Impact of the EU biodiversity strategy for 2030 on the EU
wood-based bioeconomy
Fulvio Di Fulvio a,*, Tord Snall b , Pekka Lauri a, Nicklas Forsell a, Mikko Monkkonen c,d ,
Daniel Burgas c,d , Clemens Blattert c,e , Kyle Eyvindson f,g , Astor Tora~no Caicoya h,
Marta Vergarechea i , Clara Anton-Fernandez i , Julian Klein b , Rasmus Astrup i,
Jani Lukkarinen j , Samuli Pitzen j , Eeva Primmer j
a Integrated Biosphere Futures (IBF) Research Group, Biodiversity and Natural Resources (BNR) Program, International Institute for Applied Systems Analysis (IIASA),
Schlossplatz 1, 2361 Laxenburg, Austria
b SLU Swedish Species Information Centre, Swedish University of Agricultural Sciences, P.O. Box 7007, 75007 Uppsala, Sweden
c Department of Biological and Environmental Sciences, University of Jyvaskyla, P.O. Box 35, 40014 Jyvaskyla, Finland
d School of Resource Wisdom, University of Jyvaskyla, P.O. Box 35, 40014 Jyvaskyla, Finland
e Forest Resources and Management, Swiss Federal Institute for Forest, Snow and Landscape Research WSL, Zürcherstrasse 111, 8903 Birmensdorf, Switzerland
f Faculty of Environmental Sciences and Natural Resource Management, Norwegian University of Life Sciences, P.O. Box 5003, 1433 Ås, Norway
g Natural Resource Institute Finland (LUKE), Latokartanonkaari 9, FI-00790 Helsinki, Finland
h Chair of Growth and Yield Science, TUM School of Life Sciences, Hans-Carl-von-Carlowitz-Platz 2, 85354 Freising, Germany
i Department of Forest Management, Division of Forest and Forest Resources, National Forest Inventory, Norwegian Institute for Bioeconomy Research (NIBIO),
Høgskoleveien 8, 1433 Ås, Norway
j Finnish Environment Institute (Syke), Latokartanonkaari 11, FI-00790 Helsinki, Finland
A R T I C L E I N F O
Keywords:
Bioeconomy
Wood harvest
Protection
Biodiversity
Modelling
Forest sector
Leakage
A B S T R A C T
The EU Biodiversity Strategy (EUBDS) for 2030 aims to conserve and restore biodiversity by protecting large
areas throughout the European Union. A target of the EUBDS is to protect 30 % of the EU’s land area by 2030,
with 10 % being strictly protected (including all primary and old growth forests) and 20 % being managed ‘closer
to nature’. Even though this will have a positive impact on biodiversity, it may negatively impact the EU’s wood-
based bioeconomy. In this study, we analyze how alternative interpretations and distributions of the EU’s pro-
tection targets may affect future woody biomass harvest levels, exports of wood commodities, and the spatial
distribution of managed areas under wood demands aligned with SSP2-RCP1.9. Using the model GLOBIOM-
Forest, we simulate scenarios representing a variety of interpretations and geographic distributions of the
EUBDS targets. The EUBDS targets would have a limited impact on EU harvest levels since the EU can still in-
crease its wood harvest between 21 % and 24 % by 2100. With strict protection of 30 % of the area, the EU
harvest level can still be increased by 10 %. Moreover, the most likely scenario (10 %/20 % protection within
each MS) will result in increased net exports in the coming decades, but a slight decline after 2050. However, if
protection is intended to also represent site productivity or to re-establish a green infrastructure, then EU net
exports will also decline before 2050. With the decreased EU roundwood harvest, increased harvest will occur in
other biomes and mostly leaking into boreal regions.
1. Introduction
Forest-based bioeconomy aims to utilize forest resources to replace
fossil-based rawmaterials and products (Wolfslehner et al., 2016). In the
EU, forest resources and associated bioeconomy are controlled by
several policy instruments, including those recently formulated under
the European Green Deal (Aggestam and Giurca, 2021, Lier et al., 2021).
As many of these instruments are still in the revision process, it would be
difficult and premature to investigate the overall impact of the Green
Deal on the EU forest-based bioeconomy. There are, however, some
aspects of the Green Deal that are already well documented and could be
investigated. One of them is the EU Biodiversity Strategy for 2030
* Corresponding author.
E-mail address: difulvi@iiasa.ac.at (F.D. Fulvio).
Contents lists available at ScienceDirect
Global Environmental Change
journal homepage: www.elsevier.com/locate/gloenvcha
https://doi.org/10.1016/j.gloenvcha.2025.102986
Received 30 January 2024; Received in revised form 18 November 2024; Accepted 28 February 2025
Global Environmental Change 92 (2025) 102986 
Available online 11 March 2025 0959-3780/© 2025 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY license ( http://creativecommons.org/licenses/by/4.0/ ). 
(EUBDS), which addresses the current trends in biodiversity decline and
sets a path to recovery (IPBES, 2019, Leclere et al., 2020). This plan
includes a target to protect 30 % of EU land and sea areas by 2030 (EC,
2020a, b), of which one third (10 %) should be strictly protected and
include all primary and old-growth forests. The remaining two thirds
(20 %) should be under what is labelled as “closer-to-nature” manage-
ment (Larsen et al., 2022). Currently, 23.3 % of EU forests are protected,
including 4.7 % strictly protected and 18.6 % protected in other non-
strict ways (WDPA, 2020).
