Global Change Biology (2003) 10, 105–123, doi: 10.1046/j.1529-8817.2003.00719.x
Long-term ecosystem level experiments at Toolik Lake,
Alaska, and at Abisko, Northern Sweden: generalizations
and differences in ecosystem and plant type responses to
global change
M . T . VA N W I J K *w , K . E . C L E M M E N S E N z, G . R . S H AV E R w , M . W I L L I A M S *,
T . V. C A L L A G H A N § z , F . S . C H A P I N I I I k , J . H . C . C O R N E L I S S E N **, L . G O U G H w w ,
S . E . H O B B I E zz, S . J O N A S S O N z, J . A . L E E § , A . M I C H E L S E N z, M . C . P R E S S § ,
S . J . R I C H A R D S O N § § and H . R U E T H w
*School of Geo Sciences, University of Edinburgh, Darwin Building, King Buildings, Mayfield Road, Edinburgh EH9 3JU, UK,
wThe Ecosystem Center, Marine Biology Laboratory, Woods Hole, MA 02543, USA, zDepartment of Physiological Ecology,
University of Copenhagen, Øster Farimagsgade 2D, DK-1353 Copenhagen, Denmark, §Department of Animal and Plant Sciences,
University of Sheffield, Sheffield S10 2TN, UK, zAbisko Scientific Research Station, SE 981-07 Abisko, Sweden, k Department of
Biology and Wildlife, Institute of Arctic Biology, University of Alaska-Fairbanks, Fairbanks, AK 99775, USA, **Department of
Systems Ecology, Vrije Universiteit, De Boelelaan 1085, 1081 HV Amsterdam, The Netherlands, wwDepartment of Biology,
University of Texas at Arlington, Box 19498, Arlington, TX 76019, USA, zzDepartment of Ecology, Evolution, and Behavior,
University of Minnesota, 1987 Upper Buford Circle, St. Paul, MN 55108 USA, §§Landcare Research,
PO Box 69, Lincoln 8152, New Zealand
Abstract
Long-term ecosystem-level experiments, in which the environment is manipulated in a
controlled manner, are important tools to predict the responses of ecosystem functioning
and composition to future global change. We present the results of a meta-analysis
performed on the results of long-term ecosystem-level experiments near Toolik Lake,
Alaska, and Abisko, Sweden. We quantified aboveground biomass responses of
different arctic and subarctic ecosystems to experimental fertilization, warming and
shading. We not only analysed the general patterns but also the differences in
responsiveness between sites and regions. Aboveground plant biomass showed a broad
similarity of responses in both locations, and also showed some important differences.
In both locations, aboveground plant biomass, particularly the biomass of deciduous
and graminoid plants, responded most strongly to nutrient addition. The biomass of
mosses and lichens decreased in both locations as the biomass of vascular plants
increased. An important difference between the two regions was the smaller positive
aboveground biomass response of deciduous shrubs in Abisko as compared with Toolik
Lake. Whereas in Toolik Lake Betula nana increased its dominance and replaced many of
the other plant types, in Abisko all vascular plant types increased in abundance without
major shifts in relative abundance. The differences between the responses of the
dominant vegetation types of the Toolik Lake region, i.e. tussock tundra systems, and
that of the Abisko region, i.e. heath systems, may have important implications for
ecosystem development under expected patterns of global change. However, there were
also large site-specific differences within each region. Several potential mechanistic
explanations for the differences between sites and regions are discussed. The response
patterns show the need for analyses of joint data sets from many regions and sites, in
order to uncover common responses to changes in climate across large arctic regions from
regional or local responses.
Correspondence: Mark T. van Wijk, Plant Production Systems,
Wageningen University, Postbus 430, 6700 AK Wageningen,
The Netherlands, tel. 131 (0)317 482141, fax 131 (0)317 484892.
Email: [email protected]
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106 M . T . VA N W I J K et al.
Keywords: arctic, global change, long-term ecosystem-level experiments, meta-analysis
Received 28 January 2003; revised version received 22 April 2003 and accepted 13 October 2003
Introduction
Global change is expected to have profound effects on
community composition and ecosystem functioning in
the Arctic. In the Alaskan Arctic, a warming trend has
already been detected in the surface temperatures
(Overpeck et al., 1997; Keyser et al., 2000; Serreze et al.,
2000), and predictions suggest that both winter and
summer temperatures will increase significantly in the
future (Cattle & Crossley, 1995; Rowntree, 1997; IPCC,
1998). Already, indications exist that the start of the
growing season in arctic ecosystems is shifting to earlier
dates in the spring (Myneni et al., 1997) and that shrubs
are increasing in abundance (Silapaswan et al., 2001;
Sturm et al., 2001).
Long-term ecosystem-scale experiments, in which the
environment is manipulated in controlled ways, are
important tools to facilitate an understanding of how
ecosystem functioning and species composition might
change in response to future climatic change. Longterm experiments are essential to assess ecosystem
differences in response times, buffering processes, feedbacks and their interactions (Likens, 1989; Magnuson,
1990). Long-term experiments by individual research
groups can, however, be performed only on limited
areas and on a limited number of different ecosystems.
In order to derive generalizations of responses across
larger geographical areas, combining data sets from
many regions and testing for general, regional and sitespecific validity of responses to experimental manipulations is necessary.
There have been several recent multisite comparisons
of experimental responses in arctic vegetation, using
various statistical approaches including meta-analysis
techniques, direct comparisons and correlation analyses
(Arft et al., 1999; Shaver & Jonasson, 1999; Cornelissen
et al., 2001; Dormann & Woodin, 2002). Much of this
work has focused on growth, flowering and/or biomass
changes in individual species and functional types. The
most important conclusions from these studies have
been that (i) nutrients limit production more strongly
than other factors, (ii) short-term responses to environmental factors, like warming, are often not sustained
and (iii) responses among species or functional types
are often negatively correlated. For example, when there
is a strong increase in shrub biomass and cover, the
biomass of lichens decreases (Cornelissen et al., 2001).
The present study is a multisite comparison of
responses in aboveground plant biomass to experimental manipulations of the environment in two arctic
regions, with several new features compared with
earlier studies of Dormann & Woodin (2002) and
Shaver & Jonasson (1999). First, we compare the
changes in biomass of individual plant types with the
changes in biomass of the whole vegetation. Second, we
compare the changes in whole vegetation and component plant types over longer time periods than in
previous studies. Third, besides looking for general
patterns, we also examine the main differences between
the responses of the two regions and the consequences
this may have for predicted effects of global change.
