The project:
It is common practice to separate the cow from her calf quickly after birth in most dairy farms. Despite being controversial, the practice remains widespread. Its effects on the welfare of the cow are poorly understood, especially in terms of affective (emotional) states, and scientific guidance for more welfare friendly cow‐calf contact systems is still lacking. For instance, benefits from early contact can be jeopardized by stronger distress at the moment of later separation, hence why most farmers favour early separation.
There is limited work on separation distress (at the emotional level), so the first aim of this project is to explore cows’ emotional responses to separation when given various length of contact and type of contact with their calf. For this, we will use a series of behavioural/cognitive tests designed to allow inference about animals’ subjective experiences and mood states.
We will also explore whether cows express long‐term behavioural changes after separation that may be observed when animals experience long‐lasting negative emotions (e.g., depressive‐like states). Artificial intelligence (AI) will allow tracking the cows using a network of cameras (https://doi.org/10.1016/j.compag.2021.106133) when mingled in the herd after separation. This data will then be matched with recurrent behavioural/cognitive testing aiming to assess mood states (e.g., judgment bias) and productivity metrics.
This combined approach will provide an in‐depth understanding of short‐term and long‐term effects of cow‐calf separation on the welfare of the cow and will provide an opportunity to develop monitoring tools based on patterns of behaviour assessed via computer vision in free‐moving animals.
This project will provide the student with expertise at multiple levels of behavioural analyses and the opportunity to contribute to solving an important animal welfare issue within the dairy industry. We are looking for a motivated individual with education in biology, agriculture or psychology, ideally with some experience with dairy cows, animal welfare or animal emotions. The successful applicant will be based at Bristol Vet School and join a larger group of experts on animal behaviour and welfare, led by Prof. Mike Mendl. The student will benefit from a strong collaboration with Dr Benjamin Lecorps, whom will provide expertise on dairy cow welfare; and Professor Andrew Dowsey, who will provide expertise in artificial intelligence and data science. The work will take place at the John Oldacre Centre, which supports research leading to a more sustainable dairy production, with a strong emphasis on dairy cow welfare.
This studentship will start in September 2023.
Contacts: [Email Address Removed]
Supervisory team:
Main supervisor: Prof Mike Mendl (University of Bristol)
Second supervisor: Prof Andrew Dowsey (University of Bristol)
Dr Benjamin Lecorps (University of Bristol)
How to apply:
This studentship is part of the BBSRC SWBio Doctoral Training Partnership (https://www.swbio.ac.uk/). Please apply from https://www.swbio.ac.uk/programme/projects-available/.
Candidate requirements:
Please see https://www.swbio.ac.uk/programme/eligibility/ for conditions specific to this funding.
Due to complexities and restrictions associated with visas for part-time studies, we are currently unable to accept part-time international students to the programme Project adjustments, part-time study and flexible working – SWBiosciences Doctoral Training Partnership
Standard University of Bristol eligibility rules for PhD admissions also apply. Please visit http://www.bristol.ac.uk/study/postgraduate/2023/health-sciences/phd-veterinary-sciences/ for more information.
Our aim as the SWBio DTP is to support students from a range of backgrounds and circumstances. Where needed, we will work with you to take into consideration reasonable project adaptations (for example to support caring responsibilities, disabilities, other significant personal circumstances) as well as flexible working and part-time study requests, to enable greater access to a PhD. All our supervisors support us with this aim, so please feel comfortable in discussing further with the listed PhD project supervisor to see what is feasible.
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