Individual differences in cognition have been shown to be common in some animal taxa, and recent evidence suggests that an individual’s personality can be associated with an individual’s cognitive strategy. We tested whether wild bat-eared foxes Otocyon megalotis differ in a risk- taking behavior (tameness) and whether this trait correlated with appetitive association learning performance. While our result shows that individuals differed in their tameness, we found no asso- ciation between this personality trait and learning the appetitive association. This result does not support the framework that differences in cognition are associated with differences in personality; however, our small sample size does not allow us to assert that personality cannot be associated with cognition in this system. This study highlights that measuring cognition and personality in wild systems presents added difﬁculty and that correlations found in captive animals may not be evident in their wild counterparts. Key words: carnivore, cognition, bat-eared fox, personality Individuals differ consistently in behaviors across time and context; hypothesis for this association is that personality and cognition are a phenomenon generally labeled as animal personality (Re ´ ale et al. correlated through a speed-accuracy tradeoff (Chittka et al. 2009; 2007; Carere and Maestripieri 2013). Personality traits can influ- Sih and Del Giudice 2012). For example, individuals that acquire in- ence fitness, which may have ecological and evolutionary conse- formation faster may be able to use resources sooner. However, this may also increase the chances of making a potentially costly mis- quences (Smith and Blumstein 2008; Wolf and Weissing 2012). Recent theoretical and empirical evidence suggests that personality take. These tradeoffs have been seen in a number of species includ- traits are linked to life-history strategies (Stamps 2007; Re ´ ale et al. ing bumblebees Bombus terrestris (Chittka et al. 2003) and guppies 2010), and may also be associated with individual differences in cog- Poecilia reticulate (Burns and Rodd 2008). To reduce these potential nition (Carere and Locurto 2011; Sih and Del Giudice 2012; Griffin errors, individuals often develop routines or heuristics (shortcuts), which reduces the ability to respond to rapid environmental et al. 2015; Morand-Ferron et al. 2015; Guillette et al. 2017). Individual differences in cognition have been reported in several changes. The move to acquire information faster may, therefore, be species (Griffin et al. 2015; but see Brust and Guenther 2017; correlated with individuals taking more risks (i.e., bolder or faster Guillette et al. 2017; Lucon-Xiccato and Bisazza 2017; Matzel et al. explorers). Conversely, individuals who are slower at acquiring in- 2017), and it appears likely that cognitive abilities and personality formation explore a novel environment slowly and more thoroughly traits may have been similarly shaped by natural selection, based on and retain behavioral flexibility as environments change because shared underlying mechanisms (Sih and Del Giudice 2012). they use cues from the environment (Chittka et al. 2009). For ex- Cognition is the acquisition, processing, storage, and use of informa- ample, slower exploring black-capped chickadees Poecile tion (Shettleworth 2001; 2009) and covers a wide range of processes atricapillus were quicker to relearn an acoustic operant discrimin- including attention, memory, and associative learning. One ation task than faster exploring birds (Guillette et al. 2010). V C The Author(s) (2018). Published by Oxford University Press. 1 This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact email@example.com Downloaded from https://academic.oup.com/cz/advance-article-abstract/doi/10.1093/cz/zoy021/4924851 by Ed 'DeepDyve' Gillespie user on 13 July 2018 2 Current Zoology, 2018, Vol. 0, No. 0 A personality/cognition correlation has been shown in a number of tameness as latency to approach an observer with an attractive lure captive species including insects (Chang et al. 2016), fish (Øverli from 114 approaches on 12 individuals from June 2015 to April et al. 2007; Lucon-Xiccato and Bisazza 2017), birds (Biondi et al. 2016. These approaches were part of an ongoing study on fox move- 2010; Guillette et al. 2015; de Haas et al. 2017), and mammals ment and foraging behaviors discussed above. Thus, for each follow, (Nawroth et al. 2017). However, how these traits correlate in the an individual was located between 5:00 PM and 9:00 PM and lured wild is still