary forests only, there were 19 forest types where >80% of pri-
mary forest, albeit protected, was outside strict reserves of IUCN
category I or II (Figure 4; Figure S5; Table S4). In an additional six
and twelve forest types, this proportion was between 50%–80% and
20%–50%, respectively. More than half of the primary forest was
under strict protection in only ten forest types. A total of 5,109 km2
of documented primary forests qualified as in need of upgrading.
When considering our composite dataset, the number of forest types
with upgrading gaps exceeding 50% increased to eleven (Figure S6).
Based on our model, granting strict protection to all documented
and predicted primary forests in Europe would require upgrading an
additional 5,588 km2 of protected areas (0.1% of Europe's land area,
Table 1).
Meeting a 17% conservation target would require extensive res-
toration for most forest types (Figure 4). For most forest types, a high
fraction of protected non-primary forests was coupled with smaller
areas of primary forest (e.g. lowland, and montane beech forests in
the Alpine biome). For some other forest types, however, there was
neither enough primary forest, nor enough protected forest to fulfil
a 17% target (e.g. the taiga forest in the Atlantic biome). This general
situation neither changed for the least ambitious conservation target
(i.e. 5%) nor when repeating the analysis using the composite dataset
(Figure S7). Based on the composite dataset, an area approximately
the size of Romania (226,236 km2, 21.8% of Europe's forest area)
should undergo restoration if the goal would be to ensure that 17%
of Europe's forest approach primary, or close to primary conditions,
at some point in the future (Table 1). Of this area, 28.6% is currently
outside protected areas. Embracing conservation targets of 10% or
5% would decrease the required area to 107,440 and 30,331 km2,
respectively (Table 1).
3.3 | Restoration opportunities
We mapped the most favourable areas where restoration could
complement protection to reach primary forest conservation targets
FIGURE 3 Share and amount of primary forests across forest types. Numbers indicate the absolute extent of primary forests in
thousands of hectares as predicted when integrating data from Sabatini et al. (2018) and disaggregating data from FOREST EUROPE
(2015b). White cells represent either non-existing forest types, or forest types having an amount of total forest cover below 1,000 km2.
Biogeographical regions follow BfN (2003), and forest categories follow EEA (2006) [Colour figure can be viewed at]
Alpine coniferous
Acidophilus oak−birch
Mesophytic deciduous
Lowland Beech
Montane beech
Thermophilus deciduous
Broadleaved evergreen
Coniferous Mediterranean
Mire and swamp
Share of
Primary for.
[5%, 17%)
[1%, 5%)
[0.1%, 1%)
[0.01, 0.1)
(Figure S8). The map showed that, for many forest types, favourable
areas were scattered throughout their respective biogeographical
regions. This is the case, for instance, for the mesophytic deciduous
forests in the continental region. For other forest types, we could
instead identify key regions for restoration. For the acidophilous
oak-birch forest s of the Continental biome, for instance, priority res-
toration areas were clustered along the Ukraine–Belarus border, in
Czech Republic, or in the western Cantabrian range. Similarly, for
thermophilous deciduous forests, priority areas for restoration were
widespread along the Apennines, as well as in the Spanish Pyrenees.
TABLE 1 Summary statistics for protection, upgrading and restoration gaps in Europe (excluding Russia). Only biogeographical regions
hosting >10,000 km2 of forest shown. These estimates are based on a composite dataset merging data from Sabatini et al. (2018) and
country-level estimates from FOREST EUROPE (2015b)
Alpine Atlantic Boreal Continental Mediterranean Pannonian Total
Land area
km2674, 547 855,030 983,369 1,858,760 93 7,114 151,20 5 5,7 71, 245
Forest area
km2226,962 126,722 662,233 570,294 150,355 18 ,4 41 1,770,381
%33.65 14.82 67. 3 4 30.68 16 .04 12.20 30.68
Primary forest area
km28,525 210 24,772 1,416 386 535 ,314
% of land area 1.26 0.02 2.52 0.08 0.04 0.00 0. 61
% of forest area 3.76 0.17 3.74 0.25 0 .26 0.03 1.9 9
Protection gapsa
km23,304 146 14,855 642 247 119,194
% of land area 0.49 0.02 1. 51 0.03 0.03 0.00 0.33
% of forest area 1.46 0.12 2 .24 0 .11 0.16 0.0 0 1.08
Upgrading gapsa
km22,618 16 2,573 299 79 35,588
% of land area 0.39 0.00 0. 26 0.02 0.01 0.00 0.10
% of forest area 1.15 0.01 0.39 0.05 0.05 0.02 0.32
Restoration gaps
Target 17%
km217,0 4 3 19,196 79,736 86,936 18,926 2,432 226,236
% of land area 2.5 2.2 8.1 4.7 2.0 1.6 3.9
% of forest
7.5 15.1 12.0 15.2 12.6 13.2 12.8
% not
1.4 12.5 76.2 0.0 0 .1 0.0 28.6
Target 10%
km25,353 10,620 33,732 47,13 5 8,485 1,147 1 07,44 0
% of land area 0.8 1.2 3.4 2.5 0.9 0.8 1 .9
% of forest
2.4 8.4 5.1 8.3 5.6 6.2 6 .1
% not
1.2 9.2 47. 1 0.0 0.0 0.0 16.3
Target 5%
km2708 4,495 3,585 18,839 2,044 391 30,331
% of land area 0.1 0.5 0.4 1.0 0.2 0.3 0.5
% of forest
0.3 3.5 0.5 3.3 1.4 2.1 1.7
% not
0.0 2.3 1.3 0.0 0.0 0.0 0.9
aDue to the uncertain location of undocumented (=predicted) primary forests, these figures should be taken with caution and seen as possible upper
bounds, as we expect that a higher than random proportion of undocumented primary forests occur in protected areas.
For taiga forests, restoration opportunities were concentrated
primarily in southern Finland (Figure S8).
