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FIGURE 11 in Two species of the genus Anchistrocheles (Bairdioidea: Ostracoda: Crustacea) from Japan and their developmental characteristics for adaptation to interstitial environments
FIGURE 11. Anatomical location of brush-shaped organ in Anchistrocheles yamaguchii Yajima, 1987. A, anatomical location among appendages. B, high magnification. Male, SUM-CO-2500. L5, fifth limb; L6, sixth limb; L7, seventh limb. Scale: ca. 35µm for A, ca. 10µm for B.
FIGURE 8 in Two species of the genus Anchistrocheles (Bairdioidea: Ostracoda: Crustacea) from Japan and their developmental characteristics for adaptation to interstitial environments
FIGURE 8. Three-dimensional triangular (ternary) diagram of the carapace in four bairdioid species. L, length; H, height; W, width. (a), full diagram; (b), close-up view; (c), movement of the average value for each instar.
Change Detection in Dynamic Environments by Means of a Robotic Swarm - Digital Appendix
<p>Digital Appendix for my thesis Change Detection in Dynamic Environments by Means of a Robotic Swarm.</p> <p>In the zip-file you find a README that guides you through the structure and where to find the plots for the respective experiments.</p> <p><strong>Change Detection of Dynamic Environments by Means of a Robotic Swarm - Digital Appendix</strong></p> <p>The following folder structure holds all research data of my conducted experiments(h5-logfiles and plots). The Python-Script "show_h5.py" can be used to read out the logfile in h5-format (<em>$python3 show_h5.py expample_logfilename.h5</em>). However, this shouldn't be necessary because all plots are already generated.</p> <p>To find the results you want to see, this is a small guide through the structure:</p> <ol> <li> <p>First the trials are divided into the respective methods (BOCPD, PELT, DBB, DBBCPD). In the folders you find the experiments for the specific method.</p> </li> <li> <p>In the folders of BOCPD and PELT you find the results for the different feedback types and their combinations. The id for each feedback is noted in parentheses (e.g. XX_(id)_feedback_description). Feedback combinations have their ids added up (e.g. XX_(id1+...+idn)_feedback_description).</p> </li> <li> <p>In the folder to each feedback type the different test trials can be found. This means varying environment difficulties and parameter settings. In the name of the folders this information can be found (e.g. XX_method_environmentdifficulty_parametersetting).</p> </li> </ol> <p>All experiments follow the same procedure as long as it is stated otherwise. Each trial consists of 20 individual runs with a duration of 6000 seconds. At half time (3000 s) a change to the opposite fill ratio occurs (fill ratio of 1.0 defines a completely white and one of 0.0 a completely black environment).</p> <p><strong>Environment difficulty</strong></p> <ul> <li> <p>0901 --> easy environment, fill ratio changed from 0.9 to 0.1</p> </li> <li> <p>0703 --> easy environment, fill ratio changed from 0.7 to 0.3</p> </li> <li> <p>0604 --> easy environment, fill ratio changed from 0.6 to 0.4</p> </li> <li> <p>055045 --> easy environment, fill ratio changed from 0.55 to 0.45</p> </li> </ul> <p><strong>Parameter Setting</strong></p> <p>The setting is in the name of the folder composed of: feedbackID: intervalLength amountNeighbors</p> <ul> <li> <p>3c:50s3n --> feedback 3c with a 50s interval and 3 neighbors</p> </li> </ul> <p>In these folders all plots of the respective runs can be found showing a Boxplot of all 20 runs and for each run the swarm belief, the decision distribution and the reset histogram (before/after the change)</p>
Increasing landscape complexity enhances species richness of farmland arthropods, agri-environment schemes also abundance–A meta-analysis
<p>Article dataset</p>
Data from: A warmer environment can reduce sociability in an ectotherm
