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. 2025 Oct 29;72(4):557–567. doi: 10.1093/cz/zoaf069

Which factors can influence budgerigars' feeding behavior under predation risk: individual and/or social factors?

Xueqi Zhao 1, Jie Su 2, Manxi Lu 3, Jiangping Yu 4,b,✉, Haitao Wang 5,6,✉
Editor: Zu-Shi Huang
PMCID: PMC13500172  PMID: 42634719

Abstract

Animals face a fundamental risk-reward trade-off when making feeding decisions in the presence of predation. This trade-off requires balancing time spent being vigilant with time spent feeding under predation risk, influenced by both individual and social factors. However, it remains unclear which factor plays a more significant role. In this study, we aimed to determine whether individual factors (sex, personality, and body condition) and social factors (social familiarity and social rank) influence feeding and vigilance behaviors under predation risk. When alone with the predator, budgerigars with longer tarsus length exhibited shorter latency to feed, and bold budgerigars tended to have a lower frequency of scans, but neophobia and body condition did not influence these behaviors. When facing the predator with familiar group members, individuals showed shorter latency to feed, and a lower frequency of scans compared to when with unfamiliar group members or alone. Moreover, social rank was the most important factor affecting latency to feed. Our findings suggested that both individual and social factors can influence budgerigars' foraging behaviors, with social factors playing a more significant role than individual factors when individuals are in a group.

Keywords: feeding behaviors, individual factors, predation risk, social factors

Graphical Abstract

Graphical Abstract.

For image description, please refer to the figure legend and surrounding text.

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Predation is one of the primary causes of mortality for most animal individuals, and prey typically employ appropriate anti-predator strategies to enhance their survival rates (Khater et al. 2016; Tanis et al. 2018; Dugatkin 2020). Vigilance is a common anti-predation behavior that enables individuals to detect predators early and provides an opportunity for escape before danger becomes imminent (Sirot and Pays 2011; Beauchamp 2019). In response to high predation risk, animals often allocate more time and effort to vigilance (Lima et al. 2005; Beauchamp 2020). However, heightened vigilance toward potential predators may reduce investment in other activities, such as shorter sleep durations and fewer foraging opportunities (Dall et al. 2001; Kavaliers and Choleris 2001; Lima et al. 2005). Foraging, as a fundamental activity for survival, often occupies a large portion of an animal's day and conflicts with the need to maintain vigilance. Thus, animals should consider the trade-offs between the benefits of foraging and the risk of predation to maximize their fitness (Arkhipov and Yeletsky 2021; Wong et al. 2022; Wang et al. 2024).

Most animals are capable of making trade-offs based on their own states and environmental risks, adjusting the timing, location, and frequency of foraging to minimize the likelihood of encountering predators (Drenske et al. 2024; Shiratsuru and Pauli 2024). When avoiding predators is not possible, they may stop foraging activities and shift their focus to monitoring the predator (Sirot et al. 2021). However, due to the need for energy, they will resume foraging at an appropriate time. Studies have shown that the time between stopping activity and resuming foraging can vary from a few seconds to several hours, both within and across species (Hegner 1985; Kotler 1992; Arteaga-Torres et al. 2020; LaRocque et al. 2023; Wang et al. 2024). Such behavioral differences reflect diverse adaptive strategies in response to predation risk, likely influenced by the intricacies of individual and social factors.

Individual factors of animals are crucial indicators for predicting anti-predator behaviors. Typical individual factors, such as sex, personality, and body condition, have been widely studied. In many animal species, males are more vigilant than females, often explained by differences in intraspecific competition or the absolute energy needs between them (Pays and Jarman 2008; Ahmed and Urfi 2024). However, in some species, the number of differentially expressed genes in response to predator stress is higher in females than in males (Berkel and Cacan 2022), which may result in females exhibiting higher vigilance. Personality is considered a set of individual differences in behavior, which are stable and repeatable over time and across contexts (Réale et al. 2007; Adriaenssens and Johnsson 2013; Lalot et al. 2017; Kaiser and Müller 2021). Personalities often correlate with each other at the individual level, forming behavioral syndromes (Adriaenssens and Johnsson 2013; Morinay et al. 2019). Compared to reactive individuals, proactive individuals are more aggressive, exhibit lower neophobia and higher boldness, so they may have shorter vigilance times under predation risk (Groothuis and Carere 2005; Aplin et al. 2014). An animal's body condition primarily refers to its body size, weight, fat reserves, etc. (Gallagher et al. 2014; Stepkovitch et al. 2019; Allen et al. 2024). Individuals with poor body condition are predicted to have shorter foraging delays, possibly because they need to forage more intensively to recover to better condition (Siegal et al. 2022). Although individual factors have been shown to influence foraging behavior under predation risk, it remains unverified whether these influences exhibit consistent patterns across different social factors.

