Philippa Kaur

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Experimental designOver 3 years, six paired organic British Blacktail flocks with intact beaks (i.e. not beak-trimmed) were visited between 1 and 40 weeks of age. Within each pair, one flock was ramp reared (RR) and one flock was control reared without ramps (CR). All flocks were kept on one farm which possessed two rearing houses and six laying sheds of approximately 2000 birds per flock. The site was multi-age, meaning that of the six laying sheds there were three different ages on the site at one time.The availability of this commercial facility enabled us to design an experiment whereby we allocated two rearing treatments, one with ramps provided to access elevated structures and a control with elevated structures but no ramps and to alternate these treatments between the two rearing houses available to avoid treatment x house confounds. Each rearing flock was moved independently to a laying house with no mixing, so we were able to continue data collection and examine any long-term effects of the rearing treatment during the laying period. Rearing flocks were systematically allocated so that each laying house received one RR flock and one CR flock during the experiment.Observations were made in the mornings at three time points during the rearing period at 1, 3 and 15–16 weeks, and three in the laying period at 16–17, 24 and 40 weeks of age. See Table 5 for a summary of experimental design, flock and housing information.Table 5 Experimental design for each ramp reared and control reared flock for the 6 replicates. There were two rearing sheds used, Rear1 (R1) and Rear2 (R2), with 6 different laying sheds named A1, A2, B1, B2, C1 and C2.Full size tableThe rearing sheds were static with 142.7 m2 of floor space covered with wood shavings. Rearing sheds were both set up with feed tracks giving mini pellet feed up to 11 weeks of age then pellet grower feed and 7 nipple drinker lines. The lighting schedule was 23 h light in the first day reducing gradually over the rearing period to 10 h light at 7 weeks of age. A minimum light intensity of 10 lx is required, but with windows and pop-holes light intensity was higher in the houses. The temperature was maintained at 30 °C during the first few days then slowly reduced to match the temperature in the laying sheds. Shed heating was provided by gas spot lamps, whole shed heating through hot pipes running along the length of the shed and hot air fans run by a biomass boiler. All flocks had access to the outside range by 10 weeks of age through two pop holes (each L: 2 m by H: 0.4 m). Flocks were moved the short distance from the rearing to the laying house at between 15 to 16 weeks of age in one night using transport modules.All rearing flocks had access to six elevated structures (ES) (see Fig. 3) from four days of age when the chicks were released from the brooding circles. Each ES comprised nine metal perches (length 302 cm, width 3.5 cm), with three perches (25 cm apart) at three different heights (43 cm, 73 cm and 103 cm). Two plastic grids (width 60 cm, length 115 cm) were fixed within the ES to provide platforms at different heights (Fig. 3). In each replicate, the RR flock had one ramp attached to each ES. Three of the ES were fitted with plastic grid ramps (width 60 cm, length 74 cm, angle 35.5°) leading up to the low perch and three ES had ramps (width 60 cm, length 115 cm, angle 40°) leading up to the middle perch. The CR flock had six ES without ramps.Figure 3Elevated structure dimensions used in the ramp reared sheds, (a) shows the high ramp (b) shows the low ramp. The control sheds elevated structures were identical to these but without ramps.Full size imageThe six single-tier laying houses on-site were mobile organic units with approximately 345m2 of floor space. See Fig. 4 for a schematic plan of their layout. All had a raised area comprising plastic slats over supports (approx. 70 cm from the litter) and a ground-level litter area covered with wood chip. Four of the sheds (Fig. 4a) were set up with the slatted area spanning the whole width of the shed and halfway down the length. In two of the sheds (Fig. 4b) the litter area was either side of the elevated slatted area. Nest boxes ran down the centre of the slatted area, dividing this into two sections. Intermittent ramps were installed at the level change, resulting in 4 m of ramp access and 4 m without ramps in the shed with litter at the end and 8 m of ramp access and 13 m without ramps in the shed with litter at the sides. In sheds A1 and A2 the height of the slatted area resulted in a steeper ramp angle of 45° compared to 30° in the other sheds. There were four pop holes at ground level with two on each side of the house (L: 2.35 m by H: 0.4 m) leading to the range from the litter area on both sides of the sheds. All sheds had aerial perches at 1 m high with 18 cm of perching space per bird resulting in approximately 360 m of perch length running the length of the slatted area. Feed tracks and drinker lines matched those in the rearing sheds. The lighting schedule was 16 h of light and varied between summer and winter with the lights set to turn off at the same time as natural dusk. The birds were fed on organic mini pellets throughout lay. Enrichment was provided to the flocks in the form of pecking objects such as buckets and boots. Replicates 5 and 6 were provided with pecking blocks and alfalfa hay nets hung on the litter area.Figure 4Plan view of the laying house layout (a) for replicates 1, 2, 4 and 5 and (b) for replicates 3 and 6. Images not to scale.Full size imageAssessments of behaviourObservations were made at three time points during the rearing period at 1, 3 and 15–16 weeks. On the first visit at 1 week of age, the total number of chicks on each ES was counted once in spot counts in the morning. At 3 and 15–16 weeks, observations of the movements up and down the ES were made. Three of the 6 structures were chosen at random in each shed. The number of chicks present on the different parts of the ES was counted at the beginning and end of the recording period to allow a comparison with the 1-week counts. The recordings involved 5-min continuous sampling where all movements down the ES were recorded and the area the chicks moved down from was noted. This was then repeated for movements up the ES. Focal bird recordings were taken at 3 and 15–16 weeks of age. Records were made for each of 3 randomly selected ES. When 10 focal birds had been observed (approximately 30 birds per flock), or 10 min had passed recordings stopped. A focal bird was chosen if it was performing orientation behaviour, indicating a downwards or upwards transition. This was described as the bird rotating its head to look in the direction of movement. Behaviours performed after the orientation behaviour were tallied, thus recorded as counts per behaviour (see Table 6). Recordings were stopped if birds completed a transition or moved away from transitioning.Table 6 An ethogram of behaviours of focal birds during up and down movements.Full size tableAt 15–16 weeks of age, three types of interactions were recorded for feather pecking. These included severe feather pecking (SFP), gentle feather pecking (GFP) and aggressive pecks (AP)28. A quadrat area 2 m by 2 m was randomly selected, with the number of birds in each quadrat counted at the beginning and end of the recording period. The number of SFP, GFP and AP were recorded over three minutes of continuous recordings in three different areas of the house, selected randomly at each end and the middle of the shed. Feather pecks and aggressive pecks were recorded as bouts: a series of