“…We were thus able to sample during (2020) and after (2021) the Covid-19 lockdown the same areas we sampled before lockdown (2018) in previous studies (Díaz et al, 2013(Díaz et al, , 2021(Díaz et al, , 2022. Paired comparisons according to study sites (see below) control for among-sites (cities and surrounding rural areas) variation in other factors potentially influencing FIDs, such as vegetation structure, human population density or the level of governmental restrictions (Díaz et al, 2022;Mikula et al, 2022;Morelli et al, 2022).…”
“…We were thus able to sample during (2020) and after (2021) the Covid-19 lockdown the same areas we sampled before lockdown (2018) in previous studies (Díaz et al, 2013(Díaz et al, , 2021(Díaz et al, , 2022. Paired comparisons according to study sites (see below) control for among-sites (cities and surrounding rural areas) variation in other factors potentially influencing FIDs, such as vegetation structure, human population density or the level of governmental restrictions (Díaz et al, 2022;Mikula et al, 2022;Morelli et al, 2022).…”
“…We fitted a Gaussian model structure and ran four Markov Chain Monte Carlo chains with default priors (i.e. uninformative priors) (following [ 48 ]). Also, to minimize divergent transitions, we set the target average proposal acceptance probability to 0.999 and the maximum tree depth to 20 (modified from [ 48 ]).…”
Section: Methodsmentioning
confidence: 99%
“…uninformative priors) (following [ 48 ]). Also, to minimize divergent transitions, we set the target average proposal acceptance probability to 0.999 and the maximum tree depth to 20 (modified from [ 48 ]). Lastly, we calculated the conditional R 2 and marginal R 2 to determine how much of the variance was explained by both fixed and random effects (conditional R 2 ) and only by the fixed factors (marginal R 2 ) using the b2_bayes function from the ‘performance’ package v. 0.9.1 [ 49 ].…”
Human-induced disturbances affect animal behaviours such as anti-predatory responses. Animals in urban environments tend to exhibit a reduced escape response, measured as a shorter flight initiation distance (FID), compared to their rural counterparts. While FID has been evaluated in animals dwelling in contrasting habitats (e.g. urban versus rural), little is known about how this response varies within urban environments, especially in tropical cities. Here, we studied the FID of 15 resident bird species in Bogota, Colombia, at 22 sites grouped into four categories (natural sites, metropolitan parks, zonal parks and residential areas) that differed in landscape features and evaluated which factors affected the escape responses of birds. We showed that birds foraging in larger flocks are more tolerant when being approached but they do not seem to be influenced by other factors such as heterospecific flock size, noise levels, pedestrian density, predator density, natural cover or body length. Also, birds inhabiting residential areas and parks showed a shorter FID compared to birds in natural areas suggesting that they are more tolerant of human-related disturbances compared to their conspecifics that live in natural areas within the city. Our study shows important differences in bird anti-predatory responses within the city and suggests that social strategies (i.e. flocking patterns) may be a mechanism for adapting to human-induced disturbances in urban tropical environments.
“…Various aspects of the economy of escape have been studied, e.g., the effect of life history traits (Blumstein, 2006;Møller, 2014), human disturbance (Fernández-Juricic et al, 2005;Burger et al, 2010;Li et al, 2011), habitat type (Stankowich & Coss, 2007;Davey et al, 2019;Uchida et al, 2020), distance to refuge (Cooper & Samia, 2018;Morelli et al, 2022), or group size (Braimoh et al, 2018;Morelli et al, 2019). However, not many studies assessed how behaviours of individuals prior to and during approach affect escape decisions.…”
Escape represents an important component of animals’ antipredator behaviour entailing both benefits and costs dependent on a moment an animal flees upon predator’s approach. In this study, I examined how the level of vigilance and foraging activity affected escape decision in the urban hooded crow Corvus cornix, predicting that alert distance (AD) and flight initiation distance (FID) should be positively affected by the level of vigilance and negatively affected by foraging activity, whereas buffer distance (BD) should be negatively affected by the level of vigilance and positively affected by foraging activity. Using LMMs it was shown that percent of time crows allocated to vigilance was positively correlated with AD and FID, whereas foraging activity of crows had negative impact on AD and FID. In addition, both AD and FID were positively related to starting distance (SD), while AD was also positively influenced by tree coverage. BD was positively affected by foraging activity and AD. This study demonstrated that more vigilant birds detected predators earlier, which is in accordance with the major function of vigilance. Also, it was shown that foraging crows delayed their escape, once the predator has been detected, as benefits of delayed flight, such as feeding on a profitable food item or within a profitable patch, may outweigh costs, which is consistent with the optimal escape theory.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.