lacking empirical evidence. to the observer shaking a small plastic bag and proffering a small Here we use wild habituated bat-eared foxes Otocyon megalotis food reward (raisins). Individuals initially learned the association (hereafter foxes) to understand the relationship between personality between the bag rattle and a food reward during habituation. and cognition in a wild setting. Foxes forage on transient termite Handheld spotlights were used to observe individuals as they moved Hodotermes mossambicus patches (Nel 1978), and thus need to ac- throughout the night. Observers noted the time an individual was quire and use environmental cues about resource availability and 20 m and 2 m away (distances estimated by eye). Latency to ap- distribution. We use the framework from Sih and Del Giudice proach was calculated as the time difference between the 2 distances (2012) indicating that bolder individuals are more likely to learn an in seconds. Latencies that lasted longer than 10 min were excluded association first because they are more likely to experience new situ- from analysis (3 points out of 117). ations, and thus may form association sooner. Using approach-to- observer data from a population of wild foxes, we first expected Associative learning task foxes to exhibit consistent individual differences in tameness. To examine associative learning in already-habituated animals, we Tameness is related to wariness toward humans, and can be related tested 9 individuals (a subset of the 12 above—6 males and 3 fe- to docility or the bold-shy continuum (Re ´ ale et al. 2007). Following males) over 61 trials from June to October 2015, with a novel stimu- the above framework, we predicted that more tame (approach lus–reward association. Before a follow, we paired a dog whistle humans more readily), or bolder individuals are faster at the learn- (condition stimulus, CS) with a single raisin (unconditioned stimu- ing of an appetitive association. Foxes are not highly sexually di- lus, US) 10 times, for example, a dog whistle was blown and a single morphic in morphology or social behavior; however, there may be raisin was given immediately after the whistle; this process was re- unknown sex differences in these foxes (Carazo et al. 2014; Lucon- peated 10 times consecutively with each combination happening Xiccato et al. 2016). We thus have no a priori hypotheses about po- within 5–10 s of the previous pairing. Raisins were tossed 1m tential differences in cognition between the sexes. from individuals. These pairings were considered a training period. This period was necessary as individuals were free to move or leave without hindrance. This necessitated that we call in individuals first Materials and Methods using the bag shake, pair the whistle and raisins multiple times, and We studied 12 habituated foxes (5 females and 7 males) at the then test the association. After a 10-min waiting period, the CS was Kuruman River Reserve (KRR, 28 58’S, 21 49’E) Northern Cape, given again while the fox was moving but not actively eating a prey South Africa, from July 2014 to April 2016. All foxes were con- item. If the fox returned to the observer, the US was provided. This sidered habituated when we were able to follow them at a distance of whole process constituted 1 trial (CS/US pairing and post-10-min CS 2–5 m for an extended period of time (>1 h). All foxes had been presentation). Trials were conducted once before a follow and once observed multiple times prior to recording latency to approach and after when possible (i.e., 2 h after the pre-follow trial). Once the fox associative learning. Foxes are small canids (2–4 kg) that feed pre- had returned for the US, the individual was noted as successfully dominantly on insects—termites making the bulk of their diet (Maas associating the CS with the US. Pairings were only done when foxes and Macdonald 2004; Nel 1990). Individuals spend 70–90% of their were in close proximity (<5 m) to the observer (n ¼ 6; range of tri- active time foraging (Nel 1978), while often moving between termite als¼ 8–34). To prevent social learning, trials were conducted only patches—their main food source (Nel 1978). Due to thermally driven when the focal individual was alone. changes in termite activity patterns, diurnal activity is more common for foxes in winter, and nocturnal movement in summer (Nel 1978). Statistical analysis We conducted 2-h observational sessions on each individual once a All analyses were done in R (R Core Team 2016) in the package week (henceforth a follow), wherein all foraged