To reach the EUBDS targets, many EU Member States (MS) need to
adjust their land management and policies. However, the spatial dis-
tribution of protection within the EU has not been specified in the
EUBDS. There are indeed ongoing scientific and political discussions
concerning the spatial distribution of future protected areas (Hermoso
et al., 2020) and the ways in which efforts to increase protection should
be coordinated among the EU MS. In the current EU discussions, an
equal allocation is considered at the level of countries or biogeograph-
ical regions (EC, 2022), but other distributions are also plausible since
the EUBDS also includes objectives at the finer landscape scale. This is
formulated as “green infrastructure”, a “strategically planned network of
natural and semi-natural areas with other environmental features,
designed and managed to deliver a wide range of ecosystem services,
while also enhancing biodiversity” (EC, 2013). Thus, MS are encouraged
to conserve, manage and restore sufficient areas of functional habitat
networks to support viable species populations and their migration. This
should be achieved by protected areas, including the Natura 2000
network (EC, 2013, 2019a), sustainable forest management, as well as
‘closer to nature’management. The latter is currently defined only at EU
scale (EC, 2023a) and needs to be translated into MS guidelines and local
management practices. Additionally, its implications in terms of
providing wood, non-woody ecosystem services and biodiversity require
thorough assessment.
Another key role of EU forests described in the EU Green Deal is the
contribution to reach climate neutrality by 2050 (EC, 2019b, EC,
2021a), given their ability to absorb and store large amounts of carbon
(EEA, 2020a). Combined, climate and conservation policies may create
synergies and increase the overall environmental and socioeconomic
sustainability. However, forests can be used for climate change mitiga-
tion in contrasting ways, namely to sequester carbon on the forest land
(Griscom et al., 2017), store carbon in long-lived wood products (Mishra
et al., 2022) and replace fossil fuel-based products and energy sources
(Hurmekoski et al., 2023). The emphasis placed on the different climate
mitigation functions vary across policy domains (Pitzen et al., 2023).
Mitigation through woody biomass uses in the bioeconomy may conflict
with environmental sustainability and biodiversity conservation
(Blattert et al., 2023, Mazziotta et al., 2022), due to potential manage-
ment intensification (Betts et al., 2021). Forest growth, harvest and
management vary widely across the EU as well as the future CO2
sequestration trajectories of EU member states (Pilli et al., 2017, Pilli
et al., 2022).
Achieving the EUBDS protection targets in the EU may have spill-
over effects in other parts of the world where wood is imported from
(Rosa et al., 2023, Cerullo et al., 2023), with an increased risk of failing
to achieve the targets of the Kunming-Montreal Global Biodiversity
Framework (GBF, 2022). The reason is so-called leakage when
decreased harvest in one region results in increased harvest elsewhere to
meet the same wood demands. For example, Kallio et al. (2018) iden-
tified leakage when constraining EU wood harvest levels. However, they
solely studied leakage given different country-level harvest, thus not
varying neither management regimes nor areas protected within and
among countries, both of which are key components of the EUBDS and
further likely affecting leakage.
Protection according the EUBDS targets could have considerable
impacts on the EU forest sector. Lotze-Campen et al. (2018) suggested a
13 % reduction in EU roundwood harvest potential when expanding the
network of EU protected areas. However, they limited their analyses to
year 2040 and simulated scenarios without any link to the EUBDS tar-
gets or the EU climate neutrality. Indeed, Schier at al. (2022) disclosed
that EU roundwood harvest may be reduced by 9 %-48 % by 2030 and
11%-58% by 2050when considering scenarios aligned with the EUBDS.
However, they studied solely Germany and extrapolated the results to
the rest of the EU without considering the very large spatial variation in
allocation of protected areas and wood production.
Forest sector models provide an appropriate tool to investigate the
impacts of polices on global resources use and bioeconomy while
studying the complex dynamics of forest sector. Such models include
aspects of forest management, forest industries, spatial explicit wood
production costing as well as trade patterns, and enable the connection
between wood supply and demands (Toppinen and Kuuluvainen, 2010,
Latta et al., 2013, Riviere and Caurla, 2020). The forest sector Global
Biosphere Management Model GLOBIOM (Havlík et al., 2011, Lauri
et al., 2021) simulates management regimes and protection areas
spatially explicitly at a 50 km2 scale in the EU and at a coarser resolution
globally. The model accounts for forest growths in each simulation unit
and intensity of harvest according to management regimes applied
within each unit. Hence, this model structure enables to simulate how
changing distribution of management regimes would affect harvest,
forest industry production and global trade in a consistently connected
way. Further, GLOBIOM allows to capture potential wood harvest
leakages in other global regions through wood trade.
The overall aim of this study is to investigate effects of alternative
approaches to protect forests under policy targets aligned to the EUBDS
on woody biomass harvest, considering also leakage outside the EU on
different spatiotemporal scales. We contrast six scenarios of increased
protection against a baseline scenario of unchanged protection. We
quantify the leakage outside EU resulting from increased protection,
including biomes that can be expected to compensate for the conse-
quential decreased harvest within the EU. The spatially explicit sce-
narios differ in terms of how the protection is distributed among: EU
member states, biogeographic regions, forest productivity across the
green infrastructure, and combinations thereof. We further conduct a
sensitivity analysis assuming a stricter interpretation of the conservation
policy where all 30 % of the forest land is strictly protected. We use the
state-of-art forest sector model GLOBIOM for simulating forest man-
agement and the resulting impacts on wood harvest and trade under
each of the seven forest protection scenarios until year 2100.
2. Material and methods
2.1. Modelling approach
The scenario simulations were conducted using the Global Biosphere
Management Model (GLOBIOM) (Havlík et al., 2011, 2014),a global
spatially-explicit agricultural and forest sector model. The model is
solved recursively for each 10-year time step by maximizing the eco-
nomic welfare, defined as the sum of the producer and consumer eco-
nomic monetary surplus (S.M4). Here we specifically used GLOBIOM-
forest, which includes forestry, forest industry and bioenergy modules,
as described in Lauri et al. (2019, 2021, S.M1), but where the agricul-
tural sector is simplified to include just one product, energy crops (S.
M5). The wood supply in the EU region is modelled on a 0.5 grid (ca. 50
km2) while the demand and trade are modelled using 57 economic
global regions (including 28 EU Member states as single regions, see
Table S.M3.2), where wood supply in regions outside EU is modelled at
the resolution of 2.0 (ca. 200 km2). Land-use and land-management
change is modelled according to linear land-use and land-management
change costs functions following the approach of Havlík et al. (2011).
