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888 results for “Canary”
Fig. 2 in The discovery of Barretonus (Curculionidae: Cossoninae) in the Canary Islands: barcoding, morphology and description of new species
Fig. 2. Dorsal and lateral habitus: A – Barretonus auarita sp. nov.; B – B. daute sp. nov.
Fig. 1 in Two new Phylinae (Hemiptera: Heteroptera: Miridae) from the Canary Islands
Fig. 1. Systellonotus stysi sp. nov., paratype ♀ from Tenerife. a – habitus, b – head and thorax.
Fig. 1 in New wasps and bees for the fauna of the Canary Islands (Hymenoptera, Aculeata)
Fig. 1. Nesting site of Cerceris chlorotica near Costa Calma on Fuerteventura.
Fig. 1 in Philanthus triangulum (Hymenoptera; Crabronidae) new for the fauna of the Canary Islands
Fig. 1: Map of Tenerife with the location of the capture of Philanthus triangulum.
Fig. 2 in Philanthus triangulum (Hymenoptera; Crabronidae) new for the fauna of the Canary Islands
Fig. 2: The roof garden at San Eugenio.
Figure 277 in The genus Pholcus (Araneae, Pholcidae) in the Canary Islands
Figure 277. Known distribution of Pholcus species endemic to Madeira and North-West Africa.
Figure 276 in The genus Pholcus (Araneae, Pholcidae) in the Canary Islands
Figure 276. Known distribution of Pholcus species endemic to the Canary archipelago.
Individual variation in feeding performance and kinematics in the canary
<ol> <li><span>In granivorous songbirds, feeding is a complex process as seeds need to be dehusked before they can be consumed, making the feeding act a biomechanically challenging endeavour. However, most previous research has focused on how beak morphology affects feeding performance, while the influences of beak kinematics remain largely unknown. </span></li> <li><span>In this study, we hence investigated at the individual level how feeding performance (i.e. seed processing time and success rate) relates to both beak kinematics (i.e. beak tip speed, acceleration, frequency) and skill (i.e. seed handling tactics and cracking techniques) in the Canary (<em>Serinus</em> <em>canaria</em>). To do so, high-speed videos during feeding were recorded and subjected to automated tracking of beak tip movements.</span></li> <li><span>Better skills, i.e. accurate positioning of the seed for being split in half, reduced total seed handling time compared to more random positioning and crushing the husk into multiple, scattering fragments. Surprisingly, individual variation in beak speed, acceleration, or frequency generally did not relate to differences in performance. </span></li> <li><span>Thus, our data suggests that seed positioning precision, and hence the control of coordinated beak and tongue movement, is critical to minimize feeding durations in songbirds. Further studies are needed to explore whether this develops via a positive feedback between behaviour, learning and increased efficiency or if it relates to intrinsic differences.</span></li> </ol>
Gravity change data used in the paper "Insights into the magmatic feeding system of the 2021 eruption at Cumbre Vieja (La Palma, Canary Islands) inferred from gravity data modeling"
<p>Gravity changes data observed in the network between July 2021 and January 2022 </p> <p>Reference:</p> <p>Insights into the magmatic feeding system of the 2021 eruption at Cumbre Vieja (La Palma, Canary Islands) inferred from gravity data modeling <br> F. G. Montesinos1,7, S. Sainz-Maza2,7, D. Gómez-Ortiz3, J. Arnoso4,7, I. Blanco-Montenegro5,7, M. Benavent1,7 E. Vélez4,7, N. Sánchez6 and T. Martín-Crespo3</p> <p>1 Facultad de CC. Matemáticas, Universidad Complutense de Madrid. Plaza de Ciencias 3, 28040 Madrid, Spain.<br> 2 Observatorio Geofísico Central (IGN). C/ Alfonso XII, 3. 28014 Madrid, Spain.<br> 3 Dpt. Biología y Geología, Física y Química Inorgánica, ESCET, Universidad Rey Juan Carlos. C/Tulipán s/n, 28933 Móstoles, Madrid, Spain.<br> 4 Instituto de Geociencias (IGEO), CSIC-UCM. C/ Doctor Severo Ochoa, 7. 28040 Madrid, Spain.<br> 5 Departamento de Física, Escuela Politécnica Superior, Universidad de Burgos. Avda. de Cantabria s/n, 09006 Burgos, Spain.<br> 6 Instituto Geológico y Minero de España (IGME, CSIC), Unidad Territorial de Canarias, Alonso Alvarado, 43, 2A, 35003 Las Palmas de Gran Canaria, Spain.<br> 7 Research Group ‘Geodesia’, Universidad Complutense de Madrid, Spain.</p> <p><br> Corresponding author: Fuensanta G. Montesinos (fuensant@ucm.es)</p> <p>This research is supported by the project PID2019-104726GB-I00/AEI/10.13039/501100011033 funded by the Spanish Research Agency. Further, the University Complutense of Madrid (grants Financiación Grupos 2021, UCM 2022-GRFN14/22) and the Spanish Ministry of Science and Innovation (RD 1078/2021, funding for research activities of the CSIC-PIE project CSIC-LAPALMA-07) supported this research.</p>
