Sensory integration of danger and safety cues may explain the fear of a quiet coyote.

Sensory integration theory predicts natural selection should favour adaptive responses of animals to multiple forms of information, yet empirical tests of this prediction are rare, particularly in free-living mammals. Studying indirect predator cues offers a salient opportunity to inquire about multimodal risk assessment and its potentially interactive effects on prey responses. Here we exposed California ground squirrels from two study sites (that differ in human and domestic dog activity) to acoustic and/or olfactory predator cues to reveal divergent patterns of signal dominance. Olfactory information most strongly predicted space use within the testing arena. That is, individuals, especially those at the human-impacted site, avoided coyote urine, a danger cue that may communicate the proximity of a coyote. By contrast, subjects allocated less time to risk-sensitive behaviours when exposed to acoustic cues. Specifically, although individuals were consistent in their behavioural responses across trials, 'quiet coyotes' (urine without calls) significantly increased the behavioural reactivity of prey, likely because coyotes rarely vocalize when hunting. More broadly, our findings highlight the need to consider the evolution of integrated fear responses and contribute to an emerging understanding of how animals integrate multiple forms of information to trade off between danger and safety cues in a changing world.

Goffin's Cockatoos (Cacatua goffiniana) Can Solve a Novel Problem After Conflicting Past Experiences.

Novel problems often partially overlap with familiar ones. Some features match the qualities of previous situations stored in long-term memory and therefore trigger their retrieval. Using relevant, while inhibiting irrelevant, memories to solve novel problems is a hallmark of behavioral flexibility in humans and has recently been demonstrated in great apes. This capacity has been proposed to promote technical innovativeness and thus warrants investigations of such a mechanism in other innovative species. Here, we show that proficient tool-users among Goffin's cockatoos-an innovative tool-using species-could use a relevant previous experience to solve a novel, partially overlapping problem, even despite a conflicting, potentially misleading, experience. This suggests that selecting relevant experiences over irrelevant experiences guides problem solving at least in some Goffin's cockatoos. Our result supports the hypothesis that flexible memory functions may promote technical innovations.

A framework to evaluate whether to pool or separate behaviors in a multilayer network.

A multilayer network approach combines different network layers, which are connected by interlayer edges, to create a single mathematical object. These networks can contain a variety of information types and represent different aspects of a system. However, the process for selecting which information to include is not always straightforward. Using data on 2 agonistic behaviors in a captive population of monk parakeets (Myiopsitta monachus), we developed a framework for investigating how pooling or splitting behaviors at the scale of dyadic relationships (between 2 individuals) affects individual- and group-level social properties. We designed 2 reference models to test whether randomizing the number of interactions across behavior types results in similar structural patterns as the observed data. Although the behaviors were correlated, the first reference model suggests that the 2 behaviors convey different information about some social properties and should therefore not be pooled. However, once we controlled for data sparsity, we found that the observed measures corresponded with those from the second reference model. Hence, our initial result may have been due to the unequal frequencies of each behavior. Overall, our findings support pooling the 2 behaviors. Awareness of how selected measurements can be affected by data properties is warranted, but nonetheless our framework disentangles these efforts and as a result can be used for myriad types of behaviors and questions. This framework will help researchers make informed and data-driven decisions about which behaviors to pool or separate, prior to using the data in subsequent multilayer network analyses.