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A continental comparison indicates long-term
effects of forest management on understory
diversity in coniferous forests1
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Andreas Schmiedinger, Juergen Kreyling, Manuel J. Steinbauer,
S. Ellen Macdonald, Anke Jentsch, and Carl Beierkuhnlein
Abstract: Promotion of species diversity has become a major goal in forestry. This requires an understanding of the impacts
of management disturbance on species diversity relative to natural drivers such as climatic or edaphic conditions on the relevant temporal scales, i.e., centuries. We examined the effects of long-term management disturbance on understory plant diversity in coniferous forests by comparing structure types (ages since disturbance) between regions with comparable abiotic
settings but contrasting management history, i.e., management for centuries in central Europe versus the first logging in primary forests in western Canada. We systematically sampled three age classes after disturbance and compared their alpha diversity and species composition. The structure types (age classes) showed similar differences in alpha diversity in both
landscapes, while the response of species compositions differed between the two. Fewer late-successional specialists occurred in the European landscape. Within the setting of our study, the structure types, which reflect the time since major forest management disturbance, affected understory species richness and composition at least as strongly as environmental
conditions such as climate, soil, and tree layer diversity across the broad altitudinal gradients that we sampled. Our results
suggest that forest management affects the diversity of coniferous forests, with management for centuries disadvantaging
late-successional specialists. Furthermore, it appears that human action is becoming the major determinant of diversity of
coniferous forests, emphasizing the need for sustainable management schemes.
Résumé : La promotion de la diversité des espèces est devenue un enjeu forestier important. Pour ce faire, il est important
de comprendre les impacts des perturbations causées par l’aménagement sur la diversité des espèces en relation avec des
facteurs naturels comme les conditions climatiques ou édaphiques sur une échelle temporelle pertinente, c’est-à-dire des siècles. Nous avons étudié les effets à long terme des perturbations causées par l’aménagement sur la diversité des plantes de
sous-bois dans des forêts de conifères en comparant le type de structure (temps écoulé depuis la perturbation) entre des régions ayant des caractéristiques abiotiques semblables, mais un historique d’aménagement très différent, c’est-à-dire un aménagement séculaire en Europe centrale et une première coupe dans une forêt vierge de l’ouest du Canada. Nous avons
systématiquement échantillonné trois intervalles de temps après la perturbation et comparé leur diversité alpha et leur composition en espèces. Les différences de diversité alpha entre les types de structure (classes d’âge) des deux milieux étaient
semblables alors que la réaction de ces milieux en termes de composition en espèces était différente. Il y avait moins de spécialistes de fin de succession dans le milieu européen. Dans le cadre de notre étude, le type de structure, qui reflète le temps
écoulé depuis la dernière perturbation forestière majeure, a influencé la richesse des espèces de sous-bois et leur composition au moins aussi fortement que les conditions environnementales comme le climat, le sol et la diversité de la strate arborescente le long du large gradient altitudinal que nous avons échantillonné. Nos résultats indiquent que l’aménagement
forestier influence la diversité des forêts de conifères et que l’aménagement séculaire désavantage les spécialistes de fin de
succession. De plus, il semble que l’action humaine soit devenue un déterminant majeur de la diversité des forêts de conifères, ce qui souligne le besoin de schémas d’aménagement durable.
[Traduit par la Rédaction]
Introduction
Coniferous forests are the characteristic zonal ecosystem of
the boreal biome that covers major portions of the Northern
Hemisphere. Towards lower latitudes, these forests inhabit a
major altitudinal zone in temperate climates (e.g., in central
Europe). Land use is considered to be one of the major
threats to biodiversity in boreal forest ecosystems (Sala et al.
2000), yet maintenance of forest biodiversity is important be-
Received 30 November 2011. Accepted 28 March 2012. Published at www.nrcresearchpress.com/cjfr on 26 June 2012.
A. Schmiedinger, J. Kreyling, M.J. Steinbauer, and C. Beierkuhnlein. BayCEER, Department of Biogeography, University of
Bayreuth, Universitaetsstr. 30, 95440 Bayreuth, Germany.
S.E. Macdonald. Department of Renewable Resources, University of Alberta, Edmonton, AB T6G 2E3, Canada.
A. Jentsch. BayCEER, Disturbance Ecology, University of Bayreuth, Universitaetsstr. 30, 95440 Bayreuth, Germany.
Corresponding author: Juergen Kreyling (e-mail: [email protected]).
1This
article is one of a selection of papers from the 7th International Conference on Disturbance Dynamics in Boreal Forests.
Can. J. For. Res. 42: 1239–1252 (2012)
doi:10.1139/X2012-052
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1240
cause of its close connection to ecosystem functions such as
productivity (Pretzsch 2005). Most plant diversity in boreal
forests is contained within the understory plant community,
which also plays key roles in nutrient cycling and provides
the template for faunal diversity (Nilsson and Wardle 2005;
Hart and Chen 2008).
Surprisingly, we still have a poor understanding of the
drivers of understory richness in boreal forests (Barbier et al.
2008; Hart and Chen 2008). There is evidence that the structure and composition of the tree layer play an important role
in determining understory composition by controlling resource availability such as light, water, and nutrients (Barbier
et al. 2008). Compared with this, effects of environmental
factors such as soil texture and slope appear to be of secondary importance (Hart and Chen 2006). Because of their limited species pool and wide species’ ranges (Gordon 1996), it
seems likely that diversity of boreal forests is more strongly
affected by disturbance and succession than by environmental
conditions such as climate, geology, and soil characteristics.
This expectation is supported by a few studies of rather local
scope, i.e., covering small environmental gradients such as
differences between north- and south-facing sites (Økland et
al. 2003).
Forest management is replacing fire as the main disturbance in coniferous forests throughout the Northern Hemisphere. The characteristic species in coniferous forests have
strategies to cope with disturbances such as fire and insect
outbreaks; some even depend on them (Hart and Chen
2006). Yet, natural and anthropogenic disturbances exert different effects on vegetation (Hart and Chen 2008). The influence of forest management on biodiversity has been
extensively discussed (e.g., Norton 1996; Brosofske et al.
