Content uploaded by José L. Espinar
Author content
All content in this area was uploaded by José L. Espinar on Jul 22, 2018
Content may be subject to copyright.
REVIEW AND
SYNTHESIS Ecological impacts of invasive alien plants: a meta-analysis of
their effects on species, communities and ecosystems
Montserrat Vila
`,
1
* Jose
´L. Espinar,
1
Martin Hejda,
2
Philip E. Hulme,
3
Vojte
ˇch Jaros
ˇı
´k,
2,4
John L. Maron,
5
Jan Pergl,
2,6
Urs Schaffner,
7
Yan
Sun
7
and Petr Pys
ˇek
2,4
Abstract
Biological invasions cause ecological and economic impacts across the globe. However, it is unclear whether
there are strong patterns in terms of their major effects, how the vulnerability of different ecosystems varies
and which ecosystem services are at greatest risk. We present a global meta-analysis of 199 articles reporting
1041 field studies that in total describe the impacts of 135 alien plant taxa on resident species, communities and
ecosystems. Across studies, alien plants had a significant effect in 11 of 24 different types of impact assessed.
The magnitude and direction of the impact varied both within and between different types of impact.
On average, abundance and diversity of the resident species decreased in invaded sites, whereas primary
production and several ecosystem processes were enhanced. While alien N-fixing species had greater impacts
on N-cycling variables, they did not consistently affect other impact types. The magnitude of the impacts was
not significantly different between island and mainland ecosystems. Overall, alien species impacts are
heterogeneous and not unidirectional even within particular impact types. Our analysis also reveals that by the
time changes in nutrient cycling are detected, major impacts on plant species and communities are likely to have
already occurred.
Keywords
Biological invasions, bottom-up effects, diversity, ecological complexity, ecosystem functioning, effect size,
exotic species, island, N-fixing, weeds.
Ecology Letters (2011) 14: 702–708
INTRODUCTION
Given the increasing pace of global change, it is becoming more
important than ever to understand how human activities are altering
biodiversity and ecosystem functioning (Tylianakis et al. 2008). A key
driver of change is the invasion of ecosystems by alien species, many
of which attain sufficiently high abundance to influence biodiversity.
In contrast to the extensive literature and syntheses on the processes
leading to biological invasions (Jeschke & Strayer 2005; LePrieur et al.
2008; Van Kleunen et al. 2010a,b), a robust framework to understand
impacts has yet to be developed (Parker et al. 1999). For example,
various invasive plants are known to decrease local plant species
diversity (Vila` et al. 2006; Gaertner et al. 2009; Hejda et al. 2009;
Powell et al. 2011), increase ecosystem productivity and alter the rate
of nutrient cycling (Liao et al. 2008; Ehrenfeld 2010), and hence
impact upon ecosystem services and human well-being (Pejchar &
Mooney 2009). However, while there are a growing number of studies
reporting impacts of alien plants, we still lack broad quantitative
syntheses of how impacts vary depending on the attributes of
recipient ecosystems and of the invaders themselves (Levine et al.
2003). This absence of a broad-scale assessment limits our ability to
generalize and predict when and where impacts might be most
deleterious.
To address this key issue in invasion biology, we undertake a
quantitative synthesis on the effects of alien plant species on a wide
range of ecological response variables using a meta-analytical
approach (Rosenberg et al. 2000). Meta-analysis provides an oppor-
tunity to explore heterogeneity among studies and identify large-scale
patterns across species and geographic regions (Steward 2010). Our
goal was to determine how the magnitude and direction of alien
species impacts vary across levels of ecological complexity. An alien
plant species that reaches a high abundance and dominates an
ecosystem will potentially influence the performance of individual
resident species and their population dynamics (Vila` & Weiner 2004),
and as a consequence, it will have both direct and indirect effects on
plant community structure and ecosystem functioning (Levine et al.
2003). In this study, we assess how impacts on species compare with
those on community properties and ecosystem processes.
1
Estacio
´n Biolo
´gica de Don
˜ana (EBD-CSIC), Avda. Ame
´rico Vespucio s ⁄n, Isla de
la Cartuja, E-41092 Sevilla, Spain
2
Institute of Botany, Academy of Sciences of the Czech Republic, CZ-252 43
Pru
˚honice, Czech Republic
3
The Bio-Protection Research Centre, PO Box 84, Lincoln University, Canterbury,
New Zealand
4
Department of Ecology, Faculty of Science, Charles University, Vinic
ˇna
´7,
CZ-128 01 Prague, Czech Republic
5
Division of Biological Sciences, University of Montana, Missoula, MT 59812,
USA
6
Institute of Ecology and Evolution, University of Bern, CH-3012 Bern,
Switzerland
7
CABI Europe-Switzerland, 2800 Dele
´mont, Switzerland
*Correspondence: E-mail: montse.vila@ebd.csic.es
Nomenclature as in Weber (2003).
Ecology Letters, (2011) 14: 702–708 doi: 10.1111/j.1461-0248.2011.01628.x
2011 Blackwell Publishing Ltd/CNRS
We focus on two aspects that have for long been pivotal in the
biological invasion literature. First, do N-fixing alien species exert
greater ecological impacts than non-N-fixing species? Although there
has been considerable research examining how species traits might
influence plant invasiveness (Daehler 2003; Pys
ˇek & Richardson 2007;
Van Kleunen et al. 2010a,b), the effect of particular plant traits on the
type of impact is unclear with the exception of studies reporting
N-fixing alien species having a significant impact on N-cycling
(Vitousek 1990; Ehrenfeld 2003, 2010; Liao et al. 2008). As strong
impacts on nutrient cycling subsequently affect plant performance
(e.g. plant resource allocation, plant competitive ability, plant
resistance to herbivory, etc.) and hence community structure, we
assumed N-fixing plants to have greater community impacts than
non-N-fixing species.
