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Updated: Mar 8, 2026

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Published on: October 5, 2018
Non-associative versus associative learning by foraging predatory mites
Peter Schausberger1,2, Stefan Peneder3
1Department of Behavioural Biology, University of Vienna, Vienna, Austria. peter.schausberger@univie.ac.at.
Background:
Learning processes can be broadly categorized into associative and non-associative. Associative learning occurs through the pairing of two previously unrelated stimuli, whereas non-associative learning occurs in response to a single stimulus. How these two principal processes compare in the same learning task and how they contribute to the overall behavioural changes brought about by experience is poorly understood. We tackled this issue by scrutinizing associative and non-associative learning of prey, Western flower thrips Frankliniella occidentalis, by the predatory mite, Neoseiulus californicus. We compared the behaviour of thrips-experienced and -naïve predators, which, early in life, were exposed to either thrips with feeding (associative learning), thrips without feeding (non-associative learning), thrips traces on the surface (non-associative learning), spider mites with feeding (thrips-naïve) or spider mite traces on the surface (thrips-naïve).
Results:
Thrips experience in early life, no matter whether associative or not, resulted in higher predation rates on thrips by adult females. In the no-choice experiment, associative thrips experience increased the predation rate on the first day, but shortened the longevity of food-stressed predators, a cost of learning. In the choice experiment, thrips experience, no matter whether associative or not, increased egg production, an adaptive benefit of learning.
Conclusions:
Our study shows that both non-associative and associative learning forms operate in foraging predatory mites, N. californicus. The non-rewarded thrips prey experience produced a slightly weaker, but less costly, learning effect than the rewarded experience. We argue that in foraging predatory mites non-associative learning is an inevitable component of associative learning, rather than a separate process.
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