pecks not separated by more than 5 s28. Rates of pecking were calculated as the number of pecks per bird per second.In the laying shed around 16–17 and at 24 weeks of age 3-min continuous sampling and focal bird recordings were taken for transitions between the slats and litter. Four recordings were made at 2-m lengths along the elevated slatted area: two areas with ramps (RA) and two areas without ramps (NRA) were selected. Separate recordings were taken for upwards and downwards movements and the number of birds in the recording area were counted at the start and end of the scans. At 16–17 and 24 weeks of age, feather pecking observations were taken using the same procedure as for the 15–16-week observations during rear.Welfare assessments and production data rearing phaseFeather scores of 20 birds per flock were recorded at 16–17 weeks of age by walking in a straight line down the centre of the shed, selecting a bird at random then counting two birds to the left of this and visually feather scoring that bird. Birds were not handled to minimise disturbance and plumage was scored using the method from Bright et al.33. The neck, back, rump, tail and wings were scored using a four-point scale 0 (best) to 4 (worst). Data were obtained from the farm records for percentage cumulative mortality and body weight.Welfare assessments and production data laying phaseAt 16–17 and 24 weeks of age, the attitude of the flocks was assessed using the approach distance and reactions to novel objects methodology developed by Whay et al.34. Distance to approach birds before they moved away was recorded by walking through the house selecting a bird at random and counting two birds to the left. The bird had to be standing up and facing the researcher, who approached the bird at a steady pace and recorded the distance before the bird moved away. This was repeated on 20 birds in each flock. Reactions to a novel object (blue folder at 17 weeks of age and a white and blue tub at 24 weeks of age) were assessed by placing a novel object on the ground and recording the time taken for the first bird to interact with it and then how many birds were within a 30 cm radius after 60 s. The novel object test was repeated in 4 areas per flock. Range use was recorded by counting the number of birds near to the house (5 m) in the middle range (5–20 m) and far (the rest of the range). Feather scores of 20 birds per flock were recorded at 17 and 24 weeks of age using the same procedure as for the 16-week assessment for birds at rear.At 40 weeks of age, feather cover and keel bone fractures were scored. Up to 100 birds per shed were caught from four different locations (25 litter, 25 slats, 25 perches, 25 nest boxes). In four sheds only 50 birds were caught as the birds were fearful and showed signs of distress. Feather cover was scored by picking the bird up and scoring the body and flight feathers separately using a the AssureWel three-point scale 0 (best) to 2 (worst)35. The keel damage was then scored using a 0 (no damage) to 2 scale based on the technique used by Wilkins et al.36. Validation for keel bone palpations was conducted. A score of 94% matched scores compared to an experienced gold standard assessor and 85% match at dissection for scoring a break. At 24 weeks of age, the number of floor eggs were counted over 1 day.Data were collected from the farm records on laying house percentage of daily eggs, average egg weight (grams), average hen body weight and feed conversion ratio.During the 16 week recordings in the final rearing flocks, the lighting inside the shed was considerably reduced compared to previous flocks. This resulted in poor visibility for feather cover and feather pecking observations, so these were not taken during this visit. Data were not obtained on keel fractures and feather cover scores at 40 weeks for the first laying flocks visited as their sheds were destroyed by strong winds.Statistical analysisData were analysed using SPSS 24 (IMB) or MLwiN 3.0. The statistical package MLwiN was chosen as it is designed for multilevel modelling and can therefore accommodate data nested within levels with repeated measures. Such models account for dependence between responses caused by grouping of birds within sheds, and repeated measures taken from the same sheds on different visits within and between replicates. Including visit and replicate as nested effects ensures that dependences (e.g. due to differing times of year when data were collected) are accounted for. All residuals were checked for normal distributions using a Shapiro-Wilks test or plotted graphically and no transformations were needed to meet the assumptions of the tests. All results are reported in the format mean ± SD unless when stated as the percentage of birds performing a behaviour during transitions.Assessments of behaviourAt rear, from the counts of chicks on structures and counts of transitions up and down the structures, a normal model (generalised linear model) was used with a four-level hierarchy (bird within shed within visit within replicate). The same normal model and four level hierarchy were used for the counts of transitions in the laying shed.For the focal bird behaviours of birds transitioning at rear and lay, the data were presented as the percentage of each behaviour calculated for the birds in the recording session for the two rearing treatments. The direction (up or down) was analysed separately. For the focal birds at lay, all were included in the analysis for the pre-transitioning behaviours, only birds that attempted a transition were included for analysis of the transitioning behaviours. Pre-transition behaviours for birds that moved-away and did not transition were analysed separately. Owing to the low occurrence of behaviours during the focal recordings for transitions up and down the ramps, data were coded as yes or no, and a Binomial model was used for analysis for both the rear and lay focal transition data with four hierarchical levels (bird within shed within visit within replicate).Welfare and production dataFor the Novel object test, human approach, feather pecking and feather cover data a normal model was used in MLwiN with four-levels (Bird within Shed within visit within replicate). Floor eggs were analysed using a two-tailed t-test in SPSS, due to limited data. Ordinal data such a keel bone fracture scores and feather cover recorded at 40 weeks of age were converted to binomial data due to a lack of data for some scores, these were therefore analysed using a binomial model in MLwiN with two levels (Bird within shed).Production data at rear (body weight in grams) and lay (% eggs daily, egg weight in grams, body weight in grams and feed conversion ratio) were obtained from farm records and analysed in SPSS using a general linear model with treatment (CR and RR) as a fixed factor and age (3, 8 and 14 weeks at rear and 20, 30 and 70 weeks at lay) as a random factor to account for repeated results. Cumulative percentage mortality was analysed at 14 weeks of age using a t-test to compare the treatment groups.Ethical approvalEthical approval for this project was granted by the University of Bristol’s Animal Welfare and Ethical review body under UIN: UB/16/040 and all methods were conducted in accordance with the review body and UK legislation. 