Fourth, we have access to all the individual samples for
each treatment and harvest of the sites used in this
study. The data availability allows a more detailed
and precise application of the modern statistical techniques for quantitative research synthesis, collectively
known as meta-analysis, compared with earlier studies
(Dormann & Woodin, 2002). With these meta-analysis
techniques, research results of independent studies can
be quantified and compared, and the statistical significance of the responses can be tested (e.g. Gurevitch &
Hedges, 1999; Gurevitch et al., 2001). We analyse responses in two arctic regions that have long-term data
sets of experimental treatments of ecosystems: Toolik
Lake, Alaska, and Abisko, Northern Sweden, (e.g.
Shaver & Jonasson, 1999), and that were forerunners
of the International Tundra Experiment (ITEX). In both
regions, different types of ecosystems were been
subjected to experimental warming, shading and
fertilization. We quantify the general responses observed in the results of the long-term experimental
treatments of arctic ecosystems, and also point out
how the ecosystems can differ in their responsiveness
between regions and among ecosystem types, thereby
allowing a more precise prediction of generalities of
responses to global change at different geographical
scales. Several potential mechanistic explanations for
the differences in responsiveness between sites and
regions are discussed.
Materials and methods
The data included in the analysis were obtained from
Arctic field studies north of the polar circle in the Toolik
Lake area and the Abisko area. Toolik Lake is located in
the northern foothills of the Brooks Range, Alaska
(68138 0 N, 149134 0 W, elevation 760 m). The area around
the lake has been studied intensively and is part of the
US network of Long-Term Ecological Research sites
(Hobbie et al., 1994; Shaver, 1996). The sites at Abisko
r 2003 Blackwell Publishing Ltd, Global Change Biology, 10, 105–123,
ECOSYSTEM EXPERIMENTS IN ALASKA AND SWEDEN
(68121 0 N, 18 0 49 0 E) are located between approximately
385 and 1150 m above sea level on the south shore of
Lake Torneträsk. The area has a long tradition of
environmental research and monitoring extending back
to 1913 (www.ans.Kiruna.se). In the experiments
performed in both regions, abiotic components of
expected climate change were manipulated, including
cloudiness (by shading), nutrient availability (by
fertilizer addition) and temperature (by sheltering).
We limited the analyses to treatments that were
common for Toolik Lake and Abisko, to test whether
similar treatments led to similar results in the two
different regions. Also, we limited the analyses to
treatments that had lasted for at least 3 years.
The data set combines the results of aboveground
biomass harvests in experiments performed by an
Abisko-Copenhagen group (two sites), an AbiskoSheffield group (one site) and a Toolik Lake group (five
sites). The results of the individual experiments have
been published previously on a site-by-site basis
(Chapin et al., 1995; Chapin & Shaver, 1996; Michelsen
et al., 1996; Shaver et al., 1996, 1998, 2001; Press et al.,
1998; Jonasson et al., 1999; Graglia et al., 2001a; Gough
et al., 2002; Richardson et al., 2002; Gough & Hobbie,
2003).
General information about the sites and details about
the harvesting protocols are given in Tables 1 and 2. All
data are from quadrat harvests of plots of varying sizes
(and quadrats of varying sizes, details in Table 2). The
data consisted of the aboveground biomass of individual species; the biomass of individual plant types or
the whole vegetation was calculated by adding up the
biomass of individual species. The experiments in
Toolik Lake have a block design, in which in most
cases four quadrats were harvested within each of the
three or four blocks. We calculated the mean values of
the quadrats within the individual blocks to avoid
pseudoreplication, and treated the blocks as the real
replicates.
In the Results and discussion sections, the sites will
be referred to by the name of the region (Toolik (To) or
Abisko (Ab)), the site name (either Paddus, Slåtta or
Forest for the Abisko sites, or Historic, Non-acidic, I–O
Wet Sedge, Sag Wet Sedge or Heath for the Toolik Lake
sites) followed by the length of treatment in years and
the treatment itself (Fert for fertilization, T for warming,
Sh for shading or Fert 1 T for fertilization 1 warming).
For example, ‘Abisko Forest 9 Fert 1 T’ stands for the
aboveground biomass harvest result obtained in Abisko
at the Forest site of the Sheffield group, after 9 years of
fertilization 1 warming treatment.
Besides using the harvest results for the whole
vegetation, we also analysed the biomass responses of
vascular and non-vascular plants separately, and
r 2003 Blackwell Publishing Ltd, Global Change Biology, 10, 105–123,
107
analysed the responses of the different plant types:
deciduous shrubs, evergreen shrubs, graminoids, forbs,
mosses and lichen species.
Meta-analysis
The responsiveness of the aboveground biomass to the
different treatments at the different sites was quantified
using
Xe
ð1Þ
L ¼ ln ;
Xc
where L is the responsiveness, and X is the mean value
of the characteristic analysed for the experimental (e)
and control (c) groups.
The advantage of using this measure of effect size
instead of also the commonly used ‘d-index’ (Gurevitch
& Hedges, 1999; Gurevitch et al., 2001) is that this
measure is easier to interpret in terms of changes in
biomass, whereas the d-index is also affected by the
variance of the response and therefore less easy to
interpret. The use of the natural logarithm instead of
the direct use of Xe/Xc has the advantage of linearizing
the metric (as L 5 ln Xeln Xc), thereby being less
sensitive to changes in a small control group, in
addition to providing a more normal sampling distribution in small samples. This normal approximation
is only valid if Xc/SEc is not too small (where SE is the
standard error); a value of about 3 is considered to be
necessary for the normal approximation (Gurevitch
et al., 2001). Low values of Xc/SEc appeared in the
analysis of the deciduous shrubs, graminoids and
especially the forbs, in which up to 30% of the data
had an Xc/SEc-value between 2 and 3. For the other
groups and for the totals of vascular and non-vascular
plants, all values of Xc/SEc were (much) larger than 3.
The confidence interval of L was calculated as
l ¼ L Ca=2 sðLÞ
ð2Þ
with sðLÞ being the square root of
s2 ðLÞ ¼
ðSDe Þ2 ðSDc Þ2 ðSEe Þ2 ðSEc Þ2
2 þ nc X
2 ¼ X
2 þ X
2 :
ne X
e
c
e
c
ð3Þ
Ca/2 is the two-tailed critical value of the standard
normal distribution, ne and nc are the number of
samples for experiment and control, respectively, and
SD and SE are the standard deviation and the standard
error, respectively. The responsiveness L was considered to represent a statically significant response if its
size is larger than the confidence interval (Gurevitch &
Hedges, 1999; Gurevitch et al., 2001).