<p>The costs and benefits of being social vary with environmental conditions, so individuals must weigh the balance between these trade-offs in response to changes in the environment. Temperature is a salient environmental factor that may play a key role in altering the costs and benefits of sociality through its effects on food availability, predator abundance, and other ecological parameters. In ectotherms, changes in temperature also have direct effects on physiological traits linked to social behaviour, such as metabolic rate and locomotor performance. In light of climate change, it is therefore important to understand the potential effects of temperature on sociality. Here, we took advantage of a 'natural experiment' of threespine sticklebacks from contrasting thermal environments in Iceland: geothermally warmed water bodies (warm habitats) and adjacent ambient-temperature water bodies (cold habitats) that were either linked (sympatric) or physically distinct (allopatric). We first measured the sociability of wild-caught adult fish from warm and cold habitats after acclimation to a low and a high temperature. At both acclimation temperatures, fish from the allopatric warm habitat were less social than those from the allopatric cold habitat, whereas fish from sympatric warm and cold habitats showed no differences in sociability. To determine whether differences in sociability between thermal habitats in the allopatric population were heritable, we used a common garden breeding design where individuals from the warm and the cold habitat were reared at a low or high temperature for two generations. We found that sociability was indeed heritable but also influenced by rearing temperature, suggesting that thermal conditions during early life can play an important role in influencing social behaviour in adulthood. By providing the first evidence for a causal effect of rearing temperature on social behaviour, our study provides novel insights into how a warming world may influence sociality in animal populations.</p>
Goelz_Finkel_Kehlbeck_Herschbach_Bauer_Scheib_Deussen_Randerath_AFFORDANCE JUDGEMENTS IN REAL AND VIRTUAL ENVIRONMENTS
<p><strong>Dataset belongs to manuscript:</strong></p> <p><strong>From virtual to real environments when judging action opportunities: Are diagnostics and trainings transferable?</strong></p> <p>Milena S. Gölz<sup>1, 2 </sup>*, Lisa Finkel<sup>1, 2 </sup>*, Rebecca Kehlbeck<sup>3</sup>, Anne Herschbach<sup>1, 2, 4</sup>, Isabel Bauer<sup>1, 2</sup>, Jean P. P. Scheib<sup>1, 2</sup>, Oliver Deussen<sup>3</sup> & Jennifer Randerath<sup>1, 2</sup></p> <p><sup>1</sup> Department of Psychology, University of Konstanz, Konstanz, Germany</p> <p><sup>2</sup> Lurija Institute for Rehabilitation Science and Health Research, Allensbach, Germany</p> <p><sup>3</sup> Department of Computer and Information Science, Centre for the Advanced Study of Collective Behavior, University of Konstanz, Konstanz, Germany</p> <p><sup>4</sup> Department of Psychosomatic Medicine and Psychotherapy, Medical University Hospital Tuebingen, Tuebingen, Germany</p> <p> </p> <p>* Shared first authorship</p>
Environment of the Lake (Fund) LOADING...
Study content. Source: Objaverse 1.0 / Sketchfab
Supplementary material 1 from: Visagie CM, Yilmaz N, Renaud JB, Sumarah MW, Hubka V, Frisvad JC, Chen AJ, Meijer M, Seifert KA (2017) A survey of xerophilic Aspergillus from indoor environment, including descriptions of two new section Aspergillus species producing eurotium-like sexual states. MycoKeys 19: 1-30. https://doi.org/10.3897/mycokeys.19.11161
Species isolated from house dust using selective xerophilic media : Explanation note: Species isolated from house dust using selective xerophilic media, their occurrence and GenBank numbers for sequences generated for these strains.
Supplementary material 3 from: Abarenkov K, Adams RI, Irinyi L, Agan A, Ambrosio E, Antonelli A, Bahram M, Bengtsson-Palme J, Bok G, Cangren P, Coimbra V, Coleine C, Gustafsson C, He J, Hofmann T, Kristiansson E, Larsson E, Larsson T, Liu Y, Martinsson S, Meyer W, Panova M, Pombubpa N, Ritter C, Ryberg M, Svantesson S, Scharn R, Svensson O, Töpel M, Unterseher M, Visagie C, Wurzbacher C, Taylor AFS, Kõljalg U, Schriml L, Nilsson RH (2016) Annotating public fungal ITS sequences from the built environment according to the MIxS-Built Environment standard – a report from a May 23-24, 2016 workshop (Gothenburg, Sweden). MycoKeys 16: 1-15. https://doi.org/10.3897/mycokeys.16.10000
Krona chart : Explanation note: Interactive Krona chart for visualizing the taxonomic distribution of annotated BMS sequences down to order level. Sequences classified as Fungi sp. (36.4%) or non-fungal (0.9%) were excluded from this dataset.