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Song description: terminologySong organisationBlue whale vocal sequences are traditionally referred to as ‘calls’19,20,21, however, as they meet the criterion of ‘song’ as used in the bioacoustic community22, in this study we use the term ‘song’ to refer to regularly-repeated whale vocalisations. The song is repeated in a sequence with regular intervals, defined as the Inter-Call Interval (ICI), measured as the time interval between the beginning of the one song and the beginning of the following song. Note that although we use the term ‘song’, we chose to keep the definition ‘ICI’ as this nomenclature is used traditionally in the whale literature, rather than ‘ISI’, which usually designates Inter-Series (or Sequence) Interval. Songs are composed of units and we used the term ‘unit’ to designate parts of the song that are separated by a silence (see reviewed criteria in23). Units were divided into subunits: subunits are defined as such when there is a sudden change in the sound structure for instance becoming harmonic or noisy.Sound typesA sound can be of different types: (1) the simpler one is the simple tone, which is either pure, with the same frequency all along, or showing frequency and/or amplitude modulations; (2) harmonic sounds are sounds with multiple tones at frequencies that are integer multiples of the frequency of the original wave, called the fundamental frequency ((F_{0})). When one of the harmonics has a greater amplitude than the others, it is called ‘resonance frequency’; (3) pulsed sounds are, as defined in24, the repetition of similar “pulses” or short signals with a constant pulse rate, often aurally perceived by humans as amplitude modulated sounds. On spectrogram representation, using a long analysis time window, these sounds are characterized by sidebands with regular spacing. The frequency difference ((Delta f)) between each sideband is the pulse rate of the sound. In their recent study, Patris et al. made the difference between what they defined as ‘tonal pulsed sounds’ and ‘non-tonal pulsed sounds’24. Following their criterium, the sidebands of the tonal pulsed sounds show a harmonic relationship, meaning that the frequency of each sideband divided by the pulsed rate is a positive integer. If it is not the case, then the sound is a non-tonal pulsed sound.Nonlinear phenomenaNonlinear phenomena are observed in a variety of birds25, anurans26 and mammals27,28, including marine mammals (e.g., manatee29) and more particularly cetaceans (right whales30,31, killer whales30,32 and humpback whales33). They have been well described by a variety of authors27,34 and include: (1) frequency jumps, that are characterized by sudden (F_{0}) changes which moves up or down abruptly and discontinuously, and is different from continuous, smooth modulation27; (2) subharmonics, that are additional spectral components and can suddenly appear at integer fractional values of an identifiable (F_{0}) (e.g., (F_{0}/2), (F_{0}/3, ldots)) and as harmonics of these values. On a spectrogram, it results as bands of energy evenly spaced below (F_{0}) and between its harmonics throughout the spectrum; (3) biphonation, that is the simultaneous occurrence of two independent fundamental frequencies (F_{0}) and (G_{0}). Biphonation can be visible on a spectrogram as two distinct frequency contours35. Alternatively, if one source ((F_{0})) vibrates at a much lower frequency than the other ((G_{0})), biphonation will appear as visible sidebands at linear combinations of (F_{0}) and (G_{0}) (m(G_{0}) ± n(F_{0}), where m and n are integers), because the airflow is then modulated by the frequency difference. This is equivalent to considering that the lower (F_{0}) amplitude-modulates the higher frequency (G_{0}) (carrier frequency)28; (4) finally, deterministic chaos are broadband, noise-like segments. These episodes of non-random noise appear via abrupt transitions and can also contain some periodic energy, which appears as banding in a spectrogram. In extreme cases there are no repeating periods at all27,34.Analysis of the Chagos song and comparison with the Indian Ocean pygmy blue whale song types and Omura’s whale song typesChagos songThe Chagos song was composed of 3 units (Fig. 3). The 3-unit song was repeated in stereotyped series with an ICI of (190.79 pm 1.49) s (Fig. 7b).The first unit of the Chagos song is divided into 3 subunits (Fig. 3): in 2017, subunit 1 was pulsed with a rate (Delta f_{u1su1}) = 3.22 ± 0.01 Hz. Using Patris et al. ’s criterion24, we concluded that this subunit is a non-tonal pulsed sound, since the sidebands do not have a harmonic relationship. The carrier frequency (where the peak of energy lies) was 35.74 ± 0.02 Hz for 73% of the measured songs, 32.47 ± 0.05 Hz for 23% of the songs and 38.9 ± 0.06 Hz for 3% of the measured songs. One song had a carrier frequency of 29.18 Hz. This subunit 1 lasted 3.02 ± 0.03 s in duration. Subunit 2 was often less obvious (likely due to propagation effects, lower source level or possibly to deterministic chaos) so that it could not be measured for all of the songs sampled; it is also a short (1.53 ± 0.05 s) non-tonal pulsed unit with a pulse rate ((Delta f_{u1su2})) of approximately 3 Hz and a slightly different carrier frequency, induced by a frequency jump. The carrier frequency was of 36.02 ± 0.03 Hz for 87% of the measurements, 39.16 ± 0.05 Hz for 8% of the measured songs and 32.97 ± 0.1 Hz for 5%. Finally, subunit 3 was a tonal unit showing a frequency modulation. The subunit started at 29.55 ± 0.02 Hz down to 29.35 ± 0.02 Hz over approximately 3.5 s, then down to 28.10 ± 0.09 Hz as a decrease to 27.62 ± 0.04 Hz over 3 s. The total duration of this subunit was 6.40 ± 0.07 s, and the total duration of the unit 1 was 11.36 ± 0.08 s.Unit 2 was a pure tone following after a silence of 3.06 ± 0.1 s. Its peak frequency was 22.34 ± 0.05 Hz and its duration was 3.24 ± 0.07 s. Finally, unit 3, also a pure tone, followed after a silence of 14.38 ± 0.23 s. It had a peak frequency of 17.44 ± 0.05 Hz and lasted 2.94 ± 0.15 s. The third unit was sometimes absent. This could be due to a variation in the song or due to propagation losses. When unit 3 was present, the total song duration was 34.38 ± 0.4 s.The frequency for the beginning of the third subunit of the unit 1 of the Chagos song (point 1 in Fig. 3a) decreased by approximatively 0.33 Hz/year across years (Fig. 4).This phenomenon will be examined in details in a further study.Figure 3Spectrogram (a) and waveforms (b) of a Chagos song recorded on the eastern side of the Chagos Archipelago (DGS) in August 2017. Detailed waveforms show the signal structure of the units within the song. Spectrogram parameters: Hamming window, 1024-point FFT length, 90% overlap. Note that the axes differ among plots. (c) Measurements (mean ± standard error (s.e.)) of the acoustic features. N is the number of measurements, (u_{i}su_{j}) stands for (unit_{i} subunit_{j}) where i and j are the unit and subunit numbers, (Delta f) designates the frequency difference between the sidebands, f and d are the frequency and duration of the feature indicated in subscript, and when present, the number in brackets refers to the point measured as indicated on the spectrogram. (F_{x}) or (G_{x}) designate the xth harmonic of a sound, and Cf designates the carrier frequency of a sound.Full size imageFigure 4The decline in frequency of the Chagos song from 2002 to 2017: spectrogram representation of five songs recorded at Diego Garcia in years 2002, 2005, 2012, 2015 and 2017. Spectrogram parameters: Hamming window, 1024-point FFT length, 90% overlap.Full size imageIndian Ocean pygmy blue whale songsThis section describes the structural, temporal and frequency features of the pygmy blue whale song-types commonly reported in the Indian Ocean. Note that as the frequency of at least parts of these songs are known to vary within and across years36,37,38,39,40,41, the frequency values obtained here are only valid for the years sampled.Madagascan pygmy blue