Estimating individuals’ exposure to predation risk in group-living baboons, Papio anubis

In environments with multiple predators, the vulnerabilities attached to the spatial positions of group-living prey are not uniform and depend on the hunting styles of the predators. Coursing predators, mainly canids and hyenas, follow their prey over long distances and attack open areas, making individuals at the edge of the group more dangerous than those at the center (marginal predation). In contrast, ambush predators, mainly cats, approach their prey undetected and appear randomly anywhere in the group; therefore, isolated individuals are at a greater risk of predation. However, identifying individuals at high risk of predation requires the simultaneous recording of predator locations and direct observation of predation events, which are both difficult. Therefore, several theoretical methods have been proposed to assess predation risk (predation risk proxies). In a group of wild anubis baboons exposed to predation by leopards, lions, and hyenas, we calculated predation risk proxies using movement data collected from global positioning system (GPS) collars and found that adult males were on the edge of the group with a higher risk of predation (Hypothesis 1). In addition, adult males were more isolated within this group (Hypothesis 2). None of the predation risks differed among the other age-sex classes. The most dominant male was expected to be in the safety center of the group (Hypothesis 3) but was isolated on the periphery, like the other males. Therefore, we discussed why adult males were more peripheral and isolated.


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Under the threat of predation, animals are often tightly grouped, with all group members benefiting from a reduction in 33 predation risk through several mechanisms, including dilution, many-eyes, and confusion effects [1,2]. However, 34 predation risk is often unequal among individuals with different attributes and states within a group. For example, 35 predators may select prey based on their individual vulnerabilities [3-5]because predators can conserve hunting energy 36 or reduce the risk of injury by selecting prey in poor conditions [6][7][8]. In many taxa, predators have shown evidence of 37 capturing young, old, sick, weak, injured, or inexperienced individuals from prey populations that are higher than 38 expected [4,9,10].

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The spatial position within the prey group has also been predicted to lead to vulnerability to predation [11][12][13].

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Alternatively, another reason could be related to the hunting styles of predators. Predator-hunting styles are 55 generally divided into coursing and ambushing. Because coursing predators (primarily canids and hyenas) chase their 56 prey over long distances and attack from open areas, individuals at the edge of a group are more likely to encounter 57 predators than individuals at the center and are more dangerous ('marginal predation': [12,28]

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In this study, we used multiple GPS devices simultaneously on a group of individually identified wild baboons to 64 re-examine the age, sex, and dominance of individuals in positions expected to be vulnerable to each of the two types of 65 terrestrial predators, under conditions that minimized the influence of human observers. Although the sample size of 66 predation events was small, a previous study reported that predators were more likely to hunt adults than juveniles and 67 males than females [35]. Instead of directly observing predation events, we calculated individual predation risk using five 68 alternative indices (proxies) that theoretical studies have proposed to predict the predation risk faced by individual prey 69 in two-dimensional space. We tested the following three hypotheses. Hypothesis     1.80 ± 1.70, which was not different from the 1.62 ± 0.91 for the rest of the study period (t-test, t=-0.30, n1=5, n2=34, 90 p=0.77). During the study period, excluding the first 5 days, we recorded behaviors by ad libitum observation, and the 91 PLOS ONE 5 alpha male was determined by direct behavioral observations, such as attacks or displacements of other individuals in the 92 group. The alpha male of this study period, MG, was assumed to have been born in this group because his body size was 93 a late juvenile-early adolescent when he was identified. Leopards, lions, and hyenas were sympatric with the AI group.

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The predation rate on the AI group from 2011 to 2016 was estimated to be 0.06 individuals/year [37].

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Collaring methods and GPS recorded data 97 Baboons were captured using walk-in traps (1.8 m 3 ) baited with maize and placed near the sleeping sites of the groups.

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Baboons were not fed except during capture. Two criteria were used to capture. First, a GPS weight limit of no more than 99 3% of body weight was adopted. As a result, 29 infants (46.03% of the AI group) were excluded from the study. Second,   Theoretical studies have proposed several proxies to predict the predation risk at different spatial positions (Table 1, Fig   119   1). We used the unlimited domain of danger (UDOD) and minimum convex polygon (MCP) to assess the predation risk 120 for individuals at the edge of the group, where they are most likely to encounter predators (Fig 1a, 1b). The extent to 121 PLOS ONE 6 which an individual was surrounded by others was then analyzed using the limited domain of danger (LDOD), 122 surroundedness, and dyadic distances (Fig 1c, 1d, 1e). The details of each proxy are presented below.

