Natural revegetation from indigenous soil
Naturlig revegetering fra stedegen jord
Astrid Brekke Skrindo
Dr. Scientiarum Thesis: 2005:1
Norwegian University of Life Sciences
Dept. of Plant and Environmental Sciences
Skrindo, A. B. 2005. Natural revegetation from indigenous soil. Doctor Scientiarum Thesis
2005:1. Norwegian University of Life Sciences. ISBN 82-575-0655-9
Astrid Brekke Skrindo
Dept. of Plant and Environmental Sciences.
Norwegian University of Life Sciences
P.O. Box 5003, Ås Norway
E-mail: [email protected]
2
Abstract
The main objective of this thesis was to increase the understanding about the early phase of
natural revegetation from indigenous soil on severely disturbed areas.
To evaluate the outcome of revegetation from soils of different locations, investigations were
conducted along a new main road (R23) in SE Norway. Prior to this study, the soil had been
divided into topsoil (the upper 30 cm) and subsoil (the remaining soil), stockpiled separately,
and redistributed with a 10 cm topsoil layer on the subsoil after the construction was finished.
Investigations included 10 different topsoil types at different locations, and experiments
included one other topsoil and one subsoil type with and without fertilisation treatment and in
different locations.
Revegetation was studied by recording changes in vegetation cover, vascular plant species
richness and the abundance of each species in the first years of the revegetation period, and by
analyzing the relative importance of soil content and location on the variation in vegetation
composition.
Germination success was studied on Vaccinium myrtillus, a dominant species of the
understorey of several northern hemisphere ecosystems, which may be suitable for
revegetaion along this road. Trials were conducted in growth chambers under different
experimental conditions: variable light qualities and ingestion or non-ingestion by bears as
pre-treatment.
Two years after deposition of topsoils, the vegetation cover was generally satisfactory from an
aesthetical point of view. However, the variation in vegetation cover and species composition
was considerable on different topsoils, reflecting both local variations of indigenous
vegetation and soil quality. Most of the species with decreasing abundance from the first to
the second year could be considered as africultural weeds, while most of the species with
increasing abundance often inhabit forests and forests edges.
On the roadside, the vegetation composition rapidly (after two years) reached a rather stable
state. Three years after soil redistribution, the vegetation composition was related to the soil
parameters and explanatory factors such as slope and aspect of the site, and distance to the
road. No effect of fertilisation on the vegetation composition was observed along the roadside.
Vaccinium myrtillus germinated under all treatments, although germination was reduced when
incubated at high levels of far red light, imitating tree canopy, as well as after being ingested
by bears.
We conclude that restoration of degraded rural areas in comparable environments benefits
from the use of natural revegetation from indigenous topsoil in terms of vegetation cover,
vegetation composition and heterogeneity.
Key words:
Revegetation, restoration, roadside, topsoil, indigenous vegetation, boreal forests, prorpagule
bank, Vaccinium myrtillus, germination, light quality.
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Sammendrag
Hovedmålet for denne avhandlingen er å øke kunnskapen om den tidlige fasen av naturlig
revegetering fra stedegne jordmasser på sterkt forstyrrede områder.
For å evaluere revegeteringen fra jord fra forskjellige lokaliteter, ble det utført undersøkelser
langs en ny riksveg (R23) i SØ Norge. Før denne studien startet, ble jordmassene delt inn i
toppjord (de øverste 30 cm) og undergrunnsjord. De ble lagret separert mens vegen ble
bygget, og så ble 10 cm toppjord lagt oppå undergrunnsjorda.
Undersøkelsene inkluderte 10 ulike toppjordtyper på forskjellige steder, og eksperimenter
inkluderte en annen toppjordtype og en undergrunnsjordtype på ulike steder, samt med og
uten gjødsling.
Resultatet av revegeteringen ble studert ved å registrere endring i vegetasjonsdekning,
karplantediversitet og utbredelsen av enkeltarter de første årene i revegeteringsperioden. I
tillegg ble den relative innflytelsen av jordforholdene og lokaliseringen undersøkt på
variasjonen i vegetasjonssammensetningen.
Spiringssuksess ble studert hos Vaccinium myrtillus (blåbær), en dominerende art i
undervegetasjonen i flere økosystemer på den nordlige hemisfære og samtidig en ønsket art
langs denne vegen. Spiring av blåbærfrø ble utført i vekstkammer ved ulike eksperimentelle
forhold: varierende lyskvalitet og forbehandling ved å bli spist eller ikke bli spist av bjørn.
To år etter tilbakeleggelse av toppjorden, var vegetasjonsdekningen generelt tilfredsstillende
fra et estetisk synspunkt. Likevel var variasjonen i vegetasjonsdekning og artssammensetning
tydelig mellom de ulike toppjordtypene som gjenga både lokal variasjon av den stedegene
vegetasjonen og jordkvaliteten. De fleste artene som avtok i mengde fra det første til det andre
året kan bli sett på som åkerugras mens de fleste av de artene som økte i mengde er vanlig å
finne i skog eller skogkant.
Vegetasjonssammensetningen på vegkanten ble raskt (etter to år) ganske stabil. Tre år etter at
jorda var lagt tilbake, var variasjonen i vegetasjonssammensetningen relatert til
jordparametere og til forklaringsvariable slik som helling på området, eksposisjon og
avstandene til vegen og omkringliggende vegetasjon. Det var ingen gjødslingseffekt på
vegetasjonssammensetningen langs vegkanten.
Vaccinium myrtillus spirte under alle behandlinger. Det ble redusert spiring under høyt nivå
av mørkerødt lys, som etterligner tett trekrone, og etter å ha blitt spist av bjørn.
Vi konkluderer med at restaurering av sterkt forstyrrede naturområder under sammenlignbare
miljøforhold får fordeler ved bruk av naturlig revegetering fra stedegen toppjord med hensyn
på vegetasjonsdekning, vegetasjonssammensetningen og heterogenitet.
Nøkkelord:
Revegetering, restaurering, vegkant, toppjord, stedegen vegetasjon, boreale skoger,
propagulebank, Vaccinium myrtillus, spiring, lyskvalitet.
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Contents
Abstract ..................................................................................................................................... 3
Sammendrag ............................................................................................................................. 4
Contents..................................................................................................................................... 5
List of papers ............................................................................................................................ 6
Introduction .............................................................................................................................. 7
Disturbance and human impact .......................................................................................... 7
Restoration ecology and revegetation ................................................................................ 8
Aims and objectives for the present study ....................................................................... 13
Materials and methods........................................................................................................... 14
Investigation area ............................................................................................................. 14
Study design ..................................................................................................................... 15
Data analysis .................................................................................................................... 15
Results and discussion............................................................................................................ 17
Vegetation cover and species composition on different soil types .................................. 17
The influence of environmental factors on natural revegetation...................................... 18
Variation in, and factors influencing, germination .......................................................... 19
Practical implications............................................................................................................. 21
References ............................................................................................................................... 23
Acknowledgements................................................................................................................. 30
Appendix: Papers I -IV
5
List of papers
This thesis is based on four papers, which will be referred to by their corresponding Roman
numerals.
I.
Skrindo, A. B., Pedersen, P. A. 2004. Natural revegetation of indigenous roadside
vegetation by propagules from topsoil. Urban forestry & Urban Greening 3: 29-37.
II.
Skrindo, A. B., Økland, R. H., and Pedersen, P. A. 2005. Early secondary succession
after revegetation by different topsoils on a roadside. (Manuscript).
III.
Skrindo, A. B. and Økland, R. H. 2005. Natural roadside revegetation on boreal
forest top- and subsoil. (Submitted manuscript).
IV.
Skrindo, A. B. 2005. Effects of light quality and frugivory by bears (Ursus arctos L.)
on seed germination of Vaccinium myrtillus L. (Manuscript).
6
Introduction
Disturbance and human impact
Human degradation and extensive use of nature is the most important threat to the
biological diversity (Anon. 2002). There are three ways to reduce this threat; reduce intensity
of use, conserve and restore degraded areas.
Every ecosystem is heterogeneous and continuously changing, and exposed to
disturbances, either natural of induced by human, that plays a more or less important role as
determinant of community structure and dynamics (Sousa 1984; Begon et al.1990). Of several
definitions that have been proposed for disturbance, I chose the one from Begon et al. (1990):
“Any relatively discrete event in time that removes organisms and opens up space which can
be colonized by individuals of the same or different species”. According to this definition, the
creation of a gap is highlighted, but disturbances are also linked with succession.
Furthermore, the characteristics of a disturbance (e.g. extent, time and magnitude event), will
influence the course of succession together with life history traits of the affected species (van
der Maarel 1993; Sousa 1994).
All ecosystems are affected by disturbances on different scales in time and space. In
traditional nature conservation, severely disturbed areas are often considered as “lost”
(Hendee et al. 2001; Anon. 2002) although disturbed landscapes may retain important nature
and social values and these values may be improved by restoration (Hagen 2003a).
Human activities impose on nature, reveals various kinds of disturbances including
altered nutrient supplies and hydrological conditions. While wear and tear from human
activities, directly and mediated by vehicles of different kinds (recreational areas, firing
ranges, gravel roads etc.), usually do not change the topography and other climatedetermining factors, construction of different kinds may have thorough impact on the
landscape. Preservation of indigenous vegetation close to the construction site has recently
become more valued due to the benefits of an already existing mature species composition
near the degraded site (Florgård 2004).
7
Restoration ecology and revegetation
Definition of terms
As the terms ecological restoration, rehabilitation, reclamation and revegetation often
are used as synonyms, I define each term to prohibit confusion. Restoration ecology is often
defined as “the scientific approaches to restoring the function and structure of ecosystems”
(Jordan et al. 1988; Bradshaw 1997; Hagen 2003a and ecological restoration (often called
restoration) is defined by The Society for Ecological Restoration International (SER) as “the
process of assisting the recovery of an ecosystem that has been degraded, damaged, or
destroyed” (Anon. 2004a). Rehabilitation and reclamation are synonyms and refer to the
construction of topography, soil, and plant conditions after disturbance which may give rise to
an adequately functioning ecosystem although this may differ from the original ecosystem in
important respects (Munshower 1994). Revegetation is the vegetation phase of either the
rehabilitation (reclamation) or restoration.
The correct use of term still remains an open question if it is not possible, due to
severe disturbance, to restore the exact former ecosystem but the natural ecosystem given the
new conditions. For example: is it ecological restoration or rehabilitation if you create a new
ecosystem along the edges of a large construction (e.g. road) when the foundation for the
former ecosystem does not longer exist (e.g. the trees are logged or the topography is altered)?
I will argue that it is ecological restoration if the new ecosystem is a natural edge to the
adjacent ecosystem.
History and current practice
Rehabilitation for practical and aesthetical reasons can be traced back at least to the
mid 19th century (Jordan et al. 1987), but the science of restoration ecology with the approach
of restoring the functions of ecosystems started in 1935 by Aldo Leopold (Jordan et al. 1987).
The two approaches, the applied and the scientific, are often considered to differ in purpose:
The scientific approach being connected to conservation of biodiversity (e.g. Hobbs 2002)
where as the applied approach is connected to rehabilitation with focus on the appearance
(Bradshaw 1997). Jordan et al. (1987) admonished that restoration research could contribute
to understanding basic structure and function of ecosystems, Bradshaw (1997, 2000), and
Allen et al. (1997) maintain that restoration is an acid test for understanding an ecosystem, the
latter however noting that in 1997 in the U.S.A. reclamation was still in the hands of
8
managers and only a small proportion of the projects were planned and supervised by an
ecologist. The scientific contribution to the restoration ecology has increased drastically
during the last few years (Anon. 2004a) and there is a large potential for mutual interchange
of ideas and support between the two approaches, as science can apply ecological principles
to the well-established technology of the reclaimers (Clewell & Rieger 1997; Hagen 2003a).
In Scandinavia, the goal for rehabilitation of degraded areas has shifted somewhat
over time from strong dominance of the practical and aesthetical view (Håbjørg 1976) to
limitation of environmental consequences by implementing ecological and environmental
principles in the construction process (as summed up in Folkeson 1999 for roads and
railways) and restoration of a more complete functional ecosystem that fits the surrounding
area (Anon. 1992). This can be illustrated by three examples of degraded land that needs
rehabilitation: (1) degraded and altered land around hydropower stations, (2) areas previously
used as firing ranges and 3) roadside areas.
(1) Since the beginning of 20th century hydropower stations have been built throughout
Norway. From the 1960s environmental impacts has been focused and plans for landscaping
and ecological management of the construction sites has been integrated in all new projects
(Hillestad 1992). Throughout the last 40 years, vegetation has become increasingly focused
and techniques have been developed for revegetation by seeding and planting (Hillestad 1989)
and natural revegetation on gravel (primary succession) (Hillestad 1992). More recently other
methods like addition of erosion-rugs and fertilization have been developed as well (Rørslett
et al. 1993, Eie et al. 1995).
(2) Several military training sites are now closing down leaving needs for restoration
for recreational and other use. One such area is Hjerkinn Firing Range in C. Norway in which
The Armed Forces took initiative to reclamation and later, restoration, in the late 1980’s.
Several revegetation methods have been tested as summed up by Hagen (1994, 2003b),
including seeding by local seeds as well as imported seeds, cuttings from different Salix
species, fertilisation, addition of soil and transplanting of indigenous vegetation (Hagen
2003b).
(3) Norway contains 91 916 km of public roads (Anon. 2004b); more than twice
around the globe at equator. Recently, ecological considerations have increasingly been built
into the road construction process, by placing the road in the landscape where the ecological
impact is lowest, by constructing animal and waterway passages, by preventing run-off from
road systems to important water reservoirs and wetlands without processing (Folkeson 1996;
Folkeson & Antonson 1999). Furthermore, during the last decades there has been increasing
9
focus on landscaping and plant establishment on road verges, where seeding by grass
mixtures and planting of woody species has become a standard procedure (Pedersen 1994).
These methods do, however, often turn out to give inadequate results in rural areas (Laukli et
al. 1999) and old road verges that have been revegetated naturally seem better to reach the
official goal: “to restore degraded areas and to improve road aesthetics within the natural
landscape” (Anon. 1992). Traditionally, the indigenous topsoil has been appreciated as a
valuable source for seeds and nutrients to be used in landscaping, although revegetation from
indigenous topsoil has hardly been regarded as a complete revegetation method and therefore
so far not been incorporated into road construction guidelines. To fill the gap of knowledge
about natural revegetation from topsoil as a revegetation method for roadsides, natural
revegetation from topsoil was systematically studied along a new main road, R23
Oslofjordforbindelsen, along with other revegetation techniques such as seeding by different
grass and herb mixtures, and seeding and planting of woody species (Laukli et al. 1999;
Skrindo & Pedersen 2003).
The danger of introduction of non-indigenous species and provenances, recognised as
a major threat to the biological diversity (Anon. 2005a), can be diminished by use of seeds or
plant material of indigenous species or provenance for restoration projects. Local plant
material is, however, often difficult to obtain and there is rarely enough time to produce plants
from indigenous plant material or seeds in nurseries. This dilemma needs to be handled
according to Article 8th in United Nations Convention on biological diversity of 1992:
“Prevent the introduction of, control or eradicate those alien species which threaten
ecosystems, habitats or species.” (Anon. 2004c). Two revegetation methods clearly accords
with this article: (1) transplanting of vegetation from the nearby surroundings (e.g. Hagen
2003a); (2) redistribute or leave indigenous soil for natural germination from seeds, spores
and plant parts (propagules) in the soil and from the surrounding vegetation. The term natural
revegetation can be used for situations in which the soil has been disturbed in different ways
(removed, partly removed, tramped, stockpiled and redistributed etc.).
Important issues for natural revegetation from topsoil
Natural revegetation from topsoil raises several important, partly interrelated, issues
such as practical aspects of soil erosion control, the speed of the revegetation process and the
time until an ecologically well-functioning vegetation composition that fits the surrounding
vegetation. Good understanding of species reproductive behaviours, vegetative growth rates
10
and initial phases of succession, and the relationships of these processes to climate and soil
are crucial for successful revegetation (Clewell & Rieger 1997; Palmer et al. 1997).
Broad-scaled variation in oceanity/humidity and temperature are the main factors
responsible for regional differentiation into vegetation zones (Moen 1998). In Norway the
boreal vegetation zones are most important, covering the greater part of the land area (Moen
1998). Within climatically homogeneous regions microclimate affects the local differentiation
of vegetation, e.g. in boreal forests where the species composition varies along complex
gradients partly related to incoming radiation as determined by canopy closure, aspect
favourability and inclination (R. Økland & Eilertsen 1993; T. Økland 1996; R. Økland et al.
1999; T. Økland et al. 2003). Successions after fine-scale disturbances of different severities
follow more complex patterns (Rydgren et al. 2004). One important, still unanswered question
is if large impacts such as opening of the forest canopy, altering the topography, and
stockpiling and redistributing of the soil lead to patterns of revegetation that mimic those of
fine-scale disturbances or if the revegetation patterns are different.
The topsoil is the main source for revegetation; by its content of propagules, plant
nutrients and water capacity for plant growth, micro- and macrofauna and fungi involved in
decomposition and mycorrhizal associates, and by the stabilising effect of soil itself for the
growing plants. As propagules are the main source for plant material, knowledge of the faith
for these propagules is of crucial importance for predicting the outcome of the revegetation
process. In boreal forests the correspondence between the species composition of the
understorey vegetation and the soil propagule bank varies from relatively poor to moderately
strong (cf. Eriksson 1989; Rydgren & Hestmark 1997) because most of the shade-tolerant
species do not form a persistent seed bank (Brown & Oosterhuis 1981; Bossuyt & Hermy
2001; Bossuyt et al. 2002). The species composition of the topsoil seed bank, even in boreal
forests, is therefore expected to be better suited for regeneration in the open road verge sites
than of the forest understorey from which it originates.
The composition of the persistent propagule bank differs both in number of seeds and
species composition between soil layers, as demonstrated by the larger number of seeds in the
litter layer than in the peaty mor layer of boreal forests, which in turn contains more seeds
than the bleached layer (Granström 1982; Rydgren & Hestmark 1997). Similar patterns are
also found in several linear habitats such as road verges close to agricultural fields (Berge &
Hestmark 1997).
Germination is influenced by several factors and each species has specific germination
requirements (Baskin & Baskin 1998). Knowledge of these specific requirements for
11
revegetating species will help predicting the outcome, as exemplified by the common species
in the boreal forest field layer, Vaccinium myrtillus. V. myrtillus was also chosen because
Vaccinium species and other ericaeous species would satisfy the traffic safety rules and fit
into the surrounding vegetation. Although V. myrtillus germinated over a range of
temperatures, with or without temperature stratification, it has conditional dormancy (Baskin
et al. 2000). It also requires light to germinate (Grime et al. 1981), and Giba et al. (1995)
show that germination is regulated by phytochromes and inhibited in far-red light. When V.
myrtillus seeds were sown along a gradient from forest to bog, germination was mostly
observed towards the bog end of the gradient where surviving seedlings were mostly found on
non-vegetated substrates (Eriksson & Fröborg 1996).
Soil nutrient availability influences the species composition in most (or all)
ecosystems. In boreal forests soil nutrients are forming a complex gradient together with acidbase status (R. Økland & Eilertsen 1993; T. Økland 1996; R. Økland et al. 2001). Our
knowledge of the most important gradients in boreal forests is mostly good and improving.
Nevertheless, there are still large gaps in our knowledge of the extent to which this knowledge
can be transferred to the applied situation of revegetation from indigenous topsoil and what
impact the different treatments of the soil will give. This thesis focuses on the first years of
revegetation of a roadside, beginning when the construction and preparation of the roadsides
where finished. The construction of the roadside body can be divided into different phases:
The separate removal and stockpiling of topsoil and subsoil layers, the redistribution of the
two layers in opposite order, leaving the topsoil on the top of the subsoil. During these phases,
the soil goes through major changes that may alter its quality. For instance, there has been
observed reduced microbial activity in stockpiled topsoil (Klein et al. 1984) and the
abundance of mycorrhizal infections is lower in stockpiled than in undisturbed soil with the
same amounts of fungal spores probably because infected roots disperse mycorrhiza-infection
easier than infection from spores (Rives et al. 1980). Some seeds and vegetative plant parts
(that might serve as sources for regeneration) die during storage as they get impulses for
germination when conditions are not suited for survival (Hargis & Redente 1984).