For social animals, behavior under predation risk may be influenced by social factors. In high-risk areas, most animals tend to form groups, which increases the likelihood of detecting or confusing predators, thereby reducing the individual's relative risk of predation (Krakauer 1995; Lehtonen and Jaatinen 2016; Kareklas et al. 2018; Polyakov et al. 2022). Therefore, individuals in groups often show signs of reduced risk perception compared to solitary individuals (Waite 1987; Kareklas et al. 2018). Additionally, in some species, individuals could assess current predation risk through chemical, acoustic, or visual signals from their companions, allowing them to adjust their alertness and behavioral responses (Oliveira et al. 2017; Ferreira et al. 2022; Zhao et al. 2024). For example, great tits (Parus minor) could assess the predation risks from the information contained in the conspecific alarm calls, and respond more strongly to Eurasian sparrowhawk (Accipiter nisus) than to common cuckoo (Cuculus canorus) or dove (Streptopelia orientalis) (Yu et al. 2017). However, social factors are complex, with various social interaction models and ways of delivering information among individuals. The ability to effectively interpret predation risk cues often depends on the degree of familiarity between companions, as familiar companions may exhibit increased sensitivity to alterations in their peers' behavior (Griffiths et al. 2004; Strodl and Schausberger 2012). In addition, familiar group members can form stable hierarchical relationships through long-term interactions and adjust their behavior patterns accordingly. When food resources are scarce, high-ranking individuals typically assess predation risks more cautiously, because they possess greater control over access to food (Hegner 1985; Högstad 1988). In contrast, low-ranking individuals, who may be at risk of being excluded from feeding opportunities, may display a greater eagerness to feed even under predation risks (Hegner 1985; Högstad 1988). Therefore, the feeding behavior of social animals under predation risks may become more diverse and dynamic due to the complexity of social factors.

Budgerigars (Melopsittacus undulatus) are group-living birds with a long history of domestication. Previous studies have shown that budgerigars possess distinct personalities and strong social behaviors (Buckley et al. 2017; Medina-García et al. 2017), and may identify predation risk through visual or acoustic signals (Wang et al. 2024). In this study, we explored the potential influence of individual and social factors on the feeding behavior of budgerigars under predation risk. Specifically, we observed the latency to feed in budgerigars of different group sizes, familiarity levels, and social ranks when exposed to domestic cats, which serve as predators. We also measured individual factors, including sex, personality traits (boldness and exploration), and body condition (body length, wing length, tarsus length, and body weight). We hypothesized that budgerigars would adjust their feeding behavior according to these factors. Regarding individual factors, we predicted that (1) compared to males, female budgerigars would have shorter latency to feed, as female budgerigars exhibit a higher metabolic rate (Koutsos et al. 2001; Schnegg et al. 2007); (2) budgerigars in poorer body condition, or those exhibiting less neophobic and more bold behaviors, would tend to display shorter vigilance times. Regarding social factors, we predicted that: (3) budgerigars in groups would be less responsive to predators than solitary individuals; (4) budgerigars with familiar group members would exhibit lower levels of vigilance to potential predation risks than individuals with unfamiliar group members; (5) higher ranking budgerigars would exhibit longer latency to feed and higher levels of vigilance under predation risk.

Materials and methods

Subjects

Adult budgerigars (78 males, 72 females) were used as subjects in this study. The budgerigars were purchased from a local pet market and had the same rearing history. Each budgerigar was fitted with a uniquely numbered ring for individual identification. Before the experiment, every individual was housed alone in a cage (90 cm × 40 cm × 50 cm) containing a food box, a water box, and a perch. Daylight was provided from 7:00 AM to 7:00 PM, following a 12-hour light/dark cycle. The budgerigars were fed grain seeds and provided drinking water daily, and were regularly supplemented with fresh vegetables, fruits, and parrot nourishment pills to ensure a balanced diet. During the experiment, four same-sex individuals and one opposite-sex individual (hereafter referred to as “opposite sex individuals”) were housed together in a cage. Among these, there were 16 groups consisting of 4 males and 1 female, and 14 groups consisting of 4 females and 1 male. Previous research has indicated that the time required for a flock of 5–7 birds to establish a stable hierarchy ranges from 3 to 11 days (Verbeek et al. 1999; Lange and Leimar 2004). In this study, we provided each group of budgerigars with a month to acclimate and establish a stable social hierarchy. Then, the social rank assessment and the dummy predator experiment were conducted. In total, the experiment spanned approximately one and a half months, during which the budgerigars remained active and in good health. After the experiment, the budgerigars were housed individually in separate cages.

