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The relevance of using various scoring schemes revealed by an impact assessment of feral mammals
(2018)
Impact scoring schemes are useful for identifying to what extent alien species cause damage. Quantifying the similarity and differences between impact scoring schemes can help determine how to optimally use these tools for policy decisions. Using feral mammals (including rats and mice) as a case study, environmental and socio-economic impacts were assessed using three schemes, namely the Generic Impact Scoring System (GISS), Environmental Impact Classification for Alien Taxa (EICAT) and Socio-Economic Impact Classification for Alien Taxa (SEICAT). The results show that socio-economic impacts scores differ between the respective schemes (GISS and SEICAT) possibly because they assess different aspects of social life and economy. This suggests that both scoring schemes should ideally be applied in concert to get a complete picture of socio-economic impacts. In contrast, environmental impact scores are correlated between GISS and EICAT assessments and this similarity is consistent over most mechanisms except for predation and ecosystems, suggesting that one scoring scheme is sufficient to capture all the environmental impacts. Furthermore, we present evidence for the island susceptibility hypothesis as impacts of feral mammals were found to be higher on islands compared to mainlands.
Impact assessment with different scoring tools: How well do alien amphibian assessments match?
(2017)
Classification of alien species' impacts can aid policy making through evidence based listing and management recommendations. We highlight differences and a number of potential difficulties with two scoring tools, the Environmental Impact Classification of Alien Taxa (EICAT) and the Generic Impact Scoring System (GISS) using amphibians as a case study. Generally, GISS and EICAT assessments lead to very similar impact levels, but scores from the schemes are not equivalent. Small differences are attributable to discrepancies in the verbal descriptions for scores. Differences were found in several impact categories. While the issue of disease appears to be related to uncertainties in both schemes, hybridisation might be inflated in EICAT. We conclude that GISS scores cannot directly be translated into EICAT classifications, but they give very similar outcomes and the same literature base can be used for both schemes.
Range expansion drives the evolution of alternate reproductive strategies in invasive fire ants
(2017)
Many species are expanding their ranges in response to climate changes or species introductions. Expansion-related selection likely drives the evolution of dispersal and reproductive traits, especially in invasive species introduced into novel habitats. We used an agent-based model to investigate these relationships in the red imported fire ant, Solenopsis invicta, by tracking simulated populations over 25 years. Most colonies of this invasive species produce two types of queens practicing alternate reproductive strategies. Claustral queens found new colonies in vacant habitats, while parasitic queens take over existing colonies whose queens have died. We investigated how relative investment in the two queen types affects population demography, habitat occupancy, and range expansion. We found that parasitic queens extend the ecological lifespan of colonies, thereby increasing a population’s overall habitat occupancy as well as average colony size (number of workers) and territory size. At the same time, investment in parasitic queens slowed the rate of range expansion by diverting investment from claustral queens. Divergent selection regimes caused edge and interior populations to evolve different levels of reproductive investment, such that interior populations invested heavily in parasitic queens whereas those at the edge invested almost entirely in claustral queens. Our results highlight factors shaping ant life histories, including the evolution of social parasitism, and have implications for the response of species to range shifts.
Plant traits are critical for understanding invasion success of introduced species, yet attempts to identify universal traits that explain invasion success and impact have been unsuccessful because environmenttrait- fitness relationships are complex, potentially context dependent, and variation in traits is often unaccounted for. As introduced species encounter novel environments, their traits and trait variability can determine their ability to grow and reproduce, yet invasion biologists do not often have an understanding of how novel environments might shape traits. To uncover which combination of traits are most effective for predicting invasion success, we studied three different urban habitat types along the Nile Delta in Egypt invaded by the Pink Morning Glory, Ipomoea carnea Jacq. (Family: Convolvulaceae). Over two years, we measured ten plant traits at monthly intervals along an invasion gradient in each habitat. No single trait sufficiently explained survival probability and that traits linked to invasion success were better predicted by the characteristics of the invaded habitat. While the measured traits did influence survival of I. carnea, the importance of specific traits was contingent on the local environment, meaning that local trait-environment interactions need to be understood in order to predict invasion.
The adoption of a consistent alien species pathways categorization, hierarchy and terminology is crucial for increasing the interoperability of different online databases. In the present paper the European Alien Species Information Network (EASIN) classification system of pathways is compared and discussed with the classification scheme recently published by the Convention on Biological Diversity (CBD). Although the main pathway categories of the two classifications overall match, there are substantial differences in their subcategorization, with EASIN including 20 pathway subcategories while CBD considers 44 subcategories. In most cases, each EASIN subcategory pathway can correspond to two or more CBD subcategories. About 5,500 species listed in EASIN do not match directly with the CBD pathway subcategories, most of which are terrestrial invertebrates. Aiming at achieving synchronization between the two classification systems and at facilitating the access to information to researchers and policy makers, EASIN is trying to align with the CBD pathway classification scheme. This alignment process requires the involvement of a large number of experts, especially from the terrestrial realm, and the adoption of commonly accepted definitions of the CBD pathways.