Woody biomass supply is based on spatially explicit harvest poten-
tials, harvest costs, transportation costs and forest-/management-regime
specific land-use change costs. The harvest costs are based on G4M
output and transportation costs on Di Fulvio et al. (2016). The initial
forest conditions for starting our simulations (year 2020) and economic
F.D. Fulvio et al. Global Environmental Change 92 (2025) 102986 
2 
optimizations match FRA (2020) country level data on forest area,
standing biomass stocks, the World Database of protect areas (WDPA,
2020) grid level data, Global Forest Management Map (Lesiv et al.,
2022) grid level data. These constitute the basis for the forest types
generation and assignment of forest management regimes (S.M1). Sus-
tainable harvest potentials are based on MAI (Mean Annual Increment)
for each grid cell, as simulated with the Global Forest Model G4M
(Kindermann et al., 2006, 2008; Gusti and Kindermann, 2011). More-
over, for the historical periods 2000–2020, management areas are scaled
to match with FAOSTAT country level harvest volumes (FAO, 2023).
Using G4M data and global age-class database (Besnard et al., 2021), the
model generates initial grid level biomass growth curves and structures,
that are subsequently calibrated to the country level biomass stocks.
Within each grid cell, the model can have different management regimes
with different age-class dynamics, mortality and harvest intensity. After
2020, the age-class dynamics develops endogenously and the model is
not allowed to harvest more than long term biomass growth, represented
by the mean annual increment (MAI).
GLOBIOM-forest applies three management regimes (close to nature,
multifunctional, high intensity) and three main forest types (primary,
managed and secondary forests), each characterized by two species
groups (conifer/broadleaf). Primary forests have not been used histori-
cally for wood production, managed forests are currently used for pro-
duction while secondary forests are abandoned managed forests. The
management regimes in GLOBIOM forest differ in the proportion of MAI
that can be harvested. In high intensity management, the whole MAI can
be harvested while in multifunctional and close to nature management,
only a part of it can be harvested, up to a maximum threshold set for
each management regime (Table 1). Consequently, harvest volume can
be changed in each simulation grid cell by changing the managed forest
area, the forest management regime or by changing the share of MAI
harvested within each management regime.
In all scenarios simulated, the EU (EU27 and UK, hereafter referred
as EU) forest area was fixed at 164 M ha, following FRA (2020) forest
cover harmonization. For Norway, the forest area was fixed at 12.8 M ha
following FRA (2020). The total area available for management was kept
constant over time.
After the initialization of starting year 2000, the allocation of area
shares to the four management classes in each grid cell 2000–2100 was
controlled endogenously by the model and based on the economic
optimization (i.e. maximization of economic surplus), aiming to fulfil
demands for wood at national level under each scenario.
GLOBIOM-forest includes 26 wood-based products, five harvested
products and deadwood. These includes as an example four paper and
paperboard grades, four pulp grades, three mechanical forest industry
products, four forest industry by-products and two recycled products (S.
M1). Bioenergy includes traditional fuelwood, woodchips and wood
pellets. Forest industry and wood pellets production capacities are based
on FAOSTAT production data for 2000–2020 (FAO, 2023). Final product
demands are based on constant elasticity demand functions, which are
parametrized by reference volumes, reference prices and elasticity co-
efficients. Exceptions are modern bioenergy demand, which is based on
the socio-economic and climate pathways (SSP-RCP), sourced from the
MESSAGE energy model (IIASA, 2020), and the traditional bioenergy
demand, which is assumed to stay constant over time. After 2020, the
demand volumes change over time based on gross domestic product
(GDP) development and human population growth following the SSP-
RCP scenario data (Riahi et al., 2017, IIASA, 2020). Trade is modelled
by using bilateral trade flows. Bilateral trade calibration volumes are
based on the BACI trade database for 2000–2020 (Gaulier and Zignago,
2010). After 2020, trade volumes evolve following trade dynamics,
which depend on constant elasticity trade-cost functions parametrized
by historical trade volumes and transport costs.
2.2. Protection scenarios
We simulated six scenarios on how to reach the EUBDS protection
targets for 2030, contrasting them against a scenario of no change in
protection, termed Current protection (Table 2). All scenarios assumed
national timber demands for mitigating climate change aligned with the
EU Green Deal policy package and the aim that EU should become
climate neutral by 2050 (IIASA, 2020). In GLOBIOM, this is imple-
mented as a bioenergy demand from the MESSAGE model (Riahi et al.,
2017) following a 1.5 degrees warming scenario (RCP1.9) and a socio-
economic development following a “middle of the road” (SSP2) until the
year 2100. This leads to an increased EU woody biomass demand of 31
% during 2020–2100 (IIASA, 2020), see also Sensitivity analyses.
The model was first run for a calibration period of 20 years
(2000–2020), where it was forced to reproduce the harvest volumes for
this period according to FAOSTAT (FAO, 2023). Next, the model was run
recursively until year 2100 in 10 years-time steps. The protection sce-
narios were implemented after year 2020, i.e. in year 2030.
2.3. Sensitivity analyses
We investigated effects of a stricter interpretation of the conservation
policy objective compared to the main scenarios (Table 2) by applying
‘30 % strict protection’, i.e. no harvest, on the total 30 % of forests under
future protection. We also investigated effects of assuming lower in-
crease in future EU wood demands (8 % increase during 2020–2100
instead of 31 %). This could reflect a broad combination of socioeco-
nomic growth (SSPs) and climate development (RCPs), reducing the
expected increasing rate of wood demand in the future, similarly to
assuming ‘RCP6.5′ instead of RCP1.9 (Lauri et al. 2019). The sensitivity
analyses were applied to three main scenarios: EU, Country, Green
infrastructure.
Table 1
Management regimes calibration and parametrization in the simulated EU
protection scenarios (S.M1-2).