Second, we assess whether island ecosystems are more vulnerable to
impacts than mainland ecosystems. Islands often support large
regional pools of alien species (Lonsdale 1999; Pys
ˇek et al. 2010)
and are often considered to be highly impacted by invaders (but see
Diez et al. 2009). Certainly, introduced predators can trigger strong
trophic cascades on islands and these indirect effects can importantly
influence primary production and plant community structure (Croll
et al. 2005). However, doubts have been expressed about the relative
vulnerability of island ecosystem to the impacts of alien plants (Sax &
Gaines 2008) but as yet no formal assessment of the vulnerability of
island ecosystems to impacts has been undertaken.
METHODS
Literature search
We used several data sources to gather quantitative evidence from the
literature on the ecological impacts of alien plants upon: (1) individual
plant and animal species performance, (2) characteristics of the
recipient community and (3) ecosystem processes (see Table 1 for
definitions and examples of these measures). We searched for relevant
articles on the ISI Web of Knowledge (http://apps.isiknowledge.com)
database on 11 March 2009 with no restriction on publication year,
using the following search term combinations: (plant invader OR
exotic plant OR alien plant OR plant invasion*) AND (impact* OR
effect*) AND (community structure* OR diversity* OR ecosystem
process* OR competition*). As the next step, we also screened the
reference lists from all retrieved articles for other relevant publica-
tions. As some of those articles were reviews (e.g. Levine et al. 2003)
that were also based on the Ôgrey literatureÕ, we achieved a reasonably
good coverage of the literature on impacts of alien plants, not
restricted to that indexed in Web of Science.
We examined each article to assess their potential for meeting the
selection criteria for inclusion in the review. The main selection
criterion required studies to compare quantitatively any ecological
pattern or process in both invaded and uninvaded plots in natural or
semi-natural ecosystems. We did not include studies conducted in
agricultural systems as this topic has been reviewed elsewhere (Vila`
et al. 2004). This resulted in an initial set of 515 articles from which the
following criteria for data inclusion were adopted:
(1) Replicated field studies that were either observational (i.e.
comparing non-manipulated invaded and uninvaded sites) or
experimental (i.e. removal or addition of target plants) were
included where they explicitly mentioned the identity of the alien
plant taxon causing impact. We only selected studies focusing on
the impact of a single alien species rather than that of
multispecies alien assemblages. We also excluded all studies
addressing the effects of expanding or colonizing native species
such as Ôshrub encroachmentÕ(the review of Liao et al. 2008
included many studies on native species).
(2) Where the same article examined different alien species, several
ecosystems and ⁄or more than one response variable, we
considered each of these separately as they represented different
examples of ecological impacts. A possible criticism is that using
all measures represents a form of pseudo-replication in the meta-
analysis. However, the same approach has previously used in
meta-analysis (Liao et al. 2008; Rey-Benayas et al. 2009). The
influence of pseudo-replication was tested with a randomly
selected single effect size per article for impact types with large
sample sizes (see next section).
(3) When a response variable was measured at different times (e.g.
sampling at different seasons or years), we made an informed
decision on whether to take the mean value across times or
consider each measure as independent. In some instances, we
only used the final measurement (see Criterion 5).
Table 1 Summary of the ecological impacts due to alien plant species classified by
levels of ecological complexity, impact types and response variables examined in the
meta-analysis
Level Impact type Variables
Plant species Fitness Seed set, germination rate, seedling
establishment, survival, mortality ())
Growth Increase in size of whole plants or
plant parts
Plant
communities
Production Biomass, NPP
Abundance Plant number, density, cover
Diversity Alpha diversity, richness, evenness
Animal species Fitness Egg production, adult emergence,
survival, mortality ())
Growth Increase in size of whole animals
at any life stage
Animal
communities*
Production Biomass
Abundance Density, visits, counts
Diversity Alpha diversity, richness
Behaviour Grazing, predation, mobility,
activity
Ecosystems Soil OM Soil organic matter
C pools Soil, litter, plant C
N pools Soil, litter, plant N
N available NO
3
and ⁄or NH
4
in soil
N mineralization N mineralization rate
N nitrification N nitrification rate
P pools Soil, litter, plant P
C⁄N Soil, litter, plant C ⁄N
Microbial activity Activity of soil bacteria, fungi
or enzymes
pH pH
Litter
decomposition
Litter decomposition rate
Salinity Soil Na, electrical conductivity
Soil moisture Soil water content
As low mortality indicates high survival, the sign of the effect sizes of the former
variable was changed ()).
*Although they refer mostly to animals, they also include impacts on micro-
organisms (e.g. bacteria, fungi and protozoa).
Review and Synthesis Ecological impacts of invasive alien plants 703
2011 Blackwell Publishing Ltd/CNRS
(4) There were also studies conducted on the same species in
similar ecosystems but at different locations. We made an
informed decision whether to consider studies as independent if
locations were from clearly distinct regions (e.g. different
islands, different countries) and considered the effects across
locations if they represented similar ecosystems under the
influence of the same environmental conditions. If the study
manipulated other ecological factors (e.g. N-addition, distur-
bance levels) only results from non-manipulated plots were
considered.