2001) and suggestions for the conservation of biodiversity in
managed forests have been made (e.g., Hansen et al. 1991;
Spence 2001) with a special focus on the promotion of oldgrowth attributes (Bauhus et al. 2009). However, regeneration
cycles in coniferous forests require centuries rather than decades. One plausible expectation of long-term management is
an increasing dominance by opportunistic or early-successional species at the expense of late-successional specialists
(Duffy and Meier 1992).
Evaluation of long-term effects of forest management requires comparison of forest stands managed for centuries
with old-growth control stands, but such comparisons are
nearly impossible. In North America, much of the logging
still occurs in primary forests, making it difficult to understand long-term impacts (Hart and Chen 2006). In Europe,
almost all forests are anthropogenically used (Uotila and
Kouki 2005), some for millennia. Therefore, a comparison
between central Europe with its anthropogenic disturbance
history since medieval times and western Canada could provide further insight into the response of understory diversity
and composition to long-term forest management. A necessary precondition for such a comparison is high phylogenetic
similarity of coniferous forests across the Northern Hemisphere (Brochmann et al. 2003; Qian et al. 2007). Besides
taxa, conifer forests of North America and Europe display
high structural and functional similarity (Nilsson et al.
2002). They differ, however, in tree species diversity and
land use history. European forests are depauperate in the tree
species pool due to the disproportionate impact of glaciation
Can. J. For. Res. Vol. 42, 2012
(Svenning 2003). More importantly, the duration of human
impact on forests is much longer in Europe than in North
America.
Herein we present the results of an investigation of patterns and drivers of understory plant biodiversity in coniferous forests in the Monashee Mountains (British Columbia,
Canada) and in the Fichtelgebirge (Bavaria, Germany) at the
landscape scale. The two areas have similar abiotic site conditions (i.e., climate, bedrock, soils, altitudinal gradient) but
different management history (logging of primary forests versus intensive human disturbance for at least eight centuries).
We addressed the following hypotheses: (1) disturbance due
to forest management promotes similar responses in understory plant species richness and composition across coniferous forests of two landscapes in different continents, (2) the
environmental setting (climate, soil conditions, tree layer
characteristics) along broad altitudinal gradients is less important for the diversity and composition of the understory
than are the effects of forest management, and (3) the longer
history of human disturbance in Europe results in reduced
floristic differences between different forest age classes and
especially between mature stands and those regenerating after
harvesting.
Material and methods
Here, we investigated the effects of forest management disturbance on understory diversity in coniferous forests with
comparable abiotic settings but contrasting management history. We used systematic sampling in three structure types
(age classes after disturbance) in a central European landscape (Fichtelgebirge, Germany) and a landscape in western
Canada (Monashee Mountains, British Columbia), both being
dominated by montane coniferous forests. Specifically, we
compared the differences in species richness, Shannon index,
evenness, and species compositions between the three structure types. Further, we tested the influence of management
disturbance (tree layer structure) as compared with environmental site conditions such as climate, soil properties, and
tree layer diversity.
Study areas
Both study areas covered 676 km2 (26 km × 26 km). The
Fichtelgebirge is located in northeastern Bavaria, Germany
(Fig. 1). The first intensive anthropogenic influences on the
forests date back to the 12th century with vast clearings for
settlements. Prior to that time, the forests were dominated by
Fagus sylvatica L. with Abies alba Mill. as the main conifer
(Reif 1989). In the centuries since then, the pristine woods
have been severely impacted by mining and charcoal burning
for iron smelting and the energy-consuming glass and porcelain industries. Substantial reforestation in the 1790s resulted
in the present dominance of Picea abies (L.) Karst. (Reif
1989). At the present time, the irregular shelterwood system
is predominantly used for forest management.
The study area in the Monashee Mountains is located in
southeastern British Columbia, Canada (Fig. 1). The Monashee Mountains are the western ridge of the Columbia
Range. The tree layer consists mainly of Abies lasiocarpa
(Hook.) Nutt., Picea glauca (Moench) Voss × Picea engelmannii Parry ex Engelm., Pinus contorta Douglas ex
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1241
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Fig. 1. Geographical setting of the two study areas Monashee Mountains in North America and Fichtelgebirge in Europe (left panels) and
sample plots (right panels). The squares in the right panels represent the study areas of 26 km × 26 km. Plot selection was based on a systematic grid of 2 km × 2 km with each structure type sampled within selected grid cells upon their availability. See text for further explanations of grid cell and plot selection.
Loudon, Thuja plicata Donn ex D. Don, and Pseudotsuga
menziesii (Mirb.) Franco. The Monashee Mountains were
not strongly modified by humans until the mid-20th century.
The oldest clearcuts in the study area date back to 1966 (BC
Ministry of Forests 2001). No second-growth stands have yet
been harvested; age of the mature stands is related to standreplacing fires or beetle infestations. The current standard
practice for harvest is clear-cutting followed by slash-piling,
burning, and planting.
Both study areas are characterized by comparable abiotic
conditions concerning geological substrate and soil characteristics (Table 1) and both cover a substantial altitudinal (i.e.,
climatic) gradient of more than 500 m. Climatically, mean
annual temperature in the Fichtelgebirge is warmer than in
the Monashee Mountains. This difference, however, is mainly
due to warmer winter minima; summer temperatures are very
similar (Table 1). Precipitation and seasonality of precipitation are very comparable between the study areas (Table 1).
Sampling methods
This study concentrates on the diversity of understory vegetation, including vascular plants and epigeic mosses. The
26 km × 26 km study area was divided into a systematic
grid of 2 km × 2 km cells; initial sampling took place in 24
cells that were regularly distributed. In a second phase, we
sampled additional cells between pairs of the initial 24 that
had a dissimilarity in understory composition (Bray–Curtis
index) higher than the total mean dissimilarity of the entire
set of 24 (Fig. 1). Within each 2 km × 2 km grid cell selected for sampling, we randomly located three plots
(10 m × 10 m), one in each of the three structure types if
available.
