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Dataset results
92 results for “Impatiens glandulifera”
Impatiens glandulifera Royle (BR0000011814993)
Belgium Herbarium image of <a href="https://www.plantentuinmeise.be">Meise Botanic Garden</a>.
Impatiens glandulifera Royle (BR0000015268389V)
Belgium Herbarium image of <a href="https://www.plantentuinmeise.be">Meise Botanic Garden</a>.
Impatiens glandulifera Royle (BR0000011815440)
Belgium Herbarium image of <a href="https://www.plantentuinmeise.be">Meise Botanic Garden</a>.
Impatiens glandulifera Royle (BR0000011153337)
Belgium Herbarium image of <a href="https://www.plantentuinmeise.be">Meise Botanic Garden</a>.
Impatiens glandulifera Royle (BR0000011814962)
Belgium Herbarium image of <a href="https://www.plantentuinmeise.be">Meise Botanic Garden</a>.
Impatiens glandulifera Royle (BR0000014445668)
Belgium Herbarium image of <a href="https://www.plantentuinmeise.be">Meise Botanic Garden</a>.
Impatiens glandulifera Royle (BR0000010681206)
Belgium Herbarium image of <a href="https://www.plantentuinmeise.be">Meise Botanic Garden</a>.
Data from: Invasive Impatiens glandulifera: a driver of changes in native vegetation?
<p class="western"><span>Biological invasions are one of the major threats to biodiversity worldwide and contribute to changing community patterns and ecosystem processes. However, it is often not obvious whether an invader is the "driver" causing ecosystem changes or a "passenger" which is facilitated by previous ecosystem changes. Causality of the impact can be demonstrated by experimental removal of the invader or introduction into a native community. <span>Using such an experimental approach, we tested whether the impact of the invasive plant </span><i>Impatiens glandulifera</i><span> on native vegetation is causal,</span><i> </i><span>and whether the impact is habitat-dependent. We conducted a field study comparing invaded and uninvaded plots with plots from which </span><i>I. glandulifera</i><span> was removed and plots where </span><i>I. glandulifera</i><span> was planted within two riparian habitats, alder forests and meadows. A negative impact of planting</span><i> I. glandulifera</i><span> and a concurrent positive effect of removal</span><i> </i><span>on the native vegetation indicated a causal effect of </span><i>I. glandulifera</i><span> on total native biomass and growth of </span><i>Urtica dioica</i><span>. Species </span><span>α</span><span>-diversity and composition were not affected by </span><i>I. glandulifera</i><span> manipulations. Thus,</span><i> I. glandulifera</i><span> had a causal but low effect on the native vegetation.</span><i> </i><span>The impact depended slightly on habitat as only the effect of </span><i>I. glandulifera</i><span> planting on total biomass was slightly stronger in alder forests than meadows. We suggest that </span><i>I. glandulifera</i><span> is a "back-seat driver" of changes, which is facilitated by previous ecosystem changes but is also a driver of further changes. Small restrictions of growth of the planted </span><i>I. glandulifera</i><span> and general association of </span><i>I. glandulifera</i><span> with disturbances indicate characteristics of a back-seat driver. For management of </span><i>I. glandulifera</i><span> populations this requires habitat restoration along with removal of the invader.</span></span></p>
Fig. 1. P in Impatiens glandulifera, a new host of the tortrix Pristerognatha fuligana in Bulgaria
Fig. 1. P. fuligana's larva in stem of I. glandulifera.
Data from: Invasive Impatiens glandulifera: a driver of changes in native vegetation?
Open the record for dataset details and reuse information.