(5) When the study investigated the effects of different degrees of
invasion (e.g. heavily vs. less invaded sites) and different
residence times (i.e. old vs. recent invasions) we only considered
the putative largest contrast. That is, we examined differences
between the least invaded sites (i.e. often uninvaded) and the
most invaded sites, or differences between uninvaded sites and
sites with the longest time since invasion.
Data extraction
A total of 199 articles representing 1041 cases of invasion across 135
taxa (all at the species level except four hybrids and one subspecies)
met our criteria (Appendix S1). In the vast majority of studies,
invaded sites had high alien abundance and although the measures of
plant abundance were not always given, the study sites were usually
described as having high or > 50% cover. Furthermore, the alien
species considered were in many cases explicitly described as invasive
in the study region. Thus, our results summarize the impact of
invasive alien plant species.
Among the alien plant species investigated, perennial herbs (344
cases) and trees (202 cases) were more often represented than other
life-forms and there were only 18 N-fixing species (156 cases). Almost
half of the studies (478) have been conducted in temperate regions
and one-third (340) in grasslands. Twenty-four per cent of studies
(245) were conducted on islands.
In most cases, field assessments of impact were based on
comparisons of several ecological variables in long-standing invaded
vs. uninvaded sites nearby. Only 14% of the studies involved
manipulative experiments (i.e. removal or addition of species). The
impact variables measured most frequently concerned N pools (103
cases), plant species diversity (136), animal abundance (94) and plant
biomass and production (90). Individual response variables were
related to species performance, community structure and ecosystem
processes in invaded and uninvaded plots. These levels of ecological
complexity were further classified into 24 types of impact (Table 1).
Many impact types contain different variables and sometimes the
same variable has been estimated by using different methods.
However, using different variables to estimate effect sizes within a
category is intrinsic to meta-analysis (e.g. Cardinale et al. 2006; Winfree
et al. 2009; Van Kleunen et al. 2010b). Although the inclusion of
heterogeneous data has prompted some criticism of meta-analytical
methods, they provide the opportunity to quantitatively identify large-
scale patterns (Steward 2010) as the effect size is a unit-free metric
that accounts for sample size bias (see below).
We extracted mean, statistical variation (usually SE or SD) and
sample size values for invaded and uninvaded plots for each response
variable. These data were extracted directly from tables or from graphs
using the
DATATHIEF II
software (B. Thumers; http://www.datat-
hief.org) or, in some cases, also by measuring mean and statistical
variation ÔmanuallyÕusing a ruler. For other studies, we obtained data
directly from the corresponding authors.
Response ratios
For each pair of invaded (i) and uninvaded (ni) sites per case study, we
calculated HedgesÕdas a measure of effect size. HedgesÕdis an
estimate of the standardized mean difference that is not biased by
small sample sizes (Rosenberg et al. 2000). From each pair of mean
values (X) the individual effect size dwas calculated as:
d¼
XiXni
SJ;
where Sis the pooled standard deviation and Ja weighting factor
based on the number of replicates (N) per treatment. Jwas calculated
as:
J¼13
4Nni þNi2ðÞ1:
The variance of HedgesÕd,Vd was calculated as:
Vd ¼Nni þNi
Nni Niþd2
2ðNni þNiÞ:
HedgesÕdis a unit-free index which ranges from )¥to +¥and
estimates the size of the impact and its direction. As in classical
statistical analysis, the highest effect sizes are from those studies
showing large differences between invaded and uninvaded plots when
the plots have low variability. Zero dvalues signify no difference in the
variable measured between invaded and uninvaded plots; positive and
negative dvalues imply a general trend following invasion for an
increase and decrease, respectively. HedgesÕdcalculations and
statistical analysis were conducted with the MetaWin v2.1 Software
(Rosenberg et al. 2000).
For each impact type, we calculated the weighted mean effect size
(d
+
) across the sample of studies with information on the relevant
response variable. To test whether d
+
differed significantly from zero
(i.e. no change with invasion), we assessed whether the bias-corrected
95% bootstrap-confidence interval (CI) of d
+
did not overlap zero
based on 999 iterations (Rosenberg et al. 2000). We also tested
whether effects sizes across studies were homogeneous, using the
Q
total
statistic based on a chi-squared test (Q
t
hereafter). A significant
Q
t
indicates that the variance among effect sizes is greater than that
expected by sampling error alone (i.e. effect sizes are not equal across
studies). The mean percentage of change in a response variable was
estimated as (e
R+
)1) ·100 where R
+
is the weighted mean response
ratio (R) across studies (Rosenberg et al. 2000). The natural logarithm
of Ris calculated as:
ln R¼ln Xi
Xni
!
:
For categorical comparisons (e.g. N-fixing vs. non-N-fixing), we
examined P
random
values associated to Q
between
statistic (Q
b
hereafter),
which describe the variation in effect sizes that can be ascribed to
differences between categories. We also tested whether the remaining
within-group heterogeneity (Q
w
) was significant using a chi-squared
test. Data were analysed using random-effects models which are
704 M. Vila
`et al. Review and Synthesis
2011 Blackwell Publishing Ltd/CNRS
preferable in ecological data synthesis because their assumptions are
more likely to be satisfied (Rosenberg et al. 2000).
Many studies reported data on the effect of the same alien species
on different response variables or in different ecosystems. To avoid
pseudoreplication, we also ran the analyses with a randomly selected
single effect size per article, for three response variables with the
largest sample sizes: plant diversity, animal abundance and N pools.
