14 research outputs found

    Changes in pathways and vectors of biological invasions in Northwest Europe

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    We assessed how establishment patterns of non-native freshwater, marine and terrestrial species into Northwest Europe (using Great Britain, France, Belgium and the Netherlands as the study countries) have changed over time, and identified the prevalent pathways and vectors of recent arrivals. Data were extracted from 33 sources on (a) presence/absence and (b) first year of observation in the wild in each country, and (c) continent(s) of origin, (d) invasion pathway(s), (e) invasion vector(s) and (f) environment(s) for 359 species, comprising all non-native Mollusca, Osteichthyes (bony fish), Anseriformes (wildfowl) and Mammalia, and non-native invasive Angiospermae present in the area. Molluscs, fish and wildfowl, particularly those originating from South America, arrived more recently into Northwest Europe than other groups, particularly mammals, invasive plants and species originating from North America. Non-deliberate introductions, those of aquatic species and those from elsewhere in Europe and/or Asia increased strongly in importance after the year 2000 and were responsible for 69, 83 and 89 % of new introductions between 2001 and 2015, respectively. Non-deliberate introductions and those from Asia and North America contributed significantly more to introductions of invasive species in comparison to other non-native species. From the 1960s, ornamental trade has increased in importance relative to other vectors and was responsible for all deliberate introductions of study groups since 2001. Non-deliberate introductions of freshwater and marine species originating from Southeast Europe and Asia represent an increasingly important ecological and economic threat to Northwest Europe. Invertebrates such as molluscs may be particularly dangerous due to their small size and difficulties in detection. Prevention of future invasions in this respect will require intensive screening of stowaways on boats and raising of public awareness.Research leading to this study was funded by the European Regional Development Fund through the EU co-funded Interreg 2Seas project RINSE (reducing the impact of non-native species in Europe; www.rinse-europe.eu), which seeks to improve awareness of the threats posed by INNS, and the methods to address them. AZ and BG received financial support from RINSE. AZ is supported by a Postdoctoral Research Fellowship of the University of Nottingham, Malaysia Campus. BG holds a Postdoctoral Research Fellowship from the Spanish Ministry of Economy and Competitiveness (JCI-2012-11908)

    Sambucus javanica Reinw. ex Blume Viburnaceae

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    Ebulum javanicum (Reinw. ex Blume) Hosok.; Phyteuma bipinnata Lour.; Phyteuma cochinchinensis Lour.; Sambucus argyi H.Lév.; Sambucus chinensis var. pinnatilobatus G.W.Hu; Sambucus ebuloides Desv. ex DC.; Sambucus henriana Samutina; Sambucus phyteumoides DC.; Sambucus thunbergiana Blume ex Miq.; Sambucus thunbergii G.Don. (POWO 2020

    Natural enemies from South Africa for biological control of Lagarosiphon major (Ridl.) Moss ex Wager (Hydrocharitaceae) in Europe

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    The non-native invasive plant, Lagarosiphon major (Hydrocharitaceae) is a submersed aquatic macrophyte that poses a significant threat to water bodies in Europe. Dense infestations prove difficult to manage using traditional methods. In order to initiate a biocontrol programme, a survey for natural enemies of Lagarosiphon was conducted in South Africa. Several phytophagous species were recorded for the first time, with at least three showing notable promise as candidate agents. Amongst these, a leaf-mining fly, Hydrellia sp. (Ephydridae) that occurred over a wide distribution causes significant leaf damage despite high levels of parasitism by braconid wasps. Another yet unidentified fly was recorded mining the stem of L. major. Two leaf-feeding and shoot boring weevils, cf. Bagous sp. (Curculionidae) were recorded damaging the shoot tips and stunting the growth of the stem. Several leaf-feeding lepidopteran species (Nymphulinae) were frequently recorded, but are expected to feed on a wide range of plant species and are not considered for importation before other candidates are assessed. The discovery of several natural enemies in the country of origin improves the biological control prospects of L. major in Europe

    Efficient distinction of invasive aquatic plant species from non-invasive related species using DNA barcoding

