Are there any consistent predictors of invasion success?
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Biol Invasions (2008) 10:483–506
DOI 10.1007/s10530-007-9146-5
ORIGINAL PAPER
Are there any consistent predictors of invasion success?
Keith R. Hayes Æ Simon C. Barry
Received: 4 September 2006 / Accepted: 26 July 2007 / Published online: 16 August 2007
Ó Springer Science+Business Media B.V. 2007
Abstract This article summarises the results of supported within plants but were either not
49 studies that together test the significance of 115 supported by independent data sets or contraindi-
characteristics in 7 biological groups: birds, finfish, cated by datasets within or across other biological
insects, mammals, plants, reptiles/amphibians and groups. Climate/habitat match is the only charac-
shellfish. Climate/habitat match, history of inva- teristic that is consistently significantly associated
sive success and number of arriving/released with invasive behaviour (in this case exotic range
individuals are associated with establishment suc- size) across biological groups. This finding, how-
cess in at least four independent data sets, both ever, is not supported by two or more independent
within and across biological groups, and none are data sets within any of the biological groups
contraindicated by other studies. In the introduced- examined here. Within plants there are a suite of
invasive control group, two species level charac- characteristics, predominately associated with
teristics—taxon and geographic range size—were reproduction, that are significantly associated with
significantly associated with establishment success a range of invasion metrics, predominately abun-
across two biological groups. These characteristics, dance in the invaded range. Nonef of these
however, were not supported by independent data characteristics, however, are supported across any
sets, or were contraindicated by these data sets, other biological groups. We note the confounding
within the biological groups examined here. In the effects of phylogeny, residence time and propagule
introduced-native control group, three species level pressure and suggest that site- and taxa-specific
characteristics—geographic range size, leaf surface analysis will provide further useful insights.
area and fertilisation system (monoecious, her-
maphroditic or dioecious)—were consistently Keywords Invasion Establishment
Consistent Prediction Risk assessment
K. R. Hayes (&)
Introduction
CSIRO Marine and Atmospheric Research,
GPO Box 1538, Hobart, TAS 7001, Australia
e-mail: keith.hayes@csiro.au Successful biological invasions involve complex
interactions between the invading species and the
S. C. Barry
physical and biological characteristics of the recipient
CSIRO Mathematical and Information Sciences,
GPO Box 664, Canberra, ACT 2601, Australia environment. These interactions are made complex
e-mail: simon.barry@csiro.au by the case-specific characteristics of the introduction
123484 K. R. Hayes, S. C. Barry
event and a variety of ecological phenomena includ- continued to follow the literature trail until no further
ing: positive feedback mechanisms (Noble 1989); relevant publications were found.
Allee effects (Dennis 2002); behavioural changes We deliberately excluded studies that postulate,
(Holway and Suarez 1999); genetic variability (Hold- but do not statistically test, correlates of establish-
gate 1986); adaptation and phenotypic plasticity ment or invasion success (Baker 1965; Arthington
(Rosecchi et al. 2001, Richards et al. 2006); the and Mitchell 1986; Bruton 1986; Bazzaz 1986;
potential lag between establishment and invasion Ehrlich 1989; Lodge 1993; Morton 1996; Arthington
(Sakai et al. 2001); and, cryptogenic species (Carlton et al. 1999; Kailola 2000; Rosecchi et al. 2001;
1996). Heger and Trepl 2003; Martinez-Ghersa and Ghersa
Over the years, invasion biologists have sought 2006). We also excluded studies that address
patterns and generality, or ecological rules of thumb correlates associated with successful and unsuccess-
(Cote and Reynolds 2002), amongst this complex ful introductions of native species translocated
myriad of variables. Some authors claim to be within their native range (Griffith et al. 1989; Wolf
successful in this regard by identifying the general et al. 1996), natural range expansions (O’Connor
characteristics of, for example, invasive plants 1986), invasive native species (Thompson et al.
(Arthington and Mitchell 1986; Baker 1965, 1986; 1995), and experimental studies using native species
Pysek 1998), fish (Arthington et al. 1999; Kailola in the wild or non-native species under experimental
2000), molluscs (Morton 1996) and terrestrial verte- conditions (Pattison et al. 1998; Hee et al. 2000;
brates (Ehrlich 1989). Furthermore the characteristics Radford and Cousens 2000; Beggren 2001; Thomp-
identified by these authors are often used in risk son et al. 2001; Grotkopp et al. 2002; Alroth et al.
assessment regimes designed to prevent deliberate 2003; Bellingham et al. 2004; Rehage and Sih
and accidental introductions of invasive species (see 2004).
the review by Ruesink et al. 1995). For each article included in the review we
In this study we review the methods and results recorded the data set(s), biological group and statis-
of a wide range of studies designed to identify tical method(s), together with the correlates that were
statistically significant correlates of invasion or examined. These correlates were then mapped to a
establishment success. Our primary aims are to common classification to facilitate comparison and
synthesise data on the characteristics of invasive synthesis. In a few cases we renamed correlates
species and identify consistent correlates—i.e. identified in one study to facilitate grouping and
independently verified predictors of invasion or comparison with other studies. In doing so we have
establishment success that are statistically signifi- been careful to ensure that only biologically identical
cant either within or across different biological characteristics are grouped. For example characteris-
groups. tics associated with fecundity such as the number of
seeds, eggs or pups and the size or mass of seeds or
eggs were grouped. If in doubt we left the original
Methods characteristic unchanged. All characteristics across
the studies where allocated to one of three species-,
This review follows the methodology of Kolar and location- or event-level effect classes to distinguish
Lodge (2001) but extends their work by including 33 biological (species-level) characteristics from loca-
more studies. The references in this review were tion- and event-level characteristics (Cassey et al.
collected by running the following Boolean search: 2005). We also grouped the species-level traits into
(attributes OR correlates OR characteristics) AND the following 15 sub-groups: behaviour, diet, dis-
(alien OR non-native OR non-indigenous OR exotic) persal, genetics, growth, human, leaf, lifespan, nest,
AND (invasion OR establishment) AND (success OR other, reproduction, size, survival, taxon and
predict*), in the ‘‘topic’’ function of the ISI Web of tolerance.