items, social inter- lme4 (Bates et al. 2015). In the following analyses, all 2-way inter- actions, and marking events were recorded along with Global actions were included in each model and removed from the model if Positioning System (GPS) locations. These follows were done as part not significant, based on 95% confidence intervals (C.I.). A main ef- of a larger study on fox movement and foraging activities (Pe ´riquet fect was also considered significant if the 95% C.I. did not include and le Roux 2017; Welch et al. 2017). The intervals between these zero. Individual was included as a random effect in all analyses, and sessions were designed to reduce the chance of over-habituation and observer was also included as a random effect in the tameness ana- to avoid excessive disturbance of the foxes or, potentially, their prey. lysis. Repeatability was calculated by dividing the individual vari- ance by the total phenotypic variance. Significance of a random Measuring tameness effect was tested using log-likelihood ratio tests (LRT) between Although foxes were habituated to observers, there may remain dif- models with and without the random effect. ferences in how individual foxes perceive humans. Habituation, for the purposes of this study, was the evident tolerance of observers, on Tameness foot, whereas foxes foraged and exhibited apparently natural, undis- We fit a linear mixed-effects model of latency to approach observer as turbed behavior. Tameness, or tolerance of humans, is critical in the a function of trial number. Individuals had already been habituated to domestication of animals (Driscoll et al. 2009), and has been shown to correlate with aggression, activity, and stress response in wild- observer presence for some time, but we included trial to control for derived rats Rattus norvegicus (Albert et al. 2008). Therefore, after any further habituation effects. Individual and observer were added individuals were fully habituated to observer presence, we estimated as random effects. There were a total of 6 observers in this study. Downloaded from https://academic.oup.com/cz/advance-article-abstract/doi/10.1093/cz/zoy021/4924851 by Ed 'DeepDyve' Gillespie user on 13 July 2018 Petelle et al. Tameness and learning in a fox 3 Associative learning task We fit a generalized mixed-effects model with a binomial distribu- tion of whether an individual had learned the association between CS and US as a function of trial number, sex, and the last latency to approach (by date) and observer for each individual. A random re- gression model (Nussey et al. 2007) to test for individual differences in learning (an individual environment interaction) could not be fit due to restrictions in sample size and model convergence. One in- dividual did not make the association before disappearing from the population. This individual received 4 trials and these trials were included in the analysis. Our small sample size makes it difficult to assert the null between cognition and covariates (see results below). We, therefore, calculated a Bayesian factor (BF) for nonsignificant fixed effects to determine the strength of support for our data given our result (Jarosz and Wiley 2014). Thus, we calculated the Bayesian Information Criterion (BIC) for our full model containing Figure 1. The effect of trial on the learning of an appetitive association. all covariates and for models without specific fixed effects. We then Individuals learned an association between a dog whistle and a food reward. estimated a proxy Bayes factor for each nonsignificant fixed effect Regression line is from predicted values and points are from raw data. Grey by taking the natural log and raising it to the difference between full ribbons signify 95% C.I. and nested model BICs divided by 2. It should be noted that this is an approximation to a Bayes factor and does not give a definite answer to whether one can assert the null. However, it can give sup- port for one hypothesis over another (Jarosz and Wiley 2014). A value between 0.33 and 0.10 suggests strong or substantial support for an alternative hypothesis (Jarosz and Wiley 2014). Results Tameness Mean latency to approach for all individuals took 45 s (x ¼ 42.76 s; range¼ 2–240). Individuals did not increase their ha- bituation to our presence (trial: b¼0.283; SE ¼ 0.552; 95% C.I.