The mean effect sizes for each of these types of impact were similar to
those obtained for all studies and the bias-corrected 95% bootstrap-
confidence interval (CI) overlapped between the whole dataset and the
reduced dataset (Appendix S2). As a consequence, we felt confident
to include all the data in our analyses. The inclusion of all case studies
enabled us to screen for differences in impact within levels of
ecological complexity in a manner similar to the amalgamated meta-
analysis performed by Rey-Benayas et al. (2009) or Liao et al. (2008).
In studies on ecological impact, there might be a bias against
publishing negative results and studies with larger sample sizes might
have more power to detect significant impacts. We examined
standardized effect sizes of the raw data to test these potential biases
and found that they were slightly negatively (Spearman r=)0.099)
but significantly (P= 0.001) associated with sample size. This might
suggest that studies with small sample sizes are slightly more likely to
be published when they found bigger differences between invaded and
uninvaded sites (Rosenberg et al. 2000). However, a plot of the effect
sizes against the sample size revealed a funnel-shaped distribution of
the data points (Appendix S3), as would be expected in the absence of
a sampling bias (Palmer 1999).
Following Rosenthal (1979), we estimated the fail-safe number, that
is, the number of studies that would have to be added to change the
results of the meta-analysis from significant to non-significant, to be
37 689. As this value is larger than 5N+ 10 = 5215 where
N= number of case studies in our dataset, we are confident that
the observed results can be treated as a reliable estimate of the true
effect (Rosenberg 2005). Moreover, a plot of the standardized effect
sizes against the normal quantiles revealed a straight line (Appen-
dix S3) indicating that the effect sizes are normally distributed (Wang
& Bushman 1998). Overall, this indicates that there was only a mild
publication bias unlikely to change the overall meaning of the results.
RESULTS
Averaged across all studies, there was considerable variability in the
effect sizes (Q
t
= 2257.36, d.f. = 1039, P< 0.0001) ranging over 5
orders of magnitude. Mean effect sizes differed significantly among
the impact types examined (Q
b
= 316.78, d.f. = 23, P= 0.001) not
only in magnitude but also in direction (Figs 1 and 2; Appendix S4).
The mean effect size within impact types was also heterogeneous
(Q
w
= 1940.57, d.f. = 1016, P< 0.0001; see Appendix S4 for Q
t
of
each impact type). This result indicates that even for particular impact
types the magnitude and direction of the effect size varied significantly
across studies. For 11 of the 24 impact types examined, the CI of the
mean effect size overlapped zero (Figs 1 and 2). Therefore, for these
impact types, we could not support the hypothesis that the variables
examined changed uniformly with invasion, due to heterogeneity in
the direction of effects found for different studies (Appendix S4).
Alien plants significantly reduced fitness and growth of resident
plant species by 41.7 and 22.1%, respectively, and changed plant
community structure by decreasing speciesÕabundance (43.5%) and
diversity (50.7%). However, total community production increased by
56.8% following invasion (Fig. 1a). Alien plants also significantly
decreased animal speciesÕfitness by 16.5% and abundance by 17.3%
(Fig. 1b). For the other variables related to animal species perfor-
mance and animal community structure the CI of the mean effect size
overlapped zero. Thus, although the trend was towards a decrease in
the other variables with invasion, the direction of effect sizes were not
uniform across studies.
With regard to ecosystem impacts, alien plants enhanced microbial
activity by 32.3%, available N (53.7%), N, P and C pools (22.1, 19.7
and 11.6%, respectively), and decreased pH (3%), but for the impacts
on the other variables, the CI of the mean effect size overlapped zero
(Fig. 2; Appendix S4). For instance, on average, invasion decreased
litter decomposition by 15.6% but there was a significant heteroge-
neity among studies (Q
t
= 24.14, d.f. = 12, P= 0.02) with almost as
–1.5 –1 –0.5 0 0.5 1 1.5 2
–
2
–1.5 –1 –0.5 0 0.5 1 1.5 2–2
Effect size
Effect size
(a)
(b)
Plant fitness (25, 0, 0)
Plant diversity (113, 2, 21)
Plant abundance (40, 0, 3)
Plant growth (22, 0, 10)
Plant production (32, 0, 58)
Animal fitness (14, 0, 4)
Animal growth (8, 0, 3)
Animal abundance (61, 1, 32)
Animal production (15, 0, 7)
Animal diversity (29, 1, 15)
Animal behaviour (11, 1, 10)
Figure 1 Mean effect size (HedgesÕd) of differences between alien plant species
impacts to (a) plant species and communities and (b) animal species and
communities. The bars around the means denote bias-corrected 95%-bootstrap
confidence intervals. A mean effect size is significantly different from zero when its
95% confidence interval do not bracket zero. Positive mean effect sizes indicate
that the invaded plots had on average greater values for variables describing a
particular impact type. The sample sizes with HedgesÕd< 0, HedgesÕd= 0 and
HedgesÕd> 0 are given next to the bars.
–
2–1 0 1 234 5
C/N (18, 0, 21)
N nitrification (3, 0, 8)
N pools (36, 2, 65)
P pools (17, 2, 31)
N available (15, 0, 32)
Microbial activity (5, 0, 9)
N mineralization (10, 1, 15)
Soil OM (10, 1, 15)
Salinity (10, 0, 9)
C pools (26, 2, 35)
Litter decomposition (7, 0, 6)
pH (55, 2, 5)
Soil moisture (14, 1, 15)
Figure 2 Mean effect size (HedgesÕd) of differences between ecosystem impacts
with indication of significant differences between N-fixing (closed triangles) and
non-N-fixing (open triangles) alien plant species. Otherwise as in Figure 1.
