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859 results for “neobiota”
Supplementary material 1 from: Early R, González-Moreno P, Murphy ST, Day R (2018) Forecasting the global extent of invasion of the cereal pest Spodoptera frugiperda, the fall armyworm. NeoBiota 40: 25-50. https://doi.org/10.3897/neobiota.40.28165
Supplementary material : Explanation note: Table S1. Summary of evidence for fall armyworm developmental and population responses to the environment extracted from literature sources. Figure S1. Effect of different sub-sampling proportions and pseudo-absence selection diameters on model predictions (maps). Figure S2. Effect of different sub-sampling proportions and pseudo-absence selection diameters on Balanced Accuracy. Figure S3. Histograms of each environmental variable in 10 arc-minute grid-cells from which the fall armyworm is recorded. Figure S4. Multivariate Environmental Similarity Surface analysis. Figure S5. Empirically measured environmental effects on fall armyworm life cycle. Figure S6. Trade and passenger air transportation within Africa.
Supplementary material 1 from: Clarke S, Stenekes N, Kancans R, Woodland C, Robinson A (2018) Undelivered risk: A counter-factual analysis of the biosecurity risk avoided by inspecting international mail articles. NeoBiota 40: 73-86. https://doi.org/10.3897/neobiota.40.28840
Variogram of the residuals of the random forest model : Explanation note: A variogram designed to visually assess whether there is spatial correlation present in the residuals of the random forest model. This does not indicate any spatial correlation.
Supplementary material 3 from: Iannone BV III, Potter KM, Guo Q, Jo I, Oswalt CM, Fei S (2018) Environmental harshness drives spatial heterogeneity in biotic resistance. NeoBiota 40: 87-105. https://doi.org/10.3897/neobiota.40.28558
Section-level standardised slope estimates for the 91 ecological sections from initial models of invasive richness and cover in response to four metrics of evolutionary relatedness—PSC, PSV, PD and PSE :
Supplementary material 2 from: Iannone BV III, Potter KM, Guo Q, Jo I, Oswalt CM, Fei S (2018) Environmental harshness drives spatial heterogeneity in biotic resistance. NeoBiota 40: 87-105. https://doi.org/10.3897/neobiota.40.28558
Description of differences between Northern and Southern FIA Regions in invasive plant species monitoring protocols :
Supplementary material 1 from: Iannone BV III, Potter KM, Guo Q, Jo I, Oswalt CM, Fei S (2018) Environmental harshness drives spatial heterogeneity in biotic resistance. NeoBiota 40: 87-105. https://doi.org/10.3897/neobiota.40.28558
Locations of Northern and Southern FIA Regions and of the ecological domains, provinces and sections in which study plots were located :
Supplementary material 2 from: Martín-Forés I, Casado MA, Castro I, del Pozo A, Molina-Montenegro MA, de Miguel JM, Acosta-Gallo B (2018) Variation in phenology and overall performance traits can help to explain the plant invasion process amongst Mediterranean ecosystems. NeoBiota 41: 67-89. https://doi.org/10.3897/neobiota.41.29965
Supplementary material 2 from: Martín-Forés I, Casado MA, Castro I, del Pozo A, Molina-Montenegro MA, de Miguel JM, Acosta-Gallo B (2018) Variation in phenology and overall performance traits can help to explain the plant invasion process amongst Mediterranean ecosystems. NeoBiota 41: 67-89. https://doi.org/10.3897/neobiota.41.29965
Supplementary material 2 from: Nkuna KV, Visser V, Wilson JRU, Kumschick S (2018) Global environmental and socio-economic impacts of selected alien grasses as a basis for ranking threats to South Africa. NeoBiota 41: 19-65. https://doi.org/10.3897/neobiota.41.26599
Figure S2 : Explanation note: The impact magnitude of the 48 studied alien grasses across different habitats. The impact magnitudes on the x-axis are the least-square means of the impact scores as derived from a cumulative link mixed effects model. On the y-axis are the habitat types impacted by alien grasses and in brackets is the number of species with records in that habitat. The points represent the impact magnitudes and the error bars represent 95 % confidence intervals. Letters on the right side of the confidence intervals are level groupings indicating no significant differences among the habits. Comparisons are Tukey adjusted.