Management
regime
Area,
year
2020
(Mha)
Area calibration
method
Maximum
allowed
roundwood
volume
harvest
(% MAI)
Maximum
allowed
logging
residues
harvest
volume
(%
Potential)
Strict
protection
7.8 Primary forests
allocated
according to Lesiv
et al. (2022),
National level
area matching to
FRA, 2020.
Strict protection
forest areas
according to IUCN
categories Ia, Ib,
II, III (WDPA,
2020).
0 0
Closer to nature 30.5 Non-strictly
protected forests
(IUCN classes IV-
V-VI, S.M2) within
the Natura2000
network (WDPA,
2020)
50 0
Multifunctional 92.7 Residual after
assigning all the
other classes.
75 25
High intensity 32.6 Planted forests
according to Lesiv
et al. (2022)
100 50
F.D. Fulvio et al. Global Environmental Change 92 (2025) 102986 
3 
2.4. Leakage effects of biodiversity protection scenarios
Given the scenarios for protection within the EU, we finally also
investigated how changes in future harvest levels within the EU may
affect wood harvest in other biomes. Leakage means that a decrease of
production or biophysical activity in one region is offset by an increase
of production or biophysical activity in other regions (S.M3.3). We
quantified leakage by absolute harvest volumes (increased harvest in
other biomes) or by rates (overall change in other regions relative to the
EU). Specifically, we investigated leakage of roundwood harvest and
production of semi-finished wood products.
3. Results
3.1. Protected forest area in Europe
The EU scenario, collectively reaching the policy objectives at EU
level, would mean doubling the forest area under strict protection and
increase the area under a ‘closer-to-nature’ management by 1 %
compared to Current protection (Table 3). All other scenarios would
mean protecting larger proportions of the area than 10 % and 20 %
across all the EU (Table 3). The Green Infrastructure scenario means
protecting the largest area, with an 8 % increase of the forest area under
strict protection, compared to the EU scenario. This is explained by the
current protection area of some simulation units already exceeding the
unitary protection targets, while at the same time increasing the pro-
tection area in other units, summing up to protecting 13 %/25 % at EU
scale (Table 3).
Under the Current protection scenario, there will be a 22 % expan-
sion of high intensity forest management, increasing by 22Mha between
2020 and 2100, with a parallel reduction of multifunctional manage-
ment (Fig. 1). This intensification trend in unprotected forest areas is
driven by the increasing wood demands under the climate neutrality
assumed for all simulated scenarios. The six scenarios with expansion of
protected areas reduce the areas available for other types of manage-
ment (multifunctional and high intensity) (S.R2.1). Relative to the
Current protection scenario, the increase in protected area of the Green
Infrastructure scenario (Fig. 1), firstly reduces the areas under both
multifunctional and high intensity management. Later, the development
is similar to Current protection with an increase of high intensity man-
agement at the cost of decreasing multifunctional management. The
other scenarios will fall between these two extremes.
3.2. Distribution of forest protected area
The EU scenario, collectively reaching the policy objectives means
increasing strict protection in countries where wood production gives a
relatively low profit (Fig. 2). Bulgaria, Ireland, Italy, Netherlands, and
Romania would protect more than 15 % of their forest area, while
countries like Finland and Sweden instead would contribute minimally
(Fig. 2). This contrasts the Country scenario, where strictly protected
areas are evenly distributed among all the EU countries. The same holds
true under the Green Infrastructure scenario, although leading to a
higher overall protection (Fig. 2, Table 3. S.R2). In some countries (e.g.
Portugal, Spain), the Country scenario means decreased ‘closer to na-
ture’ management compared to Current protection. This is due to areas
changing into becoming strictly protected within the country and can
even lead to a net increase in the total protected area. This results from
our assumption that new strictly protected areas are preferably distrib-
uted to areas that are currently under close to nature management.
3.3. Harvested volume and wood prices
The EU biomass harvest volume (sum of roundwood and logging
residues) projected under the Current protection scenario (and aiming
for climate neutrality) is expected to increase by 31 % during
2020–2100, and by 10 % already by 2030 (Fig. 3). Compared to Current
protection, the EU scenario will reduce harvest by 1 % in 2030 and 3 %
by 2100. A harvest reduction of 5–7 % by 2100 is projected if additional
protection is distributed equally among biogeographical regions or
countries. However, if the additional protection is distributed equally
Table 2
Assumptions of the six protection scenarios simulated.
Scenario name Description
Current protection Maintains current EU protection areas.
EU An economy-driven scenario. Protection is distributed to
land where it has the least impact on economy in terms
of wood production and harvested wood products
within the EU. Areas that are currently least profitable to
harvest are progressively moved to strict protection and
‘closer-to-nature’ management until the 10 %/20 %
target is reached. Forest areas mapped in each grid cell
as potential primary forests (7.5 Mha in EU) in Sabatini
et al. (2020) were excluded from future management.
Biogeographical region
(BioGeo)
As EU, but objectives are achieved for each EU
biogeographical region. This scenario aims to reach
representativeness of the EU biogeographical regions in
the allocation of protection.
Country As EU, but objectives are achieved for each EU country.
This scenario aims for equal distribution of protection
areas in each EU country, and it is the intended
implementation according to the EU Guidelines (EC
2022).
Country BioGeo As EU, but objectives are achieved for both each EU
country and EU biogeographical region. This scenario
aims to reach representativeness of the EU
biogeographical regions in the country-level allocation
of protection.
Country Productivity As Country BioGeo, but allocation of protection within
countries so that protected and unprotected forests have
the same country-level mean productivity (including
both new and areas protected already in 2020). This
scenario aims to distribute protection to not only the
least profitable land, but considers also
representativeness concerning productivity (affecting
biodiversity) and EU Habitat types.
Green Infrastructure As EU, but allocation of the 10 %/20 % protection target
within each grid cell (0.5). This scenario aims to
distribute protection to rebuild the EU green
infrastructure and facilitate dispersal and migration of
species.