When considering our composite dataset and all forest types
jointly, restoration gaps dominated (Figure 5). Assuming a 17% tar-
get, a strong contrast emerged between the lowlands of Southern
and Central Europe on the one hand, and Fennoscandia and the main
European mountain ranges on the other. In Western Europe, for in-
stance Great Britain, the Iberian Peninsula, Northern Italy and the
lowland areas of France, Germany and Poland, little or no primary
forest remains so that restoration gaps prevailed. In Fennoscandia
and in the Alpine, Carpathian and Balkan mountain ranges, instead,
not all primary forests were adequately protected, according to our
analyses. These were either outside protected areas (e.g. Sweden
or eastern Romania), or not strictly protected (e.g. Slovakia, Bosnia
and Herzegovina, or Bulgaria) or their protection level was not con-
sistently reported (e.g. Finland). Running the same analysis using
our database of documented primary forests showed some marked
shifts in conservation priorities, especially for data poor areas. In
Sweden, Belarus, Albania and the Alpine range, for instance, gaps in
restoration replaced protection gaps (Figure S9). Differences were
also substantial for the mountain regions of Southern Europe. Here,
most documented primary forests were effectively protected (blue
tones in Figure S9). Yet, these regions were also predicted to con-
tain additional primary forests, which were either located outside
strictly protected areas (see for instance the pink shades of the
Italian Apennines in Figure 5) or were unprotected altogether (e.g.
brown shades in Albania, Montenegro or southern Serbia).
Primary forests are essential for biodiversity (Di Marco et al., 2019;
Gibson et al., 2011; Watson et al., 2018), but are declining globally
(Potapov et al., 2017; Watson et al., 2016). Yet, major uncertainties
remain concerning the distribution of primary forests in Europe, their
protection status, and for which areas and forest types restoration
FIGURE 4 Distribution of forest area between primary and non-primary status, across protection levels and forest types. Only
documented primary forest data from Sabatini et al. (2018) considered. Each square represents 17% of the area of each forest type. For each
square, the size of the coloured rectangles is proportional to the area of forest in a given protection status (strict protection = IUCN I-II,
other protection = IUCN III-VI, not protected) or conservation status (primary, non-primary). Squares are further divided in three rectangles,
which cumulatively represent a 5% (left bar), 10% (left bar + bottom bar) and 17% (all square) of total forest. Rectangles are progressively
filled considering forest area based on the following order: (a) strictly protected primary forest, (b) primary forest occurring in other
protected areas, (c) unprotected primary forest, (d) strictly protected non-primary forest, (e) non-primary forest in other protected areas
and (f) unprotected non-primary forest. In each rectangle, forest area in higher categories is only shown if the amount of forest area in lower
categories does not reach the respective (5%, 10% or 17%) threshold. Only forest types with a total forest cover above 1,000 km2 are shown
[Colour figure can be viewed at]
efforts are most needed. By combining available data on the dis-
tribution of primary forests with a modelling approach, our study
addresses these knowledge gaps, and pinpoints areas and forest
types where restoration efforts would best complement protection
to help reach long-term conservation targets.
Remaining primary forests are not evenly distributed across for-
est types and are only partially representative of the full range of
environmental conditions in Europe. Almost three-quarters of all
forest types (39 of 54) have no or less than 1% of primary forest
remaining, which is likely insufficient to preserve the majority of
species associated with these forests (Lõhmus et al., 2004; Swanson
et al., 2011). This is particularly critical in light of the fact that primary
forests are crucial for the long-term persistence of many organismal
groups and red-listed species in Europe, including insects (Eckelt
et al., 2018), fungi and lichens (Ardelean, Keller, & Scheidegger, 2016;
Moning & Müller, 2009).
Many primary forests in Europe are unprotected, which necessi-
tates expansion of the current protected areas network. Protecting
primary forests is more cost-effective than their restoration once
they have been degraded (IUCN, 2016). Primary forests store more
FIGURE 5 Distribution of conservation gaps regarding primary forests across European administrative units. For each unit, we
highlighted the share of forested pixels classified as protection gaps (=unprotected primary forests), upgrading gaps (=protected primary
forests outside strict reserves) and restoration gaps (=forests in areas favourable for restoration for forest types with less than 17% primary
forest). All forest types are shown together. Only administrative units having more than 5 km2 in any of the three gaps are shown. Each black
dot in the triangular colour legend represents one administrative unit. Please note the axes of the triangular colour gradients are scaled
differently to improve data visualization. This graph is based on a composite dataset integrating data from Sabatini et al. (2018) and FOREST
EUROPE (2015a) [Colour figure can be viewed at]
carbon per hectare compared to logged, degraded or planted forests
in ecologically comparable locations (Burrascano, Keeton, Sabatini, &
Blasi, 2013; Watson et al., 2018) and often remain major net carbon
sinks late into forest succession (Luyssaert et al., 2008). Granting
them with adequate protection would therefore provide important
climate benefits, besides enhancing biodiversity (Moomaw, Masino,
& Faison, 2019). According to our analysis, designating 0.3% of
Europe's land area (=1,132 km2) as additional protected areas would
be sufficient to safeguard all documented primary forest fragments,
but protection would still be heavily biased towards the alpine and
the boreal biomes. Similarly, urgent is the need to upgrade the pro-
tection level in about 5,109 km2 of existing protected areas, where
primary forest patches are not yet strictly protected. We consider
these area estimates as lower bounds, since only about two fifths of
Europe's primary forests have been mapped so far. When accounting
for undocumented primary forests using a composite dataset based
on modelling, the areas in need of protection and upgrade in pro-
tection increased to 19,194 and 5,600 km2, respectively. Due to the
uncertain location of undocumented (=predicted) primary forests,
however, these figures should be seen as possible upper bounds, as
we expect that a higher than random proportion of undocumented
primary forests occur in protected areas. There is therefore the need
to further improve our knowledge of the distr ib utio n of Europe's pri-
mary forests to reduce the uncertainty concerning these estimates.