Science (http://portal.isiknowledge.com/portal.cgi? The data set(s) in each article was classified into
DestApp=WOS&Func=Frame), obtaining the rele- one of two control group categories: introduced
vant references and systematically searching their versus invasive, or native versus invasive, and into
citations for further relevant publications. We one of three introduction types: deliberate, accidental
123Predicting establishment and invasion success 485
or deliberate and accidental, in order to highlight the non-native ungulates in New Zealand, ant intercep-
different cases and control groups compared in each tions in New Zealand and non-native reptiles and
study. We also noted which studies controlled for amphibians in Florida, California and Great Britain
phylogeny. If authors performed their analysis with (Appendix 1).
and without phylogenetic correction we only took the The majority of studies (80%) compare intro-
results with correction. Finally, correlates of success duced versus invasive species—i.e. species that
were distinguished for two transition states: intro- successfully negotiated the introduced-established
duced—established and established—invasive (sensu or established-invasive transition with those intro-
Kolar and Lodge 2001). For the latter we also duced species that did not become established or
recorded how each study interpreted and used the invasive. The remaining studies compare native
word ‘‘invasive’’. species with successful non-native species (native
The results of each study were entered into an versus invasive). In most case these species were
excel spreadsheet and then grouped by transition step, either deliberately introduced or a mixture of
characteristic, control group and (for the estab- deliberate and accidental introductions. Analysis of
lished—invasive transition) meaning of the term accidental introductions alone are rare—only 5 such
‘‘invasive’’. Once grouped we counted the number studies are reported here.
of independent and overlapping data sets. Indepen- The term ‘‘established’’ uniformly refers to self-
dent and overlapping data sets for the introduced- maintaining populations of non-native species.
established transition were defined on the basis of the Studies that address the introduction—establishment
biological group, control group and location where transition and compare native versus invasive
they were studied (Fig. 1). For the established- species report total sample sizes (N) that range
invasive transition, independence and overlap was between 84 and 2,684 with a median of 292. This
additionally determined by the meaning of the word is much larger than studies that compare introduced
‘‘invasive’’. versus invasive species where the median total
sample size is 55. The median number of success-
fully established species (N+), however, is much
Results more similar between the two approaches (57 vs.
27), and the overall difference in range is also
Biological groups, group sizes and the tens rule much less (Fig. 2). The first (third) quantile of
sample size changes from 45% (152%) to 19%
A total of 49 studies were eventually included in (59%) between N and N+ in the introduced versus
this review. We believe that they represent a good invasive category. This suggests that the proportion
proportion of studies presented in the English of species successfully negotiating the introduc-
literature and are confident that any omission is tion—establishment transition is higher than the
not the result of unintended bias on our part. Overall 10% suggested by the ‘‘tens rule’’ (Williamson
the studies address 115 correlates in 7 biological 1993). Note, however, that this dataset includes
groups: birds, finfish, insects, mammals, plants, deliberately introduced species which might be
reptiles/amphibians and shellfish (the data set expected to have a higher probability of establish-
and full list of correlates are available from the ment. We did not test the ‘‘tens rule’’ for the
authors on request). Plants and birds feature prom- established—invasive transition because the term
inently in the list, accounting for 76% of the ‘‘invasive’’ is vague and context specific. The
studies examined here. Other aquatic and terrestrial studies reviewed here use this term to refer to five
examples are relatively rare: 3 studies address non- different metrics: size of the invaded range, abun-
native finfish introductions in California, Australia dance in the invaded range, harmful properties,
and the Great Lakes, 3 address non-native shellfish classified as ‘‘weedy’’ and spreading in the invaded
in the NE Pacific, Great Lakes and continental states range. This reduces the total number of studies that
of the USA. The remaining studies address bio- compare like with like to a maximum of only
control insects, non-native mammals in Australia, seven for this transition.
123486 K. R. Hayes, S. C. Barry
Fig. 1 Venn diagrams (a) Body mass: 6 overlapping data sets, 5 independant data sets
illustrating how overlapping
and independent data sets Establishment: Introduced versus invasive species
are defined for the purposes
of this study, showing data
Birds of the world
sets used to test the effect
of: (a) body mass; and (b) Mammals
in Austtalia
date of introduction, on
establishment success of Parrots of the world Birds in New
Zealand
introduced versus invasive
species Birds
in
South.
Florida
Birds in
Austtalia
Ungulates
Land birds of the world in New
Zealand
(b) Date of introduction: 2 overlapping data sets, 5 independant data sets
Establishment: Introduced versus invasive species
Birds in Bivalves in
Australia the NE
Pacific
Birds in New
Zealand
Passerine
birds in New
Zealand
Birds in
Passerine South
birds in St. Florida
Helena
Statistical methods and inconsistent results are used on various occasions, usually in concert
with other methods. On one occasion the analysis
Most of the studies reviewed here adopt a single methods is unclear. Most study/statistical method
method, most notably linear models such as least combinations were conducted without phylogenetic
squares regression, generalised linear models with a control.
logit link function (logistic regression) or an identity For the introduced-established transition we
link function (multiple regression) (Quinn and found six examples of different results reported for
Keough 2002). More sophisticated extensions of the same characteristic in the same dataset using
this approach (generalised linear mixed models) are different statistical methods. All of these examples,
much rarer with only two examples in this review. however, can be attributed to the effect of phylo-
The next most popular method is the chi-squared genetic control, different sample sizes and (in the
test. The remaining techniques include a mixture of case of plumage dichromatism) the confounding
parametric and non-parametric approaches. These effect of propagule size (Table 1). We also
123Predicting establishment and invasion success 487
Fig. 2 Sample sizes of
successfully established
(N+) species and total (N)
control population in 49
bio-invasion risk
assessment studies that
compared native versus
introduced species and
introduced versus invasive
species
discovered three examples of different results biological groups, and none are contraindicated by
reported for the same characteristic in the same other studies. The number of release/arrival
dataset using the same statistical method (Table 2). attempts is consistently positively associated with
None of these examples, however, can be attributed establishment in seven independent studies across
to the effects of phylogenetic control. The con- four biological groups (finfish, insects, mammals
founding effect of propagule pressure explains the and reptiles/amphibians) but is not consistent within
inconsistent results reported for geographic range birds because it was found to be non-significant for
size in global bird introductions. The inconsistent land birds in New Zealand by two studies
results reported for number of released/arrival (Table 2).
