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 123
484 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 123
Predicting 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. 123
486 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 123
Predicting 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). 123
488 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 123
Predicting 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 123
490 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 123
Predicting 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 123
492 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. 123
Appendix 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 493 123
Appendix 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. Barry
Appendix 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 495 123
496 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 1 123
Predicting 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 1 123
498 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 1 123
Predicting 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 1 123
500 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 1 123
Predicting 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 1 123
502 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 1 123
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