Review and Synthesis Ecological impacts of invasive alien plants 705
2011 Blackwell Publishing Ltd/CNRS
many studies showing increases as decreases in litter decomposition
due to invasion (Fig. 2).
Compared with non-N-fixing species, the alien N-fixing species
increased the impact on N pools and N nitrification significantly
(d
+
= 1.94 vs. d
+
= 0.19; d
+
= 1.83 vs. d
+
= 0.02, respectively).
By contrast, while N-fixing species decreased C ⁄N, non-N-fixing
species increased the value of this variable (d
+
=)0.65 vs. d
+
= 0.10).
The impact of N-fixing alien plants was not significantly different
from that of non-N-fixing species for any of the other impact type
addressed in this study (Table 2).
There were no significant differences in the mean effect sizes
between studies conducted on islands and on the mainland (Table 2).
DISCUSSION
Our analysis provides rigorous evidence that alien plant species exert
significant impacts on many ecological variables. However, the
magnitude and direction of these impacts vary among different levels
of ecological complexity. In absolute terms, impacts on plant species
and communities were substantial whereas those on nutrient cycling
were relatively minor. This indicates that by the time impacts on
nutrient cycling are detected, plant species and communities are likely
to have already been affected by invasion. Nevertheless, the causal
links between plant community and ecosystem impacts remain largely
unexplored (Levine et al. 2003). There are only a few experiments that
teased apart the direct impacts on nutrient cycling from the indirect
impacts via changes in community structure (but see Belnap et al.
2005; Allison et al. 2006 for exceptions).
Our analysis also shows that alien plants have bottom-up impacts
on higher trophic levels, although on average these effects are of lower
magnitude than those within the same trophic level. The effect of alien
plants on taxa at higher trophic levels might depend on the degree of
their dependence on alien plants as a food resource (de Groot et al.
2007; Gerber et al. 2008) but indirect effects may occur when alien
plants increase habitat heterogeneity (Pearson 2009). Studies which
have simultaneously investigated the impacts of alien plants on
primary producers and on other trophic levels are scarce (Valtonen
et al. 2006; de Groot et al. 2007; Gerber et al. 2008) and more are
needed to understand how frequent feedback impacts occur across
trophic levels.
One of the most striking findings of our study is that alien plant
species reduced local plant species diversity and increased plant
production of the invaded community. This is contrary to what
diversity-ecosystem functioning experiments would predict and
supports the importance of sampling effects in the patterns observed
in such studies (Cardinale et al. 2006). Experimental work has shown
that a strong invader can essentially reverse the positive diversity–
productivity relationship in a manner consistent to what we have
found (Zavaleta & Hulvey 2004; Maron & Marler 2008). Our analysis
suggests that alien plant invasions may result in a sampling effect
where ecosystem production is driven by the addition of a single
highly productive species, even if overall species diversity declines.
A prediction which our analysis did not support is generally greater
impact of alien N-fixing species compared with alien non-N-fixing
species. Seminal work on the impact of Myrica faya, an N-fixing
introduced tree in Hawaii, on early stages of primary succession
(Vitousek et al. 1987) motivated the idea that alien N-fixing species
can exert large impacts on recipient ecosystems. Current evidence
suggests that compared with non-N-fixing species, N-fixing alien
species more strongly affect N and C cycling (Liao et al. 2008), but our
results indicate that no such differences are found for impacts on
other ecosystem processes or on community structure.
Another unexpected result is that we did not find greater impacts on
islands than on mainland ecosystems. The generally accepted
assumption that islands are more threatened by plant invaders than
the mainland is largely drawn form the fact that their floras are
proportionally more dominated by alien species and ecosystems are
more disturbed (DÕAntonio & Dudley 1994). Indeed, compared with
corresponding mainland ecosystems, islands often harbour more alien
species (Lonsdale 1999) and individual alien plants can often be more
widespread (Gimeno et al. 2006). This might suggest greater impacts
but our results indicate that the magnitude of the impact is not
significantly greater than in mainland ecosystems and imply that
invasion success does not necessarily translate into greater impacts at a
local scale (Parker et al. 1999).
