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1.
PLoS One ; 17(2): e0264258, 2022.
Article in English | MEDLINE | ID: mdl-35213574

ABSTRACT

Judgement bias testing has emerged as a potential tool for assessing affective states in animals. Researchers infer an animal's affective state based on an animal's response to an ambiguous stimulus that is intermediate to both the rewarded and punished conditioned stimuli. Animals can be classified as "optimistic" or having a positive affective state if the animal displays behaviors that suggest an increased expectation of reward in the face of ambiguous stimuli. Alternatively, animals can be classified "pessimistic" or having a negative affective state if the animal displays behaviors that suggest an increased expectation of punishment in the face of ambiguous stimuli. Recent reports in multiple species question what factors influence performance in judgement bias testing, and which may allow for erroneous conclusions regarding individual affective state. In order to better understand this concern, 25 female swine were subjected to behavioral assessments at critical rearing stages to determine response variability. These same individuals were then assessed for physical measures of welfare and judgement bias using the "go/no-go" task as breeding adults. Sows which were more aggressive approached the ambiguous, but not the positive, stimulus significantly faster than others. Both optimistic and pessimistic biases were observed despite all sows living in enriched housing, and, sows with more positive physical welfare measures (fewer skin lesions and healthy body condition) did not exhibit more optimistic judgement biases. Our data demonstrate that behavior traits, such as aggressiveness, can affect a sow's performance in a judgement bias test, while measures of physical health did not. We suggest that individual differences in behavior (e.g., bold-aggressive behavioral syndrome, or, proactive coping style) generate different emotional responses and can contribute to the animal's overall affective state more so than physical ailment. Our findings highlight the complexity of how different factors impact an animal's overall affective state and support the need for complementary measures in future JBT studies, including personality assessment.


Subject(s)
Aggression/physiology , Behavior, Animal/physiology , Swine/physiology , Animals , Female , Housing, Animal
2.
Zoo Biol ; 33(5): 403-10, 2014.
Article in English | MEDLINE | ID: mdl-25113850

ABSTRACT

The present study examined the activity budgets of 15 African elephants (1 bull, 6 cows, 2 male juveniles, 2 female juveniles, and 4 male calves) living at the San Diego Zoo Safari Park during the summers of 2010 and 2011. Onsite behavioral data (n = 600 hr) were collected for approximately 12 weeks from 0400 to 0830 and 1100 to 2400 during the 2010 and 2011 summer season. Foraging was the most common behavior state during the day followed by resting, and walking. During the evening hours, the elephants spent majority of their time foraging, resting, and sleeping. The average rate of self-maintenance behavior events (dust, wallow, etc.) increased from 0600 to 0700, 1100 to 1500, and from 1700 to 1900. Positive social behavior events (touch other, play, etc.) remained high from 0500 to 2300, with peaks at 0600, 1300, 1500, and 1900. Negative social events occurred at low rates throughout the day and night, with peaks at 0600, 1900, and 2200. The majority of positive behavior events during the daylight and nighttime hours involved the mother-calf pairs. Furthermore, the calves and juveniles initiated approximately 60% of all social events during the daytime and 57% of all social interactions at night. The results of this study demonstrate the differences between diurnal and nocturnal activity budgets of a multi-age and sex elephant herd in a zoological facility, which highlights the importance of managing elephants to meet their 24 hr behavioral needs.


Subject(s)
Animals, Zoo/physiology , Circadian Rhythm/physiology , Elephants/physiology , Motor Activity/physiology , Social Behavior , Age Factors , Animals , Female , Male , Observation , Sex Factors , Statistics, Nonparametric , Time Factors
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