Rapid Changes in Ground Vegetation of Mature Boreal Forests—An Analysis of Swedish National Forest Inventory Data

Abstract

The boreal forest floor vegetation is critical for ecosystem functioning and an important part of forest biodiversity. Given the ongoing global change, knowledge on broad-scale changes in the composition and abundance of different plant species and species groups is hence important for both forest conservation and management. Here, we analyse permanent plot data from the National Forest Inventory (NFI) on changes in the vegetation over a 10-year period in four regions of Sweden. To limit the direct and relatively well-known effects of forest management and associated succession, we only included mature forest stands not influenced by forestry during the 10 years between inventories, and focused on vegetation change mainly related to other factors. Results show strong decrease among many species and species groups. This includes dominant species such as Vaccinimum myrtillus and Deschampsia flexuosa as well as several forest herbs. The only species increasing are some mosses in the southern regions. Our data do not allow for a causal interpretation of the observed patterns. However, the changes probably result from latent succession in combination with climate change and nitrogen deposition, and with time lags complicating the interpretation of their relative importance. Regardless of the cause, the observed changes are on a magnitude that suggest impacts on ecosystem functioning and hence highlight the need for more experimental work.

Full text

Article
Rapid Changes in Ground Vegetation of Mature Boreal
Forests—An Analysis of Swedish National Forest
Inventory Data
Bengt Gunnar Jonsson 1, 2, * , Jonas Dahlgren 3, Magnus Ekström 3,4, Per-Anders Esseen 5, Anton Grafström 3,
Göran Ståhl 3and Bertil Westerlund 3


Citation: Jonsson, B.G.; Dahlgren, J.;
Ekström, M.; Esseen, P.-A.; Grafström,
A.; Ståhl, G.; Westerlund, B. Rapid
Changes in Ground Vegetation of
Mature Boreal Forests—An Analysis
of Swedish National Forest Inventory
Data. Forests 2021,12, 475. https://
doi.org/10.3390/f12040475
Academic Editors: Jerzy Szwagrzyk
and Anna Gazda
Received: 9 March 2021
Accepted: 9 April 2021
Published: 13 April 2021
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Copyright: © 2021 by the authors.
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Attribution (CC BY) license (https://
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4.0/).
1Department of Natural Sciences, Mid Sweden University, SE-851 70 Sundsvall, Sweden
2Department of Fish, Wildlife and Environmental Sciences, Swedish University of Agricultural Sciences,
SE-901 83 Umeå, Sweden
3Department of Forest Resource Management, Swedish University of Agricultural Sciences,
SE-901 83 Umeå, Sweden; jonas.dahlgren@slu.se (J.D.); magnus.ekstrom@slu.se (M.E.);
anton.grafstrom@slu.se (A.G.); goran.stahl@slu.se (G.S.); bertil.westerlund@slu.se (B.W.)
4Department of Statistics, USBE, Umeå University, SE-901 87 Umeå, Sweden
5Department of Ecology and Environmental Science, Umeå University, SE-901 87 Umeå, Sweden;
per-anders.esseen@umu.se
*Correspondence: bengt-gunnar.jonsson@miun.se
Abstract:
The boreal forest floor vegetation is critical for ecosystem functioning and an important
part of forest biodiversity. Given the ongoing global change, knowledge on broad-scale changes in
the composition and abundance of different plant species and species groups is hence important
for both forest conservation and management. Here, we analyse permanent plot data from the
National Forest Inventory (NFI) on changes in the vegetation over a 10-year period in four regions of
Sweden. To limit the direct and relatively well-known effects of forest management and associated
succession, we only included mature forest stands not influenced by forestry during the 10 years
between inventories, and focused on vegetation change mainly related to other factors. Results
show strong decrease among many species and species groups. This includes dominant species such
as Vaccinimum myrtillus and Deschampsia flexuosa as well as several forest herbs. The only species
increasing are some mosses in the southern regions. Our data do not allow for a causal interpretation
of the observed patterns. However, the changes probably result from latent succession in combination
with climate change and nitrogen deposition, and with time lags complicating the interpretation of
their relative importance. Regardless of the cause, the observed changes are on a magnitude that
suggest impacts on ecosystem functioning and hence highlight the need for more experimental work.
Keywords: plants; lichens; mosses; climate change; nitrogen; succession; ecosystem function; biodi-
versity
1. Introduction
The boreal forest floor vegetation is critical for ecosystem functioning and constitutes
an important part of forest biodiversity. It affects soil properties, nutrient cycling and stand
succession and hence overall stand structure and development [
1
,
2
]. Given the ongoing
global change, knowledge on broad-scale changes in the composition and abundance of
different plant species and species groups is hence important for both forest conservation
and management.
Plants react and change their abundance in relation to both abiotic and biotic factors
at various spatial and temporal scales. The most prominent changes occur during the
succession after major disturbance events such as fire and forest harvest. These changes
are well-studied in relation to vegetation succession following both natural disturbances
and forest management [
3
–
6
], with plant species following relatively predictable change
Forests 2021,12, 475. https://doi.org/10.3390/f12040475 https://www.mdpi.com/journal/forests