Upgrading protected areas to ensure the long-term maintenance
of primary forests requires a substantial change in conservation
objectives, especially in the Natura 2000 network. The recently re-
leased “EU Biodiversity Strategy for 2030” explicitly mentions the
need to effectively protect all remaining primary and old-growth
forests in Europe and designate at least 10% of Europe's land under
strict protection (European Commission, 2020). Although moving in
the right direction, this strategy falls short by not ensuring that net-
works of strictly protected areas are fully representative of Europe's
forest types. Even where the proportion of extant primary forests
is low, existing protected areas contain large forest areas and thus
provide important opportunities for restoration. Restoring exist-
ing forests towards their ecological potential represents a low-cost
complement to other land-based solutions (e.g. afforestation, refor-
estation) to mitigate climate change, which promises to maximize
biodiversity co-benefits (Griscom et al., 2017; Moomaw et al., 2019).
We found that the areas with the most favourable socio-economic
conditions for restoration coincide with those of low forest harvest-
ing intensity and roundwood production (Levers et al., 2014; Verkerk
et al., 2019). Prioritizing restoration in these areas would reduce the
opportunity costs arising from taking forests out of timber produc-
tion (Keenelyside et al., 2012). Particularly, favourable are those
areas where harvesting intensity has been low in recent history (e.g.
northern Fennoscandia, parts of the Carpathians, the Balkan region
and the Apennines). For forest types mostly located in densely in-
habited areas with high land use pressure, however, restoring the
attributes of primary forests remains challenging. This is the case,
for instance, for the lowland areas in the Atlantic or Mediterranean
biomes. Yet, some of the areas highlighted by our model in these
regions are currently following a trajectory of land use de-intensi-
fication (Levers et al., 2018), such as the Trossachs in Scotland and
the foothills of the southern Carpathians. In this context, abandon-
ment of forest management in economically marginal areas may
provide clear opportunities for restoring future primary forests at
least in small forest patches. This would provide important benefits
to biodiversity, since these restored patches might serve as refuges
for rare or endangered species in these highly fragmented regions
(Vandekerkhove et al., 2011).
Yet, restoring primary forests has many unsettled concep-
tual, economic and technical challenges (Bauhus, Puettmann,
& Messier, 2009; Fahey et al., 2018; Keeton, Lorimer, Palik, &
Doyon, 2019; Schnitzler, 2014) and requires long timeframes. Where
the starting point is relatively natural forest, such as in long-estab-
lished protected areas, passive rewilding approaches (Navarro &
Pereira, 2012; Perino et al., 2019) may be sufficient to promote
the redevelopment of the structure, function and composition of
primary forest ecosystems (Thorn et al., 2018). Active restoration
may instead prove more useful when the starting conditions are
less favourable (e.g. young even-aged stands, non-adapted or
non-native tree species composition, low genetic diversity; Keeton
et al., 2019). Managing for old-growth characteristics, such as struc-
tural complexity, is an option, as it can accelerate stand development
processes, establishment of late-successional biodiversity and eco-
system services such as carbon storage and flood resilience (Bauhus
et al., 2009; Ford & Keeton, 2017; Keeton et al., 2019). Restoring
natural disturbance regimes could be likewise desirable where pri-
mary forests, and the biodiversity therein, depend on infrequent,
high-severity disturbance events, but this requires a careful con-
sideration of possible drawbacks given the specific socio-ecological
context (Kuuluvainen, 2002; Swanson et al., 2011). In all cases, in-
creasing the diversity and complexity of Europe's forest ecosystems
may reduce the future negative impacts of climate change (Barton &
Keeton, 2018; Mair et al., 2018). Primary forests, for instance, have
been shown to effectively buffer forest-floor summer temperatures
compared to simplified forests (Frey et al., 2016), therefore mitigat-
ing climate change impacts for those species with the highest sensi-
tivity to temperature increases (Betts et al., 2018).
Our work represents the first systematic analysis of the repre-
sentativeness, conservation gaps and restoration opportunities of
Europe's primary forests. Yet, some uncertainties need to be men-
tioned. First, the quality of the currently available data varies across
countries (Sabatini et al., 2018). Nevertheless, no biogeographical
region was systematically under-sampled, and the inclusion of ad-
ditional country-level information to derive a composite dataset
on primary forest (FOREST EUROPE, 2015b) further mitigates
this potential bias. Yet, the location of predicted primary forests
remains uncertain, so that figures based on the composite dataset
should be taken with caution. Second, there is considerable incon-
sistency surrounding the application of IUCN protection categories
for protected forest areas in Europe (Frank et al., 2007; Parviainen
& Frank, 2003). At least for certain countries, some protected
areas or alternative forms of protection (e.g. voluntary set-asides,
or certification schemes outside protected areas) may be granting
adequate protection to primary forest patches, even without being
categorized with the highest IUCN levels (Parviainen et al., 2000).
This is, for instance, the case of Finland where many Natura 2000
areas, although not currently categorized as strict protected areas,
may grant a sufficient level of protection to primary forests. If this is
true, then the current upgrading gap of primary forests might change
to restoration or protection gap in many areas in Finland (from pink
to blue or brown in Figure 5). By contrast, in certain contexts even
national parks may provide insufficient protection to primary for-
ests, for instance where widespread salvage logging is allowed after
insect, wind and fire disturbances (Mikoláš et al., 2019; Schickhofer
& Schwarz, 2019). Finally, when prioritizing areas for restoration,
our analysis neither explicitly accounted for opportunity costs, land
tenure, productivity or rent, nor did we treat the uneven distribu-
tion of threatened species and biodiversity hotspots. Aligning resto-
ration and conservation targets (e.g. habitat of threatened species),
as well as other ecosystem services (e.g. timber provisioning) would
be a useful follow-up undertaking for some biomes (Mönkkönen
et al., 2014; Sabatini et al., 2019).