Supplementary material 1 from: Abarenkov K, Adams RI, Irinyi L, Agan A, Ambrosio E, Antonelli A, Bahram M, Bengtsson-Palme J, Bok G, Cangren P, Coimbra V, Coleine C, Gustafsson C, He J, Hofmann T, Kristiansson E, Larsson E, Larsson T, Liu Y, Martinsson S, Meyer W, Panova M, Pombubpa N, Ritter C, Ryberg M, Svantesson S, Scharn R, Svensson O, Töpel M, Unterseher M, Visagie C, Wurzbacher C, Taylor AFS, Kõljalg U, Schriml L, Nilsson RH (2016) Annotating public fungal ITS sequences from the built environment according to the MIxS-Built Environment standard – a report from a May 23-24, 2016 workshop (Gothenburg, Sweden). MycoKeys 16: 1-15. https://doi.org/10.3897/mycokeys.16.10000
Keywords used to identify fungal sequences from the built environment in the INSDC : Explanation note: Keywords used to identify fungal sequences from the built environment in the INSDC.
Supplementary material 2 from: Abarenkov K, Adams RI, Irinyi L, Agan A, Ambrosio E, Antonelli A, Bahram M, Bengtsson-Palme J, Bok G, Cangren P, Coimbra V, Coleine C, Gustafsson C, He J, Hofmann T, Kristiansson E, Larsson E, Larsson T, Liu Y, Martinsson S, Meyer W, Panova M, Pombubpa N, Ritter C, Ryberg M, Svantesson S, Scharn R, Svensson O, Töpel M, Unterseher M, Visagie C, Wurzbacher C, Taylor AFS, Kõljalg U, Schriml L, Nilsson RH (2016) Annotating public fungal ITS sequences from the built environment according to the MIxS-Built Environment standard – a report from a May 23-24, 2016 workshop (Gothenburg, Sweden). MycoKeys 16: 1-15. https://doi.org/10.3897/mycokeys.16.10000
Annotations made during the workshop : Explanation note: The annotations made during the workshop shown with original INSDC data. For the BMS, we targeted nine MIxS-BE items plus country of collection, host of collection, host association, and a general "Comment" field. For the OMS, we targeted country of collection, host of collection, host association, and a general "Comment" field.
FIGURE 3. Collecting site and environment. A in Mimogonellus dreybrodti sp. n., a new cave-inhabiting Osoriinae from Laos (Coleoptera: Staphylinidae)
FIGURE 3. Collecting site and environment. A. Area map, showing the location of Tham Nam Lot. B. Map of Tham Nam Lot (red arrow indicates the locality where the beetles were collected). C. One of the entrances of the cave. D. General environment around the cave. (Fig. 3A–B reproduced from Dreybrodt & Laumanns 2010)
FIGURE 4 in Description of Stegelletina lingulata sp. n. (Nematoda, Rhabditida, Cephalobidae) from xeric environments in Iran
FIGURE 4. Schematic view of the lip region (left) and female tail (right) of the species of the genus Stegelletina. A: S. leopolitensis. B: S. similis. C: S. devimucronata. D: S. salinaria. E: S. pygmaea. F: S. insubrica. G: S. kheirii. H: S. coprophila. I: S. ankyra. J: S. argentinica. K: S. lingulata sp. n.
FIGURE 3 in Description of Stegelletina lingulata sp. n. (Nematoda, Rhabditida, Cephalobidae) from xeric environments in Iran
FIGURE 3. Stegelletina lingulata sp. n. (juvenile, scanning electron microscopy). A: Anterior end. B–E: Lip region in frontal, dorsal, ventral and lateral views, respectively. F: Cuticle. G, H: Posterior end in left lateral and ventral views, respectively. I. Lateral field.
FIGURE 2 in Description of Stegelletina lingulata sp. n. (Nematoda, Rhabditida, Cephalobidae) from xeric environments in Iran
FIGURE 2. Stegelletina lingulata sp. n. (light microscopy). A: Neck. B, C, E: Lip region (I = primary axil, II = secondary axil). D: Anterior end. F: Cuticle showing the slightly tessellated surface. G, H: Lateral field at deirid (arrow) and midbody levels, respectively. I: Female posterior end (arrow points the phasmid). J: Male posterior end.
FIGURE 1 in Description of Stegelletina lingulata sp. n. (Nematoda, Rhabditida, Cephalobidae) from xeric environments in Iran
FIGURE 1. Stegelletina lingulata sp. n. A: Neck. B: Lip region. C: Female reproductive system. D: Entire female. E: Entire male. F: Female posterior end. G: Male posterior end. H: Lateral field.