We used the measure L to quantify the responsiveness to the treatments at the different sites. As we were
also interested in the overall effect of the treatments, we
also quantified the so-called ‘mean effect size’ for each
Fertilization
Shading
Fertilization
Warming
Shading
Fertilization
Fertilization
Warming
Shading
Fertilization
Warming
Shading
Fertilization
Warming
Fertilization
Warming
Shading
Fertilization
Treatments
1
2
1
2
1
2
1
10 g m2 yr1 NH4NO3 and 5 g m2 yr1 P2O5
50%
10 g m2 yr1 NH4NO3 and 5 g m2 yr1 P2O5
1 4 1C
50%
10 g m2 yr1 NH4NO3 and 5 g m2 yr1 P2O5
10 g m yr N, 2.6 g m yr P, 9 g m yr K, 0.8 g m yr Mg
1 2–4 1C
64%
10 g m2 yr1 N, 2.6 g m2 yr1 P, 9 g m2 yr1 K, 0.8 g m2 yr1 Mg
1 2–4 1C
64%
10 g m2 yr1 N as NH4NO3, 10 g m2 yr1 P and 12.6 g m2 yr1 as KH2PO4
1 2–4 1C
10 g m2 yr1 NH4NO3 and 5 g m2 yr1 P2O5
1 4 1C
50%
10 g m2 yr1 NH4NO3 and 5 g m2 yr1 P2O5
2
Treatment levels
16
14, 15
14, 15
12, 13
8, 9, 10, 11
4, 5, 6, 7
1, 2, 3
1, 2, 3
Key publications
Key publications: 1. Graglia et al. (2001a); 2. Jonasson et al. (1999); 3. Michelsen et al. (1996); 4. Richardson et al. (2002); 5. Press et al. (1998); 6. Potter et al. (1995); 7. Parsons et al.
(1995); 8. Shaver & Chapin (1991); 9. Shaver et al. (2001); 10. Chapin et al. (1995); 11. Chapin & Shaver (1996); 12. Gough et al. (2000); 13. Gough & Hobbie (2003); 14. Shaver et al.
(1998); 15. Shaver et al. (1996); 16. Gough et al. (2002).
Dry heath
Wet sedge
Sag Wet
Sedge
Heath
I–O Wet
Sedge
Non-acidic
tussock tundra
Wet sedge
Acidic tussock tundra
Historic
Non-acidic
Birch forest undergrowth
Forest
Dry high-altitude fell-field
at Mt Slåttatjåkka
Slåtta
Abisko-Sheffield
group
Toolik Lake
Mesic tree-line heath
at Paddustieva
Paddus
Abisko-Copenhagen
group
Ecosystem type
Site name
Region
Table 1 Sites and treatments from which data were included in this study
108 M . T . VA N W I J K et al.
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8
8
Fertilization
Shading
Heath
9, 16
6, 13
Shading
Fertilization
6, 13
Warming
Sag Wet Sedge
6, 13
Fertilization
I–O Wet Sedge
3, 9
Shading
4
3, 9
Warming
Fertilization
5, 9
5, 9
3, 9, 15, 20
Fertilization
Warming
Fertilization
5, 10
Shading
Non-acidic
Historic
Forest
5, 10
Warming
Shading
5, 10
5, 10
Warming
Fertilization
5, 10
Fertilization
Paddus
Slåtta
5, 10
Treatment
Length of
treatment (years)
Beginning of August
Beginning of August
End of July–beginning
of August
End of July–beginning
of August
End of July–beginning
of August
End of July–beginning
of August
End of July–beginning
of August
End of July–beginning
of August
End of July–beginning
of August
End of July–beginning
of August
End of July–beginning
of August
End of July–beginning
of August
End of July
End of July
End of July
End of July
End of July
End of July
Harvest timing
General information about harvest protocols of the different sites
Site name
Table 2
4
4
2
4
4
4
3
4
4
3
3
4
6
6
6
6
6
6
Number of
replicate plots
20 cm by 20 cm
20 cm by 20 cm
20 cm by 20 cm
20 cm by 20 cm
20 cm by 20 cm
20 cm by 20 cm
20 cm by 20 cm
20 cm by 20 cm
20 cm by 20 cm
20 cm by 20 cm (5 years); two
by 35 cm each (10 years)
20 cm by 20 cm (5 years); two
by 35 cm each (10 years)
20 cm by 20 cm (5 years); two
by 35 cm each (10 years)
20 cm by 20 cm (5 years); two
by 35 cm each (10 years)
20 cm by 20 cm (5 years); two
by 35 cm each (10 years)
20 cm by 20 cm (5 years); two
by 35 cm each (10 years)
10 cm by 10 cm
10 cm by 10 cm
20 cm by 20 cm
Quadrat sizes
subplots of 35 cm
subplots of 35 cm
subplots of 35 cm
subplots of 35 cm
subplots of 35 cm
subplots of 35 cm
ECOSYSTEM EXPERIMENTS IN ALASKA AND SWEDEN
109
110 M . T . VA N W I J K et al.
treatment. A method for this is given in Hedges et al.
(1999), in which the responses found for the different
sites are weighted according to their statistical ‘precision’: the more precise a response of a certain location,
the more heavily it weighs in the calculation of the
mean effect size.
The weighted mean, L , of the log response ratio was
calculated as
k
P
L
¼
$i Li
i¼1
k
P
i¼1
ð4Þ
;
$i
^2l Þ, and i is the sample index
where $i ¼ 1=ðsi þ s
^2l ¼
s
k
P
i¼1
Q ðk 1Þ
k
k
P
P
$i $2i = $i ;
i¼1
ð5Þ
i¼1
which denotes the estimate of the between-experiment
variance.
k
2
P
$
L
i
i
k
X
Q¼
$i ðLi Þ2 i¼1k
ð6Þ
P
i¼1
$i
i¼1
size was larger than the confidence interval (Hedges
et al., 1999).
Set-up of analysis
First, we analysed the changes in aboveground biomass
of all vascular plants, all non-vascular plants (i.e.
mosses and lichens) and the different plant growth
forms in relation to the locations, experimental sites and
treatments. We also analysed the inter-relationships
between the responses of the individual growth forms
by exploring the most important correlations with
principal component analysis (PCA), and a redundancy
analysis (RDA) in which the axes of the PCA are limited
to a linear combination of the explaining variables (e.g.
Jongman et al., 1995). This analysis was performed with
CANOCO 4.5 (Ter Braak & ŠMilauer, 2002). In this
analysis, each data point is a combination of the
responses found in the plant types and the whole
vegetation. Missing plant morphological types at a
certain site or treatment were treated as zeros, and
included in the analysis. The strongest correlations
found in the PCA and RDA analysis were explored in
more detail by pairwise plotting responsiveness of
growth form against growth form.
2
and oi 5 1/s . The standard error of L can be calculated
with
SEðL Þ
vffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi
8
"
!