Forests 2021,12, 475 2 of 16
from shade intolerant to more shade tolerant species. In addition to succession, vegetation
change is also governed by climate as well as other biotic and abiotic factors, and in the
boreal forest is particularly related to nitrogen availability [7–9].
Fennoscandian boreal forests cover about 60 MHa [
10
] and are subjected to intensive
sustained-yield forestry mainly based on clearcut harvesting systems [
11
]. The region is
experiencing significant climate change with predictions for 2100 of temperature increase
from 2–4 degrees and 10–20% increased precipitation (RCP4.5 [
12
]). These forests are
naturally nitrogen-limited [
13
] and hence sensitive to elevated anthropogenic nitrogen
deposition [
7
,
14
]. The basal area of the forests across Sweden has increased with on average
20% during the past three decades, with the largest increase in northern Sweden [
15
]. All
these factors may influence forest-floor vegetation, and it is a challenge to disentangle the
relative contribution of the direct effects of forest management from the indirect effects of
climate and pollution [
16
]. Yet, this is critical to devise management strategies that protect
both species richness (biodiversity) and overall ecosystem function.
National Forest Inventory (NFI) data encompass a large number of sample plots from
the entire forest landscape and as such may provide an opportunity to better understand
how different factors drive changes in forest vegetation [
17
]. Covering large geographical
regions and the full range of stand ages, such data allow analysing vegetation change while
controlling for specific factors such as stand age and forestry interventions. Hence, NFI data
may increase our knowledge on the relative importance of different forest management
operations and other factors influencing forest-floor vegetation. Although vegetation
change is influenced by numerous interacting factors in a complex manner, NFI data
represent an important empirical source for identifying general trends in vegetation change
and for generating hypotheses on factors influencing these trends.
In the present study we utilize data from the Swedish NFI on the abundance (percent-
age cover) of 25 species (vascular plants, mosses, lichens) and 6 major species groups. We
analyse the changes occurring during a 10-year period in mature forest stands that did not
experience harvesting (final felling or thinning) during the study period. This limits the
direct role of succession after harvesting and highlights the importance of other factors.
Specifically, we aim to:
•
Identify if directional changes in percentage cover of species and species groups
have occurred in old/mature forests that have not been subject to forest management
during a 10-year period.
•
If such changes are present, to analyse if the direction of change varies among four
regions in Sweden, stretching from hemiboreal to northern boreal regions.
•To explore factors that might have contributed to the identified changes.
2. Materials and Methods
2.1. Study Area
The study area comprises all of Sweden except the southernmost part (temperate
region) and follows the regional delineation used in the Swedish NFI (Figure 1). About
two-thirds of the area is covered by forests (based on the FAO, Food and Agriculture
Organization of the United Nations, forest definition; [
18
]) with a total area of 28 million
hectares [
15
]. Industrial forestry has occurred on most of the area since the early 1800s,
with large-scale implementation of clearcut forestry from the middle of the 1900s [19].

Forests 2021,12, 475 3 of 16
Figure 1.
Regional delineation of Sweden in the National Forest Inventory. Regions 1–3 span the
southern boreal to northern boreal zone; region 4 belongs to the hemiboreal zone. Region 5 (temperate
zone) is not included in the present study.
2.2. NFI Data
The Swedish NFI includes a network of systematically located sampled plots where
many variables, including the cover of species in the ground vegetation, are monitored [
17
].
The NFI design is based on clusters of sample plots in square-formed tracts (4–8 plots
per tract depending on region). The plots are evenly spaced and located around the tract
perimeter with the length of tract side varying from 300 to 1200 m among regions. For our
analysis, we used data on cover of vascular plants, mosses and lichens in 100 m
2
permanent
(with repeated inventories) circular plots during one full inventory cycle with the first and
second inventory year separated by 10 years. The first year of inventory ranged from 1995
to 2003. The cover estimates include surveyor variation, but this variation is considered
relatively small compared to random errors [
20
]. Hence, we base all our analyses on a
pair-wise comparison of plots with a 10-year time interval between inventories. We only
included plots on productive forestland (annual growth > 1 m
3
ha
−1
yr
−1
). As auxiliary
information we extracted data on thinnings taking place within 10 years prior to the first
inventory (0/1), stand productivity (m
3
ha
−1
yr
−1
), change in basal area (m
2
ha
−1
) over
the 10-year period, change in canopy cover (%) over the 10-year period and stand maturity
class at the first inventory (4 classes of old/mature forest; Table 1). The stand maturity
classes included in the study have a minimum requirement of dominant and subdominant
trees with a diameter at breast height (DBH) larger than 20 cm and are based on stand age
in relation to lowest allowed and lowest recommended harvest age.
Table 1.
Stand age (basal area weighted average, year) and fraction (%) of total number of sample
plots in the different stand maturity classes (according to the Swedish National Forest Inventory
(NFI)) included in the study.
Maturity Class *
Region 33 34 41 42
1 70 (17.5%) 89 (5.9%) 102 (32.0%) 156 (44.6%)
2 64 (20.0%) 89 (8.6%) 96 (25.9%) 139 (45.5%)
3 55 (26.5%) 77 (7.0%) 81 (20.3%) 122 (46.3%)
4 50 (23.1%) 69 (6.8%) 70 (26.1%) 99 (44.1%)
* 33 = thinning stage with mean DBH >20 cm, less than minimum felling age; 34 = thinning stage with mean
DBH >20 cm, above minimum felling age; 41 = Final felling stage, but age below recommended for final felling;
42 = Final felling stage above recommended age for final felling.

