Ethology RESEARCH PAPER
Stability in Activity and Boldness Across Time and Context in Captive Siberian Dwarf Hamsters L. Leann Kanda, Laura Louon & Katherine Straley Department of Biology, Ithaca College, Ithaca, NY, USA
Correspondence L. Leann Kanda, Department of Biology, Ithaca College, 953 Danby Rd., Ithaca, NY 14850, USA. E-mail:
[email protected]
Received: January 11, 2012 Initial acceptance: March 4, 2012 Final acceptance: March 4, 2012 (D. Zeh) doi: 10.1111/j.1439-0310.2012.02038.x
Abstract Individual personality is an important source of variation in animal behavior. However, few studies have examined the reliability of individual behaviors across both time and context for even common temperament traits such as boldness, especially in mammals. We tested a laboratory colony of Siberian dwarf hamsters (Phodopus sungorus) in two similar assays, a tunnel maze and an open field, both provisioned with a home nestbox for shelter. Animals were tested in each assay at three ages, beginning at weaning. Principal components analysis on each assay identified an axis of activity level in both tests, boldness and reactivity in the tunnel maze, and nestbox orientation in the open field. All traits were moderately (7–18%) heritable. Individual activity level was the most reliably consistent trait, both within and between tests. Tunnel maze boldness, tunnel maze reactivity, and open field nestbox orientation did not correlate at any age. Correlation between boldness and activity changes from positive to negative as animals age, while reactivity was consistently negatively associated with activity. A negative correlation emerged in adults between open field activity and nestbox orientation. These results suggest that either development or habituation results in different personality trait associations in an individual over time. Individual temperament traits such as general activity level may be quite stable, but caution should be used in generalizing single assays to represent boldness across time and across contexts.
Introduction It is well established that individual animals in many species display distinct and consistent differences in behavior, and that such individual variation has implications for ecology and evolution of wild populations (Sih et al. 2004; Re´ale et al. 2007, 2010). Personality traits or temperament traits (differences in interindividual behavior that are ‘repeatable over time and across situations’, sensu Re´ale et al. 2007) can have fitness consequences, such as enhancing success at acquiring mates or increasing an individual’s mortality risk (Smith & Blumstein 2008). Multiple personality types might be maintained in natural populations through trade-offs, either within a personality trait across functional context (Sih 518
et al. 2004), between traits correlated by genetic or regulatory pathways (Sih et al. 2004), or between personality traits and various life-history traits (Wolf et al. 2007). Relative success of different personality types may also be frequency-dependent (Dall et al. 2004) or change with spatiotemporal environmental fluctuations (Dingemanse et al. 2004). Evolution, then, can shape correlations in temperaments across individuals in a population, generating what are termed behavioral syndromes (Sih et al. 2004). Repeatability of behaviors, both across time and contexts, is a key component to identifying individual personality profiles (e.g. Martin & Re´ale 2008; Uher et al. 2008). Repeated measures of individuals in controlled contexts often show high reliability (see review by Bell et al. 2009 of diverse taxa), Ethology 118 (2012) 518–533 ª 2012 Blackwell Verlag GmbH
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despite the fact that individual behavior in any given context may be influenced not only by the animal’s genetics, but also development and experience (Stamps & Groothuis 2010), current physiological status, current social status, and individual plasticity (itself with genetic and environmental determinants; Dingemanse et al. 2009), as well as correlations among these factors. Given the complexity of factors entering into individual behavior, it is not surprising that variation among individuals has historically been treated as background noise (Dall et al. 2004). The shy-bold continuum is perhaps one of the most well-studied personality traits. Boldness, or risk-taking, has been positively correlated in a wide variety of taxa with individual activity, exploration, migration, and aggression (e.g. fish, Huntingford 1976; Fraser et al. 2001; lizards, Cote & Clobert 2007; tortoises, Mafli et al. 2011; birds, Dingemanse et al. 2003; Gabriel & Black 2010; chipmunks, Martin & Re´ale 2008; spiders, Johnson & Sih 2007; ants, Chapman et al. 2011). Direct links between individual boldness and reproductive success support the importance of this personality trait as one shaped by evolution (Re´ale et al. 2010). Boldness as a personality trait may constrain individuals to behave suboptimally in different contexts; risk-taking may bring greater foraging success in novel environments, for example, but also cause the individual to increase boldness under predation risk, decreasing survival probability (Bell & Sih 2007). While the behavioral syndrome literature focuses on these correlations among behaviors across multiple contexts, the context specificity of individual behaviors has also been demonstrated, and the tension between the two is of interest for understanding the constraints on behaviors and their evolution (Bell & Sih 2007). The evaluation of a behavior with a single captive testing scheme, even conducted multiple times to demonstrate individual reliability, is still subject to the problem of context specificity. Behaviors may be artificially induced by the captive setting (e.g. social context; Dingemanse & de Goede 2004), or reflect the expression of temperament unique to a limited functional context (Herborn et al. 2010). Obtaining repeated measures on numerous individuals in comparable circumstances can be logistically challenging (Bell et al. 2009; Archard & Braithwaite 2010), let alone in multiple tests. Laboratory assessment of animals provides the best control of conditions, ensures the ability to take repeated measures, and maintaining captive colonies permits for experimental manipulation and selection (Campbell et al. 2009). Such captive assays have provided the most robust models Ethology 118 (2012) 518–533 ª 2012 Blackwell Verlag GmbH