Nevertheless, good growing conditions may be found in topsoil stored for more than five
years (e.g. Stark & Redente 1987). Neither of these studies have, however, been done with
boreal soil and their focus has mostly been on the effect of soil storage on seeded and planted
plants.
Restoration of indigenous vegetation from the topsoil propagule bank shows
contradictory results: failures have been noted for several grasslands in the U.S. (Thompson &
12
Grime 1979), successes in South African shrubland (Holmes 2001), a Californian meadow
(Kotanen 1996), Western Australian (Rokich et al. 2000) and English woodland (cf. Warr et
al. 1993). Furthermore, regeneration from topsoil has proved successful for revegetation of
contaminated soils, such as lead/zinc mine tailings in China (Zhang et al. 2001) and fly ash
and gypsum in the United Kingdom (Shaw 1996). To our knowledge, restoration of
indigenous roadside vegetation from the propagule bank of indigenous topsoil has not
previously been published from Scandinavia.
Aims and objectives for the present study
The general aim of the present study is to increase the understanding about natural
revegetation from indigenous soil. The four specific aims for this thesis are:
1. To evaluate the outcome of the revegetation from topsoils of different origins, as
revealed by changes in vegetation cover, vascular plant species richness and the abundance of
single vascular plant species in the first years after the end of the construction period. (Papers
I, II, III)
2. To assess the relative importance of different sets of explanatory variables, such as
topsoil quality and environmental conditions of the site, on the variation in vegetation
composition of revegetated sites during the early phase of secondary revegetation succession.
(Papers I, II, III)
3. To compare revegetation success on one topsoil and one subsoil type under two
different treatments (fertilisation, and location inside a forest and on the roadside). (Paper III)
4. To study the germination success of a dominant of the understorey of several
northern hemisphere ecosystems, V. myrtillus, under different experimental conditions:
variable light qualities and passage or non-passage through a digestion system as pretreatment. Furthermore, we assess the intra-specific variability by comparing two different
populations, one from the boreal forest and one from the low alpine region. (Paper IV)
13
Materials and methods
Investigation area
The field study site was located along the main road, R23 Oslofjordforbindelsen,
situated in SE Norway in Frogn, Hurum and Røyken municipalities in Akershus and
Buskerud counties (10o 44’ E, 59o 42’N to 10o 25’E, 59o 44’N) (Fig. 1).
The site is situated in the boreo-nemoral region and the climate is suboceanic (Moen
1998). Annual mean (normal) precipitation for the years 1961–1990 was 920 mm at the
Drøbak meteorological station (Førland 1993). The annual precipitation in the study period
was 1192 mm (1999), 1361 mm (2000), 992 mm (2001) and 920 mm (2002), consistently
higher than normal. The precipitation during the growing seasons was higher or about normal
in all study years, with no continuous drought period.
The road construction period extended from September 1997 to July 2000. The road
was constructed taking special care to fit the road to the terrain, by natural-looking slopes and
curves, and by extending tunnels and bridges to reduce the impact on the surrounding nature
as much as possible (Laukli et al. 1999). Soil removed during road construction was divided
into to topsoil (the upper 30 cm) and subsoil (the remaining soil), which were stockpiled
separately close to the sites from which they had been removed for one to two years. The
roadsides where constructed leaving 10 cm topsoil on the subsoil.
Natural revegetation from indigenous topsoil was used as the main revegetation
method, but other revegetation methods were used locally in addition (Laukli et al. 1999;
Skrindo & Pedersen 2003). Thus, specific seed mixtures (grasses and some herbs) where used
for erosion control in steep areas, for areas with special aesthetical needs, and in all road
intersections. Woody species were planted (and, occasionally, seeded) in some areas
motivated by special aesthetical reasons. The only revegetation method dealt with in this
thesis is natural revegetation and the study does not include the construction period.
Seeds of Vaccinium myrtillus for germination studies (paper IV) were partly collected
from the forest along road R23 and partly from the low alpine region in Ål municipality in
Buskerud county, SE Norway, at 1000 m.a.s.l. (8o 34’ E, 60o 43’N).
14
Study design
To study changes in vegetation cover, species richness and the abundance of single
species, from the first to the second year (year 2000 and 2001) after the soil was redistributed,
and the difference between soil types, 10 macro plots of 25 m2 each with different topsoil
types, were placed along the road (Fig. 1). Total vegetation cover and species abundances
recorded as subplot frequency (16 subplots; T. Økland 1988), were observed in four randomly
placed permanent 1 × 1 m plots in each macro plot (paper I).
Further studies of change in vegetation composition were carried out by recording the
species abundances in these permanent plots also in year 2002 (the third year) and by
recording of explanatory variables for each plot that made possible establishment of
relationships between variation in the vegetation and environmental variation (paper II).
Seedling emergence and change in species abundance from the first to the third year
(2000 to 2002) on one topsoil type and one subsoil type was studied in relation to location and
effect of fertilisation. A factorial design replicated six times was used, each of the blocks
consisting of a split-plot with one compartment inside the forest and one close to the road.
Within each compartment, all combinations of two soil types and two fertilisation levels
(fertilised and unfertilised control) were represented (Fig. 1). The vegetation was recorded the
same way as in paper I and II: by recording subplot frequencies in 1 × 1 m plots. Soil samples
were recorded at the macro plot level.
The germination study of Vaccinium myrtillus was carried out using seeds from
different sources (boreal forest and alpine heath), subjected to different light qualities (three
different levels red to far red-ratio: light 1: R:FR = 1.15, light 2 = 0.65, light 3 = 0.35, with a
fluence rate of 40 µmol m-2 s-1) and ingestion pre-treatments (passing or not passing through a
bear’s digestion system) on seeds from the boreal forest. The experiment was conducted in
growth chambers at 18 °C with 18 hour day length. Germination was recorded three times a
week for five weeks.
Data analysis
A variety of multi- and univarite methods were used to analyse the data. Ordination
techniques (DCA, LNMDS and GNMDS) were used to extract the main gradients in
vegetation composition. Correlation analysis, analysis of variance (ANOVA), F- and t-tests
were used to interpret ordinations. Constrained ordination (CCA) and analysis of variance
were used for test the effects of different factors for significance. Wilcoxon’s Signed-Rank
15
test was used to test for differences in species abundances between years, and in soil
properties between soil types. Generalized linear models (GLM), with the Ryan-EinotGabriel-Welsh (REGWQ) multiple range test, were used to test the significance of seed
origin, light quality and ingestion pre-treatment, on germination of Vaccinium myrtillus.
Figure 1. Location of the study site, the main road (R23 Oslofjordforbindelsen). Numbered
boxes indicate positions of 10 different study topsoil types (Paper I and II). The grey square,
showing the location of experiment in paper III, the design is enlarged above.
16
Results and discussion
Vegetation cover and species composition on different soil types
The first year following soil redistribution (year 2000), the vegetation cover on the 10
different topsoil types in papers I and II ranged from 1 % to 95 % in 2000, the second year
(2001) from 5 % to 100 % (Paper I). Vegetation cover increased significantly on all soil types
from year 2000 to 2001. The heterogeneity in vegetation cover was not an aesthetical problem
as the sites with low vegetation cover was situated in areas where the surrounding vegetation
had rather low vegetation cover as well.
On the roadside, the vegetation composition rapidly reached a rather stable state. Thus,
in paper II we demonstrate that the same two coenoclines (gradients of change in species
composition) remained the most important throughout the three-year study period although
significant displacements of plot positions along one of the gradients were observed from the
first to the second year (from 2000 to 2001), and in paper III we demonstrated a consistent
coenocline structure was established in the second year (2001). The revegetation pathways
along roadsides reported in papers II and III appear less dynamic than early successional
pathways reported in studies of revegetation after disturbance in boreal forests (Jonsson &
Esseen 1998; Rydgren et al. 1998, 2004). This also accords with our results that the
revegetation pathway was less predictable in the adjacent forest than on the road verge (paper
III). This is most likely due to the fundamental difference between in situ revegetation in
moderately disturbed natural sites and the extensive disturbance treatments involved in road
construction. Road construction brings about a change of the environment from a habitat more
or less sheltered by trees which moderates temperatures and reduces incoming radiation and
winds, to an open habitat.
For the first three years of revegetation, the indigenous species increased in abundance
while most agricultural weeds decreased in abundance (paper I, II, III). Large changes in
species composition from the first to the second year is demonstrated in paper I: fourteen
species were found only the first year and 27 species appeared (for the first time) the second
year. Also, 19 of the common species (occurring in more than five meso plots) had their
abundances significantly changed from the first to the second year (paper I). Five of the nine
species that increased (Agrostis capillaris, Deschampsia cespitosa, Carex pallescens, Luzula
pilosa and Pinus sylvestris) are known to inhabit forests or forest edges (Lid & Lid 1994;
Fremstad 1997), three are often found in moist habitats (Glyceria fluitans, Juncus effusus and
Tussilago farfara) and one is an agricultural weed growing in moist, open soil (Cirsium
17
arvense) (Lid & Lid 1994; Fremstad 1997). Among the 10 species with decreasing
abundance, all species except Picea abies and Poa nemoralis, which inhabit forests and forest
edges (Lid & Lid 1994; Fremstad 1997), were agricultural weeds growing in moist open soils
(Chenopodium polyspermum, Matricaria perforata, Persicaria maculosa, Rorippa palustris,
Stellaria media, Alopecurus geniculatus, Poa annua and Juncus bufonius) (Lid & Lid 1994;
Fremstad 1997). This demonstrates a strong tendency for the species composition to become
more similar to the indigenous vegetation of the area during the first two years of
revegetation. In paper III, none of the four common species that were restricted to subsoil
(Ranunculus repens, Rorippa palustris, Sagina subulata, Carex echinata) were forest species
(Lid & Lid 1994; Fremstad 1997), while the 11 common species restricted to topsoil, with one
exception (Chenopodium album), are known to occur in forests and forest edges (Geranium
sylvaticum, Potentilla erecta, Senecio sylvaticus, Agrostis canina, Anthoxanthum odoratum,
Carex canescens, Carex flava, Juncus filiformis, Luzula multiflora and Luzula pilosa; (Lid &
Lid 1994, Fremstad 1997). Furthermore, several common forest-floor species only appeared
in a few plots on topsoil (Calluna vulgaris, Vaccinium myrtillus, Melampyrum pratense,
Pteridium aquilinum, Trientalis europaea and Calamagrostis purpurea) (Paper III).
The influence of environmental factors on natural revegetation
Vegetation cover on each of the 10 different topsoil types (papers I and II) did not
correlate strongly with soil nutrient contents, although the strongest increase in cover was
observed on soils relatively low in organic matter but with relatively high content of mineral
nutrients (Paper I). A hypothesis adopted by several restoration ecologists is that the deeper
the organic layer (up to the natural depth), the more productive a plant community will
develop (Power et al. 1976; McGinnies & Nicholas 1980; Redente & Hargis 1985). This
contradicts our results as soil types with rather low organic compound did have high plant
cover, instead we suggest that the quality of the organic layer is of crucial importance, as
illustrated by a soil type (macro plot 4) with high content of moderately decomposed
Sphagnum sp. and slow nitrogen mineralisation on which vegetation cover was low while soil
types with high content of clay or decomposed organic matter rapidly got high vegetation
cover (Paper I).
The vegetation composition was related to soil chemical variables and type of organic
matter. The most important compositional gradient (coenocline; DCA 1), both on the between
and the within macro-plot scales, reported in paper II, correlated with the concentrations of
18
readily available Ca and Mg. Together with the concentrations of other nutrients in soil (the
availability of N in particular) and acid-base status (exemplified by pH) these factors often
contribute to a main complex gradient also in intact boreal forests (R. Økland & Eilertsen
1993; T. Økland 1996; R. Økland et al. 2001).The second most important coenocline (DCA 2
in paper II) separate vegetation on dry coniferous forest soil with weakly decomposed litter
from vegetation on moist, mixed forest soil with better decomposed litter.
The variation in vegetation among soil types is also influenced by other factors than
soil nutrients. Interpretation of ordinations and variation partitioning results unequivocally
point to large differences between the different soil types (macro plots), indicating that factors
(both soil chemical and others) operating on scales broader than the macro plots are the most
important for the variation in vegetation composition of the emerging roadside vegetation
(Paper II). The strong difference between species compositions of revegetated plots inside the
forest and close to the road, and between road verge blocks (Paper III), point in the same
direction. Because soils within each block in paper III are similar due to species composition
while there are large differences between the blocks, the explanatory factors related to the
location of the revegetation site seem to be more important than soil nutrients alone.
Our results (paper II) identify several site-scale explanatory factors of importance for
the species composition. The major coenocline (DCA 1) identified in paper II was negatively
correlated with aspect unfavourability and slope, representing a gradient in species
composition from steep sites on unfavourable aspects to vice versa. The clear distinction
between the vegetation compositions of roadside and forest in paper III is another example of
how microclimate influences the vegetation composition. Several processes may contribute to
this: (1) variation in natural growth conditions (local microclimate, aspect, packing of the
subsoil below the topsoil layer and, hence, water retention capacity of the soil column, etc.
along the road; (2) variation in distance to adjacent forest (and, hence, to the major source of
propagules); and (3) variation along the road with respect to adjacent ecosystems and the
successional stage they are in.
Variation in, and factors influencing, germination
Trees provide shelter for the forest-floor understorey from exposition to extreme
conditions of radiation, drought, heavy rain and winds. In SE Norwegian lowlands the
presence of a canopy is likely to be important for establishment of the well-known
compositional differences between the shaded forest floor and open meadows or roadsides
19
(e.g. Fremstad 1997). This is demonstrated by the occurrence of typical forest-floor species
only inside the forest and on topsoils (Vaccinium vitis-idaea, Linnaea borealis, Maianthemum
bifolium, Oxalis acetosella and Sorbus aucuparia; Lid & Lid 1994; Fremstad 1997) (paper
III).
The tree canopy filters the incoming radiation. The nature and extent of this filtering is
determined by canopy density and the dominant canopy tree species; all canopies deplete the
light spectrum in the photosynthetically active region (400–700 nm), and give rise to a peak in
throughfall radiation in the far-red region (700–800 nm) (Coombe 1957; Grime & Jarvis
1975; also see Grime et al. 1981). For some species a low red-far red ratio (R:FR) inhibits
germination (e.g. Frankland 1976; Frankland & Taylorson 1983) and may thus contribute to
lower germination inside the forest than on the roadside.
The presence of a canopy reduced germination of Vaccinium myrtillus (paper IV). All
groups of seeds, regardless of boreal or alpine origin or pre-treatment, germinated less well
when incubated in low R:FR (high level of far-red light, simulating the presence of a canopy)
than when incubated in higher levels of red light (especially R:FR = 1.15, simulating open
sites), indicating that the phytochrome activity is essential for germination of V. myrtillus
seeds (cf. also Giba et al. 1995). This reduced germination with high far-red levels is also in
accordance which the results of Eriksson & Fröborg (1996) when V. myrtillus germinated at
the bog end along a gradient from closed forest to open bog.
Different germination requirements between populations have been reported for many
species, but were not found for the two studied V. myrtillus populations from lowland forest
and from an alpine heath with respect to response to light quality (paper IV). Similarly, no
differences with respect to temperature response were observed by Baskin et al. (2000). Seeds
ingested by bears did, however, show reduced germination both in general and in light with
low R:FR-ratio (paper IV) which is contradictory to results of comparably studies of V.
myrtillus seeds ingested by marten (Schaumann & Heinken 2002), but in accordance with
results for other Vaccinium species (Crossland & Vander Kloet 1996).
20
Practical implications
During the first few years of revegetation, the variation in vegetation cover was greater
in sites naturally revegetated from topsoil than areas seeded by grass mixtures. Nevertheless,
the vegetation cover was satisfactory from an aesthetical point of view already after one or
two years on almost all soil types. Sites with low vegetation cover were confined to soil types
with sparse vegetation also in nearby undisturbed areas, thus fitting well in with the
surroundings.
Three years of revegetation has resulted in a species composition that is promising
from the points of view both of planners and ecologists. There are, however, some obvious
limitations to the extent to which the results of papers I, II and III can be generalised. Because
no comparable studies exist, neither the applicability for soil types other than the eleven
different topsoil types included in these studies, nor the applicability to areas with different
environmental conditions and vegetation types, can be assessed. It is also worth noticing that
this study only deals with the first phase of the succession. There is no guarantee that the
vegetation composition will continue to develop along the same lines, thus Rydgren et al.
(2004) demostrated a shift in the revegetation pathway three to four years after fine-scale
disturbance in a boreal forest.
Our results show that the vegetation composition becomes rather stable already after
two years of revegetation. One practical implication of this result is that with natural
regeneration from indigenous topsoil, detailed plans for additional revegetation methods such
as seeding and planting and management plans should be prepared one or two years after the
end of the construction period. Along the study road, the final result both ecologically,
aesthetically and economically would have been better with less seeding and planting several
places (Skrindo & Pedersen 2005 pers. com.) This contrasts the standard procedure for
revegetation of grassland and fields with planted shrub and tree species, in which elaboration
of management plans is a pre-construction activity.
Although most agricultural weeds decreased from the first to the second year of
revegetation (paper I) while the number of indigenous species increased (paper I, II and III),
one weed species needs particular attention: Cirsium arvense has continued to increase over
the next few years (Skrindo, pers. obs.) and in some places it has formed large and dense
stands of monoculture-like appearance. How long this weed will maintain its local dominance
will depend on the management efforts and, if not managed, the amount of seedlings of
21
woody species that may out-compete the weed. Furthermore, one major warning should be
given: natural revegetation from topsoil should not be used with agricultural soils or close to
agricultural areas. Seeds of agricultural weeds, present in the soil or rapidly dispersed into the
revegetation sites, is likely to interfere with the revegetation process to unknown extents and
the result is wanted neither from an aesthetical nor from an ecological point of view (Skrindo
pers. obs.).
Woody species represent a challenge from the perspective of management for traffic
safety (the recommended management of road verges is that a zone of 3-5 m with low
vegetation is maintained adjacent to the road (Anon.1992). Woody species were observed to
increase in some sites along the road (paper I) and the need for management for traffic safety
reasons is expected to vary, locally and over time.
We have identified several factors that influence the vegetation composition along the
road (papers II and III) and we have showed that revegetation from the same soil type on
comparable sites give rise to more similar vegetation compared to locations with different
ecological conditions (paper III). Still the predictability of species composition after natural
revegetation is expected to be overall lower than compared with revegetation by seeding of
grass mixtures and planting of shrubs and trees, although this variation also has aesthetically
benefits as the road seems to fit into the surrounding vegetation.
During construction and before the beginning of this study, the upper 30 cm of the soil
(defined as topsoil) was stockpiled and to cover the subsoil when the road construction was
finished, 10 cm topsoil was redistributed. In practice, this detailed description was difficult to
accomplish due to large variation in soil depth (some places with less than 30 cm of total soil)
and difficult to redistribute exact 10 cm with excavators (Laukli 2000 pers. com.). These
inaccuracies are not considered as a problem as the revegetation turned out to be quite
successful on topsoil with various levels of organic matter (paper I) and along the whole road
in general (Skrindo & Pedersen pers. com.). The importance is to remove the organic layer
and redistribute as much as possible although it is better with a thin layer all places than thick
layer some places and no topsoil other places.
Three years after the end of the construction period most of the naturally revegetated
sites along the studied portion of R23 have a vegetation composition that fits the surroundings
and functions well as roadside vegetation, contributing to heterogeneity along the road in a
way that maybe judged as positive both in time and space (during the season, from year to
year and along the road). I therefore recommend extensive use of natural revegetation from
topsoil in rural areas, but warn against using this method in agricultural landscapes and add
22
the reservation that other revegetation techniques might be more appropriate in areas with
special needs. And recently, in the main guideline for road construction in Norway, natural
revegetation is recommended in rural areas (Anon. 2005b). And in the Report to the Storting
(Norwegian Parliament) No 21 (2004-2005), about the environmental politics (Anon. 2005c),
natural revegetation from indigenous soil and surrounding is considered a major contribution
to conservation of biological diversity.
