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74 results for “gibbons”
Hainan gibbons (Nomascus hainanus) calls for passive acoustic monitoring
<p><em>This dataset extends an existing one (10.5281/zenodo.3991714).</em></p> <p>Data accompanying the paper: "Passive Acoustic Monitoring and Transfer Learning"</p> <p><strong>Please cite this dataset as:</strong></p> <blockquote> <p>Dufourq, Emmanuel and Batist, Carly and Foquet, Ruben and Durbach, Ian. (2022). Passive Acoustic Monitoring and Transfer Learning. BioRxiv doi: </p> </blockquote> <p>This dataset contains approximately 10 hours of audio that contained calls of the critically endangered Hainan gibbons (Nomascus hainanus). The audio data was collected in the Bawangling National Nature Reserve, Malawi using 8 Song Meter SM3 recorders. The sampling rate was set to 9,600Hz and the recordings were collected between March to August 2016.</p> <p>The annotations files are in (.svl) format which is compatible with SonicVisualiser (https://www.sonicvisualiser.org/). Each audio file has a corresponding .svl file. Each .svl has segments of audio that were manually annotated as either ''gibbon" (presence class) or "no-gibbon" (absence class) -- this dataset can be used to train a binary classification model.</p> <p>The audio files are provided in "Audio.zip" and the manually verified annotation in "Annotations.zip".</p>
Mechanisms underlying altitudinal and horizontal range contraction: The western black crested gibbon
<p>Aim: Species ranges in mountain areas may shift both horizontally and altitudinally, resulting from climate change and anthropogenic impact. Two hypotheses (the abundant center hypothesis and the contagion hypothesis) have been proposed to account for patterns of horizontal range contraction. However, undulating topograph causes a mosaic of unsuitable habitats, which may complicate the spatial pattern of range contraction. We develop a framework incorporating horizontal and altitudinal range contraction patterns of a species living in mountain areas, to better understand the underlying mechanisms of species range contraction.</p> <p>Location: China, North Laos, and North Vietnam</p> <p>Taxon: Western black crested gibbon, <i>Nomascus concolor</i></p> <p>Methods: We collected occurrence data of the gibbons from various sources and modelled their potential distribution range in the 1950s, 1980s, and 2010s, using ecological niche modelling. We compared distances from the center point of the potential range in 1950s to center points of the largest 100 patches in the 1950s and the 2010s to understand the patterns of horizontal range contraction. We also calculated potential distribution within different altitudinal range for six populations in each period to understand the patterns of altitudinal range contraction.</p> <p>Results: Potential horizontal distribution of the gibbons decreased by 69% from the 1950s to the 2010s. We found the 100 largest patches in 2010s were further apart from the center point of the potential range in 1950s compared to the 100 largest patches in 1950s, supporting the contagion hypothesis. No populations extended their range to higher altitude, suggesting climate change did not have a profound effect on gibbon range upward shift. All populations lost a substantial proportion of their ranges in lower altitude (500 – 1,500 m) but to different degrees, suggesting that populations experienced different anthropogenic pressures.</p> <p>Main conclusions: Anthropogenic threats probably including human population increase, agricultural expansion and hunting, were more likely than climate change to have caused range contraction in western black-crested gibbons. This study highlights the importance of studying horizontal and altitudinal range contraction simultaneously.</p>
Figure 1 in Current and suitable habitat of the Critically endangered Northern white-cheeked gibbon (Nomascus leucogenys) in Lao PDR
Figure 1. Map of all present locations of N. leucogenys showing the study area.
Fig. 1 in Covarvariation In The Great Calls Of Rehabilitant And Wild Gibbons (Hylobates Albibarbis)
Fig. 1. Map showing the two recording sites.
Fig. 1 in An Assessment Of Food Overlap Between Gibbons And Hornbills
Fig. 1. Hornbill and gibbon study site.
Fig. 7 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. 7. Diurnal activity cycle of three gibbons (two males and one female) from 0530−1600 hours.
Fig. 9 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. 9. Activity of three gibbons (two males and one female) at each height.
(b) Brenthis ino (Rottemburg, 1775) (Foto R. Gibbons). in Erstnachweis von Brenthis daphne (Denis & Schiffermüller, 1775) im Kanton Zürich (Lepidoptera: Nymphalidae)
(b) Brenthis ino (Rottemburg, 1775) (Foto R. Gibbons).