Social rank assessment

The social rank assessment among familiar budgerigar groups (n = 30 groups) was conducted from September 4 to 20 October 2023. The experiment was conducted in a 90 cm × 40 cm × 50 cm bird cage located in the behavioral observation room. A removable camera (HDR-PJ675; Sony, Shanghai, China) was used to record budgerigars' interactions. Prior to the experiment, a fasting period of 4 h was implemented for the budgerigars to increase motivation. Five budgerigars from the same group were carefully introduced into the bird cage every day and allowed a 2-minute acclimation period. Subsequently, they were provided with a designated food box filled with full-grain seeds and then observed for 15 min (7 to 10 days in total, amounting to 105–150 min) (Ramos et al. 2021). The total number of agonistic interactions between individuals was recorded in a matrix, including the identification of winners and losers for each interaction. Agonistic interaction matrices were used to produce a dominance hierarchy based on the Elo rating system (Neumann et al. 2011). Here, we calculated the stability index (S-value) for all budgerigars in each group. The average S-value of the social hierarchy in each group was 0.71 ± 0.11 (SD), which indicated that their social hierarchy was relatively stable.

Dummy predator experiment

  • a) familiar and unfamiliar groups

The dummy predator experiment began 1 h after the final social rank assessment. A domestic cat model made of plush fabric standing on a specimen mount was used to assess the budgerigars' responses to natural predator stimuli (Fig. 1). A specimen mount without the cat model was used as a control. The domestic cat model and the specimen mount were used in a randomized order, with each being displayed only once for one group. Budgerigars from a group (familiar groups: n = 30 groups) were first transferred from the feeding chamber to the experimental chamber and given a 2-minute acclimation period (Wang et al. 2024). During this period, the domestic cat model or the specimen mount was hidden behind an opaque curtain positioned 1 m in front of the subjects. After the acclimatization period, the experimenter gently pulled the curtain to reveal the domestic cat model or the specimen mount, exposing the budgerigars to the predator or non-predator for 3 min. Following this, the curtain was carefully closed, and the budgerigars were observed for another 2 min (Wang et al. 2024). The order of presentation for the dummy predator and control conditions was randomized. The latency to feed (the amount of time from the stimulus onset to the presence of the budgerigar's feeding behavior) and the number of scans (head-up scanning with neck stretched while feeding) were recorded (Kong et al. 2021; Wang et al. 2024). If the budgerigar did not resume feeding during the observation period, the maximum time of 301 s was recorded. After the experiment, the subject was returned to the birdcage in the feeding chamber and fed at a random time within a 0–2 h period to avoid the subject perceiving any patterns that might affect the experimental results. On the day after the familiar group experiment concluded, every five budgerigars from five groups were randomly and temporarily grouped (unfamiliar groups: n = 30 groups) to conduct the dummy predator experiment immediately. Afterward, all budgerigars in unfamiliar groups were returned to their original groups.

Figure 1.

Fig. 1 Schematic diagram of the dummy predator experiment. Budgerigars within the same group were housed in an experimental cage. A domestic cat model was positioned 100 cm in front of the cage, and an opaque curtain was placed between the cage and the cat model. During the experiment, the experimenter gently pulled the curtain to expose the budgerigars to the domestic cat model for 3 minutes, then closed the curtain and waited 2 minutes. The feeding latency and the frequency of scans of the budgerigars were recorded during the total 5-minute experiment.

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Schematic diagram of the dummy predator experiment.

  • b) solitary individuals

After the dummy predator experiment was conducted with both familiar groups and unfamiliar groups, all individuals were separated for 1 day and were treated as temporary “solitary individuals” before undergoing the dummy predator experiment again. The procedures for these solitary individuals (n = 150) were the same as those used for the familiar and unfamiliar groups. After the assessment, all budgerigars were returned to their original groups.

Personality test

In September 2023, we conducted the novel object test and the startle test. The sequence of the two tests was random. Each test was conducted independently on each bird. In November 2023, we repeated the novel object test and the startle test, using the same methods and sequence as those in September.

  • a) Novel object test

Prior to testing, budgerigars were food-deprived for 4 h to increase motivation. Since red and blue have been shown to be aversive or fearful colors for birds (Greig-Smith and Rowney 1987; Protti-Sánchez et al. 2023), we placed a red or blue plastic ball within 15 cm of the only feeder in a cage, then introduced budgerigars from a predetermined position into the cage and recorded the latency for them to feed during the 10-minute test (David et al. 2011; Barrett et al. 2022). If the individual failed to resume feeding within 10 min, a latency time of 601 s was assigned.