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stability. J. Veg. Sci. 4: 733-736.
Warr, S.J., Thompson, K. & Kent, M. 1993. Seed banks as a neglected area of biogeographic
research - A review of literature and sampling techniques. Progress in Physical
Geography 17: 329-347.
Zhang, Z.Q., Shu, W.S., Lan, C.Y. & Wong, M.H. 2001. Soil seed bank as an input of seed
source in revegetation of lead/zinc mine tailings. Restor. Ecol. 9: 378-385.
Personal communication
Laukli, K. 2000. Landscape architect at The Public Roads Administration in Norway. Current
E-mail: [email protected]
Skrindo, A.B. & Pedersen, P.A. 2005. Skrindo; the author. Pedersen; assistent professor at the
Norwegian University of Life Sciences. E-mail: [email protected]
29
Acknowledgements
This thesis is submitted in partial fulfilment of the requirements for the degree of Doctoral
Scientiarum at the Norwegian University of Life Sciences (UMB). The present study was
carried out at the Department of Plant and Environmental Sciences. UBM and The Public
Roads Administration in Norway provided financial support.
I am grateful to many people who have contributed to this thesis. First, I would like to thank
Ole Billing Hansen for giving me this opportunity and to get me started. Then, I will express
my sincere appreciations to my supervisors, Per Anker Pedersen (UMB) and Rune Halvorsen
Økland (University of Oslo, UiO). Rune, for introducing me enthusiastically to ecological
research during my Cand. Scient. degree at UiO, leading me through this doctoral project
with great knowledge, interest and the optimistic attitude I often needed. Per Anker, for
introducing me to applied research with focus on the relevance of my research, for supporting
me in my everyday ups and downs, for interesting discussions and good teamwork. To both of
you: I could never have done this without you.
I am grateful to the technical staff at the nursery at UMB who has contributed in different
ways: Dag Olav Hovet who made parts of the experimental equipment, John Anderson, Knut
Johan Vik, Jeanette Brun, Ann Helen Kalfjøs in taking care of my experiments and helping
with fieldwork, and especially, Ellen Zakariassen who has been a close companion
throughout the whole project including fieldwork, experimental- and statistical work.
The study presented in this thesis is a part of a larger project managed by The Public Roads
Administration of Norway. Several people have been involved in this project and contributed
to this thesis in various ways, especially Kirstine Laukli, the architect for the
Oslofjordforbindelsen and Sunniva Schjetne, at the Directory of Roads, both with enthusiasm
and great knowledge about roads and roadsides. Tanaquil Enzensberger worked together
with Kirstine in the early phase of the road construction (before I started). -Thank you for the
interesting discussions and the work you accomplished.
Three master students did their research at the Oslofjordforbindelsen, whom I partly
supervised: Hanne Gjesteland, Norunn Elise Fossum and Ragnhild Nessa. Thank you for your
contribution and for every fun moment in the field.
Thanks are due to Sam P. Vander Kloet (Acadia University, Canada) who met with me in
London and introduced to me the diversity of the genus Vaccinium, and to Martin Jensen for
germination expertise and my visit to the Development Centre Årslev, Denmark.
I further whish to thank colleagues at the Department of Plant and Environmental science,
Eva, Johannes, Grete and Tina for good working environment, and especially, Ingjerd for
your friendship and support in all our simultaneous ups and downs through out the years.
Finally, I will thank my family and close friends who have supported me and had faith in me
when I never thought I would get this far. My parents in particular, who both have
contributed to this thesis by helping out with fieldwork and proof-reading in addition to being
the sours of my interest out for biology and attitude to life. Audun, my husband, who has
carried me and our little family through the whole process and in addition been my main
computer-hero, field assistant, inspiration and friend. And at last, the sunshine of my life, our
2- year old Ingrid and another one kicking inside, reminding me that there are more
important things to life than restoration ecology.
30
P
A
P
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R
I
ARTICLE IN PRESS
Urban Forestry & Urban Greening 3 (2004) 29–37
www.elsevier.de/ufug
Natural revegetation of indigenous roadside vegetation by propagules from
topsoil
Astrid Brekke Skrindo*, Per Anker Pedersen
( Norway
Department of Plant and Environmental Sciences, Agricultural University of Norway, Box 5003, 1432 As,
Received 16 June 2003; accepted 2 December 2003
Abstract
Road construction degrades large areas of indigenous vegetation. Better understanding of ecosystem restoration
after degradation will require development and assessment of improved restoration techniques. The potential of
natural revegetation based on propagules from topsoil as a restoration technique, to achieve succession towards
indigenous vegetation, is not fully understood and accepted as an alternative method for vegetation establishment. The
aim of this study was to evaluate this restoration technique by comparing different topsoils with respect to their
potentials for revegetation and to describe the early succession on these topsoils by recording change in vegetation
cover and the number of species.
The study road RV23 is situated in south-east Norway and runs mainly through mixed, mostly coniferous forest.
The topsoil (the upper 30 cm) was removed before road construction started, stockpiled during the construction period
and then redistributed on the road verge afterwards. In 1999, 10 macroplots of 25 m2 were placed randomly on selected
topsoils of different qualities, to represent the soil variation in the study area. The soil quality varied from organic-rich
to organic-poor soils. Each macro plot contained four 1-m2 mesoplots in which the species composition was recorded
in 2000 and 2001.Univariate statistical tests were applied to reveal change in vegetation cover between macroplots
within 1 year and between years 2000 and 2001. Furthermore, statistical tests were used to reveal the change in singlespecies frequencies between the study years.
Two years after deposition of topsoils, the vegetation cover was generally satisfactory from an aesthetical point of
view. However, the variation in vegetation cover and species composition was considerable on different topsoils,
reflecting both the local variation of the indigenous vegetation and the soil quality. A total of 121 species of vascular
plants were recorded in all 10 macroplots, although not more than 59 species were found in one macroplot. Species
composition and single-species frequencies changed considerably from the first year to the second. Among the 61
species that were recorded in more than five mesoplots, the frequency of 16 species increased and the frequency of 10
species decreased significantly (Po0:05). Most of the decreasing species can be considered as weed species and are not
represented in the present indigenous vegetation, while most of the increasing species are. The vegetation change from
2000 to 2001 apparently represents the first steps in a succession towards an ecosystem dominated by species of the
indigenous vegetation.
r 2004 Elsevier GmbH. All rights reserved.
Keywords: Revegetation; Indigenous vegetation; Roadside; Topsoil; Propagule bank
*Corresponding author.
E-mail address: [email protected] (A. Brekke Skrindo).
1618-8667/$ - see front matter r 2004 Elsevier GmbH. All rights reserved.
doi:10.1016/j.ufug.2004.04.002
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A. Brekke Skrindo, P. Anker Pedersen / Urban Forestry & Urban Greening 3 (2004) 29–37
Introduction
Road construction degrades large areas of indigenous
vegetation. When building new roads, the added verges
make up a significant area to be revegetated for
environmental and aesthetical reasons and to prevent
erosion. Preservation and re-establishing indigenous
vegetation helps to reach the official goal: to restore
degraded areas and to improve road aesthetics within
the natural landscape (Statens, 1992). There are four
ways to re-establish indigenous vegetation: (1) Transplant larger patches of vegetation, (2) cultivate indigenous plants, (3) in situ germination of seeds collected
from the surrounding areas and (4) germination from
the topsoil propagule bank and the areas adjacent to the
road. In Norway, seeding of non-indigenous grasses is
one of the most used methods along roads resulting in a
somewhat monotonous green lawn. Since the three first
methods are expensive and time-consuming, natural
revegetation from topsoil is an appealing alternative and
the topic of this study.
Topsoil is defined differently throughout literature.
Hargis and Redente (1984) present three possible
definitions for topsoil: soil from the A-horizon; soils
from the A and E-horizon; or a specific soil depth
regardless of soil layer. In this study, the latter definition
is used for practical reasons. Revegetation from topsoil is
based on germination from the propagule bank followed
by the process of natural succession, defined as the nonseasonal, directional and continuous pattern of colonisation and extinction on a site by species populations
(Begon et al., 1990). The procedure is straightforward:
topsoil is removed before construction, stockpiled and
then replaced. The advantages are that plant nutrients,
viable propagules, mychorriza and microfauna remain in
the upper soil (cf. Hargis and Redente, 1984).
Restoration of indigenous vegetation from the topsoil
propagule seed bank shows contradictory results. It has
failed in several grasslands (Thompson and Grime,
1979), but succeeded in South African shrubland
(Holmes, 2001), in a Californian (USA) meadow
(Kotanen, 1996) and in woodland restoration in
Western Australia (Rokich et al., 2000) and in England
(cf. Warr et al., 1993). Furthermore, it has proved to be
successful for revegetation of contaminated soils, such
as lead/zinc mine tailings in China (Zhang et al., 2001)
and fly ash and gypsum in the United Kingdom (Shaw,
1996). To our knowledge, restoration of indigenous
roadside vegetation from the propagule bank in the
topsoil has not been assessed before in Scandinavia.
The study sites were integrated in the construction of
a new road (‘‘Oslofjordforbindelsen’’), which passes
through various vegetation types. The revegetation
methods along the study road are a mosaic of
revegetation from topsoil and seeded and planted areas,
but this investigation deals only with revegetation from
redistributed topsoil. Since this study consists of data
from only 2 years, we focus on the first phase of a
secondary autogenic succession.
The aim of the study was to evaluate the redistribution of topsoil as a restoration technique and to
compare revegetation success from different topsoils.
Particular attention was given to change in vegetation
cover, the number of species, relationship between soil
and vegetation and the frequency of species divided into
four functional groups: woody plants, flowering forbs,
agricultural weeds and graminoids.
Materials and methods
Study area and restoration technique
The study road, RV23 (Oslofjordforbindelsen), passes
through 13 km of mixed forest, coniferous forest
dominated by Scots pine (Pinus sylvestris) and Norway
spruce (Picea abies) and bogs. The road is situated in
south-east Norway in the municipalities of Frogn,
Hurum and Røyken in Akershus and Buskerud counties
respectively (10 440 E, 59 420 N to 10 250 E, 59 440 N).
The climate is sub-oceanic. Annual mean precipitation in the years 1961–1990 (normal) was 920 mm at the
Drøbak meteorological station (Førland, 1993). The
annual precipitation in the study period was 1191.7 mm
(1999), 1360.8 mm (2000) and 991.7 mm (2001). The
precipitation during the growing season was higher or
about the same as the normal with no continuous
drought periods.
The topsoil, defined by the Public Roads Administration as the upper 30 cm of the soil profile due to
practical reasons, was excavated before road construction and stockpiled separately during the construction
period (in 1998). The topsoil volume decreased during
stockpiling, consequently a layer of 10 cm was redistributed on top of the subsoil on the road verge (in May
and August 1999). The exact origin of the soil replaced
on plots is not known due to some degree of mixing of
soil during stockpiling. The vegetation composition in
the original site is therefore unknown. The thickness of
the humus layer in the original soil profile varied
between 5 and 20 cm except in bogs.
Sampling
Recording of vegetation data
In 1999, 10 macroplots of 25 m2 were placed
randomly on selected topsoils of different qualities
representing the topsoil-variation in the study area.
Each macroplot contained four 1 m2 mesoplots systematically placed in the corners by grid sampling (Økland,
1990). Each mesoplot was divided into 16 (25 25 cm2)
subplots.
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In July 2000 and 2001, the frequency of all vascular
plant species in the 40 mesoplots was recorded by (1)
estimating percentage cover on a 0100 scale, and (2) by
recording the presence/absence of all species in each
subplot to calculate subplot frequency on a 016 scale
(Økland, 1988). The vascular plants nomenclature
followed Lid and Lid (1994).
31
weight (unit: mg/100 ml). For soil variables, skewness
and kurtosis were calculated using Statgraphics, Version
5.0 (Table 1). Homogeneity of variances (Table 1) was
achieved by transforming variables to zero skewness by
ln (c þ x) according to Økland et al. (2001). Statistical
significance of differences in total vegetation cover (%)
between the macroplots in each year 2000 and 2001 and
the change between the years 2000 and 2001, were tested
using an analysis of variance including a multiple range
test, Ryan–Einot–Gabriel–Welsh (REGWQ), Po0:05
(SAS Institute, 1987) according to the model
Recording of soil data
Soil samples were collected from the upper 10 cm
layer on the boundaries of each mesoplot and analysed
to provide soil variables (Table 1): Readily available
plant nutrients, P, K, Mg, Ca, were extracted by 0.1 M
ammonium lactate and 0.4 M acetic acid according to
the AL-method (Egne! r et al., 1960) and determined by
inductively coupled spectroscopy (ICP). The content of
organic matter was assessed by determining the loss on
ignition and soil pH was measured in water suspension.
The soil texture was classified (Table 2) according to
Sveistrup and Njøs (1984).
Xij ¼ mi þ ai þ eij ;
where Xij is the performance of the macroplot, i the
ði ¼ 1; 2; :::10Þ; and due to the mesoplot, j the ðj ¼
1; 2; :::4Þ; m the expected mean, a the expected effect of
the macroplot, e the residual (variation between the
mesoplots).
The hypothesis tested was a ¼ 0 (no effect of the
macroplot) against aa0:
Relationships between the number of species and the
vegetation cover in the macroplots were addressed using
Kendall’s rank correlation method (Kendall, 1938). To
address the relationships between the soil variables and
the relationship between the soil and vegetation cover
Kendall’s rank correlation method (Kendall, 1938) was
Statistical analyses
All soil variables except pH were adjusted to the soil
density by multiplying the variable to the soil volume
Table 1. Soil variables measured in all 1 m2 plots
Variable
Loss on ignition
pH
P
K
Mg
Ca
Unit
Summary statistics of
untransformed variable
mg/100 ml
—
mg/100 ml
mg/100 ml
mg/100 ml
mg/100 ml
Transf. ln (c þ x)
Summary statistics of
transformed variable
Range
S.S.
S.K.
c-value
Mean
S.D
S.K
1–400
4.2–8.6
5.7–383
5.2–65.7
2.68–45
9.93–496
1.58
0.68
2.78
0.04
2.13
4.60
1.16
1.25
0.22
1.85
0.16
3.80
0.65
1.00
1.00
0.1
—
4.23
2.25
1.95
1.95
0.99
—
2.09
1.10
0.16
0.16
0.34
—
1.00
1.51
1.17
1.17
0.53
—
0.38
Abbreviations: S.S.=standardised skewness; S.K.=standardised kurtosis, c-value=index used in transformation formula; S.D.=standard deviation,
=analysed by the AL-method.
Table 2. Soil classification of the macroplots
Macro plot
Soil classification
Organic components
1
2
3
4
5
6
7
8
9
10
Silt loam
Silt loam
Medium loamy sand
Organic soil
Mold rich loam
Clay loam+silt loam
Silt loam+loam+medium loamy sand
Mold rich loam
Clay loam+silt loam
Mold rich loam
Litter—weakly decomposed
Litter—variable degree of decomposition
Litter—weakly decomposed
Sphagnum—weakly decomposed
Litter—weakly decomposed
Sphagnum—weakly decomposed
Sphagnum and litter—weakly decomposed
Litter—weakly decomposed
Litter—well decomposed
Litter—weakly decomposed
Description of the organic components; litter originating from dry coniferous woodland, litter originating from swamp woodland.
ARTICLE IN PRESS
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A. Brekke Skrindo, P. Anker Pedersen / Urban Forestry & Urban Greening 3 (2004) 29–37
used. The statistical difference of single species frequencies between years 2000 and 2001 was tested using
Wilcoxon’s signed-rank test for two paired samples (cf.
Sokal and Rohlf, 1995). The tests were against the twotailed alternatives. Testing was restricted to species
recorded in 5 or more mesoplots either year.
Results
Vegetation cover and the number of species
Two years after the redistribution of the topsoil, six
macroplots had at least 50% vegetation cover. The
mean vegetation cover ranged from 1% to 95% in 2000
and from 5% to 100% in 2001. The macroplots differed
statistically (Po0:001) both years, and there was no
significant difference within each macroplot. In year
2000, no distinct groups of macroplots could be
statistically defined (Table 3). In 2001, the macroplots
could be divided into four groups: macroplots 1, 5, 8, 9,
10 had the highest vegetation cover followed by plot 6
then plots 2 and 7, and finally plots 3 and 4 (Table 3).
The vegetation cover increased significantly in all the
macroplots from year 2000 to 2001 (Table 3). In general,
plots with high cover vegetation cover in 2001 had high
cover in 2000 as well. On the other hand, in plots with
initially low vegetation cover (1%) the differences
between year 2000 and 2001 varied substantially.
There were 121 recorded species in total and the
number of species per macroplot ranged from 8 to 51 in
year 2000 and from 10 to 59 in year 2001 (Table 3).
Fourteen species were found only in the year 2000 and
27 species appeared for the first time in year 2001. There
were strong correlations between the vegetation cover
and the number of species both years (year 2000; t ¼
0:5004; P ¼ 0:0001; year 2001; t ¼ 0:442; P ¼ 0:0002).
Relationships between vegetation cover and soil
variables
The content of plant nutrients in the soil varied
between plots (Table 4). In most samples the content
was medium high. The organic soil in macroplot 4 was
low in all elements. On the contrary, the macroplots
with clay loam (6 and 9) had the highest content of all
nutrients except for Ca, which was highest in the
medium loamy sand of macroplot 3.
Vegetation cover did not correlate strongly with most
soil variables (Table 5). The only significant relationship
in both years at level Po0:01 was with K, and organic
matter (Loss on ignition) in year 2000.
There were rather strong correlations between some
of the soil variables (Table 6) indicating a more complex
relationship between the soil variables and the vegetation cover than the direct correlation explained. The loss
on ignition had statistically significant negative correlaTable 4. Mean values of the soil variables
Macro Loss on pH P-AL K-AL Mg-AL Ca-AL Density
plot
ignition
1
2
3
4
5
6
7
8
9
10
6.4
7.9
2.8
14.1
15.4
7.5
4.6
11.8
6.4
23.7
5.4
5.2
8.0
4.3
5.5
7.0
7.4
6.2
7.2
5.8
2.8
2.3
2.2
1.6
0.8
3.4
4.7
1.0
5.1
1.4
9.8
7.2
11.0
3.0
9.5
15.2
11.7
26.8
29.0
9.5
15.0
3.6
21.4
8.1
12.8
31.2
29.6
13.9
28.6
23.1
63.0
30.8
1000.4
34.9
117.6
442.3
390.4
267.9
296.8
484.0
0.95
1.12
1.16
0.43
0.42
0.98
1.24
0.51
1.20
0.70
The unit for all variables (except pH) is mg/100 ml.
Table 3. The number of species and mean vegetation cover in
each macro plot in years 2000 and 2001
Macroplot Number of species
1
2
3
4
5
6
7
8
9
10
Mean vegetation cover (%)
2000
2001
2000
2001
51
17
8
9
40
42
24
48
47
34
59
29
13
10
42
42
27
43
40
39
45C,D
1F
1F
1F
68B,C
34D,E
19E,F
95A
50C,D
82A,B
99A
26C
10D
5D
84A
53B
32C
100A
98A
95
The letters (A–F) indicate groups with statistically significant
difference in cover (Po0:05). Mean vegetation covers indicated with
the same letter within a column are not significantly different.
Table 5. Kendall’s non-parametric correlation coefficients (t)
between the soil variables and vegetation cover in year 2000
and 2001
Vegetation
cover (2000)
Loss on ignition
pH
P
K
Mg
Ca
Vegetation
cover (2001)
t
P
t
P
0.3335
0.0415
0.1722
0.3210
0.1080
0.1571
0.0037
ns
ns
0.0052
ns
ns
0.1842
0.0320
0.0151
0.3916
0.1554
0.0618
ns
ns
ns
0.0007
ns
ns
Correlations significant at the level of Po0:05 in bold, ns (nonsignificant)=P>0.1.
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33
Table 6. Kendall’s non-parametric correlation coefficients (t) between the soil variables (lower triangle), with significance
probabilities (upper triangle)
Loss on ign.