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    Biological invasions are regarded as threats to global biodiversity. Among invasive aliens, a number of plant species belonging to the genera Myriophyllum, Ludwigia and Cabomba, and to the Hydrocharitaceae family pose a particular ecological threat to water bodies. Therefore, one would try to prevent them from entering a country. However, many related species are commercially traded, and distinguishing invasive from non-invasive species based on morphology alone is often difficult for plants in a vegetative stage. In this regard, DNA barcoding could become a good alternative. In this study, 242 samples belonging to 26 species from 10 genera of aquatic plants were assessed using the chloroplast loci trnH-psbA, matK and rbcL. Despite testing a large number of primer sets and several PCR protocols, the matK locus could not be amplified or sequenced reliably and therefore was left out of the analysis. Using the other two loci, eight invasive species could be distinguished from their respective related species, a ninth one failed to produce sequences of sufficient quality. Based on the criteria of universal application, high sequence divergence and level of species discrimination, the trnH-psbA noncoding spacer was the best performing barcode in the aquatic plant species studied. Thus, DNA barcoding may be helpful with enforcing a ban on trade of such invasive species, such as is already in place in the Netherlands. This will become even more so once DNA barcoding would be turned into machinery routinely operable by a nonspecialist in botany and molecular genetics

    Predicting alpha diversity of African rain forests: models based on climate and satellite-derived data do not perform better than a purely spatial model

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    Aim Our aim was to evaluate the extent to which we can predict and map tree alpha diversity across broad spatial scales either by using climate and remote sensing data or by exploiting spatial autocorrelation patterns. Location Tropical rain forest, West Africa and Atlantic Central Africa. Methods Alpha diversity estimates were compiled for trees with diameter at breast height ≥10cm in 573 inventory plots. Linear regression (ordinary least squares, OLS) and random forest (RF) statistical techniques were used to project alpha diversity estimates at unsampled locations using climate data and remote sensing data [Moderate Resolution Imaging Spectroradiometer (MODIS), normalized difference vegetation index (NDVI), Quick Scatterometer (QSCAT), tree cover, elevation]. The prediction reliabilities of OLS and RF models were evaluated using a novel approach and compared to that of a kriging model based on geographic location alone. Results The predictive power of the kriging model was comparable to that of OLS and RF models based on climatic and remote sensing data. The three models provided congruent predictions of alpha diversity in well-sampled areas but not in poorly inventoried locations. The reliability of the predictions of all three models declined markedly with distance from points with inventory data, becoming very low at distances >50km. According to inventory data, Atlantic Central African forests display a higher mean alpha diversity than do West African forests. Main conclusions The lower tree alpha diversity in West Africa than in Atlantic Central Africa may reflect a richer regional species pool in the latter. Our results emphasize and illustrate the need to test model predictions in a spatially explicit manner. Good OLS or RF model predictions from inventory data at short distance largely result from the strong spatial autocorrelation displayed by both the alpha diversity and the predictive variables rather than necessarily from causal relationships. Our results suggest that alpha diversity is driven by history rather than by the contemporary environment. Given the low predictive power of models, we call for a major effort to broaden the geographical extent and intensity of forest assessments to expand our knowledge of African rain forest diversity. © 2011 Blackwell Publishing Ltd

    Predicting alpha diversity of African rain forests: models based on climate and satellite-derived data do not perform better than a purely spatial model

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    Aim: Our aim was to evaluate the extent to which we can predict and map tree alpha diversity across broad spatial scales either by using climate and remote sensing data or by exploiting spatial autocorrelation patterns.Location: Tropical rain forest, West Africa and Atlantic Central Africa.Methods: Alpha diversity estimates were compiled for trees with diameter at breast height ≥ 10 cm in 573 inventory plots. Linear regression (ordinary least squares, OLS) and random forest (RF) statistical techniques were used to project alpha diversity estimates at unsampled locations using climate data and remote sensing data [Moderate Resolution Imaging Spectroradiometer (MODIS), normalized difference vegetation index (NDVI), Quick Scatterometer (QSCAT), tree cover, elevation]. The prediction reliabilities of OLS and RF models were evaluated using a novel approach and compared to that of a kriging model based on geographic location alone.Results: The predictive power of the kriging model was comparable to that of OLS and RF models based on climatic and remote sensing data. The three models provided congruent predictions of alpha diversity in well-sampled areas but not in poorly inventoried locations. The reliability of the predictions of all three models declined markedly with distance from points with inventory data, becoming very low at distances ≥ 50 km. According to inventory data, Atlantic Central African forests display a higher mean alpha diversity than do West African forests.Main conclusions: The lower tree alpha diversity in West Africa than in Atlantic Central Africa may reflect a richer regional species pool in the latter. Our results emphasize and illustrate the need to test model predictions in a spatially explicit manner. Good OLS or RF model predictions from inventory data at short distance largely result from the strong spatial autocorrelation displayed by both the alpha diversity and the predictive variables rather than necessarily from causal relationships. Our results suggest that alpha diversity is driven by history rather than by the contemporary environment. Given the low predictive power of models, we call for a major effort to broaden the geographical extent and intensity of forest assessments to expand our knowledge of African rain forest diversity.</p
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