Performance on a categorisation task suggests that removal of environmental enrichment induces ‘pessimism’ in captive European starlings (Sturnus vulgaris)

By Melissa Bateson, S. Matheson. Animal Welfare, 2007

229 citations recorded by the source corpus.

Improving the quality of life of captive animals is dependent on developing valid measures of how animals feel about their lives. It has recently been suggested that biases in information processing may offer a novel means of understanding animal emotions. Anxious and depressed people tend to interpret ambiguous information negatively. We explored the proposal that such cognitive biases also exist in non-human animals and could therefore be used as novel measures of animal welfare. We used a novel cognitive bias task based on a learnt taste aversion to determine whether birds deprived of environmental enrichment show biases in their classification of ambiguous signals. We hypothesised that starlings in enriched cages should be more likely to classify ambiguous signals as being associated with a positive outcome than starlings housed in standard, unenriched cages. Starlings were trained on a go/no-go procedure to discriminate between two visual stimuli (cardboard lids of white and dark grey) associated with outcomes of a different value (palatable and unpalatable mealworms hidden underneath). Individual birds' responses to unreinforced, intermediate stimuli (various shades of grey between white and dark grey) were subsequently examined while each bird was housed sequentially in both standard and enriched cages. The probability of a bird classifying an ambiguous pale grey lid as hiding a palatable mealworm was lower in standard cages than enriched cages, but this difference was found only in birds that received enriched cages first. Our results can be interpreted as showing a pessimistic bias in birds that have recently experienced a decline in environmental quality. These findings support the use of cognitive bias-based tasks as a novel, non-invasive technique for assessing welfare in non-human animals.

Subfields: Animal Science and Zoology, Genetics, Small Animals

View Paper: https://www.semanticscholar.org/paper/8f1810c6bd0e3ff080de2225678a0544a7216292

How researchers see this paper

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In Animal Science and Zoology

  1. A. McElligott
  2. Luigi Baciadonna
  3. Lesley J. Rogers
  4. M. Mendl
  5. Elizabeth S. Paul
  6. Oliver Burman
  7. S. Matheson
  8. Lucy Asher

In Genetics

  1. Lesley J. Rogers
  2. A. McElligott
  3. Luigi Baciadonna
  4. A. MacLarnon
  5. Stuart Semple
  6. E. Bethell
  7. A. Holmes
  8. Melissa Bateson

In Small Animals

  1. A. McElligott
  2. Luigi Baciadonna
  3. Oliver Burman
  4. Lesley J. Rogers
  5. G. Hinch
  6. R. Doyle
  7. Caroline Lee
  8. Elizabeth S. Paul

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