Our work clearly highlights the overall perilous state of Europe's pri-
mary forests. The strong biogeographical bias we found highlights
the urgent need for concerted, cross-national and multiscale con-
servation planning for Europe's forests. For instance, where primary
forests are still relatively widespread, such as in parts of Eastern
Europe, managers must be aware of the uniqueness of these forests
in a broader biogeographical context. Recent reports of primary for-
est loss from these key areas (Mikoláš et al., 2017, 2019; Schickhofer
& Schwarz, 2019) are, therefore, of greatest concern and require
prompt and coordinated action. Likewise, even small regions could
make important contributions to restoring missing primary forests
for some forest types at the European scale. Systematic conserva-
tion planning (Margules & Pressey, 2000) provides an operational
framework to prioritize areas for protection or restoration, with the
goal of creating a functional and representative network of strictly
protected primary forests, in synergy with other national to conti-
nental conservation initiatives (Perino et al., 2019; Schnitzler, 2014;
Schumacher et al., 2018). The surge in demands for materials and
bioenergy we experienced over recent years in Europe has trans-
lated into intensifying wood harvesting in many regions, including
some that are crucial for primary forest conservation (Searchinger
et al., 2018). This conjuncture further increases the urgency to pro-
tect and restore primary forests. The “decade of ecosystem resto-
ration”, as recently declared by the United Nations for 2021–2030,
may provide momentum to set ambitious restoration goals. For ex-
ample, this includes setting aside large areas where redevelopment
towards forest landscapes composed of complex mosaics of seral
habitats and late-successional stand structures will be encouraged,
either actively or passively.
Primary forests are scarce and highly fragmented in Europe,
which may engender vulnerability to anthropogenic stress and
disturbance, impair species' and ecosystems' adaptive responses,
and compromise species' capacity for refugial retreat (Angelstam
et al., 2020; Mikoláš et al., 2019; Svensson, Andersson, Sandström,
Mikusiński, & Jonsson, 2019), especially under the expected increase
in disturbances under climate change (Seidl et al., 2017). Managed
forests should play a key role in this regard. Retention forestry, for
instance, integrates primary forest structures (e.g. deadwood, large
trees, natural tree species composition) into managed forests, there-
fore increasing connectivity between forest reserves and contrib-
uting to preserve forest biodiversity across large scales (Gustafsson
et al., 2012). Diversified forest management strategies efficiently
balancing the trade-offs between timber production and biodiver-
sity impacts are therefore a crucial complement to protection and
restoration efforts in Europe (Eyvindson, Repo, & Mönkkönen, 2018;
Mönkkönen et al., 2014; Sabatini et al., 2019).
The recently released “Biodiversity Strategy for 2030” has the
merit of explicitly recognizing the irreplaceable nature of primary
forests. Yet, this strategy should be coupled with an integrated for-
est policy reforms to prevent the continued loss of Europe's most
valuable forests and in parallel ramp up both protection and resto-
ration efforts for these forests. Only an effective management and
governance of forest landscapes and resources, and a full recogni-
tion of the values and contributions of diverse states of forests can
strategically ensure the maintenance and restoration of key ecosys-
tem services and the fulfilment of human well-being in the long term
(Chazdon, 2018).
This research was funded by the European Union under the Marie
Skłodowska-Curie Project FORESTS & CO, Grant Agreement no.
658876. Additional support was provided by FCT—Portuguese
Foundation for Science and Technology, under the project UID/
AGR/04033/2019, the Swedish Environmental Protection Agency,
Stockholm, grant NV-03501-15. We are grateful to handling editor
and three anonymous reviewers for thoughtful, constructive com-
ments on a prior manuscript version that has helped to improve this
paper. Op en access fun ding enab led and organized by Projekt DE AL.
The authors declare no conflict of interest.
The peer review history for this article is available at https://publo n/10.1111/ddi.13158.
The data on primary forests presented here remain the property
of the institutions, organizations or persons who created or col-
lected them. The custodian of each dataset (i.e. the person or in-
stitution owning or representing the contributed data) is listed in
Sabatini et al., 2018 – Data
are available from the corresponding author upon request for
research or application purposes, subject to approval from the
respective custodians. The composite dataset of primary forest
is available at ata/1841
together with the maps of conservation gaps and restoration op-
portunities. All statistical code is available upon request from the
corresponding author.
Francesco M. Sabatini
Marcus Lindner
Pieter J. Verkerk
Helge Bruelheide
Matteo Garbarino
Fabio Lombardi
Peter Meyer
Gintautas Mozgeris
Leónia Nunes
Péter Ódor
Alejandro Ruete
Bojan Simovski
Johan Svensson
Kris Vandekerkhove
Tzvetan Zlatanov
Tobias Kuemmerle
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Francesco M. Sabatini is a forest ecologist. Within the frame-
work of the Marie Skłodowska-Curie Project FORESTS & CO
(Grant Agreement no. 658876), he established the Informal
Network of Forest Scientists—F&CO-NET, as a means to bring
together forest scientists and experts working on primary and
old-growth forests. The main aim of this network is maintaining
a harmonized geodatabase on the spatial distribution of primary
forests in Europe and adjacent areas, and facilitating its use for
non-commercial purposes, mainly academic and conservation-
relevant research.
Author contributions: F.M.S. and T.K. designed the study. F.M.S.
ran the statistical analyses. F.M.S., T.K. W.S.K., M.S., P-J.V., H.B.,
J.B., K.V., J.Sv. and M.S. drafted the first version of the manu-
script. S.B., N.D., M.G., N.G., F.L., M.M., P.M., R.M., G.M., L.N.,
P.Ó., M.P., A.R., B.S., J.St., J.Sz., K.V., R.V., T.V. and T.Z. contrib-
uted data. All authors contributed to the writing.
Additional supporting information may be found online in the
Supporting Information section.
How to cite this article: Sabatini FM, Keeton WS, Lindner M,
et al. Protection gaps and restoration opportunities for
primary forests in Europe. Divers Distrib. 2020;26:1646–
... Primary forests are essential refuges for biodiversity, including many endemics and species of high conservation value (Moning & Müller, 2009;Wallenius et al., 2010;Paillet et al., 2015;Eckelt et al., 2018;Di Marco et al., 2019;Langbehn et al., 2021), but due to omnipresent historic land use, they are incredibly rare in Europe (Parmasto, 2001;Sabatini et al., 2020). Since ancient times, these forests were used for acquisition of pastures through deforestation, fuel wood and timber extraction. ...