#
u2
3>
u
k
P
>
u
>
>
$j $i
u6
>
$i
<
k
X
u6 1 7
j¼1
1 $i 2
7
u
¼ u6 k
7 1þ4
!2
df1 $i
u4 P 5>
k
>
P
i¼1
$j >
t
>
>
$j
:
j¼1
j¼1
ð7Þ
and the confidence intervals are
L Za=2 SEðL Þ m L þ Za=2 SEðL Þ:
ð8Þ
If the number of studies is lower than 20 (as in this
study for the individual treatments), the confidence
intervals calculated can be too narrow. In a worst-case
scenario, the actual probability content of the confidence intervals calculated with Eqn (8) can be as low
as 91% (Hedges et al., 1999). We therefore could only
calculate statistically correct actual confidence intervals
up to 90% in this analysis. We did this by calculating
the SEðL Þ values and multiplying them with the Za/2
value for 99% (as 99% times 91% is slightly more than
90%). L was only calculated when the number of
studies including a treatment was over six. As with the
responsiveness L, the mean effect size L was considered to represent a statistically significant response if its
Results
Treatment effects
The total aboveground vegetation biomass showed a
strong and significant positive response to fertilization
and fertilization 1 warming (Fig. 1a). The warming
treatment by itself also exhibited a significant positive
response, but this response was smaller and barely
significant. The combination of fertilization with warming did not, however, increase the response as
compared with fertilization alone. The aboveground
vascular plant biomass, which made up the main
biomass fraction, responded in a similar way as the
total plant biomass, except that the positive response to
warming was non-significant (Fig. 1b).
Among the vascular plant types, deciduous shrubs
and graminoids showed a strong positive response to
fertilization. In contrast, evergreen shrubs showed a
significant negative overall response to fertilization,
although this was caused entirely by a strong decline of
the biomass at Toolik Lake, contrasting with no or even
a small positive effect at Abisko. Forbs showed no clear
overall response to fertilization. The effects of the fertilization 1 warming treatments on the different vascular
plant groups were similar to the effects of fertilization
alone, except that the evergreen shrubs now show a
non-significant positive response. However, this is
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ECOSYSTEM EXPERIMENTS IN ALASKA AND SWEDEN
Fig. 1 Continued.
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111
112 M . T . VA N W I J K et al.
Fig. 1 Continued.
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ECOSYSTEM EXPERIMENTS IN ALASKA AND SWEDEN
113
Fig. 1 Aboveground biomass responsiveness (defined as ln (Xe/Xc)) ordered by treatment (separated by dashed line) and size of
responsiveness of total vegetation (a), vascular plants (b), non-vascular plants (c), deciduous shrubs (d), evergreen shrubs (e), forbs (f),
graminoids (g), lichens (h) and mosses (i) as a function of treatment. Numbers in the graphs are the mean effect size (L ) for each
treatment and between parentheses the standard error and the 90% confidence interval value. (Abbreviations: Ab 5 Abisko; To 5 Toolik
Lake; Pad 5 Paddus; Slat 5 Slåtta; For 5 Forest; Non-ac 5 Non-acidic; Hist 5 Historic; I&O–S 5 Inlet and Outlet Wet Sedge; Sag-S 5 Sag
Wet Sedge; T 5warming; F 5 fertilization; Sh 5 shading; the number represents the length of treatment in years.)
probably because the responsiveness for this treatment
and plant type could be calculated for only two Toolik
Lake sites, where evergreen plant species responded
negatively to fertilization, as opposed to six Abisko
sites where positive responses are visible. The warming
without fertilizer addition did not lead to any significant responses among the different vascular plant
types (Fig. 1d–g), and shading did not lead to significant effects in any group of the vascular plants.
The total non-vascular plants, as well as the moss and
lichen components, when tested separately (Fig. 1c, h,
i), showed a significant negative response to fertilization 1 warming. Fertilizer addition alone caused a
pronounced and significant decline in lichens (Fig.
1h), but a far from significant response in mosses,
which varied from strongly positive to strongly
negative across the sites (Fig. 1i). In the non-vascular
component as a whole, there was a strong negative,
although not significant, trend of decreasing biomass
response to fertilizer addition (Fig. 1c). The warming
and shading treatments, by contrast, led to small and
far from significant responses.
Responsiveness of vegetation types per site
The magnitudes and ranges of response at the different
sites were clearly related to the amount of control
aboveground biomass (Fig. 2a), with responsiveness
decreasing with increased control biomass (the dots
deviate less from the x-axis). The decreasing magnitude
of the biomass response with increasing biomass is also
shown in Fig. 2b, where the slope of the response–
treatment curves of the individual systems decreases
with increasing treatment biomass.
r 2003 Blackwell Publishing Ltd, Global Change Biology, 10, 105–123,
Fig. 2 Aboveground biomass responsiveness (defined as ln
(Xe/Xc)) of all treatments of total aboveground vegetation
biomass vs. control (a) and treatment biomass (b).
Multivariate analysis
In the analysis of the overall correlative structure of the
responses of the different plant growth forms, the first
PCA axis explained 49% of the total variance of the data
set. The axis was mainly determined by the negative
correlation between the responses of the deciduous
shrubs on the one hand, and the non-vascular species
(both mosses and lichens) together with less strongly
114 M . T . VA N W I J K et al.
Fig. 3 Principal component analysis (PCA) of the inter-relationships between responses in growth forms (a) and a redundancy analysis
(RDA) of the inter-relationships between responses of growth forms with explaining variables (b). The arrows in the PCA represent the
scores of the response variables (tot nonv 5 non-vascular species; Moss 5 moss species; Forbs 5 forb species; Evergr 5 evergreen shrubs;
Lichens 5 lichen species; Tot Biom 5 all species; Tot vasc 5 vascular species; Decid 5 deciduous shrubs; gramin 5 graminoid species).
The circles are the PCA scores of the individual measurements. The eigenvalues of the first two PCA axes are, respectively, 0.488 and
0.224, and the explained variance of the two axes combined is 71.2%, of which 48.8% is explained by the first axis. In the RDA, the
explaining variables, i.e. the sites, the treatments and the length of treatments (in years; represented by ‘length’) are in bold. Only the
RDA score of ‘length’ is drawn with an arrow as it is the only quantitative variable. Each qualitative variable represents a classification of
data points as belonging to that group or not (for example: the triangle ‘Abisko’ represents the correlative direction of sites in the Abisko
region; the correlative direction of sites in Toolik Lake is not shown, as it by definition is directly in the opposite direction from the
‘Abisko’ correlation). The response variables (see (a)) are in normal font. The eigenvalues of the RDA are 0.38 and 0.32, and the
explained variance in total is 70.1%, with the first axis contributing 37.8%. Both RDA axes have a P-value smaller than 0.01.
correlated evergreen shrubs on the other (Fig. 3a). The
response of graminoids was uncorrelated to these
groups and mainly determined the second PCA axis,
which explained around 22% of the variance present in
the data set.
