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74 results for “gibbons”
Supporting data for: Vocal fingerprinting reveals a substantially smaller global population of the Critically Endangered cao vit gibbon (Nomascus nasutus) than previously thought
<p>These data were used in the publication "Vocal fingerprinting reveals a substantially smaller global population of the Critically Endangered cao vit gibbon (Nomascus nasutus) than previously thought", currently in review. </p><p>The acoustic measurements provided in the file were input to the clustering analyses detailed in the paper. Each row corresponds to a single male song phrase. The columns include:</p><ul><li>GroupID - the name of the gibbon group, based on manual identification of the song phrase</li><li>MFCC[1-88] - Mel-frequency cepstral coefficients as detailed in the paper</li><li>Delta[89-176] - Delta-cepstral coefficients as detailed in the paper</li><li>Duration - the length of the song phrase (in seconds)</li><li>Freq 5% (Hz) and Freq 95% (Hz) - 5th and 95th percentile frequencies, respectively</li><li>Cao and Vit - the number of "cao" and "vit" components, respectively, present in the song phrase</li><li>CutFileName - the file name of the extracted song phrase (which also acts as a unique identifier)</li><li>Representative - whether the given song phrase was 'representative' ("Yes" or "No") of a typical phrase for that male (as defined by the modal number of 'cao' and 'vit' components for males)</li></ul><p>All columns (except GroupID, CutFileName and Representative) have been standardised (i.e. centred to the mean and scaled according to the standard deviation).</p>
Figure 2. Predicted habitat suitability classification for N in Current and suitable habitat of the Critically endangered Northern white-cheeked gibbon (Nomascus leucogenys) in Lao PDR
Figure 2. Predicted habitat suitability classification for N. leucogenys (A, D) 2022, (B, E) 2050 and (C, F) 2070.
Fig. 2 in Assessment Of Census Techniques For Estimating Density And Biomass Of Gibbons (Primates: Hylobatidae)
Fig. 2. Cumulative number of groups of Müller's gibbon, Hylobates muelleri, as observed during range mapping in Kayan Mentarang National Park (KMNP) and Sungai Wain protection forest (SWPF), East Kalimantan, Indonesia.
Fig. 1 in Assessment Of Census Techniques For Estimating Density And Biomass Of Gibbons (Primates: Hylobatidae)
Fig. 1. The island of Borneo showing the location of the two study areas. Grey shading indicates the area in which range mapping of all gibbon groups was executed, the straight lines indicate the transects, and the triangles indicate the listening positions from which the fixed point counts were made.
Fig. 2 in Conservation Of The Javan Gibbon Hylobates Moloch: Population Estimates, Local Extinctions, And Conservation Priorities
Fig. 2. Relation between number of groups calling per day and number of census days in the Telaga Warna Nature Reserve (Sept 1999) and Lingo Asri, Dieng mountains (Sept 1998).
Fig. 1 in Conservation Of The Javan Gibbon Hylobates Moloch: Population Estimates, Local Extinctions, And Conservation Priorities
Fig. 1. Current distribution of the Javan gibbon Hylobates moloch. Based on Kappeler, 1984, Asquith et al., 1995, Nijman 2001b, and present study. All areas where the species' presence has been confirmed are indicated in black; areas where the species' possible presence was reported by Andayani et al. (1999) are indicated in white. The three main study areas are: A, Telaga Warna Nature Reserve; B, Gunung Gede Pangrango National Park; C, Dieng mountains. The insert shows Java with all remaining forest patches on the island.
Fig, 2. Example sonograms of rehabilitant, released and wild agile female gibbons: a, rehabilitant; b, released captive-raised; c, wildraised. in Covarvariation In The Great Calls Of Rehabilitant And Wild Gibbons (Hylobates Albibarbis)
Fig, 2. Example sonograms of rehabilitant, released and wild agile female gibbons: a, rehabilitant; b, released captive-raised; c, wildraised.
Fig. 2 in An Assessment Of Food Overlap Between Gibbons And Hornbills
Fig. 2. Diet composition variation, during breeding season, between hornbill species [Great Hornbill (GH), Wreathed Hornbill (WH), Oriental Pied Hornbill (PH), and White-throated Brown Hornbill (BH)] and White-handed Gibbons (GB).
Fig. 4 in An Assessment Of Food Overlap Between Gibbons And Hornbills
Fig. 4. Correspondence Analysis per hornbill nest and gibbon group: a, with all plant species included (n = 58); b, with the genus Ficus and P. viridis excluded; c, with only P. viridis excluded; d, with only the genus Ficus excluded. Hornbill species [Great Hornbill ◆, Wreathed Hornbill ■, Oriental Pied Hornbill ▲, and White-throated Brown Hornbill ■] and White-handed Gibbons ▲.
Fig. 3 in An Assessment Of Food Overlap Between Gibbons And Hornbills
Fig. 3. Correspondence Analysis per animal species: a, with all plant species included (n = 58); b, with the genus Ficus and P. viridis excluded; c, with only P. viridis excluded; d, with only the genus Ficus excluded. Hornbill species [Great Hornbill (GH), Wreathed Hornbill (WH), Oriental Pied Hornbill (PH), and White-throated Brown Hornbill (BH)] and White-handed Gibbons (GB).
