Ocean acidification does not impair the behaviour of coral reef fishes

Matters Arising to this article was published on 21 October 2020


The partial pressure of CO2 in the oceans has increased rapidly over the past century, driving ocean acidification and raising concern for the stability of marine ecosystems1,2,3. Coral reef fishes are predicted to be especially susceptible to end-of-century ocean acidification on the basis of several high-profile papers4,5 that have reported profound behavioural and sensory impairments—for example, complete attraction to the chemical cues of predators under conditions of ocean acidification. Here, we comprehensively and transparently show that—in contrast to previous studies—end-of-century ocean acidification levels have negligible effects on important behaviours of coral reef fishes, such as the avoidance of chemical cues from predators, fish activity levels and behavioural lateralization (left–right turning preference). Using data simulations, we additionally show that the large effect sizes and small within-group variances that have been reported in several previous studies are highly improbable. Together, our findings indicate that the reported effects of ocean acidification on the behaviour of coral reef fishes are not reproducible, suggesting that behavioural perturbations will not be a major consequence for coral reef fishes in high CO2 oceans.

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Fig. 1: Widespread avoidance of predator chemical cues in coral reef damselfishes exposed to present-day and end-of-century levels of CO2.
Fig. 2: Damselfishes avoid predator chemical cues to the same degree when exposed to present-day or end-of-century CO2 levels irrespective of life stage.
Fig. 3: Bootstrapping data simulations of predator chemical cue avoidance and within-group variance.
Fig. 4: Widespread similarities in the activity levels of six species of coral reef damselfish regardless of whether acclimated to present-day or end-of-century levels of CO2.

Data availability

The data necessary to reproduce figures and results in this study are publicly archived in Figshare following best-practice guidelines55, and were made available to editors and reviewers at the time of submission: https://doi.org/10.6084/m9.figshare.7871522. We place no restrictions on data availability.

Code availability

Scripts for statistical analyses are available from Figshare (https://doi.org/10.6084/m9.figshare.7871522). We place no restrictions on code availability.


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T.D.C. was funded by a Future Fellowship Grant (FT180100154) from the Australian Research Council. J.S. was funded by a Mobility Grant from the Swedish Research Council Formas (2013-947). G.D.R. was funded by a Postdoctoral Fellowship from the Natural Sciences and Engineering Research Council of Canada (NSERC). S.A.B. and B.S.-R. were funded by Discovery Grants from NSERC. B.S.-R. was also funded by a Harrison McCain Young Scholars Award. F.J. was funded by Formas (2009-596), the Swedish Research Council VR (621-2012-4679) and the Research Council of Norway (262942). Additional funding was obtained from the Society for Experimental Biology and Company of Biologists Travel Grants (J.S., JEBTF-150422), Magnus Bergvalls Stiftelse (J.S., 2014-00620), Australian Endeavor Research Fellowship (G.D.R.), IRIS stipendiet (J.S., 2015-0264), Stiftelsen Lars Hiertas Minne (J.S., FO2014-0659), the Wenner-Gren Foundation (J.S.), Wallenbergstiftelsen (J.S.), Inez Johanssons stiftelse (J.S.) and Sederholms utrikes stiftelse (J.S.). We thank N. Sopinka and A. Yu for assistance with behavioural lateralization trials in 2015, S. Noonan for analysing water samples for total alkalinity, R. Streit for assistance with some experiments in 2014, A. Severati and C. Schlott for wild fish collections in 2015, K. Stark for assistance with the R script for bootstrapping simulations, and V. Messmer, A. Hoey and A. Tobin for assisting with the collection of fishes for the 2014 experiments. Thanks to the SeaSim staff at AIMS for logistical support.

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All authors contributed to the design and execution of behavioural experiments; T.D.C. drafted the manuscript and Supplementary Information with assistance from all authors; T.D.C. and J.S. managed and prepared the raw data with assistance from co-authors; G.D.R., D.G.R. and T.D.C. conducted the statistical analyses and created the figures. J.S. managed the revisions with assistance from all co-authors.