In the RDA (in which the axes of the PCA are limited
to a linear combination of the explaining variables), the
correlative structure was very similar (Fig. 3b) to that
in the original PCA (Fig. 3a). Again the explained
variances of the first two axes were high ( 70%) and
statistically significant (Po0.01 for both axes). Fertilization (Fert) was positively correlated with the responsiveness in both graminoids and deciduous shrubs, and
thereby negatively correlated with the responsiveness
in the non-vascular group and the evergreen shrubs.
The length of treatment was strongly correlated with
the deciduous response, as was the classification of a
site as a Tussock site (only present in Toolik Lake).
However, this correlation was mainly caused by the
unique 20-year length of treatment at the Historic site
(an acidic tussock tundra site) in Toolik Lake. The
graminoid response was negatively correlated with
Tussock sites, but positively correlated with the Forest
site in Abisko, illustrating a much higher responsive-
ness there than in the Tussock sites. The shading
treatment was negatively correlated with the classification of a site as located in the Abisko region and the
graminoid response, illustrating that shading mainly
resulted in a negative response of the graminoids at
Toolik Lake (see also Fig. 1g).
Overall and regional correlations among plant growth
forms
When the strongest relationships of the multivariate
analyses were analysed in detail (Fig. 4), both the Toolik
Lake and Abisko data sets indicated a negative
correlation between the responses of mosses and lichens and the responses of deciduous shrubs (Fig. 4a, b).
The negative correlation between the evergreen and
deciduous shrubs found in both the PCA and the RDA
(Fig. 3a, b), was, however, mainly determined by the
results obtained in the Toolik Lake sites (Fig. 4c). This
was due to a pronounced growth response in deciduous shrubs in tussock tundra after fertilizer addition,
leading to the replacement of evergreen shrubs by
deciduous shrubs. At Abisko, however, both evergreen
r 2003 Blackwell Publishing Ltd, Global Change Biology, 10, 105–123,
ECOSYSTEM EXPERIMENTS IN ALASKA AND SWEDEN
115
Fig. 4 Scatter plots of aboveground biomass responses of the plant functional
types that showed the most pronounced correlative structure in Fig. 3. (a) lichens
vs. deciduous shrubs, (b) mosses vs. deciduous shrubs, (c) evergreen vs.
deciduous shrubs, (d) mosses vs. evergreen shrubs, (e) vascular plants vs.
evergreen shrubs.
and deciduous shrubs showed a positive response to
fertilization (see Fig. 1d, e), resulting in a positive
correlation between them. A similar difference between
regions also appeared in the correlation between the
responses of evergreen shrubs and mosses (Fig. 4d).
An interesting result was obtained when the overall
aboveground responses of vascular plant species were
plotted against the responses of evergreen shrubs (Fig.
4e). Note here that the response of the vascular plants is
not independent of the response of the evergreen
shrubs and one would expect a positive correlation.
However, the plot only showed a slightly positive
r 2003 Blackwell Publishing Ltd, Global Change Biology, 10, 105–123,
correlation between the vascular and evergreen response, and a clear distinction could be made between
the results found in Toolik Lake sites and Abisko sites.
When separate correlations were calculated for the
Toolik Lake sites and Abisko sites (Fig. 5), the difference
becomes even clearer. In Toolik Lake data points, there
was a clear negative relationship visible between
evergreen and deciduous aboveground biomass responsiveness (Fig. 5a). In several fertilization experiments in Toolik Lake, deciduous plant species showed a
large positive response whereas evergreen plant species
showed a negative response: deciduous plant species
116 M . T . VA N W I J K et al.
Fig. 5 Scatter plots of aboveground biomass responses of evergreen vs.
deciduous shrubs at Toolik Lake (a), evergreen shrubs vs. vascular plants at
Abisko (b) and Toolik Lake (c).
replace evergreen plant species. This led to an overall
slightly negative correlation between the responses of
evergreen species and the total vascular aboveground
biomass responses (Fig. 5c). In Abisko, however, both
evergreen and deciduous species showed a positive
response to fertilization (see Fig. 1d, e), resulting in a
strong positive correlation between aboveground vascular biomass responsiveness and the evergreen aboveground biomass responsiveness (Fig. 5b).
The shift towards dominance of deciduous shrubs
and decline of evergreen after fertilizer addition at
Toolik Lake is obvious when the average relative
contributions of the different plant types is compared
between control and fertilized plots (Fig. 6; the wet
sedge site is not included due to its different species
composition). Such a shift does not take place at
Abisko, except that graminoids increase in some of
the ecosystem types.
aboveground biomass responses between the two
locations. The analysis confirms quantitatively the
qualitative suggestions made previously (Shaver &
Jonasson, 1999; Graglia et al., 2001a) that deciduous
shrubs respond more strongly in the dominant vegetation types at Toolik Lake, Alaska than in the dominant
vegetation types above the treeline at Abisko, Sweden.
This has important implications for generalizations
about ecosystem responses to global change, because it
suggests that the Alaskan and Scandinavian arctic and
subarctic ecosystems may respond differently to global
change. It also shows the need to examine ecosystem
responses at finer levels than was done in the metaanalysis of Dormann & Woodin (2002), because
important information can be missed by lumping all
data into simple indices. We will first discuss the results
of this study by treatment, and then the correlations
between the biomass responses of the different plant
types.
Discussion
Our results demonstrate general patterns of response in
the long-term ecosystem experiments at Toolik Lake
and Abisko, and also show important differences in
Fertilization
Our analysis confirms previous results (e.g. Shaver &
Jonasson, 1999; Dormann & Woodin, 2002) showing
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ECOSYSTEM EXPERIMENTS IN ALASKA AND SWEDEN
Fig. 6 Relative contribution of each plant type to the total
vascular aboveground biomass in Abisko (a) and Toolik Lake (b)
for control plots and plots fertilized for more than 3 years. The
wet sedge sites in Toolik Lake were not included because of their
different plant-type composition.
that aboveground biomass responds stronger to fertilizer addition than to any other treatment. The fertilizer
addition led to an overall increase by 150% of the
control biomass, corresponding to L ¼ 0:41 in Fig. 1a,
and to differences in aboveground responses among the
different plant types (Figs 1, 4 and 6). At both Toolik
Lake and Abisko, the biomass of non-vascular species
(i.e. mosses and lichens) responded negatively to
several years of fertilization. Cornelissen et al. (2001)
showed that in milder arctic and subartic sites, such as
Toolik Lake and Abisko, any treatment that caused an
increase of vascular aboveground biomass tended to
cause a decline in macrolichen biomass, whereas this
relationship was absent in the more open high arctic
and arctic–alpine systems. Jonasson (1992) also found
that the biomass of lichens and mosses increased with
fertilization in open vegetation, and declined as the
vegetation closed, similar to the reduction in moss
cover observed along gradients of increased canopy
cover in wet sedge meadows (Tenhunen et al., 1992).
