# Effects of extreme environmental conditions of the Bouraké lagoon on sponge Rhabdastrella globostellata metabolism

Federica Maggioni

► To cite this version:

Federica Maggioni. Effects of extreme environmental conditions of the Bouraké lagoon on sponge Rhabdastrella globostellata metabolism. Life Sciences [q-bio]. Université de la Nouvelle-Calédonie, 2023. English. NNT: 2023NCAL0001. tel-04610309

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UNIVERSITÉ DE LA NOUVELLE-CALÉDONIE
ÉCOLE DOCTORALE DU PACIFIQUE (ED 469)

Thèse de Doctorat
Biologie des populations et écologie

Federica MAGGIONI

Effets des conditions environnementales extrêmes de la lagune
de Bouraké sur le métabolisme de l'éponge *Rhabdastrella
globostellata*

Effects of extreme environmental conditions of the Bouraké
lagoon on sponge *Rhabdastrella globostellata* metabolism

Soutenue le 13 Avril 2023 devant le jury composé de :– Defended on April 13, 2023
in front of the jury composed of:

Dr. Mathieu Pernice

Dr. Thierry Perez

Pr. Claude Payri

Dr. Verena Schoepf

Dr. Benjamin Mueller

Pr. James J. Bell

Pr. Yves Letourneur

Dr. Riccardo Rodolfo-Metalpa

Rapporteur

Rapporteur

Examinatrice

Examinatrice

Examinateur

Examinateur

Directeur

Encadrant
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"People protect what they love, they love what they understand and they understand what they are taught"

Jacques-Yves Cousteau
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**Abstract**

Anthropogenic carbon dioxide emissions and other greenhouse gasses have increased exponentially since the industrial revolution, causing significant changes in the Earth's climate. The three main effects of climate change on marine ecosystems are warming, acidification, and oxygen decline. While most ecological and physiological research targets corals, the effects on sponges and their ecological role have yet to be further investigated. Sponges provide essential ecological functions, including contributions to nutrient and carbon cycling. They can uptake dissolved organic carbon and transform and release it in particulate organic carbon (i.e., detritus), which higher trophic levels can use. Understanding how future climatic conditions could alter the ecological role of sponges is critical for a better understanding of the future of coral reefs. This thesis addressed the gaps in our knowledge of how sponge nutrients and organic matter recycling might change under extreme environmental conditions (high temperature, low pH, and low dissolved oxygen).

Firstly (chapter 2), I performed a long-term physical, chemical, and benthic characterization of the Bouraké lagoon (New Caledonia). Data collected from 2016 to 2020 showed that this site is characterized by daily variation, driven by tide, of chemical and physical parameters, which reach extreme values during low tide (33°C, 7.2 pH~T~, and 1.9 mg O~2~ L~⁻¹~). Despite these extreme environmental conditions, a rich and healthy benthic community was found with 66 coral species, 28 macroalgae species, and 11 sponge species. My results demonstrate that the Bouraké lagoon is a unique site that can be used as a natural laboratory to study the effects of extreme environmental conditions on organisms.

After characterizing my study site, I performed 118 *in-situ* incubations, in the Bouraké lagoon, using respirometric benthic chambers to study the effects of extreme conditions on sponge carbon and nutrient cycling and the photosynthetic activity of their associated symbionts (chapter 3). The most abundant sponge species found in the Bouraké lagoon, *Rhabdastrella globostellata* (Carter, 1883), was chosen as a model species and incubated *in-situ* under both normal (high tide) and extreme (low tide) conditions. The responses of the sponge holobionts were examined by comparing the changes in physical and chemical seawater parameters at the beginning and the end of incubations. The results showed that the sponges stopped producing detritus (i.e., the sponge loop) under extreme conditions. My findings also suggest that high temperature (> 31°C) could be the main driver of this break in the sponge organic carbon recycling, particularly when combined with extreme acidification and deoxygenation levels.
From the results of the *in-situ* experiments, the temperature was hypothesized as the main factor affecting the sponge carbon cycle. *Ex-situ* aquarium experiments were then performed to explore the nitrogen and carbon recycling response of *R. globostellata*′s exposed to high temperatures (chapter 4). Specimens of *R. globostellata* from the Bouraké lagoon and a control site were exposed at 28°C and 32°C. The responses were assessed by tracking labeled ¹³C and ¹⁵N in sponge tissue and detritus production. The results show that the Bouraké sponges incorporated more ¹³C and ¹⁵N, assimilated as coral mucus into the tissues than released as detritus. These rates doubled when exposed at 32°C compared to 28°C. In contrast, sponges from the control site incorporate less ¹³C and ¹⁵N in their tissues and released more in detritus. The change in C and N allocation, with greater accumulation in the sponge tissues of Bouraké specimens, may be an adaptation to the extreme environmental conditions of the site.

In a world where climate change is accelerating, and many of the effects of these changes on
organisms have yet to be studied, my research demonstrates how the sponge *R. globostellata* responds
to different environmental conditions and shows that its metabolism changes to thrive in extreme
environments. I provide the first evidence that exposure to elevated temperatures (+3°C) results in a
change in the allocation and use of carbon and nitrogen between sponge tissue and detritus, also
providing insight into the possible change in the availability and quality of food sources in a future
coral reef. Finally, I showed evidences that sponges could develop a mechanism for adapting to
different environmental conditions by making the most of it. My hope is that the suggested adaptation
to future environmental conditions will be possible also for other taxa.
Acknowledgments

First, I wish to thank my supervisor Dr. Riccardo Rodolfo-Metalpa, without whom none of this would
have been possible. I still remember our first dive in Bouraké during my MSc thesis in 2018, where
because of the visibility, I lost you after not even 1 minute and found myself on the other side of the
lagoon carried by the strong current. I thought to myself: "who made me do that?!" It feels odd to end
(for the moment) this adventure after so many years. Thank you for your support and patience. I also
want to thank my supervisor Professor Yves Letourneur, for his constant guidance and support. I am
very glad to have had the opportunity to learn from both of you!

Special thanks to Pr. Claude Payri, Dr. Verena Schoepf, Dr. Mathieu Pernice, Dr. Benjamin Mueller, Dr. Thierry Perez, Pr. James J. Bell, and for agreeing to be my examiners.

I wish to thank Professor James J. Bell for always being available to advise and support me with this
research project. Thank you so much for your inspiration and the time you took to help me. I also
thank Professor Carlo Cerrano who since my MSc has always followed me and given me advice over
the years. Both of their thoughtful advice have constantly improved my thinking. It has certainly been
a great pleasure for me to work with you, and I hope we will find ways to continue to share our ideas.

