Animals, housing and treatments

All experiments were conducted at The Swedish Livestock Research Centre Lövsta (Swedish university of agricultural sciences, Uppsala, Sweden), June - July 2014. Female Bovans Robust chicks (n = 96), which are a laying breed of domesticated fowl, were collected at day 0 from a hatchery and transported in a ventilated car to the research facility. All chicks were kept in groups of 12 individuals in eight, 1.2 m2 pens. At arrival, chicks were divided into groups that were balanced according to their weight ensuring that all groups had similar composition of individuals. The chicks were raised without mothers to reduce potential maternal influences. All chicks had ad libitum access to commercial poultry food and water. To facilitate identification, chicks were initially individually marked with leg-rings, and at around 2 weeks with round, laminated paper tags (3 cm of diameter) in both wings. All tests (see Fig. 2 for schematic of the test procedure) were performed during the light hours of the day when birds are active, 9.00–18.00. Standard fluorescent lamps were used as light source during the tests. All observers were blind to treatments and results in the preceding tests.

Figure 2 Schematic of the test procedure. See main text for further details. Full size image

The chicks were assigned to 4 treatment groups in a two by two set up (separated into 8 pens, Figure S1). The pens where divided into two blocks of 4 pens in which treatments were semi-randomly distributed in the room (see Figure S1). Half of the chicks (four pens) were raised in more complex environmental conditions (‘complex environment’) whereas the other half (four pens) were raised in simpler environmental conditions (‘simple environment’). Pens that were categorised as complex had wood shavings, a round pellet feeder, a water bell and wooden blocks on the floor to encourage movement and exploration (see Figure S2). These pens had perches at different heights underneath a sheltering roof, as well as a secluded and protected area under a lower shelf with cloth strips hanging in front of the entrance. Chicks raised under simpler environmental conditions had wood shavings on the floor, a pellet feeder and a water bell, but the pen was otherwise lacking any additional interior or shelter (Figure S2).

Two days post-hatching, chicks from two randomly selected complex and two randomly selected simple pens were exposed to a substantial decrease in room temperature over a period of 6 hours (‘cold stressed’), while chicks from the remaining pens (two complex and two simple) were kept in optimal temperature (‘not cold stressed’). All chicks were placed in pairs in small compartments (20 W × 15 L × 15 H cm) in boxes (box size 40 W × 60 L × 15 H cm) and were left alone. For the cold stress treatment, the boxes were placed directly in a room where the temperature was 18–20 °C, whereas for the unstressed treatment groups the boxes were placed in a room at the optimal 33 °C. The first 10 days after hatching the thermoregulation in chicks is underdeveloped75, making them especially vulnerable to cold stress76. The temperature used as cold stress here was decided by pilot studies prior to the experiment. The average body temperature of the cold stressed chicks decreased by 2.9 °C whereas it only decreased by 0.8 °C for the unstressed chicks, supporting the effectiveness of this treatment as a stressor.

At 4 weeks of age, we exposed all chicks (both cold stressed and those not stressed) to a battery of stressors that were chosen to stimulate an unpredictable environment. Unpredictability and lack of control are major sources of stress that have been well described, especially in rodents (reviewed by77). Unpredictability has also been used as a stressor in chickens, causing learning difficulties78, long-term effects on behaviour79 and even epigenetic effects on behaviour in offspring of stressed parents79,80. Similarly, acute noise exposure above 80 dB increased corticosterone levels in broiler chickens already after 10 minutes81. The unpredictability included stressors that are common in husbandry practices such as novel water bells, extra feeders, cleaning of pens and higher levels of human entrance to the facility. In addition, these stressors were used: (i) heavy metal music playing at 90 dB during 1 hour, at different times of day, 5 days in a row, (ii) unpredictable noise at 90 dB in random intervals during the day (including sounds of predators and other animals, and mechanical noise such as trains, airplanes and ambulances), and (iii) lights going on and off unpredictably during both day and night the last three days of the stress treatment. From behavioural observations during this week it was found that feeding behaviour was almost eliminated during the hour that the heavy metal music was being played, supporting the effectiveness of this treatment as a stressor.

Judgement bias test

At 2 weeks of age, chicks were exposed to a judgement bias test. Chicks were collected from their home pen and brought to a test room in a small transport box. The temperature in the test room was kept at the same temperature as the home pen.