Robinson et al. (1998) showed that moss growth
increased in response to fertilization in a high arctic
polar semidesert with an open canopy.
Our results also showed clear differences in the
responses of the different plant morphological types to
r 2003 Blackwell Publishing Ltd, Global Change Biology, 10, 105–123,
117
fertilization. Deciduous shrubs and graminoids were
the only plant types that showed an overall significant
increase in aboveground biomass, although the forbs
also showed a clear trend of increasing biomass.
Evergreen shrubs showed a trend of increased aboveground biomasses with fertilization in most of the
Abisko sites, whereas in the Toolik Lake sites, they
showed a clear trend of decrease (Fig. 5). In the Toolik
Lake area, with the exception of the wet sedge sites, the
proportion of deciduous shrubs increased from 28% up
to 57% (Fig. 6), whereas the proportion of deciduous
shrubs in Abisko of around 13% did not change.
However, the increase in deciduous shrubs at Toolik
Lake only took place on tussock tundra and not at the
heath site. The Toolik Lake Heath site had a low
proportion of the control biomass as deciduous shrubs,
comparable to the Slåtta site at Abisko. As at Abisko, at
the Toolik Lake Heath site graminoids instead increased strongly, from 1% to 10%.
The response of deciduous shrubs in the tussock
tundra at Toolik Lake is mainly caused by the responsiveness to fertilizer addition of the deciduous
shrub Betula nana. In the acidic tussock tundra sites in
Toolik Lake, aboveground biomass and cover of B. nana
had increased strongly (Shaver et al., 2001), whereas in
the heath-like systems at Abisko B. nana was relatively
unresponsive to fertilizer addition (Graglia et al., 1997;
Jonasson et al., 1999). At Toolik Lake, B. nana increased
both its wood and leaf production, and grew taller and
faster than other species, and came to dominate the
upper canopy entirely, and thereby caused the decrease
in the biomass of evergreen species and other vascular
plants.
Deciduous plant species in general respond more
strongly to fertilization than evergreen species (Chapin,
1980; Aerts & Chapin, 2000). Deciduous plant species
have a higher turnover rate of tissues than evergreen
plant species and in general higher potential nutrient
uptake rates. In deciduous-plant-dominated systems,
nutrient cycling is therefore much faster than in evergreen-plant-dominated systems. When nutrient sources
are increased, nutrient uptake and plant growth of
deciduous species can increase dramatically. Through
positive feedbacks on nutrient cycling, caused by leaf
litter that is relatively easily decomposable, deciduous
plant species are often capable of maintaining dominance, even after fertilization is stopped. Compared
with deciduous plant species, evergreen species are
much less plastic and have lower turnover rates of
tissues and rates of nutrient uptake, and therefore
respond less to fertilization (Berendse, 1994; Aerts,
1995; Cornelissen, 1996; Cornelissen et al., 1996).
The negative response of the non-vascular species is
probably caused by an inhibition in growth by a
118 M . T . VA N W I J K et al.
combination of shading from the dense upper canopy
of B. nana and burial by vascular plant litter. Also, nonvascular plants directly receive nutrient-containing
throughfall from the vascular plant canopy besides
forming the location where litter mineralization takes
place, and are therefore less likely to be nutrient-limited
and more sensitive to light than the vascular component
of the community. Non-vascular plants can also be
vulnerable to osmotic effects of direct contact of
fertilizers on photosynthetic tissues, although probably
mosses and lichens respond too slowly for this to be the
major explanation; it is more likely that the combination
of shading and litter burial caused the decline in nonvascular plant abundance.
Warming and shading
Increased temperature treatments had a much less
pronounced effect on aboveground vegetation biomass
than fertilization. Although clear trends emerged from
the analyses, e.g. increases in the aboveground biomass
of vascular plants, deciduous shrubs and graminoids,
and decreases in lichen biomass, none of these effects
were statistically significant. Also, we discerned no
clear added effect on aboveground biomass when
warming was combined with fertilizer addition, although
measurements of soil nutrients suggest that warming in
combination with fertilization can increase nutrient
availability even further (Chapin et al., 1995). The
warming response – or rather the lack of response in
some ecosystem types – is intriguing. Note, however,
that although when all the sites were taken together
there were no significant responses, individual sites did
respond significantly. For example, the response at
Paddus and Slåtta sites was the expected one, with
significantly increased vascular plant biomass after
warming (Fig. 3 in Jonasson et al., 1999) and generally
also with increased nutrient accumulation in the
biomass, suggesting increased nutrient mineralization
and plant uptake after warming. Also, the biomass
increased strongly at the Toolik Wet Sedge sites, at least
after 6 years (Fig. 1b). However, after 13 years, mosses
instead seem to ‘take over’. At the Abisko Forest site, it
appears that the total biomass remained essentially
unchanged because graminoids increased and replaced
the other groups and, hence, cancelled out most
biomass responses. In contrast, the tussock tundra
sites in Toolik Lake seem to be insensitive to warming
(Fig. 1b).
A number of possible explanations exist for this
rather small responsiveness to warming. First, it could
be that the warming plots are too small to produce
effective soil warming, thereby leading to the effect that
soil temperature may constrain the response to air
temperature. This constraint can lead to continued
limitation in nutrient uptake, and thereby to limited
responses (Dormann & Woodin, 2002). Second, air
warming leads to soil cooling along natural gradients
(Callaghan & Jonasson, 1995), because of a feedback
from increased leaf area index (LAI) to lower soil
temperatures. Third, arctic species have up to 90%
biomass below ground (Dennis & Johnson, 1970;
Hobbie & Chapin, 1998; Van Wijk et al., 2003b).
Warming leaves might not contribute significantly to
overall carbon gain. Finally, passive warming by greenhouses or open top chambers can result in moisture
stress, particularly for mosses. Positive warming effects
might therefore be compensated for by moisture stress.
Callaghan et al. (1999) showed that the moss Hylocomium
splendens increased its growth in response to warming
along a natural latitudinal gradient, but decreased its
growth in response to warming in open top chambers.
These issues are still part of our experimental uncertainty and imply that for reliable predictions of the
effects of future climate change, we need to know more
about the feedbacks between air warming, LAI development and soil temperature.
