This is a Preprint and has not been peer reviewed. This is version 3 of this Preprint.
Downloads
Supplementary Files
Authors
Abstract
Despite a wealth of studies documenting prey responses to perceived predation risk, researchers have only recently begun to consider how prey integrate information from multiple cues in their assessment of risk. We conduct a systematic review and meta-analysis of studies that experimentally manipulated perceived predation risk in birds and evaluate support for three alternative models of cue integration: redundancy/equivalence, enhancement, and antagonism. One key insight from our analysis is that the current theory, generally applied to study cue integration in animals, is incomplete. These theories specify the effects of increasing information level on mean, but not variance, in responses. In contrast, we show that providing multiple complementary cues of predation risk simultaneously does not affect mean response, but rather, reduces variance in responses across studies. We propose this may arise via maximum-likelihood estimation (MLE) integration. Although the MLE framework has been applied to study cue integration in humans, to date, it has not been applied to studies of cue integration in non-human animals. We highlight the broad applicability of MLE integration for information integration problems and propose avenues for future work. Our meta-analysis illustrates how explicit consideration of variance in responses can yield important biological insights.
DOI
https://doi.org/10.32942/X26W3K
Subjects
Ecology and Evolutionary Biology, Life Sciences
Keywords
predation risk, cues of predation, information theory, birds, Aves, cue uncertainty
Dates
Published: 2023-10-26 06:32
Last Updated: 2023-12-07 14:03
Older Versions
License
CC-BY Attribution-NonCommercial 4.0 International
Additional Metadata
Language:
English
Conflict of interest statement:
None
Data and Code Availability Statement:
All data and code required to reproduce the analyses and figures presented in the manuscript are available at: https://itchyshin.github.io/multimodality/ and archived on Open Science Framework (OSF): DOI 10.17605/OSF.IO/9VMZX
There are no comments or no comments have been made public for this article.