Supplementary material 1 from: Nilsson RH, Taylor AFS, Adams RI, Baschien C, Bengtsson-Palme J, Cangren P, Coleine C, Daniel H-M, Glassman SI, Hirooka Y, Irinyi L, Iršėnaitė R, Martin-Sanchez PM, Meyer W, Oh S-Y, Sampaio JP, Seifert KA, Sklenář F, Stubbe D, Suh S-O, Summerbell R, Svantesson S, Unterseher M, Visagie CM, Weiss M, Woudenberg JHC, Wurzbacher C, den Wyngaert SV, Yilmaz N, Yurkov A, Kõljalg U, Abarenkov K (2018) Taxonomic annotation of public fungal ITS sequences from the built environment – a report from an April 10–11, 2017 workshop (Aberdeen, UK). MycoKeys 28: 65-82. https://doi.org/10.3897/mycokeys.28.20887
The sequences renamed during the workshop. The INSDC accession number, the original INSDC name, and the new UNITE name are shown :
Supplementary material 3 from: Nilsson RH, Taylor AFS, Adams RI, Baschien C, Bengtsson-Palme J, Cangren P, Coleine C, Daniel H-M, Glassman SI, Hirooka Y, Irinyi L, Iršėnaitė R, Martin-Sanchez PM, Meyer W, Oh S-Y, Sampaio JP, Seifert KA, Sklenář F, Stubbe D, Suh S-O, Summerbell R, Svantesson S, Unterseher M, Visagie CM, Weiss M, Woudenberg JHC, Wurzbacher C, den Wyngaert SV, Yilmaz N, Yurkov A, Kõljalg U, Abarenkov K (2018) Taxonomic annotation of public fungal ITS sequences from the built environment – a report from an April 10–11, 2017 workshop (Aberdeen, UK). MycoKeys 28: 65-82. https://doi.org/10.3897/mycokeys.28.20887
The metadata annotations for the sequences that were found in the same SHs as sequences from the built environment :
Input data for predicted sedimentary environments on the Norwegian continental margin
<p>Input and output data relating to R workflow for predicting sedimentary environments on the Norwegian continental margin (https://github.com/diesing-ngu/SedEnv). The following files are included:</p><p><strong>SedEnv_4km_MaxCombArea_point_20230622.shp</strong> - Point shapefile of the response data (substrate type). Note that these data points were derived from mapped products and are not sample points as such. </p><p><strong>predictors_ngb.tif </strong>- Multi-band georeferenced TIFF-file of predictor variables</p><p><strong>predictors_description</strong>.txt - Information on variables stored in predictor_ngb.tif including units, statistics, time period and sources.</p><p><strong>GrainSizeReg_folk8_classes_2023-06-28.tif</strong> - Georeferenced TIFF-file of predicted substrate classes. Used to update the area of interest (exclude areas mapped as Rock and boulders).</p><p><strong>mud_2023-06-30.tif </strong>- Georeferenced TIFF-file of predicted mud content. Used as an additional predctor.</p>
Predicted sedimentary environments on the Norwegian continental margin
<p>Output data relating to R workflow for predicting substrate types on the Norwegian continental margin (https://github.com/diesing-ngu/SedEnv). The following files are included:</p><p><strong>SedEnv3_classes_2023-07-01.tif </strong>- Georeferenced Tiff-file of the predicted sedimentary environments</p><p><strong>SedEnv3_probabilities_2023-07-01.tif </strong>- Georeferenced Tiff-file of the prediction probabilities of the predicted sedimentary environments</p><p><strong>SedEnv3_max_probabilities_2023-07-01.tif </strong>- Georeferenced Tiff-file of the maximum probabilities, i.e., the probability of the class that was mapped. Can be used as an indicator of map confidence.</p><p><strong>SedEnv3_AOA_2023-07-01.tif </strong>- Georeferenced Tiff-file of the area of applicability of the model <a href="https://doi.org/10.1111/2041-210X.13650">(Meyer & Pebesma, 2021)</a></p><p><strong>SedEnv3_AOA_2023-07-01.shp</strong> - Same as above but as polygon shapefile</p>
ScienceDex guides
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These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.