Table 3
Strictly protected forest and ‘closer to nature’ management given EU protection scenarios.
Scenario Strictly protected
(Mha)
Closer to nature management
(Mha)
Strictly protected
(% of total forest area)
Closer to nature management
(% of total forest area)
Current protection 7.8 30.5 5 % 19 %
EU 16.2 32.5 10 % 20 %
BioGeo 16.8 36.1 10 % 22 %
Country 16.6 37.1 10 % 23 %
Country BioGeo 17.5 37.2 11 % 23 %
Country Productivity 16.6 38.5 10 % 23 %
Green Infrastructure 20.7 40.6 13 % 25 %
F.D. Fulvio et al. Global Environmental Change 92 (2025) 102986 
4 
Fig. 1. Development of the proportion of EU forest area (of total forest area) managed by different regimes from year 2020 to 2100 assuming the Current protection
and Green Infrastructure scenarios. (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.)
Fig. 2. Share of forest area protected in different EU countries (incl. UK and Norway) from year 2030 onwards assuming different scenarios of strict protection and
close to nature management.
F.D. Fulvio et al. Global Environmental Change 92 (2025) 102986 
5 
among the 0.5 grid cells, Green Infrastructure, the reduction will be
higher (6 % by 2030 and 9 % by 2100), simply because a larger area is
protected (Table 3, Fig. 2). Nevertheless, all scenarios that increase
protection will allow to increase EU harvest by at least 21 % (increasing
from Current protection to Green Infrastructure; Fig. 3).
The impact of protection scenarios on wood assortment prices for the
EU follows the same order as the one obseved for harvest volumes (S.
R5). Under the EU scenario, we observe increases in prices of 2–4% until
2030 compared to the Current protection scenario. Under the Country
scenario the increases are 6–15 % and under the Green Infrastructure
prices increase between 10–30 %. Conifer wood assortments tend to be
more impacted than broadleaves and the price increase is transient and
declines over time.
3.4. Distribution of harvest volume among countries
Independently of protection scenario, individual countries will
generally increase their future harvest by 2100 (4a-b), albeit less than
with Current protection (Fig. 4c-d). The changes over time in harvest
volumes will range between  28 % (Czech Republic) and ‡ 125 %
(Luxembourg).
Five out of the six countries with the largest harvest volumes by 2100
(Germany, Finland, France, Poland and Romania) (Fig. 4, S.R3) will
maintain or increase harvest levels in the long term with all protection
scenarios, but in short term (2030), Germany and Sweden could expe-
rience a 6–12 % harvest reduction compared to the current levels under
the Green Infrastructure scenario. The proportional impacts of the pro-
tection scenarios on harvests are generally higher on single countries
than on the whole EU (cf. Fig. 3 and Fig. 4). For example, the EU level
harvest reductions would reach 9 % under the Green Infrastructure
scenario, while for individual countries this would range between 0–17
%. However, this conclusion concerns comparison with the Current
protection scenario and year 2100 with assuming strong harvest in-
crease overall (Fig. 3). If we would compare year 2100 to current harvest
levels (2020) under the Green infrastructure scenario, we find harvest
increase by 20 % at EU level, but between  28 % and ‡ 105 % at na-
tional level.
Compared to Current protection, the EU scenario means larger re-
ductions (more than 5Mm3 in 2100) for only one country (France; 4c-d),
while with the Green infrastructure scenario particularly the Northern
countries and countries with large wood harvest volumes will be
affected (4c-d). However, harvests in the Northern countries will still be
similar to current level (4b). In the Country scenario, the country-level
relative impact is lower, as more countries are involved in reaching
the protection target. In this scenario, impacts over 5 Mm3 are projected
for Germany, Poland, Finland and Sweden. Whereas, with the Green
Infrastructure scenario, impacts over 5 Mm3 are projected for Sweden,
Poland, Finland, Germany, France and Norway.
3.5. Net export and wood industry production
In year 2020, the EU was a net importer of roundwood biomass ( 18
Mm3 in 2020), and will remain being importer independently of sce-
nario (Fig. 5a). However, because of increasing harvests under all sce-
narios (Fig. 3), we project reduced roundwood net import rate towards
2100. Regarding semi-finished wood products, the EU was instead a net
exporter (57 Mm3 in 2020) (Fig. 5b). When summing the historical
roundwood and semifinished products net exports (Fig. 5c), the EU was
instead a net exporter of 39 Mm3 in 2020. The trade advantage in semi-
finished products is expected to continue to grow until 2040 and
thereafter decline, due to increased competitiveness of other regions
(South America, Asia). The impact of increased protection on the net
export closely reflects the impacts on the EU biomass harvest volumes
(Figs. 3-5). Net export of semi-finished products will decline under
current levels in most scenarios after year 2040, whereas the EU scenario
would allow to maintain current export levels. By 2100, the net export of
semi-finished products would decline with 4 Mm3 under the Country
scenario and with 21 Mm3 under the Green Infrastructure scenario,
compared with the current level (Fig. 5b). Nevertheless, under all sce-
narios EU would remain a net exporter of semi-finished wood products.
Among the major wood production countries (Germany, Finland,
France, Sweden), all protection scenarios will reduce the net export,
given their expected future decreased economic competitiveness within
the EU (S.R3). In parallel, other major wood-producing countries are
Fig. 3. Development of yearly forest biomass (including roundwood and logging residues) harvest volumes in the EU under SSP2-RCP1.9 and the protection sce-
narios simulated in absolute volumes (left) and as relative changes compared to the year 2020 (right).
F.D. Fulvio et al. Global Environmental Change 92 (2025) 102986 
6 
expected to increase their competitiveness, as a result of their expected
economic growth (Poland, Romania).
Net export of semifinished products is closely related to the industrial
production levels. The changes in production of the main semifinished
products categories (sawnwood and woodpulp) reflect the order of
scenario impacts and magnitude for harvest volumes in EU (Fig. S.R3.7).