Das Hultschiner Ländchen ist heute ein Teil der Tschechischen Republik, in dem seit Jahrhunderten die mährischen/tschechischen, deutschen und polnischen sprachlichen und kulturellen Bevölkerungsgruppen zusammenlebten, wobei der deutsche Aspekt eine bestimmende Rolle spielte. In dieser Region wurde der vielseitig begabte Max Ring geboren, der als Arzt, Schriftsteller, Dramatiker und Journalist in Oberschlesien und vor allem in Berlin tätig war. In seinem autobiografischen Werk 'Erinnerungen' schildert Ring seine Kinderjahre im national und religiös liberalen Milieu des Heimatdorfes und die sozialen Verhältnisse im industriellen Oberschlesien genauso wie das Leben der Boheme in den Berliner literarischen Gesellschaften.
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.
Various mechanisms can facilitate the success of plant invasions simultaneously, but may be difficult to disentangle. In the present study, plants of the range-expanding species Bunias orientalis from native, invasive and naturalised, not yet invasive populations were compared in a field common garden over two years. Plants were grown under two nitrate-regimes and multiple traits regarding growth, defence, antagonist loads and reproduction were measured. A rank-based clustering approach was used to assign correlated traits to distinct suites. These suites were analysed for "syndromes" that are expressed as a function of population origin and/or fertilisation treatment and might represent different invasion mechanisms. Indeed, distinct suites of traits were differentially affected by these factors. The results suggest that several preadaptation properties, such as certain growth characteristics and intraspecific chemical variation, as well as post-introduction adaptations to antagonists and resource availability in novel habitats, are candidate mechanisms that facilitate the success of invasive B. orientalis in parallel. It was concluded that rank-based clustering is a robust and expedient approach to integrate multiple traits for elucidating invasion syndromes within individual species. Studying a multitude of traits at different life-history and establishment stages of plants grown under distinct resource treatments reveals species-specific trade-offs and resource sinks and simplifies the interpretation of trait functions for the potential invasive success of plants.
Thirty-seven alien plant species, pre-identified by horizon scanning exercises were prioritised for pest risk analysis (PRA) using a modified version of the EPPO Prioritisation Process designed to be compliant with the EU Regulation 1143/2014. In Stage 1, species were categorised into one of four lists – a Residual List, EU List of Minor Concern, EU Observation List and the EU List of Invasive Alien Plants. Only those species included in the latter proceeded to the risk management stage where their priority for PRA was assessed. Due to medium or high spread potential coupled with high impacts twenty-two species were included in the EU List of Invasive Alien Plants and proceeded to Stage 2. Four species (Ambrosia trifida, Egeria densa, Fallopia baldschuanica and Oxalis pes-caprae) were assigned to the EU Observation List due to moderate or low impacts. Albizia lebbeck, Clematis terniflora, Euonymus japonicus, Lonicera morrowii, Prunus campanulata and Rubus rosifolius were assigned to the residual list due to a current lack of information on impacts. Similarly, Cornus sericea and Hydrilla verticillata were assigned to the Residual List due to unclear taxonomy and uncertainty in native status, respectively. Chromolaena odorata, Cryptostegia grandiflora and Sphagneticola trilobata were assigned to the Residual List as it is unlikely they will establish in the Union under current climatic conditions. In the risk management stage, Euonymus fortunei, Ligustrum sinense and Lonicera maackii were considered a low priority for PRA as they do not exhibit invasive tendencies despite being widely cultivated in the EU over several decades. Nineteen species were identified as having a high priority for a PRA (Acacia dealbata, Ambrosia confertiflora, Andropogon virginicus, Cardiospermum grandiflorum, Celastrus orbiculatus, Cinnamomum camphora, Cortaderia jubata, Ehrharta calycina, Gymnocoronis spilanthoides, Hakea sericea, Humulus scandens, Hygrophila polysperma, Lespedeza cuneata, Lygodium japonicum, Pennisetum setaceum, Prosopis juliflora, Sapium sebiferum, Pistia stratiotes and Salvinia molesta).
The value of plant ecological datasets with hundreds or thousands of species is principally determined by the taxonomic accuracy of their plant names. However, combining existing lists of species to assemble a harmonized dataset that is clean of taxonomic errors can be a difficult task for non-taxonomists. Here, we describe the range of taxonomic difficulties likely to be encountered during dataset assembly and present an easy-to-use taxonomic cleaning protocol aimed at assisting researchers not familiar with the finer details of taxonomic cleaning. The protocol produces a final dataset (FD) linked to a companion dataset (CD), providing clear details of the path from existing lists to the FD taken by each cleaned taxon. Taxa are checked off against ten categories in the CD that succinctly summarize all taxonomic modifications required. Two older, publicly-available lists of naturalized Asteraceae in Australia were merged into a harmonized dataset as a case study to quantify the impacts of ignoring the critical process of taxonomic cleaning in invasion ecology. Our FD of naturalized Asteraceae contained 257 species and infra-species. Without implementation of the full cleaning protocol, the dataset would have contained 328 taxa, a 28% overestimate of taxon richness by 71 taxa. Our naturalized Asteraceae CD described the exclusion of 88 names due to nomenclatural issues (e.g. synonymy), the inclusion of 26 updated currently accepted names and four taxa newly naturalized since the production of the source datasets, and the exclusion of 13 taxa that were either found not to be in Australia or were in fact doubtfully naturalized. This study also supports the notion that automated processes alone will not be enough to ensure taxonomically clean datasets, and that manual scrutiny of data is essential. In the long term, this will best be supported by increased investment in taxonomy and botany in university curricula.