... Within this landscape, the Carpathian Mountains harbour the largest and most important tracts of remaining European temperate primary forests (Grodzińska et al., 2004;Kuemmerle et al., 2010;Veen et al., 2010;Sabatini et al., 2018;Mikoláš et al., 2019), which provide exceptional services in terms of carbon storage, water retention and habitat provisioning for biodiversity (Gibson et al., 2011;Potapov et al., 2017;Watson et al., 2018;Mackey et al., 2020). Nonetheless, many of Europe's primary forests remain unknown or unprotected (Sabatini et al., 2018;Sabatini et al., 2020) and are threatened by logging (Mikoláš et al., 2019). Deforestation and forest degradation imperils biodiversity worldwide (Semper-Pascual et al., 2019;Thorn et al., 2020) with detrimental effects on species of high conservation and functional value (Barlow et al., 2016). ...
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Understanding the processes shaping the composition of assemblages at multiple spatial scales in response to disturbance events is crucial for preventing ongoing biodiversity loss and for improving current forest management policies aimed at mitigating climate change and enhancing forest resilience. Deadwood-inhabiting fungi represent an essential component of forest ecosystems through their association with deadwood decomposition and the cycling of nutrients and carbon. Although we have sufficient evidence for the fundamental role of deadwood availability and variability of decay stages for fungal species diversity, the influence of long-term natural disturbance regimes as the main driver of deadwood quantity and quality has not been sufficiently documented. We used a dendroecological approach to analyse the effect of 250-years of historical natural disturbance and structural habitat elements on local (plot-level) and regional (stand-level) species richness of deadwood-inhabiting fungi. We used data collected from 51 study plots within nine best-preserved primary spruce forest stands distributed across the Western Carpathian Mountains. Historical disturbances shaped the contemporary local and regional species richness of fungi, with contrasting impacts of disturbance regime components at different spatial scales. While local diversity of red-listed species has increased due to higher disturbance frequency, regional diversity of all species has decreased due to higher severity historical disturbances. The volume of deadwood positively influenced the species richness of deadwood-inhabiting fungi while canopy openness had a negative impact. The high number of observed rare species highlights the important role of primary forests for biodiversity conservation. From a landscape perspective, we can conclude that the distribution of species from the regional species pool is-at least to some extent-driven by past spatiotemporal patterns of disturbance events. Natural disturbances occurring at higher frequencies that create a mosaic forest structure are necessary for fungal species-especially for rare and endangered taxa. Thus, both the protection of intact forest landscapes and forest management practises that emulate natural disturbance processes are recommended to support habitats of diverse fungal communities and their associated ecosystem functions.
... Moreover, salvage logging after extreme disturbance events have only been banned from 2002 (Anonymous, 2002). Although this is not the only difference between the investigated managed and strictly protected forests (for example, elevation and topographic complexity were, on average, higher in the reserves), it highlights the potential for reaching resilient forest structures within relatively short periods (Sabatini et al., 2020;Albrich et al., 2021) and benefiting from natural dynamics in selected parts of the landscape (Aszalós et al., 2022). However, this requires shifting from the narrow historical focus of conservation on the iconic landscapes and wildlife towards creating large multifunctional landscapes helping to reach conservation Norway spruce disturbance dynamics objectives and securing human well-being (Watson et al., 2014). ...
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Forest disturbances are intensifying globally, yet regional drivers of these dynamics remain poorly understood. We investigated recent disturbance intensities in Norway spruce (Picea abies L.) forests in Slovakia (Central Europe) with different management objectives in 2000-2017 based on Landsat imagery. We focused on 122 strict reserves without any management, their actively managed surroundings (500 m and 2000 m buffers), and managed production forests beyond the buffer areas. We used generalized additive mixed models to test for differences in temporal trends of disturbance intensity among these management categories. We found that disturbance intensity was increasing in all management categories during the studied period. The increase was more pronounced in the managed forests (compound annual disturbance rate 1.76% year −1) and the 2000 m buffer (2.21% year −1) than in the strict reserves (0.58% year −1). The predicted cumulative disturbance during the 18-year period was 9.9% in the reserves and 30.5% in the 2000 m buffer. We found that forests in nature reserves can be more resistant to disturbances than forests managed for timber production, despite management efforts to control disturbances in managed forests. Our findings can help reconcile the different perceptions of natural disturbances and their management in Central Europe and support climate-adapted management strategies that consider natural disturbances as an indispensable component of ecosystem dynamics.
... Finally, the existing mangrove reserves and the map of the mangrove's potential suitable habitat areas were superimposed to recognize the conservation gaps of the mangrove forests. The conservation gap was defined as the sampling sites with a medium and high probability for restoration and less than 20% of existing mangroves under protection in each grid cell (1 × 1 km) (Sabatini et al., 2020). ...
Background and objective: The area of mangroves is gradually decreasing globally, and mangroves are already one of the most threatened ecosystems. Despite net growth in the mangrove areas in China, the restoration potential of mangroves is still insufficient. This study proposed the Random forest model as an excellent data mining method to map the restoration potential based on the predicted probability of mangrove habitat suitability.Methods: We demonstrated the vital environmental variables influencing habitat suitability. The de-cisive advantages of RFM were parsimonious (variables selection), cost-effective (us-ing existing open-source data), accurate (training AUC was 0.89, testing AUC was 0.91), highly efficient (fast-training speed); and its results had high explanatory power. Here, we first mapped the conservation gaps using the RFM.Results: The results showed that temperature was the most important environmental factor influencing the habitat suit-ability of mangroves. The northern limit of suitable areas was around 24°44' N. The theoretical suitable habitat area for mangrove was 196,566.6 ha (the highly suitable area was 32,551.4 ha, the medium suitable area was 164,015.2 ha). The potential area for mangrove restoration was 176,264 ha (Guangdong with 104215.4 ha, Guangxi with 65957.5 ha).Conclusion: We proposed 24 sites with conservation gaps for mangrove forests restoration and nine potential sites as examples for the further restoration plan. We took one example site with high restoration potential for further explanation: how the key environmental factors influence the habitat suitability and how to use the infor-mation to guide the restoration strategies. RFM can be used as a data mining algo-rithm for the utmost use of the presence-only ecological data, objectively evaluating the suitability of species distribution, and providing scientifically technical data for species restoration planning.
