An Experimental Test of Predator Detection Rates Using Groups of Free‐living Emus

Boland, Christopher R. J.

doi:10.1046/j.1439-0310.2003.00860.x

Cited by 77 publications

(56 citation statements)

References 45 publications

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“…Despite these limitations, observations of predation in the wild are rare (Hanlon and Messenger, 1988;Boland, 2003;Mather, 2010), thus laboratory experiments provide a useful opportunity to gain a better understanding of when and how cephalopods vary their behaviors in response to different threats. Surprisingly few studies have evaluated cephalopod antipredator tactics in response to real predators, and those that do exist have produced inconsistent results.…”

Section: Discussionmentioning

confidence: 99%

Defensive Responses of Cuttlefish to Different Teleost Predators

Staudinger

Buresch

Mäthger

et al. 2013

The Biological Bulletin

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Abstract. We evaluated cuttlefish (Sepia officinalis) responses to three teleost predators: bluefish (Pomatomus saltatrix), summer flounder (Paralichthys dentatus), and black seabass (Centropristis striata). We hypothesized that the distinct body shapes, swimming behaviors, and predation tactics exhibited by the three fishes would elicit markedly different antipredator responses by cuttlefish. Over the course of 25 predator-prey behavioral trials, 3 primary and 15 secondary defense behaviors of cuttlefish were shown to predators. In contrast, secondary defenses were not shown during control trials in which predators were absent. With seabass-a benthic, sit-and-pursue predator-cuttlefish used flight and spent more time swimming in the water column than with other predators. With bluefish-an active, pelagic searching predator-cuttlefish remained closely associated with the substrate and relied more on cryptic behaviors. Startle (deimatic) displays were the most frequent secondary defense shown to seabass and bluefish, particularly the Dark eye ring and Deimatic spot displays. We were unable to evaluate secondary defenses by cuttlefish to flounder-a lie-and-wait predator-because flounder did not pursue cuttlefish or make attacks. Nonetheless, cuttlefish used primary defense during flounder trials, alternating between cryptic still and moving behaviors. Overall, our results suggest that cuttlefish may vary their behavior in the presence of different teleost predators: cryptic behaviors may be more important in the presence of active searching predators (e.g., bluefish), while conspicuous movements such as swimming in the water column and startle displays may be more prevalent with relatively sedentary, bottomassociated predators (e.g., seabass).

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Section: Discussionmentioning

confidence: 99%

Defensive Responses of Cuttlefish to Different Teleost Predators

Staudinger

Buresch

Mäthger

et al. 2013

The Biological Bulletin

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“…For example, panics help herding animals avoid predators after collective detection of a predator (Boland, 2003). Improved collective predator detection and evasion is known as the many-eyes hypothesis and it is thought to be one of the main drivers behind the evolution of cooperative group behavior (Roberts, 1996).…”

Section: Correlations Can Improve Performance In Voting Modelsmentioning

confidence: 99%

Rescuing Collective Wisdom when the Average Group Opinion Is Wrong

2017

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The total knowledge contained within a collective supersedes the knowledge of even its most intelligent member. Yet the collective knowledge will remain inaccessible to us unless we are able to find efficient knowledge aggregation methods that produce reliable decisions based on the behavior or opinions of the collective's members. It is often stated that simple averaging of a pool of opinions is a good and in many cases the optimal way to extract knowledge from a crowd. The method of averaging has been applied to analysis of decision-making in very different fields, such as forecasting, collective animal behavior, individual psychology, and machine learning. Two mathematical theorems, Condorcet's theorem and Jensen's inequality, provide a general theoretical justification for the averaging procedure. Yet the necessary conditions which guarantee the applicability of these theorems are often not met in practice. Under such circumstances, averaging can lead to suboptimal and sometimes very poor performance. Practitioners in many different fields have independently developed procedures to counteract the failures of averaging. We review such knowledge aggregation procedures and interpret the methods in the light of a statistical decision theory framework to explain when their application is justified. Our analysis indicates that in the ideal case, there should be a matching between the aggregation procedure and the nature of the knowledge distribution, correlations, and associated error costs. This leads us to explore how machine learning techniques can be used to extract near-optimal decision rules in a data-driven manner. We end with a discussion of open frontiers in the domain of knowledge aggregation and collective intelligence in general.

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“…This behaviour may be governed by the need to find appropriate sites for reproduction (Danchin et al 2001), to reduce predation risks related, for example, to the interception of advertisement signals by predators (Myrberg 1981;Luczkovich et al 2000) taking advantage of dilution effects (Foster and Treherne 1981), increased vigilance (Boland 2003), or confusion effects (Krakauer 1995), and to enhance mate attraction by increasing loudness and the area covered by the calling fish sounds (McCauley and Cato 2000). The effort and risk for a newcomer to assess a suitable reproduction habitat can be reduced if this habitat is already occupied by breeding conspecifics.…”

Section: Detecting and Selecting Mates In Aggregations (Chorus)mentioning

confidence: 99%

Fish Sounds and Mate Choice

Amorim

Vasconcelos

Fonseca

2015

Animal Signals and Communication

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Fish acoustic signals associated with mating behaviour are typically low-frequency sounds produced by males when in close proximity to females. However, some species make sounds that serve the function and follow the design of advertisement calls, well known in insects, anurans, and birds. Close-range courtship acoustic signals may be used by females in mate assessment as they contain information of male quality such as size and condition. For example, sounddominant frequency, amplitude, and fatigue resistance may signal body size whereas pulse period (i.e. muscle contraction rate) and calling activity are related with body condition in some species. Some signal features, such as sound pulse number, may carry multiple messages including size and condition. Playback experiments on mate choice of a restricted number of species suggest that females prefer vocal to silent males and may use sound frequency, amplitude, and mainly calling rate when assessing males. The assessment of males by females becomes more challenging when males engage in choruses or when sounds are otherwise masked by anthropogenic noise but almost nothing is known about how these aspects affect mating decisions and fish reproductive success.We would like to dedicate this review to Professor Vitor Almada, a person of vision and a landmark in fish behaviour in Portugal.

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An Experimental Test of Predator Detection Rates Using Groups of Free‐living Emus

Cited by 77 publications

References 45 publications

Defensive Responses of Cuttlefish to Different Teleost Predators

Defensive Responses of Cuttlefish to Different Teleost Predators

Rescuing Collective Wisdom when the Average Group Opinion Is Wrong

Fish Sounds and Mate Choice

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