Forests 2021,12, 475 4 of 16
The Swedish NFI includes inventory of 70 forest-floor species, or combinations of
species not identified individually in the field [
21
]. Several of these species are relatively
rare. For a species to be included in our analysis it had to occur in at least 20 sample plots
in a region and be present in at least three of four regions. Although fulfilling the inclusion
criteria, three species typical for early successional stages were excluded (i.e., Epilobium
angustifolium,Rubus ideaus and Geranium sylvaticum), since they are assumed to be in a
transient successional phase also in mature forests. With the applied selection criteria,
our analysis is based on 25 species and more than 12,500 individual species by region
observations across 1300 study plots in each of the two inventory years.
2.3. Statistical Analysis
The change in abundance was analysed by calculating a 95% confidence interval
around the mean absolute change in cover between the two inventories for individual
species and six major species groups (graminoids, herbs, dwarf shrubs, spore plants, lichens
and mosses) within individual regions. For the species group analysis, we included all
species surveyed by the NFI. Although the NFI plots are located in clusters (tracts), we
assume that observed changes are independent among plots. The distance between plots is
several hundreds of meters and even for the most frequent species, on average only two to
three plots per tract are included in the analysis. This assumption was also made in several
recent studies using vegetation data from the NFI (e.g., [4,6]).
The influence of the four stand variables on the change in abundance was explored by
linear regression, using the function “lm” in the statistical software R [
22
]. The analysis was
exploratory since there are a very large number of potential models that can be developed
and the purpose was not to predict change per se. Rather, we wanted to exclude factors
relating primarily to successional aspects and focus on change that is more likely due to
other abiotic factors. Hence, we considered region as a “block” in the analysis, and each
of the four stand variables was tested individually for a change in percentage cover for
each species (see Appendix A, Table A1). For continuous variables (stand productivity
and change in basal area), we only report the degree of explanation (adjusted R
2
) when
the factor significantly influenced percentage cover change. For the categorical factors
(thinning prior to first inventory and stand maturity class) we provide for each class the
percentage cover change for individual species when these factors were significant.
To explore the responses of individual species we selected a set of Ecological Indicator
Values (EIV) [
23
] that directly link to the main factors influencing the abundance of vascular
plants in boreal forests. We compared six EIVs (heat requirement, continentality, light,
moisture, soil reaction (pH) and nitrogen) for species showing significant change with
the EIVs for the other plant species monitored by the NFI by calculating mean EIVs for
each of the groups. If the mean EIV differed by more than one unit, we consider this as an
indication that the factor influenced the observed change (see Appendix B, Table A2).
An NMDS ordination was performed for the six major species groups to examine the
effects of inventory time and region on percentage cover. The functions “metaMDS” and
“envfit” in R-package “vegan” [
24
] were used for the analysis, with a solution converging
for a 4-dimensional solution based on a Bray–Curtis dissimilarity matrix (final stress 0.0618).
Significance test of inventory time (first or second inventory) and region was based on 1000
permutations. For the full data set of all species, no converging solution was possible to
obtain. Further details on ordination analysis are given in Appendix C.
3. Results
3.1. Stand Structure
On average, 17.5% of the 1300 sample plots was thinned during the 10-year period
prior to the first inventory, ranging from 9.4% in region 2 to 25.5% in region 4. The basal
area increased as expected, with about 10% across the regions (Table 2). Canopy cover
estimates were only available for a limited number of plots (179) and indicate an increase
of about 12% across the regions (Table 2).

Forests 2021,12, 475 5 of 16
Table 2. Changes in basal area and canopy cover over the 10-year period.
First Inventory Second Inventory
Region Mean SD Mean SD NDifference
Basal area (m2ha−1)
1 20.1 8.02 22.1 8.33 294 2.0
2 24.8 9.86 27.1 10.48 312 2.2
3 26.30 10.53 29.2 10.99 398 2.9
4 28.0 9.69 30.7 10.75 296 2.8
Total 24.9 10.05 27.4 10.72 1300 2.5
Canopy cover (%)
1 55.6 16.77 60.9 15.21 46 5.2
2 56.1 18.42 57.0 13.38 44 1.0
3 50.9 17.86 63.9 11.73 55 13.0
4 58.5 12.72 63.2 12.19 34 4.7
Total 54.8 16.96 61.3 13.36 179 6.5
3.2. Change in Species Abundance
We found significant changes in the abundance of many species in several regions
during the 10-year period. Out of 93 analysed species–region combinations, 37 showed a
significant decrease in cover, whereas only 4 combinations (all mosses) increased (Table 3),
that is, about 44% of the species–region combinations showed a significant change in cover.
Albeit the absolute change was relatively small, the relative change was high. For species
that decreased, the average relative decrease was 34%, while those that increased changed
on average with 22%. The number of species showing significant change ranged from 7 to
11 decreasing species and from 0 to 2 increasing species per region.
Table 3.
Species showing significant changes (p< 0.05) in cover in individual regions (see Figure 1). Initial cover denotes the
average cover for the first inventory year while the absolute change and the relative change refers to the average change
occurring after 10 years. N refers to the number of plots included in the analysis. The 95% confidence interval for the
absolute change is defined by its two limits: the Lower Confidence Limit (LCL) and the Upper Confidence Limit (UCL).
Cover (%)
Species * Region NInitial Change Absolute (Relative) LCL UCL
Graminoids
Broad leaved grasses 3 187 6.8 −1.7 (−25%) −
3.04
−0.36
Broad leaved grasses 4 135 7.6 −2.3 (−30%) −
3.97
−0.53
Carex globularis 2 69 1.7 −0.6 (−34%) −
1.01
−0.11
Carex globularis 3 80 2.0 −0.8 (−42%) −
1.51
−0.19
Narrow leaved grasses 2 240 3.4 −1.2 (−35%) −
1.73
−0.64
Narrow leaved grasses 3 274 5.0 −2.0 (−40%) −
3.08
−0.97
Narrow leaved grasses 4 208 5.8 −2.1 (−36%) −
3.32
−0.92
Herbs
Anemone nemorosa 3 107 2.1 −0.8 (−38%) −
1.55
−0.02
Maianthemum bifolium 1 62 3.7 −1.6 (−43%) −
3.03
−0.21
Maianthemum bifolium 3 160 1.7 −0.4 (−26%) −
0.80
−0.09
Maianthemum bifolium 4 111 1.9 −0.9 (−49%) −
1.42
−0.43
Melampyrum spp. 3 245 1.2 −0.3 (−27%) −
0.62
−0.01
Melampyrum spp. 4 155 1.0 −0.3 (−31%) −
0.52
−0.07
Oxalis acetosella 2 89 3.4 −1.3 (−38%) −
2.17
−0.43
Dwarf shrubs
Calluna vulgaris 3 164 5.3 −0.9 (−16%) −
1.68
−0.05
Empetrum nigrum 3 93 3.7 −1.1 (−29%) −
1.82
−0.31
Empetrum nigrum 4 27 1.2 −0.8 (−68%) −
1.21
−0.42
Rubus chamaemorus 1 52 4.3 −2.1 (−50%) −
3.92
−0.34
Rubus chamaemorus 3 49 4.2 −1.5 (−36%) −
2.85
−0.19
Vaccinium myrtillus 1 291 26.2 −5.8 (−22%) −
7.51
−4.07
Vaccinium myrtillus 2 307 22.6 −4.0 (−17%) −
5.49
−2.42
Vaccinium uliginosum 4 52 5.6 −1.8 (−31%) −
3.43
−0.08
Spore plants
Equisetum sylvaticum 1 80 3.5 −2.2 (−64%) −
3.38
−1.04
Equisetum sylvaticum 2 91 1.4 −0.5 (−35%) −
0.82
−0.14
Gymnocarpium dryopteris 1 52 6.8 −3.0 (−44%) −
5.02
−1.01