  • b) Startle test

Holes were drilled at both ends of the food box in the experimental cage, through which a thin wire was passed and secured with clear tape, with the other end attached to the outside of the behavioral observation room. Budgerigars were food-deprived for 4 h before the test. Each budgerigar was placed in the experimental cage, and the researcher gently pulled the wire when the budgerigars began feeding, creating vibrations in the feeder and a brief sound that startled the budgerigars, causing them to leave the feeder. Latency to feed was recorded during the 10-minute test. Individuals that did not resume feeding within 10 min were assigned a latency time of 601 s. The boldness score was calculated as the difference between 601 s and the latency to feed (David et al. 2011).

Quantifying bird morphology

We measured the morphology of all 150 budgerigars in November 2023. Body length, wing length, and tarsus length were measured using a straightedge with a precision of 0.01 mm, and weight was recorded using an electronic balance with a precision of 0.01 g. The scaled mass index (SMI) of budgerigars was computed as follows (Peig and Green 2009):

scaledmassindex:Mi∧=Mi[L0Li]bSMA

where Mi and Li are body mass and body length of individual i, respectively; bSMA is the scaling exponent estimated by the standardized major axis (SMA) regression of M on Li; L0 is the mean value of Li.

Data collection and analysis

We performed all statistical analyses in R version 4.2.1 (https://www.r-project.org). Elo ratings were calculated for all budgerigars in each group. The social rank score for each budgerigar was calculated using the Bayesian Elo rating method (the “EloRating” package) (Neumann et al. 2011). This method initialized individual ratings at 1000, with a predetermined point increment or decrement (K) of 200 for each interaction. Budgerigars were ranked according to their social rating scores. The Kolmogorov–Smirnov normality test was used to determine if the data conformed to a normal distribution. In addition, the Breusch–Pagan test was used to check whether the data conformed to the homoscedasticity assumption. Due to data that did not fit these assumptions, the Box-Cox transformation was used to transform the data (Almohaimeed and Einbeck 2022). The transformed data in models satisfied these two assumptions. Personality stability was assessed using the intraclass correlation coefficient (ICC) test for behavioral repeatability between two personality trials. The frequency of scans during feeding was calculated by dividing the number of scans by the total feeding time, serving as an indicator of the vigilance level in budgerigars. For individuals who did not engage in feeding at any point, the frequency of scans was recorded as NA.

In different social environments, the Wilcoxon signed-rank test was used to study the differences in the latency to feed and the frequency of scans between budgerigars under predation risk and those without predation risk. We tested the effect of individual factors on the feeding behavior and vigilance behavior of budgerigars by using a linear model (LM). We standardized the numerical fixed variables for subsequent analysis. The latency to feed and the frequency of scans of solitary individuals under or without predation risk were considered dependent variables, while sex (male or female), wing length, SMI, tarsus length, neophobia, and boldness were treated as fixed variables. We used the variance inflation factor (vif function in the “car” package in R) and Spearman correlation analysis to test the collinearity and correlations, respectively. No significant collinearity (all VIFs < 5) or correlations (P > 0.05 for all) were detected (Salmerón-Gómez et al. 2020).

For social factors, we used data only from the same-sex individuals in each group for analysis. In order to investigate the effect of social environments on the feeding behavior of budgerigars, we constructed a linear mixed model (LMM). The latency to feed and the frequency of scans of solitary individuals under or without predation risk were considered dependent variables, social environments (familiar groups, unfamiliar groups, or solitary individuals) were fixed variables, and both the individual ID and group ID were considered random variables. In cases of significant differences in multiple comparisons (P < 0.05), we then used the lsmeans function (“lsmeans” package in R) to make post hoc pairwise comparisons between different experimental groups and used Tukey's honest significant difference to adjust P values (Lenth 2016). Since only familiar group individuals formed stable hierarchical relationships, we used data from familiar groups to analyze the effect of social rank on feeding behavior. We constructed the LMM, where the latency to feed and the frequency of scans of familiar group individuals in experimental or control groups were considered dependent variables, social ranks (1–4) were fixed variables, and the group ID was considered a random variable.