The three structure types were as follows. The disturbed
stands represented harvested areas (in the Fichtelgebirge silvicultural clearings after windthrows or bark beetle outbreaks) not more than 10 years old. The mature stands were
defined as older than 100 years with no more than six trees
per 100 m2 and represent mature and old-growth stands in
the Monashee Mountains, whereas in the Fichtelgebirge,
only second-growth mature stands occurred. Intermediate
stands were defined based on size (diameter at breast height),
tree density, and the estimated stand age in relation to the
mature stands (Table 1). Compared with the Fichtelgebirge,
frequency of intermediate stands in the Monashee Mountains
was much lower, resulting in only five plots meeting the criteria for this structure type within the sampled grid cells.
Therefore, all analyses were run with and without the intermediate stands. Omission of the intermediate stands did not
lead to qualitative changes in the results. Further criteria for
plot selection were avoidance of forest management infrastrucPublished by NRC Research Press
1242
Can. J. For. Res. Vol. 42, 2012
Table 1. Characterization of the two study areas Fichtelgebirge (Germany) and Monashee Mountains (Canada).
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Structure
type
Altitude (m asl)
Bedrock
Humus forms
Typical soil types (WRB system)
Soil texture
Mean annual temperature (°C)
Maximum temperature of the warmest month (°C)
Minimum temperature of the coldest month (°C)
Annual precipitation (mm)
Precipitation seasonality (coefficient of variation
in monthly precipitation) (mm)
Absolute species richness within sampled plots
Stand age (years)
Stand height (m)
Tree canopy cover (%)
Species richness first tree layer
pH (organic layer)
Number of plots
DS
IS
MS
DS
IS
MS
DS
IS
MS
DS
IS
MS
DS
IS
MS
DS
IS
MS
Fichtelgebirge
680±104 (525–1002)
Granite, Phyllite, Gneiss
Mors, Moders
Podzols and Cambisols
Sand and silt
6.5±0.5 (4.5–7.7)
20.6±0.6 (18.0–22.1)
–5.3±0.4 (–6.8 to –4.0)
761±53 (661–979)
18.3±1.5 (15.0–22.0)
Monashee Mountains
1468±211 (980–1935)
Granite
Mors, Moders
Podzols and Cambisols
Silt and sand
2.4±1.2 (–0.5 to 6.0)
20.7±1.4 (17.1–25.2)
–11.5±0.9 (–13.7 to –8.8)
654±36 (580–755)
19.9±1.4 (18.0–25.0)
155
6±2
53±15
120±49
3±7
21±4
29±5
2±9
62±10
49±12
0±0
1±1
1±0
2.8±0.3
2.7±0.4
2.7±0.6
37
37
41
176
10±7.5
103±30
166±53
1±3
19±4
28±6
3±14
50±14
46±16
0±1
3±2
2±1
4.3±0.6
3.8±0.5
4.0±0.7
24
5
35
Note: Given are means ± 1 SD with range in parentheses. Climate data from http://www.worldclim.com with a spatial resolution of 30 arcseconds (∼1 km) (Hijmans et al. 2005) are given as long-term averages (1950–2000) for each study area; all other data are per plot. Structure
types: DS, disturbed stands; IS, intermediate stands; MS, mature stands.
ture like extraction lines, log trails, and forest service roads as
well as forest edges, water bodies, and game feedings.
Abundance (cover) for each vascular plant and epigeic
moss species was recorded on the Londo scale (decimal scale
in steps of 10% cover) within each 100 m2 plot. We differentiated between the moss, graminoid, herb, shrub, and two tree
layers with the second tree layer comprising all trees smaller
10 m height and the first tree layer those larger than 10 m
height. The nomenclature of vascular plant species followed
Douglas et al. (1998–2001) for the Monashee Mountains and
Oberdorfer (2001) for the Fichtelgebirge and for mosses followed Lawton (1971) for the Monashee Mountains and
Frahm and Frey (1992) for the Fichtelgebirge.
Within each plot, soil samples were taken with five replicates of the LFH or Oh and Ah horizons. Samples were dried
and sieved to 2 mm for analysis of pH values (measured in
1 mol/L KCl), soil texture, and nutrient availability (aluminium, magnesium, potassium, and calcium concentrations determined via ICP-AES on KCl extraction). After grinding the
sieved samples, C/N ratios were measured with a C/N analyzer. The structure of the tree layer was characterized by estimated canopy cover, the number of species, tree density,
stand height, diameter at breast height, and basal area. Further, slope, altitude, aspect, and stand age (based on forest
cover maps verified by tree coring) were documented for
each plot.
Statistical analyses
Differences in understory alpha diversity (i.e., species richness, Shannon index, and evenness) among structure types,
study areas, and their interaction were analyzed by blocked
ANOVA using the cell ID as a random factor to account for
spatial dependencies (using the function lme from the package nlme 3.1-102 for the R statistics system). Significant
main effects in the ANOVA were followed by Tukey HSD
post hoc comparisons with a = 0.05 (using the function glht
from the package multcomp 1.2-7 for the R statistics system).
Normality and homogeneity of variances were tested by examining the residuals versus the fitted plots and the normal
q–q plots of the models. No transformations were necessary.
An unconstrained ordination, nonmetrical multidimensional scaling (NMDS), was used to illustrate variation in
community composition between the structure types (using
the function metaMDS from the package vegan 1.17-11 for
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Schmiedinger et al.
the R statistics system). The significance of differences in
community composition between the structure types was
evaluated by an analysis of similarity (ANOSIM) after 10
000 permutations using the function anosim from the package vegan 1.17-11 for the R statistics system. Bray–Curtis
similarity based on the species-specific abundance was used
as a distance metric for NMDS and ANOSIM.
A permutational multivariate analysis of variance (PERMANOVA) (Anderson 2001) was utilized to test for the effect of structure type, study area, and their interaction on
understory composition, i.e., testing if the response to management was similar in both study areas. The permutationbased PERMANOVA is a multivariate, nonparametric analogue of univariate analysis of variance. Here, PERMANOVA was run on the species abundance data with Bray–
Curtis index as dissimilarity measure and 9999 permutations.