of behavioral syndromes to date, notably investigation of sticklebacks (Bell 2005; Bell & Sih 2007; Dingemanse et al. 2007) and great tits (Verbeek et al. 1994; Dingemanse et al. 2003; van Oers et al. 2004). Although animal personality research classically began with laboratory mammals (see reviews in Gosling 2001; Sih et al. 2004), examination of mammalian personality from the behavioral syndrome perspective is still relatively scant. Bell et al. (2009) included only three mammalian studies in their meta-analysis of 114 personality studies with comparable repeatability estimates. Within the extensive mammalian work on personality (see Gosling 2001), much of it is on artificially selected domestic animals or laboratory models where individual variation had been deliberately minimized with inbred strains, often focusing on single phenotypes (e.g. aggression, Chiavegatto et al. 2001; exploration, Kazlauckas et al. 2011). In this study, we present the first examination of individual variation and cross-contextual consistency in boldness behavior of a laboratory mammal gaining popularity in endocrinological research, the Siberian dwarf hamster Phodopus sungorus. Model System The dwarf hamsters (genus Phodopus) have been used as models of hormones and behavioral processes, particularly in relation to photoperiod (e.g. Helwig et al. 2009; Zysling et al. 2009; Scherbarth & Steinlechner 2010), parental care (Wynne-Edwards 1995; Timonin & Wynne-Edwards 2008), or aggression (Jasnow et al. 2000; Gammie & Nelson 2005; Scotti et al. 2007). These animals are more recently wild-outbred than most laboratory rodents, but are as easily maintained in captive conditions. Their activity patterns in the laboratory are consistent with wild behavior (Wynne-Edwards et al. 1999; Weinert et al. 2009). Sister species Phodopus campbelli and Phodopus sungorus show between-species differences in activity (Wynne-Edwards et al. 1999), reproduction and photoperiod (Timonin et al. 2006), and parental care (Wynne-Edwards 1995). Djungarian dwarf hamsters, Phodopus campbelli, showed high individual variation in a suite of behavioral and physiological stress responses (Guimont 2009). However, the hamsters showed no correlation between physiological and behavioral measures. Interestingly, different behavioral assays expected to measure the same behavior (called by Guimont exploratory, but what we call boldness, i.e. risk-taking) failed to correlate with one another. 519
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Here, we examined the Siberian dwarf hamster (Phodopus sungorus) to evaluate whether individual boldness and activity behaviors in this species are distinct, heritable, temporally stable, and consistent across multiple assays with similar contexts. We predicted interindividual variation, but consistent within-individual personalities. Methods Study animals
Our first generation was composed of fourteen Siberian dwarf hamsters (Phodopus sungorus), seven males and seven females, obtained from N.J. Place (Cornell University, Ithaca, NY) as the animals were weaned. They are descendents of wild-bred stock from K.E. Wynne-Edwards (Queen’s University, Kingston, ON). The animals were housed in Sterilite polypropylene tubs (Sterilite, Townsend, MA, USA) 42.5 · 30.2 · 17.8 cm with wire mesh tops, either individually or with a single same-sex sibling. Each cage was provided with a nestbox (15 · 15 · 8 cm Ziploc (SC Johnson, Racine, WI, USA) or equivalent container) with a defensible (5 cm diameter) entrance. Water and food (a mix of Kaytee Forti-Diet chow (Kaytee Products, Chilton, WI, USA) and mixed seeds) were available ad libitum. Cages were cleaned only once per week to minimize disturbance, with nesting material transferred to the new nestbox to help with olfactory continuity. The colony was maintained under a long-day 16L ⁄ 8D cycle. All testing was completed within the first 4 h of the dark cycle. Each hamster was tested in a tunnel maze and in an open field test at three ages: juvenile (postweaning 18–29 d old), adult1 (45–65 d), and adult2 (>72 d). Animals were not tested more than once a day, and the order of tests at each age was random. Each subsequent generation was the product of four litters. We used the activity level in the tunnel maze to identify the highest and lowest activity animals. We then mated high–high (two pair) and low–low (two pair) activity animals, avoiding brother–sister pairings. Breeding pairs were placed in cages 85 · 40 · 15 cm, and the male was removed before the litter was born. In the first generation (P), we were only able to successfully breed three pairs, so we obtained an additional six animals from Dr. Place (Cornell University). These new animals were included with F1 animals in the selection of parents to generate F2. The data set encompasses four generations (P through F3), a total of 84 animals. By the last generation (F3), all animals were first cousins. 520
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Testing Tunnel maze
The tunnel maze is based upon a design used by Myers & Krebs (1971) to examine captive activity tendencies in voles. The maze consisted of two 85 · 40 · 15 cm translucent Sterilite containers connected by PVC tubing. Each container was divided into 15 sections using 35 · 10 cm pieces of opaque plastic, creating in total a 12-m-long (5 cm wide) run for the animal zig-zagging through 30 rows connected by 180 blind turns. The maze was covered with a clear plastic sheet to limit airflow between rows and prevent escape. At one end, the individual’s home nestbox was connected to the maze with PVC tubing. Prior to testing, the entrance to the maze was gated and the individual was allowed 10 min to settle in its box. The hamster was then allowed free range of the maze for 30 min. An observer noted the time of movements between tunnels with the JWatcher software, either while watching the test live or scoring based upon the video recording of the test (JWatcher v1.0, Blumstein & Daniel 2007).
Open field
Variations of the open field test are perhaps the most commonly used assessment of mammalian boldness (Walsh and Cummins 1976, Gosling 2001). Our open arena consisted of a 180 · 75 cm (1.35 m2) light gray hard plastic surface surrounded by a 35cm-tall white plastic walling. The open arena was left uncovered. The animal was secured into its home nestbox, and the nestbox was placed within the arena, centered on one of the short walls. The entrance to the box was then immediately opened, and the test began. The animals were permitted up to 45 min to exit the box, at which point, if they were still in the box, the test was ended (in analysis, this was truncated for logistical reasons to 30 min). Once they exited the box, they were allowed to move freely for 30 min. An observer recorded the animal’s behaviors live during the test using JWatcher (JWatcher v1.0, Blumstein & Daniel 2007). Both tunnel maze and open field tests were carried out under red light and recorded with infraredequipped video cameras. All open field tests were scored by one of 13 observers during the live test. We had only one observer available per test, and as camera resolution was inadequate for identifying behaviors on video, we were not able to test for interobserver reliability. Interobserver reliability among 15 observers in the tunnel maze was not of Ethology 118 (2012) 518–533 ª 2012 Blackwell Verlag GmbH
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concern because the raw scores were not strongly subject to observer interpretation (raw data was a timestamp of when an animal was in each row); the primary author (LLK) spot-checks observer scores against video recordings and has found only a few seconds’ deviation with observer records (L. L. Kanda, unpubl. data). Between each test, the testing arenas were cleaned with a mild solution of Roccal-D veterinary disinfectant, rinsed with water, and dried. All animal housing and testing conformed to Ithaca College IACUC Protocol S08-01. Measures