In addition, the random forest was used to assess the importance of individual factors and social factors on feeding behavior (the “randomForest” and “caret” packages) (Breiman 2001; Graf et al. 2015). Since SMI and wing length consistently did not affect feeding behavior, we removed them from the model. To properly account for the nesting structure of the data, we included the group ID in the analysis. Cross-validation was employed to optimize the selection of hyperparameters. In this study, we used an ensemble of 900 trees (ntree = 900), as we found that this setting would be sufficient, and an increase in the ntree value would not further improve the prediction (Janitza et al. 2018; Phung et al. 2022). The number of mtry (the number of variables considered at each split in a tree) was automatically determined using the tuneRF function of the randomForest package, where the mtry value corresponding to the lowest error estimation was used. The final value of variable importance was obtained from the best model using a 10-fold cross-validation. The training set to test set ratio was 9:1. We set 0.05 as the significance threshold and 0.1 as the significance trend (Grimaudo et al. 2020; Maneejuk and Yamaka 2020).

Results

Compared to when confronted with the specimen mount, budgerigars in both familiar groups and unfamiliar groups exhibited significantly longer latency to feed (Wilcoxon signed-rank test, familiar groups: V = 4,515, P = 0.03; unfamiliar groups: V = 3,050, P < 0.01) and a significantly higher frequency of scans (familiar groups: V = 8,550, P < 0.01; unfamiliar groups: V = 9,006, P < 0.01) when confronted with the domestic cat. Furthermore, when solitary individuals were confronted with the domestic cat, their frequency of scans was significantly higher (V = 5,979, P < 0.01) than when confronted with the specimen mount. However, there was no significant difference in the latency to feed (V = 4,668, P = 0.06).

The influence of individual factors on feeding and vigilance behaviors

Boldness (N = 150, F(149,149) = 29, P < 0.01, ICC = 0.93) and neophobia (F(148,128) = 8.43, P < 0.01, ICC = 0.78) scores were highly consistent across the two replicate experiments.

  • a) The latency to feed

The latency to feed under predation risk was significantly affected by tarsus length (LM, t = −3.43, P < 0.01), but not by sex, wing length, SMI, neophobia, or boldness (P ≥ 0.25 for all, Supplementary Table S1). Individuals with shorter tarsus length exhibited a longer latency to feed. However, in the absence of predation risk (control: specimen mount), the latency to feed tended to be affected by neophobia (LM, t = 1.71, P = 0.09) and tarsus length (t = −1.75, P = 0.08), but not by sex, wing length, SMI or boldness (P ≥ 0.52 for all, see details in Supplementary Table S1). Individuals with shorter tarsus length exhibited a longer latency to feed. Similarly, more neophobic individuals also tended to hesitate for a longer time before feeding.

  • b) The frequency of scans

The frequency of scans under predation risk tended to be affected by boldness (LM, t = −1.70, P = 0.09), with bold individuals showing a lower frequency of scans. But the frequency of scans was not affected by sex, wing length, SMI, tarsus length, or neophobia (P ≥ 0.11 for all, see details in Supplementary Table S1). However, when there was no predation risk (control: specimen mount), frequency of scans tended to be affected by sex (LM, t = −1.94, P = 0.05), but was not affected by wing length, SMI, tarsus length, neophobia, or boldness (P ≥ 0.17 for all). Males tended to have a lower frequency of scans than females.

The influence of group factors on feeding and vigilance behaviors

  • a) The latency to feed

The latency to feed varied significantly across different social environments (LMM, domestic cat: χ22 = 42.51, df = 2, P < 0.01; control: χ22 = 50.39, df = 2, P < 0.01, Fig. 2). The latency to feed for solitary individuals was significantly longer than that of the familiar groups (domestic cat: adjusted P < 0.01; control: adjusted P < 0.01) and unfamiliar groups (domestic cat: adjusted P < 0.01; control: adjusted P < 0.01, Fig. 2, see details in Supplementary Table S2). Additionally, the latency to feed was usually longer in unfamiliar groups compared to familiar groups (domestic cat: adjusted P = 0.01; control: adjusted P = 0.45, Fig. 2).

Figure 2.

Fig. 2 bar chart depicting the differences in the latency to feed of budgerigars based on social environments and risk types. Error bars represent standard error of the mean; **represents P<0.01, *represents P<0.05, and ns represents a non-significant effect; familiar represents familiar groups, unfamiliar represents unfamiliar groups, and solitary represents solitary individuals.

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Bar chart depicting the differences in the latency to feed of budgerigars based on social environments and risk types. Error bars represent standard error of the mean; **represents P < 0.01, * represents P < 0.05, and ns represents a non-significant effect; familiar represents familiar groups, unfamiliar represents unfamiliar groups, and solitary represents solitary individuals.