Loss on ignition
pH
P
K
Mg
Ca
0.4162
0.5083
0.1578
0.1643
0.1809
pH
P-AL
K-AL
Mg-AL
Ca-AL
0.0002
0.0000
0.0208
ns
0.0001
ns
ns
0.0000
0.0024
0.0000
ns
0.0000
ns
0.0009
0.0000
0.2575
0.4484
0.5722
0.7369
0.2142
0.3338
0.1142
0.4657
0.3667
0.5555
Correlations significant at the level of Po0:05 are in bold, ns (non-significant)=P>0.1.
tion with pH and P and showed a tendency (Po0:1) of
negative correlation with the other inorganic soil
variables (Table 6), illustrating that the organic-rich
soil had a relatively low nutrient-level and low pH.
Macroplot 3 had the lowest content of organic matter
(Table 4) and among the lowest vegetation cover in year
2000 and 2001 (Table 3). Macro plot 8 had one of the
highest organic matter content (Table 4) and also the
highest vegetation cover both years. The inorganic
variables made up a group of more or less significantly
positively correlating variables (Table 6). The highest
increase in vegetation cover took place in the macroplots
(1 and 9) with intermediate vegetation cover in year
2000, on soils relatively low in organic matter but with
relatively high content of mineral nutrients (Table 4).
Species frequency
Since the vegetation on the site of origin is not
recorded, revegetation from topsoil might not only
include indigenous species but all species in the
propagule bank. This is the case in most construction
areas and due to practical maintenance and aesthetical
aspects, the change in frequency of species is discussed in
relation to the following functional groups: woody
plants, flowering forbs, agricultural weeds and graminoids.
The different species showed a highly variable
frequency pattern: among the 121 species, 58 were
recorded in more than 5 mesoplots (Table 7) and 30
occurred in five or more of the macroplots (the bold
names in Table 7): five were woody plants, four were
considered to be typical agricultural weeds, 11 were
flowering forbs (forbs are not considered to be weeds in
this context) and 10 were graminoids (including the
families: Poaceae, Juncaceae and Cyperaceae). Nine of
the 30 species found in five or more macroplots,
occurred in 20 or more mesoplots: four woody plants
(Rubus idaeus, Picea abies, Salix caprea and Pinus
sylvestris), two agricultural weeds (Persicaria maculosa
and Tussilago farfara), two flowering forbs (Ranunculus
repens and Galeopsis tetrahit) and one grass species
(Agrostis capillaris).
Some of the most frequent species accounted for the
largest vegetation cover: Ranunculus repens and Tussilago farfara had greater cover percentage than the rest
of the species, and both increased in cover from 2000 to
2001, T. farfara more than R. repens. Other dominant
species, Picea abies, Pinus sylvestris and Galeopsis
tetrahit, were low in cover.
Among the 14 species recorded only in year 2000,
three species were considered to be agricultural weeds,
five flowering forbs and five graminoids. Among the
species appearing in year 2001, all functional groups
were represented although the number of flowering
forbs and graminoids increased notably (only one
woody species, but five agricultural weeds, nine flowering forbs and 11 graminoids). Thirteen species showed
statistically significant increase (Po0:05) of frequency
from 2000 to 2001 while 10 species showed significant
decline (Table 7). Pinus sylvestris was the only woody
plant that increased and Picea abies was the only woody
species that decreased. Other species did not change
statistically significantly in frequency. Four species of
flowering forbs (Cerastium fontanum, Ranunculus repens,
Veronica officinalis and Veronica scutellata) increased
significantly (Po0:05) and Stellaria nemorum showed a
tendency of increasing (Po0:1). Only Omalotheca
sylvatica declined significantly. Thirteen other species
of flowering forbs did not change significantly in
frequency during the 2 years. The graminoids Agrostis
capillaris, Carex pallescens, Deschampsia caespitosa,
Glyceria fluitans, Luzula pilosa and Juncus effusus
increased significantly while Alopecurus geniculatus,
Poa annua and Poa nemoralis decreased significantly.
Juncus articulatus and J. bufonius showed a tendency of
declining (Po0:1). Ten other graminoids did not change
significantly. Among the agricultural weeds Cirsium
arvense and Tussilago farfara were the only ones, which
increased significantly (Po0:05) and Senecio sylvaticus
showed a tendency of increasing (Po0:1). Chenopodium
polyspermum, Matricaria perforata, Persicaria maculosa,
Rorippa palustris and Stellaria media which are wellknown agricultural weeds, declined significantly from
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A. Brekke Skrindo, P. Anker Pedersen / Urban Forestry & Urban Greening 3 (2004) 29–37
Table 7. Change in frequency of the vascular species occurring in more than 5 meso plots from year 2000 to 2001
Code and species
Occur.
Change
Ma
Me
n+
n
(w)Pinus sylvestris
(g)Luzula pilosa
(g)Juncus effusus
(g)Glyceria fluitans
(g)Deschampsia cespitosa
(g)Carex pallescens
(g)Agrostis capillaris
(f)Veronica scutellata
(f)Veronica officinalis
(f)Stellaria nemorum
(f)Ranunculus repens
(f)Cerastium fontanum
(a)Tussilago farfara
(a)Senecio sylvaticus
(a)Cirsium arvense
7
5
4
6
7
6
8
4
6
5
7
6
9
4
4
24
8
10
17
18
11
22
8
17
19
26
11
29
15
10
13
8
10
12
11
8
16
7
11
13
14
11
24
8
9
(w)Picea abies
(g)Poa nemoralis
(g)Poa annua
(g)Juncus bufonius
(g)Juncus articulatus
(g)Alopecurus geniculatus
(f)Omalotheca sylvatica
(f)Galeopsis tetrahit
(a)Stellaria media
(a)Rorippa palustris
(a)Persicaria maculosa
(a)Matricaria perforata
(a)Chenop. polyspermum
9
3
4
8
5
7
4
8
8
4
9
6
3
32
9
11
18
12
17
13
20
15
7
22
10
6
4
0
2
6
3
6
1
5
3
0
4
0
0
Species
P
I
7
0
0
4
4
1
3
1
3
4
2
0
2
7
1
0.0418
0.0095
0.0064
0.0161
0.0157
0.0208
0.0027
0.0280
0.0185
0.0886
0.0318
0.0028
0.0001
0.0832
0.0080
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
26
8
8
12
8
11
12
13
12
6
18
7
6
0.0000
0.0095
0.0249
0.0641
0.0559
0.0092
0.0016
0.0611
0.0381
0.0210
0.0029
0.0142
0.0210
(w)Salix caprea
(w)Rubus idaeus
(w)Betula pubescens
(g)Poa pratensis
(g)Luzula multiflora
(g)Juncus filiformis
(g)Juncus conglomeratus
(g)Festuca rubra
(g)Descha. flexuosa
(g)Carex flava
(g)Carex echinata
(g)Carex canescens
(g)Agrostis stolonifera
(f)Viola riviniana
(f)Trifolium repens
(f)Stellaria graminea
(f)Solanum dulcamara
(f)Silene dioica
(f)Oxalis acetosella
(f)Lythrum salicaria
(f)Impatiens noli-tangere
(f)Galium palustre
(f)Epilobium sp.
(f)Epilo. angustifolium
(f)Anemone nemorosa
(a)Polygonum aviculare
(a)Plantago major
(a)Filipendula ulmaria
(a)Chenopodium album
(a)Urtica dioica
Occur.
Change
Ma
Me
n+
n
P
I
8
9
5
5
3
2
4
4
4
3
3
5
2
8
4
3
3
5
3
3
4
5
5
2
5
3
2
2
5
4
25
33
12
15
10
6
7
11
11
6
6
10
7
16
5
5
5
11
6
7
13
11
14
5
13
5
5
5
11
11
12
15
7
8
3
2
5
5
7
4
4
7
4
7
4
4
1
4
1
4
4
8
7
3
8
2
3
3
5
5
9
14
2
7
6
4
1
6
3
2
2
2
3
7
1
1
2
5
3
2
9
3
5
2
5
3
2
1
6
5
ns
ns
ns
ns
ns
ns
ns
ns
ns
ns
ns
ns
ns
ns
ns
ns
ns
ns
ns
ns
ns
ns
ns
ns
ns
ns
ns
ns
ns
ns
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
The codes: (w)=woody plant, (f)=flowering forbs except (a)=agricultural weeds, (g)=graminoids, total number of occurrences in 10 macroplots
(Ma) and 40 mesoplots (Me) in either 2000 or 2001; n+, n=number of mesoplots with decreasing and increasing subplot frequencies, respectively;
P=statistical significance (Po0:05 in bold), Wilcoxon one-sample test, (ns=non-significant); I=indication of decreasing () or increasing (+)
frequency. Species in bold were recorded in more than 50% of the mesoplots.
year 2000 to 2001. Five other weeds showed no
significant change.
There was no clear frequency pattern for the different
functional groups related to the soil. Woody species
occurred in all plots, but more species were recorded in
macro plots 5–10 than in the rest. The agricultural weeds
occurred in all macro plots except macroplot 3 but only
a few were present in plots 2, 4 and 7. The flowering
forbs and the graminoids occurred in all macroplots, but
the highest number of species was recorded in macroplots 1, 8, 9 and 10 for the forbs and 1, 2, 5 and 6 for the
graminoids.
Discussion
When driving on the study road 2 years after the
topsoil was redistributed, the vegetation appears to fit
well into the surrounding indigenous vegetation even
though the species composition is far from identical to
the surrounding and the vegetation cover varies from
less than 10% to more than 90%.
The variation between the macro plots from year 2000
to 2001 could not be explained by the soil variables only.
The significant relationship between the vegetation
cover and organic matter (loss on ignition) in year
2000 is well documented from other studies. Bradshaw
(1989) found increased growth yield in topsoils with
high content of organic matter. Soils with a high content
of organic matter are likely to have a larger seed bank
than soils with lower organic matter content (cf.
.
Granstrom,
1982). Somewhat surprisingly there was no
significant relation between the vegetation cover and the
content of organic matter in year 2001. However, the
subsoil with high clay content may have provided more
essential nutrients than the organic soil and thus support
good growth. This is a possible explanation why some
ARTICLE IN PRESS
A. Brekke Skrindo, P. Anker Pedersen / Urban Forestry & Urban Greening 3 (2004) 29–37
macro plots with low content of organic matter, but
high clay content have rather high vegetation cover (e.g.
macroplots 6 and 9). Other possible explanations could
lie in processes during stockpiling, uneven distribution
of organic soil on the sites, the shorter growth period at
macro plots 1–4 and other ecological factors not
recorded in this study . The quality of the organic soil
is probably of major importance as illustrated in
macroplot 4 with high content of moderately decomposed Sphagnum sp. Slow mineralisation leads to limited
amount of available nitrogen, resulting in low vegetation
cover. Nitrogen is usually considered to be the most
important limiting resource in boreal forests (cf.
Hesselmann, 1937; Tamm, 1991).
The thickness of the excavated topsoil influences the
availability of propagules. The number of viable seeds
from different depths has been studied in different
. (1982) found most
ecosystems. For instance, Granstrom
viable seeds in the thin humus layer in five different
boreal forest stands. The humus—mineral soil ratio
varies with the thickness of the humus layer. Consequently, number of seeds is likely to be higher in
macroplots with topsoil rich in organic matter.
The quantity of redistributed topsoil also affects the
revegetation. The topsoil layer in this study after
redistribution was supposed to be 10 cm thick, but there
are patches of thinner and thicker topsoil layer due to
the inaccuracy of the distribution method. Several
scientists working in the field of reclamation have
accepted the hypothesis that the deeper the humus layer
(up to the natural depth), the more productive the plant
community (Power et al., 1976; McGinnies and Nicholas, 1980; Redente and Hargis, 1985). However, Redente
et al. (1997) found no difference in vegetation cover after
10 years although the thickness of the humus layer
varied from 15 to 60 cm.
When comparing seed bank studies and revegetation
from stockpiled topsoil (including the propagule
bank, the micro fauna, flora and the nutrition), the
effects of stockpiling on the soil quality have to be
taken into account. Hargis and Redente (1984) found
decreased germination and revegetation success and
Rives et al. (1980) found less mycorrhiza-infected
roots in stockpiled topsoil. The soil used in this
study had been stockpiled for 1–1.5 years but good
revegetation results are obtained from different soiltypes up to 5 years of storage according to Stark and
Redente (1987).
The revegetation process in macroplots 1–4 was 2
months shorter than in the other plots due to the
delayed redistribution of topsoil. The variation between
the macro plots, however, cannot be explained by this
delay alone because the difference between the macroplots with the same growth period was significant as
well. In spite of good climatic conditions for germination and growth throughout the summer some macro
35
plots still had a vegetation cover less than 10% in
year 2001.
The propagule bank size does influence the vegetation
cover demonstrated by the correlation between the
number of species and the vegetation cover. In this
study, some of the most frequent species had the largest
cover percentage (i.e. Ranunculus repens, Tussilago
farfara and Rubus idaeus). However, other frequent
species did not contribute much to the vegetation cover
(Picea abies, P. sylvestris and Galeopsis tetrahit).
The change in species composition over time is
demonstrated by the 14 species recorded only in the
first year and 27 new species appearing the second year.
This considerable alteration is typical in the first phase
of a secondary succession due to variation in the
microclimate, variation in the propagule bank and due
to seed dispersal from the surroundings (Connell and
Slatyer, 1977). The 121 species recorded in this study are
dominated by pioneer species but species expected to
establish throughout the whole succession period
occurred as well. Connell and Slatyer (1977) found that
individuals of any species that happened to fulfil their
germination requirements could establish in this early
stage. Among the species with altered frequency from
2000 to 2001 some grasses (Agrostis capillaris,
Deschampsia caespitosa and Glyceria fluitans) increased
and others (Alopecurus geniculatus, Poa annua and P.
nemoralis) decreased and other graminoids (Carex
pallescens, Luzula pilosa and Juncus effusus) increased.
All of these species are often found in moist places, but
the species that decreased are known to loose in
competition for light (cf. Lid and Lid, 1994).
As woody plants may represent a maintenance
problem and influence traffic safety, their slow invasion
is good news. Only P. sylvestris increased significantly,
whereas Picea abies decreased. Rubus idaeus was among
the most frequent species, which was expected because
of the viability of the seeds in comparable seed banks
.
(cf. Granstrom,
1982). Salix caprea was also among the
most frequent species even without a persistent seed
bank, because it disperses and germinates easily (cf.
Brinkman, 1974).
The weeds are neither an aesthetic nor a management
problem yet. Among the 16 species that increased
significantly in frequency, only two can be considered
as weeds (Cirsium arvense and Tussilago farfara). If they
continue to increase, they might dominate some areas
completely and prevent other indigenous species to
grow. Six of the nine species that decreased were also
typical weeds (Chenopodium polyspermum, Matricaria
perforata, Persicaria maculosa, Rorippa palustris and
Stellaria media). All of these species are annuals or at
least short-lived (Korsmo, 1986; Lid and Lid, 1994) and
might be expected to decrease. There were several weeds
that did not change in frequency, and their future
presence remains unknown.
ARTICLE IN PRESS
36
A. Brekke Skrindo, P. Anker Pedersen / Urban Forestry & Urban Greening 3 (2004) 29–37
The macro plots are situated in a landscape with
different vegetation history and ecology influencing
the propagule bank as argued by Baskin and Baskin
(1998): The size and the content of the propagule bank
varies with plant age, species composition, disturbance
level, predispersal seed predation and plant seed
production. There is no clear relationship between the
soil properties and the species composition except in
macroplot 4 with organic soil that had few weeds,
woody plants and graminoids, and in plots 2, 3 and 7
with loamy soil that host none or only a few weeds.
Several studies show a lack of correspondence between
the species composition of the seed bank and the
associated plant community in surrounding forests
(e.g. Oosting and Humphreys, 1940; Thompson and
.
Grime, 1979; Granstrom,
1982). The species composition in the early phase of succession seems hard to
predict. That the species composition in the early phase
of succession is hard to predict is illustrated by the
variation between the macroplots in this study. In
general, however, both the vegetation cover and species
composition were satisfactory already 2 years after the
soil was redistributed. Natural revegetation from redistributed topsoil is therefore recommended in comparable ecosystems.
Acknowledgements
This project was partly financed by the Public Roads
Administration, Buskerud county and the Directorate of
Public Roads in Norway.
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P
A
P
E
R
II
Early secondary succession after revegetation
by different topsoils on a roadside
Astrid B. Skrindo1, Rune H. Økland2 & Per Anker Pedersen1
1Department
of Plant and Environmental Sciences, Norwegian University of Life Sciences,
P.O.Box 5003, N-1432 Ås, Norway; 2 Department of Botany, Natural History Museum,
University of Oslo, P.O. Box 1172 Blindern, N-0318 Oslo, Norway.
Abstract
Questions: Does the early phase of natural revegetation from indigenous soils follow the
paths of a comparable ecosystem? What is the relative importance of explatory variables such
as topsoil origin, environmental conditions of the site during the early phase of secondary
revegetation succession.
Location: Southeast Norway
Methods: We studied a recently constructed road in SE Norway, running through various
forests types with topsoils of different qualities. For three years (2000-2002) we recorded
plant species composition and 12 explanatory variables in 40 1-m2 meso plots, four within
each of 10 25-m2 macro plots, along the road. Multivariate ordination methods and univariate
tests were used to assess the relative importance of different explanatory variables for the
variation in species composition in the early phase of secondary succession, 1–3 years after
road construction.
Results: The species composition was fairly stable during the study period, although a
significant shift in the species composition took place from the first to the second year
after construction, along the main gradient in species composition (DCA ordination axis
1). This main compositional gradient was related to a complex-gradient from steep sites on
unfavourable aspects with low base cation concentration to vice versa and parallels complex
gradients demonstrated for boreal forests. The second most important compositional gradient
(DCA 2) reflected a gradient of distance to undisturbed forest, in time and space. Most of the
variation in species composition occurred at the between-macro plot scale, indicating that
qualities of the re-redistributed topsoils (origin, organic content, chemical properties) are
important for the outcome of revegetation succession.
Conclusion: We conclude that the species composition during the early phase of roadside
revegetation may be rather stable, and therefore predictable, following the well-known
pathways of secondary succession in boreal forests.
Keywords: Boreal forest; DCA; Indigenous vegetation; Ordination; Propagule bank;
Revegetation; Roadside; Seed bank; Succession; Topsoil.
1
Introduction
Road construction implies degradation of the vegetation over extensive areas. Reestablishment of indigenous vegetation on new roadsides therefore becomes an increasingly
important measure to reach the official goal, to restore degraded areas and improve road
aesthetics within the natural landscape (Anonymous 1992).
Several strategies exist for revegetating roadside areas; by seeding, by planting and
by revegetation on indigenous topsoil, collected at the site before the road was constructed,
stored during the construction period and then re-distributed. Revegetation from indigenous
topsoil is recommended for rural areas in Norway (Anonymous 2004) and is the topic for this
study.
The term topsoil has been defined in several ways, as soils either from the A-horizon,
the A and E-horizons, or from a specific soil depth regardless of soil layer (Hargis & Redente
1984). We will, for practical reasons, use the latter definition and define topsoil as the upper
30 cm of the soil profile. Revegetation after disturbance by use of indigenous topsoil relies
on three sources of plant material: (i) seed dispersed into the revegetated area from intact
neighboring areas or patches; (ii) in situ germination of viable seeds present in the supplied
soil (the seed bank); and (iii) re-sprouting of vegetative plant parts present in the supplied soil
(Moore & Wein 1977). In this study, we do not distinguish between these three sources but
assume that germination from the seed bank and re-sprouting are the most important during
the first phase of revegetation.
Previous attempts to use the seed bank to restore indigenous vegetation have been
successful to variable degrees. Failure has been recorded for several grasslands (Thompson
& Grime 1979) while success has been recorded for South African shrubland (Holmes
2001), Californian meadows (Kotanen 1996) and Western Australian (Rokich et al. 2000)
and English woodlands (Warr et al. 1993). Seed supply in addition to the seed bank has been
shown to be important for successful revegetation of contaminated soils in China (Zhang et
al. 2001) and the United Kingdom (Shaw 1996). To our knowledge, the present road project
provides the first scientific assessment of roadside vegetation restoration from indigenous
topsoil in Scandinavia (Skrindo & Pedersen 2004).