The 30-min records of tunnel maze behavior were summarized for each animal. We calculated the time to exit the nestbox (t-to1), the time from first exiting the nestbox to reaching the final (30th) maze row (t-to30), the number of the highest row entered (t-highest), the total time spent in the maze (t-totalout), the percentage of the time spent in the maze that was spent in the five rows closest to the nestbox (t-near), the length of the longest bout outside the nestbox before returning (t-maxout), the number of times the animal returned to the nestbox (t-returns), and the total number of times the animal transitioned between rows (or the nestbox) (t-moves). If the animal did not reach the end of the maze, t-to30 was set to the maximum 30 min. If the animal did not enter the maze, t-to1 was also set at 30 min. From the open field test records, we calculated several measures, beginning with the time it took the animal to first exit its nestbox (o-toexit), up to 30 min in analysis. Once the animal left the nestbox, we summarized animal activity for the following 25 min, truncated from a 30-min protocol. We measured the total time spent outside the nestbox (o-totalout) and the length of the longest bout outside the box (o-maxout). We also summed the time spent oriented on the box (for example, moving or pulling nesting material out of the box; o-nbmanipulate), oriented on the arena wall (o-escape), in general walking or running (o-move), and in grooming (o-groom). Finally, we counted the number of times the animal climbed on top of the nestbox (o-top), returned into the nestbox (o-returns), and squeaked (o-squeaks). If the animal did not leave the nestbox, o-toexit was set to 30 min, and all other measures were set to zero. Statistical Analysis
All statistical analyses were conducted in R (v 2-12-2; R Development Core Team 2011). We used principal Ethology 118 (2012) 518–533 ª 2012 Blackwell Verlag GmbH
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components analyses (PCA) as a data reduction method on each test’s set of measures to yield composite behavior scores for each experiment. Measures were standardized, but not transformed, although they were not normally distributed. When using PCA for data reduction rather than inferential analysis, assumption of normality is not required (Tabachnick & Fidell 2001). Both the scree plots of the eigenvalues and the Kaiser–Guttman criterion (eigenvalues > 1) were considered in deciding the number of factors to retain. We removed measures that did not load at least 0.3 on the retained factors and reran the analysis. We examined unrotated, varimax, and oblimin rotations for scores that were most easily interpreted for behavioral meaning. The repeated measures design could cause problems in interpretation of resulting principal components if the association among the test measures changes with age (Tabachnick & Fidell 2001). We therefore also conducted PCA on each age class data set separately for each test to examine the consistency of factor loadings. After identifying related principal components across the four analyses (3 ages and the full data set), we evaluated the consistency of the factor loadings with Pearson’s correlations between the full data set and individual age classes. As the open field test failed to show strong consistency in PCA factor loadings across ages, we also selected for parallel analysis some of the original measures to represent behaviors of interest in that assay. Measures were standardized, but not normalized (normal distributions are not required by the subsequent analyses). Finally, to directly examine the developmental plasticity between juvenile and adult behavior, we also calculated the difference between juvenile and adult1 scores for each test. Once scores characterizing each individual’s behavior in each trial were established, we measured the reliability (repeatability) of individual hamster performance by calculating Cronbach’s a (a measure of the ratio of covariance within the individual to the variance of the whole group) in each score for the full data set, and Cronbach’s a and Pearson’s correlations (r) in pairwise comparisons among the three ages. Significance of Cronbach’s a was determined by estimating a distribution-free confidence interval (Coffman et al. 2008), set to accommodate family-wise correction. Plasticity between juvenile and adult behavior cannot be replicated over time, but we examined the correlation in plasticity across measures. To characterize each individual in each behavior, some prior studies have relied upon BLUPs (best 521
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linear unbiased prediction) from mixed models (e.g. Martin & Re´ale 2008; Boyer et al. 2010). However, statistical issues have led to cautions against such a use (Hadfield et al. 2010; Wilson et al. 2010). We used Spearman’s rank correlations to compare the behavior scores for each age class separately. We considered significance both before and after sequential Bonferroni correction in each data set (Moran 2003). Realized (narrow-sense) heritability (h2), the proportion of additive genetic variance to phenotypic variance, can be estimated in numerous ways, for example, in a simple regression of offspring on mean parent phenotype (Falconer & Mackay 1996). We chose the adult1 trial to represent individuals in such a regression analysis as a rough estimate. To take advantage of additional pedigree information and repeated measures available in our study, we also estimated heritability using the animal model described by Wilson et al. (2010) using R package MCMCglmm (Hadfield 2010). The animal model works as a Bayesian version of linear mixed modeling, with the pedigree providing additive genetic variance as a random effect. This Bayesian technique requires selection of priors. The inversegamma is often used (all V = 1, l = 0.002); however, with small variance (as we have in our scores), this can cause problems (Gelman 2006). We instead selected a univariate inverse-Wishart with all V = 1, l = 1 (Hadfield 2010). We conducted univariate models instead of a single multivariate model because exploratory alteration of priors greatly altered multivariate but not univariate models. We examined the fixed effects of gender, age class, housing (with a sibling or alone), and generation as well as including additive genetic variance (Vg) and individual (Vi) as random effects. We used the Bayesian 95% HDI to determine whether fixed effects contributed significantly to the model, and used backward selection to a final model. In the final model, heritability was calculated as Vg ⁄ (Vg + Vi + Vr) where Vr is the residual variance (Wilson et al. 2010). Results Principal Components Scores
We ran the 84 animals, representing four generations, through a total of 229 trials in the tunnel maze and 205 trials in the open field. Among unrotated, varimax, and oblimin solutions, the unrotated PCA generated the most biologically meaningful loading interpretations. The first three principal components in the tunnel maze assay and the first two 522
