Parental provisioning behaviour plays a key role in linking personality
with reproductive success
Mutzel, A., Dingemanse, N.J., Araya-Ajoy, Y.G., Kempenaers, B.
Electronic Supplementary Material
Page
Contents1
Text S1.Effects of song and model number on male aggressiveness2
Text S2.Behavioural proxies for male aggressiveness2
Text S3.Automated recording of visits to the nest3
Text S4. Prior specifications for multivariate models3
Table S1.Effects of nest stage on male aggressiveness4
Table S2. Variance-covariance-correlation matrix for males 5
Table S3. Variance-covariance-correlation matrix for females6
Table S4.Sources of variation in exploratory behaviour and feeding rate 7
Table S5. Sample sizes for exploratory behaviour and feeding rate 7
Figure S1.Experimental setup of the cage used for the exploration assay8
Supplementary References9
Text S1.Effects of song and model number on male aggressiveness
Likelihood ratio tests (LRT) were performed to test for effects of song and model number on male aggressiveness using the restricted maximum likelihood method (REML). The test was constructed by comparing a linear mixed-effect model with a Gaussian error structure containing nest stage and year as fixed effect and random intercepts for song and model number (‘model 1’) with similar models where song number (‘model 2’),or model number (‘model 3’), were respectively excluded. The LRT did not reveal a significantly better fit of model 1 compared to model 2 (AICmodel 1= 356.2, log Lmodel 1= -170.1; AICmodel 2= 354.2, log Lmodel 2= -170.1, LRT= 0, P=1) and model 1 compared to model 3 (AICmodel 3= 354.2, log Lmodel 3= -170.1, LRT= 0, P=1). We also ran this analysis using Bayesian methods (with similar model structure but using the MCMCglmm function in R) [1], confirming that both song and model number had variance estimate that were close to zero (variance explained by song number: 3.55×10-4 %, 95% CI: 2.32×10-5,0.08; variance explained by model number: 1.43×10-3 %, 95% CI: 2.33×10-5,0.20). Altogether these analyses imply that there was little to no variance explained by song or model identity.
Text S2.Behavioural proxies for male aggressiveness
We recorded the following behavioural variables as proxies for male aggressiveness: latency to approach the model within a 5 m radius (in sec), attack probability (a bivariate variable indicating whether a male attacked the model), and latency to attack (in sec). We assumed that the latency and the probability of attack were both good predictors of male aggressiveness in the context of territory defence [e.g. 2]. However, analysis based on attack latency would have led to the exclusion of all subjects with missing values (i.e. non-attacking, non-aggressive birds; 55 out of 112 tested males) resulting in a highly biased dataset, whereas the bivariate variable attack probability would not capture the total variation in aggressiveness of the population(see Dingemanse and coworkers [3]for asimilar discussion on the usage of latency variables). We therefore focused on approach latency for the analyses presented in the main text; a continuous variable comprising all birds that entered the 5 m radius around the intruder (80 out of 112 tested males). Amixed-effect modelwith attack probability as the dependent variable,approach latency, nest stage as predictors, with individual identity as random intercepts, and a binary error structure, showed that males that entered the 5 m radius more quickly, were significantly more likely to attack the conspecific intruder (estimate: 0.27±0.10, p=0.008). This finding suggeststhat approach latency wasindeed a good predictor of male aggressiveness towards a conspecific territorial intruder.
Text S3.Automated recording of visits to the nest
Our recording device consisted of an antenna (‘PIT-tag reader’)fitted around the entrance hole of the nest box, a light barrier inside and anotherlight barrier outside the nestbox hole, a power supply and a data logger placed on the ground underneath the nestbox. The sequence of activation of the two light barriers indicated the direction of the movement of a bird, allowing differentiation of entries and exits. Every time the bird passed through the nestbox hole the PIT tag was read, thus determining the identity of the bird entering or leaving the nestbox[4].