I owe a debt of gratitude to all of the people with that I have worked with who have influenced and
supported me along the way. I wish to express my sincere gratitude to the IRD diver staff (Mahé, and
Magali), boat captains (Miguel, Sam, Philippe, Jordi), and the ALIS staff for logistical support during
all field trips and experiments. Thanks to the LAMA laboratory staff and the IFREMER staff (Adecal,
Saint-Vincent) for their willingness and hospitality during the endless days of the laboratory. Thanks
to Dr. Hugues Lemonnier for his advice and support. Special thanks to all the staff of “Aquarium de
lagoon” for their support during my aquarium experience, particularly to Dr. Olivier Chateau who
supported me at every step of the experimental design, even though sometimes my ideas might have
been a bit crazy! I wish to sincerely thank Dr. Clarisse Majorel for her support during these years and
assistance during laboratory experiments. Finally, thanks to all the researchers of IRD research center
for always being helpful to me, and thanks to you Veronique Perrin for your constant help with
administrative paperwork, and your delicious desserts. Special thanks for colleagues Dr. Veronique
Berteaux-Lecellier and Dr. Gaël Lecellier who allowed me to find the site for the control sponge.
Thanks also to my co-authors and collaborators who helped me throughout my thesis and projects:
Mireille Pujo-Pay, Patrick Raimbault, James J. Bell, Lorenzo Bramanti, Carlo Cerrano, Philippe
Jourand, Pierre-louis Stenger, Barbara Calcinai, Andreas Ravache, Olivier Chateau, Megan Shaffer,
Hugues Lemonnier, Fanny Houlbreque, Francesca Benzoni, Claude Payri, and Jérome Aucan.
During my PhD I have the chance to meet some researchers and spent time with them during fieldwork. I would like to thank each of them for the inspiration and the good times spent together.

Thanks to Timothy Ravasi, Erina Kawai, Billy Moore, Greg Torda, Micheal Izumiyama, Celia Schunter, Sandra Ramirez Calero, Megan Shaffer, James J. Bell, Chris Cornwall. How amazing was the Supernatural 2 mission ? A memory I will have for a lifetime! I hope our collaborations, field trips, after-work drinks, and friendship will continue. Thanks also to Greg and Esme owners of "Chez Esme" in Bouraké, where I spent a lot of time during my fieldwork activity. Thanks for their hospitality, kind dinner and party during fieldwork, and of course the "kava" specialty!

A very special thanks go to my parents Marta e Dario for instilling in me the tenacity, drive, and motivation to get this completed, and for continuous encouragement. I know I have not always been very present, working on the other side of the world, but thank you for letting me live with my passion and making my own choices. Thanks also to my brother Filippo, who never often believed in me by giving me his continuous and fundamental moral support, and to my uncle Domenico for his support. Finally, thanks to Olivier, with whom I have been sharing my life for two years. Thank you for your support, positivity, patience, care, and love.

My experience in New Caledonia would have certainly been hard without the affection and support of my lab mates and friends (Cinzia, Thibault, Valentine and Clément), always ready for advice, 5 minutes of madness (well, maybe 15 minutes), a coffee break or a beer after work! Thanks also to the interns, the other PhD student became my friends and friends during these years (Camille, Laure, Maxime, Andreas, Tristan, Thomas, Nohé, Mahé, Magali, Sebastian, Hadrien, Laetitia, Perrine, Valentine, Hugo, Pauline, Hugo, Xavier, Juliette, Leo, Prisca). A special thanks also to my friends from Italy (Giulia, Giulia, Alice, Alice, Stefania, Alessandro, Federica, Enzo, Luca, Marika, and Davide), who despite the distance have always stayed by my side to listen and support me. This PhD would have been very hard without their infallible affection, morals, and smile.

Finally, I wish to express my sincere gratitude to my funding agency, the University of New Caledonia and "Ecole Doctoral du Pacific" which made this PhD possible through a Doctoral Scholarship. I would like also to thank the IRD center and Aquarium de lagoon for financial support during the field and experiments. Thanks to the 11th sponge scholarship supported my attendance at the 11th sponge conference in Leiden, where I meet all the amazing people of the sponge family.

Thank you to all to make this chapter of my life possible!

Tata
**Contributions and Publications**

The data chapters that make up this thesis are based on four manuscripts. Chapters 2 and 3 are published in *Biogeosciences* and *Marine Pollution Bulletin*, respectively. Chapter 4 was submitted on *Limnology and Oceanography* journal. A further method article was submitted for publication in *Limnology and Oceanography Methods* (see **Appendix B** – Section B3.1 for article details).

**Chapter 2:**

**Publication:** Maggioni F., Pujo-Pay M., Aucan J., Cerrano C., Calcinai B., Payri C., Benzoni F., Letourneur Y., and Rodolfo-Metalpa R. The Bouraké semi-enclosed lagoon (New Caledonia) – a natural laboratory to study the lifelong adaptation of a coral reef ecosystem to extreme environmental conditions. *Biogeosciences*, 18, 5117–5140, **2021**. https://doi.org/10.5194/bg-18-5117-2021

**Chapter 3:**

**Publication:** Maggioni, F., Bell, J. J., Pujo-Pay M., Shaffer M., Cerrano C., Lemonnier H., Letourneur Y., and Rodolfo-Metalpa R. Sponge organic matter recycling: Reduced detritus production under extreme environmental conditions. *Marine Pollution Bulletin*, 190: 114869, **2023**. https://doi.org/10.1016/j.marpolbul.2023.114869

**Chapter 4:**

**Publication under review:** Maggioni F., Raimbault P., Chateau O., Pujo-Pay M., Letourneur Y., and Rodolfo-Metalpa, Carbon and nitrogen recycling shift in warm-adapted sponges. *Limnology and Oceanography*.

**Additional method article:**

**Publication in preparation:** Maggioni F., Ravache A., Pecorari F., and Rodolfo-Metalpa R. Testing the performance of 3D photogrammetry to calculate underwater sponge volume. *Limnology and Oceanography Method*.

**Beside my thesis, three other publications resulting from side projects were written in these three years:**

**Publication under review:** Maggioni F., Stenger P. L., Jourand P., and Majorel C. The phylum Chloroflexi and their SAR202 clade dominate the microbiome of two marine sponges living in extreme environmental conditions. *Marine Ecology*.

**Publication under review:** Maggioni F., Stenger P. L., Jourand P., Letourneur Y., and Majorel C. Bioaccumulation of heavy metals in two marine sponges living in the Bouraké lagoon (New Caledonia). *MDPI metals*.