The relative influence of different drivers on the species
richness and community composition was assessed by a variance partitioning based on linear regression and redundancy
analysis ordination (RDA) (Legendre 2008). Variance partitioning can differentiate the percentage of variance in species
richness or community composition that is explained by
structure type alone, by other drivers alone, or jointly by
structure type and alternative drivers. Twenty-three explanatory variables were summarized into four groups (Table 2).
For each explanatory variable, the significance of the optimal
relation (i.e., quadratic, square root, log transformation) to the
dependent variable was assessed beforehand based on significance and explained variance for each study area. This was
implemented for species richness by univariate regression
(significance assessed via the F statistic) and for community
composition via an RDA with one explanatory variable (significance assessed via an ANOVA-like permutation test as
implemented in the function anova.cca). Only those variables
with a significant relation were included in the final variance
partitioning model using the function varpart from the package vegan 1.17-11 for the R statistics system.
Furthermore, the relative importance of the different drivers on species composition was tested by a correlation of all
explanatory environmental parameters with the two-dimensional NMDS of the species compositions using the function
envfit in the package vegan 1.17-11 for the R statistics system.
The affinity of species to structure types was evaluated by
an indicator species analysis (Dufrêne and Legendre 1997)
on abundance data with the function indval of package
labdsv version 1.41 for the R statistics system for each study
area separately.
Homogeneity of understory community compositions in
mature stands was measured by multiplicative partitioning
and by mean Bray–Curtis similarity (1 – Bray Curtis distance) of all pairwise comparisons (Jurasinski et al. 2009).
All statistical analyses were performed using R 2.13.1 (R Development Core Team 2011).
Results
Effects of structure type and study area
We found similar levels of gamma diversity in both study
areas; a total of 155 understory plant species were found in
the Fichtelgebirge and 176 species in the Monashee Moun-
1243
tains. There were 21 species that were found to occur in
both regions. Tree species richness in the mature plots was
higher in the Monashee Mountains than in the Fichtelgebirge
(2.2 versus 1.2, t test: p < 0.001). Understory richness, however, was not significantly affected by canopy diversity (linear regression of understory diversity on tree layer diversity
over all mature plots: Monashee Mountains: adjusted r2 =
0.08, ns; Fichtelgebirge: adjusted r2 < 0.01, ns). Both structure types and study area had a significant influence on
measures of alpha diversity, either for all species combined
or by life form, but there were only a very few instances in
which these two main effects had a significant interaction
(Table 3).
Considering all species combined, the highest species richness was found in disturbed stands followed by mature stands
for both study areas (Fig. 2). The lowest species richness was
present in the intermediate stands. The different life forms for
vascular plants generally followed these same trends in species richness (Fig. 2). Results for the Shannon index and
evenness were variable. For all species combined and for the
tree layer, the Shannon index and evenness did not differ significantly between structure types in the Monashee Mountains but did in the Fichtelgebirge. For all species combined,
the Fichtelgebirge showed the highest Shannon index values
in intermediate and mature stands, while the highest evenness
was in the intermediate stands (Fig. 2).
Even when analyzed by life forms (trees, shrubs, grasses,
herbs, and mosses), very few (4 out of 18) interactions were
significant (Table 3). There were significant interactions between structure type and study area for moss richness. Richness increased with time since disturbance in both study
areas but the increase was much stronger in the Fichtelgebirge. Furthermore, the evenness of the shrub layer was distinctly lower in mature stands of the Fichtelgebirge as
compared with the other structure types, while there were no
differences in shrub evenness among structure types in the
Monashee Mountains (Fig. 2). In contrast, the Shannon index
and evenness of the herb layer did not differ between structure types in the Fichtelgebirge, while in the Monashee
Mountains, disturbed stands had lower values for these variables than the other two structure types (Fig. 2).
In both study areas, species composition differed strongly
between structure types; disturbed stands were clearly separated from both intermediate and mature stands (Fig. 3).
PERMANOVA showed highly significant differences among
structure types (F = 12.6, p < 0.001) and study areas (F =
47.2, p < 0.001) and the significant interaction showed that
the study areas differed in the response of understory species
composition to the structure types (interaction: F = 6.0, p <
0.001). Quantitatively and qualitatively similar results were
obtained when the analysis was performed without the intermediate stands.
Homogeneity of understory vegetation in the mature stands
was higher in the Fichtelgebirge than in the Monashee Mountains (multiplicative partitioning: 7.5 versus 5.5; mean Bray–
Curtis similarity: 0.45 versus 0.35, p < 0.001 according to a t
test). A similar, yet weaker difference was found for disturbed
stands (multiplicative partitioning: 6.0 versus 5.0; mean
Bray–Curtis similarity: 0.41 versus 0.34, p < 0.001 according
to a t test).
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Can. J. For. Res. Vol. 42, 2012
Table 2. Explanatory variables used in the variance partitioning divided into four major groups to differentiate the effect of
management from other possible drivers of species richness and composition (see Fig. 4 for results).
Group name
Tree layer structure
Tree layer diversity
Soil
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Climate
Explanatory variables
Stand age, structure type, stand height, canopy cover in the first and second tree layer (five variables)
Number of species in the first and second tree layer, tree density (three variables)
Concentrations of aluminium, magnesium, potassium, and calcium, pH, and C/N ratio of the O (LFH)
and A layer (12 variables)
Altitude, aspect, slope (three variables)
Table 3. Results of ANOVA testing for the effects of the three structure types (disturbed stands, intermediate
stands, and mature stands), the two study areas (Fichtelgebirge and Monashee Mountains), and their interaction on
alpha diversity measures (richness, Shannon index, and evenness) for all understory species and separated by life
forms.