Shading did not lead to any changes in aboveground
plant biomass. The reductions of incident radiation
were on the order of 50–60%, corresponding to values
experienced by understorey plants in open woodlands
adjacent to the tundra (Michelsen et al., 1996). Reductions in radiation expected due to increased cloudiness
will probably be less severe, and therefore effects of
shading on plant biomass may only be expected over
very long time periods, although leaf traits may
respond on a shorter time scale (Graglia et al., 1997).
It is also an important factor for subcanopy species,
mosses and other low-growing species, when shifts in
the dominance of overtopping vegetation occur; see for
example the earlier discussion of the effects of increased
B. nana dominance in tussock tundra at Toolik Lake.
Although shading did not lead to changes in aboveground biomass in the Historic tussock tundra site at
Toolik Lake, it did substantially reduce production after
9 years (Chapin & Shaver, 1996). This could suggest that
arctic ecosystems may eventually respond to reduced
light availability, but that this response will be much
slower and less pronounced than the response to
nutrients, perhaps because of the large carbohydrate
concentrations characteristic of arctic plants.
Correlations between responses of plant types
Because nutrients, light and space are limiting factors in
ecosystems, resulting in competition among individual
plants, aboveground biomass responses of one plant
type to environmental perturbations are often correr 2003 Blackwell Publishing Ltd, Global Change Biology, 10, 105–123,
ECOSYSTEM EXPERIMENTS IN ALASKA AND SWEDEN
lated with contrasting responses of other plant types.
This has happened in the acidic tussock tundra in
Toolik Lake, where fertilizer addition has stimulated
the growth of B. nana and caused a decline of other
plant types and total shift in dominance (Fig. 6), and
also in the Abisko Forest site where graminoids dominated the fertilized plots. The pronounced differences
in the changes in dominance structure after fertilizer
addition at Toolik Lake and Abisko sites illustrate that
aggregating results of ecological experiments into one
number expressing the responsiveness of arctic and
subarctic systems over whole regions is a very coarse
way of treating data, because even obvious differences
may be masked. Within that single number, there is a
wide range of different responses, which, if ignored, do
not allow us to predict reliably as to what will happen
to these systems under climate change. Also, there are
clear differences within the regions: in the dry Heath
sites of Toolik Lake, graminoids respond most strongly
(Gough et al., 2002), a response much more similar to
the responses found at Abisko Forest and Paddus. At
the more detailed plant-type level, this analysis shows
that there are relatively few common responses across
the two regions and these ‘individualistic responses’ of
arctic ecosystems show the need to examine particular
ecosystems besides looking for general patterns.
Site and regional differences in biomass response: possible
explanations and implications
The most important difference between the vegetation
responses of the Toolik Lake and Abisko regions was
the strong increase in biomass of the deciduous shrubs
in Northern Alaska with fertilization. B. nana began to
dominate tussock tundra after 6 years of fertilizer
addition and from that moment onwards, outcompeted
most of the other plant species. In Northern Sweden,
such a strong increase in dominance by one plant
species or plant type did not take place, thereby leading
to a much more evenly distributed positive biomass
response of the vascular plant types to fertilizer
addition.
This difference in response of B. nana between the
Toolik Lake and Abisko regions is still not satisfactorily
explained. In the control plots of the Slåtta sites at
Abisko, B. nana was present in relatively low densities,
but at the Paddus site, B. nana was present in significant
amounts. Jonasson et al. (1999) suggest that it could be
due to differences in the effects of fertilization on soil
nutrient availability. Soil N and P solutions increased
10- to 100-fold in the tussock tundra at Toolik Lake,
whereas the levels after several years of fertilizer
addition at Paddus and Slåtta in Abisko were nonsignificant (N) or only slightly increased (P) (Chapin
r 2003 Blackwell Publishing Ltd, Global Change Biology, 10, 105–123,
119
et al., 1995; Jonasson et al., 1999). This difference in soil
nutrient levels could have resulted from greater
drainage through the rocky non-permafrost soils of
the Abisko region, whereas soil drainage is much more
limited in the highly organic permafrost soils of the
Toolik Lake region. This difference in nutrient availability would be expected to cause a stronger deciduous-shrub response at Toolik Lake because of the
strong growth response to nutrients in this functional
type (Chapin, 1980). Another consistent difference is the
greater investment in herbivore-deterring phenolics by
B. nana at Abisko in response to environmental changes
(Graglia et al., 2001b). A large investment in phenolics
at Abisko might restrict the ability to grow rapidly in
response to increased nutrient supply. Recent work on
branching patterns and secondary growth of B. nana at
Abisko (M.S. Bret-Harte and G.R. Shaver, unpublished
results) indicates that B. nana in unfertilized plots at
Abisko produces fewer branches and has thinner stems
for a given branch age than at Toolik Lake (Bret-Harte
et al., 2001, 2002), and that one reason for the slower
response to fertilizer addition at Abisko may be a
slower rate of addition of new meristems than at Toolik
Lake. In the Forest site at Abisko, the tree birch B.
pubescens ssp. Tortosa, which is known to dominate
heath ecosystems with natural climatic warming, may
be the species that allows this ecosystem to be responsive to nutrient addition (Sonesson & Hoogesteger,
1983).
Another possible explanation for the differences in
B. nana responsiveness between sites could be related to
snow depth. As stated before, B. nana came to dominate
the fertilized, acidic tussock tundra in Toolik Lake
through its ability to form long shoots (Bret-Harte et al.,
2001, 2002), permitting the shrubs to overtop the cooccurring, lower-growing species. This was possible
because snow cover is deep enough to protect the
canopy from damage during winter. At the Heath sites
at both Abisko and Toolik Lake, snow cover is
shallower, and increased vertical growth would expose
the shrubs to adverse winter conditions, causing
dieback of branches exposed above the snow surface
(Callaghan et al., 1997). Hence, B. nana cannot assume
the same dominance as in more snow-protected
ecosystem types. Indeed, B. nana naturally dominates
on fine textured soils of high soil moisture content and
medium deep (450 cm) to deep snow, where it forms a
second canopy stratum above the dwarf shrubs and the
herbaceous plants as in the tussock tundra. In contrast,
it grows mixed with other species in a single vascular
plant stratum at sites with shallow snow (Jonasson,
1982). In the Heath sites at both Abisko and Toolik
Lake, graminoids with basal rather than with apical
meristems and a canopy that dies back during winter
120 M . T . VA N W I J K et al.
showed the strongest response. This suggests that part
of the different responses to fertilization was due to
differences in local rather than regional conditions,
which constrained the growth of species with an
overwhelmingly vertical growth of perennial structures
(Jonasson, 1992). Indeed, regardless of whether the
strongly responding species were shrubs or graminoids, the effect on co-occurring species when the
canopy closed was similar with a reduction of the
subcanopy species, either both vascular plants or
cryptogams as in the tussock tundra or low-growing
cryptogams as in the Heath and Forest sites.