After initial pre-training where chicks were familiarised with the test arenas (plastic boxes covered with corrugated cardboard paper, measuring 46 W × 68 L × 42 H cm), rewards (mealworms) and handling45,82, chicks were singly trained to associate a colour cue (black or white, n white = 46, n black = 49) with a reward (1/3 of a mealworm). The colour cues were printed on photo paper and laminated. Colour signs (one black and one white, 9 × 9 cm) and similarly coloured bowls were placed on both sides of a small partition (Figure S3a). The reward was placed close to the front edge of the bowls to make sure that the chicks could not see the reward before making their choice. During training, chicks had to make an active choice between the two colour cues (black and white) that were presented to them (for further details see ref.45). Chicks were allowed to make an unrestricted amount of choices during each training session and were allowed three sessions that each lasted ca. 15 minutes and were at least 1 hour apart. Chicks needed to reach a criterion of 6 correct choices in a row, and to again reach this criterion on the following day before proceeding to the judgement bias test. In the judgement bias test we presented colour cues one by one to the chicks in the middle of the arena (the partition had been removed, see Figure S3b). In addition to the previously rewarded and unrewarded colour cues we introduced three ambiguous colour cues that were intermediate between the previously rewarded and unrewarded colour cues; dark grey: 25% white/75% black, medium grey: 50% white/50% black, and light grey: 75% white/25% black. Latency (sec) until the chick had approached the colour cue after being released was recorded as a behavioural measure of the chicks’ response to these ambiguous cues. A short latency to an ambiguous colour cue similar to that chick’s unrewarded colour cue would indicate an optimistic chick, whereas a long latency to an ambiguous colour cue similar to that chick’s rewarded colour would indicate a less optimistic chick (sensu e.g. refs3,7,26). During testing, the chick was placed in the arena with her head facing away from the colour cue to prevent the chick from making any decision before starting to move. A maximum latency of 30 seconds was allowed to approach the colour cue. If the chick did not approach the presented stimuli within this time, the trial was aborted and the next trial started. Similarly, if the chick jumped out of the arena, the trial was aborted and the chick received a max score of 30 seconds and the next trial started. The order of the colour cues was presented according to a pre-determined, semi-randomized schedule, where two of each intermediate grey colour cue were presented in-between eight rewarded and seven unrewarded cues. Therefore, any potential order effect should not systematically have affected any specific cue. To keep the chicks motivated throughout the test we continued to reward the colour that the chicks had been trained to associate with a reward, while all other colours were left unrewarded.

A second judgement bias test was performed when the chicks were 5 weeks old and after the chicks had been exposed to the battery of unpredictable stressors. To make sure that the association between colour cue and reward remained, we performed a new associate learning trial prior to the test. Again the chicks were required to have 6 correct choices in a row before proceeding to the judgement bias test. The judgement bias test was performed in a similar fashion as the first test, the only differences being that the arenas were larger during the second test (measuring 49 W × 99 L × 50 H cm) as the chicks had grown in size. Sixty-five chicks were tested in the second judgement bias test (9 chicks failed the associative learning task and 22 chicks died, most likely as a consequence of contaminated blood used in an immunological test, not part of this study) performed on the chicks after the first judgement bias test.

Multivariate behavioural assay

Birds were exposed to a multivariate behaviour assay at 2 and 5 week of age (i.e. before and after exposure to unpredictable stress, and before each judgement bias tests). The test was modified from a previously used test83. The arena was adjusted between the two test occasions to compensate for the increased size of the birds. In both trials the arena had a start box (40 W × 40 L × 40 H) that included a detour; a u-shaped route from the starting position leading to the larger arena (Figure S4a). The larger arena was a circular arena (first test: Ø 1.20 m, second test: Ø 1.60 m, Figure S4a,b) with a companion box (first test: Ø 0.30 m, second test: Ø 0.40 m, Figure S4a) out of wire mesh in the centre. The arena was built of aluminium plate with a wooden floor. Four cardboard screens (first test: 0.20 W × 0.20 H m, second test: 0.30 W × 0.30 H) were mounted inside the arena opposite to each other, creating a not fully closed circle measuring (first test: Ø 0.70 m, second test: Ø 0.80 m), aiming to encourage birds to be risk-taking and explore the arena. The arena was divided into 3 zones, which were not visible to the chicks, but that were used to observe their use of the arena. In the ‘Inner circle’ the chicks were close to their conspecifics, in the ‘Outer circle’ they were not in close proximity to conspecifics but could still see them, and in the ‘Behind screen’, they were not in close proximity to conspecifics and had no visual contact with them (Figure S4). A chick was considered to be in a particular zone when at least 50% of its body was located in the zone.