... Most of Europe's forests either have a long history of management or are recent forests resulting from the abandonment of former agricultural land. Forest management and natural disturbance control also truncate significant parts of natural forests dynamics in European forested landscapes (Kuuluvainen, 2009;Sabatini et al., 2020). In contrast, natural forests and those that have been little influenced by industrialization are much more abundant in North America compared to Europe, particularly in Canada and in the western United States (Ellis, 2011;Venter et al., 2016;Potapov et al., 2017), providing interesting references for TreM research. ...
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Sustainable management of forest ecosystems requires the use of reliable and easy to implement biodiversity and naturalness indicators. Tree-related microhabitats (TreMs) can fulfill these roles as they harbor specialized species that directly or indirectly depend on them, and are generally more abundant and diverse in natural forests or forests unmanaged for several decades. The TreM concept is however still recent, implying the existence of many knowledge gaps that can challenge its robustness and applicability. To evaluate the current state of knowledge on TreMs, we conducted a systematic review followed by a bibliometric analysis of the literature identified. A total of 101 articles constituted the final corpus. Most of the articles (60.3%) were published in 2017 or after. TreM research presented a marked lack of geographical representativity, as the vast majority (68.3%) of the articles studied French, German or Italian forests. The main themes addressed by the literature were the value of TreMs as biodiversity indicators, the impact of forest management on TreMs and the factors at the tree- and stand-scales favoring TreMs occurrence. Old-growth and unmanaged forests played a key role as a “natural” forest reference for these previous themes, as TreMs were often much more abundant and diverse compared to managed forests. Arthropods were the main phylum studied for the theme of TreMs as biodiversity indicators. Other more diverse themes were identified, such as restoration, remote sensing, climate change and economy and there was a lack of research related to the social sciences. Overall, current research on TreMs has focused on assessing its robustness as an indicator of biodiversity and naturalness at the stand scale. The important geographical gap identified underscores the importance of expanding the use of the TreMs in other forest ecosystems of the world. The notable efforts made in recent years to standardize TreM studies are an important step in this direction. The novelty of the TreM concept can partially explain the thematic knowledge gaps. Our results nevertheless stress the high potential of TreMs for multidisciplinary research, and we discuss the benefits of expanding the use of TreMs on a larger spatial scale.
... We do not oppose efforts to improve and expand forest protections in Europe and remain agnostic about the hotly debated appropriate share of biodiversity-rich forests [18][19][20] . Efforts, for example, to definitively protect Europe's remaining primary forests for their biodiversity benefits (see EU Biodiversity Goals for 2030; Sabatini et al. 21,22 ), enjoy dedicated support across multiple segments of the LULUCF stakeholder community. However, from a climate perspective, growth eventually declines in older, more protected forests. ...
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Reversing the declining land carbon sink drives the European decision to increase net carbon uptake in the forest. This decision, however, has been made without considering the consequences for the circular bioeconomy. One principal reason is that LULUCF (Land Use, Land Use Change and Forestry) accounting fails to balance LULUCF emissions/removals with the forest-based substitution effects recorded in the energy sector. Moreover, the focus on carbon sequestration in standing forests is oddly disconnected from the fact that, over the past century, several EU Member states have managed to harvest ever larger amounts of forest, while simultaneously increasing both forest carbon stocks and the annual forest increment. This fact suggests we should more closely scrutinize the net annual contributions to the global carbon budget provided by the circular bioeconomy (avoided emissions, the net flux in forest-based carbon emissions/removals, or "net removals," and renewed forest growth). Reducing forest use intensity (i.e., annual harvest) may directly conflict with the pathway to increasing LULUCF-based climate change mitigation potential. Moreover, the mix of micro-level incentives created by the EU LULUCF policy framework may be incompatible with those public and private sector interests and investment goals that would otherwise underpin future forest growth potential. As evidenced by recent experience, the emphasis on reforestation and forest protection has provided marginal contributions to the European carbon budget, failing to encourage the kind of forest investment momentum required. Far greater contributions to the European carbon budget derive from Managed Forest Lands (MFL) but remain under-mobilized and even heavily restricted in the EU LULUCF policy framework. A more strategic approach is required to strike a meaningful balance between the need for protected, biodiverse-rich forest environments, on the one hand, and societal interests in the mitigation, human livelihood and consumption benefits forests and forest-based resources can provide.