In familiar groups, the latency to feed under predation risk was significantly affected by social hierarchical ranking (LMM, domestic cat: χ22 = 42.18, t = −6.49, P < 0.01; control: χ22 = 21.22, t = −4.61, P < 0.01, Fig. 3). Lower-ranking individuals had a shorter latency to feed.

Figure 3.

Fig. 3 box plot displaying the effect of social ranking on the latency to feed. Error bars represent the interquartile range; familiar-risk represents familiar groups with predation risk, familiar-safe represents familiar groups without predation risk; the numbers of social hierarchical ranking represent the ranking of each individual among same-sex members within each group (1 represents the highest rank, 4 represents the lowest rank).

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Box plot displaying the effect of social ranking on the latency to feed. Error bars represent the interquartile range; familiar-risk represents familiar groups with predation risk, familiar-safe represents familiar groups without predation risk; the numbers of social hierarchical ranking represent the ranking of each individual among same-sex members within each group (1 represents the highest rank, 4 represents the lowest rank).

  • b) The frequency of scans

The frequency of scans varied significantly across different social environments (LMM, domestic cat: χ22 = 92.42, df = 2, P < 0.01; control: χ22 = 145.62, df = 2, P < 0.01, Fig. 4). The frequency of scans of solitary individuals was significantly higher than that of the familiar groups (domestic cat: adjusted P < 0.01; control: adjusted P < 0.01) and unfamiliar groups (domestic cat: adjusted P < 0.01; control: adjusted P < 0.01, Fig. 4, Supplementary Table S2). However, there was no significant difference in the frequency of scans between familiar and unfamiliar groups (domestic cat: adjusted P = 0.43; control: adjusted P = 0.35, Fig. 4, Supplementary Table S2).

Figure 4.

Fig. 4 bar chart depicting the differences in frequency of scans of budgerigars based on social environments and risk types. Error bars represent standard error of the mean; **represents P<0.01, and ns represents a non-significant effect; familiar represents familiar groups, unfamiliar represents unfamiliar groups, and solitary represents solitary individuals.

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Bar chart depicting the differences in frequency of scans of budgerigars based on social environments and risk types. Error bars represent the standard error of the mean; **represents P < 0.01, and ns represents a non-significant effect; familiar represents familiar groups, unfamiliar represents unfamiliar groups, and solitary represents solitary individuals.

In familiar groups, the frequency of scans under predation risk was significantly affected by social ranks (LMM, domestic cat: χ22 = 14.93, t = −3.86, P < 0.01; control: χ22 = 4.32, t = −2.08, P = 0.04, Fig. 5). Lower-ranking individuals had a lower frequency of scans.

Figure 5.

Fig. 5 box plot displaying the effect of social ranking on the frequency of scans. Error bars represent the interquartile range; familiar-risk represents familiar groups with predation risk, familiar-safe represents familiar groups without predation risk; the numbers of social hierarchical ranking represent the ranking of each individual among same-sex members within each group (1 represents the highest rank, 4 represents the lowest rank).

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Box plot displaying the effect of social ranking on the frequency of scans. Error bars represent the interquartile range; familiar-risk represents familiar groups with predation risk, familiar-safe represents familiar groups without predation risk; the numbers of social hierarchical ranking represent the ranking of each individual among same-sex members within each group (1 represents the highest rank, 4 represents the lowest rank).

The importance of individual factors and social factors to feeding and vigilance behavior

  • a) The latency to feed

In familiar groups, predation risk (random forest, 46.62%, RMSE = 5.29, MAE = 4.37, R2 = 0.24) and social rank (26.02%) were the most important factors affecting the latency to feed, while boldness, neophobia, tarsus length, and sex (<5% for all) had little effect on the latency to feed.

  • b) The frequency of scans

In familiar groups, predation risk (random forest, 28.19%, RMSE = 0.08, MAE = 0.05, R2 = 0.12) and social rank (13.65%) were the most important factors affecting the frequency of scans, while boldness, neophobia, tarsus length, and sex (<5% for all) had little effect on the frequency of scans.

Discussion

In our study, budgerigars exposed to domestic cats had a longer latency to feed and a higher frequency of scans during feeding, regardless of the social factors. Domestic cats are one of the main predators of urban birds and pose a significant threat to birds (Courchamp et al. 2003; Hunter 2015; Crowley et al. 2020). They not only directly prey on birds, but also increase birds' fear and stress (Beckerman et al. 2007; Tryjanowski et al. 2015). Given that the budgerigars in this study had lived in a human environment for a long time, it was likely that they had been exposed to domestic cats and had perceived them as a significant threat. Therefore, budgerigars had a strong avoidance behavior, reduced time spent on foraging activities, and increased vigilance when facing domestic cats as predators.