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components in the open field assay met both scree and Kaiser–Guttman criteria (Table 1). As the sign of loadings is arbitrary (Maindonald & Braun 2010), for ease in interpretation, we oriented all axes to make principal component scores positively associated with the interpreted behavior. Factor loadings on the first three principal components from the tunnel maze showed behavioral axes that were highly consistent across the age classes (Table 1). We can therefore be confident that the principal component scores from the aggregate data are appropriate for interpretation of behaviors in individual trials regardless of age. T1, the first principal component of the tunnel maze, accounts for 50% of the variation among trials and describes activity level in the test; high scores are associated with moving quickly to the far end of the test and spending most of the test in the maze (Table 1). On the other hand, T2, the second component explaining 19% of the variance in the full data set, contrasts the maximum bout out of the box and the number of nestbox returns, suggesting that this axis is associated with a willingness to spend time away from the nestbox. We consider this an aspect of boldness, that is, risk-taking behavior. T3 further explained 15% of the variance, but its biological interpretation is not as clear. T3 scores relate latency to enter the maze and time in the maze spent in proximity to the nest box. We tentatively refer to this as a measure of reactivity, with animals that are reactive to disturbance moving quickly out of the nestbox but then remaining near it for most of the time spent in the maze. As in the tunnel maze, the first component of the open field PCA, O1, appears to relate to activity, representing 27% of the variation among trials. High scores in O1 are particularly associated with short latency to exit the nestbox, high total time spent outside the box, and high time spent in escape behavior oriented at the arena wall (Table 2). The second component, O2, contrasts nestbox-oriented behavior with spending long bouts outside the nestbox and accounts for an additional 23% of the variance. The nestbox-oriented activity does not appear to be entirely ‘shy’ (or non-risk-taking) behavior, as it involves highly conspicuous activities such as climbing on top of the box, dragging the box around the arena, and pulling nesting material out of the box. This behavioral axis then appears to represent a manipulative, nestbox-oriented temperament. The open field maze principal component axes are not as stable as the tunnel maze assay across ages (Table 2). One axis (the second component derived in the full data set) is identifiable at all age classes, Ethology 118 (2012) 518–533 ª 2012 Blackwell Verlag GmbH
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Table 1: Eigenvectors of first three principal components from the tunnel maze full data set, with comparison to eigenvectors identified with individual age classes. Variables with the largest effect (>0.4) are in bold Measure Time to enter maze % time in maze near box # of returns to box Highest row Time to far end of maze Longest bout in maze Total time in maze # of moves Eigenvalue % variance explained Correlation with T1
t-to1 t-near t-returns t-highest t-to30 t-maxout t-totalout t-moves
Measure Time to enter maze % time in maze near box # of returns to box Highest row Time to far end of maze Longest bout in maze Total time in maze # of moves Eigenvalue % variance explained Correlation with T2
t-to1 t-near t-returns t-highest t-to30 t-maxout t-totalout t-moves
Measure Time to enter maze % time in maze near box # of returns to box Highest row Time to far end of maze Longest bout in maze Total time in maze # of moves Eigenvalue % variance explained Correlation with T3
t-to1 t-near t-returns t-highest t-to30 t-maxout t-totalout t-moves
T1 (activity)
Juvenile PC1
Adult1 PC1
Adult2 PC1
)0.28 )0.38 0.20 0.46 )0.43 0.23 0.41 0.36 4.03 50.4
)0.27 )0.28 0.04 0.46 )0.40 0.38 0.42 0.39 4.09 51.1 0.97
)0.32 )0.44 0.15 0.43 )0.41 0.23 0.41 0.32 4.3 53.8 1.00
)0.20 )0.41 0.27 0.45 )0.44 0.15 0.41 0.37 4.04 50.5 0.99
T2 (boldness)
Juvenile PC3a
Adult1 PC2
Adult2 PC2
)0.05 )0.07 )0.61 0.04 0.14 0.66 0.22 )0.33 1.51 15.3
)0.28 0.30 )0.44 )0.09 0.20 0.54 0.29 )0.46 1.06 13.3 0.86
)0.15 0.04 )0.66 )0.09 0.16 0.65 0.21 )0.21 1.41 17.6 0.97
)0.12 )0.09 )0.49 0.08 0.11 0.75 0.23 )0.32 1.44 18.00 0.99
T3 (reactivity)
Juvenile PC2a
Adult1 PC3
Adult2 PC3
)0.66 0.49 0.32 )0.16 0.29 0.11 0.32 )0.07 1.22 15.3
)0.51 0.48 0.61 )0.07 0.22 0.11 0.20 0.14 1.83 22.8 0.89
)0.62 0.30 0.44 )0.24 0.39 0.02 0.35 )0.07 0.95 11.9 0.96
)0.72 0.43 0.34 )0.17 0.24 0.06 0.30 )0.01 1.28 16.0 0.99
a
PC scores across age groups were aligned to maximize correlation among data sets.
but the other axes do not clearly align. The interpretations and applicability to the original trial behaviors may be suspect. We also chose to directly examine measures o-totalout (the total time spent exposed in the open field) and o-escape (time spent in escape behavior) as representatives of activity, with o-escape also interpretable as a measure of boldness. We presume higher time spent in escapeoriented behavior is associated with lower boldness, as wall-oriented activity in an open field test is classically interpreted as high stress (Archer 1973; Martin & Re´ale 2008). We also included o-nbmanipulate, Ethology 118 (2012) 518–533 ª 2012 Blackwell Verlag GmbH
time spent manipulating the nestbox, as a primary representative of nestbox orientation. Individual Variation and Repeatability
Neither gender nor housing arrangement had a significant effect on any of the behavioral scores. Juvenile trials had significantly lower T1 activity compared with either adult trial (Bayesian 95% HDI with adult1 as baseline: juvenile, )1.77 < )1.46 < )1.00; adult2, )0.52 < )0.11 < 0.22; Fig. 1). T2 boldness scores tended to decrease across all three 523
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Table 2: Eigenvectors of first three principal components from the open field full data set, with comparison to eigenvectors identified with individual age classes. Variables with the largest effect (>0.4) are in bold. Adult2 trials had no squeaks. Only O1 and O2 were retained for further analysis
Time to enter arena # of squeaks Time oriented on box # climbs on top of box # returns to box Time oriented on arena wall Time moving (non-escape) Longest bout in arena Total time in arena Eigenvalue % variance explained Correlation with O1
Time to enter arena # of squeaks Time oriented on box # climbs on top of box # returns to box Time oriented on arena wall Time moving (non-escape) Longest bout in arena Total time in arena Eigenvalue % variance explained Correlation with O2
Time to enter arena # of squeaks Time oriented on box # climbs on top of box # returns to box Time oriented on arena wall Time moving (non-escape) Longest bout in arena Total time in arena Eigenvalue % variance explained Correlation with O3
o-toexit o-squeaks o-nbmanipulate o-top o-returns o-escape o-move o-maxout o-totalout
o-toexit o-squeaks o-nbmanipulate o-top o-returns o-escape o-move o-maxout o-totalout
o-toexit o-squeaks o-nbmanipulate o-top o-returns o-escape o-move o-maxout o-totalout
O1 (activity)
Juvenile PC1
Adult1 PC3a
Adult2 PC2a
0.45 )0.03 0.07 )0.17 )0.08 )0.42 )0.33 )0.34 )0.60 2.47 27.4
0.42 )0.14 )0.21 )0.26 )0.32 )0.31 )0.42 )0.22 )0.51 3.17 35.2 0.88
0.39 )0.42 0.31 )0.66 )0.24 )0.20 0.00 0.18 )0.08 1.23 13.70 0.34
0.21 )0.44 )0.32 )0.10 )0.56 0.13 )0.37 2.11 26.4 0.65
O2 (nestbox orientation)
Juvenile PC2
Adult1 PC1a
Adult2 PC1a
)0.19 0.15 0.42 0.42 0.56 )0.26 0.17 )0.42 0.04 2.08 23.1
0.09 0.35 0.44 0.36 0.38 )0.34 0.03 )0.48 )0.24 2.06 22.8 0.87
0.15 0.09 0.39 0.11 0.43 )0.46 )0.07 )0.50 )0.40 2.60 28.9 0.80
0.36 0.26 0.40 )0.53 0.02 )0.47 )0.33 2.73 34.2 0.83
O3
Juvenile PC3
Adult1 PC2a
Adult2 PC3
0.02 )0.62 )0.17 )0.24 0.12 )0.37 0.61 )0.02 0.01 1.07 11.90
)0.23 )0.69 )0.06 )0.29 0.40 )0.19 0.29 )0.31 )0.07 1.01 11.30 0.80
0.06 0.03 0.08 0.16 0.02 )0.42 0.78 0.10 0.41 1.45 16.1 0.74
0.43
0.17
0.40 )0.57 )0.30 0.09 0.06 )0.10 )0.38 )0.51 1.06 13.2 0.14
a
PC scores across age groups were aligned to maximize correlation among data sets, considering only the first three principal components.