Supplementary material 4 from: Martín-Forés I, Casado MA, Castro I, del Pozo A, Molina-Montenegro MA, de Miguel JM, Acosta-Gallo B (2018) Variation in phenology and overall performance traits can help to explain the plant invasion process amongst Mediterranean ecosystems. NeoBiota 41: 67-89. https://doi.org/10.3897/neobiota.41.29965
Supplementary material 4 from: Martín-Forés I, Casado MA, Castro I, del Pozo A, Molina-Montenegro MA, de Miguel JM, Acosta-Gallo B (2018) Variation in phenology and overall performance traits can help to explain the plant invasion process amongst Mediterranean ecosystems. NeoBiota 41: 67-89. https://doi.org/10.3897/neobiota.41.29965
Supplementary material 1 from: Nkuna KV, Visser V, Wilson JRU, Kumschick S (2018) Global environmental and socio-economic impacts of selected alien grasses as a basis for ranking threats to South Africa. NeoBiota 41: 19-65. https://doi.org/10.3897/neobiota.41.26599
Supplementary material 1 from: Nkuna KV, Visser V, Wilson JRU, Kumschick S (2018) Global environmental and socio-economic impacts of selected alien grasses as a basis for ranking threats to South Africa. NeoBiota 41: 19-65. https://doi.org/10.3897/neobiota.41.26599
Supplementary material 3 from: Martín-Forés I, Casado MA, Castro I, del Pozo A, Molina-Montenegro MA, de Miguel JM, Acosta-Gallo B (2018) Variation in phenology and overall performance traits can help to explain the plant invasion process amongst Mediterranean ecosystems. NeoBiota 41: 67-89. https://doi.org/10.3897/neobiota.41.29965
Supplementary material 3 from: Martín-Forés I, Casado MA, Castro I, del Pozo A, Molina-Montenegro MA, de Miguel JM, Acosta-Gallo B (2018) Variation in phenology and overall performance traits can help to explain the plant invasion process amongst Mediterranean ecosystems. NeoBiota 41: 67-89. https://doi.org/10.3897/neobiota.41.29965
Supplementary material 1 from: Martín-Forés I, Casado MA, Castro I, del Pozo A, Molina-Montenegro MA, de Miguel JM, Acosta-Gallo B (2018) Variation in phenology and overall performance traits can help to explain the plant invasion process amongst Mediterranean ecosystems. NeoBiota 41: 67-89. https://doi.org/10.3897/neobiota.41.29965
Figure S1 : Explanation note: Distribution of Leontodonsaxatilis, Hypochaerisglabra and Trifoliumglomeratum in both the native (Spain) and the introduced (Chile) ranges.
Supplementary material 5 from: Cabezas MP, Ros M, Santos AM, Martínez-Laiz G, Xavier R, Montelli L, Hoffman R, Fersi A, Dauvin JC, Guerra-García JM (2019) Unravelling the origin and introduction pattern of the tropical species Paracaprella pusilla Mayer, 1890 (Crustacea, Amphipoda, Caprellidae) in temperate European waters: first molecular insights from a spatial and temporal perspective. NeoBiota 47: 43-80. https://doi.org/10.3897/neobiota.47.32408
: Explanation note: A Phylogenetic tree of nuclear 28S rRNA. Unfortunately, this gene could not be amplified in P.tenuis species. In P.pusilla, only two haplotypes were detected, differing only by the presence of an indel. B Phylogenetic tree of nuclear ribosomal internal transcribed spacer (ITS). No variation was observed among P.pusilla sequences. Trees were rooted with Caprelladanilevskii and Caprellaliparotensis. Values at the nodes correspond to ML bootstrap support and Bayesian posterior probabilities, respectively.