The differences in the vegetation responses between
the two regions cannot be explained by differences in
the experimental methods and sampling protocols.
Differences in plot and quadrat sizes should affect
sample variances at the two sites, but should have little
effect on the overall means (Goldsmith et al., 1986).
Although the current data set has its limitations (see
also the discussion in the subsection Current limitations
of the data set), the responsiveness of the different
vegetation types differs greatly, with clear unambiguous
statistical significance, and the measurements represent
truly strong differences in ecosystem behaviour.
The differences between the responses of the dominant vegetation types of the Toolik Lake region, i.e.
tussock tundra systems, and that of the Abisko region,
i.e. heath systems, may have important implications for
ecosystem development under expected patterns of
global change. If global change enhances nutrient
availability, according to the results obtained in these
experiments, one would expect a large deciduous shrub
response in the Alaskan Arctic, as observed during the
last 25 years of pronounced warming (Sturm et al.,
2001), whereas in the Swedish Arctic the response will
be less extreme. However, if these regional differences
in biogeochemical cycling and biodiversity are actually
site- or ecosystem-specific rather than regional-specific,
further analyses of joint data sets including more
regions and sites are needed in order to establish the
scales of responses. To refine the predictions of global
change effect in the Arctic, both the regional- and
ecosystem-related differences in responsiveness need to
be accounted for and incorporated in models of element
cycling over the whole pan-Arctic, like terrestrial
ecosystem model (TEM) (McGuire et al., 2000), and in
calculations of the potential change in the biodiversity
(Sala et al., 2000). Otherwise, the predictions of these
models will have a limited connection to reality.
Current limitations of the data set
Although only based on a limited data set, the analysis
suggests that common vegetation types at both Toolik
Lake and Abisko have more similar responses than
dissimilar vegetation types within regions: for example,
the response of the heath system in the Toolik Lake
region was more similar to the responses of the heath
systems of the Abisko region than to those of the tussock
tundra systems in the Toolik Lake region itself. Besides
resulting in only a few significant responses when all
sites are lumped across both regions, this would mean
that for a thorough analysis of the effects of global
change on arctic vegetation, much larger data sets with
many different vegetation types in many regions are
needed. The data set we used is biased strongly towards
the dominant vegetation types in the two regions, i.e.
tussock tundra in Toolik Lake and heath-like systems
above the treeline in Abisko, and can therefore be used
to predict qualitatively what the general responses will
be at both regions, and also how the regions will differ
in their response. For more accurate predictions covering the full range of vegetation types, however, more
detailed data sets must be compiled.
Also, the manipulations of the experiments analysed
in this study have their limitations in the context of
predictions for the possible effects of climate change on
arctic vegetation. For example, the effective warming of
the ecosystems was taking place in summer, but
scenarios of climate change imply that winter warming
will dominate (Cattle & Crossley, 1995; Rowntree, 1997).
Also, the fertilizer applications were unrealistically
high for simulations of increased nutrient availability
following warming, and other environmental variables
may co-vary with climate, e.g. CO2 (Tissue & Oechel,
1987; Gwynn-Jones et al., 1997; Moorhead & Linkins,
1997), UV-B (Gwynn-Jones et al., 1997; Gehrke, 1999;
Johnson et al., 2002) and precipitation (Parsons et al.,
1995; Potter et al., 1995; Wookey et al., 1995; Press et al.,
1998). For these reasons, the results provide some
insight into responses to climate change, but interpretations need to be made with care. However, the results
clearly demonstrate the individualistic nature of the
environmental and species-compositional controls on
community biomass at different sites.
Another point is that, although aboveground biomass
can provide important insights into the response of
arctic ecosystems to global change, it is only part of the
story. Belowground responses of plants (Wookey et al.,
1994; Van Wijk et al., 2003b) and micro-organisms
(Johnson et al., 2002), reproductive responses (Wookey
et al., 1993, 1995; Molau & Shaver, 1997; Arft et al., 1999),
and physiological and phenological responses (Wookey
et al., 1993; Oberbauer et al., 1998; Pop et al., 2000; Van
Wijk et al., 2003a) can all interact and result in long-term
shifts in community composition that cannot be
detected on the time scale of the experiments that have
been analysed here, i.e. on average 10 years, with the
r 2003 Blackwell Publishing Ltd, Global Change Biology, 10, 105–123,
ECOSYSTEM EXPERIMENTS IN ALASKA AND SWEDEN
Historic tussock tundra site of Toolik Lake as the
extreme with 20 years. Even the Historic tussock tundra
site of Toolik Lake exhibited transient behaviour after
15 years (Shaver et al., 2001) and continues to show
major changes (G.R. Shaver, personal communication).
Conclusions
The results of this study demonstrate that the aboveground plant biomass responses found in the long-term
ecosystem experiments in Toolik Lake, Alaska, and
Abisko, Northern Sweden, exhibit some general patterns in both locations, and also some important
differences. In both locations, aboveground plant
biomass responded most strongly to nutrient addition.
Deciduous and graminoid plants showed a particularly
strong positive response to fertilization. Another general pattern was the strong decrease of the biomass of
mosses and lichens as the biomass of vascular plants
increased. An important difference between the two
regions was the smaller positive aboveground biomass
response of deciduous shrubs in Abisko as compared
with Toolik Lake. Whereas in Toolik Lake B. nana
increased its dominance and replaced many of the other
plant types, in Abisko all vascular plant types increased
in abundance without major shifts in relative abundance. The differences between the responses of the
dominant vegetation types of the Toolik Lake region,
i.e. tussock tundra systems, and that of the Abisko
region, i.e. heath systems, may have important implications for ecosystem development under expected patterns of global change. However, there were also large
site-specific differences within each region. These response patterns show the need for analyses of joint data
sets from many regions and sites in order to uncover
common responses to changes in climate across large
arctic regions from regional or local responses.
Acknowledgements
This research was funded by US National Science Foundation
Grant DEB0087046, with contributions from Copenhagen Global
Change Initiative (COGCI). Funding for the experimental work
of which the data were used in this study came from the US
National Science Foundation, The Danish Natural Science
Research Council, The Swedish Environmental Protection Board,
The Nordic Council of Minister’s Nordic Arctic Research
Programme, the Swedish Royal Academy of Sciences and UK
NERC (Arctic Terrestrial Ecology Programme) and ESRC (Global
Environmental Change Programme).
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