However, among the main producing countries, Sweden is unable to
maintain current sawnwood and wood pulp production under the
Country and the Green Infrastructure scenarios. Similarly, Germany
experiences a reduction of sawnwood production under these scenarios,
while the other major wood producers are still able to maintain or in-
crease their levels (Fig. S.R3.8-Fig S.R3.10). French woodpulp produc-
tion is more strongly affected under the EU scenario compared to the
Country scenario (Fig S.R3.10), and oppositely to the other major pro-
ducers, the Country and Green Infrastructure scenarios are more im-
pactful than the EU scenario.
The EU was historically a net importer of wood pellets ( 30 Mm3 in
2020). The net export of wood pellets is projected to become more
negative over time under all scenarios (Fig. 5d), because of the expected
bioenergy demand increase under RCP1.9 which cannot be satisfied by
increased harvest from EU forests. Hence, there is a larger increase of
woodpellets import from other global regions. Compared to the Current
protection scenario, the protection scenarios will lead to a 3–6 %
decrease in wood pellets net export towards year 2100 (i.e. import in-
crease by 1–2 Mm3) (Fig. 5d).
3.6. Sensitivity analyses
Assuming strict protection of 30 %, instead of 10 % of the EU forest
area, the biomass harvest would decline by 10–15 % compared to the
Current protection scenario in year 2100 (Fig. 6a). However, also with
this high protection level, the harvest would increase compared to
today. Nevertheless, the harvest reduction given by 30 % strict protec-
tion combined with the Green Infrastructure scenario is large enough for
EU to become a net importer after 2040 (Fig. 6b). With all other sce-
narios simulated, the EU would remain a net exporter albeit at a lower
level than with Current protection.
If instead assuming lower future demand for wood, i.e. following
climate change mitigation leading to the RCP6.5, EU harvests may still
somewhat increase in the coming decades under all scenarios. Moreover,
Fig. 4. Change in harvest volumes per country in 2100 for three protection scenarios when comparing to year 2020 in absolute (A) and relative values (B), and when
comparing in year 2100 to the Current protection scenario in absolute (C) and relative values (D) under SSP2-RCP1.9.
F.D. Fulvio et al. Global Environmental Change 92 (2025) 102986 
7 
harvest could possibly decrease (2–6 %) with protection scenarios
compared to the RCP6.5 Current protection scenario (Fig. 6c). Net-
export would follow a similar development as for the main scenarios
until 2060, and thereafter continue to decrease sharply, though remain
positive until 2100 (Fig. 6d).
3.7. Leakage outside EU and in other sectors
Up to 79 % of the decreased roundwood harvest within the EU
resulting from the protection scenarios would result in increased harvest
in the rest of the world (Table 4, Fig. 7). This relative change is hereafter
referred as EU leakage rate. Specifically, the average leakage rate in EU
roundwood harvest ranged between 22–79% (Table 4, Fig. 7). However,
this is compared to the Current protection scenario, which assumes a
large harvest increase in the future (Fig. 6). The leakage is immediate,
but also transient resulting from new equilibria reached after the middle
of the century.
During the coming 40–50 years, the leakage only affects harvest in
the boreal parts of the world, with negligible impact on the tropics or the
temperate region (Fig. 7). After 2060, the contribution of the tropical
region starts to increase, going from 10 % to 20 %, in parallel to a
decreasing contribution from the boreal region toward the end of the
century (Fig. 7, S.R4).
The relatively lower leakages after the middle of the century are
caused by a contraction of the global roundwood harvest rate (Fig. 8A).
This is driven by the development in bioenergy feedstock in the rest of
the world, where a substitution of roundwood by wood pellets from
energy crops is projected to take place (Fig. 8B). However, the relative
effect of the EUBDS protection on these future leakages is rather low,
and the trade dynamics are mainly driven by historical trade de-
velopments and GDP growth.
Hence, we note two complementary effects, on one hand a global
contraction of roundwood harvest takes places reaching 50 Mm3 in the
most ambitious protection scenario (30 % Green Infrastructure). On the
other hand, harvest from energy crops increases and reaches a maximum
of 45 Mm3 under the same scenario (Fig. 8). Another leakage effect is
endogenously considered in the model, with an intensification of forest
management in unprotected forest areas within the EU.
4. Discussion
We present the impacts of alternative spatial allocations of protected
areas according to the EU Biodiversity Strategy (EUBDS) on the EU
forest sector, considering specifically wood harvest and wood-based
Fig. 4. (continued).
F.D. Fulvio et al. Global Environmental Change 92 (2025) 102986 
8 
industry developments. We provide a seamless understanding of impli-
cations of different interpretations of targets, including spatial trade-
offs, EU external impacts and a global perspective. We show that the
EUBDS will have a larger risk of impact on the forest industries than on
harvest levels, and further that these risks concern the last half of the
century. Implementation of the EUBDS in fact still allows for an increase
of the EU forest harvest level by 21 % to 31 %, depending on the spatial
distribution of the EUBDS targets. We expected the EUBDS protection to
have larger impact on the EU forest industries net export of roundwood
and semifinished products. However, the most likely scenario (10 %/20
% protection within each MS) means increased net exports than current
ones in the coming decades, but slightly lower after 2050. With pro-
tection also aiming to be representative of site productivities or re-
building the green infrastructures, net exports decreased also during
the coming decades. The study also allowed to show that the leakage
resulting from decreased EU roundwood harvest (ca. 80 % of the
decrease) will correspond to higher harvest in boreal regions outside the
EU, but a minor increase in tropical regions.
In terms of total EU woody biomass harvest levels, we show that an
implementation of the EUBDS would have limited impact. At the EU
level, we project that harvesting can increase by 24% between 2020 and
2100 with implementation at the EU level, and by 21 % with the green
infrastructure implementation. A very strict interpretation of ‘closer-to-
nature’ management, i.e. strict protection and hence excluding 30 % of
the land from harvesting, would restrict harvest more, but still allow for
higher future harvests than today (10 % increase). Nevertheless, our
scenarios did not account for potential impacts of increased harvests on
non-timber ecosystem services and biodiversity outside protected areas.