¼1.376 to 0.798). There was significant but low among- individual differences in latency to approach (R ¼ 0.110; LRT ¼ 4.389; P ¼ 0.036). We also found a significant effect of ob- server (R ¼ 0.275; LRT ¼ 18.867; P< 0.001) suggesting that foxes may view observers differently, or a systematic bias by observers in Figure 2. The association between average tameness and the learning of an measuring fox approaches. Mean approach for observers varied appetitive association. Regression line is from predicted values and points greatly (range¼ 9.417–70.273), but when the fox with the highest are from raw data. Grey ribbon signiﬁes 95% C.I. mean latency to approach was removed from analysis the observer effect was still present (R ¼ 0.274; LRT ¼ 16.916; P< 0.001). Discussion Interestingly, the 2 observers with the highest mean approach were Animal personality is now ubiquitous throughout the behavioral also the only observers that conducted this fox’s trials. However, ecology literature (Sih et al. 2012), and our results support the hy- these 2 observers remained as the observers with the highest ap- pothesis that individuals vary consistently in their tameness. Our re- proach times without this fox in the analysis. This suggests that an peatability estimates are lower than reported in a recent meta- unknown observer characteristic still had a large effect even with analysis (Bell et al. 2009), but are well within reported estimates of this extreme fox’s approaches excluded. activity and sociability in carpenter ants Camponotus aethiops (Udino et al. 2017) and escape behaviors in blue tits Cyanistes Associative learning caeruleus (Kluen and Brommer 2013). It should be noted that work- Mean trials to learn the association was 4 (range 1–10). ing with habituated individuals should reduce the probability of de- Individuals made the association between CS and US as trials tecting consistent individual differences in tameness. Indeed, we increased (b ¼ 0.879; SE ¼ 0.247; 95% C.I. ¼ 0.476–1.476; expect bolder individuals to be more likely to be habituated and Figure 1). There was no sex difference (females as reference: thus erode among individual variance (Carter et al. 2013). Despite b¼1.700; SE ¼ 1.295; 95% C.I.¼5.075 to 1.014), and we this potential erosion, we still detected consistent individual differ- found no association between tameness (b¼0.024; SE ¼ 0.023; ences in willingness to approach a human observer. Thus, we believe 95% C.I.¼0.081 to 0.027) and learning (Figure 2). We found no that our repeatability of tameness is a conservative estimate as we interaction between any variables. We found low support to assert most likely were only able to habituate individuals with certain be- the null for the last latency to approach—our measure of tame- havioral types. ness—(BF ¼ 0.219). We also found low support to assert the null Our analysis also shows that foxes react differently to observers, for no differences in sex (BF ¼ 0.307). or alternatively there may have been systematic bias in how Downloaded from https://academic.oup.com/cz/advance-article-abstract/doi/10.1093/cz/zoy021/4924851 by Ed 'DeepDyve' Gillespie user on 13 July 2018 4 Current Zoology, 2018, Vol. 0, No. 0 observers judged distances. The exact cause of this result is un- Finally, trial had a significant effect on learning the association. known. Determining the exact cause of these differences may be dif- This is not surprising; individuals should learn the association as ficult. Salient features of the observers, such as sex, size, and odor, they received more training. It is, however, interesting that individ- are confounded in this study (only 1 male observer, M.B. Petelle). uals made the association at different speeds. This suggests that indi- Furthermore, the male observer had the third highest best linear un- viduals may differ in their cognitive abilities. Measuring cognition in biased predictor (BLUP) suggesting that the larger, male observer the wild can be difficult (Morand-Ferron et al. 2015), and our study did not stand out from the female observers. Past research has highlights this issue. Yet studies showing individual differences in shown that observers can have an impact on a species’ behavior cognition are rare in the wild, and more so for wild carnivores (but (Iredale et al. 2010; Nowak et al. 2014). Indeed, research on obser- see Benson-Amram and Holekamp 2012). ver effects within our own fox population shows that foxes are more Individuals that live in complex, heterogeneous environments, vigilant toward certain observers during follows (Welch et al. 2018). like the Kalahari Desert, should be adept at detecting environmental This result suggests that researchers should take observer effects into cues, which in turn should promote individuals learning new