Fig. 6 in Activity budget, travel distance, sleeping time, height of activity and travel order of wild East Bornean Grey gibbons (Hylobates funereus) in Danum Valley Conservation Area
Fig. 6. Average daily travel distance and average sleeping time of the JACUZZI male for May–June (dry season) and December (wet season) from 2011 to 2013. Travel distance was counted for 13 days in August and for 13 days in December. Sleeping time was counted for 14 days in August and for 15 days in December. Solid line: travel distance. Dotted line: sleeping time.
Fig. 3 in Activity budget, travel distance, sleeping time, height of activity and travel order of wild East Bornean Grey gibbons (Hylobates funereus) in Danum Valley Conservation Area
Fig. 3. Activity budget of the SAPA male in both wet season (December) and dry season (August) from 2005 to 2008.
Fig. 2 in Activity budget, travel distance, sleeping time, height of activity and travel order of wild East Bornean Grey gibbons (Hylobates funereus) in Danum Valley Conservation Area
Fig. 2. Location of the BRL, the territory of the SAPA group and the territory of the JACUZZI group. The grey area represents the territory.
Fig. 1 in Activity budget, travel distance, sleeping time, height of activity and travel order of wild East Bornean Grey gibbons (Hylobates funereus) in Danum Valley Conservation Area
Fig. 1. Location of the Borneo Rainforest Lodge (BRL) in the Danum Valley Conservation Area (DVCA; arrow), Sabah, Malaysia.
Fig. 5 in Activity budget, travel distance, sleeping time, height of activity and travel order of wild East Bornean Grey gibbons (Hylobates funereus) in Danum Valley Conservation Area
Fig. 5. Average daily travel distance and average sleeping time of the SAPA male for August (dry season) and December (wet season) from 2003 to 2008. Travel distance was counted for 38 days in August and for 35 days in December. Sleeping time was counted for 39 days in August and for 37 days in December. Solid line: travel distance. Dotted line: sleeping time.
Fig. 4 in Activity budget, travel distance, sleeping time, height of activity and travel order of wild East Bornean Grey gibbons (Hylobates funereus) in Danum Valley Conservation Area
Fig. 4. Activity budget of the JACUZZI male and the JACUZZI female in both wet season (December) and dry season (May–June) from 2011 to 2013.
Fig. 8 in Activity budget, travel distance, sleeping time, height of activity and travel order of wild East Bornean Grey gibbons (Hylobates funereus) in Danum Valley Conservation Area
Fig. 8. Heights of diurnal activity of three gibbons (two males and one female) from 0530–1600 hours.
Fig. 1 in Secondary removal of seeds dispersed by gibbons (Hylobates lar) in a tropical dry forest in Thailand
Fig. 1. Distribution of experimental sites where seeds were dispersed by 4 groups of white-handed gibbons (Hylobates lar). Home range maps of the gibbons are based on Light (2016) and Phiphatsuwannachai et al. (2018), plus newly-discovered areas (extended home ranges) by the author. Fruiting trees and gibbon defecation locations were recorded in a GPS. Each site when active contained a camera trap and a paired control/treatment.
Fig 2 in Secondary removal of seeds dispersed by gibbons (Hylobates lar) in a tropical dry forest in Thailand
Fig 2. Estimates of beta-coefficients from binomial regressions with parameter estimates derived from model averaging with 95% confidence intervals. A variable is considered significant if the confidence interval does not overlap zero.
Hainan gibbon (Nomascus hainanus) bioacoustics dataset for machine learning
<p>Data accompanying the paper: "<strong>Empowering Deep Learning Acoustic Classifiers with Human-like Ability to Utilize Contextual Information for Wildlife Monitoring</strong>"</p> <p>We provide the audio data (.wav) used to test our neural network classifier along with the corresponding labelled text files (.svl). The audio and labelled files can easily be viewed in Sonic Visualiser. Drag and drop the audio file. Create the spectrogram layer. Drag and drop the corresponding .svl file.</p> <p>The dataset provided here is a subset of the full dataset provided here: 10.5281/zenodo.3991714. This dataset has additional files that were manually annotated, which were not manually verified in the original version (10.5281/zenodo.3991714).</p> <p><strong>Files provided</strong></p> <ul> <li><strong>Audio_x.zip</strong> -- we provide x number of .zip files containing audio files, numbered 1 to 4. These were created in batches to simplify downloads.</li> <li><strong>Annotations.zip -</strong>- .svl files which contain the manually verified labels. These files can be read in Sonic Visualiser, or as .XML files in a programming language. We took care to annotate the start and stop time of each gibbon call. The height of each bounding box is not important as the frequency range of Hainan gibbons is already known.</li> <li><strong>model_weights_tensorflow.hdf5 </strong>-- the Tensorflow model. Load the model using: model = tf.keras.models.load_model(model_filepath) note that the model expects a three channel input as explained in the research article.</li> </ul>
ScienceDex guides
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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.