Forests 2021,12, 475 6 of 16
Table 3. Cont.
Cover (%)
Species * Region NInitial Change Absolute (Relative) LCL UCL
Lichens
Cladonia spp. excl. Cladina 2 196 0.4 −0.1 (−32%) −
0.23
−0.03
Cladonia spp. excl. Cladina 4 162 0.4 −0.2 (−48%) −
0.28
−0.07
Cladonia grp. Cladina 2 162 6.3 −3.0 (−47%) −
4.15
−1.78
Cladonia grp. Cladina 3 184 8.3 −2.5 (−30%) −
3.56
−1.47
Cladonia grp. Cladina 4 81 2.8 −0.9 (−33%) −
1.85
−0.02
Other ground lichens 2 151 0.9 −0.2 (−25%) −
0.39
−0.03
Other ground lichens 3 195 1.1 −0.4 (−33%) −
0.68
−0.05
Mosses
Hylocomium splendens 3 358 16.9 3.6 (21%) 1.82 5.34
Hylocomium splendens 4 269 14.3 5.7 (40%) 3.59 7.79
Pleurozium schreberi 1 293 36.2 −5.9 (−16%) −
8.39
−3.40
Pleurozium schreberi 3 383 22.7 2.2 (10%) 0.46 3.94
Pleurozium schreberi 4 276 22.5 −4.4 (−20%) −
6.64
−2.18
Polytrichum spp. 2 127 4.1 −1.2 (−28%) −
2.09
−0.21
Sphagnum spp. 1 120 21.8 −3.6 (−17%) −
6.31
−0.90
Sphagnum spp. 2 157 20.2 −3.0 (−15%) −
5.03
−0.93
Sphagnum spp. 4 149 21.3 3.4 (16%) 0.56 6.30
* In addition, the following species and species groups did not show significant change in any species–region combination; Vaccinium
vitis-idea,Rhododendron tomentosum,Lycopodiaceae and tall ferns.
3.3. Factors Correlating with Change in Cover
The explored linear regression models (including stand productivity, presence of
thinning during 10 years prior to the first inventory, change in basal area during the 10-
year period and stand maturity class) were in most cases nonsignificant (see Appendix A,
Table A1). However, some of the independent variables influenced cover of the species:
Stand productivity—Reindeer lichens (Cladonia grp. Cladina) and other ground lichens
tended to decrease their cover less on plots with higher forest productivity, while broad-
leaved grasses decreased more at high productivity plots. However, the models were very
weak and explained 1% or less of the change in cover.
Change in basal area—Anemone nemorosa and broad-leaved grasses decreased more at
sites with a higher increase in basal area. However, these models only explained about 2%
of the change in cover.
Thinning before the first period—Melampyrum spp., Vaccinium myrtillus and Calluna
vulgaris decreased in unthinned plot and increased in thinned plots. By contrast, Carex
globularis and Pleurozium schreberi were negatively influenced by thinning (Table 4).
Table 4.
Relative cover change for species where thinning occurred during 10 years prior to first
inventory significantly (p< 0.05) explained the observed variation. Sample size in parenthesis.
Relative cover Change (%) in Un-Thinned and Thinned Stands
Species Unthinned Thinned
Melampyrum spp. −33% (635) 8% (127)
Vaccinium myrtillus −15% (1033) 6% (197)
Calluna vulgaris −20% (358) 59% (84)
Carex globularis −32% (217) −69% (23)
Pleurozium schreberi −5% (1052) −16% (210)
Stand maturity class—The change in cover of some species (Oxalis acetosella,Anemone
nemorosa,Vaccinium myrtillus, and Cladonia grp. Cladina) maintained their cover better in
the younger maturity classes, except for Cladonia grp. Cladina, which decreased most in
the youngest class. Lycopodiaceae showed varying cover change in the different maturity
classes (Table 5).