associ- account when analyzing behavioral data. ations quickly. Yet the acquisition of information and the ability to We found no relationship between tameness and learning of an make association can be costly and involves a speed-accuracy trade- appetitive association. The resulting Bayes factor suggests strong off (Chittka et al. 2009). If individuals can access clear cues of envir- evidence for the alternative hypothesis that personality may be onmental resources, or if the costs of accessing these cues are not linked to cognitive processes. Although we did not test accuracy in necessarily high, they may not need to acquire more information this study, we still expect personality traits to correlate with the and bypass the speed-accuracy tradeoff. We may then not see behav- speed of learning an association. An individual’s last latency to ap- ioral flexibility and personality linked in this scenario. Termite proach, however, was not linked to how quickly this learning patches, the main food of these foxes, are ephemeral, but occur occurred, for example, we found no interaction between trial and widely throughout the habitat (Pe ´ riquet and le Roux 2017), which tameness. The link between cognition and personality in the wild is may not lend itself to a speed-accuracy tradeoff. Thus, further inves- still ambiguous with relatively few studies on the subject. tigation of when and how links between differences in behavior and Importantly, our results are inconsistent with theory and previous cognition are warranted, as personality may be important only in empirical support. For instance, learning was associated with neo- specific cognitive tests. phobia in zebra finches Taeniopygia guttata (Gibelli and Dubois Our study highlights that researching cognition in the wild can 2016), and research on cavies Cavia aperea showed that individuals be challenging, but it is important to understand the potential correl- willing to take more risks were quicker in learning an association ations between behavioral types and cognition. We call for further (Guenther et al. 2014). However, new evidence from cavies suggests investigation into why we may see clear links between cognition and that only certain personality traits might be linked to individual dif- personality and when we may not. We expect that personality traits ferences in cognition (Guenther and Brust 2017), and neophilia in and cognition may be associated based on the ecology or sociality of zebra finches was only linked to learning during the simplest dis- the species in question. Thus, ecologically or socially functional per- crimination tasks (Gibelli and Dubois 2016). We may, therefore, sonality traits (exploration and sociability, respectively) should be need to expand future studies to investigate other dimensions of per- sonality such as exploration or aggression. One potential explan- linked to cognition if these traits help individuals gather information ation for our results is that hunger levels may have masked the effect about their information. of personality when using an appetitive association. In many associ- ation studies, a food reward is used as the US, yet individuals are Acknowledgments held an appropriate amount of time to limit the effect of hunger We thank all the Bat-Eared Fox Research Project members for helping with the (Guillette et al. 2015). It is difficult to control for hunger levels in data collection (Rebecca J Welch, Keafon Jumbam, Samantha Renda, and the wild. It may be possible to test the effect of hunger in masking Elizabeth Karslake). We would like to thank Tim Clutton-Brock, Marta Manser, personality by testing whether personality of individuals that have and the Kalahari Meerkat Project for access to the Kuruman River Reserve and foraged during the follow has a large effect, but with very few post- their support. The Kalahari Meerkat Project was supported by European follow tests (4 trials) it is difficult to tease apart hunger as a factor. Research Council [Grant No 294494 to T.H. Clutton-Brock since 1 July 2012]. We found no sex effect in associative learning; however, our Bayes factor does not allow us to make a definitive statement given our data. Previous studies have found sex differences in cognition in Funding a number of cognitive tests. Eastern water skink Eulamprus quoyii This research was funded by the National Research Foundation (NRF) males performed better at a spatial learning task, and female guppies Thuthuka grant (TTK1206041007) awarded to A.L.R. M.B.P. and S.P. were P. reticulata were found to outperform