Mass for growth and reproduction was converted to Joules by using the ... Photoshop software to form a block transect. ... structured network of a free-ranging shark species. Anim. ... Bates, D. M. (2010). lme4: Mixed-Effects Modelling with R. Available online at: ... URL http://cran.r-project.org/web/packages/gamm4/index.html.
Current Biology, Volume 26
Supplemental Information
Extreme Inverted Trophic Pyramid of Reef Sharks Supported by Spawning Groupers Johann Mourier, Jeffrey Maynard, Valeriano Parravicini, Laurent Ballesta, Eric Clua, Michael L. Domeier, and Serge Planes
Figure S1, related to Figure 1. Description of the study location. Zonation of the pass (blue) including shark aggregation (orange), grouper spawning aggregation (green) and location of acoustic receivers (white circles). Locations of ReefLifeSurvey transects are also indicated.
Figure S2, related to Figure 3. Presence and residency of tagged grey reef sharks. (A) Number of tagged sharks detected per day by the receiver network (top panel) and daily detections of each tagged shark at the receiver network (bottom panel). Grey dots indicate males and black dots indicate females. (B) Response curve of the effect of time of the year on proportion of time per day spent inside the receiver array as estimated by the generalized additive model GAMM. This model shows a significant increase in time spent in the pass between June and October. (C) Probabilities of presence at each receiver as a function of time of day (hour) and season (month).
Figure S3, related to Figure 4. Shark foraging activity inferred by behavioral underwater observations using rebreather diving equipment. (A-B) High number of sharks at night foraging in the pass. (C-E) Bite wounds inflicted to groupers by sharks as indirect evidence of hunting in the pass. (F-G) Direct evidence of grey reef sharks foraging on reef fish in the pass at night. Fish species that were observed targeted and consumed by sharks (14 in total): Kneeled Needlefish (Platybelone argalus platyura), Sabre Squirrelfish (Sargocentron spiniferum), Marbled grouper (Epinephelus polyphekadion), Yellow-edged lyretail (Variola louti), Tricoloured fusilier (Pterocaesio tile), Goldlined emperor (Gnathodentex aureolineatus), One-spot snapper (Lutjanus monostigma), Convict surgeonfish (Acanthurus triostegus), Yellowfin surgeonfifh (Acanthurus xanthopterus), Spotted unicornfish (Naso brevirostris), Chinese trumpetfish (Aulostomus chinensis), Moontail bullseye (Priacanthus hamrur), Stellate puffer (Arothron stellatus) and Moorish idol (Zanclus cornutus).
Figure S4, related to Figure 3. Illustrated examples of other energetic subsidies within the pass. (A) Acanthurus triostegus form spawning aggregation in large groups every new and full moons at sunset in the pass and are targeted by C. amblyrhynchos. (B) Diel migration of school of pelagic fish at dawn also targeted by C. amblyrhynchos. (Photo © V. Truchet).
Table S1, related to Figure 1. Detailed grey reef shark census surveys. Abundance is given for groups 1 and 2 as well as for the entire aggregation. Data are represented as mean ± SEM.
Date
Abundance Group1
Group2
Total
25/06/2014
301 (4)
404 (4)
705 (7)
27/06/2014
353 (6)
272 (5)
625 (9)
29/06/2014
234 (2)
235 (6)
469 (8)
01/07/2014
166 (4)
276 (6)
442 (9)
02/07/2014
217 (1)
247 (5)
464 (6)
04/07/2014
180 (1)
210 (5)
389 (4)
07/07/2014
327 (8)
239 (2)
566 (7)
08/07/2014
280 (9)
257 (2)
537 (10)
09/07/2014
222 (3)
250 (6)
472 (9)
11/07/2014
184 (7)
174 (4)
358 (10)
13/07/2014
280 (2)
323 (1)
603 (1)
15/12/2014
148 (7)
103 (4)
251 (10)
16/12/2014
234 (6)
154 (2)
388 (5)
Table S2, related to Figure 1. Bioenergetics model output for estimates of shark daily food requirements. Abundance, biomass, individual daily ration (individual DR in % body weight ± SEM) and global daily ration (in kg) are indicated for all shark species and each sex. Note that for C. amblyrhynchos we estimated minimal and maximal values corresponding to minimal and maximal abundances within the year.
