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Prioritization of introduction pathways is seen as an important component of the management of biological invasions. We address whether established alien plants, mammals, freshwater fish and terrestrial invertebrates with known ecological impacts are associated with particular introduction pathways (release, escape, contaminant, stowaway, corridor and unaided). We used the information from the European alien species database DAISIE (www.europe-aliens.org) supplemented by the EASIN catalogue (European Alien Species Information Network), and expert knowledge. Plants introduced by the pathways release, corridor and unaided were disproportionately more likely to have ecological impacts than those introduced as contaminants. In contrast, impacts were not associated with particular introduction pathways for invertebrates, mammals or fish. Thus, while for plants management strategies should be targeted towards the appropriate pathways, for animals, management should focus on reducing the total number of taxa introduced, targeting those pathways responsible for high numbers of introductions. However, regardless of taxonomic group, having multiple introduction pathways increases the likelihood of the species having an ecological impact. This may simply reflect that species introduced by multiple pathways have high propagule pressure and so have a high probability of establishment. Clearly, patterns of invasion are determined by many interacting factors and management strategies should reflect this complexity.
The Editorial presents the focus, scope, policies, and the inaugural issue of NeoBiota, a new open access peer-reviewed journal of biological invasions. The new journal NeoBiota is a continuation of the former NEOBIOTA publication series. The journal will deal with all aspects of invasion biology and impose no restrictions on manuscript size neither on use of color. NeoBiota implies an XML-based editorial workflow and several cutting-edge innovations in publishing and dissemination, such as semantic markup of and enhancements to published texts, data publication, and extensive cross-linking within the journal and to external sources.
Robust predictions of alien species richness are useful to assess global biodiversity change. Nevertheless, the capacity to predict spatial patterns of alien species richness remains largely unassessed. Using 22 data sets of alien species richness from diverse taxonomic groups and covering various parts of the world, we evaluated whether different statistical models were able to provide useful predictions of absolute and relative alien species richness, as a function of explanatory variables representing geographical, environmental and socio-economic factors. Five state-of-the-art count data modelling techniques were used and compared: Poisson and negative binomial generalised linear models (GLMs), multivariate adaptive regression splines (MARS), random forests (RF) and boosted regression trees (BRT). We found that predictions of absolute alien species richness had a low to moderate accuracy in the region where the models were developed and a consistently poor accuracy in new regions. Predictions of relative richness performed in a superior manner in both geographical settings, but still were not good. Flexible tree ensembles-type techniques (RF and BRT) were shown to be significantly better in modelling alien species richness than parametric linear models (such as GLM), despite the latter being more commonly applied for this purpose. Importantly, the poor spatial transferability of models also warrants caution in assuming the generality of the relationships they identify, e.g. by applying projections under future scenario conditions. Ultimately, our results strongly suggest that predictability of spatial variation in richness of alien species richness is limited. The somewhat more robust ability to rank regions according to the number of aliens they have (i.e. relative richness), suggests that models of aliens species richness may be useful for prioritising and comparing regions, but not for predicting exact species numbers.