Forests 2021,12, 475 7 of 16
Table 5.
Relative change in cover of species where maturity class (stand age proxy) was a significant
(p< 0.05) factor explaining the observed variation. The sample size in given in parenthesis. For
definition of maturity classes see Table 1.
Relative Cover Change (%) in Maturity Classes
Species 33 34 41 42
Oxalis acetosella 10% (40) −59% (14) −46% (72) −21% (133)
Anemone nemorosa 8% (51) −36% (16) −25% (49) −65% (79)
Vaccinium myrtillus −1% (185) −13% (71) −14% (314) −14% (660)
Lycopodiaceae −39% (41) 74% (15) −2% (70) −28% (153)
Hylocomium splendens 34% (190) 23% (73) 9% (296) 9% (635)
Cladonia grp. Cladina −54% (77) −29% (38) −28% (165) −22% (327)
The mean value of three EIVs for the vascular plants showing decreasing cover,
differed with more than one unit compared to the other species monitored in the NFI plots
(Appendix B, Table A2); Heat EIV was 1.3 units lower, Soil pH EIV was 1.8 units lower and
Nitrogen EIV was 2 units lower. Hence, the decreasing species occurred in colder climates
and less productive forests compared to the other forest species.
3.4. Change in Species Groups
When combining the species into six functional groups, most of the groups showed a
significant decrease in their cover. Only mosses in region 3 increased (relative increase of
9%). The change was not significant for seven of the 24 species group–region combinations
(Table 6). The average relative cover change for decreasing species groups was 23%, ranging
from 4% to 44%. Herbs significantly decreased in all regions, while graminoids and lichens
decreased in three regions.
Table 6.
Change in cover of six species groups in four regions (see Figure 1). Initial cover denotes the average cover for the
first inventory year, while the absolute change and the relative change refer to the average change occurring after 10 years.
N refers to the number of plots included in the analysis. The 95% confidence interval for the absolute change is defined
by its two limits: the Lower Confidence Limit (LCL) and the Upper Confidence Limit (UCL). NS denotes nonsignificant
(p> 0.05) change.
Cover (%)
Species Group NInitial Change Absolute (Relative) LCL UCL Direction
Graminoids
Region 1 245 3.6 −0.5 (−13%) −0.99 0.06 NS
Region 2 254 6.0 −1.3 (−22%) −2.15 −0.54 Decrease
Region 3 332 10.2 −2.8 (−27%) −4.16 −1.43 Decrease
Region 4 250 10.7 −2.6 (−24%) −4.12 −1.09 Decrease
Herbs
Region 1 179 3.0 −1.0 (−33%) −1.57 −0.37 Decrease
Region 2 230 4.6 −0.9 (−19%) −1.51 −0.19 Decrease
Region 3 309 3.8 −0.8 (−20%) −1.34 −0.17 Decrease
Region 4 225 4.1 −1.1 (−28%) −1.93 −0.32 Decrease
Dwarf shrubs
Region 1 269 56.4 −8.0 (−14%) −10.49 −5.56 Decrease
Region 2 286 49.7 −6.7 (−14%) −8.91 −4.57 Decrease
Region 3 354 33.7 −1.7 (−5%) −3.55 0.17 NS
Region 4 277 24. 8 −0.8 (−3%) −2.70 1.12 NS
Spore plants *
Region 1 159 5.0 −2.2 (−44%) −3.23 −1.11 Decrease
Region 2 175 5.1 −1.3 (−25%) −2.19 −0.36 Decrease
Region 3 124 2.9 −0.3 (−9%) −0.95 0.44 NS
Region 4 80 2.5 0.4 (15%) −0.40 1.18 NS

Forests 2021,12, 475 8 of 16
Table 6. Cont.
Cover (%)
Species Group NInitial Change Absolute (Relative) LCL UCL Direction
Lichens
Region 1 221 5.7 −0.6 (−11%) −1.68 0.48 NS
Region 2 241 7.3 −3.0 (−42%) −4.08 −1.99 Decrease
Region 3 308 6.9 −2.0 (−28%) −2.79 −1.12 Decrease
Region 4 222 1.6 −0.4 (−26%) −0.85 −0.01 Decrease
Mosses
Region 1 269 79.4 −7.6 (−10%) −10.29 −4.95 Decrease
Region 2 290 79.1 −3.2 (−4%) −5.91 −0.42 Decrease
Region 3 367 63.6 5.9 (9%) 3.56 8.33 Increase
Region 4 280 57.4 2.2 (4%) −0.78 5.09 NS
* Including ferns, Equisetum spp. and Lycopodiaceae.
The NMDS ordination of the six groups mirrors the general pattern of significant
change in most species groups (Figure 2). The ordination highlights that the composition
differs among regions and that it is change over time (both factors significant, p< 0.01).
However, only a minor fraction of the total variation in species composition was explained.
The ordination suggests that the composition becomes more similar and moves towards the
composition in region 1, with a stronger relative dominance of mosses and dwarf shrubs.
Additional details on the ordination results are presented in Appendix C.
Figure 2.
NMDS ordination (dimensions 1 and 2) of six species groups, where filled circles denote
average “site scores” for the four regions at the two inventories. Arrows denote the direction of
change. Note that, to increase the readability of the figure, the positions of the species group scores
do not represent their actual scores along the axes, since these are outside the current axis’s ranges.
However, their relative position indicates where they occur in the ordination.