Our results summarize the impacts of strongly dominating alien
plant species prone to cause changes in species, communities or
ecosystems (Vila` et al. 2010). The data available did not allow us to
determine how impacts might increase as a function of alien plant
abundances. This seems to be a major gap in our understanding of
biological invasion regarding whether the relationship between alien
plant abundance and impact is saturating, sigmoid or linear (Ehrenfeld
Table 2 Heterogeneity between (Q
b
) the impact of N-fixing and non-N-fixing alien
plant species and for studies conducted in islands and in mainland ecosystems with
indication of sample sizes and P-values (significant results are in bold)
Level Impact type
N-fixing Insularity
Q
b
N
yes
,N
no
PQ
b
N
yes
,N
no
P
Plant species Fitness 1.31 8, 18 0.29 0.77 2, 23 0.46
Growth – – – 1.08 8, 46 0.37
Plant
communities
Production 7.25 4, 86 0.06 4.74 13, 77 0.14
Abundance 1.92 11, 42 0.17 0.66 4, 49 0.45
Diversity 3.60 15, 121 0.09 1.03 25, 111 0.34
Animal species Fitness – – – – – –
Growth – – – – – –
Animal
communities*
Production 0.00 4, 18 1 0.45 3, 19 0.46
Abundance 4.45 11, 83 0.06 0.00 34, 60 0.97
Diversity 0.12 3, 42 0.74 1.19 12, 33 0.30
Behaviour – – – – – –
Ecosystems Soil OM 1.31 8, 18 0.29 0.34 3, 23 0.60
C pools 2.62 7, 56 0.14 0.46 3, 19 0.46
N pools 28.21 25, 78 0.001 0.04 34, 69 0.87
N available 1.96 13, 34 0.22 0.17 10, 37 0.71
N mineralization 0.19 7, 18 0.71 0.08 4, 21 0.82
N nitrification 8.35 3, 8 0.01 0.96 2, 9 0.35
P pools 4.33 13, 37 0.06 4.25 12, 38 0.10
C⁄N 3.99 7, 32 0.05 0.73 20, 19 0.42
Microbial
activity
0.86 3, 11 0.39 – – –
pH 0.14 11, 51 0.77 0.00 25, 37 0.96
Litter
decomposition
0.01 2, 11 0.97 2.30 3, 10 0.27
Salinity 0.11 5, 14 0.75 0.17 4, 15 0.69
Soil moisture 0.23 3, 17 0.66 0.73 3, 17 0.41
Significance values of Q
b
are based on randomization tests. Empty cells denote the
analysis could not be conducted due to the lack of replicates.
*Although they refer mostly to animals, they also include impacts on micro-
organisms (e.g. bacteria, fungi and protozoa).
706 M. Vila
`et al. Review and Synthesis
2011 Blackwell Publishing Ltd/CNRS
2010). It is of interest to know whether there are thresholds or
ÔbreakpointsÕwhere impacts of alien plants may not scale linearly with
their abundances, and how this relationship may vary among invading
species (Andreu et al. 2009) and the spatial scale of study (Powell et al.
2011). The experimental studies examining this relationship found it
to either scale linearly (Maron & Marler 2008) or not at all (Meffin
et al. 2010) with invader abundance. Thus, additional experiments are
needed before we can make generalizations about the nature of this
relationship (Parker et al. 1999; Levine et al. 2003). This topic remains
at the core of whether the impact of alien species is related to their
ecological success.
In conclusion, our analyses have highlighted that alien plants pose
significant impacts at the species, community and ecosystem level.
Current understanding of invasive plant impacts is restricted to
relatively few dominant alien species (Pys
ˇek et al. 2008). However,
possibly because our database had different representation of alien
plant life forms and ecosystems, the magnitude of the impacts was
very variable and even for a given impact type, the direction of the
ecological change was context-dependent. Our quantitative approach
to value impacts could be further developed as the basis for scoring
alien species and recipient ecosystems for risk assessment of invasions
(Nentwig et al. 2009). We hope this article helps to re-invigorate this
area of research by highlighting the association among impacts at
several levels of ecological complexity and also the links between
invasion success and invasion impacts.
ACKNOWLEDGEMENTS
Discussions with J.M. Levine, C.M. DÕAntonio, J.S. Dukes, K. Grigulis
and S. Lavorel at a European Science Foundation Workshop held in
Barcelona in 2001 inspired portions of this work. We thank I. Parker
and two anonymous referees for comments on an early draft of this
article. Funding was provided by PRATIQUE (KBBE-212459) and
STEP (244090-STEP-CP-FP) of the EU 7FP; the Spanish Ministerio
de Ciencia e Innovacio´n project RIXFUTUR (CGL2009-7515) and
MONTES (CSD2008-00040); the Junta de Andalucı
´a RNM-4031; the
Czech Science Foundation (206 ⁄09 ⁄0563); the Academy of Sciences
of the Czech Republic Projects No. AV0Z60050516 and
MSM0021620828; the Ministry of Environment of the Czech
Republic project LC06073 and the Swiss National Science Foundation
(NCCR ÔPlant SurvivalÕ). P.P. acknowledges the support by Praemium
Academiae award from AS CR and J.P. from SCIEX.
AUTHOR CONTRIBUTIONS
MV, PP, US and PEH designed research; MV, JLE, MH, JP and YS
prepared the database; MV and VJ analysed data; and MV, PP, VJ,
JLM, US and PEH wrote the article.
REFERENCES
Allison, S.D., Nielsen, C. & Hughes, R.F. (2006). Elevated enzyme activities in soils
under the invasive nitrogen-fixing tree Falcataria moluccana.Soil Biol. Biochem., 38,
1537–1544.
Andreu, J., Vila`, M. & Hulme, P.E. (2009). An assessment of stakeholder per-
ceptions and management of alien plants in Spain. Environ. Manag., 43, 1244–
1255.
Belnap, J., Phillips, S.L., Sherrod, S.K. & Moldenke, A. (2005). Soil biota can change
after exotic plant invasion: does this affect ecosystem processes? Ecology, 86,
3007–3017.
Cardinale, B.J., Srivastava, D.S., Duffy, J.E., Wright, J.P., Downing, A.L., Sankaran,
M. et al. (2006). Effects of biodiversity on the functioning of trophic groups and
ecosystems. Nature, 443, 989–992.
Croll, D.A., Maron, J.L., Estes, J.A., Danner, E.M. & Byrd, G.V. (2005). Introduced
predators transform subarctic islands from grassland to tundra. Science, 307, 1959–
1961.
Daehler, C.C. (2003). Performance comparisons of co-occurring native and alien
invasive plants: Implications for conservation and restoration. Annu. Rev. Ecol.
