Assessing the impact of new animal management technologies on welfare
Caroline Lee (view profile) and Dana Campbell
CSIRO, Agriculture and Food, FD McMaster Research Laboratory, Locked Bag 1, Armidale, NSW, 2350, Australia.
New husbandry technologies and livestock management systems must ensure that welfare is improved or maintained. To achieve this goal, the design and implementation of new technologies need to harness and complement the learning abilities of animals. From literature on cognitive evaluation and the cognitive activation theory of stress (CATS), we describe a framework to assess welfare outcomes in terms of the animal’s affective state and its learned ability to predict and control interaction with the environment, including new technologies, for example. In CATS, animals’ perception of their situation occurs through cognitive evaluation of predictability and controllability (P/C) that influence learning and stress responses. Stress responses result when animals are not able to predict or control both positive and negative events. A case study of virtual fencing involving avoidance learning will be described. We propose a framework for determining welfare outcomes in relation to new technologies and highlight examples of how animals’ cognitive evaluation of their environment and their ability to learn relates to stress responses. New technologies or systems should ensure that predictability and controllability are at intermediate levels and that operant tasks align with learning abilities to provide optimal animal welfare outcomes.