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Towards a coherent protected area network – Priorities of protecting biodiversity in Finland (In Finnish with an English abstract) The objective of the Towards a coherent protected area network (KOKASU) project was to collect data for the national definition and implementation of the EU Biodiversity Strategy, which sets the target of protecting 30% of land and sea areas. The project gathered data produced by research and study projects and various processes and tapped a wide range of GIS data sources on the Finnish protected area network and its development needs. A key objective was investigating the current conservation status of the main biotopes and threatened species in land and sea areas and identifying gaps in the protection of biodiversity, in other words ecological features that are underrepresented in the Finnish network of protected areas, considering their threatened status or conservation needs identified by other means. In addition, an effort was made to outline regional priorities for protecting additional areas with the aim of improving the coherence and connectivity of the existing protected area network. The following main habitats were identified in the project: 1) forests, 2) mires, 3) rocky habitats, 4) coastal habitats, 5) fells, 6) traditional rural biotopes, 7) inland waters and shores, and 8) the Baltic Sea. Major variations regarding the need to protect different biotypes and species and conservation methods were found between these biotopes and species. For each habitat covered by the KOKASU report, gaps were found in Finland's current network of protected areas. A large number of threatened biotypes and species is found outside protected areas, and the report proposes urgently complementing the network of protected areas with them and, where possible, also improving connectivity between concentrations of biotopes and species. The report additionally identifies significant needs for ecological management and restoration of species and biotopes. Attention should also be paid to connections between habitats. For example, measures taken in the catchment areas of inland waters, especially those aiming to protect forest and mire biodiversity, also play a key role in improving the state of these waters. Southern and Central Finland are key areas for efforts to develop Finland's terrestrial protected area network. The areas with the greatest conservation needs associated with forests, mires, rocky habitats and scree, inland waters and shores as well as traditional rural biotopes are found to the south of Forest Lapland (in hemiboreal, southern boreal and middle boreal zones, and for the part of mires, in southern parts of the north boreal zone). Coastal and marine habitats in need of protection are found in the Gulf of Finland, the Åland Islands, the Archipelago Sea, Kvarken and the Bay of Bothnia. A significant part of the conservation needs in both land and sea habitats are associated with areas in private ownership. Consequently, incentives and different policy instruments for protecting private land and water areas are an important area of development. More detailed conservation needs related to certain better known biotopes or species could be identified regionally, however taking into consideration the bias of biotope and species inventory data, in other words their focus on protected areas. The best data are produced by methods that address the complementary nature and connectivity of sites, including the Zonation analyses carried out for the Baltic Sea in the KOKASU project. Due to bias and gaps in the data, presenting specific protection needs in hectares is difficult. This is why the KOKASU report refrains from setting conservation objectives in hectares. Instead, the report proposes measures for each habitat type with the aim of developing the Finnish protected area network and improving the status of biodiversity. The report also highlights some of the most significant information gaps. Keywords: Baltic Sea, biodiversity strategy, coastal habitats, fell habitats, forests, habitat type, inland waters, mires, protected areas, rocky habitats, seminatural grasslands, shores, species.
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Aim Many vertebrate species globally are dependent on forests, most of which require active protection to safeguard global biodiversity. Forests, however, are increasingly either being disturbed, planted or managed in the form of timber or food plantations. Because of a lack of spatial data, forest management has commonly been ignored in previous conservation assessments. Location Global. Methods We combine a new global map of forest management types created solely from remote sensing imagery with spatially explicit information on the distribution of forest‐associated vertebrate species and protected areas globally. Using Bayesian logistic regressions, we explore whether the amount of forested habitat available to a species as well as information on species‐specific threats can explain differences in IUCN extinction risk categories. Results We show that disturbed and human‐managed forests dominate the distributional ranges of most forest‐associated species. Species considered as non‐threatened had on average larger amounts of non‐managed forests within their range. A greater amount of planted forests did not decrease the probability of species being threatened by extinction. Even more worrying, protected areas are increasingly being established in areas dominated by disturbed forests. Conclusion Our results imply that species extinction risk and habitat assessments might have been overly optimistic with forest management practices being largely ignored so far. With forest restoration being at the centre of climate and conservation policies in this decade, we caution that policy makers should explicitly consider forest management in global and regional assessments.
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Aim of the report - This report aims to explore the importance of biodiversity in the context of European forests and to make suggestions on how this biodiversity can be effectively maintained and enhanced through protection, management and restoration. The term Europe in this document means European Union, except where mentioned otherwise. The report is meant for all kinds of decision-makers at the EU, national and local levels who are confronted with policy and management decisions related to biodiversity conservation and sustainable forest management. Although the primary focus is on the EU, most of the insights and recommendations made should be transferrable, with varying degrees of customisation where necessary, to non-EU countries as well. This report does not and cannot provide black and white guidelines on how to support forest biodiversity, rather it is designed to be a reference source for information and inspiration on the basics of forest biodiversity and forest biodiversity management. As such, it is a useful tool that highlights what is possible for evidence-based decision-making on this complex and dynamic matter. The report is purposely written and presented in a manner to stimulate dialogue on maintaining and restoring forest biodiversity while illuminating ways to bridge gaps between divergent viewpoints on the available options to avoid the loss of the irreplaceable and invaluable natural and cultural heritage inherent to European forest biodiversity.
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One of the essential tasks of sustainable forest management is to maintain native biodiversity. Primary forest research is one of the ways to understand what this biodiversity is. Matherials and methods. The primary, as confirmed by their land-use history and structural peculiarities, mesic dark-conifer forests remain in Visim and Pechora–Ilych nature biosphere reserves (boreal and sub-boreal zones respectively, the Ural Mountains, Russian Federation). We compared the primary forests and post fire 100-year small-leaved deciduous forests by diversity of vascular flora and soil invertebrate macrofauna. Results and discussion. The diversity of some functional groups of species (low boreal herbs, earthworms) in post fire forests is lower than in primary forests, the research shows. These species largely depend on deadwood and other tree-related microhabitats common in the primary forests but not so in the 100-year post fire forests. Repeated fires at intervals of several decades, as is the case with the use of prescribed fires in forest management, will be expected to reduce the biodiversity quality of these specialist species. Additionally, we revealed that post fire forest flora is more synanthropic in the woodland of a small area (Visim reserve) than in the intact forest landscape (Pechora–Ilych reserve). It demonstrates that, within extensive woodlands, native forests are more resilient to sporadic stand-replacing disturbances than small woodlands. Conclusion. Strict conservation of intact forest landscapes is necessary as they serve as large buffer areas around the remaining primary forests to maintain native biodiversity.