**Publication in preparation:** Stenger P. L., Maggioni F., Jourand P., and Majorel C. Selection of appropriate DNA markers to assess the hidden microbiome of marine sponges in a specific environment.
# TABLE OF CONTENTS

## Chapter 1: General introduction .................................................................................................................. 1

1.1 Climate change implications for coral reefs .................................................................................................................. 2

1.2 The sponge holobiont .................................................................................................................................................................................. 4

1.3 Ecological roles of sponges in coral reefs .................................................................................................................................................. 7

1.4 Impacts of climate change on sponges .................................................................................................................................................. 9

1.5 The natural laboratories .................................................................................................................................................................................. 11

1.6 Objectives of the study.................................................................................................................................................................................. 16

## Chapter 2: The Bouraké semi-enclosed lagoon (New Caledonia) – a natural laboratory to study the lifelong adaptation of a coral reef ecosystem to extreme environmental conditions. 19

### Résumé .................................................................................................................................................................................. 20

### Abstract.................................................................................................................................................................................. 23

2.1 Introduction .................................................................................................................................................................................. 25

2.2 Methods .................................................................................................................................................................................. 27

2.2.1 Study site .................................................................................................................................................................................. 27

2.2.2 Environmental monitoring.................................................................................................................................................. 28

2.2.2.1 Oceanographic sensors deployment and short- to long-term measurements ........................ 28

2.2.2.2 Phase averaged and tidal harmonic analyses for diurnal and semidiurnal oscillations .................................................................................................................................................................................. 29

2.2.2.3 Diel cycles of carbonate chemistry and chemical parameters ................................................................. 30

2.2.3 Benthic community characterization and distribution .................................................................................. 32

2.2.4 Stable isotopes analyses.................................................................................................................................................. 33

2.3 Results .................................................................................................................................................................................. 35

2.3.1 Variability of physical environmental parameters.................................................................................. 35

2.3.2 Diel cycles of carbonate chemistry and chemical parameters ................................................................. 42

2.3.3 Benthic community distribution and species identification.................................................................................. 45

2.3.4 Stable isotope signatures.................................................................................................................................................. 49

2.4 Discussion .................................................................................................................................................................................. 51

2.4.1 Physical and chemical characteristics of the Bouraké lagoon ................................................................. 51

2.4.2 Stable carbon and nitrogen isotope signature of the Bouraké lagoon .................................................. 54

2.4.3 Effects of physical and chemical conditions on species distribution ................................................................. 55

2.5 Conclusion.................................................................................................................................................................................. 60

## Chapter 3: Sponge organic matter recycling: reduced detritus production under extreme environmental conditions .................................................................................................................. 63

### Resumé .................................................................................................................................................................................. 64

### Abstract.................................................................................................................................................................................. 67
<table><tbody><tr><td>3.1 Introduction</td><td>68</td></tr><tr><td>3.2 Materials and methods</td><td>71</td></tr><tr><td>3.2.1 The sponge study model Rhabdastrella globostellata (Carter, 1883)</td><td>71</td></tr><tr><td>3.2.2 Experimental design</td><td>71</td></tr><tr><td>3.2.3 Incubation set up</td><td>72</td></tr><tr><td>3.2.4 Data collection</td><td>73</td></tr><tr><td>3.2.5 Seawater analyses</td><td>73</td></tr><tr><td>3.2.6 Data analysis</td><td>74</td></tr><tr><td>3.3 Results</td><td>75</td></tr><tr><td>3.3.1 Environmental conditions at the start of the dark incubations</td><td>75</td></tr><tr><td>3.3.2 Metabolic activities of the sponge holobiont in the dark</td><td>76</td></tr><tr><td>3.3.3 Sponge holobiont photosynthetic activity</td><td>81</td></tr><tr><td>3.4 Discussion</td><td>83</td></tr><tr><td>3.4.1 Changes in sponge organic matter recycling</td><td>83</td></tr><tr><td>3.4.2 Effect of extreme conditions on sponge holobiont nutrient recycling and feeding</td><td>86</td></tr><tr><td>3.4.3 Effect of extreme conditions on the sponge photosynthetic activity</td><td>88</td></tr><tr><td>3.5 Conclusion</td><td>89</td></tr><tr><td>Chapter 4: Carbon and nitrogen recycling shift in warm-adapted sponges</td><td>91</td></tr><tr><td>Resumé</td><td>92</td></tr><tr><td>Abstract</td><td>93</td></tr><tr><td>4.1 Introduction</td><td>94</td></tr><tr><td>4.2 Materials and methods</td><td>95</td></tr><tr><td>4.2.1 Samples collection and maintenance</td><td>95</td></tr><tr><td>4.2.2 Acclimatization and experimental set-up</td><td>96</td></tr><tr><td>4.2.3 Corals labelling</td><td>97</td></tr><tr><td>4.2.4 Transfer and incorporation of coral mucus to sponges</td><td>98</td></tr><tr><td>4.2.5 Organic matter and seawater chemical measurements</td><td>99</td></tr><tr><td>4.2.6 Isotopic analyses</td><td>100</td></tr><tr><td>4.2.7 Statistical analyses</td><td>101</td></tr><tr><td>4.3 Results</td><td>102</td></tr><tr><td>4.3.1 Environmental parameters</td><td>102</td></tr><tr><td>4.3.2 Carbon and nitrogen consumption and production</td><td>102</td></tr><tr><td>4.3.3 Sponges and detritus enrichment</td><td>105</td></tr><tr><td>4.3.4 <sup>13</sup>C and <sup>15</sup>N total fluxes and incorporation in the sponge tissue and detritus</td><td>106</td></tr><tr><td>4.4 Discussion</td><td>108</td></tr><tr><td>Chapter 5: General discussion</td><td>113</td></tr><tr><td>5.1 Rhabdastrella globostellata shows different strategies to cope with extreme environmental conditions</td><td>114</td></tr><tr><td>5.2 Bouraké sponges: a model of adaptation for future coral reefs?</td><td>119</td></tr></tbody></table>
<table><tr><td>5.3 Future perspectives</td><td>121</td></tr><tr><td>5.4 General conclusion</td><td>122</td></tr><tr><td><strong>References</strong></td><td><strong>125</strong></td></tr><tr><td><strong>Appendices</strong></td><td><strong>150</strong></td></tr><tr><td>Appendix A</td><td>151</td></tr><tr><td>Appendix B</td><td>164</td></tr><tr><td>Appendix C</td><td>184</td></tr><tr><td><strong>French summary - résumé</strong></td><td><strong>190</strong></td></tr><tr><td><strong>Italian summary - sintesi</strong></td><td><strong>214</strong></td></tr></table>
reef (St A-C); (b) between the inner and the outer reefs (St B1, B2); (c) between the outer reef (but still inside the Bouraké lagoon), and the reef outside the semi-enclosed lagoon (St U vs T). Depth-related variations were assessed between shallow reefs and the bottom of the channel: (d) at the inner reef (St R); and (e) at the outer reef (St S). Tide (black line) refers to St B2. 39

**Figure 2.6.** Spatial and depth-related short-term measurements (24 h) of dissolved oxygen (DO) at stations in the Bouraké lagoon (see Figure 1 for the location of the stations). Spatial variations were assessed on (a) the inner reef (St A-G), (b) the middle reef (St H-N), and (c) the outer reef (St O-Q). Depth-related variations between shallow reefs and bottom water within the Bouraké lagoon were assessed (d) at the inner reef (St R) and (e, f) at the middle reef (St I and N). Tide (black line) refers to St B2. 41

**Figure 2.7.** Short-term salinity monitoring during (a) the winter of 2019 (from 15/07/2019 to 18/07/2019) at the reference (St R1 and R2) and Bouraké reefs (St B1 and B2); (b) the summer of 2020 (from 29/11/2020 to 04/12/2020) at the reference (St R1 and R2) and Bouraké reefs (St T and B2). Tide (black line) refers to St B2. 42