males at a visual discrimin- funded by Dire torate Research Development at the U.F.S. ation task (shoal size) when that task was harder (Lucon-Xiccato et al. 2016). Foxes are not a morphologically sexually dimorphic species or in terms of social behavior (i.e., males perform much of References the parental care—Pauw 2000); males perform remarkably similar Albert FW, Shchepina O, Winter C, Ro ¨ mpler H, Teupser D, 2008. Phenotypic roles to females. This may explain why male and female foxes ex- differences in behavior, physiology and neurochemistry between rats se- hibit similar cognitive ability. Nonetheless, an alternative hypothesis lected for tameness and for defensive aggression towards humans. Horm is that the cognitive task we presented to the foxes was not compli- Behav 53:413–421. cated enough to display sex-dependent differences. For example, Bates D, Ma ¨ echler M, Bolker B, Walker S, 2015. Fitting linear mixed-effects great tits Parus major were found to differ in a sex-by-personality models using lme4. J Stat Soft 67:1–48. interaction only when the learning tasks became harder (Titulaer Bell AM, Hankison SJ, Laskowski KL, 2009. The repeatability of behavior: a et al. 2012). meta-analysis. Anim Behav 77:771–783. Downloaded from https://academic.oup.com/cz/advance-article-abstract/doi/10.1093/cz/zoy021/4924851 by Ed 'DeepDyve' Gillespie user on 13 July 2018 Petelle et al. Tameness and learning in a fox 5 Benson-Amram S, Holekamp KE, 2012. Innovative problem solving by wild Biology and Conservation of Wild Canids. Oxford: Oxford University spotted hyenas. Proc R Soc B Biol Sci 279:4087–4095. Press, 227–242. Biondi LM, Bo ´ MS, Vassallo AI, 2010. Inter-individual and age differences in Matzel LD, Kolata S, Light K, Sauce B, 2017. The tendency for social submis- exploration, neophobia and problem-solving ability in a Neotropical raptor sion predicts superior cognitive performance in previously isolated male Milvago chimango. Anim Cogn 13:701–710. mice. Behav Process 134:12–21. Brust V, Guenther A, 2017. Stability of the guinea pigs personality— Morand-Ferron J, Cole EF, Quinn JL, 2015. Studying the evolutionary ecology cognition—linkage over time. Behav Process 134:4–11. of cognition in the wild: a review of practical and conceptual challenges. Burns JG, Rodd FH, 2008. Hastiness, brain size and predation regime affect Biol Rev 91:367–391. the performance of wild guppies in a spatial memory task. Anim Behav 76: Nawroth C, Prentice PM, McElligott AG, 2017. Individual personality differ- 911–922. ences in goats predict their performance in visual learning and Carazo P, Noble DWA, Chandrasoma D, Whiting MJ, 2014. Sex and boldness non-associative cognitive tasks. Behav Process 134:43–53. explain individual differences in spatial learning in a lizard. Proc R Soc B Nowak K, le Roux A, Richards SA, Scheijen CPJ, Hill RA, 2014. Human Biol Sci 281:20133275. observers impact habituated samango monkeys’ perceived landscape of Carere C, Maestripieri D, 2013. Animal Personalities: Behavior, Physiology, fear. Behav Ecol 25:1199–1204. and Evolution. Chicago (IL): University of Chicago Press. Nel JAJ, 1978. Notes on the food and foraging behavior of the bat-eared fox Carere C, Locurto C, 2011. Interaction between animal personality and ani- Otocyon megalotis. Bull Carnegie Mus Nat Hist 6:132–137. mal cognition. Curr Zool 57:491–498. Nel JAJ, 1990. Foraging and feeding by bat-eared foxes Otocyon megalotis in Carter AJ, Feeney WE, Marshall HH, Cowlishaw G, Heinsohn R, 2013. the southwestern Kalahari. Koedoe 33:9–16. Animal personality: what are behavioural ecologists measuring? Biol Rev Nussey DH, Wilson AJ, Brommer JE, 2007. The evolutionary ecology of indi- Camb Philos Soc 88:465–475. vidual phenotypic plasticity in wild populations. J Evol Biol 20:831–844. Chang C, Ng PJ, Li D, 2016. Aggressive jumping spiders make quicker deci- Øverli Ø, Sørensen C, Pulman KGT, Pottinger TG, Korzan W et al. 2007. sions for preferred prey but not at the cost of accuracy. Behav Ecol. doi: Evolutionary background for stress-coping styles: relationships between 10.1093/beheco/arw174. physiological, behavioral, and cognitive traits in non-mammalian verte- Chittka L, Dyer AG, Bock F, Dornhaus A, 2003. Psychophysics: bees trade off brates. Neurosci Biobehav Rev 31:396–412. foraging speed for accuracy. Nature 424:388. Pauw A, 2000. Parental care in a polygynous group of bat-eared foxes, Chittka L, Skorupski P, Raine NE, 2009. Speed-accuracy tradeoffs in animal Otocyon megalotis (Carnivora: canidae). Afr Zoo 35:139–145. decision making. Trends Ecol