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Loss of forest naturalness challenges the maintenance of green infrastructure (GI) for biodiversity conservation and delivery of diverse ecosystem services. Using the Convention on Biological Diversity’s Aichi target #11 with its quantitative and qualitative criteria as a normative model, we aim at supporting landscape planning through a pioneering assessment of the extent to which existing amounts and spatial distributions of High Conservation Value Forests (HCVFs) meet these criteria. Highly forested and committed to both intensive wood production and evidence-based conservation targets of 17–20% protected areas, Sweden was chosen as a case study. Specifically, we estimated the amount, regional representation, and functional connectivity of HCVF patches using virtual bird species, validated the results using field surveys of focal bird species, and assessed conservation target fulfilment. Finally, we linked these results to the regional distribution of forest land ownership categories, and stress that these provide different opportunities for landscape planning. Even if 31% of forest land in Sweden is officially protected, voluntarily set-aside, or not used for wood production now and in the future, we show that applying the representation and connectivity criteria of Aichi target #11 reduces this figure to an effective GI of 12%. When disaggregating the five ecoregions the effective GI was 54% for the sub-alpine forest ecoregion, which hosts EU’s last intact forest landscapes, but only 3–8% in the other four ecoregions where wood production is predominant. This results in an increasing need for forest habitat and landscape restoration from north to south. The large regional variation in the opportunity for landscape planning stresses the need for a portfolio of different approaches. We stress the need to secure funding mechanisms for compensating land owners’ investments in GI, and to adapt both the approaches and spatial extents of landscape planning units to land ownership structure.
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Reducing the rate of global biodiversity loss is a major challenge facing humanity¹, as the consequences of biological annihilation would be irreversible for humankind2–4. Although the ongoing degradation of ecosystems5,6 and the extinction of species that comprise them7,8 are now well-documented, little is known about the role that remaining wilderness areas have in mitigating the global biodiversity crisis. Here we model the persistence probability of biodiversity, combining habitat condition with spatial variation in species composition, to show that retaining these remaining wilderness areas is essential for the international conservation agenda. Wilderness areas act as a buffer against species loss, as the extinction risk for species within wilderness communities is—on average—less than half that of species in non-wilderness communities. Although all wilderness areas have an intrinsic conservation value9,10, we identify the areas on every continent that make the highest relative contribution to the persistence of biodiversity. Alarmingly, these areas—in which habitat loss would have a more-marked effect on biodiversity—are poorly protected. Given globally high rates of wilderness loss¹⁰, these areas urgently require targeted protection to ensure the long-term persistence of biodiversity, alongside efforts to protect and restore more-degraded environments.
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Climate change and loss of biodiversity are widely recognized as the foremost environmental challenges of our time. Forests annually sequester large quantities of atmospheric carbon dioxide (CO 2), and store carbon above and below ground for long periods of time. Intact forests-largely free from human intervention except primarily for trails and hazard removals-are the most carbon-dense and biodiverse terrestrial ecosystems, with additional benefits to society and the economy. Internationally, focus has been on preventing loss of tropical forests, yet U.S. temperate and boreal forests remove sufficient atmospheric CO 2 to reduce national annual net emissions by 11%. U.S. forests have the potential for much more rapid atmospheric CO 2 removal rates and biological carbon sequestration by intact and/or older forests. The recent 1.5 Degree Warming Report by the Intergovernmental Panel on Climate Change identifies reforestation and afforestation as important strategies to increase negative emissions, but they face significant challenges: afforestation requires an enormous amount of additional land, and neither strategy can remove sufficient carbon by growing young trees during the critical next decade(s). In contrast, growing existing forests intact to their ecological potential-termed proforestation-is a more effective, immediate, and low-cost approach that could be mobilized across suitable forests of all types. Proforestation serves the greatest public good by maximizing co-benefits such as nature-based biological carbon sequestration and unparalleled ecosystem services such as biodiversity enhancement, water and air quality, flood and erosion control, public health benefits, low impact recreation, and scenic beauty.
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Facilitating “wildness” Humans have encroached upon a majority of Earth's lands. The current extinction crisis is a testament to human impacts on wilderness. If there is any hope of retaining a biodiverse planetary system, we must begin to learn how to coexist with, and leave space for, other species. The practice of “rewilding” has emerged as a method for returning wild lands, and wildness, to landscapes we have altered. Perino et al. review this concept and present a framework for implementing it broadly and in a way that considers ongoing human interaction. Science , this issue p. eaav5570
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Outcome-based targets are needed to achieve biodiversity goals.
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When management for old-growth characteristics in eastern forests first began to be discussed in the late twentieth century, there was skepticism from some quarters as to whether it was a desirable or even a feasible idea. Old growth will recover on its own. Why not just let nature take its course? There were also those who saw little value in managing for old-growth features, perceiving this as a threat to more traditional management objectives (Puettmann et al. 2015). Since that time, concepts of managing for stand structural complexity, in ways that encourage some characteristics of old-growth forests, have caught on in a variety of contexts (Bauhus et al. 2009; Puettmann et al. 2009). In many ways this shift mirrors how the profession has grown to embrace multifunctional forestry broadly defined (Gustafsson et al. 2012). Old-growth silviculture increasingly has a place within this framework, filling the niche of enhancing the representation of late successional forests on landscapes where they are now vastly underrepresented relative to their abundance on landscapes prior to Euro-American settlement (Lorimer and White 2003; Rhemtulla et al. 2007). The working hypothesis is that this type of management will contribute to sustainable forest practices focused on providing a broad array of ecosystem goods and services, including those associated with late successional systems. And in recent decades there has been increasing interest in old-growth restoration more narrowly and management for older forest characteristics in working forests generally, both in terms of experimental research (e.g., Keeton 2006; Gronewold et al. 2010; Forrester et al. 2013; Palik et al. 2014) and practical applications (Hagenbuch et al. 2013; Fassnacht et al. 2015).
There is a growing need to assess and monitor forest cover and its conservation status over global scales to determine human impact on ecosystems and to develop sustainability plans. Recent approaches to measure regional and global forest status and dynamics are based on remotely sensed estimates of tree cover. We argue that tree cover should not be used to assess the area of forest ecosystems because tree cover is an undefined subset of forest cover. For example, tree cover can indicate a positive trend even in the presence of deforestation, as in the case of plantations. We believe a global map of forest naturalness that accounts for the bio-ecological integrity of forest ecosystems, for example, intact forests, old-growth forest patches, rewilding forests (exploited forest landscapes undergoing long-term natural succession), and managed forests is needed for global forest assessment. © 2019 Society for Conservation Biology.