Objective
One benefit of sociality in animals is collective predator detection, which provides early warning of threats and enables more effective escape responses. For collective detection to occur, information regarding the presence of predators must be transferred from knowledgeable to naïve individuals. The mechanisms of information sharing have rarely been studied outside of laboratory settings, and for most species it is unclear how information transfer is achieved and how the reliability of transfer is affected by social, ecological, and behavioral factors. Using UAV-based aerial video technology and novel computer vision techniques, The Experience Research (ER) will study the mechanisms of information transfer in groups of African ungulates in their natural savannah habitats. The ER will observe unperturbed herds, and conduct field experiments in which she present threatening stimuli to groups and observe how awareness of the stimuli spreads through the group. Using custom-built automated tracking software, the ER will quantify the behavior of every individual within each group and combine this data with computationally reconstructed visual fields and 3D habitat models. This dataset will enable her to precisely identify the visual information available to each individual continuously throughout each trial and explicitly consider the role of this information in driving individual vigilance strategies in the absence of immediate threats. In undertaking this project, the ER will adapt quantitative methods developed for laboratory settings for use in stochastic, large-scale field studies. This research programme will shed new light on the benefits of sociality, a classic topic in animal behavior, and promote the use of novel quantitative approaches in field studies that will advance the field of behavioural ecology.
Fields of science (EuroSciVoc)
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques. See: https://op.europa.eu/en/web/eu-vocabularies/euroscivoc.
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques. See: https://op.europa.eu/en/web/eu-vocabularies/euroscivoc.
- natural sciences computer and information sciences artificial intelligence computer vision
- natural sciences biological sciences biological behavioural sciences behavioural ecology
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Programme(s)
Multi-annual funding programmes that define the EU’s priorities for research and innovation.
Multi-annual funding programmes that define the EU’s priorities for research and innovation.
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H2020-EU.1.3. - EXCELLENT SCIENCE - Marie Skłodowska-Curie Actions
MAIN PROGRAMME
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H2020-EU.1.3.2. - Nurturing excellence by means of cross-border and cross-sector mobility
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Topic(s)
Calls for proposals are divided into topics. A topic defines a specific subject or area for which applicants can submit proposals. The description of a topic comprises its specific scope and the expected impact of the funded project.
Calls for proposals are divided into topics. A topic defines a specific subject or area for which applicants can submit proposals. The description of a topic comprises its specific scope and the expected impact of the funded project.
Funding Scheme
Funding scheme (or “Type of Action”) inside a programme with common features. It specifies: the scope of what is funded; the reimbursement rate; specific evaluation criteria to qualify for funding; and the use of simplified forms of costs like lump sums.
Funding scheme (or “Type of Action”) inside a programme with common features. It specifies: the scope of what is funded; the reimbursement rate; specific evaluation criteria to qualify for funding; and the use of simplified forms of costs like lump sums.
MSCA-IF-EF-ST - Standard EF
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Call for proposal
Procedure for inviting applicants to submit project proposals, with the aim of receiving EU funding.
Procedure for inviting applicants to submit project proposals, with the aim of receiving EU funding.
(opens in new window) H2020-MSCA-IF-2016
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Net EU financial contribution. The sum of money that the participant receives, deducted by the EU contribution to its linked third party. It considers the distribution of the EU financial contribution between direct beneficiaries of the project and other types of participants, like third-party participants.
80539 Munchen
Germany
The total costs incurred by this organisation to participate in the project, including direct and indirect costs. This amount is a subset of the overall project budget.