Richness
All life forms
Trees
Shrubs
Herbs
Graminoides
Mosses
Structure type
Study area
Interaction
Structure type
Study area
Interaction
Structure type
Study area
Interaction
Structure type
Study area
Interaction
Structure type
Study area
Interaction
Structure type
Study area
Interaction
F
17.7
75.7
0.9
19.3
0.0
0.0
13.8
301.0
0.0
6.0
142.7
0.1
16.2
0.0
0.1
19.0
58.0
4.9
p
<0.001
<0.001
0.390
<0.001
0.943
0.973
<0.001
<0.001
0.437
0.003
<0.001
0.868
<0.001
0.857
0.940
<0.001
<0.001
0.009
Shannon index
Evenness
F
p
2.0
69.4
1.0
7.8
1.0
0.7
16.6
258.2
2.9
3.4
52.1
9.1
6.1
2.3
2.5
3.0
16.8
0.3
0.141
<0.001
0.360
<0.001
0.329
0.513
<0.001
<0.001
0.057
0.035
<0.001
<0.001
0.003
0.131
0.083
0.050
<0.001
0.779
F
12.0
23.4
2.4
1.1
1.3
1.2
14.4
96.8
6.7
0.7
0.1
5.5
3.9
1.5
3.5
1.2
0.5
0.3
p
<0.001
<0.001
0.091
0.326
0.262
0.315
<0.001
<0.001
0.002
0.497
0.815
0.005
0.021
0.221
0.031
0.294
0.475
0.768
Note: Significant effects in bold.
Relative importance of explanatory variables
In addition to the effects of structure type and study area,
understory species richness was also influenced by the other
explanatory variables examined (Table 2; Fig. 4). In the Fichtelgebirge, the largest part of the explained variance was due
to the combined influence of tree layer structure, tree layer
diversity, and soil parameters (Fig. 4a). Tree layer diversity
showed no individual explanatory power, while considerable
and similar amounts of the variance were associated with tree
layer structure (24%) and soil characteristics (24%). Surprisingly, climate variables (as encapsulated in altitude, aspect,
and slope) did not explain any of the variation in species
richness. In the Monashee Mountains, the overlap in explanatory power between tree layer structure, tree layer diversity,
and soil characteristics was considerably smaller (Fig. 4b).
Again, no variance was explained by tree layer diversity
alone; a very small part was explained by tree layer structure
alone. Even soil characteristics, despite playing the largest
role in shared explanation, showed almost no individual explanatory power. Here, climate variables jointly with soil
characteristics contributed significantly.
Species composition was mainly influenced by the combination of tree layer structure and tree layer diversity in both
study areas (Figs. 4c and 4d). In the Fichtelgebirge, tree layer
structure and tree layer diversity jointly explained almost 45%
of the variance (with an additional 17% by structure alone),
while soil characteristics and climate together contributed another 20% (Fig. 4c). Eighteen percent of the explained variation was shared among tree layer structure, tree layer
diversity, and soil characteristics, while climate contributed
rather weakly. In the Monashee Mountains, the majority of
variation (48%) was jointly explained by tree layer structure
and diversity (with an additional 5% by structure alone)
(Fig. 4d). Besides some variation being explained by different combinations of the variable groups, climate alone contributed 26%.
Regarding single explanatory factors, characteristics of the
tree layer yielded the highest correlations in the Fichtelgebirge (≥50% of the variation) (Table 4). The structure types
explained 42% of the variation, while altitude explained only
25% and no soil parameter explained more than 20% of the
variance. In the Monashee Mountains, variables related to
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Fig. 2. Various measures of alpha diversity as influenced by structure type (DS, disturbed stand; IS, intermediate stand; MS, mature stand)
and study area over all understory species and separated by life forms (only understory, i.e., <2 m height). Numbers refer to number of plots;
boxes with the same letter were not significantly different according to Tukey post hoc comparisons. ANOVA results are presented in Table 3.
Published by NRC Research Press
1246
Can. J. For. Res. Vol. 42, 2012
Fig. 4. Results of variation partitioning of (a and b) species richness and (c and d) species composition between the groups of explanatory
variables: tree layer structure (i.e., time since major disturbance), tree layer diversity, and soil and climate (see text and Table 2 for details).
Overlapping bars indicate jointly explained variance. Nonoverlapping parts depict variance explained only by a single group.
Fichtelgebirge
Monashee Mountains
Richness
a)
b)
Tree layer structure
Tree layer structure
Tree layer diversity
Tree layer diversity
Soil
Soil
Climate
0
20
40
c)
Composition
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Fig. 3. Nonmetric multidimensional scaling (NMDS) showing species composition of the the different structure types for each study area
separately (DS, disturbed stands; IS, intermediate stands; MS, mature stands). Final stress: 17.9 (Fichtelgebirge) and 23.0 (Monashee Mountains). Results of analysis of similarity (ANOSIM) are given, demonstrating that in both study areas, the disturbed stands were significantly
different from the intermediate and mature stands; in the Fichtelgebirge, these two were also significantly different from one another but in the
Monashee Mountains they were not.
0
20
40
0
20
40
d)
Tree layer structure
Tree layer structure
Tree layer diversity
Tree layer diversity
Soil
Soil
Climate
Climate
0
20
40
Explained variance in %
tree layer structure were highly correlated with understory
composition; stand height explained 75% of the variation,
while stand age explained 63% and the structure types 47%.
In contrast with the Fichtelgebirge, however, in the Monashee
Mountains, altitude (i.e., climatic differences) had a strong
influence, explaining 73% of the variation in understory species composition (Table 4).
Importance of mature stands
Species diversity (richness, Shannon index, and evenness),
the occurrence of certain species, and species composition
were found to be strongly influenced by the forest structure
types. Yet, the importance of mature stands differed between
the study areas: only 9 of 155 species (6%) showed a significant affinity to mature stands in the Fichtelgebirge versus 17
of the 176 species (10%) in the Monashee Mountains
(Table 5). Of these specialists of mature stands, eight were
epigeic mosses in the Fichtelgebirge with Oxalis acetosella
being the only herb. A similar number of mosses (seven)
showed significant affinity for mature stands in the MonaPublished by NRC Research Press
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Table 4. Correlation of explanatory variables with understory
species composition (overlay in nonmetric multidimensional
scaling, function envfit) sorted by decreasing r2.