whale The Madagascan pygmy blue whale song had 2 units (Fig. 5a). Unit 1 was divided into 2 subunits. In 2004, subunit 1 was a noisy pulsed sound, characteristic of deterministic chaos, with a pulse rate (Delta f_ {u1su1}) = 1.44 ± 0.01 Hz and of 4.76 ± 0.005 s duration. Subunit 2 was a tonal sound with harmonics. Its (F_ {0}), estimated as the mean frequency difference between the harmonics, was 7.04 ± 0.005 Hz. The maximum energy was in the (F_ {5}) (resonance frequency), which commenced at 35.31 ± 0.02 Hz and remained stable over 10.65 ± 0.13 s ((F_{5_{u1su2}}) in Fig. 5a). The frequency then remained stable over another 3.00 ± 0.16 s or in some songs increased to 35.91 ± 0.05 Hz [range = 34.84–37.05 Hz]. The total duration of subunit 2 was 13.65 ± 0.12 s, and unit 1 was 18.41 ± 0.15 s.Unit 2 followed after 27.74 ± 0.13 s. It had 2 subunits. Subunit 1 was a noisy pulsed sound, identified as deterministic chaos, it had a pulsed rate of (Delta f_ {u1su1}) = 1.25 ± 0.017 Hz, and a duration of 3.30 ± 0.05 s. Subunit 2 was a complex harmonic-like signal, with sidebands spaced by (Delta f_ {u2su2}) = 1.39 ± 0.003 Hz. Calculations of the ratio of the sideband frequencies over (Delta f) show that these 1.39 Hz-spaced bands do not have a harmonic relationship. However, relatively higher energy lies in frequency bands that have a harmonic relationship, where the band with the greatest energy started at 25.11 ± 0.02 Hz and ended at 24.33 ± 0.02 Hz ((G_{3_{u2su2}}) on Fig. 5). On the low signal-to-noise ratio (SNR) songs, only the harmonic bands were visible, this explains why this unit has been described previously as a harmonic signal when it is not7. The complex structure of subunit 2 can be explained by a phenomenon of biphonation, where there are two concurrent frequencies, with a lower fundamental frequency ((F_{0})) of 1.39 Hz, a higher fundamental frequency ((G_{0})) of 8.37 Hz (resonance frequency (G_{3}) starting at 25.11 Hz), and the sidebands at m(G_{0}) ± n(F_{0}) consistent with the amplitude modulation of (G_{0}) by (F_{0}). This biphonation event lasted for 16.04 ± 0.19 s. Finally, subunit 2 ended in a tonal sound with the harmonics ((G_{0}) = 7.94 Hz ± 0.003 Hz), that decreased in frequency from 24.30 ± 0.02 Hz to 23.05 ± 0.04 Hz over 4.88 ± 0.11 s (measured for the harmonic where there is the greatest energy ((G_{3_{u2su2}}))). Unit 2 was 23.63 ± 0.73 s in duration. The total duration of the Madagascan pygmy blue whale song was 68.68 ± 0.34 s.Sri Lankan pygmy blue whale The Sri Lankan pygmy blue whale song had 3 units (Fig. 5b). In 2009, unit 1 was a pulsed, non-tonal sound of a duration of 22.25 ± 0.11 s. The pulse rate was (Delta f_{u1}) = 3.28 ± 0.09 Hz. The carrier frequency of unit 1 started at 29.87 ± 0.09 Hz (‘Cf’ on Fig. 5b), and slightly down swept to 29.68 ± 0.09 Hz over 4.57 ± 0.06 s, then the frequency decreased to 25.85 ± 0.09 Hz over 17.68 ± 0.09 s.Unit 2 followed after 16.45 ± 0.12 s of silence. Unit 2 was a tonal sound with harmonics spaced by 12.21 ± 0.08 Hz. The maximum of energy was in the (F_{5_{u2}}) and started at 56.55 ± 0.12 Hz, increased to 60.63 ± 0.03 Hz over 4.87 ± 0.09 s, then increased to 60.80 ± 0.03 Hz over 8.80 ±0.09 s, and finally increased sharply to 70.13 ± 0.18 Hz overe 0.92 ± 0.06 s. Unit 2 was 14.60 ± 0.07 s in duration.Unit 3 followed after 2.20 ± 0.06 s of silence. It started as a non-tonal pulsed sound lasting 4.46 ± 0.01 s, with a pulse rate (Delta f_{u3}) = 3.29 ± 0.12 Hz and a carrier frequency starting at 103.47 ± 0.05 Hz and slightly decreasing to 102.91 ± 0.03 Hz. It then continued as a pure tone starting at 102.63 ± 0.05 Hz down to 102.41 ± 0.04 Hz during 24.19 ± 0.14 s and then suddenly peaked to 108.08 ± 0.06 Hz. Unit 3 lasted 29.25 ± 0.10 s in total, and the entire song was 84.76 ± 0.16 s in duration.Australian pygmy blue whale The Australian pygmy blue whale song is the most complex of the pygmy blue whale songs. It is traditionally described as a 3-unit signal, although multiple variations in the unit order (or syntax) are found42. The song variants change the order and repetition of the unit types. Here, for simplicity, we selected and thus described only the common traditional 3-unit song (Fig. 5c).Unit 1 was 48.83 ± 0.20 s in duration. It had 2 subunits: subunit 1 was a pulsed sound, with a pulse rate (Delta f^{s}_{u1su1}) = 1.21 ± 0.01 Hz at the beginning of the subunit, pulsing accelerated to reach (Delta f^{e}_{u1su1}) = 1.71 ± 0.01 Hz at the end of the unit. Following the ratio “band frequency/pulse rate” criterion, this unit is a non-tonal pulsed sound. However, it is a biphonation sound, as higher energy bands, which do have a harmonic relationship and are spaced by approximately 9 Hz, are obvious on the spectrogram (grey arrows on Fig. 5). The higher fundamental frequency (G_{0}) was at (sim) 9.10 Hz. The resonance frequency of this harmonic sound was the (G_{1_{u1su1}}). It started at 18.20 ± 0.02 Hz and ended at 18.47 ± 0.02  Hz, and was 23.85 ± 0.16 s in duration. Subunit 2 is also a biphonation sound, with a (F_{0}) at 2.80 ± 0.03 Hz at the beginning of the unit ((Delta f^{s}_{u1su2}) in Fig. 5c), decreasing to 1.78 ± 0.01 Hz at the end of the subunit ((Delta f^{e}_{u1su2})), which gives an impression of a decreasing pulse rate when listening to the song. This change in (F_{0}) frequency creates the complicated pattern of intersecting sidebands toward the end of unit 2. The harmonic bands are spaced by approximately 20 Hz (= (G_{0}), precise measurements are given below). Subunit 2 had two variations: subunit 2 was continuous in 42.9% of the sampled songs, but was interrupted by a short gap in 57.1%. In the continuous subunit case (N = 48), the fundamental frequency ((G_{0_{u1su2}})), which is here the band with the most energy, started at 20.22 ± 0.03 Hz and ended at 20.71 ± 0.02 Hz. The subunit lasted 23.26 ± 0.2 s. In the interrupted subunit case (N = 64), the fundamental frequency ((G_{0_{u1su2}})) started at 20.12 ± 0.03 Hz and slightly increased to 20.44 ± 0.02 Hz over 15.27 ± 0.21 s. Then, there was a silence of 3.32 ± 0.08 s followed by the resumption of the subunit at 20.29 ± 0.03 Hz increasing to 20.48 ± 0.17 Hz over 5.71 ± 0.17 s. In this case, the total duration of the subunit (gap included) was 24.31 ± 0.14 s.Unit 2 followed after 7.30 ± 0.09 s. It started as a slightly noisy pulsed sound (possibly deterministic chaos) with a rate (Delta f_{u2}) = 2.77 ± 0.06 Hz during 4.54 ± 0.07 s, then continued as a tonal sound with harmonics. The (F_{0_{u2}}) started at 20.11 ± 0.06 Hz, increased to 22.61 ± 0.02 Hz over 5.14 ± 0.10 s, and then slowly increased to 23.84 ± 0.02 Hz over 23.84 ± 0.02 s. Unit 2 was 23.12 ± 0.12 s in duration.Unit 3 followed after 24.28 ± 0.09 s of silence. It started as a tonal sound with harmonics spaced by 8.93 ± 0.05 Hz. The resonance frequency ((F_{1_{u3}})) started at 7.59 ± 0.02 Hz then increased to 18.26 ± 0.01 Hz over 3.76 ± 0.05 s, with the appearance of sidebands with non-harmonic relationship, spaced by (Delta f_{u3}) = 3.19 ± 0.09 Hz. These non-tonal pulses stopped approximately 3.5 s before the end of the unit, which ends on the harmonic sound, slightly down swept to 18.05 ± 0.02 Hz. These sidebands could be subharmonics, ((F_{0}/3, 2F_{0}/3), etc). Alternatively, they could suggest a biphonation sound. This third unit lasted 18.82 ± 0.12 s in duration, and the whole 3-unit song was 123.54 ± 0.29 s in duration.Figure 5Spectrograms (upper panels) and waveforms (middle panels) of the song of the Madagascan, Sri Lankan and Australian pygmy blue whales, including detailed waveforms to show the internal signal structure. The Madagascan song was recorded off Crozet Island (CTBTO