Evol. Syst., 34, 183–211.
DÕAntonio, C. & Dudley, T. (1994). Biological invasions as agents of change on
islands versus mainlands. In: Islands: Biological Diversity and Ecosystem Function (eds
Vitousek, P.M., Loope, L. & Andersen, H.). Springer-Verlag, Berlin, pp. 103–
121.
Diez, J.M., Williams, P.A., Randall, R.P., Sullivan, J.J., Hulme, P.E. & Duncan, R.P.
(2009). Learning from failures: testing broad taxonomic hypotheses about plant
naturalization. Ecol. Lett., 12, 1174–1183.
Ehrenfeld, J.G. (2003). Effect of exotic plant invasions on soil nutrient cycling
processes. Ecosystems, 6, 503–523.
Ehrenfeld, J.G. (2010). Ecosystem consequences of biological invasions. Annu. Rev.
Ecol. Evol. Syst., 41, 59–80.
Gaertner, M., Breeyen, A.D., Hui, C. & Richardson, D.M. (2009). Impacts of alien
plant invasions on species richness in Mediterranean-type ecosystems: a meta-
analysis. Progr. Phys. Geogr., 33, 319–338.
Gerber, E., Krebs, C., Murrell, C., Moretti, M., Rocklin, R. & Schaffner, U. (2008).
Exotic invasive knotweeds (Fallopia spp.) negatively affect native plant and
invertebrate assemblages in European riparian habitats. Biol. Cons., 141, 646–
654.
Gimeno, I., Vila`, M. & Hulme, P.E. (2006). Are islands more susceptible to plant
invasion than continents? A test using Oxalis pes-caprae in the western Mediter-
ranean. J. Biogeogr., 33, 1559–1565.
de Groot, M., Kleijn, D. & Jogan, N. (2007). Species groups occupying different
trophic levels respond differently to the invasion of semi-natural vegetation by
Solidago canadensis.Biol. Cons., 136, 612–617.
Hejda, M., Pys
ˇek, P. & Jaros
ˇı
´k, V. (2009). Impact of invasive plants on the species
richness, diversity and composition of invaded communities. J. Ecol., 97, 393–
403.
Jeschke, J.M. & Strayer, D.L. (2005). Invasion success of vertebrates in Europe and
North America. Proc. Natl Acad. Sci. U.S.A., 102, 7198–7202.
LePrieur, F., Beauchard, O., Blanchet, S., Oberdorff, T. & Brosse, S. (2008). Fish
invasions in the worldÕs river systems: when natural processes are blurred by
human activities. PLoS Biol., 6, 404–410.
Levine, J.M., Vila`, M., DÕAntonio, C.M., Dukes, J.S., Grigulis, K. & Lavorel, S.
(2003). Mechanisms underlying the impact of exotic plant invasions. Proc. R. Soc.
London, Serie B, 270, 775–781.
Liao, C., Peng, R., Luo, Y., Zhou, X., Wu, X., Fang, C. et al. (2008). Altered
ecosystem carbon and nitrogen cycles by plant invasion: a meta-analysis. New
Phytol., 177, 706–714.
Lonsdale, W.M. (1999). Global patterns of plant invasions and the concept of
invasibility. Ecology, 80, 1522–1536.
Maron, J.L. & Marler, M. (2008). Effects of native species diversity and resource
additions on invader impact. Am. Nat., 172, S18–S33.
Meffin, R., Miller, A.L., Hulme, P.E. & Duncan, R.P. (2010). Experimental intro-
duction of the alien weed Hieracium lepidulum reveals no significant impact on
montane plant communities in New Zealand. Diversity Distrib., 16, 804–815.
Nentwig, W., Ku
¨hnel, E. & Bacher, S. (2009). A generic impact-scoring system
applied to alien mammals in Europe. Cons. Biol., 24, 302–311.
Palmer, A.R. (1999). Detecting publication bias in meta-analysis: a case study of
fluctuating asymmetry and sexual selection. Amer. Nat., 154, 220–233.
Parker, I.M., Simberloff, D., Lonsdale, W.M., Goodell, K., Wonham, M., Kareiva,
P.M. et al. (1999). Impact: toward a framework for understanding the ecological
effects of invaders. Biol. Invas., 1, 3–19.
Pearson, D.A. (2009). Invasive plant architecture alters trophic interactions by
changing predator abundance and behaviour. Oecologia, 159, 549–558.
Pejchar, L. & Mooney, H.A. (2009). Invasive species, ecosystem services and hu-
man well-being. Trends Ecol. Evol., 24, 497–504.
Powell, K.I., Chase, J.M. & Knight, T.M. (2011). A synthesis of plant invasion
effects on biodiversity across spatial scales. Am. J. Bot., 98, 539–548.
Review and Synthesis Ecological impacts of invasive alien plants 707
2011 Blackwell Publishing Ltd/CNRS
Pys
ˇek, P. & Richardson, D.M. (2007). Traits associated with invasiveness in alien
plants: where do we stand? In: Biological Invasions, Ecological Studies 193 (ed.
Nentwig, W.). Springer-Verlag, Berlin & Heidelberg, pp. 97–125.
Pys
ˇek, P., Richardson, D.M., Pergl, J., Jaros
ˇı
´k, V., Sixtova´, Z. & Weber, E. (2008).
Geographical and taxonomic biases in invasion ecology. Trends Ecol. Evol., 23,
237–244.