Fichtelgebirge
Cover of first tree layer
Number of species in first tree layer
Tree density in first tree layer
Structure type
Stand height
Altitude
Stand age
Monashee Mountains
Stand height
Altitude
Cover of first tree layer
Stand age
Number of species in first tree layer
pH (organic layer)
Structure type
pH (A horizon)
r2
p
0.57
0.51
0.50
0.42
0.42
0.25
0.22
0.001
0.001
0.001
0.001
0.001
0.001
0.001
0.75
0.73
0.70
0.63
0.56
0.48
0.47
0.35
0.001
0.001
0.001
0.001
0.001
0.001
0.001
0.001
Note: Only highly significant correlations (p < 0.01) with r2 > 0.2
are shown.
shee Mountains and, in addition, 10 vascular plants showed
strong affinity to mature stands; these included species such
as Tiarella trifoliata, Viola orbiculata, or Goodyera oblongifolia.
A similar pattern was found for the proportion of species
that were restricted to a specific structure type; only 14% of
the species occurred exclusively in the mature stands in the
Fichtelgebirge, whereas this share increased to 22% of the
species in the Monashee Mountains. The number of species
with significant affinity to disturbed stands was comparable
between the two study areas (11% and 12%, respectively)
(Table 5). The proportion of species affiliated with intermediate stands was comparable in both regions (27% versus 29%),
whereas the proportion of species that was found in more
than one structural type was higher in the Fichtelgebirge
(56%) than in the Monashee Mountains (47%). Nevertheless,
both study areas had species that were abundant in all structure types, for instance, dwarf shrubs such as Vaccinium myrtillus in the Fichtelgebirge and Vaccinium membranaceum in
the Monashee Mountains. The grass Deschampsia flexuosa
was frequent in all structure types in the Fichtelgebirge. A
herbaceous plant, Clintonia uniflora, was the most frequent
plant across all structure types in the Monashee Mountains
where grasses had their highest abundance in disturbed
stands. There, 6% of the recorded plants were invasive species (aliens) such as Dactylis glomerata and Trifolium repens.
However, no aliens were found in the intermediate or mature
stands. In the Fichtelgebirge, aliens such as Impatiens glandulifera or Impatiens parviflora accounted for only up to 2%
of the species pool.
Discussion
Effects of forest management disturbances across
continents
Time since major forest management disturbance ex-
pressed as the three structure types affected measures of alpha diversity similarly in both study areas. Thus, forest
management disturbance is an important driver of alpha diversity irrespective of differences in regional species pool,
niche saturation, or silvicultural history. In contrast, the response of community compositions to management disturbance differed between the study areas in central Europe and
western Canada. Our results support previous conclusions
that species composition is a more sensitive indicator for
community response to forest management disturbance than
measures of alpha diversity (Brosofske et al. 2001; Hart and
Chen 2008).
The overall trend of understory species richness peaking in
disturbed stands is in accordance with earlier findings (e.g.,
Halpern and Spies 1995; Rees and Juday 2002). This pattern
is mainly driven by herb and grass species, while bryophyte
diversity is highest in mature stands, especially in coniferous
forests (Hart and Chen 2008). The early-successional herb
and grass species disappear during succession in coniferous
forests mainly because of decreasing light availability
(de Grandpré et al. 2011). Most of the understory species affiliated with disturbed stands in our study were ubiquitous
species that are common in many anthropogenically impacted
habitats. Other studies, however, have suggested that pyrophilic early-successional species may be threatened by the
shift from fire to logging as the primary disturbance factor
(Hart and Chen 2006). Conservation attention should therefore not be exclusively limited to late-successional forest
floor specialists.
Relative importance of environmental drivers
The tree layer structure, which is based on variables that
reflect the time since major forest management disturbance,
affected understory species richness and composition as
strongly or stronger than climate or soil characteristics. This
finding was surprising given the strong climatic variation
covered by the altitudinal gradients of more than 500 m in
the Fichtelgebirge and more than 800 m in the Monashee
Mountains (Table 1). At local scales, temperature and exposure, which can be viewed as a surrogate for small-scale climatic differences, are found to be correlated with understory
species composition (Økland et al. 2003; Chavez and Macdonald 2010). Interestingly, understory richness and composition in our study were much more strongly affected by
climate in the Monashee Mountains than in the Fichtelgebirge. Here, homogenization due to long-term forest management may have diminished the relevance of climatic
differences. Besides climate, edaphic conditions are reported
to drive understory species composition in coniferous forests
(Narhi et al. 2011). The relative importance of such environmental gradients in comparison with tree layer characteristics
and forest management, however, remains poorly investigated. Studies on the variation in understory species composition along considerable climatic gradients in coniferous
forests are largely missing (Hart and Chen 2008). Covering
large geographic and environmental gradients, however, is
crucial for further generalizations and evaluation of forest
management effects on understory vegetation.
Our results support the hypothesis that understory diversity
in coniferous forests is strongly determined by the composition and structure of the tree layer, as affected by prior manPublished by NRC Research Press
1248
Can. J. For. Res. Vol. 42, 2012
Table 5. Species with significant (indicator species analysis) affinity to mature stands (in bold) and disturbed stands sorted by decreasing
indicator value for each study area and structure type.