**Figure 2.8.** Seawater carbonate chemistry measured (pH<sub>T</sub>) and calculated (DIC and Ωara) during diel cycles in 2017 and 2019 (pooled data, see also Appendix A Figure A2.1.) at R1, R2 and the Bouraké reefs (outer, middle and inner) (a-c). Boxes (n = 6-14) represent the interquartile range (25th and 75th percentile); the horizontal line is the median, and the whiskers represent the data range (i.e., minimum and maximum). Changes are illustrated across a 12 h tidal phase in the Bouraké lagoon (d-f). Linear regression lines are plotted for each falling (HT to LT) and rising tide (LT to HT). Shaded boxes have only a graphical significance and only suggest the tide changes during measurements. 43

**Figure 2.9.** Orthosilicic acid, organic carbon and nitrogen parameters measured during diel cycles in 2017 and 2019 (pooled data, see also Appendix A Figure A2.2.) at R1, R2 and the Bouraké reefs (outer, middle and inner) (a-d). Boxes (n = 6-14) represent the interquartile range (25th and 75th percentile); the horizontal line is the median, and the whiskers represent the data range (i.e., minimum and maximum). Changes are illustrated across a 12 h tidal phase in Bouraké (e-h). Linear regression lines are plotted for each falling (HT to LT) and rising tide (LT to HT). Shaded boxes have only a graphical significance and only suggest the tide changes during measurements. 45

**Figure 2.10.** Benthic community and bottom substrate characterization in the Bouraké lagoon. Hierarchical Ward's method cluster dendrogram (top) and non-metric multidimensional scaling (nMDS) of abiotic and biotic percent cover and species richness per transect (T1-T24) (a). Colored circles represent clusters of transects identified in the dendrogram; circle size corresponds to species richness. Ellipses represent 95% confidence intervals. Dominant biotic and abiotic descriptors were used to describe the benthic community and bottom substrate for each cluster in (b). The satellite image is from georep New Caledonia database (https://georep.nc/), and the QGis software was used for transect georeferencing. 47

**Figure 2.11.** Principal component analysis (PCA) between benthic community (macroalgae, sponges, corals, branching corals and massive corals) data and environmental parameters (PON, POC, DOC, Si(OH)<sub>4</sub>, PO<sub>4</sub><sup>3-</sup>, NOx, and NH<sub>4</sub><sup>+</sup>) measured for each transect (n = 24). The length of the vectors indicates the contribution of each parameter. The first dimension explains 48.1% of the variance, and the second dimension explains 23.1% of the variance. Colours refer to the cluster subdivision (Figure 2.10). 48
**Figure 2.12.** Plot of δ¹³C versus δ¹⁵N (mean ± SD when more than 1 sample) of macroalgae, sponges, fish, mangrove leaf and seagrasses collected at Bouraké outer (B02), Bouraké inner (B05), and Reference site (R1). Label with * refer to sample collected in March 2019, while the other were collected in December 2020. 49

**Figure 3.1.** Dissolved oxygen consumption measured during the incubations in the dark in 2018 (in gray) at both LT (n = 9) and HT (n = 12), and 2020 (in blue) at both HT (n = 24) and LT (n = 28). Boxes are the interquartile range of data (25th and 75th percentiles); the horizontal line is the median, and the whiskers represent the data range (i.e., minimum and maximum). 76

**Figure 3.2.** Sponge nutrients and organic matter consumption/production measured during the incubations in the dark at HT and LT in 2018 and 2020. (a) Si(OH)₄, (b) NOx, (c) PO₄³⁻, (d) NH₄⁺, (e) Dissolved Organic Carbon (DOC), (f) Particulate Organic Carbon (POC), (g) Dissolved Inorganic Carbon (DIC), and (h) Bacteria abundance. Data are the difference between the beginning and the end of the incubations. Boxes represent the interquartile range (25th and 75th percentile); the horizontal line is the median, and the whiskers represent the data range (i.e., minimum and maximum). 78

**Figure 3.3.** Sponge consumption/production measured during the incubations in the dark at HT and LT in 2020. (a) Detritus (POC-LPOC), (b) phytoplankton abundance, (c) Life Particulate Organic Carbon (LPOC). Data are the difference between the beginning and the end of the incubations. Boxes represent the interquartile range (25th and 75th percentile); the horizontal line is the median, and the whiskers represent the data range (i.e., minimum and maximum). 79

**Figure 3.4.** Principal Component Analyses (PCA) on the parameters measured in the incubation medium (a) in 2018, (b) in 2020 at both HT and LT. Each dot in red indicates one single sponge incubation metabolism made during HT, while triangles in blue indicates incubations during LT. Arrows indicate the variable and their length approximates the variance of the variables. The ellipses represent the 95% interval confidence. Large triangles or dots indicate multiple incubations at the same point. 80

**Figure 3.5.** Principal Component Analyses (PCA) on Spearman correlation matrix on data collected in 2020 between the seawater chemical parameters measured at the beginning of the incubations, and the absolute values of their changes (i.e., consumption and production) during the incubations. Each dot indicates the sponge metabolism parameters while arrows indicate the variable, and their length approximates the variance of the variables. 81

**Figure 3.6.** Generalized additive models (GAM) on (a) relative ETR (rETR) and (b) the effective quantum yield (Fv/Fm) versus irradiance (PAR). Data were obtained from dark-adapted sponges during the ex-situ incubations in 2020 under high tide (HT; n = 9 red) and low tide (LT; n = 9 black) conditions. The shaded areas indicate the 95% confidence intervals of the GAM model. Individual measurements were also reported. 82

**Figure 4.1.** Map of New Caledonia (top panel) with the two study sites and pictures of the fragments of *Rhabadastrella globostellata* freshly transplanted at the control site (Tupeti Island, A), and after one month in-situ in the Bouraké lagoon (B). Within A and B, a graph reports a typical temperature variation measured during the summer at each study site. Georep New Caledonia database
(https://georep.nc/, last access: November 2022) and Qgis software were used to build the figures.
..................................................................................................................................................96

**Figure 4.2.** Sponge dissolved organic carbon (DOC) and detritus consumption, and production during the incubations at 28°C and 32°C for both sponges from Bouraké and Control site (Tupeti). Boxes are the interquartile range of data (25th and 75th percentiles); the horizontal line is the median, and the whiskers represent the data range (i.e., minimum and maximum). .................................................. 104

**Figure 4.3.** Carbon source uptake (%) by the sponge at 28°C and 32°C from Bouraké and Control (Tupeti) sites. Only consumed values (negative values) of bacteria, dissolved organic carbon (DOC), phytoplankton and particulate organic carbon (POC) as sources of carbon were considered. ........ 105

**Figure 4.4.** Stable isotope enrichment of ¹³C and ¹⁵N in sponge tissue (a-b) and detritus (c-d) after 4 and 8 days of experiment, at 28°C and 32°C, for both sponges from Bouraké (dots) and Control (triangles). Non-enriched stable isotope signature as also reported as CTRL (square). Data as expressed as isotope tracer enrichment Δδ¹³C (‰) and Δδ¹⁵N (‰). Note that detritus enrichment was calculated on a day basis. .................................................................................................................. 106