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[Insert Table 1  125 Hamilton [29] proposed the domain of danger (DOD) concept as a measure of the predation risk taken by each prey 126 individual within a group. This concept assumes that a predator currently undetected by prey might appear anywhere 127 within the field, inside or outside the group. DOD is defined as the space around the individual within which a predator 128 can attack and kill it; the larger the size, the higher an individual's expected predation risk. The predatory is assumed to 129 attack individuals at the closest distance (Table 1). When a perpendicular bisector is drawn on a line connecting points   animal. This radius corresponds to the range over which a predator can strike, the maximum detection distance of the 147 predator, or the distance within which the predator can successfully launch an attack after approaching undetected [42]. If 148 a focal individual is, its LDOD is maximal, defined as πr2 where r is the predator's attack distance (Fig 1c). If there is a 149 conspecific individual within its maximum LDOD, the distance between the two is less than 2r, and the created bisector 150 reduces the LDOD.

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The definition of r based on field reports is important to represent the most realistic range of danger. Information on 152 the attack ranges of baboons' main ambush predators, leopards and lions, is scarce in the literature. However, only two 153 studies have been cited. Observations by Bailey [43] suggest that prey will allow visible leopards to approach 25 m 154 without feeling threatened but will flee if they are closer than 10 m. Specifically, there is a distance limit of 10-25 m

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The following calculations were performed according to Cremers and Klugkist [48]. A unit was drawn around a 170 focal individual, and the directions of all the group members were projected as points on the circle's circumference.

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Connecting these points to the origin (the focal individual) yielded individual vectors (Fig 1-d). Vectors with the same   . Thus, one way to determine which individuals are more susceptible to predation is to 183 determine their distance from all members. Individuals that maintain a greater distance from others are more physically 184 isolated (Fig 1-e) and thus may be the preferred target for predators. Therefore, we calculated the Euclidean distance for 185 each focal individual and the dyadic combination of all other group members at each timestamp.

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We aimed to explore the potential differences among age-sex classes for all predation risk proxies.  were inside [0] vs. boundary [1]. The predictors were similar to those of the LMMs. To study the differences in dyadic 201 distances between each age-sex class, we used an LMM with dyadic distances as the response variable and pairs of age-202 sex classes (factors with 10 levels) as the predictor. A two-sided test was used to ascertain the differences in mean values 203 for each age-sex group. All LMMs and GLMMs were followed by Tukey's post-hoc comparisons with Bonferroni 204 correction to assess the specific differences between each age-sex class.

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In all the models, individual identities were set as random factors on the intercept. The significance of predictors in  age-sex classes (Fig 2c1, 2c2). For LDODs with a radius of 25 m, significant differences were in the percentages of finite

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The special position of the alpha male

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The UDOD and MCP results showed that the alpha male, MG, was located peripherally of the group to a similar extent 256 as the other males (Fig 2a, 2b). In addition, LDOD, surroundedness, and dyadic distance indicated that the MG was not 257 surrounded less by individuals as other males.

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In Hypothesis 1, we proposed that adult males are located peripherally, where coursing predation is most likely to 261 occur. Our results from the UDOD and MCP showed that, as expected, adult males were located more on the 262 periphery, consistent with previous studies on primates [50] and other animals [51-53]. Two well-studied 263 hypotheses have been proposed from ecological and sociological perspectives to explain why males are located 264 peripherally. One hypothesis is that there is a trade-off between increased foraging efficiency and higher predation 265

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Elucidating the costs of predation risk associated with individuals' spatial positions within a group is important for 330 understanding group formation and maintenance. In this study, we demonstrated that adult males were consistently 331 PLOS ONE 13 weaker than predators that attacked them from outside the group, as well as predators that ambushed them within the 332 group. Determining whether adult males position themselves voluntarily or unwillingly on the edge is difficult; however, 333 it is an interesting future challenge for both ecological and social interests.