trials, with adult2 trials significantly lower than either of the others (juvenile, )0.08 < 0.25 < 0.62; adult2, )1.11 < )0.78 < )0.46). F2 and F3 generations had significantly higher T1 activity than P and F1 generations (Bayesian 95% HDI with baseline generation P: F1, )0.04 < 0.87 < 2.26; F2, 0.98 < 2.19 < 3.45; F3, 1.20 < 2.30 < 3.86.) We verified that the T1 and T2 patterns by age remain even if the parental generation is removed from the data set 524
(analysis not shown). Generation had no effect on T2 boldness, and neither age nor generation emerged as significant factors for T3 reactivity. O1 activity, total time out, and time in escape behavior in the open field test are lower in juveniles than in adults (Bayesian 95% HDI with adult1 as baseline: O1 juvenile, )1.52 < )1.06 < )0.71; adult2, )0.66 < )0.20 < 0.20; o-total juvenile )0.98 < )0.78 < )0.47, adult2 )0.43 < )0.78 < 0.16; Ethology 118 (2012) 518–533 ª 2012 Blackwell Verlag GmbH
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Fig. 1: Group means with SE for each behavior score by three age classes and four generations. O-total and O-nbmanipulate are highly nonnormal, so they are represented by median with upper and lower hinges. Note that group means do not correctly illustrate interaction effects.
o-escape juvenile )0.85 < )0.70 < )0.38, adult2 )0.21 < 0.09 < 0.33; Fig. 1). O1 activity and total time were significantly lower in the parental generation (P) than in any other generation (Bayesian 95% HDI with baseline generation P: O1 F1 0.64 < 1.41 < 2.20, F2 1.25 < 2.00 < 2.79, F3 1.02 < 1.64 < 2.69; o-total F1 0.32 < 0.73 < 1.30, F2 0.64 < 1.16 < 1.75, F3 0.32 < 1.10 < 1.51). Time in escape-oriented behavior was also significantly lower in generation P than in generation F2 and F3 (F2, 0.15 < 1.00 < 1.30; F3, 0.21 < 0.77 < 1.47). F1 generation’s time in escapeoriented behavior is also lower than in generation F2 (F1, )0.15 < 0.29 < 0.99). Removal of the parental generation from the data set did not change the observed effect by age class for any of these measures (analyses not shown). General nestbox orientation (O2) and specific nestbox manipulation also increase between juvenile and adult trials (O2: juvenile, )1.45 < )1.11 < )0.61; adult2, )0.57 < )0.14 < 0.32; o-nbmanipulate: juvenile, )0.80 < )0.54 < )0.22; adult2, )0.24 < Ethology 118 (2012) 518–533 ª 2012 Blackwell Verlag GmbH
0.04 < 0.36). Generation showed no effect on O2, but a significant difference emerges between generation P and F3 in o-nbmanipulate (o-nbmanipulate: F1, )0.78 < )0.12 < 0.27; F2, )0.71 < )0.17 < 0.40; F3, )1.24 < )0.50 < )0.03). The reliability estimates agree that an individual’s tunnel maze activity score (T1) was significantly repeatable among juvenile, adult1, and adult2 scores, with the strongest correlation between the two adult scores (a1–a2 a = 0.851, r = 0.741, both p < 0.001; Table 3). Individual scores in tunnel maze boldness (T2) and in reactivity (T3) are less consistent. In these two scores, only the adult trials significantly correlated (T2: a1–a2 a = 0.553, r = 0.382, both p < 0.001; T3: a1–a2 a = 0.540, r = 0.374, both p < 0.001). Open field activity (O1) showed repeatability (overall a = 0.542), with significant correlation between juvenile and adult1 trials (a = 0.437, r = 0.417, both p < 0.001; Table 3) and between the two adult trials (a = 0.694, r = 0.553, both p < 0.001). The same pattern was found in the repeat525
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Table 3: Comparison of reliability estimates of individual scores within the tunnel maze (T) and open field (O) across juvenile, adult1, and adult2 trials, and of the plasticity score (D) across tests T1 (activity)
T2 (boldness) Cronbach’s a
Full set j–a1 j–a2 a1–a2
0.819 0.723 0.679 0.851
Pearson’s r
0.567 0.515 0.741
O1 (activity)
0.542 0.437 0.296 0.694
Pearson’s r
0.417 0.251 0.553
O-totalout
Pearson’s r
Cronbach’s a
Pearson’s r
N
0.048 )0.392 )0.326 0.553
)0.164 )0.140 0.382
)0.039 )0.612 )0.093 0.540
)0.270 )0.047 0.374
64 69 64 76
Cronbach’s a
Pearson’s r
N
0.281 0.360 )0.201 0.272
0.269 )0.102 0.158
49 64 51 55
Cronbach’s a
Pearson’s r
N
)0.020 0.304 )0.243 0.202
0.179 )0.109 0.113
49 64 51 55
O-escape Cronbach’s a
Full set j–a1 j–a2 a1–a2
Cronbach’s a
O2 (nestbox orientation) Cronbach’s a
Full set j–a1 j–a2 a1–a2
T3 (reactivity)
0.374 0.332 0.171 0.562
Pearson’s r
0.337 0.136 0.391
Cronbach’s a 0.514 0.591 0.419 0.424
O-nbmanipulate Pearson’s r
0.422 0.265 0.270
D First trial (plasticity)
Full set DO1-DO2 DO1-DT1 DO1-DT2 DO1-DT3 DO2-DT1 DO2-DT2 DO2-DT3 DT1-DT2 DT1-DT3 DT2-DT3
Cronbach’s a
Pearson’s r
N
0.269 )0.017 0.003 )0.291 0.197 )0.657 )0.473 0.681 )0.171 )0.048
0.160 )0.009 0.002 )0.128 0.109 )0.248 )0.193 0.516 )0.079 )0.023
64 64 64 64 64 64 64 64 69 69 69
Correlations in bold are significant after family-wise correction (all significant p < 0.001).