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Study area
Fichtelgebirge
Monashee Mountains
Species
Dicranum scoparium
Plagiothecium laetum
Pohlia nutans
Polytrichum formosum
Lophocolea heterophylla
Ptilidium ciliare
Bazzania trilobata
Oxalis acetosella
Leucobryum glaucum
Epilobium angustifolium
Deschampsia flexuosa
Rubus idaeus
Betula pendula
Agrostis capillaris
Galium harcynicum
Frangula alnus
Brachythecium rutabulum
Calamagrostis villosa
Betula pubescens
Galeopsis tetrahit
Calluna vulgaris
Sambucus racemosa
Urtica dioica
Holcus mollis
Athyrium filix-femina
Juncus conglomeratus
Senecio sylvaticus
Rhytidiadelphus triquetrus
Tiarella trifoliata
Clintonia uniflora
Vaccinium membranaceum
Rubus pedatus
Abies lasiocarpa
Pleurozium schreberi
Rhododendron albiflorum
Viola orbiculata
Dicranum scoparium
Orthilia secunda
Barbilophozia lycopodioides
Goodyera oblongifolia
Tsuga heterophylla
Brachythecium erythrorrhizon
Brachythecium hylotapelum
Ptilium crista-castrensis
Epilobium angustifolium
Polytrichum juniperinum
Hieracium albiflorum
Anaphalis margaritaceae
Pinus contorta v. latifolia
Ceratodon purpureus
Picea glauca x engelmannii
Rubus idaeus
Lupinus arcticus
Brachythecium albicans
Carex species2
Taraxacum officinale
Life form
Moss
Moss
Moss
Moss
Moss
Moss
Moss
Herb
Moss
Herb
Graminoid
Shrub
Tree
Graminoid
Herb
Shrub
Moss
Graminoid
Tree
Herb
Shrub
Shrub
Herb
Graminoid
Herb
Graminoid
Herb
Moss
Herb
Herb
Shrub
Shrub
Tree
Moss
Shrub
Herb
Moss
Herb
Moss
Herb
Tree
Moss
Moss
Moss
Herb
Moss
Herb
Herb
Tree
Moss
Tree
Shrub
Herb
Moss
Graminoid
Herb
Disturbed
0.07
0.06
0.11
0.26
0.09
0.09
0.00
0.03
0.16
0.97
0.63
0.96
1.00
0.99
0.95
0.94
0.80
0.95
0.86
1.00
0.97
0.97
0.91
1.00
1.00
1.00
1.00
0.05
0.06
0.24
0.21
0.12
0.09
0.02
0.14
0.04
0.15
0.23
0.00
0.00
0.00
0.03
0.07
0.04
1.00
0.99
0.97
1.00
1.00
0.97
0.75
1.00
0.98
0.93
0.96
1.00
Mature
0.93
0.94
0.89
0.74
0.91
0.91
1.00
0.97
0.84
0.03
0.37
0.04
0.00
0.01
0.05
0.06
0.20
0.05
0.14
0.00
0.03
0.03
0.09
0.00
0.00
0.00
0.00
0.95
0.94
0.76
0.79
0.88
0.91
0.98
0.86
0.96
0.85
0.77
1.00
1.00
1.00
0.97
0.93
0.96
0.00
0.01
0.03
0.00
0.00
0.03
0.25
0.00
0.02
0.07
0.04
0.00
Indicator value
0.93
0.87
0.63
0.60
0.49
0.38
0.29
0.28
0.25
0.89
0.62
0.60
0.43
0.40
0.36
0.33
0.32
0.31
0.30
0.30
0.29
0.24
0.22
0.16
0.11
0.11
0.11
0.81
0.75
0.69
0.65
0.65
0.62
0.52
0.50
0.48
0.42
0.36
0.35
0.35
0.32
0.32
0.30
0.25
0.91
0.78
0.73
0.71
0.63
0.61
0.57
0.46
0.45
0.43
0.36
0.33
p
0.001
0.001
0.003
0.008
0.001
0.008
0.001
0.014
0.009
0.001
0.023
0.001
0.001
0.001
0.007
0.004
0.011
0.011
0.007
0.001
0.005
0.017
0.009
0.011
0.043
0.046
0.047
0.001
0.001
0.002
0.014
0.001
0.002
0.001
0.004
0.001
0.015
0.022
0.002
0.002
0.003
0.018
0.009
0.020
0.001
0.001
0.001
0.001
0.001
0.001
0.002
0.001
0.001
0.002
0.001
0.002
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1249
Table 5 (concluded).
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Study area
Species
Bromus vulgaris
Festuca occidentalis
Spiraea betulifolia
Alnus viridis
Sambucus racemosa
Calamagrostis canadensis
Betula papyrifera
Dactylis glomerata
Senecio pseudaureus
Salix sitchensis
Life form
Graminoid
Graminoid
Shrub
Tree
Shrub
Graminoid
Tree
Graminoid
Herb
Shrub
agement history and stand age (see also Brosofske et al.
2001). However, tree layer diversity did not influence understory richness significantly in our data set. The structure
types and tree layer characteristics overlapped strongly in
their explained variance because management affects the tree
layer characteristics, especially dominance patterns and composition. The importance of tree layer composition for understory diversity is a crucial consideration for managers; it
suggests that restoring predisturbance tree species composition is likely important for maintaining native understory
compositions. Natural regeneration, especially in combination
with small cutblock sizes, can help achieve this goal (Kreyling et al. 2008a).
Importance of mature stands
The mosaic of disturbances and, consequently, structure
types is essential to the diversity of conifer forests (see Table 5). Ongoing forest management, however, removes oldgrowth stands and threatens the occurrence of mature stands
in general. In our study, mature stands harbored a considerably smaller share of understory specialists in the Fichtelgebirge with its long and intensive silvicultural history than in
the Monashee Mountains where second-growth stands are
yet to be harvested. In particular, only one vascular plant species was specialized to mature stands in the Fichtelgebirge,
whereas the Monashee Mountains had 10 vascular plants
that were mature forest indicators. This implies that the longterm management in Europe has led to a loss of such specialist species. This is assuming that the species pools before
management were similar, which seems probable given the
phylogenetic similarity of coniferous forests throughout the
Northern Hemisphere (Gordon 1996; Brochmann et al. 2003;
Qian et al. 2007). Uotila and Kouki (2005) identified seemingly old-growth forest stands in European Russia dominated
by P. abies and provided species lists from different successional stages after major natural disturbances. Analyzing
these lists with regard to our structure types results in nine
higher plant species (21% of all higher plants) with strong affinity (>90% abundance) to mature stands (in addition to 21
bryophytes, 25%). These numbers, together with a remarkable share of nearly 50% species occurring in their data set
and our Fichtelgebirge data set, support our conclusion that
anthropogenic disturbances for centuries, not phylogenetic
differences, predominantly affect late-successional specialists.