As pointed out by several authors, artificial revegetation of degraded sites benefits
from knowledge of the history of the seed banks and of natural recovery mechanisms
(Bradshaw 1983, McGraw & Vavrek 1989). Knowledge of the fine-scale disturbance regime
of the seed source site is of particular interest in this respect as the size of the seed bank
generally increases with increasing disturbance intensity (Thompson 1978, Ebersole 1989).
Other factors, likely to be important, are the quality and quantity of the seed rain, and the
climatic conditions during the revegetation period. The relative importance of these factors
for the outcome of revegetation experiments have, however, hardly been studied, and it is
therefore not known if the outcome of such experiments is governed by general rules or if it
2
is context-dependent and varies from site to site, like the ‘diversion of reasons for diversity’
paradigm (Tilman 1999). Studies in which roadside revegetation from different topsoils
is followed for several years and related to external factors at the revegetation sites may
therefore provide results with general interest for restoration ecology.
The present study of roadside revegetation from indigenous topsoil was integrated
in the planning process for construction of a new main road in SE Norway (‘Oslofjordforbindelsen’), a road that passes through various forest types from which the topsoil was
removed before construction, stockpiled and then re-distributed on the new roadsides. Some
important topics for landscaping, such as the time of greening and the fate of different species,
including invasive weeds, during the first three years of revegetation, have been treated by
Skrindo & Pedersen (2004). This study aims at assessing the relative importance of different
sets of explanatory variables, such as topsoil origin, environmental conditions of the site,
and weather conditions during revegetation, for the variation in species composition of
revegetated sites during the early phase of secondary revegetation succession.
Material and methods
Investigation area
The study area comprises a 13 km road section, passing through coniferous forest,
mixed forest and bogs with variable soil depth. The area is situated in SE Norway, 30 km
south of Oslo; in Frogn, Hurum and Røyken municipalities in Akershus and Buskerud
counties (10o 44-45’ E, 59o 42-44’N).
The area is situated in the boreo-nemoral vegetation zone, the slightly oceanic (O1)
section (Moen 1998). Annual mean precipitation (1961–90 normal) was 920 mm at the
nearest meteorological station (Drøbak; Førland 1993) and the annual temperature was 5.3 °C
(Aune 1993).
The topsoil (defined as the upper 30 cm of the soil profile) was excavated before
the onset of road construction and stockpiled separately from the subsoil (defined as all soil
but the topsoil) during the construction period (which started in 1998). In 1999, the topsoil
was redistributed on top of the subsoil on the roadside, as a layer of 10 cm vertical extent.
Attempts were made to place re-distributed topsoil in sites comparable (in as many respects
as possible) to those from which the soil originated. However, due to some mixing of soils
during stockpiling, exact links between the geographical origin of the topsoil and the target
sites were lost. Properties of the re-distributed topsoils are given in Table 1.
Field work was carried out during the years 2000–2002, i.e. in years 1–3 after topsoil
redistribution. The precipitation was above, or close to, normal for all three growing seasons
and no extended, continuous, drought period occurred.
3
Table 1. Classification of soils re-distributed on each macro plot. MaP – macro plot.
MaP Soil texture
1
2
3
4
5
6
7
8
9
10
Silt loam
Silt loam
Medium loamy sand
Organic soil
Mold rich loam
Clay loam + silt loam
Silt loam + loam + medium loamy sand
Mold rich loam
Clay loam + silt loam
Mold rich loam
Organic components
Origin of litter
Decomposition
Dry coniferous forest
Dry coniferous forest
Dry coniferous forest
Sphagnum
Moist forest
Sphagnum
Sphagnum and Moist forest
Moist forest
Moist forest
Moist forest
Weakly decomposed
Wariable decomposition
Weakly decomposed
Weakly decomposed
Weakly decomposed
Weakly decomposed
Weakly decomposed
Weakly decomposed
Well decomposed
Weakly decomposed
Sampling design
In 1999, 10 macro plots of 25 m2 were placed randomly on selected, representative
topsoils in the study area, in the range 4–34 m from the road. Four 1-m2 meso plots were
systematically placed in the corners of each macro plot. Each meso plot was divided into 16
subplots of 0.0625 m2 each.
Recording of vegetation
Vascular plants abundances were recorded in the meso plots as subplot frequency (1–
16 scale; T. Økland 1988). Recording was made three times (July 2000, July 2001, and July
2002).
Four data sets, all containing subplot frequency information for the 134 species
recorded in the 40 1-m2 plots, were subjected to further analysis: three sets consisted of the 40
plots analysed each of the years 2000, 2001 and 2002, the fourth included all 120 plot-by-time
combinations (the total data set).
Recording of explanatory variables
Twelve explanatory variables (Table 2) were recorded for each meso plot. Soil
samples were collected for each meso plot from the upper 10 cm of the soil and analysed for
soil physical and chemical variables. Readily available plant nutrients; P, K, Mg, Ca, were
extracted by the AL-method (Egnér et al. 1960) and determined by Inductively Coupled
Spectroscopy (ICP) at the Norwegian Centre for Soil and Environmental Research. Soil
organic matter content was assessed by determining the loss on ignition. Soil pH was
measured in water suspension (14 mL soil in 35 mL water). Soil texture (Table 1) was
classified according to Sveistrup & Njøs (1984). Aspect unfavourability, expressed as
deviation from SSW (225g, cf. R.Økland & Eilertsen 1993), was calculated from clinometer
4
Table 2. Soil variables measured for 1-m2 plots. Abbreviations: S.S. – Standardized skewness; S.K.–
standardized kurtosis, c-value – index used in transformation formula: ln (c+x) for most variables, and ecx for
variables marked with asterisk; S.D. – Standard deviation.
Variable
Loss on ignition
pH
P-AL
K-AL
Mg-AL
Ca-AL
Unit
mg/100 ml
mg/100 ml
mg/100 ml
mg/100 ml
mg/100 ml
Summary statistics for
Trans-
Summary statistics for
untransformed variable
formation
transformed variable
Range
S.S
S.K.
c-value
Mean
S.D
S.K
1-400
4.2-8.6
5.7-383
5.2-65.7
2.68-45
9.93-496
1.58
0.68
2.78
0.04
2.13
4.60
-1.16
1.25
-0.22
-1.85
0.16
3.80
-0.65
1.00
1.00
0.1
–
-4.23
2.25
1.95
1.95
0.99
–
2.09
1.10
0.16
0.16
0.34
–
1.00
-1.51
-1.17
-1.17
-0.53
–
-0.38
Aspect
Slope
Rock
%
0-175
0-20
0-30
-1.41
1.67
5.40
-0.75
0.017
4.31
0.006*
11.1
2.7
1.92
2.89
1.46
0.59
0.29
0.82
-1.10
-0.66
0.72
Distance to forest
Distance to road
Topsoil time
m
m
-
1.8-14
4-34
1-2
0.11
2.14
0
-0.89
-0.43
-2.72
47.5
0.99
–
4.01
2.59
–
0.06
0.56
–
-0.91
-1.20
–
measurements (400g scale) representative for the macro plot. SSW is considered to be the
most favourable aspect (Dargie 1984, R. Økland & Eilertsen 1993) with respect to radiation
and warmth. The slope was measured by a compass (400 g scale), to be representative for the
average surface topography of the meso plot. Percentage cover of rock (diameter > 5 cm)
was estimated subjectively. The shortest distance to undisturbed forest outside the roadside
(Distance to forest) and to the road (Distance to road) were measured from the lower right
corner of each meso plot, i.e. the corner facing the forest. The topsoil was redistributed at two
different time intervals, May and August 1999; as reflected in the Topsoil time variable
(Table 1).
To satisfy demands of parametric statistical methods for homogeneity of variances
(homoscedasticity) all variables were transformed to zero skewness (R. Økland et al. 2001,
2003). Summary statistics and transformation formulae are presented in Table 2.
Ordination
One representative for each of the two main families of ordination methods were
used in parallel to extract the main gradients in the vegetation data sets, as recommended
by R. Økland (1990, 1996): (1) Detrended Correspondence Analysis (DCA; Hill 1979, Hill
& Gauch 1980) as implemented in CANOCO Verison 4.0; ter Braak & Šmilauer 1998),
using standard options (detrending by segments, non-linear rescaling of axes and no downweighting of rare species); and (2) Local Non-metric Multidimensional Scaling (LNMDS;
Kruskal 1964a, 1964b, Kruskal et al. 1973, Minchin 1987) as implemented in DECODA,
Vesion 2.01 (Minchin 1990), using the following options (T. Økland 1996): dimensionality =
5
2, dissimilarity measure = percentage dissimilarity (Bray-Curtis), standardized by division with
species maxima (as recommended by Faith et al. 1987), 500 starting configurations, maximum
number of iterations = 1000, stress reduction ratio for stopping iteration procedure (stress is
a measure of correspondence between floristic dissimilarities between plots and the distance
between plots in the ordination diagram) = 0.99999. Because the minimal stress solution was
reached only from one out of 500 starting configurations, the two solutions with lowest stress
were considered. Both ordination methods were applied to all data sets.
Results for the total data set, obtained by the two ordination methods, were
compared by calculation of Kendall’s rank correlation coefficients τ (Kendall 1938) between
corresponding ordination axes. Strong correlations (DCA 1 vs. LNMDS 1; τ = –0.7526, p
< 0.0001, n = 40; and DCA 2 vs. LNMDS 2; τ = 0.5910, p < 0.0001, n = 40) indicated that
the two methods revealed the same main gradient structure (R. Økland 1996) and further
interpretation of gradients was therefore restricted to DCA.
Interpretation of the vegetation composition
Kendall’s τ was also calculated between all pairs of explanatory variables, and
between plot scores along ordination axes and explanatory variables.
Gradient positions (plot ordination scores; dependent variable) were tested for
differences between macro plots by one-way analysis of variance (ANOVA) (Sokal & Rohlf
1995).
For each plot and DCA ordination axis, one-year displacement along the axis was
calculated, for each of the periods 2000–2001 and 2001–2002. The hypotheses of no change
(displacement = 0) were tested against the two-tailed alternative hypothesis, using the t-test
(see Sokal & Rohlf 1995). Tests were made separately for all combinations of axis and time
period.
The variance of plot scores along each of the major DCA ordination axes (1 and 2)
in a given year was used as a measure of the extent of variation in species composition. A
hypothesis of equality of this quantity between two given years was tested against the twotailed alternative hypothesis by the variance F-test (cf. Sokal & Rohlf 1995).
Variation partitioning
The relative contribution of four different explanatory factor groups to explaining the
variation in species composition on the investigated roadsides was quantified by variation
partitioning, using partial canonical correspondence analysis (pCCA; ter Braak 1986).
Partitioning of variation on four sets of explanatory variables was performed according to the
procedure of R. Økland (2003), by which the two-group approach of Borcard et al. (1992)
and R. Økland & Eilertsen (1994) is generealised to s sets of explanatory variables. CCA was
preferred over RDA (Redundance Analysis; Rao 1964) because DCA ordination demonstrated
6
high compositional turnover along main gradients in the data set (ter Braak & Wiertz 1994, R.
Økland et al. 1999).
The four factors, and the set of variables used to represent each, were: (1) Macroplot affiliation (nine dummy variables with 1 for plots belong to a given macro plot; the
tenth macro plot characterised by 0 for all nine variables); (2) Environmental conditions
(soil, topography, stoniness; variables 1–9 in Table 2); (3) Position relative to surroundings
(distance variables 10 and 11 in Table 2); and (4) Time (time-point for soil re-distribution
(variable 12 in Table 2) and time-point for vegetation analysis (years after 2000)). Before
variation partitioning, each variable set was subjected to tests of all variables for independent,
significant contributions to explaining variation in species abundance. The forward selection
procedure in CANOCO, with its Monte Carlo test (9999 permutations of the full model; ter
Braak & Šmilauer 1998), was used. Only variables with an additional contribution significant
at the α = 0.01 level were included.
By variation partitioning, the total variation in a species-by-plot data matrix, the total
inertia TI (obtainable as the sum of eigenvalues for all unconstrained (e.g. CA) ordination
axes that may be extracted), given in arbitrary inertia units (IU), is distributed on all
unique components of variation (combinations of explanatory variable sets) and residual
variation. Because the lack-of-fit of data to the statistical model implicit in correspondence
analysis contributes strongly to the residual variation, variation components are reported as
percentages of the total variation explained by the four sets (TVE) rather than as percentage of
the total inertia (R. Økland 1999).With s = 4 sets, there are 2s – 1 = 15 unique components of
variation (partial intersections in the terminology of R. Økland 2003). Small and insignificant
components were distributed on simpler unique components (components that involved fewer
sets) by the stepwise procedure of R. Økland (2003) in order to obtain clearer results. We used
TVE/(2s–1) = 276/15 = 18.4 IU as an (arbitrary) threshold criterion; variation components
below this threshold were re-distributed. We used path diagrams to visualise variation
partitioning results (see R. Økland 2003). The nomenclature follows Lid & Lid (1994).
Results
Relationships between explanatory variables
The explanatory variables did not segregate into distinct groups (with p< 0.001; Table
3), but the soil variables were generally strongly correlated and other significant correlations
were also found (see Table 3): Soil pH increased with increasing soil stoniness (Rock; τ =
0.4142), increasing distance from undisturbed forest (τ = –0.3155), decreasing soil organic
matter (measured as loss on ignition; τ = –0.6538), and with increasing slope (τ = 0.3170).
Soils were more stony closer to the road (τ = –0.4470) although Distance to road and Distance
7
Table 3. Matrix of Kendall’s rank correlation coefficients τ between the 12 explanatory variables in the 40 plots
(lower triangle), with significance probabilities (upper triangle). Very strong correlations (|τ| > 0.36, P < 0.0001)
are given in bold face.
Loss on
ignition
Loss on ignition
pH
P-AL
K-AL
Mg-AL
Ca-AL
Aspect
Slope
Rock
Distance to forest
Distance to road
Topsoil time
pH
P-AL
K-AL
Mg-AL Ca-AL Aspect Slope
Rock
Distance Distance Topsoil
to forest to road time
-1 <0.0001 <0.0001 <0.0001
ns
ns
ns
ns 0.0028 0.0074
-0.653
<0.0001 0.0360 0.0006 0.0006
ns 0.0066 0.0010 0.0050
-0.508 0.592
0.0517 0.0024
ns
ns
ns
ns 0.0775
<0.0001 0.0009 0.0293
-0.157 0.231 0.214
ns
ns
ns
<0.0001 0.0099 0.0349
-0.163 0.380 0.335 0.467
ns
ns
0.554
<0.0001 0.0018
-0.180 0.380
ns
ns
0.114 0.366
-0.078 -0.107 0.132 -0.258 -0.305 -0.579
0.0236
ns
ns
-0.102 0.317 0.073 0.033
0.246
0.357 -0.285
0.0994
ns
-0.376 0.414
0.074 0.123 0.220
0.0271
0.114 -0.205 -0.149
0.300 -0.315 -0.198 -0.065 -0.102 -0.052 -0.176 -0.188 -0.283
0.231 -0.132 -0.040 0.335
0.171
0.052 -0.285 -0.132 -0.447 0.129
-0.041 0.073 0.164 0.526
0.342
0.189 -0.064 0.162 -0.303 0.154
0.0405
ns
ns
0.0030
ns
ns
0.0286
ns
0.0005
ns
0.294
ns
ns
ns
0.0001
0.0098
ns
ns
0.0460
ns
0.0299
ns
-
to undisturbed forest were not significantly correlated. The only significant correlation
with topsoil redistribution time was observed for Potassium (τ = 0.5263), which was also
correlated with distance to road (τ = 0.3352).
Ordination
The first two DCA ordination axes obtained for the three single-year data sets were
all strongly correlated with the corresponding axes in the ordination of the total data set
(axis 1: Kendall’s τ = 0.601–0.774; axis 2: τ = 0.355–0.660; n = 40, all P < 0.0001). This
indicates that the pattern of variation in species composition in revegetated sites did not
change significantly after the first year after revegetation. Accordingly, we therefore restrict
presentation and interpretation of ordination results to the ordination of the total data set.
The eigenvalues of the first two DCA-axes obtained for the total data set were 0.496
and 0.334, respectively. Considerably lower eigenvalues for axes 3 and 4 (0.176 and 0.140,
respectively), suggested that the data set contained two major gradients, the lengths of which
were 3.94 and 2.95 S.D. units. The strong correlations between axes of single-year ordinations
and the ordination of the total data set show that the same two major coenoclines remained the
most important throughout the three-year study period.
Although some aggregation of meso plots occurred in the two-dimensional
representation of DCA1 and DCA2, the plot scores made up a rather continuous cloud with
no distinct outliers, indicating that the meso plots made up a continuum along the underlying
complex gradients, illustrated by the 2002 DCA plot (Figure 1).
Interpretation of the ordination
Some soil variables (K and Mg) were significantly correlated (at P < 0.01) with both of
8
Fig. 1. DCA ordination of the 2002 data set, showing affiliation to macro plot.
DCA 1 and DCA 2, and Ca was correlated with DCA 1, demonstrating a relationship between
species compositional gradients and soil variables along both gradients (Table 4). DCA 1
was negatively correlated with slope and, like DCA 2, negatively correlated with aspect and
positively correlated with distance to the road. Contrary to DCA 1, DCA 2 was significantly
correlated both with time of topsoil redistribution and distance to undisturbed forest (Table 4).
DCA 2 therefore reflected a gradient of distance to undisturbed forest, in time and space.
The analysis of variance (ANOVA) revealed significant differences between macro
plot positions along both ordination axes (Table 5), indicating relatively broad-scaled patterns
of vari ation in species composition. Comparing the litter component of the soil classification
(Table 1) with positions of macro plots in the ordination diagram (Figure 1) revealed a
gradient in species composition from dry coniferous forest soils with weakly decomposed
litter to moist, mixed forest soils with better decomposed litter along DCA 2.
Although the same two coenoclines remained the most important throughout the
three-year study period, a significant displacement of plot positions was observed towards
lower DCA-1 scores from 2000 to 2001 (t-test: mean displacement = –1.44, t39 = – 6.27, P <
0.0001). Displacements from 2001 to 2002 and along DCA 2 were not significant (Table 6).
9
Table 4. Kendall’s rank correlation coefficients τ between DCA ordination axes and the 12 explanatory variables
in the 40 plots, with significance probabilities. Very strong correlations (|τ| > 0.36, P < 0.0001) are given in bold
face.
τ
Loss on ignition
PH
P
K
Mg
Ca
Aspect
Slope
Rock
Distance to forest
Distance to road
Topsoil time
Year of registration
DCA1
-0.03
0.01
0.10
0.34
0.27
0.25
-0.30
-0.29
-0.24
0.09
0.29
0.17
0.05
DCA2
P
τ
0.6613
0.9420
0.1023
0.0000
0.0037
0.0055
0.0013
0.0017
0.0102
0.3340
0.0016
0.0233
0.5279
0.07
-0.05
0.07
0.30
0.34
0.14
-0.29
0.04
-0.39
0.48
0.56
0.58
-0.17
P
0.2891
0.4589
0.2490
0.0000
0.0002
0.1238
0.0015
0.6844
0.0000
0.0000
0.0000
0.0000
0.0140
Table 5. ANOVA of gradient position (plot score in ordination of the total data set)
with respect to macro plot affiliation Separate analyses are made for each DCA axis and year.
Axes
SS
df
MS
Residual-df
Residual-MS
F-rat
P
2000
2001
2002
2000
2001
2002
DCA1
DCA1
DCA1
DCA2
DCA2
DCA2
27.885
9
3.098
30
0.450
68.799
0.0000
51.404
9
5.711
30
0.0625
91.355
0.0000
52.305
9
5.811
30
0.030
188.663
0.0000
20.736
9
2.304
30
0.0218
105.532
0.0000
25.419
9
2.824
30
0.109
25.826
0.0000
21.992
9
2.443
30
0.038
64.298
0.0000
The amount of compositional turnover along DCA, the main coenocline (as quantified
by the range of scores for plots analysed in one specific year, in S.D. units), increased strongly
from 2000 to 2001 (from 2.45 to 3.89 S.D.). This between-year difference was significant
(variance F-test of plot scores: F39,39 = 1.822, P = 0.0322). Compositional turnover remained
unchanged from 2001 to 2002 (3.79 S.D.; variance F-test: F39,39 = 1.001, P =0.4948). No
significant differences among years with respect to compositional turnover along DCA 2
were found (2.48, 2.83 and 2.50 S.D. units, respectively; variance F-test for 2000–01: F39,39 =
1.342, P =0.1813, 2001–02: F39,39 = 1.241, P =0.2519).