Chicks were calmly collected in groups of 4 directly from their home pen. All four chicks were placed in the companion box and left there for 3 min to habituate. Thereafter, one of the birds, the focal bird, was placed in the start box in the periphery of the arena (Figure S4a). If the chick did not leave the starting box within 7 minutes i.e. did not solve the detour, the barrier was removed and the test continued, discarding the detour part of the test. All focal chicks received 5 minutes to move freely in the area, time starting as soon as a chick entered the arena after the detour. Thus, all chicks received an equal amount of time to explore the arena despite differences in initial fear response or problem solving skills (i.e. despite differences in latency to move and latency to detour). Behaviours scored (in seconds) were; ‘latency to start moving’, ‘latency to find the entrance’ (i.e. latency to detour and cross the line of the detour barrier). We also video recorded ‘proportion of time spent in the ‘Inner circle’ and the ‘Outer circle’ as well as if they explored the ‘Behind screen’ or not (Figure S4b). Videos were decoded blindly by the same observer (IC). After a chick had completed the test, it was returned to the companion box and a new bird was tested.

Analyses of brain monoamines

Brains of birds that successfully finished the second judgement bias test (n = 65) were sampled at 7 weeks of age. The chicks were anesthetized by a hard hit to the head and euthanized by swift cervical decapitation (in accordance with the ethical permit approved for the study). Immediately following euthanasia, brains were removed and dissected into 7 parts84 on a metal tray chilled with dry ice. The left mesencephalon, telencephalon, hypothalamus-thalamus and optic tectum were snap frozen on dry ice within a few minutes from euthanasia (mean = 2.5 min, range = 1.42–5.25 min). The brain tissues were subsequently stored in −80 °C until they were analysed.

Frozen tissue samples were weighed before being homogenised in 1500 μl, 4% (w/v) ice-cold perchloric acid containing 100 ng/ml dihydroxybenzylamine (DHBA). DHBA was used as an internal control to correct for potential degradation. Homogenised and thawed samples were centrifuged at 15 000 rpm for 10 min at 4 °C. The supernatant was used for high performance liquid chromatography with electrochemical detection (HPLC-EC) as described in detail by85. Briefly, the HPLC-EC system consisted of a solvent delivery system model 582 (ESA, Bedford, MA, USA), an autoinjector Midas type 830 (Spark Holland, Emmen, the Netherlands), a reverse phase column (Reprosil-Pur C18-AQ 3 μm, 100 mm × 4 mm column, Dr. Maisch HPLC GmbH, Ammerbuch-Entringen, Germany) kept at 40 °C, and an ESA 5200 Coulochem II EC detector (ESA, Bedford, MA, USA) with two electrodes with reducing and oxidizing potentials of −40 mV and +320 mV. A protecting electrode with a potential of +450 mV was used before the analytical electrodes to oxidize any contaminants. The mobile phase had a flow of 1 ml/min and was prepared by adding 75 mM sodium phosphate, 1.4 mM sodium octyl sulphate and 10 mM EDTA, and around 7% acetonitrile to deionized water that was brought to pH 3.1 with phosphoric acid. Norepinephrine (NE), dopamine (DA), serotonin (5-HT), and the metabolite of dopamine; 3.4-dihydroxyphenylacetic acid (DOPAC) and the metabolite of serotonin; 5-hydroxyindoleacetic acid (5-HIAA), were analysed. The concentration of brain monoamines and metabolites were calculated from a reference curve made using standards. Concentrations were estimated as nanogram per gram brain tissue. The ratios of DOPAC/DA and 5-HIAA/5-HT were calculated and used as an index of dopaminergic and serotonergic activity, respectively.

Ethical note

In this study, we only use brains of individuals that reached our learning criteria for associative learning, and thus started with a relatively large number of birds, to ensure a sufficient sample size for our statistical analysis. Further motivating our relatively large number of animals used, all individuals were also part of an additional study. The experiment was conducted according to ethical requirements in Sweden, and approved by Uppsala Ethical committee (ethical permit number C70/14).

Statistical analyses

All statistical analyses and model selections were conducted in R version (3.2.3).

Analyses of variation in latencies obtained in judgement bias tests

The two first colour cues in our judgement bias test were the rewarded colour cue followed by the unrewarded colour cue. Data from these trials were not included in the statistical analysis since they were considered to be acclimatisation trials to the new test set-up.

To explore whether cold stress and environmental complexity affected latencies in the first judgement bias test, we performed Mann-Whitney U-tests for each colour cue. We adjusted for multiple comparisons using Bonferroni correction.