records, site H04S1) in April 2004, the Sri Lankan song was recorded at DGN (CTBTO records, site H08N1) in April 2009 and the Australian song was recorded at Perth Canyon in March 2008 (IMOS records). (Spectrogram parameters: Hamming window, 1024-point FFT length, 90% overlap. Note that the axes differ among plots.) And measurements (mean ± s.e., lower panels) of the acoustic features of the different song types. N is the number of measurements, (u_{i}su_{j}) stands for (unit_{i} subunit_{j}) where i and j are the unit and subunit numbers, (Delta f) designates the frequency difference between the sidebands, f and d are the frequency and duration of the feature indicated in subscript, and when present, the number in brackets refers to the point measured as indicated on the corresponding spectrogram. (F_{x}) or (G_{x}) designate the xth harmonic of a sound, and Cf designates the carrier frequency of a sound.Full size imageOmura’s whale songsAll Omura’s whale songs showed energy between 15 and 55 Hz and peaks of energy around 20 and 40–45 Hz (Fig. 6 lower panels).Ascension Island Omura’s whale Omura’s whale songs recorded in 2005 off Ascension Island started as a tonal sound at 19.84 ± 0.03 Hz. This tone was 3.21 ± 0.08 s in duration but less than 1 s after its beginning, it was overlapped by a noisy pulsed sound, typical of deterministic chaos. The pulse rate was estimated at (Delta f) = 1.44 ± 0.05 Hz. This deterministic chaos lasted for 5.20 ± 0.07 s. Finally, 2.65 ± 0.06 s after the beginning of the song, three tonal components appeared at harmonically independent frequencies, characteristic of triphonation: two tones starting simultaneously, one at 20.88 ± 0.02 Hz and the other at 21.85 ± 0.03 Hz, lasting respectively 4.08 ± 0.23  s and 3.65 ± 0.16 s, and a third tone starting a bit later, 4.48 ± 0.07 s after the beginning of the song, at a frequency of 47.22 ± 0.03 Hz and lasting 3.33 ± 0.09 s. The duration of the total component was 7.64 ± 0.11 s (Fig. 6a).Madagascan Omura’s whale song The following description of the Madagascan Omura’s whale song uses the description provided by Moreira et al.18 and observation from the spectrogram (Fig. 6b). In 2015, Cerchio et al. described the Madagascan Omura’s whale song recorded in 2013–2014 as a single-unit amplitude-modulated low frequency vocalization, with a 15–50 Hz bandwidth15. More recently, Moreira et al. reported a 2-unit song, with the first unit commencing as an amplitude-modulated component with bimodal energy at 20.75 Hz and 40.04 Hz, followed by a harmonic component with a low harmonic at 20.0 Hz and an upper harmonic at 41.0 Hz, as well as an additional tone at (sim) 30 Hz. Unit 1 was characterized as sometimes followed by a tonal unit at 16 Hz18. The ICI was 189.7 s (s.d. 16.47 s, measured from 118 series with (ge) 20 consecutive songs) and ranged from 145.5 to 237.6 s43.Based on the song example recorded in December 2015 in Nosy Be, Madagascar, and provided by S. Cerchio, we observed a 2-unit song (Fig. 6b). The first unit started as chaotic, with no visible sidebands. After (sim) 3 s the signal had a bi- or triphonation event (whilst the deterministic chaos still continues), with first a tone at 40.04 Hz, another tone with a harmonic relationship at 20.02 Hz but starting circa 2.6 s later and a third one at 27.8 Hz starting 4.4 s after the beginning of the first tone, whilst the chaotic sound ends (the chaotic sound lasted circa 9.3 s). The tones of the bi- or triphonic sound all ended at the same time, 11.7 s after the beginning of the song. The second unit seems to be optional15,17,18,44. It followed after 2.8 s silence. It was a tonal sound of 4.9 s in duration with a peak frequency of 16.6 Hz. (Note that the observations here are purely qualitative since only based on 1 song).Diego Garcia Omura’s whale song (DGC) The ‘Diego Garcia Croak’—DGC—recently attributed to the Omura’s whales17 was comprised of one unit (Fig. 6c), although sometimes a second unit was present. The first unit was tonal at the start, with a frequency of 17.91 ± 0.03 Hz, quickly becoming a noisy pulsed sound, characteristic of deterministic chaos, with a pulsed rate of 2.09 ± 0.07 Hz estimated on 41 songs. This chaotic component was 2.76 ± 0.06 s in duration to then became pulsed, although still slightly noisy, with a pulse rate of 2.21 ± 0.005 Hz. This part showed a peak of energy around 19.46 ± 0.08 Hz, and another one around 43.51 ± 0.11 Hz (Fig. 6c, lower panel), and lasted 4.07 ± 0.05 s. Finally, the unit ended as a tonal sound at 17.62 ± 0.04 Hz lasting 5.29 ± 0.12 s. This whole unit had a duration of 10.56 ± 0.14 s. In some occurrences (N = 12), a second tonal unit was present after a silence of 39.89 ± 0.5 s. Unit 2 started at 13.51 ± 0.06 to 13.46 ± 0.04 Hz and lasted for 3.81 ± 0.20 s. When the second unit was present, the entire song was 54.74 ± 0.19 s in duration. Note that in our study, out of the 80 songs measured only 12 had unit 2.Australian Omura’s whale song The Omura’s whale song recorded in 2013 off western Australia had two units (Fig. 6d). Unit 1 was a noisy pulsed sound with a pulse rate of 1.65 ± 0.06 Hz with deterministic chaos, and a duration of 6.28 ± 0.06 s.The peak in energy was at 25.32 ± 0.14 Hz followed by a gap of 2.53 ± 0.04 s, and then a second noisy pulsed unit, with a pulsed rate of 1.80 ± 0.02 Hz estimated on 83 songs. This unit lasted 4.08 ± 0.03 s and had a peak of energy at 25.25 ± 0.18 Hz and another one at 41.20 ± 0.18 Hz (Fig. 6d, lower panel). During the last third of unit 2, the song transitioned to a tonal sound, starting at 25.15 ± 0.02 Hz and swept down to 25.07 ± 0.02 Hz over 3.28 ± 0.04 s, then abruptly decreased to 19.8 ± 0.02 Hz and became tonal for 4.90 ± 0.07 s, forming a z-shape on the spectrogram representation. The whole song was 16.39 ± 0.08 s in duration.Figure 6Spectrograms (a–d), waveforms (e–h), acoustic measurements (mean ± (s.e.)—i–l), and Power Spectral Density (PSD—m–p) of the songs of the Omura’s whales from Ascension Island, Madagascar, Diego Garcia and Australia. The stars on the PSD (m–p) outline the peaks of energy. The Ascension Island song was recorded off Ascension Island (CTBTO records, site H10N1) in November 2005, the Madagascar song was recorded off Madagascar in December 2015 and provided by S. Cerchio, the Diego Garcia DGC song was recorded at DGN (CTBTO records, site H08N1) in October 2003 and the Australian song was recorded at Kimberley site in March 2013 (IMOS records). For the panels (a–d) and (i–j): N is the number of measurements, (u_{i}su_{j}) stands for (unit_{i} subunit_{j}) where i and j are the unit and subunit numbers, (Delta f) designates the frequency difference between the sidebands, f and d are the frequency and duration of the feature indicated in subscript, and when present, the number in brackets refers to the point measured as indicated on the corresponding spectrogram. (Spectrogram parameters: Hamming window, 1024-point FFT length, 90% overlap. Note that the axes differ among plots).Full size imageDeterministic chaosWe classified deterministic chaos as: ‘slight’, where sidebands were easily distinguished but the sound was noisy; ‘moderate’, where the sidebands were visible but difficult to measure; and ‘strong’, where the sound had no discernible structure. Where deterministic chaos was present, we identified its persistence, defined as the proportion of deterministic chaos over the duration of a song31.It was difficult to characterize the presence of deterministic chaos where the song (sub)unit was short and the pulse rate was low, as it is difficult to ascertain if the noisy structure (i.e., lack of structure) was part of the whale’s song (i.e., deterministic