Highly precise community science annotations of video camera‐trapped fauna in challenging environments

Remote Sensing in Ecology and Conservation, Journal Year: 2024, Volume and Issue: unknown

Published: June 24, 2024

Abstract As camera trapping grows in popularity and application, some analytical limitations persist including processing time accuracy of data annotation. Typically images are recorded by traps although videos becoming increasingly collected even though they require much more for To overcome with image annotation, trap studies linked to community science (CS) platforms. Here, we extend previous work on CS annotations from a challenging environment; dense tropical forest low visibility high occlusion due thick canopy cover bushy undergrowth at the level. Using platform Chimp&See, established classification 599 956 video clips Africa, assess annotation precision comparing 13 531 1‐min professional ecologist (PE) output 1744 registered, as well unregistered, Chimp&See scientists. We considered 29 categories, 17 species 12 higher‐level which phenotypically similar were grouped. Overall, was 95.4%, increased 98.2% when aggregating groups together. Our findings demonstrate competence scientists working environments hold great promise future animal behaviour, interaction dynamics population monitoring.

Language: Английский

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The ontogeny of chimpanzee technological efficiency

bioRxiv (Cold Spring Harbor Laboratory), Journal Year: 2024, Volume and Issue: unknown

Published: July 31, 2024

Abstract Primate extractive foraging requires years of dedicated learning. Throughout this period, learners peer at conspecifics engaging in the behaviour (“models”), interacting with model and their tools, sometimes stealing freshly extracted resource. This also corresponds to an extended period tolerance from models. Yet long-term effect variation experiences during on technological efficiency individuals is unknown for primate tool use, no research has assessed role both learner model(s) generating individual differences. Using >680 hours video spanning 25 years, we whether stone use social learning (“early period”; ages 0–5) predicted post-early (ages 6+) wild chimpanzees Bossou, Guinea. We found that varied how frequently they peered models’ whole nut-cracking bouts, many opportunities mothers presented, amount intolerance experienced all selected Learners who more became less efficient users, whereas were exposed efficient. Peering bout decreased subsequent efficiency, hinting acquiring cultural components behaviour. Our findings highlight acquisition support view within a tolerant environment are key explaining emergence maintenance complex forms technology. Significance Statement The capacity inclination learn others, along provided by groupmates, thought have enabled evolution technology primates, including hominins. influence remains non-human primates but significant implications transmission evolution. provide longitudinal hypothesis exposure development predicts efficiency. Moreover, show low amounts tolerance, not just general ontogeny Finally, find aspects behavioural relating accurate traits rather than tools efficiently.

Language: Английский

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To drum or not to drum: Selectivity in tree buttress drumming by chimpanzees (Pan troglodytes verus) in the Nimba Mountains, Guinea

American Journal of Primatology, Journal Year: 2022, Volume and Issue: 84(7)

Published: April 5, 2022

Abstract Chimpanzees live in fission‐fusion social organizations, which means that party size, composition, and spatial distribution are constantly flux. Moreover, chimpanzees use a remarkably extensive repertoire of vocal nonvocal forms communication, thought to help convey information such socially spatially dynamic setting. One proposed form communication is buttress drumming, an individual hits tree with its hands and/or feet, thereby producing low‐frequency acoustic signal. It often presumed this behavior functions communicate over long distances is, therefore, goal‐oriented. If so, we would expect exhibit selectivity the choice trees buttresses used drumming. Selectivity key attribute many other goal‐directed chimpanzee behaviors, as nut‐cracking ant dipping. Here, investigate whether at Seringbara study site Nimba Mountains, Guinea, West Africa, show their drumming behavior. Our results indicate more likely larger select thinner have greater surface area. These findings imply not random act, but rather goal‐oriented requires knowledge suitable buttresses. also point long‐distance probable function based on for characteristics impact sound propagation. This provides foundation further assessing cognitive underpinnings wild chimpanzees.

Language: Английский

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A toolkit for the dynamic study of air sacs in siamang and other elastic circular structures

PLoS Computational Biology, Journal Year: 2024, Volume and Issue: 20(6), P. e1012222 - e1012222

Published: June 24, 2024

Biological structures are defined by rigid elements, such as bones, and elastic like muscles membranes. Computer vision advances have enabled automatic tracking of moving animal skeletal poses. Such developments provide insights into complex time-varying dynamics biological motion. Conversely, the soft-tissues organisms, nose elephant seals, or buccal sac frogs, poorly studied no computer methods been proposed. This leaves major gaps in different areas biology. In primatology, most critically, function air sacs is widely debated; many open questions on role evolution communication, including human speech, remain unanswered. To support dynamic study soft-tissue structures, we present a toolkit for automated semi-circular video data. The contains unsupervised tools (using Hough transform) supervised deep learning (by adapting DeepLabCut) methodology to track inflation laryngeal other spherical objects (e.g., gular cavities). Confirming value kinematic analysis, show that correlates with acoustic markers likely inform about body size. Finally, pre-processed audiovisual-kinematic dataset 7+ hours closeup audiovisual recordings siamang ( Symphalangus syndactylus ) singing. https://github.com/WimPouw/AirSacTracker aims revitalize non-skeletal morphological across multiple species.

Language: Английский

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Behavioral Coding of Captive African Elephants (Loxodonta africana): Utilizing DeepLabCut and Create ML for nocturnal activity tracking.

Published: Aug. 28, 2024

This study investigates the possibility of using machine learning models created in DeepLabCut and Create ML to automate aspects behavioral coding aid analysis. Two with different capabilities complexities were constructed compared a manually observed control period. The accuracy was assessed before being applied 7 nights footage nocturnal behavior two African elephants (Loxodonta africana). resulting data used draw conclusions regarding differences between individually nights, thus proving that such can researchers be-havioral capable tracking simple behaviors high accuracy, but had certain limitations detection complex behaviors, as stereotyped sway, displayed confusion when deciding visually similar behaviors. Further expansion may be desired create more automating coding.

Language: Английский

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