Can Donkey Behavior and Cognition Be Used to Trace Back, Explain, or Forecast Moon Cycle and Weather Events?

Abstract

Simple SummaryDonkeys have been traditionally attributed the ability to inform humans about the environment. Carefully observing the behavior and cognitive reactions of donkeys in their habitat may enable to quantify such reactions to develop informative mathematical models. These models can be used to explain present environmental situations, trace back past events or even predict future conditions. Our results suggest, environmental stressing situations may affect donkeys in a way that they register the cognitive adaptations or sequels derived from such situations. Furthermore, such environmental events may not only affect the present cognitive status of the animals, but they may drive this cognitive record affecting the behavioral patterns donkeys display through their lives. Our model is able to explain 75.9% of the variability in response type and intensity, mood, or learning capabilities. Conclusively, donkeys can be used as an environment informative sensitive tool and may therefore, predict and register slight human-unappreciable climatic variations to which they may behaviorally adapt beforehand.AbstractDonkeys have been reported to be highly sensitive to environmental changes. Their 8900–8400-year-old evolution process made them interact with diverse environmental situations that were very distant from their harsh origins. These changing situations not only affect donkeys’ short-term behavior but may also determine their long-term cognitive skills from birth. Thus, animal behavior becomes a useful tool to obtain past, present or predict information from the environmental situation of a particular area. We performed an operant conditioning test on 300 donkeys to assess their response type, mood, response intensity, and learning capabilities, while we simultaneously registered 14 categorical environmental factors. We quantified the effect power of such environmental factors on donkey behavior and cognition. We used principal component analysis (CATPCA) to reduce the number of factors affecting each behavioral variable and built categorical regression (CATREG) equations to model for the effects of potential factor combinations. Effect power ranged from 7.9% for the birth season on learning (p < 0.05) to 38.8% for birth moon phase on mood (p < 0.001). CATPCA suggests the percentage of variance explained by a four-dimension-model (comprising the dimensions of response type, mood, response intensity and learning capabilities), is 75.9%. CATREG suggests environmental predictors explain 28.8% of the variability of response type, 37.0% of mood, and 37.5% of response intensity, and learning capabilities.

Judgement Bias in Miniature Donkeys: Conditioning Factors and Personality Links

“…Individual personality was scored using an adaptation of the questionnaire proposed by Navas et al [ 38 ], and French [ 39 ]. The aforementioned methodology has been previously used to evaluate behavioural patterns in problem-focused coping styles, the genetic background behind them and the conditioning factors involved in donkeys [ 24 , 27 , 28 , 35 , 40 ]. A questionnaire was completed by ten observers.…”

“…The expression degree of a total of eighteen behavioural traits was ordinally rated from 1 to 10 with these values representing the minimum and maximum extremes in the scale, respectively. The description of each of the levels comprising each of the traits in the scale was accessed from Navas et al [35] and Navas González, et al [40], and a summary of the descriptors, scales, and extreme adjectives used is shown in Table 1. Since sample size was a limitation in this study, parametric assumptions were tested to decide on the most appropriate statistical approach to follow.…”

Dumb or smart asses? Donkey's (Equus asinus) cognitive capabilities share the heritability and variation patterns of human's (Homo sapiens) cognitive capabilities

“…The standardization and development of the tests and scales was described in a previous stage of the study (Navas et al, 2017a;Navas González et al, 2018b) and is summarized in Figure 1. Statistical verification that tests being used are in fact measuring the constructs they are intended to measure and whether they can do so with internal reliability was performed in two previous studies (Navas et al, 2017a;Navas González et al, 2018a).…”