10
Table 6. t-test of the hypothesis that one-year displacement of plots along DCA ordination axes (120 time-byplot combinations) = 0 against the two-tailed alternative hypothesis.
mean
DCA1
DCA2
-1.44
-0.33
2000 vs 2001
t
-10.96
1.57
p
mean
2001 vs 2002
t
p
-5.3291E-15
0.117519
0.16
-0.05
-2.24
-0.50
0.0260017
0.615641
Variation partitioning
The path diagram for variation partitioning results (Figure 2) shows a key position for
macro plot in explaining variation in species composition; 70% of TVE (the total variation
explained) was attributable to macro-plot affiliation. Of this, half (36% of TVE) was
attributable to between-macro plot variation in recorded environmental variables, a minor
component (8%) was shared with time variables (most likely due to differences in time-point
for re-distribution of soil), while 26% of TVE was unshared with other measured variables.
Within macro-plot variation in recorded environmental variables accounted for 16% of TVE
(less than half of the environmental variation between macro plots), while distance and time
variables each accounted for unique components of 8% of TVE.
Macro plot
��
�
��
Environment
Distance
Time
�
�
��
Understorey species composition
Figure 2. Path diagram for partitioning of variation in species composition on four groups of explanatory
variables (see text). Numbers indicate variation as given in arbitrary inertia units.
11
Discussion
Three years after soil was redistributed on the new roadsides a heterogeneous
vegetation had established that covered the roadsides satisfactorily (Skrindo & Pedersen
2004). Although vegetation cover and species number have increased from year to year
(Skrindo & Pedersen 2004), we show in this study that the positions of sample plots along the
main gradients in species composition (ordination axes) remained relatively stable.
The stability of the gradient structure of roadside vegetation for the entire revegetation
period indicates that climatic and other external factors are relatively unimportant as
determinants of the successional pathway in the present case. Nevertheless, a succession
has evidently taken place on the experimental roadsides: our results show significant plot
displacements and differences in compositional turnover along DCA 1 from 2000 to 2001
but not from 2001 to 2002 while no such displacements were found along DCA 2. Parallel
trajectories in ordination space through time indicate that a succession is in operation
(Austin 1977), but in this case the succession mostly involves increasing species abundances
with time while the species composition remains rather stable for the first three years of
revegetation.
The revegetation pathways observed in our experiment appear less dynamic than
early successional pathways reported in studies of revegetation after disturbance in boreal
forests (Jonsson & Esseen 1998, Rydgren et al.1998, 2004). However, in situ revegetation
in moderately disturbed natural sites differs fundamentally from the ‘treatments’ involved in
road construction, from which no comparable study exists. Road construction brings about
a change of the environment from a habitat more or less sheltered by trees which moderates
temperatures, reduces incoming radiation, and reduces winds, to an open habitat.
In general, the rate of vegetation change during succession tends to slow down with
time, after a more or less chaotic start (Rydgren et al. 2004 and references cited therein). The
roadsides investigated in this study are most likely not fully revegetated after three years
although a rather stable species composition seems to establish rapidly. Our interpretation of
DCA 2 as a gradient of distance to undisturbed forest in time and space also opens for future
roadside vegetation changes in response to changes in the adjacent forest stand along with the
changes in vegetation composition and cover from year to year found in Skrindo & Pedersen
(2004).
Results of ordination as well as variation partitioning analyses unequivocally identify
large differences between the macro plots, indicating that factors operating on scales broader
than the macro plots are the most important for the variation in species composition of the
emerging roadside vegetation. Our results suggest that the key to this pattern is limited
variation in soil properties within macro plots, because of common origin of the soil from
the same pile of topsoil. Although soil characteristics vary to some extent also between
meso plots within each macro plot (as demonstrated by the significant fraction of variation
12
in species composition uniquely explained by meso-plot scale environmental variables; in
accordance with the fine-scaled spatial variation in boreal forest soil properties documented
by Skyllberg (1996), this finer-scale variation is of small magnitude in our case compared
to the variation at broader scales. Meso plots from the same macro plot share major
environmental characteristics and are therefore similar with respect to species composition,
as demonstrated by the large fraction of variation explained by environmental factors
at between-macro plot scales and by DCA axis 2 (see Figure 1) along which plots from
different macro plots segregate along a gradient from dry coniferous forest soil with weakly
decomposed litter to moist, mixed forest soil with better decomposed litter.
The variation in species composition related to soil chemical variables, both on the
between- and the within-macro plot scales, follows patterns typical of boreal forests (R.
Økland & Eilertsen 1993, 1996, T. Økland 1996, T. Økland et al. 2004). The concentrations
of Ca and Mg, correlated with DCA 1, often contribute to a complex gradient related to
soil nutrient conditions, together with acid-base status (exemplified by pH), several other
cations and the availability of N (R. Økland & Eilertsen 1993, T. Økland 1996, R. Økland
et al. 2001). In the present case, however, Ca is weakly (but significantly) correlated with
pH, but pH is unrelated to variation along DCA 1. The reason for this is not known, but the
relationship between Ca concentration and pH of forest soils is known to vary among regions
and sites in a complex manner where the relationship between pH and Ca is weakest in humid
areas (T. Økland 1996). The climate in the study area is slightly oceanic, moderately humid
(Moen 1998). A complex gradient related to soil nutrients is often related to, or conditioned
by, topographic factors such as aspect favourability, stoniness etc. (T. Økland 1996). This
is the case also in our study: DCA 1 is positively correlated with Ca and Mg concentrations
and negatively correlated with aspect unfavourability and slope, showing that the species
composition of revegetated sites makes up a gradient from steep sites on unfavourable
aspects with low base cation concentrations to vice versa. The demonstration of gradients in
species composition of revegetated roadsides that, to some extent, reflect the same underlying
complex gradients as demonstrated for (virgin) boreal forests shows that knowledge of natural
processes in the surrounding ecosystem, from which the topsoil is derived, is relevant, and
therefore important, for understanding the outcome of the revegetation process.
The usefulness and widespread use of natural topsoils for roadside revegetation is
dependent on the degree to which the outcome of such revegetation is predictable. Ingersoll &
Wilson (1990) mention three sets of predictors, knowledge of which may be important in this
respect: (i) propagule availability before disturbance; (ii) disturbance characteristics; and (iii)
morphological and physiological characteristics of plant species that influence their response
to disturbance. The difficulties we experienced with controlling the fate of topsoils during
the construction period are important in this respect, as lack of knowledge of topsoil origin
reduces control over propagule availability. Most likely, lack of such control in our case has
contributed to the large fraction of variation in species composition among revegetated plots
13
that is not due to measured environmental variables (cf. ANOVA and variation partitioning
results). Although unmeasured variables may have contributed to this variation as well,
we will emphasize that the vegetation composition after three years of revegetation were
satisfying (Skrindo & Pedersen 2004) although improved procedures for practical handling of
topsoils would increase the predictability.
Topsoil quality directly influences the emergent vegetation by its content of
propagules. Furthermore, the number of viable seeds differs among soil layers and depths
(Granström 1982, Rydgren & Hestmark 1997), in boreal forest soils generally being highest in
the humus layer and decreasing with increasing soil depth. The thickness of the humus layer
(in our study from 5 to 20 cm), and hence the organic content of the soil and its content of
propagules, varies horizontally in forests. Consequently, the number of seeds is likely to be
higher in macro plots with topsoil rich in organic matter.
Also the quantity of redistributed topsoil is likely to affect the revegetation process.
Several restoration ecologists have accepted the hypothesis that the deeper the topsoil layer
(up to the normal depth under natural conditions), the more productive will the restored plant
community be (Power et al. 1976, McGinnies & Nicholas 1980, Redente & Hargis 1985)
although Redente et al. (1997) found no difference in vegetation cover relatable to soil depth
after 10 years between topsoils that varied in thickness between 15 and 60 cm. Topsoil layers
thicker than 20 cm are considered inappropriate for revegetation of roadsides adjacent to
boreal forests like in our study area, where the humus layer before construction is less than
20 cm thick. In this study topsoil-layer thickness after re-distribution was initially set to 10
cm, but patches of thinner and thicker topsoil layers occurred because of inaccuracy in the
distribution method. This may have added to the observed within macro-plot vegetational
heterogeneity.
The great variation among different linear habitats, both in above-ground and seed
bank species composition, in a study carried out not far from the study road by Berge &
Hestmark (1997) opens for the possibility that the topsoils of different macro plots are
different also because the sites from which they originate differ with respect to vegetation
history.
Variation in seed bank quantity and species composition among topsoil lots may have
been induced by difference storage conditions and mixing of soil. No relevant study has
been done on storage effects, but seeds have been reported to die or to become dormant by
initiation of a germination process under conditions when germination cannot proceed (cf.
Baskin & Baskin 1998). Such conditions are likely to be frequent during storage.
In boreal forests there is in general a relatively poor correspondence between species
in the understory vegetation and in the soil propagule bank (cf. Eriksson 1989, Rydgren &
Hestmark 1997) because most typical shade-tolerant species do not form a persistent seed
bank (Brown & Oosterhuis 1981, Bossuyt & Hermy 2001, Bossuyt et al. 2002), in contrast to
ruderal species (i.e. Chambers & McMahon 1994). Thus, the shade-tolerant forest species, not
14
likely to survive on roadsides, are from the outset poorly represented in the forest topsoil. The
species composition of the topsoil seed bank is therefore more suited for regeneration in the
open roadside sites than that of the forest understorey in general.
Although several unknown factors reduce the predictability of the revegetation
outcome, this study shows that the first phase of the revegetation prosess follows some of the
well known paths of secondary succession in boreal forest although with stability reached
more rapidly than we had expected. Our study suggests that better knowledge of soil origin
and properties will increase outcome predictability, as the vegetation composition in this
study is related to the same underlying complex gradients as found in boreal forest. The large
amounts of unexplained variation may open for some surprises with respect to the species
composition and the changes to come, although as concluded by Skrindo & Pedersen (2004),
the vegetation composition and cover after three years are satisfactory.
Aknowledgements
We would like to thank The Public Roads Administration in Norway for letting us use
the roadside and for providing financial support. Thanks are due to the technical staff at the
nursery at The Norwegian University of Life Sciences and to Hanne Gjesteland and Mariane
Kokkim to help with the field work.
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19
P
A
P
E
R
III
Natural roadside revegetation on boreal forest top- and subsoil
Skrindo, A.B1* & Økland, R.H.2
Department of Plant and Environmental Sciences, Norwegian University of Life Sciences,
P.O.Box 5003, N-1432 Ås, Norway; 2 Department of Botany, Natural History Museum,
University of Oslo, P.O. Box 1172 Blindern, N-0318 Oslo, Norway, E-mail: r.h.okland@nhm.
uio.no;* Corresponding author; Fax +47 64947802, E-mail: [email protected]
1
Abstract.
Questions: Does natural revegetation from indigenous soil improve the procedure for
restoration of roadside areas? What are the effects of topsoil, subsoil and fertilisation, and
does the result vary between different revegetation locations?
Location: Southeast Norway
Methods: We used a recently constructed road through a boreal coniferous forest for a
three-year (2000–2002) fully replicated revegetation experiment (6 replications). Treatments
were soil type (2 levels; one topsoil and one subsoil type), fertilisation (2 levels; NPK and
unfertilsed control), and position relative to road (2 levels; road verge and the adjacent forest).
Multivariate and univariate statistical methods were used to assess the relative importance and
significance of treatments for the species composition.
Results: The species compositions of the revegetated forest and roadside differed
significantly, with more indigenous forest species in the forest than on the roadside. Inside
the forest the effects of soil type and fertilisation treatments on species composition were
weak (although significant) and no difference was found between blocks. On the road verge,
a stable pattern of variation along species compositional gradients was established already the
second year. The blocks were significantly different and significant effects of soil type (more
indigenous species on topsoil than on subsoil) but not of fertilisation were observed.
Conclusion: Our study is showing satisfactory results of natural revegetation of roadsides
from coniferous forest topsoil without fertilization.
Keywords: Restoration; Fertilisation; Norway; Ordination; Vascular plants; Vegetation
dynamics.
1
Introduction
Road construction degrades large areas and for decades roadsides have been planted
and seeded to control soil erosion and for aesthetical reasons (Laukli et al. 1999). Scientific
and practical efforts have addressed the ‘right’ choice of plant species and sowing and
planting techniques. Nevertheless, the vegetation alongside many roads struggles for survival
and the official goal ‘to restore degraded areas and to improve road aesthetics within the
natural landscape’ (Anonymous 1992) is often not reached (Laukli et al. 1999). At the same
time, old roadsides in rural areas that were never planted or seeded often revegetate naturally
to form healthy-looking vegetation with aesthetically acceptable appearance. The natural
revegetation process, from seeds, spores and vegetative parts (propagules) in the soil and
supplied from surrounding intact ecosystems, is well known for many ecosystems and on a
variety of scales, from small forest-floor gaps (Jonsson & Esseen 1990; Rydgren et al. 2004)
to revegtation after continent-scale glaciations (Blytt 1876; Matthews 1992).
Most road constructions result in road verges dominated by exposed subsoil, simply
because subsoil occurs in larger quantities than topsoil. Revegetation of subsoil often
requires amendments like fertilisation. In theory, natural revegetation by removal, storage
and redistribution of topsoil provides a simple, alternative method to seeding and planting
on subsoil. Natural revegetation from topsoil has been used as a method for restoring
degraded land throughout the world for several decades although this method has been
underrepresented in revegetation studies (e.g. Bell 1990, seeding; Wali 1999, seeding;
Petersen et al. 2004, seeding and fertilisation) and, to our knowledge, no scientific evaluation
of this method has been carried out in the boreo-nemoral and boreal regions.
Although a multi-layered soil profile is often found, in boreal forests and elsewhere,
we have restricted ourselves to a division into topsoil and subsoil. Topsoil is a wide term for
which many different definitions have been proposed, always including the upper part of the
soil horizon with the organic layer and the larger part of the propagule bank (Munshower
1994). The subsoil is defined as all soil layers not included in the topsoil.
Boreal forest soil propagule banks have been extensively studied (e.g. Moore & Wein
1977; Granström 1982; Komulainen et al. 1994; Rydgren & Hestmark 1997). Few germinable
seeds are present in the mineral subsoil layer; most viable seeds occur in the organic topsoil
(Granström 1982). Rydgren & Hestmark (1997) The species composition of the organic layer
is more similar to that of the above-ground vegetation than is the composition of the mineral
soil (Rydgren & Hestmark 1997).
Revegetation in boreal forests has also been studied under different disturbance
regimes. Rydgren et al. (1998) confirm that species differing in life history traits show
different patterns of recovery and Rydgren et al. (2004) show that revegetation succession
does not follow one path but instead follows several independent pathways, among related to
disturbance severity. Experimental disturbance studies have implied removal of different soil
2
layers (e.g. Jonsson & Esseen 1990; Rydgren 1998, 2004) while, to our knowledge, the only
studies in comparable systems in which the responses to removal, storage and redistribution
of soil have been studied are those of Skrindo & Pedersen (2004) and Skrindo et al.(subm.).
These studies show that a vegetation cover which is satisfactory from a landscape planner’s
point of view may establish rapidly and a diverse species composition with an increasing
fraction of indigenous species may establish on redistributed soil of many different types
already two years after treatment (Skrindo & Pedersen 2004). After the first two turbulent
years of revegetation a fairly stable species composition may establish, that is related to a
complex gradient of aspect favourability and soil cation concentrations (Skrindo et al. 2004
subm.) and thus comparable to main environmental complex gradients in boreal forests (R.
Økland & Eilertsen 1993; T. Økland 1996).
A newly constructed road leaves open degraded areas with large variation in
environmental conditions, e.g. along gradients in terrain shape, slope and aspect, soil
moisture, and the presence or absence of a tree canopy. Comparison of natural revegetation on
similar soils in various environments is likely to give new important insights into the natural
revegetation method and the relevance of knowledge gained in comparable ecosystems, in this
case coniferous forests, for the outcome and practical usefulness of revegetation.
Addition of NPK fertiliser is a standard treatment in roadside landscaping that
typically accompanies seeding and planting, but that is also recommended for natural
revegetation if there is shortage of essential nutrients (Pedersen 1994). The understorey
vegetation of boreal coniferous forests has been subjected to fertilisation experiments
throughout the Nordic countries, mostly with large doses of nitrogen supplied over relatively
few years (e.g. Persson 1981; Nygaard & Ødegaard 1993; Mäkipää 1995; Skrindo & Økland
1998, 2002). Negative effects on bryophyte and lichen species have often been observed,
while effects on understorey vascular plants vary strongly among studies. The need for
fertilization of redistributed topsoil used for natural revegetation of road verges may therefore
be questioned.
With the general aim of improving current procedures for restoration of degraded
roadside areas by use of indigenous soil, our aims are to quantify and test the significance of
effects of: (1) soil layer (topsoil or subsoil); (2) position relative to road (road verge and in the
adjacent forest); and (3) fertilisation (by NPK fertiliser compared to unfertilised control), on
the species composition of the restored vegetation
This study of revegetation from indigenous, stored, coniferous forest, subsoil
and topsoil, is part of a larger project dealing with natural revegetation along the
Oslofjordforbindelsen road (main road 23) in SE Norway (see Skrindo & Pedersen 2004,
Skrindo et al. subm.).
3
Material and method
Investigation area
The study area comprises a 1 km road section passing through coniferous forest,
situated in Frogn municipality in Akershus county, SE Norway (10o 25’E, 59o 44’N).
The area is situated in the boreo-nemoral vegetation zone, the slightly oceanic (O1)
section (Moen 1998). Annual mean precipitation (1961–90 normal) was 920 mm at the nearest
meteorological station (Drøbak; Førland 1993) and the annual temperature was 5.3 °C (Aune
1993). The investigation was conducted from year 1999 to year 2002.
Revegetation method
This study differs from most road revegetation projects in Norway (in which all
soil is given similar treatment) by the soil being divided into topsoil (the upper 30 cm) and
subsoil (the remaining soil). Topsoil and subsoil were stored separately for about one year
and redistributed, topsoil on top of subsoil. In the study area, no seeding or planting was
performed.
Experimental design
In 1999, six study sites (replicates, blocks) were randomly located along the road
(Fig. 1). In each block, two paired macro plots (10 ×10 m) were placed edge by edge close
to the road (roadside) while two more paired plots were placed inside the adjacent forest
(forest; 20–50 m from the road). One roadside macro plot in each pair was covered by 10 cm
topsoil while the other macro plot in each pair was covered by subsoil. Six 1-m2 plots were
Fig 1. Experimental design
4
randomly placed within each of the 12 roadside macro plots, and two plots in each macro
plot were fertilized by applying 30 kg·daa–1 NKP-fertilizer (Hydro Fullgjødsel 15, 4, 12) in
June of years 1999, 2000, and 2001. In each of the 12 forest macro plots four 1-m2 plots were
randomly placed, each surrounded by a 0.5 m buffer zone. In these plots vegetation and the
humus layer were removed entirely before applying topsoil to one macro plot and a top layer
of subsoil to the other. Two plots in each macro plot were fertilized, like roadside plots. Each
plot was divided into 16 subplots of 0.0625 m2.
Due to recurrent episodic damage during the road construction period, the number of
available plots was reduced throughout the study, in the end leaving slightly unbalanced data
sets of 44 forest plots and 69 roadside plots.
Recording of soil and vegetation and preparation of data matrices
Soil samples were collected in 1999 from the upper 10 cm soil layer in each macro
plot. Soil texture was classified according to Sveistrup & Njøs (1984). Readily available
plant nutrients, P, K, Mg and Ca were extracted by 0.1 M ammonium lactate and 0.4 M acetic
acid according to the AL-method (Egnér et al. 1960) and determined by inductively coupled
spectroscopy (ICP). Soil pH was measured in water suspension. Organic matter content was
assessed by determining the loss on ignition.
The precipitation was above, or close to, normal for all three growing seasons and no
extended, continuous, drought period occurred.
