How the Foraging Decisions of a Small Ruminant are Influenced by Past Feeding Experiences with Low-Quality Food

Document Type

Article

Journal/Book Title/Conference

Behavioural Processes

Volume

126

Publisher

Elsevier BV

Publication Date

2-27-2016

First Page

12

Last Page

20

Abstract

Feeding experiences with low-quality foods can be improved when these foods are ingested in close temporal association with foods of higher nutritional quality. However, preference for low-quality foods in nature seems to be rather insensitive to past positive experiences and more related to their intrinsic nutritional value. An explanation for this observation is still lacking, mainly because little is known about how herbivores use information about low-quality foods during foraging. Our objective was to provide original information about this issue using a small ruminant (sheep; Ovis aries) as animal model. We manipulated the sheep’s experience with a low-quality food (wheat straw) using a conditioning procedure (“oral-delay conditioning procedure”), and then we evaluated the use of this information in a simulated foraging scenario provided with wheat straw and a variable amount of a high-quality food in spatially separated feeding stations. Inclusion of wheat straw into the diet was strongly dependent on the availability of the high-quality food. We observed a threshold level in the availability of the high-quality food, which defined a zone of drastic change in the likelihood of inclusion of the wheat straw into the diet (i.e., acceptance or rejection of wheat straw). This threshold level did not change for sheep with (CS+) or without (CS-) a previous positive experience with wheat straw. However, once foraging conditions stimulated all sheep to start including the wheat straw into the diet (i.e., below the threshold level), the intake of this food was greater by CS+ sheep. This increased intake was not explained by a higher motivation to eat the wheat straw but to a greater amount of time spent foraging this food and less time spent searching for the preferred higher-quality alternative. We discuss these results based on optimal foraging models and learning models of diet selection.

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