Forests 2021,12, 475 9 of 16
4. Discussion
Our analysis of the change in cover of ground vegetation in mature boreal forests
shows a rapid and significant decrease for many of the studied species and most species
groups. We recognize that our data do not allow for a formal cause-and-effect analysis of
the reasons behind these changes, but the results highlight the need to explore potential
factors that contribute to our observations. Our data are large and for most species and
species groups include several hundreds of randomly distributed plots throughout boreal
and hemiboreal Sweden, adding strong statistical support for the observed patterns.
Previous studies using NFI data from Sweden and Finland have demonstrated clear
effects of forest management on forest-floor vegetation [
4
,
6
,
25
,
26
]. Their results can mostly
be attributed to the direct effects of forest management (clearcut harvesting and thinning)
and the subsequent succession in forest-floor vegetation. Changes in light, nutrient and
moisture availability are obvious after forestry interventions, and vegetation dynamics
reflect these changes in abiotic conditions. Two recent studies [
25
,
26
] acknowledged that
climate change may also play a role in observed changes, but the impact is likely minor
compared to the effects of the conducted forest management operations. In our case, we
have as far as possible removed the direct effects of management activities by focusing on
mature forest stands that have not been subjected to major anthropogenic disturbances.
4.1. Succession
Although the study plots have not been recently subject to major management inter-
ventions, successional transitions may still potentially explain at least part of the observed
changes. Several studies from Fennoscandia have described the pattern of vegetation dy-
namics after disturbance by using comparable data. For example, in a study from northern
Finland [
27
], succession after disturbance was studied in both managed (after clearcutting)
and natural forests (after forest fire), ranging from recently disturbed sites to overmature
stands (>100 years). In the managed forest stands, Vaccinium myrtillus increased in cover
from mature to overmature forests. Also in Swedish forests, the cover of V. myrtillus in-
creased up to a forest age of about 120 years [
28
]. This was not the case in our study. Here
the cover of V. myrtillus decreased in the two northern regions and remained rather stable
in the two southern regions. Hence, our results are more in line with recent studies in
Sweden [
5
,
6
] showing a general decrease of V. myrtillus and other dwarf shrubs, which
could be attributed to increasing stand density across Swedish forests (see [
15
]). These
contrasting observations add to a somewhat puzzling variation in the abundance of this
keystone species in Fennoscandian forests [
4
]. Probably there is an interaction between
stand density and stand age in these studies. The importance of stand density is supported
by our data, since V. myrtillus decreased less in stands thinned prior to the first inventory
period and in younger stand maturity-classes.
It is well-established that light availability, and hence canopy cover, in combination
with precipitation strongly affect lichen growth [
29
,
30
]. In a study comparing lichen
growth rate across sites with different canopy cover, it was shown that canopy cover over
60% reduced growth of two common terricolous lichens (Cladonia stellaris and Cetraria
islandica) [
31
]. This suggests that increasing canopy cover could result in decreased abun-
dance of ground lichens also in our data set. During the studied 10-year period, the canopy
cover increased with on average about 6%, from just below to just above the 60% threshold.
It should also be noted that the basal area in mature forests in our dataset is higher than in
the cited study [31].
However, if our observed changes would be mainly associated with a successional
trajectory from younger to older forest, with increasing basal area and canopy cover, we
would expect to see consistent effects of the changes in basal area during the study period
as well effects of thinning events prior to the 10-year inventory period. Our analyses clearly
indicate that this is not the case. We found only minor effects of the change in basal for a
few species, that is, for Anemone nemorosa, broad-leaved grasses and for three species that
increased in thinned stands and decreased in unthinned stands (Table 4). This suggests that

Forests 2021,12, 475 10 of 16
the observed changes in cover of major plant groups are not only driven by successional
change and that other factors may contribute to the changes in vegetation.
4.2. Climate
A significant increase in average temperature and precipitation was observed through-
out Sweden from the early 1990s. Compared to the reference period 1961–1990, the average
temperature in Sweden was 1.0 degrees higher during the inventory period 1995–2014,
with a 9% increase in precipitation [
32
]. The long-term trend with a warmer climate is
clear, and the response of the vegetation may well be associated with this trend. Given that
our observed changes cannot be fully explained by succession, climate change should at
least be considered a contributing factor. This is supported by the EIV analysis, since the
decreasing species tended to be more associated with colder environments than the other
vascular plants monitored by the NFI.
A warmer climate extends the vegetation period and may shift the competitive balance
among species, with some winners and some losers. It is well-established that soil warming
has significant effects on ground vegetation in tundra habitats [
33
]. However, it is likely
that closed canopy forests mediate the effects of soil temperature on ground vegetation [
34
].
In a long-term experimental study of soil warming, Hedwall et al. [
35
] found a strong
initial vegetation response in young forests, but the long-term effects were less clear, except
that moss cover increased as the forest became older. The soil temperature during winter is
strongly connected to the insulating effect of snow cover [
36
]. Milder winters in the south
will give a less consistent snow cover, which may increase soil temperature. Hence, we
hypothesize that increased temperature may contribute to the observed increase in moss
cover in southern Sweden. By contrast, a decrease in snow cover in northern regions may
result in stronger ground frost. This has been shown to have dramatic effects on ground
vegetation, with significant decrease in the cover of understory vegetation and mosses [
37
],
in accordance with our observations.
An increase in precipitation should favour species and species groups typical of
more moist conditions. However, our results contradict this since plants typical for moist
forests (Equisetum sylvaticum,Rubus chamaemorus,Carex globularis and Sphagnum spp.) also
decreased in cover. Neither do the EIVs provide any indication that species associated with
moist habitats were favoured.
4.3. Nitrogen Deposition
Deposition of atmospheric nitrogen is a factor known to have significant impact on
boreal forest ground vegetation [
38
]. There is a clear gradient through Sweden with higher
deposition in the southwest and lower towards the north [
39
,
40
]. Nitrogen deposition has
decreased since the 1980s across Europe [
41
]. However, the change is not as evident in
Sweden, besides an indicative trend of decreasing nitrogen deposition in the southwestern
part (i.e., including parts of region 4) since around year 2000, and for long time series in
northern regions [
40
]. Yet, the EIV analysis suggests that species associated with more
nutrient-poor environments (low soil pH and less nitrogen demanding) are overrepresented
among species showing decreasing cover.
In experimental studies it has been shown that narrow-leaved grasses (dominated by
Deschampsia flexuosa) and herbs increase with increasing nitrogen deposition while dwarf
shrubs and lichens decrease [
14
,
42
]. In comparison with our results, the effect of nitrogen
corresponds to the decline in dwarf shrubs and lichens, but not for narrow-leaved grasses
and herbs, since all these species groups decline in mature Swedish forests. It should
be noted, however, that even if experimental studies often show clear effects on ground
vegetation, the effect of the overall atmospheric deposition of nitrogen is less evident,
mainly because experimental doses applied are commonly much higher than background
deposition [38]. This complicates the interpretation of our results.