Pys
ˇek, P., Bacher, S., Chytry
´, M., Jaros
ˇı
´k, V., Wild, J., Celesti-Grapow, L. et al.
(2010). Contrasting patterns in the invasions of European terrestrial and fresh-
water habitats by alien plants, insects and vertebrales. Glob. Ecol. Biogeogr., 19,
319–331.
Rey-Benayas, J.M., Newton, A.C., Diaz, A. & Bullock, J.M. (2009). Enhancement of
biodiversity and ecosystem services by ecological restoration: a meta-analysis.
Science, 325, 1121–1124.
Rosenberg, M.S. (2005). The file-drawer problem revisited: a general weighted
method for calculating fail-safe numbers in meta-analysis. Evolution, 59, 464–468.
Rosenberg, M.S., Adams, D.C. & Gurevitch, J. (2000). Metawin: Statistical Software for
Meta-Analysis. Sinauer Associates, Sunderland, MA.
Rosenthal, R. (1979). The ‘‘file-drawer problem’’ and tolerance for null results.
Psychol. Bull., 86, 638–641.
Sax, D.F. & Gaines, S.D. (2008). Species invasions and extinction: the future of
native biodiversity on islands. Proc. Natl Acad. Sci. U.S.A., 105, 11409–11497.
Steward, G. (2010). Meta-analysis in applied ecology. Biol. Lett., 6, 78–81.
Tylianakis, J.M., Didham, R.K., Bascompte, J. & Wardle, D.A. (2008). Global
change and species interactions in terrestrial ecosystems. Ecol. Lett., 11, 1–13.
Valtonen, A., Jantunen, J. & Saarinen, K. (2006). Flora and lepidoptera fauna
adversely affected by invasive Lupinus polyphyllus along road verges. Biol. Cons.,
133, 389–396.
Van Kleunen, M., Dawson, M., Schaepfer, D., Jeschke, J.M. & Fischer, M. (2010a).
Are invaders different? A conceptual framework of comparative approaches for
assessing determinants of invasiveness. Ecol. Lett., 13, 947–958.
Van Kleunen, M., Weber, E. & Fischer, M. (2010b). A meta-analysis of trait dif-
ferences between invasive and non-invasive plant species. Ecol. Lett., 13, 235–
245.
Vila`, M. & Weiner, J. (2004). Are invasive plant species better competitors than
native plant species? Evidence from pair-wise experiments. Oikos, 105, 229–238.
Vila`, M., Williamson, M. & Lonsdale, M. (2004). Competition experiments in alien
weeds with crops: lessons for measuring invasive impact? Biol. Invas., 6, 59–69.
Vila`, M., Tessier, M., Suehs, C.M., Brundu, G., Carta, L., Galanidis, A. et al. (2006).
Local and regional assessment of the impacts of plant invaders on vegetation
structure and soil properties of Mediterranean islands. J. Biogeogr., 33, 853–861.
Vila`, M., Basnou, C., Pys
ˇek, P., Josefsson, M., Genovesi, P., Gollasch, S. et al.
(2010). How well do we understand the impacts of alien species on ecosystem
services? A pan-European cross-taxa assessment. Front. Ecol. Environ., 8, 135–
144.
Vitousek, P.M. (1990). Biological invasions and ecosystem processes: towards an
integration of population biology and ecosystem studies. Oikos, 57, 7–13.
Vitousek, P.M., Walker, L., Whiteaker, L., Mueller-Dombois, D. & Matson, P.
(1987). Biological invasion by Myrica faya alters ecosystem development in Ha-
waii. Science, 238, 802–804.
Wang, M.C. & Bushman, B.J. (1998). Using the normal quartile plot to explore
meta-analytic data sets. Psychol. Methods, 3, 46–54.
Weber, E. (2003). Invasive Plant Species of the World: A Reference Guide to Environmental
Weeds. CAB International Publishing, Wallingford.
Winfree, R., Aguilar, R., Va´zquez, D.P., LeBuhn, G. & Aizen, M.A. (2009). A meta-
analysis of beesÕresponses to anthropogenic disturbance. Ecology, 90, 2068–2076.
Zavaleta, E.S. & Hulvey, K.B. (2004). Realistic species losses disproportionately
reduce grassland resistance to biological invaders. Science, 306, 1175–1177.
SUPPORTING INFORMATION
Additional Supporting Information may be found in the online
version of this article:
Appendix S1 List of studies for meta-analysis on alien plant species
impact on species, communities and ecosystems.
Appendix S2 Total heterogeneity (Q
t
) with indication of sample size,
effect sizes (d
+
) and 95% CI for three impact types of alien plant
species when considering all case studies (whole) and only one study
per article (reduced).
Appendix S3 MetaWin output for (a) normal quartile plot and (b)
funnel-plot of effect sizes (HedgesÕd) of the raw data vs. sample size.
Appendix S4 Total heterogeneity (Q
t
) with indication of P-values,
mean effect sizes (d
+
), degrees of freedom (d.f.) and 95% CI for
different impact types of alien plant species.
As a service to our authors and readers, this journal provides
supporting information supplied by the authors. Such materials are
peer-reviewed and may be re-organized for online delivery, but are not
copy-edited or typeset. Technical support issues arising from
supporting information (other than missing files) should be addressed
to the authors.
Editor, Elsa Cleland
Manuscript received 11 April 2011
First decision made 16 December 2010
Manuscript accepted 12 April 2011
708 M. Vila
`et al. Review and Synthesis
2011 Blackwell Publishing Ltd/CNRS