In addition, the tree species diversity, which was higher in
Disturbed
0.89
0.95
0.98
0.89
1.00
0.96
1.00
1.00
1.00
1.00
Mature
0.11
0.05
0.02
0.11
0.00
0.04
0.00
0.00
0.00
0.00
Indicator value
0.30
0.28
0.24
0.22
0.21
0.20
0.17
0.17
0.17
0.13
p
0.022
0.006
0.012
0.027
0.006
0.026
0.030
0.023
0.026
0.049
the North American than in the European study site, did not
influence understory diversity significantly.
Resource heterogeneity is suggested to be the main driver
of understory plant diversity in old-growth forests (Bartels
and Chen 2010) and forest management is known to reduce
spatial heterogeneity in comparison with natural disturbances
such as fire or insect outbreaks (Kemball et al. 2005). Homogenization of stands and landscapes due to forest management for centuries in the Fichtelgebirge as indicated by the
multiplicative partitioning and the mean Bray–Curtis similarity may therefore explain the lower diversity and lack of mature forest specialists of its mature stands as compared with
the old-growth stands in the Monashee Mountains. However,
since we only sampled two regions, we should be cautious in
this interpretation. Although increasing the sample size might
be possible, we argue that sites featuring forest management
for centuries will be restricted to Eurasia where almost no
pristine forests are left to compare with. Potential differences
in the continental species pool will therefore always limit the
conclusiveness of such comparisons despite the strong phylogenetic similarity among all parts of the boreal zone (Gordon
1996; Brochmann et al. 2003; Qian et al. 2007).
The differences in understory species compositions that we
observed along the succession after stand-replacing disturbance were mainly driven by the absence of specialized latesuccessional moss and herb species in the younger stands.
The time horizon necessary for their recolonization, however,
is quite unclear. There is ample evidence that two to five decades is much too short for recovery of these species in the
understory in montane coniferous and zonal boreal forests
(Selmants and Knight 2003; Kreyling et al. 2008b; Sullivan
et al. 2009). Here, our data suggest that even 50–100 years
does not allow for full recovery, emphasizing the importance
of the question if understory composition will ever recover
from management disturbance (Duffy and Meier 1992). Due
to their harsh climates, montane coniferous forests may therefore differ strongly from coastal coniferous forests, which
demonstrate relatively fast and uniform recovery of the
understory composition after clear-cutting (Halpern and Spies
1995).
The fact that the most important indicators of mature forests were mosses suggests that recovery of the bryophyte
community is particularly slow. Other studies have found
that dispersal limitations might explain the slow reestablishment of bryophyte species on forest sites where they have
been locally extirpated (Fenton and Frego 2005; Gignac and
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1250
Dale 2005). Similar reasons might also explain the prolonged
absence of herbaceous forest understory specialists (Brunet
and von Oheimb 1998; Kolb and Diekmann 2005). Conventional management activities decrease microsite heterogeneity
and result in fewer remnants of late-successional bryophytes
on site and hence fewer sources for recolonization and a decline in forest floor heterogeneity (Hart and Chen 2006).
Management practices such as retention of as little as 10%–
20% of the previous stand may promote considerably faster
recovery even of specialized bryophytes (Newmaster and
Bell 2002; Fenton and Frego 2005; Craig and Macdonald
2009).
Old-growth coniferous forest stands with their specific species diversity are becoming rare (Bauhus et al. 2009). In the
Monashee Mountains, about 25% of the study area has been
harvested since the year 1960. Approximately one third of
that was harvested in the 1990s. At the beginning of the 21st
century, about 37% of the study area consisted of stands
older than 120 years (BC Ministry of Forests 2001) and this
share will decrease rapidly if exploitation rates remain constant. Management activities ensuring the protection of oldgrowth habitats in regions without a long history of management should therefore be a conservation priority. Furthermore, silvicultural practices aimed at the restoration of oldgrowth characteristics in second-growth forests are of great
interest (Bauhus et al. 2009). For example, shelterwood harvesting focusing on enhancement of structural complexity in
the tree layer (Smith et al. 2008) or thinning of young stands
may be options to restore old-growth characteristics that will
have an important influence on the understory (Lindh and
Muir 2004). However, the intensity of canopy cover reduction is crucial, as too much reduction might just promote
early-successional species (Lindh 2008). Other experiments
show no positive effect of various levels of thinning on latesuccessional understory species (Ares et al. 2009).
Conclusions
Disturbances due to forest management are promoting
comparable responses in understory plant species richness
across coniferous forest landscapes in central Europe and
western Canada. However, the response of species compositions during succession after management disturbance differed. Fewer species that are specialized to old-growth stands
were found in central European forests with their history of
human disturbances for centuries than in the western Canadian landscape. Our continental comparison suggests that
long-lasting human impact promotes opportunistic generalists
and suppresses late-successional specialists.
Within the setting of our study, understory richness and
composition were driven at least as strongly by management
disturbance as by environmental conditions such as climate
and edaphic conditions. This is especially noteworthy because of the broad altitudinal gradients associated with
marked differences in climate and soil that were covered
within each of our two study sites. Further direct comparisons of the relative importance of anthropogenic and environmental drivers on understory diversity along broad climatic
and edaphic gradients are clearly needed for the evaluation
of the human footprint in boreal and montane coniferous forests. So far, it appears that human action is becoming the major determinant of species diversity and composition of
Can. J. For. Res. Vol. 42, 2012
boreal forests, a fact that calls for sustainable and sound management schemes.
Acknowledgements
Funding for this study was provided by the German Science foundation (DFG Be 2192/4-1), the German Academic
Exchange Service (DAAD) and the BayCEER laboratories
(funding No. 0339476 D, Federal Ministry of Education and
Research), and a Discovery Grant from the Natural Sciences
and Engineering Research Council of Canada to S.E.M. We
would like to thank Prof. Melanie Jones (University of British Columbia, Okanagan) and Hadrain Merler (OkanaganShuswap Forest District) for their cooperation and assistance
during the project.
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