ability of total time in the open field (Table 3). Time in escape-oriented behavior was also significantly correlated (overall a = 0.514) with significant pairwise correlation between juvenile and adult1 trials (a = 0.591, r = 0.422, both p < 0.001) and a significant Cronbach’s a between juvenile and adult 2 trials (a = 0.419, p < 0.001). O2 nestbox orientation was not significantly repeatable among trials (Table 3). Nestbox manipulation (o-nbmanipulate) also showed low overall repeatability (a = 0.281). A significant correlation between juvenile and adult1 trials emerges for nestbox manipulation in Cronbach’s a, but not in the Pear-
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son’s correlation (a = 0.360, p < 0.01; r = 0.269, p = 0.031). Plasticity (change from juvenile to adult1 score) was not correlated among any of the tunnel maze or open field scores except for a correlated plasticity in T1 activity and T2 boldness (a = 0.681; r = 0.516, p < 0.001; Table 3). Correlation Among Scores
Each tunnel maze behavioral score was compared to open field principal component scores (Fig. 2) and to open field measures (Fig. 3) with pairwise Spearman’s correlations. The correlation of activity scores
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(a)
(a)
(b)
(b)
(c) (c)
Fig. 2: Spearman’s correlations among the principal component behavior scores for age class (a) juvenile (3 wk old), (b) adult 1 (6 wk old), and (c) adult 2 (>9 wk old). Bold arrows indicate significant correlations after family-wise correction. Negative correlations are in gray. For simplicity, correlations of 0.10 or weaker are omitted.
Fig. 3: Spearman’s correlations among tunnel principal component behavior scores and open field measures for age class (a) juvenile (3 wk old), (b) adult 1 (6 wk old), and (c) adult 2 (>9 wk old). Bold arrows indicate significant correlations after family-wise correction. Negative correlations are in gray. For simplicity, correlations of 0.10 or weaker are omitted.
between the two contexts is significant and positive in all age sets, although more strongly associated in adults (juvenile, 0.37, p = 0.002; adult1, 0.47, p < 0.0001; adult2, 0.50, p < 0.0001). Correlation between tunnel maze activity (T1) and tunnel maze boldness (T2) is positive in juveniles (0.64, p < 0.0001), uncorrelated in adult1 ()0.08, p = 0.456), and negative in adult2 ()0.41, p = 0.0002). There is a similar pattern between open field activity (O1) and tunnel maze boldness, although the only significant correlation is the negative association in adult2 trials ()0.35, p = 0.005). Tunnel maze boldness also tends to reverse correlation over development with open nestbox orientation (O2) (negative in juveniles, positive in adult2), but none of the correlations are significant (juvenile, )0.21, p = 0.087; adult1, )0.03, p = 0.807; adult2, 0.11, p = 0.393).
Tunnel maze reactivity does not significantly correlate with any other measure in juveniles or adult1, but does negatively correlate with tunnel maze activity in adult2 trials ()0.36, p = 0.0015). Open field nestbox orientation (O2) is not significantly correlated with any other behavior in juveniles, but is negatively associated with open field activity in adults (adult1, )0.51, p < 0.0001; adult2, )0.40, p = 0.001). Comparison of tunnel behavior scores with the open field measures of total time out, time in escape, and nestbox manipulation shows that tunnel maze activity is consistently positively associated with open field escape behavior (0.34–0.38, all p < 0.002, Fig. 3) and with open field total time out (juvenile, 0.31, p = 0.011, not significant after family-wise correction; adult1 0.52, adult2, 0.48, both p < 0.0001).
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Fig. 4: Regression of offspring phenotypes on mean parental phenotypes for adult1 trials for each behavior score.
Open field total time out (o-total) and time in escape (o-escape) are positively correlated at all ages (0.45– 0.62, all p < 0.0001). In adults, nestbox manipulation is negatively correlated with time in escape (both, )0.62, p < 0.0001) and, less strongly, with total time out (adult1, )0.45, p < 0.0001; adult2, )0.23, nonsignificant at p = 0.062). Heritability
Over the course of this study, 16 litters were produced from 15 mating pairs. The 65 offspring with an adult1 trial in the tunnel maze showed no significant regression slope against their mean parent adult1 T1 activity score (slope 0.08 0.09 SE) (Fig. 4). Regression estimates for the other tunnel maze scores were slightly higher, but large variability makes them nonsignificant (T2 boldness 0.12 0.26 SE; T3 reactivity 0.24 0.21 SE). Similarly, none of the measures or principal component scores from the adult1 open field trials had significant regression coefficients (O1 activity 0.21 0.13 SE; O2 nestbox orientation 0.32 0.26 SE; o-total 0.22 0.14 SE; o-escape 528
0.26 0.15 SE; o-nbmanipulate 0.14 0.18 SE; N = 49). Heritability as calculated from the additive genetic variance in the animal model did come out significantly nonzero in all measures. Point estimates range from h2 = 0.07 (T1 activity) to h2 = 0.18 (o-total), but all HDIs overlap, indicating no significant difference in heritability among the measures (h2 and HDI: T1, 0.03 < 0.07 < 0.27; T2, 0.04 < 0.11 < 0.22; T3, 0.05 < 0.11 < 0.21; O1, 0.04 < 0.13 < 0.26; o-total, 0.07 < 0.13 < 0.28; o-escape, 0.08 < 0.18 < 0.35; O2 h2 = 0.05 < 0.12 < 0.29; o-nbmanipulate, 0.06 < 0.14 < 0.28). Discussion This study supports the literature that emphasizes the multidimensional nature of personalities with activity ⁄ exploration, boldness, and emotional reactivity as separate axes, as seen in laboratory rodents (e.g. Koolhaas et al. 1999), wild rodents (e.g. chipmunks, Martin & Re´ale 2008), and other species (e.g. fish, Budaev 1998). We found that despite Ethology 118 (2012) 518–533 ª 2012 Blackwell Verlag GmbH
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original concerns over the interpretability of the open field principal component scores, similar patterns emerge whether we use those scores or select individual measures. Time spent in escape-oriented behavior does seem to have some components of activity, positively correlating with total time out in the open field test and activity level in the tunnel maze. Compared with the raw measures of escape or total time out, the composite activity score shows higher reliability and stronger correlations with other measures. The use of principal components analysis on multiple measures helps parse general activity level from other behaviors. It is not surprising that general activity level emerges as a major component of variation in both of our assays, and that individual activity level is the most consistent individual temperament, repeatable both over time and across the two assays. General activity level appears to be a stable individual trait in rodents (e.g. voles, Timonin et al. 2011; chipmunks, Martin & Re´ale 2008) as well as numerous other taxa, both wild (Fraser et al. 2001) and in the laboratory (Drent et al. 2003). Activity levels are often interpreted as exploration, boldness, or anxiety, especially in open field tests (Walsh & Cummins 1976; Stanford 2007). However, if