Evol 24:400–407. Pe ´ riquet S, le Roux A, 2017. Seasonal patterns of habitat selection in the in- de Haas EN, Lee C, Hernandez CE, Naguib M, Rodenburg TB, 2017. sectivorous bat-eared fox. Afr J Ecol 67:1–7. Individual differences in personality in laying hens are related to learning a R Core Team, 2016. R: A Language and Environment for Statistical colour cue association. Behav Process 134:37–42. Computing. Vienna: R Foundation for statistical computing. http://www.R- Driscoll CA, Macdonald DW, O’Brien SJ, 2009. From wild animals to domes- project.org/ tic pets, an evolutionary view of domestication. Proc Natl Acad Sci USA Re ´ ale D, Garant D, Humphries MM, Bergeron P, Careau V et al., 2010. 106:9971–9978. Personality and the emergence of the pace-of-life syndrome concept at the Gibelli J, Dubois F, 2016. Does personality affect the ability of individuals to population level. Phil Trans R Soc B Biol Sci 365:4051–4063. track and respond to changing conditions? Behav Ecol. doi: Re ´ ale D, Reader SM, Sol D, McDougall PT, Dingemanse NJ, 2007. 10.1093/beheco/arw137. Integrating animal temperament within ecology and evolution. Biol Rev 82: Grifﬁn AS, Guillette LM, Healy SD, 2015. Cognition and personality: an ana- 291–318. lysis of an emerging ﬁeld. Trends Ecol Evol 30:207–214. Shettleworth SJ, 2001. Animal cognition and animal behaviour. Anim Behav Guenther A, Brust V, Dersen M, Trillmich F, 2014. Learning and personality 61:277–286. types are related in cavies Cavia aperea. J Comp Psychol 128:74. Shettleworth SJ, 2009. Cognition, Evolution, and Behavior. Oxford: Oxford Guenther A, Brust V, 2017. Individual consistency in multiple cognitive per- University Press. formance: behavioural versus cognitive syndromes. Anim Behav 130: Sih A, Cote J, Evans M, Fogarty S, Pruit J, 2012. Ecological implications of be- 119–131. havioural syndromes. Ecol Lett 15:278–289. Guillette LM, Hahn AH, Hoeschele M, Przyslupski A, Sturdy CB, 2015. Sih A, Del Giudice M, 2012. Linking behavioural syndromes and cognition: a Individual differences in learning speed, performance accuracy and explora- behavioural ecology perspective. Phil Trans R Soc B Biol Sci 367: tory behaviour in black-capped chickadees. Anim Cogn 18:165–178. 2762–2772. Guillette LM, Naguib M, Grifﬁn AS, 2017. Individual differences in cognition Smith BR, Blumstein DT, 2008. Fitness consequences of personality: a and personality. Behav Process 134:1–3. meta-analysis. Behav Ecol 19:448–455. Guillette LM, Reddon AR, Hoeschele M, Sturdy CB, 2010. Sometimes slower Stamps JA, 2007. Growth-mortality tradeoffs and “personality traits” in ani- is better: slow-exploring birds are more sensitive to changes in a vocal dis- mals. Ecol Lett 10:355–363. crimination task. Proc R Soc B Biol Sci 278:767–773. Titulaer M, van Oers K, Naguib M, 2012. Personality affects learning per- Iredale SK, Nevill CH, Lutz CK, 2010. The inﬂuence of observer presence on formance in difﬁcult tasks in a sex-dependent way. Anim Behav 83: baboon (Papio spp.) and rhesus macaque Macaca mulatta behavior. App 723–730. Anim Behav Sci 122:53–57. Udino E, Perez M, Carere C, D’ettorre P, 2017. Active explorers show low Jarosz AF, Wiley J, 2014. What are the odds? A practical guide to computing learning performance in a social insect. Curr Zool 63:555–560. and reporting Bayes factors. J Probl Solving 7:2–9. Welch RJ, Pe ´ riquet S, Petelle MB, Le Roux A, 2017. Hunter or hunted? Kluen E, Brommer JE, 2013. Context-speciﬁc repeatability of personality traits Perceptions of risk and rewqrd in a small mesopredator. J Mammal 98: in a wild bird: a reaction-norm perspective. Behav Ecol 24:650–658. 1531–1537. Lucon-Xiccato T, Dadda M, Bisazza A, 2016. Sex differences in discrimin- Welch RJ, Le Roux A, Petelle MB, Pe ´ riquet S, 2018. The inﬂuence of environ- ation of shoal size in the guppy (Poecilia reticulate). Ethology 122:481–491. Lucon-Xiccato T, Bisazza A, 2017. Sex differences in spatial abilities and cog- mental and social factors on high- and low-cost vigilance in bat-eared foxes. nitive ﬂexibility in the guppy. Anim Behav 123:53–60. Beh Ecol Sociobiol 72:29. Maas B, Macdonald DW, 2004. Bat-eared foxes, insectivory and luck: lessons Wolf M, Weissing FJ, 2012. Animal personalities: consequences for ecology from an extreme canid. In: Macdonald DW, Sillero-Zubiri C, editors. The and evolution. Trends Ecol Evol 27:452–461. Downloaded from https://academic.oup.com/cz/advance-article-abstract/doi/10.1093/cz/zoy021/4924851 by Ed 'DeepDyve' Gillespie user on 13 July 2018
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