attempts and migratory tendency also appear to be In the introduced-invasive control group, only two
due to the confounding effects of propagule species level characteristics—taxon and geographic
pressure. range size—were consistently, significantly associ-
ated with establishment success across two biological
groups. These results, however, were not supported
Establishment success/failure by independent data sets, or were contraindicated by
these data sets, within the biological groups examined
Our analysis indicates that climate/habitat match, here. In the introduced-native control group, three
history of invasive success and number of arriving/ species level characteristics—geographic range size,
released individuals are consistently associated with leaf surface area and fertilisation system (monoe-
successful transition from introduction to establish- cious, hermaphroditic or dioecious)—were consis-
ment (Table 3, Appendices 2, 3). All of these tently supported within plants but were either not
characteristics have been found to be significantly supported by independent data sets or contraindicated
associated with establishment success in at least by datasets within or across other biological groups
four independent data sets, both within and across (Table 3).
123488 K. R. Hayes, S. C. Barry
Table 1 Characteristics from the same data sets, analysed with different methods, that are inconsistently reported as positively (+),
negatively ( ) or not significantly (NS) associated with establishment success/failure
IDa Characteristic Data set Methodb CCc PCd + NS
13 Altitude Plants of the British Isles Sign test, CST NvI Y 1
49 Altitude Plants of the British Isles CST NvI N 1
13 Pollination type Plants of the British Isles Sign test, CST NvI Y 1
49 Pollination type Plants of the British Isles CST NvI N 1
13 Seed/egg mass/size Plants of the British Isles Sign test, CST NvI Y 1
49 Seed/egg mass/size Plants of the British Isles CST NvI N 1
17 Diet breadth/type Birds in Australia t-test IvI Y 1
34 Diet breadth/type Birds in Australia CST IvI N 1
9 Plumage dichromatism Birds of the world GLMM IvI Y 1
45 Plumage dichromatism Birds of the world GLM IvI Y 1
32 Body length/size Bivalves in NE Pacific t-test (with bootstrap) IvI N 1
42 Body length/size Bivalves in NE Pacific Mann–Whitney U-test NvI Y 1
a
ID: Reference identifier
b
Statistical methods: Analysis of Variance (ANOVA), Correlation (Pearson/Spearman) (C), Correspondance Analysis (CA),
Categorical Regression Tree (CART), Chi-squared test (CST), Discriminant analysis (DA), Generalised Linear Model (GLM),
Generalised Linear Mixed Model (GLMM), Logistic regression (LR), Multiple regression (MR), Principal Components Analysis
(PCA), Regression (R)
c
CC: Control class, I v I = Introduced versus invasive, N v I = Native versus invasive
d
PC: Phylogenetic control, Y = Yes, N = No
Table 2 Characteristics from the same data sets, analysed with the same method, that are inconsistently reported as positively (+),
negatively ( ) or not significantly (NS) associated with establishment success/failure
IDa Characteristic Data set Methodb CCc PCd + NS
3 Geographic range size Birds of the world GLMM IvI Y 1
9 Geographic range size Birds of the world GLMM IvI Y 1
46 No. of release/arrival attempts Birds in New Zealand LR, MR IvI N 1
48 No. of release/arrival attempts Birds in New Zealand LR, MR IvI N 1
46 Migratory tendency Birds in New Zealand LR, MR IvI N 1
48 Migratory tendency Birds in New Zealand LR, MR IvI N 1
a
ID: Reference identifier
b
Statistical methods: Analysis of Variance (ANOVA), Correlation (Pearson/Spearman) (C), Correspondance Analysis (CA),
Categorical Regression Tree (CART), Chi-squared test (CST), Discriminant analysis (DA), Generalised Linear Model (GLM),
Generalised Linear Mixed Model (GLMM), Logistic regression (LR), Multiple regression (MR), Principal Components Analysis
(PCA), Regression (R)
c
CC: Control class, I v I = Introduced versus invasive, N v I = Native versus invasive
d
PC: Phylogenetic control, Y = Yes, N = No
Invasive/not invasive biological groups (Table 4, Appendices 4, 5). This
finding, however, is not supported by two or more
Climate/habitat match is the only characteristic that is independent data sets within any of the biological
consistently significantly associated with invasive groups examined here. Within plants there are a suite
behaviour (in this case exotic range size) across of characteristics, predominately associated with
123Predicting establishment and invasion success 489
Table 3 Characteristics that are significantly associated with establishment success in at least two independent data sets either
within or across biological groups
Level Characteristic NIDa CCb Within Across
Location Climate/habitat match 6 IvI B B, F, I, M, P, R
Species History of invasive success 8 IvI B, F, P B, F, M, P, R
Event Number of released/arriving individuals 4 IvI B B, F, I
Event Number of release/arrival attempts 7 IvI F, I, M, R
Species Taxon 5 IvI P, R
Species Geographic range size 8 IvI I, M
Species Geographic range size 8 NvI P
Species Leaf surface area 3 NvI P
Species Fertilisation system 2 NvI P
a
NID: Number of independent data sets
b
CC: Control class, I v I = Introduced versus invasive, N v I = Native versus invasive. Biological groups are Birds (B), Finfish (F),
Insects (I), Mammals (M), Plants (P) and Reptiles/Amphibians (R)
Table 4 Characteristics that are significantly associated with invasion success in at least two independent data sets either within or
across biological groups
Level Characteristic MIa NIDb CCc Within Across
Location Climate/habitat match RS 3 IvI B, M, P
Species History of invasive success W 2 IvI P
Event Date of introduction A, W 2 IvI P
Location Biogeographic origin A 2 IvI P
Species Length of juvenile period S 2 IvI P
Species Growth form RS, A, H 2 NvI P
Species Asexual/vegetative reproduction A 2 IvI P
Species Length of flowering period A 2 IvI P
Species Flowering season A 2 IvI P
a
MI: Meaning of invasive, W = Weedy, RS = Range size (exotic), A = Abundance, S = Spreading, H = Harmful
b
NID: Number of independent data sets
c
CC: Control class, I v I = Introduced versus invasive, N v I = Native versus invasive. Biological groups are Birds (B), Mammals
(M) and Plants (P)
reproduction, that are significantly associated with a This typically leads to successful species (N+) being
range of invasion metrics, predominately abundance over-represented. Thus the structure of the data
in the invaded range, in two independent data sets. collection method is a retrospective case/control
None of these characteristics, however, are supported sample and not a random sample of a defined
across any other biological groups and in all cases population. Standard analysis shows that regression
there are only two independent data sets (Table 4). parameters may be consistently estimated from such
data but that the intercept (i.e. the rate of invasion)
Discussion cannot (Breslow and Clayton 1993).
