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56 results for “Swiss Alps”
FIGURE 3 in One century of vegetation change on Isla Persa, a nunatak in the Bernina massif in the Swiss Alps
FIGURE 3. Map of China (excluding Taiwan) and its seven subunits as used in this catalogue. NW: Northwestern China. NO: Northern China. NE: Northeastern China. WP: Western Chinese Plateau. SW: Southwestern China. CE: Central China. SE: Southeastern China. Map adapted from Lelej (2002).
Hypocenter-based 3D Imaging of Active Faults: Method and Applications in the Southwestern Swiss Alps [Dataset]
<p>Data repository to the JGR publication of Truttmann et al. (2023), including following datasets for the two analyzed earthquake sequences (St. Léonard and Anzère)</p> <p>- Interactive 3D fault-network models</p> <p>- Focal mechanisms</p> <p>- Relocated hypocenter locations (hypoDD)</p> <p>- Station networks</p> <p>- hypoDD parameters</p>
Data from: Reduced genetic diversity, increased isolation and multiple introductions of invasive giant hogweed in the western Swiss Alps
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Bird communities in the Swiss Alps, 1999-2018, abundance data
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Data from: Evidence of local adaptation to fine- and coarse-grained environmental variability in Poa alpina in the Swiss Alps
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Data from: Snowbeds are more affected than other subalpine-alpine plant communities by climate change in the Swiss Alps
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Data from: Postglacial recolonizations, watershed crossings and human translocations shape the distribution of chub lineages around the Swiss Alps
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What are the most crucial soil variables for predicting the distribution of mountain plant species? a comprehensive study in the Swiss Alps
Aim: To investigate the potential of a large range of soil variables to improve topo-climatic models of plant species distributions in a temperate mountain region encompassing complex relief. Location: The western Swiss Alps. Methods: Fitting topo-climatic models for >60 plant species across >250 sites with and without added soil predictor variables (>30). Testing included: (i) which soil variables improve plant species distribution models; (ii) whether an optimal subset of soil variables can improve models for the majority of species and habitat types; and (iii) how much variation in plant species distributions soil variables alone explain. Results: Geochemical variables (i.e., CaO, pH and inorganic carbon) and a drainage indicator (i.e., bulk soil water content) improved the predictive abilities of the models across the large majority of alpine plant species. The improvement of the models after the addition of soil information varied strongly between plant species and habitat types, but a trade-off was found between the number of soil variables and the associated gain in model performance. Finally, across all species, one specific combination of soil variables–bulk soil water content + total phosphorus + <i>δ</i><sup>13</sup>C–outperformed the commonly used topo-climatic variables. Main conclusions: Several soil variables significantly increased the predictive power of plant species distribution models in the temperate mountain region. Geochemical and drainage variables proved most important.
FIGURE 2. O. rhilensis Stierlin, 1888 in Otiorhynchus (Nihus) grischunensis sp. n. — a new species of the O. rhilensis species group from the Swiss Alps (Curculionidae, Entiminae)
FIGURE 2. O. rhilensis Stierlin, 1888 dorsal (above) and lateral view (down) – E-Rila, Belmeken.
Supplementary material 2 from: Shaw MR, Giannotta M, Herrera-Flórez AF, Klopfstein S (2021) Two males, one female: triplet-style mating behaviour in the Darwin wasp Xorides ater (Gravenhorst, 1829) (Hymenoptera, Ichneumonidae, Xoridinae) in the Swiss Alps. Alpine Entomology 5: 15-22. https://doi.org/10.3897/alpento.5.64803
Figure S1
Supplementary material 3 from: Cosandey V, Broennimann O, Guisan A (2022) Modeling the distribution of coprophagous beetle species in the Western Swiss Alps. Alpine Entomology 6: 25-38. https://doi.org/10.3897/alpento.6.83730
Figure S3
Supplementary material 2 from: Cosandey V, Broennimann O, Guisan A (2022) Modeling the distribution of coprophagous beetle species in the Western Swiss Alps. Alpine Entomology 6: 25-38. https://doi.org/10.3897/alpento.6.83730
Figure S2
Supplementary material 1 from: Cosandey V, Broennimann O, Guisan A (2022) Modeling the distribution of coprophagous beetle species in the Western Swiss Alps. Alpine Entomology 6: 25-38. https://doi.org/10.3897/alpento.6.83730
Figure S1
Linked collectors and determiners for: Notes on the genus Dictyogenus Klapálek, 1904 (Plecoptera, Perlodidae) in the Austrian, Italian, Slovenian and Swiss Alps, with the description of six new species.
Natural history specimen data linked to collectors and determiners held within, "Notes on the genus Dictyogenus Klapálek, 1904 (Plecoptera, Perlodidae) in the Austrian, Italian, Slovenian and Swiss Alps, with the description of six new species". Claims or attributions were made on Bionomia by volunteer Scribes, <a href="https://bionomia.net/dataset/d5904726-bcb3-4e99-88f6-8d3ae01d333c">https://bionomia.net/dataset/d5904726-bcb3-4e99-88f6-8d3ae01d333c</a> using specimen data from the dataset aggregated by the Global Biodiversity Information Facility, <a href="https://gbif.org/dataset/d5904726-bcb3-4e99-88f6-8d3ae01d333c">https://gbif.org/dataset/d5904726-bcb3-4e99-88f6-8d3ae01d333c</a>. Formatted as a Frictionless Data package.
What are the most crucial soil variables for predicting the distribution of mountain plant species? a comprehensive study in the Swiss Alps
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Data archive for the journal article "Black Carbon Aerosols in the Lower Free Troposphere are Heavily Coated in Summer but Largely Uncoated in Winter at Jungfraujoch in the Swiss Alps"
<p>Data archive for figures accompanying the journal article "Black carbon aerosols in the lower free troposphere are heavily coated in summer but largely uncoated in winter at Jungfraujoch in the Swiss Alps". In 2020 this article was accepted for publication in the journal <em>Geophysical Research Letters</em>. Data are uploaded in the form of Igor Pro experiment files (.pxp).</p>
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International Brain Laboratory public data
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OpenNeuro
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