**Figure 4.5.** Sponge tissue and detritus incorporation of ¹³C (a) and ¹⁵N (b) at 28°C and 32°C, for both sponges from Bouraké and Control site (Tupeti). Daily incorporation rates (mean ± SD) of coral mucus are expressed in µmol C or N g⁻¹ d⁻¹. .................................................................................................................. 108

**Figure 5.1.** Synthetic scheme of the main strategies used by the Bouraké sponge *R. globostellata* to cope (i.e., adaptive response) with a change in temperature. .................................................................................. 117
LIST OF TABLES

**Table 2.1.** Summary of the statistical analyses applied to the seawater physical and chemical parameters collected between 2016 and 2020 at the Bouraké lagoon (St B1, B2, St A-R, outer, middle and inner) and at reference reefs (St R1 and R2). Differences in temperature, salinity and chemical parameters between the Bouraké lagoon and reference reefs and spatial and vertical differences in pH and DO inside the Bouraké lagoon. K-W: Kruskal-Wallis's test; W: Wilcoxon test; GLM: General Linear Model; D: Dunn's test; T: Tukey's test; C: Conover's test. 37

**Table 2.2.** Summary of the seawater physical and chemical data (mean ± SD) measured in July 2017 and June 2019 and calculated using the CO2SYS package. Data were pooled and averaged per station. nd = not determined. Reference reefs: St R1 and R2; Bouraké lagoon stations: outer, middle and inner. 44

**Table 2.3.** Summary of isotopic signature (mean ± SD, when more than 1 sample) in carbon (δ¹³C ‰) and nitrogen (δ¹⁵N ‰) for macroalgae, fish, sponges, mangrove leaf and seagrasses collected in March 2019 (Mar-19) and December 2020 (Dec-20) at R1, Bouraké outer (B02), and Bouraké inner (B05). 50

**Table 3.1.** Summary of the environmental parameters measured at the beginning of the incubations in 2018 and in 2020, both at HT and LT. Data are expressed as mean ± SD; number of replicates are in brackets; nd means not determined. 75

**Table 3.2.** Summary of the gross photosynthesis (P<sub>g</sub>), respiration (R<sub>dark</sub>), and their ratio (P:R) measured in-situ, and the initial photosynthetic efficiency (F<sub>v</sub>/F<sub>m</sub>) and rETR<sub>max</sub> measured ex-situ. For in-situ, n = 9 and n = 8 at HT and LT, respectively; and for ex-situ, n = 9. Data are normalized and expressed as mean ± SD. 82

**Table 4.1.** Summary of two-way ANOVAs between temperature conditions (two levels, constant and variable), origin (two levels, control and Bouraké), and their interaction. a) the carbon and nitrogen consumption and/or production measured during 3h of incubation; b) carbon sources consumed during the incubations (only data showing carbon consumption were included); c) ¹³C and ¹⁵N enrichments (Δδ¹³C and Δδ¹⁵N) measured on both the sponge tissue and detritus at the end of incubations; d) ¹³C and ¹⁵N incorporation measured on both tissue and detritus; and e) ¹³C:¹⁵N ratio. When the interaction was significant, a Tukey HSD test was applied. B. is Bouraké and C. the control at 32°C and 28°C. 103
# CHAPTER 1:
GENERAL INTRODUCTION
## 1.1 Climate change implications for coral reefs

Greenhouse gas emissions such as carbon dioxide or methane from human activities directly impact all ecosystems by altering the composition of communities and threatening species persistence (Chapin et al., 1997; Dinerstein et al., 2019). Atmospheric carbon dioxide (CO₂ atm) is now 50% higher than pre-industrial levels exceeding 400 ppm (NOAA Mauna Loa website: http://www.esrl.noaa.gov/gmd/ccgg/trends/mlo.html). It is expected to increase at unprecedented rate reaching 1000 ppm by 2100 if no additional efforts are made to moderate greenhouse gas emissions (IPCC, 2014). It is estimated that, of the approximately 350 billion tons of CO₂ that have been already emitted into the atmosphere, 25% has already been absorbed by the ocean (Canadell et al., 2007; Le Quéré et al., 2010; Heinze et al., 2015; Cao and Zhang, 2017). The CO₂ absorbed in seawater causes an increase in the partial seawater pressure of CO₂ (pCO₂) and forms carbonic acid (H₂CO₃), which is unstable and dissociates into hydrogen (H⁺) and bicarbonate (HCO₃⁻) ions and, at a lower rate, carbonate ions (CO₃²⁻). The increase in H⁺ affects the water chemistry causing an acidification shift in seawater (e.g., Caldeira and Wickett, 2003; Raven et al., 2005) and a decrease in the pH of the upper layers of the world's oceans (Pörtner and Farrell, 2008). This phenomenon is called ocean acidification (OA) (i.e., Langdon and Atkinson, 2005). Currently, the surface ocean pH ranges on average between 7.9 and 8.2 (Takahashi et al., 2014). The shift in the carbonate chemistry of the ocean has significant implications for marine organisms including reduced calcification rates and disruptions of acid-base physiology, causing general negative impacts on organism physiology, survival and ecosystem functioning (Fabry et al., 2008; Pörtner, 2008). Rising CO₂ atm has increased global surface temperatures by ~0.2°C per decade over the past 30 years (Hansen et al., 2006). Oceans absorb a significant amount of this excess energy (Hoegh-Guldberg and Bruno, 2010). The Intergovernmental Panel on Climate Change (IPCC) predicts that ocean warming (OW) resulting from this rising atm CO₂ will cause an increase in the sea surface temperatures of 1.1°C to 3.0°C by the end of the century (IPCC, 2014). Organisms are acclimated to a range of temperatures, and, outside these optimum temperatures, biological processes are likely to be compromised, resulting in changes in individual metabolism, population survival, and species persistence (Hoegh-Guldberg and Bruno, 2010). Organisms' optimum temperatures drive the large-scale geographical distributions of marine organisms (Pörtner, 2008). Ocean warming also influences oceanic processes such as ocean mixing (Manucharyan et al., 2011) and ocean current dynamics, contributing to seawater's oxygen depletion (Winton et al., 2013). This phenomenon is called ocean deoxygenation (OD) (Shaffer et al., 2009), and impacts fundamental ecological processes. According to the IPCC (2014), dissolved oxygen (DO) will decrease by 2% to 4% by the end of the 21st century for the RCP 2.6 and RCP 8.5 scenarios, respectively (**Box 1 for RCP details**).
**Box 1: What are scenarios and RCPs? (Source: IPCC website glossary)**

In the context of the IPCC, scenarios aim to explore possible future pathways of GHG (Greenhouse gases) emissions, their main driving forces, and how they might be affected by policy interventions (IPCC, 2007). Based on these factors, four different 21st century pathways, the so-called “representative Concentration Pathways” (RCPs), are used for making projections of GHG emissions and atmospheric concentrations, air pollutant emissions and land-use (IPCC, 2007). The RCPs include a stringent mitigation scenario (RCP 2.6), two intermediate scenarios (RCP 4.5 and RCP 6.0), and one scenario with very high GHG emissions (RCP 8.5). Numbers correspond to the radiative forcing peaks of 3 W m⁻², 4.5 W m⁻², 6.0 W m⁻², and 8.5 W m⁻². By the end of the 21st century, in the worst-case scenario (RCP 8.5), pH is projected to decrease (in pH units) by 0.29 ± < 0.005, sea surface temperature (SST) is projected to increase by 2.39 ± 0.50°C, and oxygen concentrations averaged over 100-600 m depth are projected to decrease by 6.98 ± 1.02 mmol m⁻³ (IPCC, 2007). Those oxygen units are equivalent to µmol L⁻¹ and ~µmol kg⁻¹ (Box Figure 1.1).