The definition of the control sample has an
Population and confounding factors important bearing on the interpretation of the results
of the studies reported here. Native species do not
The data reviewed here is not a random sample of make a good control sample if the aim of the analysis
all species arriving at a particular transition, but is to predict which species will invade (rather than
rather a sample defined by what data is available. understand why species are successful) because
123490 K. R. Hayes, S. C. Barry
differences may arise through biogeography rather than (Lockwood et al. 2005). Deliberate introductions, by
a direct ecological process. Studies that compare native definition, imply a high degree of human-mediated
versus invasive species are afforded the luxury of larger selection. This selection process is controlled by
datasets (Fig. 1) but they are forced to untangle historical, economic and sociological factors that may
differences attributable to biogeography and invasion have no relevance to the biological characteristics of
ecology. Studies that compare introduced versus inva- successful invasive species (for relevant examples see
sive species face similar problems if the case and/or Cassey et al. 2004b and Garcia-Berthou et al. 2005). In
control set do not represent unbiased samples from accidental introductions there is a direct, and arguably
relevant populations (see also Simons 2003; Cassey more relevant, interaction between the species-level
et al. 2004b). If the model is being used as a predictive characteristics of an invasive species (e.g. planktonic
tool to support decisions about the deliberate importa- larval duration) and other historical or economic factors
tion of a species, then the unsuccessful species (N ) (e.g. the advent of ballast water transport). An exam-
should be an unbiased sample of species that had an ination of significant invasion characteristics in
opportunity to invade but were unsuccessful. This data accidental introductions may therefore provide further
is sometimes available for deliberate introductions (e.g. useful insights into important species-level characteris-
Kolar and Lodge 2001; Cassey et al. 2004b), and in tics. Future studies of deliberately introduced species
these instances a regression-based approach is appro- should consider the confounding effects of propagule
priate so long as the control set (N+) is an unbiased pressure before reporting other statistically significant
sample of species that had an opportunity to invade and characteristics of invasion success.
were successful. This allows the model to be used to
assess the relative risk of a new deliberate introduction.
For accidental introductions, however, unbiased reports Statistical methods
of successful (N+) and unsuccessful (N ) species are
generally not available because unsuccessful accidental All of the statistical methods reviewed here estimate
introductions are not comprehensively reported and how the probability of success responds conditionally
patterns of trade vary through time. As a consequence on covariates, usually with regression-based techniques.
very few studies to date have quantitatively addressed They vary, however, in the flexibility of their response
accidental introductions. This is an important avenue surface with respect to the covariates. The simplest
for future research. approaches, such as a t-test, measure significant differ-
If the case and control data are truly a random ences in the marginal success rate. More complex
sample from the population of successful and unsuc- approaches, such as regression trees, model sets of
cessful invaders then phylogenetic correction is not variables jointly, allow for discontinuities in the
technically necessary. The sample might not be a response surface and can flexibly map interactions.
representative sample of all species, but may be The appropriateness of an analytic approach
representative of the species that can potentially depends on a number of limitations. The primary
invade a location. If the sample is biased, a correction issue in this context is that the number of successful
for this bias may be needed and this could be based species (N+) is typically small (Fig. 1). The com-
on the phylogeny. In this context the use of gener- plexity of regression models must therefore be
alised linear mixed models with phylogenetic group carefully controlled to avoid over fitting (Burnham
as a random effect would appear to provide a better and Anderson 2002; Caley and Kuhnert 2006). The
foundation for prediction than phylogenetic contrasts, ‘‘best’’ model (in terms of appropriateness to new
because the theoretical basis of General Linear data) will depend on the underlying population and
models is more clearly defined. the particular sample at hand but a few general
Phylogeny, however, is only one of a number of recommendations can be made. First, modern statis-
potentially important sources of bias. Other important tical arguments suggest it is better to model variables
sources are residence time (Richardson and Pysek jointly rather than one at a time, as this allows the
2006) and propagule pressure as demonstrated by the analysis to consider the effects of confounding
inconsistent results reported here. Propagule pressure is variables and provides more concise results with a
particularly important for deliberate introductions clearer interpretation. Regression techniques that
123Predicting establishment and invasion success 491
allow multiple variables are therefore better. The spread in the exotic range but only within plants—
second recommendation is to use a technique, such as none of these were consistently significant within or
regression trees, that allow for more complex across any other biological groups (Table 4, Appen-
response surfaces. This last recommendation is dix 4).