Sex Number Biomass (t) Biomass (g m-2) Individual DR in fish (%BW) Total DR (kg of fish)
Species C. amblyrhynchos
Max F Min F
529 188
14.54 4.84
83.08 27.65
1.56 (5.8 10-4)
226.80
-4
75.55
-4
1.56 (9.2 10 )
Max M
176
5.16
29.48
1.54 (7.9 10 )
79.66
Min M
63
1.73
9.88
1.54 (1.4 10-3)
26.69
C. melanopterus
F M
C. albimarginatus All T. obesus C. limbatus
60 60 15
0.84 0.84 0.14
4.8 4.8 0.8
-3
12.35
-3
12.22
-3
2.36
-3
1.46 (1.6 10 ) 1.45 (1.6 10 ) 1.69 (3.4 10 )
F
15
0.10
0.57
1.92 (4.4 10 )
2.01
M
15
0.10
0.57
1.91 (5.4 10-3)
1.98
F M
16
0.82
4.68
-3
9.99
-3
3.77
1.21 (1.8 10 )
6
0.31
1.77
1.19 (2.4 10 )
Max
892
22.85
130.57
351.14
Min
438
9.72
55.54
146.92
Total
Table S3, related to Figure 3. Species-specific parameters used for the bioenergetics model. Model component and parameters
Definition
Value and Source
C. amblyrhynchos
C. melanopterus
C. albimarginatus
T. obesus
C. limbatus
Sex ratio
Sex ratio (M : F)
1 : 4 [This study]
1 : 1 [This study]
1 : 1 [This study]
1 : 1 [This study]
1 : 4 [This study]
a
Species-specific length-mass scaling constant
0.00000136 [S1]
0.000001004 [S3]
0.00000305 [S7]
0.00000047 [S2]
0.00000614 [S7]
b
Species-specific length-mass scaling constant
3.34 [S1]
3.39 [S3]
3.243 [S7]
3.39 [S2]
3.01 [S7]
Wb
Mass at birth
1200 g [S1]
580 g [S4]
immature
500 g [S2]
1200 g [S7]
Ls
Average litter size
4 pups/year [S1]
3 pups/year [S5]
immature
2 [S2]
5 [S7]
L∞
Asymptotic length
229.2 cm [S2]
158.5 cm [S6]
300 [S7]
207.8 (F) -150.9 (M) [S2]
179.2 cm [S7]
K
Von Bertanffy growth rate coefficient
0.05 [S2]
0.251 [S6]
0.05
0.05 (F) -0.10 (M) [S2]
0.21 [S7]
D
Proportion of fish in shark’s diet
85% [S1]
70% [S3]
75 [S7]
80% [S7]
75 [S7]
Table S4, related to Figure 3. Residency of Carcharhinus amblyrhynchos tagged with acoustic transmitters at the study site. Information on tagged sharks is provided with residency index (%). Tag ID ID1208 (Ca7) ID1225 (Ca8) ID1219 (Ca9) ID1224 Ca10) ID1205 (Ca11) ID1227 (Ca12) ID1192 (Ca13) ID1203 (Ca14) ID1197 (Ca15) ID1218 (Ca16) ID1196 (Ca17) ID1228 (Ca18) ID1229 (Ca19)
TL
Sex
Tagging date
Location
Days
Residency Index (%)
detected
Global
R1
R2
R3
R4
R5
R6
150
F
15/07/2011
R3
414
73.8
1.6
10.9
7.0
0.5
0.5
71.5
149
M
15/07/2011
R3
133
23.7
0.2
0.5
0.0
0.0
0.0
23.4
143
F
16/07/2011
R5
400
71.3
1.8
10.3
54.7
6.4
6.1
29.8
155
F
17/07/2011
R5
12
2.1
0.0
0.2
1.8
0.0
0.4
0.2
169
F
17/07/2011
R4
223
39.8
1.6
2.7
2.1
6.2
13.9
19.8
144
M
17/07/2011
R6
50
8.9
0.2
0.0
7.8
0.2
0.2
2.7
152
F
18/07/2011
R3
538
95.9
13.4
86.6
46.9
8.6
3.9
91.6
151
M
18/07/2011
R3
223
39.8
5.7
29.2
0.0
0.0
0.0
24.1
158
F
19/07/2011
R3
224
39.9
1.8
0.5
4.8
0.0
0.9
34.8
154
F
19/07/2011
R3
396
70.6
21.0
69.0
52.9
19.8
4.5
69.2
161
F
19/07/2011
R4
131
23.4
0.0
4.5
15.3
17.8
0.2
6.4
161
F
19/07/2011
R4
207
36.9
1.2
6.4
13.2
8.7
0.7
19.3
159
F
19/07/2011
R4
127
22.6
0.2
0.0
0.0
0.2
0.0
22.5
TL: Total length in cm. Sex: M males, F Females. Location: tagging and release site with receiver name given. Days detected: Number of days detected within the monitoring period of 561 days. Residency Index: Percentage of days a shark was detected within the receiver array divided during the experiment (values are given for the entire pass as well as for each receiver).