Increasing harvest to strive for climate mitigation targets might cause
adverse effects on forest multifunctionality (Blattert et al., 2023), which
Fig. 5. Development of EU net export of different wood assortments under SSP2-RCP1.9 and different protection scenarios, specified by roundwood(e.g. sawlogs,
pulpwood) (A), semi-finished products (eg. sawnwood, woodpulp) (B), total net export (sum of roundwood (A) and semi-finished products (B) (excluding wood-
pellets), C) and woodpellets net export (D).
F.D. Fulvio et al. Global Environmental Change 92 (2025) 102986 
9 
is a central objective of the EU Forest Strategy (EC, 2021b). Future
studies should take this multifunctional view into account while
exploring the interplay of protection and mitigation policies.
Our findings of 2 % to 6 % harvest reductions by 2050 contrast the
recent study of Schier et al. (2022) who claimed an overall harvest
reduction of 11–58 % by 2050 for the EU27 compared to a baseline
development that aligns to our RCP6.5. The main reason for the differ-
ence is that they applied a stricter definition of “old-growth” forest
adopting variable age thresholds (i.e. more than 120 years for Norway
spruce and 160 years for oaks) for identifying old growth forests and
further excluding them from wood harvesting in the future. Such an age-
based identification of “old growth” forests implies that any forests that
over time reaches the threshold automatically becomes protected. We
believe that this overestimates impact of the EUBDS, as forest age per se
cannot be considered sufficient information for identifying “old-growth”
forests according to EC (2023b), recommending that a series of com-
plementary structural indicators would be needed.
Our study is the first one to provide long-term developments beyond
2050 and also effects of alternative distributions of increased protection
in accordance with the EUBDS. Concerning the near-coming decades,
Fig. 6. Harvest (A) and net export (B) projections assuming considerably increased protection, specifically 30% strict protection (dashed line) under SSP2-RCP1.9. C
and D show the corresponding trajectories under a considerably lower demand for wood following the SSP2-RCP6.5 scenario (dashed line). For comparison, the
trajectories of the four main scenarios from Figs. 3 and 5 are also shown (solid lines).
F.D. Fulvio et al. Global Environmental Change 92 (2025) 102986 
10 
our results are generally in line with Lotze-Campen et al. (2018) that
estimated a reduction in stemwood harvest of 45–73Mm3 by 2040 when
expanding protection areas (compared to their baseline), which aligns to
the 43 Mm3 reduction in stemwood harvest estimated with the Green
Infrastructure scenario in the present study. The main reason for the
higher reductions in Lotze-Campen et al. (2018) is that they assumed a
higher 26 % increase in strictly protected area by 2040 instead of our 13
% in the Green Infrastructure scenario.
We find that applying any scenario to protect forests according to the
EUBDS will dampen the future increase in EU harvest level and will be
compensated by increasing roundwood harvests in other regions. For
every cubic meter reduction, the rest of the world will increase its har-
vest by up to 0.79 cubic meters. The rest of EU harvest reduction will
translate into lower global roundwood harvest and consumption, which
could potentially be replaced by the consumption of other commodities
(including fossil based) not included in our modelling. However, the
global roundwood harvest reduction (max. 50 Mm3 year 1) is relatively
insignificant compared to the current global roundwood harvest (3.9
Billion m3 in 2020). This level of leakage is in agreement with estimated
the roundwood harvest leakage by Kallio et al. (2018) for the year 2030.
However, we further show that the leakage will decrease over time. This
decreasing leakage trend occurs due to the structure of GLOBIOM-forest
that accounts for the interaction of roundwood from natural forests with
other sources of woody material from energy crops within and outside
the EU. These additional sources of wood will compensate for the
reduced roundwood harvest in the EU and thus decrease the leakage
outside the EU in the long run. The boreal region absorbs most of the
leakage, as also concluded by Kallio et al. (2018) and Schier et al.
Table 4
Change in roundwood harvest (Mm3 over bark) in EU and Rest of the World compared to the Current protection scenario and associated harvest leakage rate* (%) for
six scenarios (see also Fig. 7 for scenario EU, Country, Green Infrastructure).
Year
Scenario 2030 2040 2050 2060 2070 2080 2090 2100
EU EU  4.3  11.2  16.8  18.8  19.6  21.8  21.7  21.2
Harvest decrease Country  17.1  24.9  29.0  30.0  30.2 –32.5  31.7  31.0
(Mm3 year 1) Green Infrastructure  35.6  43.3  49.5  49.2  48.0  49.4  50.3  50.1
​ EU 30 % Strict  36.8  52.5  65.6  68.9  70.3  74.2  70.3  70.2
​ Country 30 % Strict  54.8  65.7  75.8  76.2  76.2  79.6  76.0  76.8
​ Green infrastructure 30 %  77.4  90.4  97.9  96.0  95.0  97.5  99.3  100.1
Rest of World EU 2.8 6.5 11.6 12.0 4.6 6.0 4.9 6.4
Harvest increase Country 12.5 18.2 20.9 20.1 11.4 13.8 11.7 13.8
(Mm3 year 1) Green Infrastructure 26.6 33.5 38.4 29.8 20.2 24.9 25.0 29.2
​ EU 30 % Strict 24.2 36.3 43.6 32.5 22.5 29.0 30.8 35.3
​ Country 30 % Strict 38.8 50.2 55.0 39.0 31.9 39.3 43.2 48.0
​ Green infrastructure 30 % 56.9 71.2 76.9 52.4 44.3 53.1 57.5 64.7
Leakage rate (%)* EU 66 58 69 64 24 28 22 30
​ Country 73 73 72 67 38 42 37 44
​ Green Infrastructure 75 77 78 60 42 50 50 58
​ EU 30 % Strict 66 69 66 47 32 39 44 50
​ Country 30 % Strict 71 77 73 51 42 49 57 62
​ Green infrastructure 30 % 73 79 79 55 47 55 58 65
*Leakage rate (%) ˆ -100 x (Rest of the Word harvest increase/EU harvest decrease).