tempered by the typical data limitations (ten obser- Cote and Reynolds (2002) suggest that general,
vations per variable is a useful rule of thumb—see and sometimes broadly applicable, ecological rules of
van Belle 2002 ), and the need to provide an easily thumb may exist. This statement is supported by the
interpretable output. Generalised linear mixed models recent discovery of consistent spread dynamics in
are a promising analytical technique in this context, invasive species in widely different contexts (Arim
because they can simultaneous control for confound- et al. 2006). The collective research effort of the
ing variables, in an easily interpreted manner. many studies reviewed here, however, suggest that
across (within) biological groups, there are only three
(nine) species-level characteristics that distinguish
Sample sizes and consistently significant successful established/invasive species from unsuc-
characteristics cessful species, and the results within biological
groups have to date only been demonstrated for
Kolar and Lodge (2001) examined the characteristics plants. The most significant result of this analysis is
that were quantitatively associated with establishment that two location- and event-level correlates—cli-
and invasion success in 16 studies. We have repeated mate/habitat match and number of introduced
their analysis but added another 33 studies and organisms—are consistently significant predictors of
distinguished taxonomic group, population, statistical successful establishment across all of the biological
method and sample size. Kolar and Lodge (2001) groups in which they have been tested. Modern
note that the probability of establishment of non- biology accepts that on average organisms are
native birds increases with the number of individuals adapted to particular conditions and are not generally
released and the number of release events, and the able to vary this adaptation arbitrarily. Hence some
probability of invasion by non-native plants increases degree of climate/habitat match is a pre-requisite of
if the species has a history of invasion and reproduces establishment success and the number of introduced
vegetatively. We found that the probability of organisms (and number of repeat introductions) is an
establishment increases with the number of individ- important determinant of the likelihood of establish-
uals released across all the biological groups (birds, ment success, so long as the climate/habitat is
finfish and insects) where this correlate has been suitable. Our results confirm that other species-level
tested (Table 3, Appendix 2). This conclusion is also characteristics of establishment and invasion success
supported by many of the studies excluded from this exist but (with the exception of a history of invasion
review (Williamson 1993; Ruesink et al. 1995; Wolf success) they have only been demonstrated in plants.
et al. 1996; Gruestad 1999; Beggren 2001; Alroth It is important to note here that the various interpre-
et al. 2003) and a quantitative meta-analysis of bird tations of the term ‘‘invasive’’ significantly reduces
introductions (Cassey et al. 2005). The number of the number of studies that compare like with like, and
release events was consistently statistically associated this reduces our ability to identify patterns within the
with establishment success across finfish, insects, results of the available literature.
mammals and reptiles/amphibians but was not con- The concept that some species are inherently more
sistently significant within birds (Tables 2, 3, invasive is at the core of the models reviewed here.
Appendix 2). We found that a history of invasive This effect is obviously confounded with the impact
success was positively and consistently associated of other variables that are correlated with invasion
with establishment success, across all of the biolog- success. A history of invasion success is a consis-
ical groups examined here (except insects where it tently significant correlate of establishment success
was not tested), but not with invasion success where across all biological groups in which it has been
it was only consistently associated with weed status tested but for the established—invasion transition it is
in plants. We found four reproduction-related char- only consistently significant within plants. Again, this
acteristics to be the associated with abundance and is probably due to the various different interpretations
123492 K. R. Hayes, S. C. Barry
of the word ‘‘invasive’’ (see also Ricciardi and Cohen very few species-level characteristics have been
2007). When this variable is analysed marginally (i.e. independently verified as significant, and none of
on its own) a significant result indicates that some these are consistently significant in more than two
other unknown covariate(s) has a consistent effect on biological groups. This conclusion suggests that
invasion success. When analysed jointly with the species-level characteristics that are predictive of
other covariates a significant result indicates that the successful invaders are likely to be taxa-specific
pattern of success cannot be purely explained by the (Sakai et al. 2001) and even site-specific (Lake and
available covariates. Lewisham 2004). It is important to note that this
The results of this review suggest that we still have conclusion is not new. Plant ecologists often empha-
a long way to go to identify broadly applicable sise habitat/species interactions and the important
species-level characteristics of successful invasive role of location-level characteristics such as land-
species. Cassey et al. (2005) criticise ‘vote-counting’ scape and community variables, in invasion success
reviews, such as this one, on the grounds that they are (Thompson et al. 1995; Radford and Cousens 2000;
qualitative and subjective, recommending a quantita- Allen 2006; Bass et al. 2006; Richardson and Pysek
tive meta-analysis. We do not dispute the advantages 2006). Heger and Trepl (2003) refer to these as ‘‘key-
of a quantitative meta-analysis, but we see no reason lock models’’ noting that there are no (species-level)
why a quantitative meta-analysis, applied across the characteristics common to all invaders. Rather each
groups reviewed here, would reverse our conclusions. characteristics has to suit the specific conditions of
We do not claim that particular characteristics are not the new environment.
significantly associated with invasion/establishment If this conclusion is true it imposes a tension
success in certain contexts. Instead, we argue that between the generality and the accuracy of risk
most of these characteristics are not consistently assessment schemes that rely on species-level char-
significant in different contexts. Furthermore, meta- acteristics to prevent introductions. Furthermore this
analysis is applicable to multiple studies of the same conclusion cautions studies that promote risk assess-
population in similar contexts. In this study we ments, based largely on species-level characteristics,
examined multiple populations in various contexts. as accurate and readily generalised to new locations
Hence, it is not immediately clear to us that the (see for example Krivanek and Pysek 2006). In some
primary assumption of meta-analysis—that the stud- cases the apparent effect of accuracy and generality
ies examined are sufficiently similar for pooled data may be the result of no more than a simple statistical
to produce meaningful results—would be applicable overfit in the risk assessment model (Caley and
here. Kuhnert 2006). Risk managers can, however, place
much greater faith in assessments that identify
potential invaders based on climate/habitat matching,
Risk management implications invasion history and number of released/arriving
individuals. These correlates must be interpreted
Invasion biologists continue to suggest and test a carefully and are not foolproof but they are consis-
large number of species-level characteristics in tently supported by the available literature.
search of a set that predicts invasion and establish-
ment success, and risk analysts continue to Acknowledgements We would like to thank Piers Dunstan,
Ullrika Sahlin, Nic Bax, Mary Bomford, Dave Richardson and
recommend their use in risk management schemes four anonymous reviewers for comments on earlier drafts of
(Stohlgren and Schnase 2006). To date, however, this article.