Breastfeeding, carrying, grooming, and playing behaviours in wild Javan gibbons (Hylobates moloch)
<p><span>In pair-living species, female and male pairs may maintain stable social bonds by adjusting spatial and social associations. Nevertheless, each sex invests differently to maintain the pair bond, and the investment can depend on the presence of paternal care or 'male services.' While most species live in pairs, the sex responsible for pair bond maintenance in gibbons is still controversial. We investigated pair bond maintenance and parental care in three pairs of wild Javan gibbons in Gunung Halimun-Salak National Park, Indonesia, for over 21 months. We found that Javan gibbon fathers groomed their offspring more than adult females, especially as offspring get older. While both parents increased playing time with offspring when offspring became older and more independent, fathers played with offspring 20 times more than mothers on average. Grooming within Javan gibbon pairs was male-biased, suggesting that pair bond maintenance was heavily the job of males. However, offspring age as a proxy for paternal care did not affect the pair bond maintenance. Our study highlights that adult male Javan gibbons may have an important role in pair bond maintenance and the care of juveniles.</span></p>
Dataset for "Benchmarking for the automated detection of southern yellow-cheeked crested gibbon calls from passive acoustic monitoring data"
<p>"<span>Benchmarking automated detection and classification approaches for long-term acoustic monitoring of endangered species: a case study on gibbons from Cambodia</span>"</p> <div> <p><span>Recent advances in deep learning and transfer learning have revolutionized our ability for the automated detection of acoustic signals from long-term soundscape recordings. Here, we provide a benchmark for the automated detection of southern yellow-cheeked crested gibbon (<em>Nomascus gabriellae</em>) calls recorded in Jahoo, Cambodia. For the benchmarking, we compared the performance of support vector machines (SVMs), a quasi-DenseNet architecture (Koogu), transfer learning with ResNet50 models trained on the ‘ImageNet’ dataset (ResNet), and transfer learning with embeddings from a global birdsong model (BirdNET). We also investigated the impact of varying the number of training samples on the performance of these models. Transfer learning models based on <span>BirdNET embeddings had superior performance with a smaller number of training samples, whereas Koogu and ResNet models only had acceptable performance with a larger number of training samples (>200 gibbon samples). We deployed the BirdNET-based model over </span>> 130,000 hours<span> of continuous soundscape data, which, after manual review, resulted in >12,000 verified true positive detections. We found that gibbon calling events occurred mostly in the early morning hours between 05:00 to 0:600 local time. We had fewer gibbon detections during the monsoon period and found substantial variation in spatial patterns of calling events across months and years. </span>We show that automated detection can be used to investigate long-term spatial and temporal patterns of gibbon calling events. Reliable automated detection approaches are a critical first step for using passive acoustic monitoring to assess endangered gibbon populations at ecologically relevant temporal- and spatial-scales. </span></p> <p> Detailed instructions regarding use are provided on GitHub.</p> </div> <p>Link to GitHub: https://github.com/DenaJGibbon/benchmark-gibbon-calls.</p> <p>Please cite both if you use these data: </p> <p>Clink, D., Cross-Jaya, H., Kim, J., Ahmad, A. H., Hong, M., Sala, R., Birot, H., Agger, C., Vu, T. T., Thi, H. N., Chi, T. N., & Klinck, H. (2024). Dataset for "Benchmarking for the automated detection of southern yellow-cheeked crested gibbon calls from passive acoustic monitoring data" [Data set]. Zenodo. <a href="https://doi.org/10.5281/zenodo.12706803" target="_blank" rel="noopener">https://doi.org/10.5281/zenodo.12706803</a></p> <p>Clink DJ, Cross-Jaya H, Kim J, Ahmad AH, Hong M, Sala R, Birot H, Agger C, Vu TT, Thi HN, Chi TN. Benchmarking for the automated detection and classification of southern yellow-cheeked crested gibbon calls from passive acoustic monitoring data. bioRxiv. 2024:2024-08.</p>
Breastfeeding, carrying, grooming, and playing behaviours in wild Javan gibbons (Hylobates moloch)
Open the record for dataset details and reuse information.
Mechanisms underlying altitudinal and horizontal range contraction: The western black crested gibbon
Open the record for dataset details and reuse information.