Vascular plants were recorded at the plot (1 m2) scale, on three occasions (July 2000,
2001, and 2002). Abundances were recorded as subplot frequency (1–16 scale; T. Økland
1988). Totals of 83 and 28 species were recorded in roadside and forest plots, respectively.
Seven vegetation data matrices were analysed: the total data set from 2002 (2002total)
with 44+69 plots, and six component data matrices, one for each combination of position
relative to road (roadside and forest) and year of analysis: 2000forest, 2001forest and
2002forest (44 plots each), and 2000road, 2001road, and 2002road (69 plots each). To each
vegetation data matrix corresponded a treatment matrix with three (component data matrices)
or four (total data matrix) factors: ‘block’ (6 levels), ‘soil’ (2 levels; subsoil and topsoil),
‘fertilisation’ (2 levels; control and NKP), and ‘forest’ (2 levels; roadside and forest).
Data analyses
Differences in soil factors between subsoil and topsoil were tested using Wilcoxon’s
signed-rank test for two paired samples (cf. Sokal and Rohlf 1995). Tests were against the
two-tailed alternatives.
Ordination methods were applied to the vegetation data matrices to summarise the
main gradients in species composition. One representative for each of the two main families
5
of ordination methods were used in parallel to extract the main gradients, as recommended
by R. Økland (1990, 1996): (1) Detrended Correspondence Analysis (DCA; Hill 1979; Hill
& Gauch 1980) and (2) Global Non-metric Multidimensional Scaling (GNMDS; cf. Minchin
1987).
Both methods were run using R Version 2.0.1 (Anonymous 2004a), including
packages ‘vegan’ Version 1.7–24 (Oksanen 2004) and ‘MASS’, the latter included in package
cluster ‘stats’ (Anonymous 2004b). DCA was run using function decorana with detrending
by segments, non-linear rescaling of axes, and no downweighting of rare species; GNMDS
was run using functions vegdist, initMDS, isoMDS and postMDS, with the Bray-Curtis
dissimilarity index, number of dimensions = 2, maximum number of iterations = 200 and
convergence tolerance criterion = 10–7 (cf. T. Økland 1996). GNMDS solutions were obtained
from 100 different random starting configurations. The best solution was rotated to principal
components and axes re-scaled to half-change units (H.C. units).
Corresponding DCA and GNMDS axes were strongly correlated (Kendall’s rank
correlation coefficients (Sokal & Rohlf 1995): τ > 0.223; p < 0.0066). The strong correlations
ensured that the main gradient structure in all data matrices had been found (R. Økland 1996).
Further interpretation was restricted to the GNMDS ordinations because the DCA ordinations
were burdened with tongue effects (R. Økland 1990).
The GNMDS ordination was interpreted by relating site scores to the block, soil and
fertilisation variables by split-plot ANOVA (Crawley 2002), using the aov function of R with
specification of error components (Anonymous 2004b).
The variation explained by the fertilisation, soil and block variables were quantified
by constrained ordination using Canonical Correspondence Analysis (CCA; ter Braak 1986).
CCA was applied to each of the seven data matrices, using vegan in R (Oksanen 2004).
The significance of the explained variation was assessed by a permutation test, using 999
unrestricted permutations and the partial F-statistic. The cca and pt functions of ‘vegan’
were used (Oksanen 2004). When more than two variables explained significant amount of
variation, variation partitioning by partial canonical correspondence analysis (pCCA; ter
Braak 1986) was conducted according to R. Økland (2003), who generalises the two-group
approach of Borcard et al. (1992). The nomenclature followed Lid & Lid (1994).
Results
The total species richness of revegetation plots varied throughout the study period; in
forest plots the total number of observed species increased from 24 in 2000 and 28 in 2001
to 29 in 2002; in roadside plots the total species number was 49 in 2000 and 83 in 2001 and
2002 (Table 1). The total species numbers were rather similar between subsoil and topsoil
both on the roadside and in the forest (figures incommensurable due to different plot numbers;
6
Table 1. Total number of species observed in different subsets of plots, over the three-year study period.
Year
2000
2001
2002
Topsoil
Subsoil
Forest
Forest
n = 44
n = 22
n = 22
24
28
29
17
20
19
22
26
24
Forest
Topsoil
Subsoil
Road
Road
n = 69
n = 34
n = 35
49
83
83
36
61
64
36
66
69
Road
(Table 1). Even though the total number of species was far higher on roadsides, several
species were confined to forest: Sorbus aucuparia, Vaccinium vitis-idaea, Linnaea borealis,
Maianthemum bifolium, and Oxalis acetosella. Most of these species were predominantly
found on topsoil.
Not unexpectedly, the species composition close to the road differed substantially from
that inside the forest, as demonstrated by the GNMDS ordination of the 2002total data matrix
(gradient length of first axis: 2.19 H.C. units, of the second axis: 2.03 H.C. units; Fig. 2). This
motivated for separate analyses of roadside and forest subsets.
The topsoil was a mixture of coarse and fine sand and silty loam and the subsoil
was mixture of coarse loamy sand and clay loam. The subsoil had higher concentrations of
all nutrients (P, K, Mg and Ca; Table 2) and was less acid than the subsoil. The difference
Fig. 2. GNMDS ordination of the species composition of 69 roadside (open symbols) and 44 forest (dots) plots
in year 2002, after three years of revegetation.
7
Table 2. Soil variables measured in macro plots. The codes: * - analysed by the AL-method, P – statistical
significance (Wilcoxon two-sample test for unpaired observations against the two-tailed alternative).
Topsoil
Range
Mean
Volume weight
Loss on ignition
pH
P*
K*
Mg*
Ca*
mg/ml
%
–
mg/100 ml
mg/100 ml
mg/100 ml
mg/100 ml
1.25–1.29
2.8–3.6
5.3–5.9
0.8–2.6
4.4–6.6
5.0–13.0
23–73
Subsoil
Range
Mean
1.28
3.2
5.4
1.3
4.9
7.6
35
1.13–1.17
2.5–3.3
7.1–7.8
4.9–5.3
7.6–9.1
32.6–33.8
199–293
P
1.15
3.1
7.4
4.7
8.3
33.5
257
0.059
0.035
0.031
0.031
0.031
0.031
0.031
between the topsoil and subsoil was significant for all variables except Volume weight (Table
2) although the difference in organic matter was small (Table 2).
The major coenoclines in single-year datasets for forest, extracted by GNMDS,
had gradient lengths of 2.33, 2.30 and 2.40 H.C. units for MDS1 (years 2000–2002), and
2.55, 2.28 and 2.32 H.C. units for MDS2, respectively. Correlations between corresponding
ordination axes for the different years were non-significant (MDS1; τ < 0.032, P > 0.783,
MDS2; τ < 0.175, P > 0.125, results not shown); thus no consistent coenocline structure was
established in forest in the study period.
The revegetation process in forest started out with apparently random distribution
of species over sites; the difference between blocks remained insignificant until year 2002,
three years after the start of the revegetation experiment (Table 3). No effects of soil type
Table 3. ANOVA of gradient position (plot score in ordination of the respective data set) in forest with respect to
the block, soil type and fertilisation treatments. Separate analyses are made for each GNMDS axis and year.
Response
Year 2000
GNMDS 1
GNMDS 2
Year 2001
GNMDS 1
GNMDS 2
Year 2002
GNMDS 1
GNMDS 2
Error stratum
Block
Block
Block
Block
Block
Block
Block
Block
Block
Block
Block
Block
Block
Block
Block
Block
Block
Term
Soil
Fert
Soil
Fert
Soil
Fert
Soil
Fert
Soil
Fert
Soil
Fert
df
df(Res)
Sum sq
Mean sq
F
p(F)
5
1
1
5
1
1
32
31
31
32
31
31
3.384
0.008
0.072
1.216
0.375
0.386
0.676
0.008
0.072
0.243
0.375
0.386
2.903
0.034
0.304
1.016
1.595
1.647
0.028
0.853
0.585
0.424
0.225
0.208
5
1
1
5
1
1
32
31
31
32
31
31
2.248
0.023
0.101
3.506
0.515
0.145
0.449
0.023
0.101
0.701
0.515
0.145
1.581
0.079
0.348
2.855
2.737
0.727
0.193
0.780
0.559
0.125
0.108
0.400
5
1
1
5
1
1
32
31
31
32
31
31
6.0005
0.0897
0.0561
5.2923
0.0331
0.41516
1.2001
0.0897
0.0561
1.0585
0.0331
0.41516
8.8201
0.6517
0.4047
10.026
0.3065
4.3432
< 0.0001
0.4257
0.5293
< 0.0001
0.5838
0.0455
8
or fertilization were found for the 2000 and 2001 data sets, while for year 2002 a weakly
significant effect of fertilisation on MDS2 was found (Table 3).
A direct test of the effect of soil type and fertilization on species composition in forest
by CCA revealed no significant effect in year 2000 but weakly significant effects of both soil
type and fertilisation were observed in both years 2001 and 2002 (Table 4).
The major coenoclines in single-year roadside datasets, extracted by GNMDS, had
gradients lengths of 2.33, 2.14 and 1.90 H.C. units for MDS1, and 2.55, 2.00 and 1.80
H.C. units for MDS2, respectively, for years 2000-2002. No clear pattern was found in the
ordination of the 2000 data (Fig. 3) while in the ordination of the 2002 data plot segregated
along MDS2 according to soil type (Fig. 4).
Correlation analyses showed that the corresponding ordination axes for 2000 and
each of the two other years were unrelated (τ < 0.172, p > 0.0363), while corresponding 2001
and 2002 axes were strongly correlated (τ > 0.450, P < 0.0001). Accordingly, a consistent
coenocline structure was established by the second year after treatment.
Although the piles of subsoil and topsoil were both rather homogeneous, the patterns
of roadside revegetation differed significantly among blocks in all years (Table 5).
No effects of fertilization or soil type were found for the 2000 data set, while for the
Table 4. Constrained ordination (CCA) of forest- and roadside plots seperately with the block, soil and
fertilisation variables as factors and with block as a constraining variable. P – significance level
as tested by a Monte Carlo test, VE – variation explained, TVE – total variation explained.
Year 2000
Factor
Pseudo-F
P
VE as fraction of TVE
Constraining variable
Covariable
Pseudo-F
P
Year 2001
Factor
Pseudo-F
P
VE as fraction of TVE
Constraining variable
Covariable
Pseudo-F
P
Year 2002
Faktor
Pseudo F
P
VE av TVE
Constraining var
Covariable
Pseudo-F
P
Forest
Block
0.835
0.123
–
Block
–
–
Block
1.081
0.063
–
Block
–
–
Block
1.877
< 0.001
46%
Block
–
–
Roadside
Soil
0.641
0.434
–
Fert
0.631
0.485
–
Soil
–
–
Fert
–
–
Soil
1.189
0.023
0.166
Fert
0.961
0.104
–
Soil
1.659
0.001
Fert
1.224
0.048
Soil
1.044
0.029
27%
Fert
1.096
0.023
26%
Soil
1.114
0.053
Fert
1.244
0.029
9
Block
2.202
< 0.001
66%
Block
Block
2.665
< 0.001
62%
Block
3.305
< 0.001
Block
3.458
< 0.001
57%
Block
3.056
< 0.001
Soil
1.083
0.004
34%
Fert
0.730
0.287
–
Soil
1.303
< 0.001
Fert
0.906
0.104
Soil
1.571
0.011
37%
Fert
0.899
0.670
–
Soil
1.839
< 0.001
Fert
1.079
0.308
Soil
1.831
< 0.001
31%
Fert
0.759
0.915
–
Soil
2.118
< 0.001
Fert
0.8754
0.7287
Fig. 3. GNMDS ordination of the 69 roadside plots recorded in year 2000, showing soiltype and fertilization;
unfertilized subsoil (open squares), fertilized subsoil (x), unfertilized topsoil (filled box), fertilized topsoil (filled
square).
Fig. 4. Figure 3. GNMDS ordination of the 69 roadside plots recorded in year 2002, showing soiltype and
fertilization; unfertilized subsoil (open squares), fertilized subsoil (x), unfertilized topsoil (filled box), fertilized
topsoil (filled square).
10
Table 5. ANOVA of gradient position (plot score in ordination of respective data set) on roadside with respect to
the block, soil type and fertilisation treatments. Separate analyses are made for each GNMDS axis and year.
Response
Year 2000
GNMDS 1
GNMDS 2
Year 2001
GNMDS 1
GNMDS 2
Year 2002
GNMDS 1
GNMDS 2
Error stratum
Block
Block
Block
Block
Block
Block
Block
Block
Block
Block
Block
Block
Block
Block
Block
Block
Block
Term
Soil
Fert
Soil
Fert
Soil
Fert
Soil
Fert
Soil
Fert
Soil
Fert
df
df(Res)
Sum sq
Mean sq
F
p(F)
5
1
1
5
1
1
63
62
62
63
62
62
14.6918
0.2268
0.1537
7.2874
0.6138
< 0.0001
2.9384
0.2268
0.1537
1.4575
0.6138
< 0.0001
19.341
1.5045
1.0121
7.1423
3.1088
0.0001
< 0.0001
0.2246
0.3183
< 0.0001
0.0828
0.9920
5
1
1
5
1
1
63
62
62
63
62
62
17.2564
0.1075
0.0002
5.507
0.6688
0.0042
3.4513
0.1075
0.0002
1.1014
0.6688
0.0042
33.053
1.0302
0.0016
6.3608
4.0492
0.0238
< 0.0001
0.3141
0.9680
< 0.0001
0.0485
0.8778
5
1
1
5
1
1
63
62
62
63
62
62
3.4196
0.6744
0.1149
4.5693
1.1225
0.0093
0.6839
0.6744
0.1149
0.9139
1.1225
0.0093
4.345
4.5241
0.7265
10.312
15.601
0.1035
0.0018
0.0374
0.3973
< 0.0001
0.0002
0.7487
2001 and 2002 data sets significant effects of soil type were found on MDS2 in 2001 and on
both axes in 2002 (Table 5).
A direct test of the effects of soil and fertilisation on species composition by CCA
revealed no effect of fertilization but a significant effect of soil type in all three years (both
when blocks were included as a factor and after removal of a block effect by including a
covariable; Table 4). The variation explained by block was about twice the variation explained
by soil type, but the effect of soil type remained significant after the variation due to block had
been removed (Table 4).
Among rather common species (each of which occurred in more than five plots; Table
6), four were restricted to subsoil plots (Ranunculus repens, Rorippa palustris and Sagina
subula, Carex echinata) and eleven were restricted to topsoil plots (Table 6). All the observed
woody species were more frequent in topsoil than in subsoil plots (Table 6). In addition, seed
plants typically inhabiting the forest floor only appeared in a few forest plots and then in
the topsoil only (Calluna vulgaris, Vaccinium myrtillus, Melampyrum pratense, Pteridium
aquilinum, and Calamagrostis purpurea).
11
Table 6. Frequency (%) of species occurring in more than five 1-m2 plots in forest in year 2002.
Names in bold face occurred on one soil type only. Top; topsoil, Sub; subsoil.
Top
%
Sub
%
Betula pubescens
Picea abies
Pinus sylvestris
Rubus idaeus
Salix caprea
42
31
36
33
23
10
25
23
23
10
Achillea millefolium
Artemisia vulgaris
Cerastium fontanum
Chenopodium album
Cirsium arvense
Epilobium
Equisetum arvense
Geranium sylvaticum
Leontodon autumnalis
Matricaria perforata
Potentilla erecta
Ranunculus repens
Rorippa palustris
Sagina subulata
Senecio sylvaticus
10
13
11
6
9
30
9
9
16
17
30
7
7
16
19
10
30
14
14
10
12
20
9
9
-
Top
%
Sub
%
Taraxacum sp
Trifolium pratense
Tussilago farfara
Veronica officinalis
7
16
43
30
38
19
50
-
Agrostis canina
Agrostis capillaris
Alopecurus geniculatus
Anthoxanthum odoratum
Carex canescens
Carex echinata
Carex flava
Carex ovalis
Deschampsia cespitosa
Deschampsia flexuosa
Festuca ovina
Festuca rubra
Juncus filiformis
Luzula multiflora
Luzula pilosa
Phleum pratense
15
46
12
7
23
9
30
19
23
9
7
7
8
26
8
39
17
9
9
9
13
12
9
13
10
Discussion
Differences between forest and roadside
The strong difference between the emerging species compositions inside the forest
and close to the road was probably due to a combination of several factors that differed
between the two locations relative to the road: microclimate (radiation and temperature),
soil moisture, and influx of, and germination from, seeds, spores and vegetative plant
parts from the surroundings. This is demonstrated by the occurrence of typical forest-floor
species only inside the forest and on topsoils (Vaccinium vitis-idaea, Linnaea borealis,
Maianthemum bifolium, Oxalis acetosella and Sorbus aucuparia; Lid & Lid 1994, Fremstad
1997). These results also accord with results of another revegetation experiment along the
same road (Skrindo et al. subm.), in which strong correlations were observed between the
emergent species composition on soils of 10 different origins and slope and aspect, factors
known to affect the microclimate. Trees provide shelter for the forest-floor understorey from
exposition to extreme conditions of radiation, drought, heavy rain and winds, and the presence
of a canopy is likely to be important for establishment of the well-known compositional
differences between the shaded forest floor and open meadows or roadsides in the Norwegian
12
lowlands (e.g. Fremstad 1997). Even within boreal forests, the species composition varies
along a complex gradient related to incoming radiation and canopy closure (R. Økland &
Eilertsen 1993; T. Økland 1996; R. Økland et al. 1999; T. Økland et al. 2003).
The tree canopy filters the incoming radiation and, although there is some variation
due to canopy density and among canopy trees, all canopies deplete the spectre in the
photosynthetically active region (400–700 nm), and give rise to a peak in throughfall radiation
in the far-red region (700–800 nm) (Coombe 1957, Grime & Jarvis 1975; also see Grime et
al. 1981). For some species a low red-far red ratio inhibits germination (e.g. Frankland 1976;
Frankland and Taylorson 1983) and may thus contribute to lower germination inside the forest
than on the roadside.
Although the upper soil layer inside the forest and on the roadside was derived from
the same pile of soil, the constructed roadside differs from the adjacent forest with respect to
surface water flow, drainage and soil water content (e.g. Montgomery 1994). The different
growth conditions are likely to be important for the species compositional differences.
The higher number of species in the roadside may also, at least partly, be a result of
the better opportunities for longer-distance dispersal of diaspores in the open roadside habitat
(e.g. Panetta & Hopkins 1991; Tyser & Worley 1992; Trombula & Frissell 2000), and the
opportunity for dispersal by vehicles (e.g. Schmidt 1989).
In the forest, no significant correlation was found between ordination axes obtained for
any pair of years. This is in accordance with results of revegetation studies after disturbance
in boreal forests (Jonsson & Esseen 1998; Rydgren et al.1998, 2004), showing that the first
turbulent phase of the secondary succession in boreal forests lasts for more than three years.
The species composition on roadsides stabilises the second year after the start of our
revegetation experiment, as demonstrated by the strong correlation between corresponding
ordination axes from 2001 and 2002. Rapid stabilisation of species composition on roadsides
is in accordance with the results of the parallel revegetation experiment of Skrindo et al.
(subm.).
Factors affecting the outcome of roadside revegetation
On the road verge, the species composition differed significantly between topsoil and
subsoil in all three years. None of the four common species (occurring in more than five plots)
that were restricted to subsoil (Ranunculus repens, Rorippa palustris, Sagina subulata, Carex
echinata) were forest species (Lid & Lid 1994; Fremstad 1997), while the 11 common species
restricted to topsoil with one exception (Chenopodium album) are known to occur in forests
and forest edges (Geranium sylvaticum, Potentilla erecta, Senecio sylvaticus, Agrostis canina,
Anthoxanthum odoratum, Carex canescens, Carex flava, Juncus filiformis, Luzula multiflora
and Luzula pilosa; Lid & Lid 1994, Fremstad 1997). In addition, several common forestfloor species only appeared in a few plots on topsoil (Calluna vulgaris, Vaccinium myrtillus,
Melampyrum pratense, Pteridium aquilinum, Trientalis europaea and Calamagrostis
13
purpurea). We conclude that topsoil provides a revegetation result in better accordance
with the indigenous vegetation than does subsoil. This accords with the results of Rydgren
& Hestmark (1997), that the species composition of the propagule bank is more similar to
above-ground vegetation in upper than in lower soil layers, and with results of Jonsson &
Esseen (1990) and Rydgren et al. (1998, 2004) that the revegetation species composition is
more similar to the composition of the forest floor when the disturbance is less severe.