<figure><img src="image_4.png" /><figcaption>**Box Figure 1.1.** Time series and spatial patterns of simulated change in surface pH, sea surface temperature (°C), and oxygen concentration (mmol m⁻³) averaged over 100 to 600 m depth. Simulated spatial patterns of multi-model mean changes in year 2095 for the (middle column) RCP 8.5 scenario and right column RCP 2.6 scenario (From Laffoley, D. and Baxter, 2019).</figcaption></figure>
These three main effects of climatic change (i.e., OA, OW, and OD) have impacts on reef structures and communities with consequences spanning from ecosystem shift to biodiversity loss (e.g., Fabricius et al., 2013; Sunday et al., 2017; Agostini et al., 2018). Reported acidification effects ranges from changes in cellular metabolism and organism physiology to population and ecosystem-level dynamics (Gattuso and Hansson, 2011). A decrease in the complexity, extent and species richness of biogenic reefs in all the biogeographic regions of the World was also reported as a consequence of OA (Hall-Spencer and Harvey, 2019). The OW has been demonstrated to cause shifts in species distribution, mass mortalities, reduction in ocean productivity, disruption in food web dynamics, and decline in habitat-forming species (e.g., Pörtner and Farrell, 2008; Hoegh-Guldberg and Bruno, 2010; Byrne and Przeslawski, 2013). Finally, OD has widespread effects on marine life, causing changes in the physiology of marine organisms (Seibel, 2011; Somero, 2015) and habitat reduction (Prince and Goodyear, 2006; Stramma et al., 2012). Although corals are the most studied organisms, when we want to study the effects of climate change on the coral reef ecosystem, we must consider other less studied organisms, such as sponges, whose role in the reefs' ecological processes is particularly relevant.

## 1.2 The sponge holobiont

Sponges are the most ancient multicellular animals on Earth and the oldest metazoan group still extant on our planet (Li et al., 1998). They are the exclusive representatives of the phylum Porifera, which is divided into four classes: Calcarea, Hexantinellida, Homoscleromorpha and Demospongiae, with 83% of all known sponges belonging to the latter class (van Soest et al., 2012). Sponges have a simple level of organization since they are deprived of organs but have specialized cells with various life functions.

The sponge body architecture is arranged around the aquiferous system (Figure 1.1), which consists of a network of channels and chambers with flowing ambient water supporting sponge feeding. The sponges are made up of an external layer of flat cells called pinacocytes (external epithelium, pinacoderm), which isolates the sponge's internal structure (mesohyl) from the external environment, and an inner layer of flagella-bearing cells called choanocytes (internal epithelium, choanoderm), which generate the water currents necessary for filtering seawater. The pinacoderm present small inhalant apertures (ostia) and larger exhalant apertures (oscula) for the water flow (Figure 1.1).
<figure><img src="image_5.png" /><figcaption>**Figure 1.1.** Schematic representation of a sponge with pinacocytes (external epithelium, Pinacoderm), choanocytes (internal epithelium), the mesohyl with spicules and Amoebocyte cells. Arrows indicate the direction of water flow (modified from istockphoto.com).</figcaption></figure>

The aquiferous system is involved in the production and maintenance of water current flow within the sponge body. Its functional role is to support sponge feeding (pinocytosis/phagocytosis) and allow excretion and O₂/CO₂ exchanges (by simple diffusion). The direction of ambient water flow is from dermal pores through an ostia canal to a choanocyte chamber, and then out an osculum canal (Figure 1.1). The mesohyl includes an extracellular matrix with jelly consistency, collagen fibrils and fibers, skeletal structures with mineral deposits (spicules), and cells (i.e., amoebocyte). Most body cells are totipotent, with a high degree of mobility and morpho-functional plasticity (De Vos et al., 1991). In the mesohyl, archeocytes cells are involved in food particle digestion via phagocytosis. These totipotent cells are capable of differentiating into any sponge cell type. The sponge skeleton is made of organic and inorganic materials that form a scaffold-like framework, which supports the various cell types. The organic material is composed of collagen microfibrils, which are referred to as spongin in demosponges. The inorganic materials increase stiffness and are composed of either silica (SiO₂) or calcium carbonate (CaCO₃). The distinction between the two inorganic materials has important taxonomic and phylogenetic consequences. Sponges belonging to the Class Demospongiae and Hexactinellida produce siliceous spicules with some exceptions in demosponges. For example, the Dictyoceratida have lost the inorganic component of the skeleton, while the Calcarea produce calcitic spicules forming the skeleton (Hill and Hill, 2009).

Sponge species have been reported to grow in distinct sizes and shapes due to the form of internal mineral and/or organic skeletons secreted by specialized cells. The shapes of sponges may vary between species and genera, mainly in response to environmental factors such as hydrodynamics,
light, and turbidity. For example, globular and fistular sponges are usually abundant in an environment with high sediment deposition, while sponges with much horizontal surface area often exclude in fine sediment deposition (Schönberg, 2021) (Figure 1.2).

This simple yet effective way of life has undoubtedly helped the persistence of sponges through historical mass extinction events, allowing them to persist today within benthic ecosystems of all aquatic (and mainly marine) environments, spanning temperate, tropical, and polar habitats (van Soest et al., 2012). Their survival under this extensive range of conditions is also due to their associated microbial communities. All macro-organisms (i.e., metazoans, fungi, plants, and algae) are associated with microbial communities and are called holobionts, which refers to a complex system consisting of the host, the microbiota, and the interactions among them (Pita et al., 2018). The microbial partners contribute to the nutrition (Nicholson et al., 2012), defense (Flórez et al., 2015), immunity (Eberl, 2010), and/or development (Koropatnick et al., 2004) of the host.

<figure><img src="image_6.png" /><figcaption>**Figure 1.2.** Example of different sponge morphologies based on environmental conditions (from Schönberg, 2021).</figcaption></figure>

Marine sponges perfectly illustrate the idea of holobionts, given the exceptionally diverse microbial communities (about 40,000 operational taxonomic units or OTUs) housed within them (Thomas et al., 2016; Moitinho-Silva et al., 2017a). The sponge holobiont can be categorized into two nutritional types based on the sponge association with phototrophic (i.e., more than 50% of energy requirements are acquired from photosynthetically fixed carbon) or heterotrophic symbionts (i.e., primarily reliant on filter-feeding for carbon requirements, Cheshire and Wilkinson, 1991). Based on the abundance
and diversity of microbes in tissues, sponges can be classified into high microbial abundance (HMA) or low microbial abundance (LMA) sponges. For example, the HMA sponges can contain 10¹⁰ bacterial cells/g wet weight of sponge, which is 2-4 orders of magnitude higher than surrounding seawater (Hentschel et al., 2006). Sponges are efficient filter feeders vital to the health of all marine systems by linking nutrients of the open water column to benthic communities. Their wide distribution and often biomass dominance, besides their important functional roles, mean that their contribution to ecosystem functioning should not be overlooked, as their ecological role in the global ecosystem is likely higher than previously thought (Bell, 2008).