Forests 2021,12, 475 11 of 16
4.4. Time Lags in Responses
Most of the studied species and species groups are clonal and long-lived. Hence,
although abiotic conditions change, associated changes in cover and occurrence of plants
likely include time lags, that is, integrating effects over a longer time period than the
studied 10-year period. For instance, major distributional and abundance changes in
Finnish ground vegetation are predicted up to mid-late 21st century due to increased
temperature [
9
], and hence highlight trends over longer time periods. When evaluating
potential factors behind the observed changes, this implies that increasing stand age and
changes in climate and nitrogen deposition occur in parallel time scales, which might
require several decades before fully manifested.
4.5. Conclusions
We have shown large changes in the ground vegetation in mature Swedish forests over
a relatively short time period (10 years). These changes may imply ecosystem-level impacts
on the function of boreal forests [
43
]. At this stage, we cannot attribute the observed
changes to a single factor. The changes likely result from a combination of succession,
climate change and nitrogen deposition, and where time lags complicate the interpretation.
This confirms the conclusion from the review by [
16
] that it is necessary to consider both
previous land management and functional properties of plant communities when analysing
and modelling effects of the ongoing global change.
Author Contributions:
B.G.J. conceived the idea, and performed the statistical analysis with support
from M.E., A.G. and G.S.; J.D. and B.W. provided empirical data from the NFI and advised on its
use; P.-A.E. contributed with ecological knowledge on boreal vegetation. All authors have read and
agreed to the published version of the manuscript.
Funding:
This work was financially supported by the Swedish Research Council (Vetenskapsrådet),
Grant 340-2013-5076.
Data Availability Statement:
All data used in the study were obtained from the Swedish National
Forest Inventory and are available upon request. See links at https://www.slu.se/en/ (accessed on
23 August 2017).
Acknowledgments:
We thank Joachim Strengbom for comments on an earlier version of the manuscript.
Conflicts of Interest: The authors declare no conflict of interest.
Nomenclature
Vascular plants [44]; Lichens [45]; Bryophytes [46].
Appendix A
Table A1.
Effects of stand productivity, basal area change, presence of thinning 10 years prior to first inventory period and
stand Maturity class (see Table 1) on the change in cover during the studied 10-year period. Values are p-values from linear
models with regions treated as a block in the analysis. Bold numbers indicate a significant effect. N denotes number of plots
where the species occurred.
Species Stand Productivity Basal Area Change Thinning Prior First Inventory Maturity Class N
Graminoids
Broad leaved grasses 0.044 <0.001 0.066 0.160 482
Narrow leaved grasses 0.613 0.431 0.397 0.204 953
Carex globularis 0.606 0.686 0.014 0.527 240
Herbs
Anemone nemorosa 0.429 0.036 0.538 0.048 195
Maianthemum bifolium 0.111 0.963 0.299 0.067 470
Melampyrum spp. 0.718 0.099 0.010 0.368 762
Oxalis acetosella 0.325 0.844 0.287 0.020 259

