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Predation threat is a major driver of behavior in many prey species. Animals can recognize their relative risk of predation based on cues in the environment, including visual and/or chemical cues released by a predator or from its prey. When threat of predation is high, prey often respond by altering their behavior to reduce their probability of detection and/or capture. Here, we test how a clonal fish, the Amazon molly (Poecilia formosa), behaviorally responds to predation cues. We measured aggressive and social behaviors both under ‘risk’, where chemical cues from predatory fish and injured conspecifics were present, and control contexts (no risk cues present). We predicted that mollies would exhibit reduced aggression towards a simulated intruder and increased sociability under risk contexts as aggression might increase their visibility to a predator and shoaling should decrease their chance of capture through the dilution effect. As predicted, we found that Amazon mollies spent more time with a conspecific when risk cues were present, however they did not reduce their aggression. This highlights the general result of the ‘safety in numbers’ behavioral response that many small shoaling species exhibit, including these clonal fish, which suggests that mollies may view this response as a more effective anti-predator response compared to limiting their detectability by reducing aggressive conspecific interactions. 

The study of individual behavioral variation, sometimes called animal personalities or behavioral types, is now a well-established area of research in behavioral ecology and evolution. Considerable theoretical work has developed predictions about its ecological and evolutionary causes and consequences, and studies testing these theories continue to grow. Here, we synthesize the current empirical work to shed light on which theories are well supported and which need further refinement. We find that the major frameworks explaining the existence of individual behavioral variation, the pace-of-life syndrome hypothesis and state-dependent feedbacks models, have mixed support. The consequences of individual behavioral variation are well studied at the individual level but less is known about consequences at higher levels such as among species and communities. The focus of this review is to reevaluate and reestablish the foundation of individual behavioral variation research: What do we know? What questions remain? And where are we going next?