## 1.3 Ecological roles of sponges in coral reefs

Sponges play an essential ecological role in the marine environment (Diaz and Rützler, 2001; Wulff, 2001; Bell, 2008). Although some rare sponge species are carnivorous (e.g., Chevaldonné et al., 2015), the vast majority are filter-feeding organisms, feeding primarily on nano- and picoplankton and heterotrophic bacteria in the water column. In addition, they also uptake dissolved organic carbon (DOC) and can contribute considerably to organic production in oligotrophic habitats (Reiswig, 1971; Riisgard et al., 1993; De Goeij et al., 2013; Hoytema et al., 2023). Consequently, sponges influence ecosystem functions by modifying biotic and abiotic factors (Bell, 2008) and are considered key ecosystem engineers for efficiently retaining, transforming, and allocating the nutrients and energy needed by coral reef ecosystems. Indeed, sponges have been reported to play a key role in benthic-pelagic couplings through complex biogeochemical processes, such as the carbon cycle (e.g., Maldonado et al., 2012; Mueller et al., 2014; Cathalot et al., 2015), the nitrogen cycle (e.g., Jiménez and Ribes, 2007; Maldonado et al., 2012; Fiore et al., 2013), the silicate cycle (e.g., Maldonado et al., 2005; Chu et al., 2011), and the phosphorus cycle (e.g., Maldonado et al., 2012; Colman, 2015).

In coral reef ecosystems, the largest available organic matter pools in seawater is in the form of dissolved organic matter (DOM). However, DOM remains largely inaccessible to most reef fauna (Benner et al., 1992). Bacterioplankton is known to process DOM and then return it to the classic food chain through planktonic grazing, a pathway known as the microbial loop (Azam et al., 1983). Essentially, by consuming DOM, bacteria remineralize nutrients that would otherwise be lost to the environment (Fenchel, 2008). In shallow tropical water, a similar DOM recycling pathway called the “sponge loop” was hypothesized by De Goeij et al. (2013). In the sponge loop, sponges transform DOM into a more readily available food source for other benthic reef fauna. Sponges convert DOM released by primary producers into particulate organic matter (POM) in the form of detritus and is more readily accessible to most sponge detritus-feeding associated fauna (e.g., De Goeij et al., 2013; Alexander et al., 2014; Rix et al., 2017; Archer et al., 2017). However, no detritus production has
been found for several massive sponges for which an alternative sponge-loop pathway was
hypothesized. In this alternative pathway, it has been hypothesized that sponge-assimilated DOM is
transferred to higher trophic levels *via* direct predation on sponge tissue (Figure 1.3) (e.g., Pawlik et
al., 2016; McMurray et al., 2018; Pawlik and McMurray, 2020). Predators reported for sponges are
spongivory fishes (e.g., angelfishes, parrotfishes, filefishes, and trunk-cowfishes), sea turtles,
nudibranch, and starfish (Wulff, 1994; Pawlik, 1998; Wulff, 2006).

<figure><img src="image_7.png" /><figcaption>**Figure 1.3.** Cycling of dissolved organic carbon (DOC, blue), dissolved inorganic nitrogen and nutrients (DIN, green), and detritus (black) in Caribbean fore-reef environments (Pawlik and McMurray, 2020). The consumption of component organisms is shown in red. This figure summarizes essential components of the sponge loop (De Goeij et al., 2013) and the direct predation on sponge tissue (Pawlik et al., 2016; Mumby and Steneck, 2018). Evidence for seaweed production of labile DOC (1), which forms a major component of the diet of sponges (2), along with detritus (3). While the sponge-loop hypothesis proposes the transformation of DOC as detritus by cryptic sponges (4), this does not occur for emergent sponges, which return DOC to the ecosystem as food for spongivores (5) (Pawlik and McMurray, 2020).</figcaption></figure>

The assimilation of DOC by sponge holobionts is supported mainly by the sponge itself (De Goeij et al., 2013; Rix et al., 2016; 2017), accounting for up 90% of the holobiont's total heterotrophic carbon uptake (Yahel et al., 2003; Hoer et al., 2018); the remainder is due to the microbes associated with the sponge. Through these two pathways, sponges contribute to the control of the marine top-down (Pawlik et al., 2013), such as sponge predation, and bottom-up, such as food availability in the coral reefs (Lesser and Slattery, 2013).
Another important role of sponges is their impact on benthic substrates. Both bioeroders and consolidators/stabilizers are important roles that sponges can play in tropical environments and, in some cases, even temperate regions (Cebrian and Uriz, 2006). For example, studies have shown that some sponges contribute to the consolidation of the reef structure by binding corals to the reef and discouraging excavation by other organisms (Wulff, 2001), thereby increasing coral survival. In addition, sponges provide important microhabitats for coral reef organisms (Bell, 2008) and often host a significant diversity of crustaceans, mollusks, bryozoans, polychaetes, cnidarians, echinoderms, and even fish. Finally, various chemical and physical adaptations make sponges efficient competitors for space in reef ecosystems (Hill, 1998; Diaz and Rützler, 2001, Rützler, 2002). Despite the fundamental role of sponges in coral reefs, most studies are focused on stress response/tolerance to future environmental conditions (e.g., Bennet et al., 2017; Bell et al., 2018a; 2022) rather than ecological processes, such as carbon and nutrient cycling. Therefore, filling these gaps and understanding how future conditions may affect their role in the entire reef becomes important.

**1.4 Impacts of climate change on sponges**

Sponges are both winners and losers in future climate scenarios with species-specific responses. Some studies identified sponges as more tolerant to OW and OA than several other benthic groups, and they likely will benefit from changing ocean conditions through increased productivity and reduced spatial competition (Bell et al., 2013; 2018b). Globally, there have been numerous reports of increased sponge abundance on coral reefs as the coral cover has declined (i.e., Aronson et al., 2002; McMurray et al., 2010; Bell et al., 2013; Kelmo et al., 2014). In the Caribbean, the giant barrel sponge *Xestospongia muta* has increased up to 50% in some reefs since 2000, while the mean coral cover has decreased (McMurray et al., 2010). Contrary to reef-building corals, in which all species rely primarily upon photosynthetic dinoflagellates to satisfy nutritional requirements (Muscatine and Porter, 1977), not all sponges are phototrophic (Taylor et al., 2007). Phototrophic sponges comprise only half of the total sponge biomass on the outer reefs of the Great Barrier Reef (Taylor et al., 2007), and slightly lower percentages of phototrophic species have been reported on Caribbean reefs (Vicente, 1990). This suggests that the impacts of OW and OA may be less important on the sponges' metabolism than for corals. Studies assessing the combined effects of OW and OA have predominantly focused on the response of bioeroding sponge species, such as *Cliona celata* (Duckworth and Peterson, 2013), *C. orientalis* (Fang et al., 2013; Wisshak et al., 2012) and *C. varians* (Stubler et al., 2015). For instance, sponge bio-erosion rates have been reported to increase by 17% and 61% under future OW and OA scenarios compared to present-day conditions (e.g., Wisshak et
al., 2012; Duckworth and Peterson, 2013; Fang et al., 2013). Studies on non-bioeroding sponges also suggest a degree of sponge tolerance to the effects of mainly OA and OW (Duckworth et al., 2012; Lesser et al., 2016; Vicente et al., 2016). Research exposing six sponge species to OW and OA conditions suggested no impact on growth, survival, or secondary metabolite biosynthesis (Duckworth et al., 2012). Furthermore, OW and OA have only marginal negative effects on spicule biomineralization and little effects on the overall survival or growth rates of the Hawaiian sponge *Mycale grandis* (Vicente et al., 2016).