All woody species are more frequent in topsoil than in subsoil plots. Woody species
are not always welcomed on roadsides for traffic safety reasons and will, eventually, trigger
needs for management. However, woody species are also frequent in subsoil, showing that
eventually there will be a need for management regardless of choice of soil type.
The surprisingly similar organic matter contents in topsoil and subsoil may be
unwarranted side effects by practical handling of the soil. Higher amounts of organic matter
increase plant growth in revegetation studies (Claassen & Zasokski 1993; Redente et al. 1997;
Rokich et al. 2000) and result in higher species richness (Skrindo & Pedersen (2004).
Different species compositions between topsoil and subsoil despite the small
differences in organic matter and soil texture indicate that the content of the propagule bank
is more important than the soil nutrient balance as long as no deficiency of essential nutrients
occurs.
A weak fertilisation effect was observed inside the forest in years 2001 and 2002,
while no effect was observed in roadside. This apparently contrasts with our expectations,
because fertilisation is well known to increase plant production in general and in seeded
roadsides in particular (Petersen et al. 2004), and nitrogen limits growth in Fennoscandian
boreal forests (Tamm 1991). However, strongly variable effects of fertilisation on the
boreal coniferous forest understorey species composition is reported in the literature with
no consistent pattern for vascular plant species (e.g Persson 1981;Skrindo & Økland 2002;
Falkengren-Grerup & Schöttelndreier 2004). This accords with our results and strengthens our
conclusion that fertilisation of naturally revegetating roadsides is not needed as long as soil
nutrient levels are satisfactory.
The significant difference in roadside species composition among blocks, persisting
for the entire study period, indicates that local factors are important determinants of the
outcome of revegetation, and that natural revegetation will produce a roadside with variation
in species composition. Several processes may contribute to this: (1) natural heterogeneity
in seed composition due to the aggregation of seeds in the seedbank (Granström 1982;
Rydgren & Hestmark 1997); (2) variation in natural growth conditions (local microclimate,
aspect, packing of the subsoil below the topsoil layer and, hence, water retention capacity
of the soil column, etc. along the road; (3) variation in distance to adjacent forest (and,
hence, to the major source of propagules); and (4) variation along the road with respect
to adjacent ecosystems and the successional stage they are in. The strong effect of factor
‘block’ in our study shows that six more or less different outcomes of natural revegetation
14
will result from the same topsoil. All outcomes are, however, likely to be satisfactory from
a planner’s point of view of aesthetics and ease of management, because all represent high
vegetation cover, acceptable species richness, and a rather self-sustainable ecosystem.
Thus, the use of unfertilized coniferous forest topsoil for natural revegetation of roadsides
provides satisfactory results even when the organic component is small, albeit the results of
revegetation are not entirely predictable in terms of species composition.
Aknowledgements
We would like to thank The Public Roads Administration in Norway for letting us use
the roadside and for providing financial support. Thanks are due to the technical staff at the
nursery at The Norwegian University of Life Sciences to help with the experimental work.
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19
P
A
P
E
R
IV
Effects of light quality and frugivory by bears (Ursus arctos L.) on
seed germination of Vaccinium myrtillus L.
Skrindo, A.B
Department of Plant and Environmental Sciences, Norwegian University of Life Sciences,
P.O.Box 5003, N-1432 Ås, Norway
Abstract
Questions: Does germination of Vaccinium myrtillus vary between light quality regimes
imitating different tree canopies? Is there a difference between lowland and alpine
populations? Does ingestion by bears affect germination of V. myrtillus? Does the interaction
between ingestion by bears and light quality affect germination of V. myrtillus?
Location: Southeast Norway
Methods: Factorial germination tests were performed in growth chambers with seeds
extracted from berries harvested in a forest, with and without having been ingested by bears,
and from an alpine population of V. myrtillus. The light quality varied in red to far-red ratios
imitating no canopy, open canopy and dense coniferous canopy.
Statistical difference in germination percentage was analysed with generalized linear models
(GLM), including a multiple range test, Ryan-Einot-Gabriel-Welsh (REGWQ) on the main
effects.
Results: There was a significant effect of light quality. The lowest germination percentage
was found when the seeds were incubated at the highest far-red level (dense canopy).
Reduced germination was found in seeds that had been ingested by bears, but no difference
was found between the two Vaccinium populations. The lowest germination percentage was
observed in seeds from feces incubated at the highest far-red level.
Conclusion: Germination of V. myrtillus seeds, both from alpine and lowland populations, is
poorer in light conditions imitating a dense tree canopy. Ingestion by bears does not enhance
germination.
Key words: Vaccinium myrtillus, germination, seed, light quality, far-red light, frugivory,
bears
1
Introduction
From a life history perspective, the existence of any plant species is dependent on
reproduction, either vegetative or generative. The overall importance of generative
reproduction is expected to decrease from annual to perennial species and and even more so
for species with the capacity for clonal growth as seedling recruitment is generally infrequent
in most clonal plant species (i.e Harper 1977; Eriksson & Fröborg 1996). Clonal species still
have seed regeneration to secure a genetic variation and for revegetation of new sites.
Vaccinium myrtillus is a deciduous, clonal shrub with berries. It is a dominant species of
the field layer in boreal forests, other forests and in the low alpine region of the northern
hemisphere (Kielland-Lund 1981). The seeds are dispersed either by falling and rolling on the
ground or eaten by frugivores.
Seed production in stands of Vaccinium species is often high but some species hardly
develope seed banks (Thompson 1992; Vander Kloet & Hill 1994). V. myrtillus, however, has
a large seed bank recorded from all soil layers and in several stands of boreal forests differing
in age (Granstöm 1982; Rydgren & Hestmark 1997).
Even though different Vaccinium species dominate the field layer of many temperate,
boreal and alpine ecosystems, few observations of seedling recruitment in natural populations
are reported (Van der Kloet and Hill 1994; Eriksson & Fröborg 1996; Laskurain et al. 2004).
However, V. myrtillus is found to germinate in some experiments (Eriksson & Fröborg 1996,
Eriksson 2002, Skrindo unpublished) and Eriksson & Fröborg (1996) found seedlings to
survive on disturbed, non-vegetated substrates, and mostly on the bog end of a gradient from
closed forest to open bog.
Along the gradient from forest to bog the presence of tree canopy is a major changing
factor. The tree canopy filters the sun light and, although variation in the spectre between
canopy types and densities exist (Morgan & Smith 1981), all canopies show depletion in the
photosynthetically active region (400-700 nm) and a peak in the far-red region (700-800 nm)
(Grime & Jarvis 1975; Morgan & Smith 1981).
Light-controlled seed germination is often a phytochrome-mediated response
(Frankland 1976, Kendrick & Kronenberg 1994). The promotion of seed germination takes
place after exposure to red light, which converts the inactive Pr form of phytochrome to the
active Pfr form. Exposure to far-red light converts the phytocrome back to Pr and inhibits
germination. Giba et al. (1995) germinated V. myrtillus seeds by exposing them to different
intervals of red light and far-red light and found that phytochrome controlled germination. As
2
the red to far-red ration (R:FR) differs with type of tree canopy and distance to tree canopy,
varying germination under different R:FR regimes is relevant for the recruitment under
canopy.
The benefits of seed movement away from parent plants are well known (reviwed by
Schupp 1993) but the effect on germination after being ingested varies both between plant and
frugivore species (reviewed by Traveset 1998; Baskin & Baskin 1998). Few studies have been
published on the effect of frugivory on the germination of V. myrtillus and closely related
species. V. myrtillus seeds ingested by martens (Martes foina, M. martes) showed enhanced
germination compared to not ingested seeds (Schaumann & Heinken 2002). In the closely
related species V. ovalifolium and V. alaskaensis, no germination effect was found between
non-ingested seeds and seeds ingested by bears (Ursus spp.) or several bird species (Turdus
spp. and Ixoreus spp.) (Traveset & Willson 1997; Traveset et al. 2001) and V. augustifolium
seeds ingested by American robin (Tardus migratorus) germinated less than non ingested
seeds (Crossland & Vander Kloet 1996), and the same result was found when the seeds were
ingested by three rodent species (Krefting & Roe 1949).
The aims of this study are to study the germination success in different constant light
qualities, imitating absence of tree canopy and two different tree canopy densities and to
compare the seed germination success of V. myrtillus from two different populations, from a
forest and from a low alpine population. Finally, germination effects after being ingested by
bear were to be studied.
Materials and methods
Berry collection and seed preparation
In August 1999, berries were collected from a boreal coniferous forest in Frogn
municipality in Akershus county, SE Norway (10o 25’E, 59o 44’N) at 130 m.a.s.l and in a
low alpine heath in Ål municupality in Buskerud county, SE Norway (8o 34’ E, 60o 43’N ) at
1000 m.a.s.l. A batch of forest-berries was fed to brown bears (Ursus arctos) in a wildlife
park (Vassfaret bjørnepark) in Flå municipality, Buskerud county, SE Norway. The feces
were collected after two days.
The berries and feces were crushed gently and rinsed of fruit material and dirt to release
the seeds. The seeds where dried in open containers at room temperature for 5-10 days. The
seeds where stored for six to eight months at 2° C in a dark and dry room prior to the
3
germination test. The three different seed categories originating from the different populations
and treatments, are termed: (1) forest seeds, (2) alpine seeds and (3) ingested seeds.
Experimental design
In February 2000, a factorial experiment of four lots of 50 seeds from alpine, forest and
bear feces were placed on moist filter paper (distilled water) in boxes, incubated in growth
chambers at 18° C, 18 hour day length. To imitate different light qualities in open areas (light
1), a rather open forest (light 2) and a dense canopy (light 3), the seeds where incubated under
three different light regimes, based on red (660 nm) to far-red (730 nm) ratios (R:FR) of 1.15
(light 1), 0.65 (light 2) and 0.35 (light 3). The choices of R:FR-ratios were based on Smith
(1994) for daylight in open areas, Smith et al. (1990) for rather open tree canopies and
Coombe (1957) for dense coniferous forests. The incubation light was a combination of white
light (Osram L36/W22) and far-red light from far-red fluorescent light tubes (No. 7080, from
Sylvania BioSystems). The light quality (R:FR ) was detected by an SKR 100: 660/730
radiation detector (SKYE instruments Ltd., Landrindod Wells, Powys, Wales, U.K.). All light
qualities had a fluence rate of 40 µmol m-2 s-1.
Germination was recorded three times a week and the germination percentage was
recorded after five weeks. All subsequent operations were performed under a weak green
safe-light.
Another similar experiment was conducted directly after the first, under the same
conditions. However, only three lots of forest and alpine seeds were used, and no ingested
seeds. This resulted in an unbalanced design: seven replicates for alpine and forest seeds and
four replicates for seeds from bear feces.
Data analyses
The difference in germination percentage between the three light qualities and the three
seed qualities was statistically tested using variance analysis, generalized linear models
(GLM), including a multiple range test, Ryan-Einot-Gabriel-Welsh (REGWQ) on the main
effects, with a significance level of p < 0.05 (Anon. 1989). To study the interaction between
light quality and seeds from lowland forests, with and without ingestion by bears, a GLM
analysis was performed without the seeds from the alpine heath.
A cumulative germination curve was constructed to describe the germination rate
throughout the germination period.
4
Results
Seeds from both the alpine heath and the lowland forest, and seeds extracted from bear
feces germinated in all three light qualities. There was no difference in germination
percentage between the population from the alpine heath and the population from the lowland
forest that was not ingested by bears (Table 1).
The effect of light quality on germination was significant (F-value = 20.90, P =
<0.0001), as there was a lower germination percentage at the highest far-red level (light 3,
Table 1), but no difference between germination in the other two light qualities (Table 1).
Seeds of all qualities germinated at approximately the same time and during the same
period. Seeds incubated in light 1 (highest R:FR-ration) germinated after 14 days, in light 2
after 15 days and in light 3 after 17 days, and seeds continued to germinate until five weeks
had passed.
The germination rate was higher for all seeds incubated in light imitating open areas and
rather open forests (light 1 and 2) compared to light imitating a dense coniferous forests (light
3; Fig. 1). All three seed qualities showed a similar germination pattern in the light regime
imitating open areas (light 1) compared to the two other light regimes. In the light imitating a
dense coniferous forest (light3), seeds ingested by bears showed a slower germination rate
than the two other seed qualities. The differences in germination rate between seed qualities
are not as obvious, as there are overlapping standard deviations at all light qualities (Fig. 1).
There was a significant effect of seed category on germination percentage (F-value =
5.79, P = 0.0055), as fewer ingested seeds germinated than non-ingested forest or alpine seeds
(Table 1).
Table 1. Germination of seeds from forest, alpine heath and bear feces after five weeks of incubation
in different light qualities. Values followed by the same letter within a column are not significant
different at P < 0.05.
Seed category
Light quality
1 (R:FR = 1.15)
2 (R:FR = 0.65)
3 (R:FR = 1.35)
Mean
Forest seeds
Alpine seeds
Ingested seeds
Mean
73 %
65 %
56 %
79 %
87 %
50 %
67 %
71 %
22 %
73 % A
74 % A
42 % B
65 % B
72 % B
53 % A
5
The interaction between light quality and seed quality was also significant (F-value =
2.74, P = 0.0388). The germination percentage after five weeks of incubation varied from
87 % for alpine seeds at light 2 (the second highest R:FR-ratio) to 22 % for ingested seeds at
light 3 (the lowest R:FR-ratio, Table 1). The interaction between ingested seeds and seeds
from forest without beeing ingeste was also significant (F-value = 4.00, P = 0.282).
Discussion
There was no difference in the effect of light quality on germination percentage or rate
between alpine and lowland forest seeds. This agrees with other germination characteristics,
such as temperature and stratification, between populations of V. myrtillus in Sweden (Baskin
et al. 2000), although several other species show varying germination traits between
populations (Baskin & Baskin 1998).
Fewer seeds germinated after being ingested by bears in all light qualities. Although
ingestion effect often varies between frugivore species (Traveset 1998), this contradicts
findings of enhanced germination of V. myrtillus in marten feces (Schaumann & Heinken
2002). Our findings, however, are in accordance to Krefting & Roe (1949) and Crossland &
Vander Kloet (1996), who found a negative germination effect on a related species, V.
angustifolium, after ingestion by three rodent species and robins (Turdus migratorius).
Vaccinium seeds are relatively small, therefore the plant invests little energy in the production
of individual seeds, according to Croch & Vander Kloet (1980). These authors thus argue that
destruction of some seeds by ingestion is not a major loss to the parent plant, just part of the
cost of dispersing seeds away from the parent plant (Crossland & Vander Kloet 1996).
There was no obvious effect on the germination rate between the seeds ingested by
bears and those not ingested by bears in our study. This agrees partly with results from a
related species, V. ovalifilium/alaskaenses, where no effect on germination rate or
germination percentage was observed after ingestion by bears (Ursus arctos) and several bird
species (Traveset & Wilson 1997; Traveset et al. 2001).
Several other non-Vaccinium species also showed reduced germination (Baskin &
Baskin 1998; Traveset 1998), as V. myrtillus did in this study. The reason is not well
understood, although damage to the seeds could be a possible explanation. While the testa of
uningested seeds of V. myrtillus were intact and the cell walls were evident, the coat of an
ingested seed showed some damage to its cell wall (Shcaumann & Heinken 2002). If the testa
was damaged due to bear ingestion in the present study, it is likely that the treatment of
washing, cleaning, drying and storing the seeds killed them. Seed treatment differs between
7
studies, and these differences might not be accounted for when comparing different studies.
Schaumann & Heinken (2002) washed and dried the seeds the same way as in the present
study, but did not store the seeds and found increased germination after being ingested by
martens. Crossland & Vander Kloet (1996) did not wash the seeds and detected 15 pathogens
when they found reduced germination of V. angustifolium after ingestion by robins.
The most common positive germination effect of frugivore ingestion on plant species
from several ecosystems is breaking of physical dormancy (Baskin & Baskin 1998). V.
myrtillus only has conditional physiological dormancy (Baskin et al. 2000), given that mature
seeds germinate under limited conditions and that the condition amplitude increases after
stratifications (Baskin & Baskin 1998).
The comparison between related species is questionable, as the seeds are different and
often show varying frugivore effects (Traveset 1998; Vander Kloet & Hill 2000). In some
cases, even the same plant species has been shown to respond differently to the same
frugivore, depending on environmental factors, plant population and seed age (Traveset
1998). Nevertheless, in order to see the complex picture and for finding implications for other
V. myrtillus populations, I find the comparison interesting, although no clear pattern seems to
dominate.
Although the germination effect is questionable both in this and other related studies,
frugivores can affect seedling establishment in different ways (as summed up in Traveset
1998): (1) the site and micro site where they regurigate or defecate seeds; (2) the time when
seed ingestion and dispersal takes place; (3) how clean of pulp they leave the seed; (4) the
amount of seeds defecated in a dropping; (5) the diversity of seed species found in a
defecation; (6) the frugivore’s selection of a specific fruit’s traits (i.e., size) within a species;
and the plant nutrient content of the frugivore’s feces.
In the present study, the interaction between the different seed categories and light
quality is significant. The lowest germination percentage was found for seeds that had been
ingested by bears, and thereafter incubated at the lowest R:FR-ratio. Although no comparable
studies have previously been published for Vaccinium species, some tropical species ingested
by mammals gain the ability to germinate in far-red light and hence, are able to germinate
under a canopy cover (Vazquez-Yanes & Oroxco-Segovia 1986). This would have broadened
the range of germination conditions for V. myrtillus, but this study does not provide any proof
for that.
8
For all seed categories, the seeds incubated at a low R:FR-ratio (high level of far-red
light) had lower germination rate and percentage than the two other R:FR- ratios, indicating
that seeds germinating under a tree canopy germinate poorer than seeds in clearings.
V. myrtillus does not germinate in the dark without being irradiated (Giba et al. 1993;
Giba et al. 1995; Baskin et al. 2000). Germination of V. myrtillus is known to be controlled by
phytochrome, as two days of continuous red light at a fluence rate of 3.54 µmol m-2 s-1 was
sufficient to induce germination in about 50 % of the seeds, but five minutes of far-red light at
a fluence rate of 4.85 µmol m-2 s-1 alone was sufficient to inhibit germination (Giba et al.
1995). No previous studies have been done with different R:FR ratios on either V. myrtillus or
other related species, although it is known that the phytochrome system is active in
intermediate ratios of R:FR (Baskin & Baskin 1998). Several forest species show a
comparable effect of far-red light on germination, for example, Picea abies (Leinonen & De
Chantal 1998), Betula pendula (Ahola & Leinonen 1999) and Pinus sylvestris (Nyman 1961)
although in the study of Ahola & Leinonen (1999).
In contrast to these tree species, seedlings of V. myrtillus are rarely reported in natural
populations, and seedling survival is poorly studied (Vander Kloet and Hill 1994; Eriksson &
Fröborg 1995, Laskurain et al. 2004). The reasons for poor germination and seedling survival
in natural populations are probably a complex combination of factors, including the
preference of decaying wood by seedlings, although germination is found on other nonvegetated substrates (Eriksson og Fröborg 1996), and non-overlapping niches for mature
plants and seedling (Eriksson 2002). Still, the seeds germinate under different controlled light,
temperature and seed treatment conditions (i.e, Giba et al. 1993; Giba et al. 1995; Baskin et al.
2000; Schaumann & Heinken 2002). Germination is mostly found in open areas (Eriksson and
Fröborg 1996). This is supported by this study, which found higher germination percentages
in light qualities imitating a rather open forest and an open area than in light conditions
imitating a dense forest.
Acknowledgements
I would like to express my appreciations to the staff at the wildlife park (Vassfaret
bjørnepark) for letting me feed the bears and retrieve the feces. I thank Ole Billing Hansen for
initiating this study, Per Anker Pedersen for comments on the manuscript, Ann Helen Kalfjøs
for techical assistance and especially Ellen Zakariassen for techical and statistical assistance.
9
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