chaos) or whether it was due to an artefact, such as a sound propagation issue. This was the condition for the subunit 2 of unit 1 of the Chagos song. If this subunit had indeed a chaotic structure, this chaos was slight, and represented 4.5% of the entire duration of the song (Fig. 7a).Pygmy blue whale songs had only slight deterministic chaos, and of the entire song, it represented: 11.7% of the duration of the Madagascan song; 3.7% of the Australian song; and it was not present in the Sri Lankan pygmy blue whale song (Fig. 7a). In the Madagascan pygmy blue whale songs, slight deterministic chaos was in subunits 1 of both units 1 and 2, and in the Australian pygmy blue whale songs, deterministic chaos was present in subunit 1 of unit 2.In contrast, deterministic chaos was a significant proportion of all Omura’s whale songs (Figs. 6a–d and 7a). For the song of the Ascension Island Omura’s whale, moderate deterministic chaos was present across 68% of the duration of their song. For the Australian Omura’s whales, deterministic chaos was present across 63.2% of their song, it was moderate-to-strong in the first unit and slight in the second unit. The Madagascan Omura’s whales had strong deterministic chaos across 72% of their song, which excludes the tonal unit as the tonal part was not always present. The Diego Garcia DGC Omura’s whale song had a total chaos persistence of 65.2% (Fig. 7a), with a moderate deterministic chaos present in the first 2.7 s of the song, which represents 26.3% of the song duration (Fig. 7a medium grey section). The song then evolved to a more clearly pulsed sound, with a slightly noisy structure, classified as slight deterministic chaos. Here again, it was difficult to ascertain whether this lack of structure was a characteristic of the song or an artefact of the propagation. Yet, the slight lack of structure was consistently observed across the sampled songs.Inter-call-intervalsWhilst the Madagascan pygmy blue whale had a shorter ICI, all the other acoustic groups studied here had a similar ICI duration (Fig. 7b). Thus, ICI is not a key parameter in the distinction among species and cannot be used to determine whether Chagos-whales are a blue or an Omura’s whale.Figure 7(a) Proportion of deterministic chaos (i.e., chaos persistence) in the Chagos song compared with the three Indian Ocean pygmy blue whale song types (Madagascan, Sri Lankan and Australian) and the four Omura’s whale song types (Madagascan, Diego-Garcia DGC, Australian and Ascension Island). Chaos persistence is defined as the proportion of deterministic chaos across the entire song duration (given as a percentage). Shades of grey indicate the strength of the chaos: slight (light grey), moderate (medium grey) and strong (dark grey)). (b) Boxplot representation of the Inter-call Intervals (ICI expressed in s) for the different song-types measured in this study. On each box, the central mark is the median, the edges of the box are the 25th and 75th percentiles, the whiskers extend to the most extreme data points considered to be not outliers, and the outliers are plotted individually.Full size imageGeographic distributionChagos song was detected at 5 of our 6 recording sites at disparate locations across the Indian Ocean, from: the northern Indian Ocean, off Sri Lanka; on both sides of the central Indian Ocean, off the Chagos Archipelago; and in the far eastern Indian Ocean, off northern Western Australia (Fig. 2). The Chagos song was recorded off Sri Lanka (i.e., Trincomalee) in April. Blue whales were observed at the time the recordings were made, and the songs of the Sri Lankan pygmy blue whale were also recorded at the time. The acoustic recording had become degraded as they were made nearly forty years before, on 19 April 1984, and only six distinct Chagos songs were found. Unfortunately, these recordings were of poor SNR which prevented detailed acoustic measurement. The songs, however, had the distinct structure of the Chagos song (Fig. 3) and an ICI of (simeq) 200 s (range 200 to 209 s), consistent with the ICI rate measured for the Chagos song off the Chagos Archipelago (Fig. 7b). Further south in the northern Indian Ocean, 6,984 Chagos songs were detected in 2013 (from January to early December) at our recording site RAMA, but no songs were detected at this site in 2012, although recording had been made over a shorter period, from May to December, in that year. In the central Indian Ocean, a total of 486,316 Chagos songs were detected from January 2002 to March 2014 at DGN, and 737,089 Chagos songs from January 2002 to August 2018 at DGS. In the far eastern Indian Ocean, off Kimberley, northern Western Australia, low SNR Chagos songs were manually detected from January to May, in 41 out of the 331 recording days in 2012–2013. In the south-central Indian Ocean, at our recording site RTJ, no Chagos songs were detected in 2018.Figure 8 shows the average number of Chagos songs detected per day for each year of data at the sites located on: (a) the western (DGN); and (b) eastern (DGS) sides of the Chagos Archipelago; as well as (c) further north-east, at RAMA site. The number of songs varied over the years; fewer songs were recorded at both DGN and DGS sites in 2008. In comparison with the Chagos Archipelago sites, the number of songs detected at north-eastern RAMA was low in 2013, with an average of only 20 songs/day.Figure 8Average number of Chagos songs per day detected in each year of data on the (a) western (DGN) and (b) eastern (DGS) sides of the Chagos Archipelago, and (c) further north-east, at RAMA site.Full size imageSeasonalityFigure 9b shows the average seasonality of Chagos song occurrence on both sides of the Chagos Archipelago. On the western side of the central Indian Ocean (DGN site), Chagos songs were heard predominantly from September to January, with detections peaking in December and January. On the eastern side of the central Indian Ocean (DGS site), songs were detected from June to November, with detection peaks in August to October, depending on the year. In 2013, at the RAMA site (further north-east of the Chagos Archipelago), Chagos songs were detected from January to June (with peaks in May), and in November (Fig. 9a). Off Kimberley, in the north of Western Australia, low SNR Chagos songs were found from the 22 January 2012 to the 20 May 2012, with a peak in March (Fig. 9c).Figure 9(a) Seasonality of Chagos songs at RAMA in 2013, presented as a percentage of songs per month (i.e. monthly number of songs divided by total number of songs detected in the year); (b) Seasonality of Chagos song averaged over the years (±SE) on the western (DGN—gray) and eastern (DGS—orange) sides of the Chagos Archipelago. This average seasonality is calculated as such: the monthly number of songs is divided by the total number of songs detected in the corresponding year, and averaged over the years. Note that due to the low number of recording days at DGN in 2007 and 2014, and in 2007 at DGS, these years were removed from the averaging (DGN: 11 years and DGS: 15.5 years); (c) Hourly presence of Chagos songs in Kimberley (Western Australia) in 2012–2013. Note that the metric and thus the graphic representation used for this site is different from that for RAMA and DGN/DGS: in the Kimberley data set, Chagos songs were logged upon visual inspection of the spectrograms, and a metric of hourly presence/absence of the song per day was used (see the Methods section for details).Full size imageWe found strong evidence at both Chagos Archipelago sites (DGN and DGS) that the number of Chagos songs changes not only across months (Table 1; (p=0.02417), Table 2; (p < 0.001)) and years (Table 2; (p < 