general activity level is an underlying temperament distinct from these behaviors, it may be confounding interpretations of the test. In a recent study of mouse temperament, Iba´n˜ez et al. (2009) found activity was a significant contributor to measures in a wide range of standard behavioral assays but was distinct from anxiety and novelty-seeking, both of which also influenced several of the same assays. While dwarf hamster activity in the two test contexts was generally associated, the measures were not interchangeable. At both juvenile and adult ages, the activity across contexts was correlated, but an individual’s activity in the tunnel maze as a juvenile showed greater consistency with its adult tunnel maze behavior than its activity across ages in the open field test. Interestingly, although on average the dwarf hamsters were less active in both contexts when they were juveniles, the plasticity of activity scores (change from juvenile to adult) was uncorrelated between the two tests. The larger number of behavioral options open to the dwarf hamsters in the open field may account for the greater lability in individual behavior in this test. Boldness, or risk-taking, is a particularly thorny temperament trait to define, despite (or perhaps because of) its popularity as a behavior of interest (Re´ale et al. 2007). In both of our contexts, we had Ethology 118 (2012) 518–533 ª 2012 Blackwell Verlag GmbH
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originally anticipated that boldness would be reflected by individuals spending time exposed outside of the nestbox. In the tunnel maze, we assumed that risk would be perceived to be greater the further an animal went in the maze, as the only path to shelter would be to retrace the length of the maze. In the open field, movement in the center rather than the edge of the arena is generally considered to be a measure of risk-taking (Walsh & Cummins 1976), and we assumed that the nestbox at the edge of the arena would serve as the focus of refuge-seeking behavior. However, in the open field, our dwarf hamsters had the opportunity to interact with the nestbox beyond sheltering in it. Many manipulated their nestboxes, with a negative correlation between time spent in escape behavior and time manipulating the nestbox. We conclude that hamsters with high nestbox manipulation or a composite high nestbox orientation are coping well with the open field in contrast to animals that display high thigmotaxis (attention to arena walls). Manipulation of the environment is a common characteristic of ‘proactive’ animals, normally associated with high boldness, exploration, and aggression (Koolhaas et al. 1999; Sih et al. 2004). Neither general nestbox orientation nor nestbox manipulation was significantly repeatable across trials, yet their heritability estimates are similar to the other scores. Nestbox orientation ⁄ manipulation appears to be a different functional trait from both the boldness and the reactivity axes identified in the tunnel maze, as there was no significant correlation, at any age, between an animal’s nestbox orientation or nestbox manipulation score in the open field and its boldness or reactivity scores in the tunnel maze. As studies increasingly use multiple methods to evaluate what are presumed to be single temperaments, there have been mixed results on the cross-context generalizability of assay results. In several species, boldness in risk-taking and foraging contexts are not correlated (pumpkinseed sunfish, Coleman & Wilson 1998; dumpling squid, Sinn et al. 2008). In other cases, individual boldness has been relatively invariate across functional contexts (e.g. spiders, Johnson & Sih 2007) or time frames (e.g. Stellar’s jays, Gabriel & Black 2010). Results may even be mixed for traits on the same individuals; in the same study on Stellar’s jays, Gabriel & Black (2010) found two ‘exploratory’ measures (reaction to a novel feeder and off-territory movement) did not correlate. Similarly, Herborn et al. (2010) found no relationship between two exploratory measures (‘exploration’ and ‘neophobia’) in blue tits, 529
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although each was repeatable over time and across captive and wild situations. Juvenile activity levels appear to be highly variable among individuals, with many more low-activity scores than at other ages. Where higher activity juveniles generally continue to have fairly similar activity level as adults, low-activity juveniles tend to increase activity as adults, but by an unpredictable amount. Such an increase in activity over development is unlike previous studies in rats (Ray & Hansen 2005; Gracceva et al. 2011). A positive association between plasticity of tunnel activity and tunnel boldness is probably an artifact of the assay; in a trial where an animal is very low activity, it spends so little time in the tunnel that it can only have a low boldness score. Adults with low activity, however, have moderate boldness scores, while higher activity adults show the range of extreme high and extreme low boldness. The relationships among activity level and other behaviors change as dwarf hamsters age. Individual trajectories between juvenile and first adult trial were varied. As a group, the dwarf hamsters became more active, more nestbox oriented and manipulative, but less bold as they got older. This does not mean that at any given age, individual activity level and nestbox orientation are positively correlated, with both negatively correlated with boldness. Rather, as juveniles, high-activity animals show higher boldness and a tendency to lower reactivity, with no clear relationship to open field nestbox orientation or manipulation. Association of high activity with boldness and low avoidance tendencies is a typical behavioral syndrome (Sih et al. 2004). However, as animals age, these typical personality profiles break down. The correlation between activity and tunnel maze boldness reverses, and a negative relationship between activity and open field nestbox orientation and manipulation emerges in adults. Reactivity, however, remains lower in highactivity animals. The decrease in both boldness and nestbox orientation and manipulation with increased activity among adult animals may reflect a habituation expressed in high-activity animals, but not in low-activity animals. Individual variation in plasticity has been documented in numerous laboratory and wild populations (Dingemanse et al. 2010). The level of plasticity has also been related to other behaviors. The proactive–reactive coping literature suggests that proactive animals tend to be less plastic (Koolhaas et al. 1999); however, in great tits, exploratory behavior was positively correlated with plastic530
