Developing an integrative understanding of escape mode decisions
Type
Journal article
Language
English
Date issued
2025
Author
Díaz, Mario
Møller, Anders P.
Benedetti, Yanina
Blumstein, Daniel T.
Markó, Gábor
Morelli, Federico
Ibáñez-Alamo, Juan D.
Jokimäki, Jukka
Kaisanlahti-Jokimäki, Marja-Liisa
Mikula, Peter
Tätte, Kunter
Grim, Tomas
Faculty
Wydział Medycyny Weterynaryjnej i Nauk o Zwierzętach
PBN discipline
biological sciences
Journal
Animal Behaviour
ISSN
0003-3472
Volume
229
Number
November 2025
Pages from-to
art. 123338
Abstract (EN)
Optimal escape theory predicts that individuals should escape when the costs of staying (risk of being injured or killed) exceed the costs of leaving (energetic costs of escape, lost foraging opportunities and costs incurred for monitoring the approaching predator). We extend these theoretical principles to analyse preferences for alternative escape modes in a model animal group, birds, which can escape by either flight (costlier but safer) or using cheaper but riskier alternatives (jump, walk, or swim). We used a large, published database that included 21 222 records on 179 species taken in 15 European localities during the breeding seasons of 2009–2019, with data on escape mode, latitude, habitat (urban or rural), precipitation and temperature. Most individuals escaped by taking flight (15 940 records; 79%). Variation in escape mode decisions was mostly driven by species-specific traits (body size, diet), whereas external environmental variables (climate, geography, habitat) showed small effects. Flight initiation distances were longer when birds escaped by taking flight than when they chose lower-cost alternatives. Overall, escape mode preferences showed spatial and temporal variation compatible with expectations from risk–energy trade-off optimization. Escape mode decisions seemed more related to predation avoidance and flight initiation distance decisions to energy-saving goals. Thus, escape mode preferences interacted with fleeing–staying decisions, suggesting a behavioural integration of different aspects of escape strategies under a general optimization model.
License
CC-BY-NC - Attribution-NonCommercial
Open access date
September 30, 2025