0.001), Table 2; (p < 0.001)), but also that there is an interaction between months and years (Table 1; (p < 0.001), Table 2; (p < 0.001); Fig. 10). This provides evidence to suggest that there is variation in the pattern of whale songs across years at both sites. Although Chagos songs were detected throughout the year, there were more songs detected at restricted times (Fig. 10). The timing of peaks in song detection was different between the sites. At DGN most songs were detected in 2 to 3 months, whereas at DGS songs were detected over a longer period, from 2 to 6 months. At DGN, where the Chagos song distribution in most years shows clear peaks towards December and January, in a few years, peaks were outside this time (e.g., 2005 in March and September, 2006 in September and 2008 in July and August; Fig. 10). Conversely, in DGS most songs were observed between June and November, although there were inter-annual differences (Fig. 10).Table 1 Assessing the likelihood of an effect on the number of Chagos songs per day at site DGN (n = 3917 days).Full size tableTable 2 Assessing the likelihood of an effect on the number of Chagos songs per day at site DGS (n = 5557 days).Full size tableFigure 10Number of Chagos songs per month for each year at DGN and DGS. Note that the scale of the y-axis differs among years to highlight the seasonal patterns. Months without data are indicated by ‘No Data’, and months with more than 50% of missing days are indicated by a black dot.Full size image More

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Soil resident microbesWe chose sand as a realistic source of a mixed microbial community (which is referred to as the sand community or SC). Because the sand community cannot be preserved as a whole by freezing, we collected fresh material for better consistency for each experiment from the same spot in St. Sulpice near Lake Geneva (GPS coordinates: 46.508032N, 6.544050 E) as described in Moreno et al.51. Sampled sand at different seasons thus likely carried slightly different starting communities and cell densities. The sand was sieved through 2 mm2 pores to remove large particles. The sieved sand was stored at room temperature and used within 7 days for extraction of resident microbial cells.Microbial cells were extracted from four aliquots of 200 g of sand. Each 200 g aliquot was transferred into a 1-l conical flask and submerged in 400 ml of 21 C minimal media salts (MMS) (containing, per litre: 1 g NH4Cl, 3.49 g Na2HPO4·2H2O, 2.77 g KH2PO4, pH 6.8)21. Flasks were incubated at 25 °C under rotary shaking at 120 rpm for 1 h. The sand was allowed to settle and the supernatant was decanted into a set of 50 ml Falcon tubes, which were centrifuged at 800 rpm with an A-4-81 rotor and a 5810R centrifuge (Eppendorf AG.) for 10 min to precipitate heavy soil particles. Supernatants were decanted into clean 50 ml Falcon tubes and centrifuged at 4000 rpm for 30 min to pellet cells. The supernatants were carefully discarded and the cell pellets were resuspended and pooled from the four aliquots (i.e., from the initial 800 g of sand) in one tube using 5 ml of MMS. The pooled liquid suspension was further sieved through a 40 µm Falcon cell strainer (Corning Inc.) in order to remove any particles and large eukaryotic cells that may obstruct flow cytometry analysis (see below). A small proportion of the sieved liquid suspension was used to quantify the numbers of recovered cells (see below); the remainder was used within 12 h for bead encapsulation or for mixed liquid suspended growth (see below). With this gentle method, we extracted approximately 3 × 105 cells g−1 of sand.Flow cytometry cell countingCell numbers in extracted soil communities and in the mixed liquid suspended growth experiments were counted by flow cytometry. SC-suspensions were diluted 100 times in MMS and stained in 200 µl aliquots with 2 µl of diluted SYBR Green I solution (1:100 in DMSO; Molecular Probes) in the dark for 30 min at room temperature. In some experiments, cells were additionally stained with 2 µl propidium iodide solution (10 µg ml–1, Molecular Probes). Aliquots of 20 µl were aspired at 14 µl min–1 on a Novocyte flow cytometer with absolute volumetric cell counting (ACEA Biosciences, USA). Cells were thresholded above a forward scatter signal (FSC-H) of 20 and further gated for propidium iodide-staining (excited at 535 nm and its fluorescence was collected at 617 ± 30 nm) and for SYBR Green I (excitation 488 nm, 530 ± 30 nm band-pass filter; channel voltage at 441 V) above values of 1000 (Supplementary Fig. 5).Cell samples from the mixed liquid suspension growth experiments were diluted to approximately 106 ml−1 and subsampled to aliquots of 100 µl. The subsamples were then mixed with 100 µl of 8 g l–1 sodium azide in phosphate buffered saline and incubated for 1 h at 4 °C to arrest cell respiration and growth. Samples were then stained with SYBR Green I as above and quantified by flow cytometry using the same thresholds and gates as describe above.Bacterial strains and pre-culturing proceduresP. veronii 1YdBTEX2 is a toluene, benzene, m-xylene and p-xylene degrading bacterium isolated from contaminated soil20. The strain was tagged with a single-copy chromosomally inserted mini-Tn7 transposon carrying a Ptac–mCherry cassette (Pve, strain 3433) as described in the ref. 52. A single P. veronii colony from a selective plate with toluene as the sole carbon substrate after 48 h incubation at 30 °C was inoculated into 10 ml of liquid MMS containing 5 mM sodium succinate as the sole carbon source and grown for 24 h at 30 °C with rotary shaking at 180 rpm21. After 24 h, the cells were harvested and washed for bead encapsulation or for comparative liquid mixed suspension growth, as described below.Agarose bead encapsulationSC cell suspensions containing between 2 × 107 to 108 cells ml–1 were encapsulated in agarose using rapid mixing with pluronic acid in dimethylpolysiloxane and subsequent cooling, followed by sieving to achieve beads with a diameter range of 40–70 µm53. The entire procedure was carried at room temperature and near a gas flame to maintain antiseptic conditions. 1% (w/v) low melting agarose (GEPAGA04-62, Eurobio ingen, France) was prepared in PBS solution (PBS contains per L H2O: 8 g NaCl, 0.2 g KCl, 1.44 g Na2HPO4, 0.24 g KH2PO4, pH 7.4) and dissolved by heating in a microwave. The molten agarose solution was cooled down and equilibrated in a 37 °C water bath. Separately, 15 ml of dimethylpolysiloxane (Sigma-Aldrich, DMPS5X-500G) was poured in a 30 ml glass test tube. 1 ml of the 37 °C-agarose solution was mixed with 30 µl of pluronic acid (10% Pluronic® F-68, Gibco, Life Technologies) by vortexing at the highest speed (Vortex-Genie 2, Scientific Industries, Inc.) for a minute. Into this mixture of agarose and pluronic acid, 200 µl of prepared SC cell suspension at 0.2–1.0 × 108 cells ml–1 was pipetted and vortexed again at the highest speed for another minute. Five hundred microliter of this mixture was added drop-wise into the glass tube with dimethylpolysiloxane that was being vortexed at maximum speed. Vortexing was continued for 2 min. The tube was then immediately plunged into crushed ice and allowed to stand for a minimum of 10 min. After this, the total content of the tube was transferred into a 50 ml Falcon tube. The tube was centrifuged for 10 min at 2000 rpm using an A-4-81 swinging-bucket rotor (Eppendorf). The oil was carefully decanted while retaining the beads pellet. Fifteen milliliter of sterile PBS was added to the pellet and the beads were resuspended by vortexing at a speed set to 5. The tubes were again centrifuged at 2000 rpm for 10 min and any visible oil