123Appendix 1 Biological groups, transition step, statistical method, sample size, introduction mode and control class in 49 biological invasion studies
a g
Group Reference IDb Methodc Sd Ne N+f N TIh CCi PCj
B Allen (2006) 1 LR E 46 26 20 D/A IvI N
Brooke et al. (1995) 6 Kruska–Wallis test, C E 31 5 26 D IvI N
Cassey et al. (2004a) 9 GLMM E 416 D IvI Y
Cassey et al. (2004b) 10 GLM E 54 38 D IvI N
Cassey (2001) 11 LR, MR E 118 31 87 D IvI N
Duncan et al. (1999) 16 R, t-test I 34 D NvI Y
Duncan et al. (2001) 17 LR, MR, t-test E 55 19 36 D/A IvI Y
I 19 D/A IvI Y
Duncan (1997) 18 LR, MR E 42 15 27 D IvI Y
Green (1997) 22 LR, MR E 47 21 26 D IvI Y
Predicting establishment and invasion success
Moulton and Pimm (1986) 33 CST E 50 33 17 D IvI Y
Newsome and Noble (1986) 34 CST E 107 59 48 D IvI N
Sorci et al. (1998) 46 LR, MR E 47 27 20 D IvI N
Veltman et al. (1996) 48 LR, MR E 79 27 52 D IvI N
Sol and Lefebvre (2000) 44 LR, MR E 39 19 20 D IvI Y
Sol et al. (2002) 45 GLM E 69 51 18 D/A IvI Y
Blackburn and Duncan (2001) 3 GLMM E 389 D/A IvI Y
Cassey (2002) 12 GLM E D/A IvI Y
F Kolar and Lodge (2002) 25 DA E 45 24 21 D/A IvI N
I 24 D/A IvI N
Marchetti et al. (2004) 31 LR, MR E 109 71 38 D/A IvI N
I 71 D/A IvI N
Bomford and Glover (2004) 4 PCA , CART, LR, C E 50 31 19 D/A IvI N
I Lester (2005) 27 Kruskal–Wallis test E 17 43 A IvI N
Crawley (1987) 14 Unclear E 225 146 79 D IvI N
M Forsyth et al. (2004 20 LR, MR E 40 23 17 D IvI Y
I 23 D IvI Y
Forsyth and Duncan (2001) 19 LR, CST E 14 11 3 D IvI N
493
123Appendix 1 continued
494
g
Groupa Reference IDb Methodc Sd Ne N+f N TIh CCi PCj
123
P Cadotte and Lovett-Doust (2001) 7 LR, CST E 1,330 484 D/A NvI N
Crawley et al. (1996) 13 GLM, Sign test, CST E 2,684 D/A NvI N
Daehler, (1998) 15 CST I 240,100 1041 D/A NvI Y
Goodwin et al. (1999) 21 LR, MR E 165 D/A NvI Y
Hamilton et al. (2005) 23 LR, MR I 152 D/A IvI Y
Lake and Lewishman (2004) 26 CST, ANOVA E 86 57 29 A NvI N
I 57 A NvI N
Lloret et al. (2005) 28 GLM I 354 D/A IvI Y
Lonsdale (1994) 29 Kruska–Wallis test I 466 61 405 D IvI N
Maillet and Lopez-Garcia (2000) 30 CA, CART I 78 D/A IvI N
Perrins et al. (1992) 35 PCA, HCA, DA I 49 A/D NvI N
Pysek (1998) 36 MR, ANOVA E 8,003 A/D IvI Y
I 8,003 A/D IvI Y
Reichard and Hamilton (1997) 37 DA, CART E . 235 114 D IvI N
Reichard (2001) 38 DA, CART, t-test, CST E 416 418 270 D IvI N
Rejmanek and Richardson (1996) 39 DA I 24 12 12 D IvI N
Rejmanek (1996) 40 DA I 24 12 D IvI N
Richardson et al. (1990) 41 CA I 60 D IvI N
Scott and Panetta (1993) 43 LR, MR I 242 36 206 D IvI N
Sutherland (2004) 47 CST I D/A IvI N
Williamson and Fitter (1996) 49 CST E 974 112 D/A NvI N
Baruch and Goldstein (1999) 2 ANOVA E 84 30 34 D/A NvI N
Cadotte et al. (2006) 8 GLM I 846 272 D/A IvI Y
8 CST I 1,153 D/A IvI Y
R/A Bomford et al. (2005) 5 LR, t-test, CST E 163 60 103 D/A IvI N
K. R. Hayes, S. C. BarryAppendix 1 continued
g
Groupa Reference IDb Methodc Sd Ne N+f N TIh CCi PCj
S Miller et al. (2002) 32 t-test (with bootstrap) E 38 3 35 A IvI N
Roy et al. (2002) 42 Mann-Whitney U-test E 292 7 A NvI Y
42 LR, MR I 13 9 4 A IvI N
Keller et al. (2007) 24 LR, CART I 15 5 10 A IvI N
18 8 10 A IvI N
a
Biological groups: Birds (B), Finfish (F), Insects (I), Mammals (M), Plants (P), Reptiles/Amphibians (R/A) and Shellfish (S)
b
ID: Reference identifier
c
Statistical methods: Analysis of Variance (ANOVA), Correlation (Pearson/Spearman) (C), Correspondance Analysis (CA), Categorical Regression Tree (CART), Chi-squared
test (CST), Discriminant analysis (DA), Generalised Linear Model (GLM), Generalised Linear Mixed Model (GLMM), Logistic regression (LR), Multiple regression (MR),
Principal Components Analysis (PCA), Regression (R)
Predicting establishment and invasion success
d
Step: Transition step, E = Introduced to established, I = Established to invasive
e
N: Number of species or individual organisms
f
N+: Number of successful (established or invasive) species or individuals
g
N : Number of unsuccessful (established or invasive) species or individuals
h
TI: Type of introduction, D = deliberate introduced, A = Accidentally introduced
i
CC: Control class, I v I = Introduced versus invasive, N v I = Native versus invasive
j
PC: Phylogenetic control, Y = Yes, N = No
495
123496 K. R. Hayes, S. C. Barry