Text S4. Prior specifications for multivariate models
For each analysis, we used 5.3 x 106 iterations with a burn-in phase of 300 000 and a thinning interval of 5000, resulting in a sample of 1000 values for each estimate. We ran each model with 4 different priors: (i) inverse Wishart (V=diag(n), nu=n), (ii) inverse Gamma (V=diag(n), nu=b.002), where b = n-1, (iii) flat covariances (V=diag(n)*10-6, nu=c), where c = n+1, and (iv) parameter expanded (V=diag(n), nu=c). Using different priors resulted only in minor changes in the model output, strongly suggesting that the presented results are not influenced by our prior choice. The results presented in this paper are from models with an inverse-Wishart prior.
Table S1. Fixed effects estimates derived from a univariate mixed-effect modelwhere male aggressiveness was fitted as the response variable. We implemented the model using maximum likelihood (ML) with a Gaussian error structure, where nest stage (4 levels: empty box, nest building, egg laying and incubation) and year were fitted as categorical fixed effects, and random intercepts were fitted for individual identity. The intercept gives the estimate of the mean aggression score forreference category nest stage ‘empty box’ in the year 2009. 95% confidence intervals (CI) were calculated with the sim-function of the R package ‘arm’. To test for an overall effect of nest stage on male aggressiveness wecompared the full model (‘model 1’) with a similar model but without nest stage as fixed effect (‘model 2’). Model 1 fitted the data much better than model 2 as indicated by the lower AIC value of model 1 (AICmodel 1= 388.5, AICmodel 2= 399.7). These results imply that nest stage explained variation in male aggressiveness, with males being the most aggressive before the onset of nest building (when competing for territories) and least aggressive during the incubation period.
β / 95% CIintercept / -5.67 / -0.72, -0.94
nest building / -2.32 / -3.86, -0.84
egg laying / -0.35 / -2.19, 1.48
incubation / -5.24 / -7.80, -2.36
year 2011 / -3.06 / -4.12, -1.97
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Table S2. Correlations, covariances and variances between behaviours and fitness estimates formale blue tits. We give the point estimate plus 95% credible intervals between brackets for each variance component. Variances are given on the diagonal (shaded in dark grey), covariances on the loweroff-diagonals (shaded in light grey),and correlations on the upper off-diagonals (no shading). Correlations and covariances with non-overlapping credible intervals (implying significant covariance) are given in bold face.
♂ aggression / ♂ exploration / ♂ feed rate / ♀ feed rate / lay date / brood size / fledglingno. / fledgling mass
♂ aggression / 6.69
(5.13, 11.23) / 0.27
(0.01, 0.54) / -0.39
(-0.64, -0.06) / 0.24
(-0.08, 0.53) / 0.09
(-0.15, 0.46) / 0.02
(-0.34, 0.26) / 0.06
(-0.28, 0.27) / -0.20
(-0.37, 0.14)
♂ exploration / 20.90
(-3.76, 68.81) / 1967.71
(1229.78,2602.70) / 0.11
(-0.27, 0.36) / 0.19
(-0.20, 0.39) / -0.12
(-0.44, 0.17) / 0.06
(-0.18, 0.35) / 0.09
(-0.08, 0.40) / -0.08
(-0.33, 0.16)
♂ feed rate / -10.65
(-26.07, -1.77) / 27.88
(-128.68, 224.79) / 139.19
(86.89, 218.03) / -0.28
(-0.63, -0.09) / -0.39
(-0.64, -0.07) / 0.40
(0.19, 0.63) / 0.27
(-0.08, 0.50) / -0.30
(-0.58, -0.03)
♀ feed rate / 6.25
(-3.74, 16.79) / 21.81
( -89.61, 208.00) / -40.87
(-94.78, -0.89) / 98.77
(67.71, 167.63) / -0.25
(-0.53, 0.10) / 0.44