Because we observed no difference between the treatment groups in the first judgement bias test (see statistics above) we continued by exploring whether there was variation in the changed response between the fist and the second judgement bias test that was explained by our treatments or influenced by brain monoamines. The change in latency ‘changed latency’ was calculated as (latency to colour cues in test 1 – latency to colour cues in test 2, +30 to allow all values to be on a positive scale). This variable had a normal distribution and parametric tests were used. We constructed full linear mixed-effects models containing our predictor variables; environmental complexity (‘complex environment’ vs. ‘simple environment’); cold stress (‘cold stressed’ vs. ‘not stressed’); interaction between environmental complexity and cold stress; brain monoamines (‘NE’ for norepinephrine, ‘DA’ for dopamine, ‘DOPAC/DA’ for dopamine turnover rates, ‘5-HT’ for serotonin, and ‘5-HIAA/5-HT’ for serotonin turnover rates), in each brain area measured (‘Tel’ for telencephalon, ‘Ht’ for hypothalamus-thalamus, ‘Mes’ for mesencephalon, or ‘Ot’ for optic tectum), and ‘Cue’ to account for the inclusion of the 5 colour cues used in judgement bias tests. We used separate models containing treatment and one of the brain monoamines at the time, due to co-linearity of monoamines within brain areas. In all models, ‘pen’ and bird ‘ID’ were included as cross-random effects. In cases where the monoaminergic activity had a significant effect on the response in the judgement bias tests, we explored whether increased monoamine levels or increased metabolites explained the increased activity by performing Spearman rank correlations between the monoamine and behavioural response, and between the metabolite and the behavioural response.

Our general approach was to use classical statistics with p-values, however when there were many covariates we tried to minimise the number of models by using model selection. We used the R-package ‘MuMIn’ and the function ‘dredge’ to determine models which best explained variation in ‘changed latency’. To estimate the most parsimonious models we used Akaike’s Information Criterion (AICc), with the conventional cut-off point of delta 2 (ΔAICc <2 change from the best ranking model86,87), for models to be considered (all models within ΔAICc <2 are shown in the results section below). Models were ranked according to their AICc value (AIC values adjusted for small sample sizes) and weight (ω), where lower AICc values and higher ω suggest a better goodness of fit86. AICω was used to evaluate the relative support for the best models, and sum of AICω (ΣAICω) used to evaluate the relative support for the individual variables in the models. Sum of AICω were obtained for all models within cumulative weight 0.95. For comparison, we included ‘Null models’ containing only the random effects. If the null model was included in ΔAICc < 2, the model was interpreted as uninformative because it did not explain the variance of the data better than a null model. Random effects were estimated using intra class correlations from the R package ‘multilevel’ (Table S1).

Environmental condition explained changes in latencies toward the cues between the two judgement bias tests (see results above). To analyse whether this difference was due to changed latencies in the complex or simple condition and to see at what cue the difference was observed, we performed Wilcoxon Signed Rank Test on mean latencies for each individual for each cue and adjusted for multiple comparisons with Bonferroni correction. We used a non-parametric test because the raw latency data was not normally distributed.

Analyses of variables from the multivariate behavioural tests

Because the assumption of normality was not met for the behavioural variables attained from the multivariate behavioural assay, the effects of stress and environmental complexity were analysed using generalized mixed linear models. If models were over-dispersed, we included an observation-level random intercept to account for the extra variance in the residuals. Latency to start moving was subtracted from latency to solve the detour to obtain independent measures. In the first test, there was no variation between individuals in time spent in the different zones (i.e. all individuals were in the zone close to the pen mates), therefore only variables from the second test were analysed. Because times spent in the ‘Behind screen’ zone in test 2 was zero inflated, we analyzed it as a binomial model investigating if animals explored the area ‘Behind screen’ or not.

Analyses of brain monoamine levels

To explore the effect of cold stress and environmental complexity on levels of brain monoamines, we constructed linear mixed-effects models with each monoamine as response variables and with cold stress, environmental complexity, and their interaction, as predictors. If the interaction term was non-significant, we re-ran the model without the interaction term. We included ‘pen’ as a random effect. Because the variables had non-normal distributions, we chose suitable transformations using box-cox. This resulted in log (x) for Mes NE, Mes 5-HT Tel DOPAC/DA, OT DA, √ (x) for Mes DA, Mes 5-HIAA/5HT, Ot DOPAC/DA, -1(X) for Tel 5-HIAA/5-HT, Ht NE, Ht DA, Ht 5-HT, Ht 5-HIAA/5-HT, 1000000/(X) ^ 3 for Ht DOPAC/DA and Ot 5-HIAA/5-HT.