COST Actions IMPROVE (CA21139), AFFECT-EVO (CA23106), and LIFT (CA21124) jointly organise a webinar series called the Animal Welfare Synergy Series. The webinars are organised and moderated by the Action members: Anna Olsson, Rohish Kaura, Fernando Gonzalez Uarquin, and Irene Camerlink. The webinars address topics that are relevant across these COST Actions, which focus on various aspects of animal welfare science.
COST Action IMPROVE focuses on improving the quality of biomedical sciences, including the use of animals in research, through the 3Rs concept (https://cost-improve.eu/). COST Action AFFECT-EVO, which started in November 2024, takes an evolutionary view to understand affective states across species (https://affect-evo.eu/). COST Action LIFT focuses on positive animal welfare in farm animals. While the Actions differ in their topics and aims, there are commonalities and active researchers across the Actions. This synergy therefore makes optimal use of our shared interests.
In the first webinar (episode 1), the Chairperson of AFFECT-EVO Dr Tom Smulders presented adult hippocampal neurogenesis as a valence marker.
In episode 2, Prof. Georgia Mason presented about proxy measures for animal feelings: how to validate indicators of affective state or cumulative affective experience. This relates to an upcoming book from UFAW about affective states in animals. Due to technical issue, only the second half of the webinar was recorded. Accompanied slides are available in the Members Area to download (folder: Training school and Webinar Materials).
In the 3rd episode, Dr Laura Webb from Wageningen University, the Netherlands, gave a presentation about animal happiness: understanding and assessment through behaviour, cognition and physiology. Laura is co-chair of COST Action LIFT.
The webinar recordings are made available online on the LIFT YouTube channel.
Webinar 1: https://youtu.be/TuzKz0jZob4?si=NVnbRCTooFXO1uvL
Webinar 2: https://youtu.be/qK_1GlQG9kk?si=aPzPT3q0UghIxyur
Webinar 3: https://youtu.be/p_1vveS7UHs?si=kplBXaPyWUJvLwyh