Appendix 2 Number of studies where establishment success/failure is reported as positively (+), negatively ( ) or not significantly
(NS) associated with event- and location-level characteristics in at least two independent data sets
Characteristic NODa NIDb CCc Group IDd + NS
Date of introduction 2 5 IvI Birds 1 1
6 1
18 1
22 1
34 1
Shellfish 42 1
No. of arriving/released individuals 5 5 IvI Birds 9 1
11 1
17 1
18 1
22 1
34 1
44 1
45 1
46 1
48 1
Finfish 31 1
Insects 14 1
No. of release/arrival attempts 3 7 IvI Birds 11 1
17 1
18 1
19 1
22 1
46 1
48 1
Finfish 4 1
Insects 14 1
Mammals 20 1
Reptiles/Amphibians 5 1
Biogeographic origin 2 4 IvI Birds 1 1
22 1
33 1
Plants 36 1
37 1
38 1
Climate/habitat match 2 6 IvI Birds 3 1
17 1
34 1
Finfish 4 1
Insects 27 1
Mammals 20 1
Plants 36 1
Reptiles/Amphibians 5 1
123Predicting establishment and invasion success 497
Appendix 2 continued
Characteristic NODa NIDb CCc Group IDd + NS
Mainland/island 2 2 IvI Birds 3 1
9 1
34 1
Plants 38 1
Great circle distance 0 2 IvI Birds 11 1
Finfish 31 1
a
NOD: Number of overlapping data sets
b
NID: Number of independent data sets
c
CC: Control class, I v I = Introduced versus invasive, N v I = Native versus invasive
d
ID: Reference identifier
Appendix 3 Number of studies where establishment success/ in at least two independent data sets for: (a) birds; (b) finfish;
failure is reported as positively (+), negatively ( ) or not (c) insects; (d) mammals; (e) plants; (f) reptiles/amphibians;
significantly (NS) associated with species-level characteristics and, (g) shellfish
CGa Characteristic NODb NIDc CCd IDe + NS
(a) Birds
Diet Diet breadth/type 6 5 IvI 1 1
9 1
10 1
11 1
12 1
17 1
34 1
45 1
48 1
Dispersal Migratory tendency 5 2 IvI 9 1
10 1
12 1
17 1
44 1
45 1
46 1
48 1
Human Human commensal 2 2 IvI 17 1
45 1
Nest Nest type 4 2 IvI 12 1
34 1
44 1
45 1
Other History of invasive success 2 8 IvI 6 1
17 1
123498 K. R. Hayes, S. C. Barry
Appendix 3 continued
CGa Characteristic NODb NIDc CCd IDe + NS
Reproduction Age at maturity/first breeding 0 2 IvI 10 1
12 1
Broods per season 0 2 IvI 17 1
34 1
48 1
Incubation period 4 2 IvI 3 1
10 1
12 1
17 1
Mating system 0 2 IvI 46 1
No. of seeds/eggs/pups 4 7 IvI 3 1
11 1
17 1
22 1
34 1
45 1
48 1
Parental care 2 3 IvI 45 1
46 1
Size Body length/size 2 6 IvI 11 1
48 1
Body mass 6 5 IvI 1 1
3 1
9 1
10 1
12 1
17 1
22 1
45 1
46 1
48 1
Taxon Taxon 2 5 IvI 3 1
48 1
Tolerance Geographic range size 7 8 IvI 3 1
9 1
10 1
11 1
12 1
17 1
33 1
48 1
(b) Finfish
Diet Diet breadth/type 6 5 IvI 25 1
31 1
123Predicting establishment and invasion success 499
Appendix 3 continued
CGa Characteristic NODb NIDc CCd IDe + NS
Human Human commensal 2 2 IvI 25 1
Lifespan Lifespan 0 4 IvI 25 1
31 1
Other History of invasive success 2 8 IvI 4 1
25 1
31 1
Reproduction Incubation period 4 2 IvI 25 1
Length of juvenile period 0 3 IvI 25 1
No. of seeds/eggs/pups 4 7 IvI 25 1
31 1
Parental care 2 3 IvI 25 1
31 1
Size Body length/size 2 6 IvI 4 1
25 1
31 1
Seed/egg mass/size 0 2 IvI 25 1
Taxon Taxon 2 5 IvI 4 1
25 1
Tolerance Geographic range size 7 8 IvI 4 1
25 1
31 1
Physiological tolerances 0 3 IvI 4 1
25 1
31 1
(c) Insects
Lifespan Lifespan 0 5 IvI 14 1
Size Body length/size 2 6 IvI 27 1
Tolerance Geographic range size 7 8 IvI 14 1
(d) Mammals
Diet Diet breadth/type 6 5 IvI 20 1
Dispersal Migratory tendency 5 2 IvI 20 1
Lifespan Lifespan 0 4 IvI 19 1
20 1
Other History of invasive success 2 8 IvI 20 1
Reproduction Length of juvenile period 0 3 IvI 20 1
Mating system 0 2 IvI 19 1
No. of seeds/eggs/pups 4 7 IvI 19 1
20 1
Size Body mass 6 5 IvI 19 1
20 1
Tolerance Geographic range size 7 8 IvI 20 1
123500 K. R. Hayes, S. C. Barry
Appendix 3 continued
CGa Characteristic NODb NIDc CCd IDe + NS
(e) Plants
Growth Growth form 0 4 NvI 7 1
21 1
26 1
49 1
Leaf Leaf surface area 0 3 NvI 2 1
26 1
49 1
Lifespan Monocarpy 0 2 NvI 49 1
Other History of invasive success 2 8 IvI 37 1
38 1
Reproduction Asexual/vegetative reproduction 0 2 NvI 7 1
26 1
Fertilisation system 0 2 NvI 7 1
49 1
Length of flowering period 0 3 NvI 7 1
21 1
26 1
Length of juvenile period 0 3 IvI 38 1
No. of seeds/eggs/pups 0 2 NvI 7 1
49 1
Pollination type 0 2 NvI 7 1
13 1
49 1
Size Canopy/stem/plant height 0 3 NvI 13 1
21 1
26 1
49 1
Seed/egg mass/size 0 2 IvI 38 1
NvI 13 1
26 1
49 1
Taxon Taxon 2 4 NvI 7 1
5 IvI 36 1
Tolerance Geographic range size 6 7 NvI 13 1
21 1
7 8 IvI 38 1