(0.12, 0.59) / 0.59
(0.40, 0.75) / 0.12
(-0.38, 0.24)
lay date / 1.88
(-3.04, 7.00) / -29.69
(-116.01, 38.14) / -22.42
(-50.40, -1.97) / -13.74
(-33.20, 8.38) / 26.74
(20.44, 39.88) / -0.52
(-0.64, -0.25) / -0.41
(-0.59,-0.18) / 0.18
(-0.09, 0.37)
brood size / 0.14
(-2.20, 2.01) / 11.49
(-20.39, 35.92) / 13.26
(3.57, 20.60) / 8.64
(2.20, 16.29) / -5.36
(-9.88, -2.34) / 5.59
(3.95, 7.92) / 0.76
(0.61, 0.83) / -0.55
(-0.70, -0.36)
fledgling no. / -0.29
(-2.20, 1.93) / 9.64
(-10.56, 45.58) / 7.50
(-2.65, 16.68) / 14.75
(7.72, 25.33) / -5.36
(-9.21, -1.96) / 4.04
(2.60, 6.32) / 6.92
(4.46, 8.74) / -0.14
(-0.38, 0.16)
fledgling mass / -0.48
(-1.28, 0.48) / -2.91
(-16.65, 8.42) / -3.75
(-8.80, 0.59) / -1.62
(-4.63, 3.26) / 1.13
(-0.48, 2.58) / -1.32
(-2.25, -0.78) / -0.40
(-1.11, 0.50) / 1.06
(0.82, 1.80)
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Table S3.Correlations, covariances and variances between behaviours and fitness estimates forfemale blue tits. We give the point estimate plus 95% credible intervals between brackets for each variance component. Variances are given on the diagonal (shaded in dark grey), covariances on the lower off-diagonals (shaded in light grey), and correlations on the upper off-diagonals (no shading). Correlations and covariances with non-overlapping credible intervals (implying significant covariance) are given in bold face.
♀ exploration / ♀ feed rate / ♂ feed rate / lay date / brood size / fledgling no. / fledgling mass♀ exploration / 1740.28
(977.98, 2489.73) / 0.41
(0.11, 0.70) / -0.28
(-0.57, 0.05) / -0.38
(-0.62, 0.02) / 0.10
(-0.18, 0.33) / 0.18
(-0.13, 0.35) / 0.02
(-0.25, 0.27)
♀ feed rate / 152.89
(21.05, 353.86) / 102.94
(71.04, 168.47) / -0.31
(-0.58, -0.06) / -0.15
(-0.50, 0.12) / 0.36
(0.06, 0.56) / 0.58
(0.33, 0.74) / 0.11
(-0.33, 0.33)
♂ feed rate / -142.96
(-318.17, 57.98) / -38.89
(-95.04, -6.27) / 156.25
(95.17, 234.76) / -0.51
(-0.68, -0.13) / 0.44
(0.29, 0.69) / 0.31
(0.04, 0.57) / -0.43
(-0.61, -0.03)
lay date / -74.20
(-165.37, 11.88) / -8.66
(-30.84, 10.50) / -28.44
(-53.07, -2.54) / 27.19
(21.60, 41.52) / -0.50
(-0.69, -0.34) / -0.45
(-0.61, -0.24) / 0.18
(-0.06, 0.41)
brood size / 8.16
(-20.05, 35.43) / 8.95
(0.67, 16.13) / 11.75
(5.73, 24.66) / -6.19
(-10.98, -3.51) / 5.79
(3.91, 8.13) / 0.77
(0.65, 0.85) / -0.47
(-0.65, -0.29)
fledgling no. / 17.23
(-12.49, 45.13) / 14.08
(7.35, 25.25) / 8.79
(-0.78, 19.50) / -6.22
(-10.27, -2.49) / 4.55
(3.08, 6.94) / 6.65
(4.70, 9.44) / 0.01
(-0.29, 0.24)
fledgling mass / 1.75
(-13.74, 14.30) / 0.44
(-3.92, 5.57) / -5.55
(-10.63, 0.06) / 1.12
(-0.59, 2.81) / -1.41
(-2.27, -0.64) / 0.03
(-0.96, 0.83) / 1.32
(0.93, 2.20)
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Table S4. Sources of variation in exploratory behaviour and feeding rate based on repeated exploration tests in 2009 and 2011 and repeated measures of feeding rates in 2011. We used univariate mixed-effect models (MCMCglmm) with a Gaussian errors structure with random intercepts fitted for individual. For the model on exploratory behaviour we further fitted sex, test sequence (1st vs. 2nd)[see 5]and year (only when measures for 2009 and 2011 were included) as fixed effects, whereas for the feeding rate model only sex was included. We give estimates of adjusted repeatability, i.e. the proportion of ‘phenotypic variance not explained by fixed effects’ explained by differences between individuals [6]. Values are reported with 95% credible intervals (CI).