phase on the top was removed using a pipette. The process was repeated once more to remove any visible oil phase. Beads of diameter between 40 and 70 µm were then recovered by passing the PBS-resuspended bead content of the tube first over a 70-µm cell strainer (Corning Inc.). A further 5 ml of PBS was added to the cell strainer to flush remaining beads ( 0.25). Finally, we tested further interaction terms that influenced attributed growth rates. The initial carbon concentration was set to 50 mg ml–1, which allowed similar community development in terms of size (i.e., cell numbers) as in the experiments.Growth was simulated for 120 time steps, corresponding to 60 h in the experiments, at which point the substrate is depleted and cells stop dividing (stationary phase). Based on the attributed growth rates to every OTU (i.e., every cell and genotype of the vector or double vector), the model calculates per time step how much substrate is converted into biomass (we allow continuous biomass formation) and lost in form of CO2, which is subtracted to calculate the remaining substrate concentration for the next time step. When the overall substrate concentration is lower than ({S}_{{min }}) = 3 × 10–6 g ml–1, growth stops. The production of cell biomass is converted to cell numbers, which is then subsampled at the last time step per OTU (to an equivalent of 50,000 sequence reads), per single or pair (to an equivalent of 5000 beads) to calculate developed microcolony sizes, diversity measures, and interaction effects (as in Figs. 5 and 6).The following interaction scenarios were simulated. Although we allowed growth penalties and interspecific interactions to influence attributed OTU growth rates, a threshold of ~0.6 h–1 was imposed as the maximum individual OTU growth rate in all simulations.High connectivity random vs. OTU-abundance growth rates. OTU-specific growth rates (µmax,sp) were drawn randomly between 0.01 and 0.6 h–1. Alternatively, growth rates were attributed to the vector of OTUs according to the probability distribution function reflecting their measured log10 empiric abundance at t = 0 h (Supplementary methods, Section 2).Low connectivity single founder cell growth penalty. We contrasted simulations with single founder cells growing according to their OTU-proportional attributed growth rate and those in which that growth rate was multiplied by a penalty, composed by a factor equal to the inverse proportion of the initially attributed µmax,sp per OTU. The assumptiton is that the slower the inherent growth rate, the more likely that OTU is penalized when it is alone (Supplementary methods, Sections 2 and 3). This was combined with testing the effect of random or biased death on the starting community.$${{rm{mu }}}_{{{rm{max}} },{{rm{sp}}}}=frac{1.2}{{{log }}_{10}({{rm{mu }}}_{{{rm{max}} },{{rm{sp}}}})}$$
(3)
Low connectivity paired interspecific interaction effects. We further tested different assumptions on the nature of interspecific interactions and simulated how these affected community growth rates and diversity outcomes. These effects directly influenced the OTU attributed growth rates in the doubles (Supplementary methods, Sections 3.1–3.3). In the bimodal scenario (Supplementary methods, Section 3.4.1), we assumed that the community is composed of two underlying distributions; rare and abundant members (the threshold being placed at log10 measured OTU relative abundance = 2.8), with abundant members having a higher probability to be positively influenced in pairs. The probability is drawn from a bimodal interaction curve that attributes an interaction factor (between 0.01 and 2.2), which is multiplied with the assigned OTU growth rate at start.In the biased positive model (Supplementary methods, Section 3.4.2) we allowed a 40% chance for an interaction term imposed independently on each founder cell in a pair to lower the attributed OTU growth rate (factor range 0.4–0.6), and 60% chance for a factor in between 0.6 and 1.4 to modulate or increase the growth rate.In the positive on slow model (Supplementary methods, Section 3.4.3), the attributed OTU growth rates on each founder cell in a pair had a chance of 40% to become improved inversely proportionally to its initial growth rate, thereby favoring slow growers$${{rm{mu }}}_{{max },{{rm{sp}}}}={{mbox{-}}}{rm{ln}}({{rm{mu }}}_{{max },{{rm{sp}}}}),times {{rm{mu }}}_{{max },{{rm{sp}}}}$$
(4)
In the biased negative model (Supplemtary methods, Section 3.4.4), we attributed OTU-abundance proportional growth rates to each partner of the founder pair, but penalized faster growers (µ  > 0.15) at 20% chance and the others at 40% chance that their growth rate would be multiplied by a negative interaction factor (range 0.01–0.1).Finally, in a random model (Supplementary methods, Section 3.4.5), we allowed OTU-abundance proportional growth rates in pairs to be multiplied with a factor randomly drawn in the range of 0.01–1.25, independently for each partner in a pair. The models were contrasted to those without any assumed interspecific interactions, and without or with assumed random or fast-growing genotype biased cell death at start (Supplementary methods, Section 2.3.1).All simulations were run five times from the beginning, independently producing five derived parameter values for alpha-diversity, OTU- and microcolony size distributions in stationary phase and partner interactions.Statistics and reproducibilityLiquid suspension growth experiments were carried out in biological quadruplates and all bead experiments were carried out in biological triplicates. Total numbers of analyzed bead and those of beads with single or double occupancy are reported. Derived community growth rates and P. veronii-normalized yields were compared using t-tests (n as reported, two-sided test, unequal variance). Normalized PBP bin-size distributions were globally compared using Fisher’s exact test implemented in R (2000 replicates). Median and 75th percentile aggregate PBPs across different experiments were compared using the non-parametric Wilcoxon signed-rank test. Correlations between simulated species abundance distributions and empirical OTU relative abundances were calculated by bootstrapping (n = 1000) in MATLAB. Correlation coefficients from five independent simulations were compared using t-tests. The proportion correctly predicted OTU abundances by simulation was calculated as the ratio to observed values within a two-fold or four-fold range, and compared by two-sided t-tests on five independent simulations. Simulated and observed microcolony size distributions for single or paired founder cells among different models were compared by principal component analysis in MATLAB (pca), and by Spearman rank correlation (spear) from five independent simulations. Single and paired productivity was then compared between each other using two-sided t-tests of the 75th percentiles of microcolony size distribution (n = 5). Simulated and observed paired growth (excluding pairs with dead cells) was categorized and counted in a grid of 12 × 12 (each bin covering 0.5 log10-distance) using MATLAB’s hist3d function, and then compared by pca from five independent simulations. Confidence intervals on ratios of paired simulated microcolony sizes (excluding those pairs with a non-growing or dead partner) were determined by subsampling (n = 1000) from mean ratio distributions, which were then used to calculate the fractions deviating from experimentally observed paired size ratios.Reporting summaryFurther information on research design is available in the Nature Research Reporting Summary linked to this article. More

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