Temporal variability of explosive activity at Tajogaite Volcano, Cumbre Vieja (Canary Islands), 2021 eruption from ground-based infrared photography and videography
<p>Supplementary material to: Temporal variability of explosive activity at Tajogaite Volcano, Cumbre Vieja (Canary Islands), 2021 eruption from ground-based infrared photography and videography (2023). </p> <p>Files are short infrared videos of explosive activity in the near-vent region of Tajogaite Volcano. Files are named by date of acquisition. </p>
IDW interpolation dataset of ash and tephra deposition following the 2021 Tajogaite volcanic eruption on La Palma, Canary Islands, Spain
<p>The compiled dataset is the result of a field collection campaign to measure the depth of the ash and tephra layer in the aftermath of the 2021 volcanic eruption (Tajogaite) on the island of La Palma, Canary Islands, Spain.</p> <p>The dataset consists of two files: a shapefile and a GeoTIFF raster. The shapefile is a point layer file that displays the location of all ash depth measurements (415 points) taken in the field. To improve our sampling near the crater, where safety and time constraints prevented field collection, we manually sampled additional drone-based measurements (66 points). We combined these data into a single dataset ("ash_depth"; 481 total points) that was then used as input for a spatial interpolation using Inverse Distance Weighting (IDW).</p> <p>The IDW interpolation was performed using the Spatial Analyst toolbox in ArcMap 10.8.1 (Esri, 2021). As an exact deterministic interpolation, IDW estimates pixels values of unknown points by using average distance and a weight between sample points (Watson & Philip, 1985). This is ideal for a dataset that includes many field measurements since IDW interpolates between the minimum and maximum of the collected data. The model parameters were adjusted manually but the best results were yielded using the default settings, with the exception of the output cell size. The output cell size was calibrated to 2 m. The IDW parameters can be viewed in Table 1.</p> <p>The sample point locations were resampled from the raster file to estimate the Root Square Mean Error (RMSE) and were saved to the shapefile as "ash_idw". The RMSE of the dataset is 0.34 m. For further inquiries please contact Christopher Shatto (email: christopher.shatto@uni-bayreuth.de).</p> <p> </p> <p>Please cite the data paper link to this repository as: </p> <p><strong>C. Shatto, F. Weiser and A. Walentowitz et al., Volcanic tephra deposition dataset based on interpolated field measurements following the 2021 Tajogaite Eruption on La Palma, Canary Islands, Spain, Data in Brief, https://doi.org/10.1016/j.dib.2023.109949</strong></p> <p> </p> <table> <tbody> <tr> <td>Power</td> <td>2</td> </tr> <tr> <td>Output cell size</td> <td>2</td> </tr> <tr> <td>Search neighborhood type</td> <td>Standard (circular)</td> </tr> <tr> <td>Major/minor semiaxis</td> <td>12161.79/12161.79</td> </tr> <tr> <td>Max/minimum neighbors</td> <td>15/10</td> </tr> <tr> <td>Sector type</td> <td>1</td> </tr> <tr> <td>Angle</td> <td>0</td> </tr> <tr> <td>Weight field</td> <td>None</td> </tr> </tbody> </table> <p> </p>
Using the Canary Breathing System for Panic Disorder Patients
ClinicalTrials.gov study NCT01955954. IPD Sharing: Not stated. Countries: 1. Publications: 1.
Individual variation in feeding performance and kinematics in the canary
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Colonization history of the Canary Islands endemic Lavatera acerifolia, (Malvaceae) unveiled with Genotyping-by-Sequencing data and niche modeling
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Data from: Niche evolution during allopatric and sympatric diversification of Aeonium (Crassulaceae) on the Canary Islands
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Perineuronal nets in HVC and plasticity in male canary song
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Changes in community-weighted trait mean, functional diversity, soil chemical properties and temperature along an elevational gradient in Tenerife, Canary Islands
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The non-dereliction in evolution: Trophic specialisation drives convergence in the radiation of red devil spiders (Araneae: Dysderidae) in the Canary Islands
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Data from: Species-level divergences in multiple functional traits between the two endemic subspecies of Blue Chaffinches Fringilla teydea in Canary Islands
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Morphological traits of the flora of the Canary Islands
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