Corresponding authors

Correspondence to Timothy D. Clark or Josefin Sundin.

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The authors declare no competing interests.

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Peer review information Nature thanks David Bierbach and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.

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Extended data figures and tables

Extended Data Fig. 1 Interactions between CO2 treatment and size for fish activity.

ac, Raw data points and fitted model estimates for activity in D. aruanus in 2014 (a), A. polyacanthus in 2014 (b) and A. polyacanthus in 2015 (c) as a function of acclimation treatment (grey diamonds, control; blue circles, high CO2) and size (x axis), with shaded areas indicating 95% confidence intervals of model estimates. Model parameter estimates are included in Extended Data Table 3. a, n = 23 per treatment. b, n = 8 per treatment. c, Control, n = 28; CO2, n = 38. Sample sizes represent biologically independent animals.

Extended Data Fig. 2 Widespread resilience of behavioural lateralization in coral reef damselfishes when faced with end-of-century levels of CO2.

ag, Number of right turns (out of 10) under control (closed grey bars) and high CO2 (open blue bars) conditions for fishes facing either a centred barrier at one end of the T-maze (af) or an offset barrier at the other end of the T-maze (g). Sample sizes represent biologically independent animals). a, P. moluccensis. Control, n = 29; CO2, n = 20. b, C. atripectoralis. Control, n = 26; CO2, n = 17. c, D. aruanus. Control, n = 19; CO2, n = 21. d, P. amboinensis. Control, n = 21; CO2, n = 22. e, P. amboinensis retested. Control, n = 15; CO2, n = 15. f, A. polyacanthus. Control, n = 120; CO2, n = 104. g, A. polyacanthus (same sample sizes as in f). ae, Data were obtained at the LIRS in 2014. f, g, Data were obtained at the AIMS in 2015. Dashed lines represent the mean number of right turns for each treatment group. A tick mark on the panel (coloured according to treatment) indicates significant individual-level lateralization, whereas an asterisk at the top of the panel indicates significant population-level lateralization. See Extended Data Tables 4, 5 for statistics.

Extended Data Fig. 3 Histogram of the percentage of time in predator cue data for fish used in choice flume trials at LIRS in 2016.

Each data point included in this summary represents analysis of one minute of behavioural data for a fish; the plot contains many repeated measurements for each fish.

Extended Data Fig. 4 Histogram of representative data for percentage of time spent in water containing predator cue or conspecific alarm cue.

Histograms of representative data (4-min means) from a previous study25 (solid bars) showing the disproportionate number of fish that were reported to spend 0% of time in conspecific chemical alarm cue when acclimated to control water (a) or 100% of time in the cue when acclimated to water with elevated CO2 levels (b). The representative treatment groups25 are juvenile A. polyacanthus in control water from parents acclimated to high CO2 water (a, n = 62) and juvenile A. polyacanthus in high CO2 water from parents acclimated to high CO2 water (b, n = 62). Also presented are data (4-min means) from the present study (6 species, open bars; n = 247 control, n = 239 high CO2) showing peak frequencies around 50% of time in predator cue for both control (a) and high-CO2-exposed (b) fish. Sample sizes represent biologically independent animals. Mean values for each of the datasets are indicated with vertical lines, and arrows are directed at modal values in each of the datasets.

Extended Data Table 1 Water chemistry data for the two sites for the three years of the study
Extended Data Table 2 Model predictions of time spent in predator chemical cue
Extended Data Table 3 Model predictions of mean activity levels
Extended Data Table 4 Individual- and population-level lateralization of coral reef fishes
Extended Data Table 5 Individual- and population-level lateralization of wild and captive-reared A. polyacanthus

Supplementary information

Supplementary Information

This file contains additional details on the methods. It also contains notes on replication studies, life stages and definition of larval versus juvenile fishes, on the importance of inter-individual variation, and further details on the contents of Figure. 3.

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Clark, T.D., Raby, G.D., Roche, D.G. et al. Ocean acidification does not impair the behaviour of coral reef fishes. Nature 577, 370–375 (2020). https://doi.org/10.1038/s41586-019-1903-y

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