Unsupervised acoustic classification of individual gibbon females and the implications for passive acoustic monitoring
<p>1. Passive acoustic monitoring (PAM) has the potential to greatly improve our ability to monitor cryptic yet vocal animals. Advances in automated signal detection have increased the scope of PAM, but distinguishing between individuals— which is necessary for density estimation— remains a major challenge. When individual identity is known, supervised classification techniques can be used to distinguish between individuals. Supervised methods require labeled training data, whereas unsupervised techniques do not. If the acoustic signals of individuals are sufficiently different, the number of clusters might represent the number of individuals sampled. The majority of applications of unsupervised techniques in animal vocalizations have focused on quantifying species-specific call repertoires. However, with increased interest in PAM applications, unsupervised methods that can distinguish between individuals are needed. <br> 2. Here, we use an existing dataset of Bornean gibbon female calls with known identity from five sites on Malaysian Borneo to test the ability of three different unsupervised clustering algorithms (affinity propagation, K-medoids, and Gaussian mixture model-based clustering) to distinguish between individuals. Calls from different gibbon females are readily distinguishable using supervised techniques. For internal validation of unsupervised cluster solutions, we calculated silhouette coefficients. For external validation, we compared clustering results with female identity labels using a standard metric: normalized mutual information. We also calculated classification accuracy by assigning unsupervised cluster solutions to females based on which cluster had the highest number of calls from a particular female.<br> 3. We found that affinity propagation clustering consistently outperformed the other algorithms for all metrics used. In particular, classification accuracy of affinity propagation clustering was more consistent as the number of females increased, and when we randomly sampled females across sites. <br> 4. We conclude that unsupervised techniques may be useful for providing additional information regarding individual identity for PAM applications. We stress that although we use gibbons as a case study, these methods will be applicable for any individually-distinct vocal animal. <br> </p>
FIGURE 8 A in Description of a new species of Hoolock gibbon (Primates: Hylobatidae) based on integrative taxonomy
FIGURE 8 A juvenile male of H. tianxing from Mt. Gaoligong jumping across trees. Photo taken by Lei Dong
FIGURE 2 in Description of a new species of Hoolock gibbon (Primates: Hylobatidae) based on integrative taxonomy
FIGURE 2 Photos of male (top row) and female (bottom row) hoolocks from different taxa and geographic populations. Photos of H. h. hoolock and H. h. mishmiensis are from Choudhury (2013)
FIGURE 3 A in Description of a new species of Hoolock gibbon (Primates: Hylobatidae) based on integrative taxonomy
FIGURE 3 A hoolock specimen from Homushu Pass, Mt. Gaoligong (AMNH M-43068, top row) and the holotype of H. leuconedys (NHM ZD.1950.391, bottom row), showing (left to right) eye brows and suborbital area, beard, and genital tuft
FIGURE 7 in Description of a new species of Hoolock gibbon (Primates: Hylobatidae) based on integrative taxonomy
FIGURE 7 Mitochondrial gene tree for hoolocks, showing two major clades within Hoolock leuconedys sensu lato. Specimens shaded in gray were originally identified as H. hoolock. Node numbers indicate Bayesian posterior probabilities. Branch lengths represent substitutions/site
FIGURE 1 in Description of a new species of Hoolock gibbon (Primates: Hylobatidae) based on integrative taxonomy
FIGURE 1 Field localities for eastern hoolocks, and collection localities for museum specimens of eastern and western hoolocks. The distribution and type localities of H. hoolock hoolock (red, Garo Hills), H. h. mishmiensis (gray, Delo), H. leuconedys (yellow, Sumprabum), and H. tianxing (blue, Homushu) are shown
FIGURE 4 in Description of a new species of Hoolock gibbon (Primates: Hylobatidae) based on integrative taxonomy
FIGURE 4 PCA and DFA for hoolock taxa, using craniodental measurements (A and B), shape of the outline of the upper M2 (C and D), and shape of the outline of the lower M2 (E and F)
FIGURE 6 in Description of a new species of Hoolock gibbon (Primates: Hylobatidae) based on integrative taxonomy
FIGURE 6 Bayesian tree of various catarrhines estimated using complete mitochondrial genome sequence data. Branch lengths represent time. Node bars indicate the 95%CI for the clade age. Unless specified, all interspecific relationships are strongly supported (PP = 1.0). PPs lower than 1.0 are shown in gray. Numbers above the nodes indicate Bayesian posterior probabilities, numbers below the nodes refer to median ages
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International Brain Laboratory public data
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OpenNeuro
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