Exploratory behaviour (both years combined) / Exploratory behaviour (2011 alone) / Feeding rate(2011 alone)
Fixed effects / β (95%CI) / β (95%CI) / β (95%CI)
intercept / 96.85 (88.24, 105.02) / 114.15 (105.31, 123.02) / 21.02 (18.04, 24.06)
sex / 1.89 (-7.77, 12.57) / -5.31 (-19.06, 7.34) / -2.00 (-6.25, 2.00)
sequence / 30.30 (20.63, 39.55) / 30.45 (15.71, 44.54) / -
year / 15.62 (7.13, 24.53) / - / -
Repeatability / r (95% CI) / r (95% CI) / r (95% CI)
0.66 (0.44,0.76) / 0.60 (0.13,0.79) / 0.78 (0.64,0.83)
Table S5. Sample sizes for exploratory behaviour and feeding rates for 2009 and 2011. Time intervals between repeated measures of exploratory behaviour ranged between 13-69 days within year and between 297-402 days between years. The time interval between repeated measures of feeding rate was 4 days.
Exploratory behaviour / Feeding rate2009 / 2011 / combined / 2011
N individuals / 108 / 128 / 236 / 96
N total / 132 / 152 / 284 / 192
Figure S1.Experimental setup of the cage used for the exploration assay. The cage consisted of a solid plastic box with one mesh side (122L x 50W x 50H cm, Joko-Systemtechnik) and was fitted with 6 wooden perches covered with plastic ivy to increase habitat complexity. For video analysis both the mesh side and the ground were divided into 4 sections, resulting in a total of 14 different potential positions (including the 6 perches). A sliding door on the right wall connected a small holding box (11L x 12W x 11H cm) with the experimental chamber. The right side of the holding box was closed with a transparent sliding door, which was covered by a piece of cloth. The bird was transferred to the dark holding box right after capture and was allowed to recover from handling stress for two minutes. The subject was then released in the experimental chamber by opening the left sliding door and at the same time moving the piece of cloth[see Ref. 3]. This movement induced all birds to promptly enter the experimental chamber without any further handling.
Supplementary References
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2. Garamszegi L.Z., Rosivall B., Hegyi G., Szollosi E., Torok J., Eens M. 2006 Determinants of male territorial behavior in a Hungarian collared flycatcher population: plumage traits of residents and challengers. Behav Ecol Sociobiol60(5), 663-671.
3. Dingemanse N.J., Both C., Drent P.J., Van Oers K., Van Noordwijk A.J. 2002 Repeatability and heritability of exploratory behaviour in great tits from the wild. Anim Behav64, 929-938.
4. Mutzel A., Blom M., Spagopoulou F., Wright J., Dingemanse N.J., Kempenaers B. In Press. Temporal trade-offs between nestling provisioning and defence against nest predators in blue tits. Anim Behav.
5. Dingemanse N.J., Bouwman K.M., van de Pol M., van Overveld T., Patrick S.C., Matthysen E., Quinn J.L. 2012 Variation in personality and behavioural plasticity across four populations of the great tit Parus major. J Anim Ecol81(1), 116-126. (DOI 10.1111/j.1365-2656.2011.01877.x).
6. Nakagawa S., Schielzeth H. 2010 Repeatability for Gaussian and non-Gaussian data: a practical guide for biologists. Biol Rev85(4), 935-956.
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