Neophobia did not influence individuals' feeding and vigilance behaviors under domestic cat predation risk. However, when faced with the specimen mount, more neophobic individuals tended to have a longer latency to feed. In this study, budgerigars may have perceived the specimen mount as a novel object. Low-neophobic individuals tended to explore their environments actively, and thus were more likely to exhibit reduced fear responses to novel objects (Batisteli et al. 2022; Bibi et al. 2023). However, because domestic cats represent a strong predation risk, budgerigars remain vigilant against potential predators, regardless of neophobia. Besides, in line with our second prediction, more bold individuals may scan less frequently under domestic cat risk. Bold individuals are more capable of taking predation risk and therefore show less vigilance when faced with the domestic cat (Brehm and Mortelliti 2024). The results suggested that budgerigars can adjust their feeding and vigilance behaviors in response to predation risk, depending on their personality.

Sex did not influence the feeding and vigilance behaviors of budgerigars in response to predation risk, but male budgerigars tended to scan less frequently than females in the presence of the specimen mount. In our experiment, budgerigars of both sexes and body conditions all perceived a similarly high level of risk from domestic cats. To ensure their safety, individuals must remain highly vigilant. Because of physiological or genetic factors, males tend to exhibit more proactive behavior (Weatherhead 1990; Mautz et al. 2011; Gravolin et al. 2021; Wallace and Hofmann 2021). Therefore, males exhibit less fear of the specimen mount compared to females. Additionally, budgerigars with shorter tarsus exhibit longer latency to feed. The tarsus is a strong indicator of a bird's body condition and genetic traits (Abasiekong 1986; Silva et al. 2017). Birds with longer tarsi may have greater aggressiveness and protect themselves from predators through scratching and attacking maneuvers. Moreover, the elongated and robust tarsi likely give budgerigars greater gripping strength and cursorial capacities (Kirkwood et al. 1989; Gianechini et al. 2020), potentially enhancing their ability to cope with predation risk in the cage (a limited space). However, wing length and SMI have no significant effect on feeding behavior. This may be because the limited space of the captive environment restricted the budgerigars' ability to fly freely, and the adequate and nutritionally balanced food supply led to individuals exhibiting similar body conditions. In summary, budgerigars of different sexes and tarsus lengths may exhibit varying vigilance toward novel objects or potential predators.

Consistent with our third hypothesis, budgerigars in groups had significantly shorter latencies to feed and lower frequencies of scans during feeding compared to solitary individuals when exposed to domestic cats. Living in groups can dilute each individual's predation risk (Krakauer 1995; Lehtonen and Jaatinen 2016; Polyakov et al. 2022), and individuals may also infer predation risk based on the behaviors of group members. If one of the group members forages safely, it may indicate that it is currently safe to feed, thereby stimulating other individuals to engage in foraging behavior as well. However, solitary individuals must independently assess the current level of predation risk, and failure to accurately evaluate the threat can result in substantial costs, including injury or even mortality (Lima and Dill 1990). Our results were consistent with previous studies (Kareklas et al. 2018; Ardila-Villamizar et al. 2022; Sehner et al. 2022), which have indicated that individuals exhibit lower vigilance when in groups compared to when they are solitary.

In line with our fourth hypothesis, the latency to feed of budgerigars in familiar groups was significantly shorter than that of those in unfamiliar groups, but there was no significant difference in the frequency of scans. In social groups, higher familiarity among members enables them to gather social cues of predation risk more quickly, and thus may reduce the delay time before eating under predation risk (Bairos-Novak et al. 2019). Due to compromised vision during feeding (feeding box obscuring the view), budgerigars may frequently stretch their necks and raise their heads to scan for potential predators. Individuals within a group are able to assess predation risk based on the defensive behaviors or vigilant signals exhibited by other group members (Beauchamp et al. 2012), which may reduce the burden of constant vigilance. Therefore, regardless of the individual's familiarity with other group members, it can derive benefits from the vigilance behaviors exhibited by others during foraging, as long as it is part of the group (Rowe et al. 2023). In summary, we suggest that social factors can influence the level of feeding activity in individuals under predation risk.