Supplementary material 1 from: Amatangelo KL, Stevens L, Wilcox DA, Jackson ST, Sax DF (2018) Provenance of invaders has scale-dependent impacts in a changing wetland ecosystem. NeoBiota 40: 51-72. https://doi.org/10.3897/neobiota.40.28914
Supplementary material 1 from: Amatangelo KL, Stevens L, Wilcox DA, Jackson ST, Sax DF (2018) Provenance of invaders has scale-dependent impacts in a changing wetland ecosystem. NeoBiota 40: 51-72. https://doi.org/10.3897/neobiota.40.28914
Supplementary material 4 from: Haubrock PJ, Cuthbert RN, Yeo DCJ, Banerjee AK, Liu C, Diagne C, Courchamp F (2021) Biological invasions in Singapore and Southeast Asia: data gaps fail to mask potentially massive economic costs. In: Zenni RD, McDermott S, García-Berthou E, Essl F (Eds) The economic costs of biological invasions around the world. NeoBiota 67: 131-152. https://doi.org/10.3897/neobiota.67.64560
Extrapolated annual average costs for those invasive species known to be in Singapore with recorded costs in InvaCost
Supplementary material 1 from: Haubrock PJ, Cuthbert RN, Yeo DCJ, Banerjee AK, Liu C, Diagne C, Courchamp F (2021) Biological invasions in Singapore and Southeast Asia: data gaps fail to mask potentially massive economic costs. In: Zenni RD, McDermott S, García-Berthou E, Essl F (Eds) The economic costs of biological invasions around the world. NeoBiota 67: 131-152. https://doi.org/10.3897/neobiota.67.64560
Description of the procedure used for collecting and describing cost data in the InvaCost database (adapted from Diagne et al. 2020)
Supplementary material 5 from: Haubrock PJ, Cuthbert RN, Yeo DCJ, Banerjee AK, Liu C, Diagne C, Courchamp F (2021) Biological invasions in Singapore and Southeast Asia: data gaps fail to mask potentially massive economic costs. In: Zenni RD, McDermott S, García-Berthou E, Essl F (Eds) The economic costs of biological invasions around the world. NeoBiota 67: 131-152. https://doi.org/10.3897/neobiota.67.64560
Relationships between trade value and recorded cost entries per country in InvaCost, as well as land area and human population with total cost
Supplementary material 4 from: Cuthbert RN, Bartlett AC, Turbelin AJ, Haubrock PJ, Diagne C, Pattison Z, Courchamp F, Catford JA (2021) Economic costs of biological invasions in the United Kingdom. In: Zenni RD, McDermott S, García-Berthou E, Essl F (Eds) The economic costs of biological invasions around the world. NeoBiota 67: 299-328. https://doi.org/10.3897/neobiota.67.59743
Total costs of species with individual cost entries, alongside first record years and introduction pathways
Supplementary material 8 from: Renault D, Manfrini E, Leroy B, Diagne C, Ballesteros-Mejia L, Angulo E, Courchamp F (2021) Biological invasions in France: Alarming costs and even more alarming knowledge gaps. In: Zenni RD, McDermott S, García-Berthou E, Essl F (Eds) The economic costs of biological invasions around the world. NeoBiota 67: 191-224. https://doi.org/10.3897/neobiota.67.59134
List of the 68 invasive alien species in metropolitan France for which no economic cost was documented in our database
Supplementary material 6 from: Renault D, Manfrini E, Leroy B, Diagne C, Ballesteros-Mejia L, Angulo E, Courchamp F (2021) Biological invasions in France: Alarming costs and even more alarming knowledge gaps. In: Zenni RD, McDermott S, García-Berthou E, Essl F (Eds) The economic costs of biological invasions around the world. NeoBiota 67: 191-224. https://doi.org/10.3897/neobiota.67.59134
Categorical representation of the cumulated costs caused by invasive alien species in metropolitan France and French overseas over the period 1993–2018
Supplementary material 7 from: Renault D, Manfrini E, Leroy B, Diagne C, Ballesteros-Mejia L, Angulo E, Courchamp F (2021) Biological invasions in France: Alarming costs and even more alarming knowledge gaps. In: Zenni RD, McDermott S, García-Berthou E, Essl F (Eds) The economic costs of biological invasions around the world. NeoBiota 67: 191-224. https://doi.org/10.3897/neobiota.67.59134
For each French region, listing of the taxa for which we had cost information in the InvaCost database over the time range 1993–2018
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