SUPPLEMENTAL EXPERIMENTAL PROCEDURES
Underwater visual censuses (UVC) Common methods to measure shark densities and abundance have shown their limits [S8-9]. Individualbased visual identification [S10] is only possible when the population size is small for sharks with uniform body coloration [S11] such as the grey reef shark (C. amblyrhynchos). We developed a video-assisted method that is perfectly adapted to our study site and prevents most common biases. The count sessions were conducted with SCUBA during the inward flow because of the high water visibility (>30 m) in these current conditions. Because the channel is narrow ( 12.5 cm TL as these fish represent shark prey. For community biomass spectra, we assigned individual fish to mass classes (i.e. 4-8, 8−16, 16−32, 32−64, 64−128, 128−256, 256−512, 512−1024, 1024−2048, 2048−4096, 4096−8192, 8192−16384 and 16384−32768 g) following previous work [S22]. We then summed all biomass in each bin to the bin midpoints (W) for each species and divided by total area surveyed to give biomass (B) per unit area (g m−2) within each size class. Biomass spectrum was modelled as a linear regression model with the midpoints of the log2 size bins (log2 (W)) as the predictor and log2 (B) as the response [S22]. The channel serves as a spawning aggregation zone for the camouflage grouper (Epinephelus polyphekadion) during June and July but is absent during the rest of the year. Therefore, we separately estimated the density and biomass of groupers using a 25×25 m quadrat divided into four 6.25×25 m blocks placed in the middle of the aggregation. Digital continuous photo-quadrats were then taken directly downwards from approximately 10 m above the seabed (sufficient to encompass the 6.25*25 m block transects) with a diver swimming at constant speed and depth. Sequences of pictures were then processed and assembled into Photoshop software to form a block transect. Fish were then counted within each block and abundance was extrapolated to the global fish aggregation zone. Acoustic tracking has demonstrated that groupers congregate from the entire atoll (70km long), and mainly from the lagoon (Mourier, unpublished data). Predator-prey interaction model The rate of annual fish production (P; g.ha-1.year-1) was estimated by converting the body mass (W; g) of fish to rates of annual biomass production using the metabolic theory [S24], which considers the intrinsic relationship between fish size and the rate at which it produces new biomass through a combination of growth and reproduction, and depends on body mass and temperature [S23-S25] as follow: P = exp(25.22 – E/kT) W0.76
(7)
where E is the ‘activation energy of metabolism’ (0.63 eV); K is the Boltzmann’s constant (8.62x10-5 ev.K-1) and T is the temperature in Kelvin (27.5°+273). P was calculated for each fish in transect surveys, summed and converted in g.year-1 of fish produced by m-2. Then it was extrapolated to the pass and transformed to obtain a daily production DPPrey in kg.day-1 at the scale of the pass (17.5 ha). We then developed a model to investigate how prey biomass would evolve as a function of shark consumption based on energy requirements. Based on the prey fish biomass at t0 (time of fish census), we calculated the biomass for all consecutive days following equation: BPrey (t) = BPrey (t-1) – DRShark (t-1) + DPPrey (t-1) where DRShark is a function of time of year (orange curve in Figure 2) and is dependent of d, the proportion of groupers in shark’s diet during the spawning aggregation. When the spawning aggregation is finished at tS, d
(8),
equals zero and sharks no longer consume groupers. We created 10 scenarios in which d can range from 0 to 100 % of grouper in the shark diet during the spawning aggregation period. For each scenario i, DRShark (t, i) = (1-di) * DRShark (t)
(10),
where d = 0 for t > tS. For each day, DPPrey is updated based on new biomass available such as: DPPrey (t) = BPrey (t) / BPrey (t-1) * DPPrey (t-1)
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