Consistent with our fifth prediction, a significant positive correlation was found between social rank and the latency to feed in individuals, as well as between social rank and the frequency of scans. Evidence from captive flocks of blue tits (Parus caeruleus) suggests that following the appearance of a predator, socially dominant individuals are likely to wait until subordinate members of their flock resume feeding before doing so themselves, possibly because their ability to occupy food resources reduces the energetic costs of their extra caution (Hegner 1985). In our study, social rank was assessed based on individuals' ability to compete for food, with those possessing greater competitive abilities occupying higher ranks. We speculated that an individual's feeding motivation under predation risk was influenced by their food acquisition capacity within the group, and those with lower abilities were more eager to feed. Additionally, in groups exhibiting cooperative vigilance, high-ranking individuals are more likely to assume additional vigilance tasks (Bednekoff and Naguib 2015). This may be because of their greater capacity to endure the energetic costs of vigilance and their superior predator detection abilities, which enable them to provide more reliable information (Bednekoff and Naguib 2015; Kern et al. 2016). By undertaking vigilance responsibilities, high-ranking individuals could enhance their trust and respect within the group and further consolidate their social ranks. Therefore, group-living birds may adjust their feeding and vigilance behaviors in response to predation risk according to social ranks.

Predation risk and social rank were the most significant factors influencing the feeding behavior and vigilance behavior of budgerigars, while individual factors were of comparatively less importance. Predation is one of the main causes of bird mortality. To reduce predation risk, bird species have evolved various anti-predator strategies, including mechanisms for accurately identifying and distinguishing predator types and risk levels (Zuo et al. 2024). Since underestimating the danger posed by a predator can be fatal (Caro 2005), budgerigars should be sensitive to predators to avoid injury and death. The social rank of individuals may reflect their overall quality (Colléter and Brown 2011; Wright et al. 2019), thereby exerting a significant influence on feeding and vigilance behaviors under risk. Besides, social birds may adjust their behavior to align with group norms (social conformity), resulting in the suppression of individual differences in personality and body condition (King et al. 2015). This conformity enhances group cohesion, ultimately improving predator avoidance and/or resource acquisition for group-living individuals (Fürtbauer and Fry 2018). Our results align with previous research, which indicates that, in natural conditions, both individual and social factors collectively influence the vigilance behavior of birds during feeding (Hegner 1985; Maxwell et al. 2024). For budgerigars, although individual factors may influence their frequency of scans during feeding, social factors play a more important role in their feeding behavior.

In conclusion, we have shown that budgerigars are able to adjust their feeding behavior according to individual factors and social factors, with the social rank playing a more vital role. This study contributes to understanding how animals weigh risks and benefits in different environments and make optimal behavioral decisions. When investigating social animals, it is essential to consider the impact of their companions' presence on their behavior. Future research should further investigate how feeding behaviors evolve in response to changing social factors.

Supplementary Material

zoaf069_Supplementary_Data
zoaf069_supplementary_data.zip (131.7KB, zip)

Contributor Information

Xueqi Zhao, Jilin Engineering Laboratory for Avian Ecology and Conservation Genetics, Northeast Normal University, Changchun 130024, China.

Jie Su, Jilin Engineering Laboratory for Avian Ecology and Conservation Genetics, Northeast Normal University, Changchun 130024, China.

Manxi Lu, Jilin Engineering Laboratory for Avian Ecology and Conservation Genetics, Northeast Normal University, Changchun 130024, China.

Jiangping Yu, Jilin Engineering Laboratory for Avian Ecology and Conservation Genetics, Northeast Normal University, Changchun 130024, China.

Haitao Wang, Jilin Engineering Laboratory for Avian Ecology and Conservation Genetics, Northeast Normal University, Changchun 130024, China; Jilin Provincial Key Laboratory of Animal Resource Conservation and Utilization, Northeast Normal University, Changchun 130024, China.

Funding

Fundings were provided by the Scientific Research Project of the Education Department of Jilin Province (nos. JJKH20250325KJ to J.Y.), National Natural Science Foundation of China (nos. 32271560 to H.W.), and the Fundamental Research Funds for the Central Universities (nos. 2412022ZD019 to J.Y.).

Ethics statement

The experimental procedures were approved by the National Animal Research Authority in Northeast Normal University, China (Approval No. NENU-20080416). Behavioral experiments complied with the experimental animal management regulations of the People's Republic of China (State Scientific and Technological Commission Decree [1988] No. 2). No budgerigars were injured or died during the research.

Data availability

All data generated or analyzed during this study are included in this published article (and its supplementary information files).

Supplementary material

Supplementary material can be found at https://academic.oup.com/cz.

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Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

zoaf069_Supplementary_Data
zoaf069_supplementary_data.zip (131.7KB, zip)

Data Availability Statement

All data generated or analyzed during this study are included in this published article (and its supplementary information files).

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