Fig. 7. Roundwood leakage rates from the EU to three forest biomes outside the EU given three protection scenarios compared to the Current protection sce-
nario (Table 4).
F.D. Fulvio et al. Global Environmental Change 92 (2025) 102986 
11 
(2022). However, although the impact on the tropical region is fairly
low in terms of wood volumes, the tropical region has much higher
endemic biodiversity that might be under risk (Hill et al., 2019, Jung
et al., 2021). Rosa et al. (2023) have accounted for global biodiversity
impacts of combined increasing wood harvests and expansion of pro-
tection/‘closer-to-nature’ management of the EU forest. They conclude
that increasing strict protection to more than 25 % of the EU currently
managed forestland by 2100 increased the global extinction risk
compared to continuing current forest management. However, a major
limitation of their work is that their biodiversity measure concerned
plants, mammals and birds by applying the countryside species-area
relationship. A focus on just these species groups will underestimate
the biodiversity benefits of protection within the EU, as these are not the
main groups negatively affected by forestry in the EU. These are instead
species associated with deadwood, old forests (rich in deciduous trees)
(EEA, 2020b) and concern species-rich groups of invertebrates, fungi,
cryptogams etc. Thus, further work is needed to understand leakage
effects of adopting protection according to the EUBDS.
Our study also presents solutions for how decreased harvest due to
increased protection can be mitigated for within the EU, by intensified
management in non-protected forest. An intensification of harvest in
forest area managed for production is identified as a solution to mitigate
for the implementation of the EUBDS in Finland (Raty et al., 2023).
Intensified harvesting on production land also comes out as a solution
when optimizing management to reach also biodiversity targets under
increasing wood demands (Blattert et al., 2022, Eggers et al., 2022), and
constitutes a strategy under climate smart forestry for facing future
European wood demands (Yousefpour et al., 2018).
Additionally, non-strictly protected areas under ‘closer to nature’
forest management (20 %), can provide up to an extra 6–7% of EU wood
harvest, compared to strictly protecting entirely 30 % of the area.
Therefore, wood harvest from non-strictly protected areas could also
substantially contribute to mitigate impacts of the protection policy.
Our work can provide quantitative basis for calculating the
compensation for economic loss of harvest income through a payment
for ecosystem services (Wunder, 2015), assuming the generation of at
least biodiversity and climate benefits, alongside wood production as a
co-produced provisioning service (Kangas and Ollikainen, 2022). This
analysis could also help targeting the marketing of voluntary payments
(Forsius et al., 2021). Yet, it is important to keep in mind that the na-
tional policies and institutional framework in each MS will vary
(Primmer et al., 2021).
Overall, this study provides a negotiation basis for demonstrating
that it would be possible to achieve common EU policy conservation
targets without disproportionate impacts on the forest sector demands
inside and outside EU by applying different approaches to allocate
protected areas.
CRediT authorship contribution statement
Fulvio Di Fulvio: Writing – review & editing, Writing – original
draft, Methodology, Investigation, Formal analysis, Data curation,
Conceptualization. Tord Snall: Writing – review & editing, Writing –
original draft, Conceptualization. Pekka Lauri: Writing – review &
editing, Writing – original draft, Methodology, Formal analysis, Data
curation, Conceptualization. Nicklas Forsell: Writing – review & edit-
ing, Writing – original draft, Conceptualization. Mikko Monkkonen:
Writing – review & editing, Funding acquisition, Conceptualization.
Daniel Burgas: Writing – review & editing, Conceptualization. Clem-
ens Blattert: Writing – review & editing, Conceptualization. Kyle
Eyvindson: Writing – review & editing, Conceptualization. Astor
Tora~no Caicoya: Writing – review & editing. Marta Vergarechea:
Writing – review & editing. Clara Anton-Fernandez: Writing – review
& editing. Julian Klein: Writing – review & editing. Rasmus Astrup:
Writing – review & editing. Jani Lukkarinen: Writing – review &
editing. Samuli Pitzen: Writing – review & editing. Eeva Primmer:
Writing – review & editing.
Declaration of competing interest
The authors declare the following financial interests/personal re-
lationships which may be considered as potential competing interests:
Fulvio Di Fulvio reports financial support was provided by ERA-Net
Cofund scheme. Fulvio Di Fulvio reports a relationship with Interna-
tional Institute for Applied Systems Analysis that includes: employment.
If there are other authors, they declare that they have no known
Fig. 8. Development of roundwood harvest (A) and energy crops harvest (B) compared to the Current protection scenario under SSP2-RCP1.9.
F.D. Fulvio et al. Global Environmental Change 92 (2025) 102986 
12 
competing financial interests or personal relationships that could have
appeared to influence the work reported in this paper.
Acknowledgments
This work was conducted within the project MultiForest, which is
supported under the umbrella of ERA-NET Cofund ForestValue by:
Academy of Finland (326321), Business Finland, Federal Ministry of
Agriculture, Forestry, Environment & Water Management (Austria),
Agency for Renewable Resources (Germany), Research Council of Nor-
way, Vinnova (2018-04982; Sweden). ForestValue has received funding
from the European Union Horizon 2020 research and innovation pro-
gram under grant agreement N 773324. Additionally, we acknowledge
support from the EU Horizon Europe project Forest-
Navigator—Navigating European forests and forest bioeconomy sus-
tainably to EU climate neutrality (GA No. 101056875). We are thankful
to Dr. Nicolas Robert for the critical reading of this paper.
Appendix A. Supplementary data
Supplementary data to this article can be found online at https://doi.
org/10.1016/j.gloenvcha.2025.102986.
Data availability
Data will be made available on request.
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