(f) Reptiles/Amphibians
Other History of invasive success 2 8 IvI 5 1
Taxon Taxon 2 5 IvI 5 1
123Predicting establishment and invasion success 501
Appendix 3 continued
CGa Characteristic NODb NIDc CCd IDe + NS
Tolerance Geographic range size 7 8 IvI 5 1
(g) Shellfish
Size Body length/size 2 6 IvI 32 1
42 1
a
CG: Species-level category
b
NOD: Number of overlapping data sets
c
NID: Number of independent data sets
d
CC: Control class, I v I = Introduced versus invasive, N v I = Native versus invasive
e
ID: Reference identifier
Appendix 4 Number of studies where invasion success/failure is reported as positively (+), negatively ( ) or not significantly (NS)
associated with event- and location-level characteristics in at least two independent data sets
Characteristic NODa NIDb CCc Group MId IDe + NS
Date of introduction 0 2 IvI Plants A 8 1
23 1
W 30 1
43 1
No. of arriving/released individuals 0 2 IvI Birds RS 17 1
Finfish RS, A 31 1
No. of release/arrival attempts 0 2 IvI Birds RS 17 1
Mammals RS 20 1
Biogeographic origin 0 2 IvI Plants A 8 1
RS, A 36 1
Climate/habitat match 0 3 IvI Birds RS 17 1
Mammals RS 20 1
Plants RS, A 36 1
a
NOD: Number of overlapping datasets
b
NID: Number of independent data sets
c
CC: Control class, I v I = Introduced versus invasive, N v I = Native versus invasive
d
MI: Meaning of invasive, A = Abundance, W = Weedy, RS = Range size (exotic)
e
ID: Reference identifier
Appendix 5 Number of studies where invasion success/failure two independent data sets for: (a) birds; (b) finfish; (c)
is reported as positively (+), negatively ( ) or not significantly mammals; (d) shellfish; and, (e) plants
(NS) associated with species-level characteristics in at least
CGa Characteristic NODb NIDc CCd MIe IDf + NS
(a) Birds
Diet Diet breadth/type 0 4 IvI RS 17 1
Dispersal Migratory tendency 0 2 IvI RS 17 1
Reproduction No. of seeds/eggs/pups 0 3 IvI RS 17 1
NvI RS 16 1
123502 K. R. Hayes, S. C. Barry
Appendix 5 continued
CGa Characteristic NODb NIDc CCd MIe IDf + NS
Size Body mass 0 2 IvI RS 17 1
Seed/egg mass/size 0 2 NvI RS 16 1
Tolerance Geographic range size 0 3 IvI RS 17 1
(b) Finfish
Diet Diet breadth/type 0 4 IvI RS, A 31 1
RS, H 25 1
Growth Growth rate 0 2 IvI RS, H 25 1
Lifespan Lifespan 0 2 IvI RS, A 31 1
3 3 IvI RS, H 25 1
Other History of invasive success 0 2 IvI RS, A 31 1
Reproduction No. of seeds/eggs/pups 0 2 IvI RS, A 31 1
Size Body length/size 2 2 IvI RS, H 25 1
Seed/egg mass/size 0 3 IvI RS, H 25 1
Taxon Taxon 0 2 IvI RS, H 25 1
Tolerance Geographic range size 0 3 IvI RS, A 31 1
(c) Mammals
Diet Diet breadth/type 0 4 IvI RS 20 1
Dispersal Migratory tendency 0 2 IvI RS 20 1
Lifespan Lifespan 0 2 IvI RS 20 1
Other History of invasive success 0 2 IvI RS 20 1
Reproduction Length of juvenile period 3 2 IvI RS 20 1
No. of seeds/eggs/pups 0 3 IvI RS 20 1
Size Body mass 0 2 IvI RS 20 1
Tolerance Geographic range size 0 3 IvI RS 20 1
(d) Shellfish
Lifespan Lifespan 3 3 IvI H 24 2
Reproduction Fertilisation system 2 2 IvI H 24 2
Size Body length/size 2 2 IvI H 24 2
(e) Plants
Growth Growth form 0 2 NvI RS, A, H 15 1
26 1
Growth rate 0 2 IvI W 29 1
Leaf Leaf surface area 0 2 IvI A 23 1
28 1
NvI W 35 1
RS, A, H 26 1
Lifespan Lifespan 3 3 IvI H 47 1
S 39 1
40 1
Other History of invasive success 0 2 IvI W 30 1
43 1
123Predicting establishment and invasion success 503
Appendix 5 continued
CGa Characteristic NODb NIDc CCd MIe IDf + NS
Reproduction Annual versus perennial 0 2 IvI A 8 1
28 1
Asexual/vegetative reproduction 0 2 IvI A 8 1
28 1
NvI W 35 1
RS, A, H 26 1
Fertilisation system 0 2 IvI A 8 1
28 1
2 2 IvI H 47 1
Length of flowering period 0 2 IvI A 8 1
28 1
NvI W 35 1
RS, A, H 26 1
Length of juvenile period 3 2 IvI S 39 1
40 1
41 1
No. of seeds/eggs/pups 0 2 IvI A 8 1
Flowering season 0 2 IvI A 8 1
28 1
Size Canopy/stem/plant height 0 3 IvI A 8 1
23 1
28 1
Seed/egg mass/size 0 2 IvI A 23 1
28 1
W 29 1
3 NvI W 35 1
RS, A, H 26 1
Taxon Taxon 0 2 IvI W 43 1
a
CG: Species-level category
b
NOD: Number of overlapping datasets
c
NID: Number of independent data sets
d
CC: Control class, I v I = Introduced versus invasive, N v I = Native versus invasive
e
MI: Meaning of invasive, A = Abundance, W = Weedy, RS = Range size (exotic), S = Spreading, H = Harmful
f
ID: Reference identifier
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