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Simple decision rules underlie collaborative hunting in yellow saddle goatfish.

ABSTRACT: Collaborative hunting, the coordination of animal behaviour in space and time to capture prey, is reported in several vertebrate species. However, previous studies are observational, hampering our ability to identify individual decision rules that result in collaboration. We experimentally investigated collaborative hunting in yellow saddle goatfish (Parupeneus cyclostomus) by exposing pairs to a mock prey that fled to an artificial shelter with multiple entrances. The first fish to initiate the chase (the 'initiator') was always closest to the prey and pursued it directly in its path. Conversely, the behaviour of the second goatfish (the 'follower') depended on its spatial position relative to the initiator. When the follower was less than one body length behind the initiator, it also accelerated directly towards the prey in over 95% of cases. However, if the two goatfish were separated by a distance of one body length or more, the follower chose a less direct route to reach the prey in 87% of cases. In this scenario, the follower often reached the prey's more distant refuge first, which might increase its hunting success or block the prey's escape path under natural conditions. Our findings suggest that coordinated hunting behaviour can result from simple, self-serving decisions.

SUBMITTER: Steinegger M

PROVIDER: S-EPMC5805943 | biostudies-other | 2018 Jan

REPOSITORIES: biostudies-other

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Simple decision rules underlie collaborative hunting in yellow saddle goatfish.

Steinegger Marc M Roche Dominique G DG Bshary Redouan R

Proceedings. Biological sciences 20180101 1871

Collaborative hunting, the coordination of animal behaviour in space and time to capture prey, is reported in several vertebrate species. However, previous studies are observational, hampering our ability to identify individual decision rules that result in collaboration. We experimentally investigated collaborative hunting in yellow saddle goatfish (<i>Parupeneus cyclostomus</i>) by exposing pairs to a mock prey that fled to an artificial shelter with multiple entrances. The first fish to initi ...[more]

PMID: 29367395

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Project description:Low rates of vaccination, emergence of novel variants of SARS-CoV-2, and increasing transmission relating to seasonal changes leave many U.S. communities at risk for surges of COVID-19 during the winter and spring of 2022 that might strain hospital capacity, as in previous waves. The trajectories of COVID-19 hospitalizations during this period are expected to differ across communities depending on their age distributions, vaccination coverage, cumulative incidence, and adoption of risk mitigating behaviors. Yet, existing predictive models of COVID-19 hospitalizations are almost exclusively focused on national- and state-level predictions. This leaves local policymakers in urgent need of tools that can provide early warnings about the possibility that COVID-19 hospitalizations may rise to levels that exceed local capacity. In this work, we develop simple decision rules to predict whether COVID-19 hospitalization will exceed the local hospitalization capacity within a 4- or 8-week period if no additional mitigating strategies are implemented during this time. These decision rules use real-time data related to hospital occupancy and new hospitalizations associated with COVID-19, and when available, genomic surveillance of SARS-CoV-2. We showed that these decision rules present reasonable accuracy, sensitivity, and specificity (all â‰¥80%) in predicting local surges in hospitalizations under numerous simulated scenarios, which capture substantial uncertainties over the future trajectories of COVID-19 during the winter and spring of 2022. Our proposed decision rules are simple, visual, and straightforward to use in practice by local decision makers without the need to perform numerical computations.Significance statementIn many U.S. communities, the risk of exceeding local healthcare capacity during the winter and spring of 2022 remains substantial since COVID-19 hospitalizations may rise due to seasonal changes, low vaccination coverage, and the emergence of new variants of SARS-CoV-2, such as the omicron variant. Here, we provide simple and easy-to-communicate decision rules to predict whether local hospital occupancy is expected to exceed capacity within a 4- or 8-week period if no additional mitigating measures are implemented. These decision rules can serve as an alert system for local policymakers to respond proactively to mitigate future surges in the COVID-19 hospitalization and minimize risk of overwhelming local healthcare capacity.

Project description:BackgroundAcute trauma of the wrist is one of the most frequent reasons for visiting the Emergency Department. These patients are routinely referred for radiological examination. Most X-rays however, do not reveal any fractures. A clinical decision rule determining the need for X-rays in patients with acute wrist trauma may help to percolate and select patients with fractures.Methods/designThis study will be a multi-center observational diagnostic study in which the data will be collected cross-sectionally. The study population will consist of all consecutive adult patients (≥18 years) presenting with acute wrist trauma at the Emergency Department in the participating hospitals. This research comprises two components: one study will be conducted to determine which clinical parameters are predictive for the presence of a distal radius fracture in adult patients presenting to the Emergency Department following acute wrist trauma. These clinical parameters are defined by trauma-mechanism, physical examination, and functional testing. This data will be collected in two of the three participating hospitals and will be assessed by using logistic regression modelling to estimate the regression coefficients after which a reduced model will be created by means of a log likelihood ratio test. The accuracy of the model will be estimated by a goodness of fit test and an ROC curve. The final model will be validated internally through bootstrapping and by shrinking it, an adjusted model will be generated. In the second component of this study, the developed prediction model will be validated in a new dataset consisting of a population of patients from the third hospital. If necessary, the model will be calibrated using the data from the validation study.DiscussionWrist trauma is frequently encountered at the Emergency Department. However, to this date, no decision rule regarding this type of trauma has been created. Ideally, radiographs are obtained of all patients entering one of the participating hospitals with trauma to the wrist. However, this is ethically and logistically not feasible and one could argue that patients, for whom no radiography is required according to their physician, are not suspected of having a distal radius fracture and thus are not part of the domain.Trial registrationThis study is registered at the Netherlands Trial Register (NTR 2544) and was granted permission by the Medical Ethical Committee of the Academic Medical Center Amsterdam on 06-01-2011.

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Simple decision rules underlie collaborative hunting in yellow saddle goatfish.

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Simple decision rules underlie collaborative hunting in yellow saddle goatfish.

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