Forests 2021,12, 475 12 of 16
Table A1. Cont.
Species Stand Productivity Basal Area Change Thinning Prior First Inventory Maturity Class N
Dwarf shrubs
Calluna vulgaris 0.081 0.482 <0.001 0.320 442
Empetrum nigrum 0.698 0.346 0.854 0.866 486
Rubus chamaemorus 0.634 0.291 0.447 0.334 172
Rhododendron tomentosum 0.857 0.570 0.066 0.595 133
Vaccinium myrtillus 0.459 0.318 0.004 0.018 1230
Vaccinium uliginosum 0.374 0.233 0.467 0.434 325
Vaccinium vitis-idae 0.777 0.633 0.300 0.232 1143
Spore plants
Equisetum sylvaticum 0.482 0.258 0.347 0.503 236
Gymnocarpium dryopteris 0.435 0.351 0.828 0.234 222
Lycopodiaceae 0.818 0.552 0.271 0.037 278
Tall ferns 0.096 0.528 0.611 0.474 124
Lichens
Cladonia spp. excl. Cladina 0.151 0.46 0.704 0.570 799
Cladonia grp. Cladina <0.001 0.608 0.401 <0.001 607
Other ground lichens 0.003 0.623 0.572 0.443 626
Mosses
Hylocomium splendens 0.148 0.083 0.086 0.046 1194
Pleurozium schreberi 0.718 0.070 0.007 0.268 1262
Polytrichum spp. 0.825 0.997 0.186 0.517 465
Sphagnum spp. 0.275 0.513 0.686 0.257 629
Appendix B
To further explore patterns among the vascular plants showing significantly decreasing
cover we utilized the ecological indicator values (EIV) provided by [
23
]. Although available
for a large range of aspects, we limit this comparison to EIVs directly linked to factors
well-known to influence boreal forest plants, that is, heat requirement, continentality, light,
moisture, soil reaction (pH) and nitrogen. For these six EIVs, an ordinal scale is provided
by [
23
]. Although the scales are ordinal, we have calculated the mean EIV values for the
species showing a significant decrease in cover in our study and compared these with the
mean values for all other vascular plants included in the Swedish NFI. However, note that
broad-leaved grasses cannot be included since the group includes several species with
contrasting EIVs.
•Heat indicator—range from 1 (high alpine) to 13 (climate cultivation zone 1 in south-
ernmost Sweden)
•Continentality indicator—range from 1 (hyperoceanic) to 9 (hypercontinental)
•Light indicator—range from 1 (deep shade) to 7 (always in full sun)
•Moisture—range from 1 (very dry) to 12 (deep permanent water)
•Soil pH—range from 1 (strongly acidic, pH < 4.5) to 8 (alkaline, pH > 7.5)
•Nitrogen—range from 1 (very N-poor) to 9 (mostly on artificially N-enriched soils)
Table A2.
Individual and mean EIV for species showing decreasing cover in this study and mean value for all other species
included in the Swedish NFI. No. of regions indicates the number of regions where the species significantly decreased
in cover.
Species No. of Regions Heat Continentality Light Moisture Soil (pH) Nitrogen
Species included with decreasing cover
Maianthemum bifolium 3 4 4 3 4 3 3
Narrow leaved grasses * 3 2 5 4 4 3 5
Melampyrum spp.** 2 3.5 5.5 4.5 3.5 3 3.5
Equisetum sylvaticum 2 3 5 4 5 2 3
Carex globularis 2 4 8 4 6 2 2
Rubus chamaemorus 2 3 5 4 6 1 2
Vaccinium myrtillus 2 3 5 4 5 2 2
Empetrum nigrum 2 3 6 5 6 2 3
Gymnocarpium dryopteris 1 3 5 2 4 4 6

Forests 2021,12, 475 13 of 16
Table A2. Cont.
Species No. of Regions Heat Continentality Light Moisture Soil (pH) Nitrogen
Oxalis acetosella 1 4 4 2 5 4 5
Anemone nemorosa 1 5 4 4 5 4 6
Calluna vulgaris 1 5 5 5 4 2 2
Vaccinium uliginosum 1 2 6 5 6 2 2
Mean value 3.5 5.2 3.8 4.9 2.9 3.4
NFI species (N=36) not included in the study or not showing decreased cover
Mean value 4.8 4.9 4.0 5.4 4.7 5.4
* EIV used for Avenella flexuosa, which is by far the most dominant species in this group. ** Average EIV for M. pratense and M. sylvaticum,
which are by far the two most dominant Melampyrum species in the studied forests.
Appendix C
Ordination details
R-Package vegan [24]
Dissimilarity measure: Bray-Curtis
Dimensions: 4
Final stress: 0.061801
R-functions used
set.seed(13)
metaMDS(comm = group, k = 4, try = 20, trymax = 50, maxit = 1000)
envfit(group.sol, env, permu = 1000)
Table A3. Significance test of region and inventory period.
r2p-Value
Region 0.0304 <0.0001
Period 0.0021 =0.0040
Table A4. Species group scores.
NMDS1 NMDS2 NMDS3 NMDS4
Graminoids −0.48293 0.178719 0.513926 0.278248
Herbs −0.658058 0.256932 −0.1777114 −0.4974966
Spore plants −1.053622 −0.587013 −0.7484537 0.465134
Dwarf shrubs 0.307069 −0.163221 −0.0674924 0.0319021
Lichen 0.647159 0.894044 −0.339901 0.2470946
Mosses 0.197559 −0.157064 0.1328394 −0.1176820
Table A5. Region/time (“site”) scores based on average scores for individual plots.
Region Time NMDS1 NMDS2 NMDS3 NMDS4
1 1 0.10220234 −0.06057463 −0.0929060 0.06475263
2 1 −0.01220946 0.00021519 −0.0994352 0.02586666
3 1 −0.06833441 0.07131811 0.01481396 −0.01272042
4 1 −0.07908161 0.03532577 0.14189990 −0.03512510
1 2 0.12696383 −0.06684115 −0.06356854 0.06253225
2 2 0.02208145 −0.02946240 −0.08038184 0.00224422
3 2 −0.00856692 0.01606524 0.0243088 −0.03468139
4 2 −0.04081097 −0.00274272 0.12981631 −0.04795374

Forests 2021,12, 475 14 of 16
Figure A1.
NMDS ordination (dimensions 3 and 4) of the six different species groups where markers
provide the average “sites scores” for the four different regions at the two inventories. Arrows
denote the direction of change. Note that, to increase the readability of the figure, the placement of
the species group scores is not representing their actual scores since these are outside the current
axes. However, their relative position indicates where they occur in the ordination. The difference
between regions remains clear also along the NMDS 3 and 4 axes, while the change between periods
is negligible.
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