Supplementary material 3 from: Bieberich J, Feldhaar H, Lauerer M (2020) Micro-habitat and season dependent impact of the invasive Impatiens glandulifera on native vegetation. NeoBiota 57: 109-131. https://doi.org/10.3897/neobiota.57.51331
Figure S1. Initial model of the piecewise structural equation modeling (SEM) for summer (A) and spring (B)
Supplementary material 4 from: Bieberich J, Feldhaar H, Lauerer M (2020) Micro-habitat and season dependent impact of the invasive Impatiens glandulifera on native vegetation. NeoBiota 57: 109-131. https://doi.org/10.3897/neobiota.57.51331
Table S1. Result of the automated model selection approach identifying environmental variables that affected the cover of Impatiens glandulifera in summer 2016 and spring 2017
Supplementary material 7 from: Bieberich J, Feldhaar H, Lauerer M (2020) Micro-habitat and season dependent impact of the invasive Impatiens glandulifera on native vegetation. NeoBiota 57: 109-131. https://doi.org/10.3897/neobiota.57.51331
Figure S3. Micro-habitat specific impact of I. glandulifera on the resident plant species composition
Impatiens glandulifera SNP and SilicoDArT genotyping data
<p>We conducted genomic characterization based on SNP and SilicoDArT markers on the invasive Himalayan balsam (<i>Impatiens glandulifera</i>) plants originating from the native and non-native regions of their distribution. When genetic relationships were explored by PCoA based on SNP and SilicoDArT marker data, the first, second and third principal coordinates explained altogether 37.4% and 31.0% of the variability, respectively. Samples from the UK, Canada and Pakistan grouped together, while Indian plants were clearly distinct based on SNP markers but relatively close to the UK-Canada-Pakistan group based on SilicoDArT markers. Constructed trees differentiated the individuals into clusters resembling the patterns observed by PCoA.<span> The Bayesian BAPS analysis revealed that the individuals were distributed in seven clusters, representing samples from each of the four Finnish populations, India, Pakistan and the combination of the UK and Canada. Similar clustering was visible in the constructed UPGMA tree. The Indian cluster did not display any ancestral gene flow with the others, while the Pakistani cluster showed ancestral gene flow only with the combined UK and Canada cluster. Furthermore, the latter cluster displayed ancestral gene flow with the Finnish populations varying from 0% to 3.1%. The AMOVA analysis showed that 45% and 26% of genetic variation was present among the <i>I. glandulifera</i> groups/populations and the rest within them based on SNP and SilicoDArT markers, respectively. Overall, the Bayesian BAPS analysis</span> <span>and the following gene flow network were the most informative tools for resolving relationships among native and introduced plants. </span></p>
Supplementary material 2 from: Najberek K, Solarz W, Wysoczański W, Węgrzyn E, Olejniczak P (2023) Flowers of Impatiens glandulifera as hubs for both pollinators and pathogens. NeoBiota 87: 1-26. https://doi.org/10.3897/neobiota.87.102576
Data on I. glandulifera individuals, bumblebees pollinating them, and additional information on statistical analyses
Impatiens glandulifera SNP and SilicoDArT genotyping data
Open the record for dataset details and reuse information.
Data from: Low genetic diversity despite multiple introductions of the invasive plant species Impatiens glandulifera in Europe
Open the record for dataset details and reuse information.
Supplementary material 5 from: Bieberich J, Feldhaar H, Lauerer M (2020) Micro-habitat and season dependent impact of the invasive Impatiens glandulifera on native vegetation. NeoBiota 57: 109-131. https://doi.org/10.3897/neobiota.57.51331
Table S2. Abbreviations of species names as shown in Figure 5
Supplementary material 2 from: Bieberich J, Feldhaar H, Lauerer M (2020) Micro-habitat and season dependent impact of the invasive Impatiens glandulifera on native vegetation. NeoBiota 57: 109-131. https://doi.org/10.3897/neobiota.57.51331
Maximum vegetation height in summer and spring
Supplementary material 10 from: Bieberich J, Feldhaar H, Lauerer M (2020) Micro-habitat and season dependent impact of the invasive Impatiens glandulifera on native vegetation. NeoBiota 57: 109-131. https://doi.org/10.3897/neobiota.57.51331
Dataset environment and vegetation characteristics
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