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ity in other behaviors (Dingemanse & de Goede 2004). Animal age and experience with the test are confounded in this experiment, making it impossible to distinguish between habituation and developmental differences in behavior. Guimont (2009) found little evidence of neophobia in adult Phodopus campbelli, as was the case in the wild (Wynne-Edwards 1995), suggesting that these animals may become insensitive to novel stimuli as adults. Such insensitivity may explain our observation that both boldness and reactivity are negatively associated with activity level in adult Phodopus sungorus. The shifting personality structure we see in these trials suggests that Phodopus may make a good model for further examining developmental reaction norms, such as those described by Stamps & Groothuis (2010). Developmental effects may have played an unintended role as the mean activity level rose across our generations, even after accounting for pedigree. Our parental generation differed from the other generations, particularly as juveniles. This generation was raised in different conditions (at Cornell University) and was tested shortly after arriving at our facilities after weaning. In tunnel maze activity, a generational difference carried over into later generations. While all individuals were housed in the same cage conditions throughout the duration of the study, the number of animals housed in the room increased over time as the colony size grew. Population density is a classic influence on behaviors such as aggression and dispersal, particularly in rodents (Chitty 1960), and the general increase of activity level may have been influenced by the olfactory cues of a crowded environment. The behaviors we investigated were all heritable, although our heritability estimates are on the low end of those typical of behavioral traits. Laboratory estimates of behavioral heritability averaged 0.36 in 24 studies reviewed by Weigensberg and Roff (1996), with similar reports for field studies, supporting that laboratory studies such as ours are reliable indicators of heritability in the wild. While we saw similar heritability estimates for activity in each of our assays, heritability of activity level can be dependent upon context. Dingemanse et al. (2009), for example, found that stickleback activity when first introduced to a novel environment was considerably more heritable (0.27) than their activity 2 or 4 h later (0.06). Risk-taking often has lower heritability than other behaviors (van Oers et al. 2004), and we were surprised to find that tunnel maze boldness and reactivity, as well as open field nestbox Ethology 118 (2012) 518–533 ª 2012 Blackwell Verlag GmbH
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orientation, open field escape, and open field nestbox manipulation, all had similar heritability to the activity level even though the within-individual variability in these behaviors was higher. As we expected, activity level was a robust, crosscontextual, and heritable trait. Given that general activity level accounted for so much of the variation in both contexts, we echo Re´ale et al.’s (2007) call for promoting decomposition of multiple measures to generate behavioral scores for an assay. The other behavioral axes identified in our two contexts were surprisingly unrelated, although heritable. Even with the advantage of laboratory control, we found that age and ⁄ or repeated exposure to the test, as well as additional environmental effects over the generations, influenced the personality structure. The consideration of individual personality as an ecological and evolutionary force is an exciting avenue of research, but caution should be used in generalizing the meaning of individual assays across both time and context. Acknowledgements We are indebted to the many students who have worked in the Kanda laboratory, especially A. Abdulhay, L. Easton, E. Edwards, C. Erickson, K. MacKellar, and Y. Tabora. We also thank two anonymous reviewers for constructive comments. This work was funded by the Ithaca College Biology Department. Literature Cited Archard, G. A. & Braithwaite, V. A. 2010: The importance of wild populations in studies of animal temperament. J. Zool. 281, 149—160. Archer, J. 1973: Tests for emotionality in rats and mice: a review. Anim. Behav. 21, 205—235. Bell, A. M. 2005: Behavioral differences between individuals and two populations of stickleback (Gasterosteus aculeatus). J. Evol. Biol. 18, 464—473. Bell, A. M. & Sih, A. 2007: Exposure to predation generates personality in threespined sticklebacks (Gasterosteus aculeatus). Ecol. Lett. 10, 828—834. Bell, A. M., Hankison, S. J. & Laskowski, K. L. 2009: The repeatability of behavior: a meta-analysis. Anim. Behav. 77, 771—783. Blumstein, D. & Daniel, J. C. 2007: Quantifying Behavior the JWatcher Way. Sinauer, Sunderland, MA. Boyer, N., Re´ale, D., Marmet, J., Pisanu, B. & Chapuis, J. L. 2010: Personality, space use and tick load in an introduced population of Siberian chipmunks Tamias sibiricus. J. Anim. Ecol. 79, 538—547.
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Dingemanse, N. J., Kazem, A. J. N., Re´ale, D. & Wright, J. 2010: Behavioral reaction norms: animal personality meets individual plasticity. Trends Ecol. Evol. 25, 81—89. Drent, P. J., van Oers, K. & van Noordwijk, A. J. 2003: Realized heritability of personalities in the great tit (Parus major). Proc. R. Soc. Lond. B 270, 45—51. Falconer, D. S. & Mackay, T. F. C. 1996: Introduction to Quantitative Genetics, 4th edn. Prentice Hall, Harlow, UK. Fraser, D. F., Gilliam, J. F., Daley, M. J., Le, A. N. & Skalski, G. T. 2001: Explaining leptokurtic movement distributions: intrapopulation variation in boldness and exploration. Am. Nat. 158, 124—135. Gabriel, P. O. & Black, J. M. 2010: Behavioral syndromes in Steller’s jays: the role of time frames in the assessment of behavioral traits. Anim. Behav. 80, 689—697. Gammie, S. C. & Nelson, R. J. 2005: High maternal aggression in dwarf hamsters (Phodopus campbelli and P. sungorus). Agg. Behav. 31, 294—302. Gelman, A. 2006: Prior distributions for variance parameters in hierarchical models. Bayesian Analysis 1, 515—534. Gosling, S. D. 2001: From mice to men: what can we learn about personality from animal research? Psychol. Bull. 127, 45—86. Gracceva, G., Koolhaas, J. M. & Groothuis, T. G. G. 2011: Does the early social environment affect structure and consistency of personality in wild-type male rats? Dev. Psychobiol. 53, 614—623. Guimont, F. S. 2009: Stress Responses in an Outbred, Wild-Derived Hamster, Phodopus Campbelli: Individuality in the Cortisol Response to Acute Restraint Stress and the Absence of Strong Association with Behavioral Responses to Acute Restraint. Ph.D. Thesis, Queen’s Univ., Kingston, Ontario, Canada. Hadfield, J. 2010: MCMC methods for multi-response generalized linear mixed models: the MCMCglmm R package. J. Stat. Softw. 33, 1—22. Hadfield, J. D., Wilson, A. J., Garant, D., Sheldon, B. C. & Kruuk, L. E. B. 2010: The misuse of BLUP in ecology and evolution. Am. Nat. 175, 116—125. Helwig, M., Archer, Z. A., Heldmaier, G., Tups, A., Mercer, J. G. & Klingenspor, M. 2009: Photoperiodic regulation of satiety mediating neuropeptides in the brainstem of the seasonal Siberian hamster (Phodopus sungorus). J. Comp. Physiol. A. 195, 631—642. Herborn, K. A., Macleod, R., Miles, W. T. S., Schofield, A. N. B., Alexander, L. & Arnold, K. E. 2010: Personality in captivity reflects personality in the wild. Anim. Behav. 79, 835—843. Huntingford, F. A. 1976: The relationship between antipredator behavior and aggression among conspecifics
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