Several authors have reported the positive effects of OA on sponges. For example, Wisshak et al. (2012) found an increase in bioerosion rates of up to 61% in *Cliona orientalis* exposed to experimentally manipulated seawater (pH 7.9 and 7.6). Both Goodwin et al., (2014) and Morrow et al., (2015) reported high tolerances of some sponge species to low pH near volcanic CO₂ vents. In these studies, the two sponges *Coelocarteria singaporensis* and *Cinachyra* sp. showed an increase in photosynthetic microbial activity, providing nutritional benefit to the sponge, and increased potential for growth under future climate scenarios (Morrow et al., 2015). A general tolerance to reduced pH was also reported in New Zealand for temperate sponges exposed to a range of pH (7.6-8.0) for four weeks (Bates and Bell, 2018). Overall, sponges appear generally insensitive to OA (Leung et al., 2022), and their responses to elevated pCO₂ are species-specific. The fitness and success of the host could also be due to the stability and flexibility of the microbial partnerships (Morrow et al., 2015).

In contrast, a decline in sponge abundance was also reported (e.g., Cebrian et al., 2011; Goodwin et al., 2014). The combined effects of OW and OA on *Xestospongia muta* have shown that the phototrophic cyanobacterial symbiont productivity declines with exposure to elevated temperature and pCO₂. However, no evidence of associated host stress was reported and this despite a reduction in both holobiont carbohydrate levels and stability of the sponge microbiome (i.e., β-diversity) (Lesser et al., 2016). A study on the effects of OA in sponges reported that the percentage of sponge cover decreases significantly at volcanic CO₂ vents (Fabricius et al., 2011). Since OA has been shown to affect most species with carbonate skeletons, directly altering their calcification and increasing dissolution, only sponges of the class Calcarea, which have calcium carbonate skeletons and represent 8% of all sponges (van Soest et al., 2012), will likely be affected. However, it is also hypothesized that OA can impact more dominant species with siliceous skeletons because sponges have a limited ability for acid-base regulation (Philp, 1997; Pörtner, 2008). Studies focusing exclusively on the effects of OW have demonstrated that some sponges are sensitive to temperature predicted under future climate change scenarios. For example, the Great Barrier Reef sponge *Rhopaloides odorable* has a thermal threshold of 32°C (Webster et al., 2008; Pantile and Webster, 2011; Massaro et al.,
2012) when host-symbiont molecular interactions start to breakdown, eventually leading to death (Fan et al., 2013). In addition, some sponge disease outbreaks have been correlated with elevated seawater temperatures (Sutherland et al., 2004). In the Mediterranean, several reports of sponge loss have been caused by increased sea temperature (Cerrano et al., 2000). Recent work has also shown that *Cliona* sp. cannot survive ocean temperatures projected for 2100 (Achlatis et al., 2017; Ramsby et al., 2018b).

Depending on local environmental characteristics, species-specific responses, and the environment in which the sponge lives, sponges could be advantaged or disadvantaged in a future coral reef. For a scenario where sponges will become dominant on the reef, the balance between accretion and erosion of the reef will be altered, especially considering that both abundances of bio-eroding sponges and bio-erosion rates would increase at higher *pCO*₂ (e.g., Wisshak et al., 2014). However, while sponge reefs might still provide some three-dimensional habitat, the overall complexity will be considerably reduced, which may drastically reduce the overall biodiversity (Bell et al., 2013). Future reefs, dominated primarily by sponges, would also cause the benthic community to shift from primarily comprised of phototrophic organisms to predominately heterotrophic species (Bell et al., 2018a). Initially, this would impact the organisms that are obligate coral feeders (Pratchett et al., 2006) or taxa that rely on coral-derived DOM and/or POM (Wild et al., 2004). However, it is possible that these species could acclimatize to utilize exclusively DOC from increased microalgae production. In general, coral reefs are complex systems, and it is difficult to accurately predict how a reef might function if sponges become the dominant fauna. However, increased sponge abundance is likely to directly influence some key processes, such as bio-erosion and water filtering (including nutrient and carbon cycling), which are the most important functional roles of sponges on reefs (Bell, 2008), and both are predicted to increase in sponge-dominated systems. In contrast, if sponges decline in future coral reefs, important players in carbonate balance and coral reef health will disappear (reviews in Diaz and Rützler, 2001; Wulff, 2001).

Despite the ecological importance of sponges, little is known about the effects of environmental changes and adaptive sponge capacities to cope with changing ocean conditions. Most studies rely on replicating these conditions in controlled environments and/or assessing these parameters separately, which gives an unrealistic view of the response of organisms to the multiple effects of climate change occurring concurrently in their natural environments.

**1.5 The natural laboratories**

Climate change effects (warming and acidification) have been studied over the past 15 years, mainly in the laboratory (in vitro), where it has been possible to consider the effect of individual parameters
and controlled conditions over time. *In vitro* experiments have been fundamental to understanding how reef organisms might respond to future climates. Advantages of using aquaria include the possibility of studying one factor at a time, the possibility of changing several parameters under time-controlled conditions, and the possibility of repeating experiments. However, it is impossible to replicate the complex ecological and biogeochemical interactions that govern coral reef systems using aquaria, especially if co-limiting factors such as nutrients, currents, and irradiance are considered. Furthermore, some experiments can be difficult to simulate (Atkinson and Cuet, 2008), and most are too short for complete acclimatization of the organisms to take place.

The discovery of these natural laboratories, where organisms are already living under future-like conditions, makes it possible to study the multiple long-term effects of future climate change conditions directly *in-situ* in the context of natural variability. These natural sites are becoming important tools to study the actual response of organisms exposed to future-like conditions during their whole life. Studies of populations or communities that persist under extreme and marginal physical and chemical conditions in nature have thus become increasingly popular for ecosystem-scale predictions of future coral reefs. Here, an extreme environment is referred to as a habitat characterized by harsh environmental conditions beyond the optimal range for the development of organisms as reviewed by Camp et al., (2018).

Natural laboratories such as shallow-water volcanic CO₂ seeps, low-pH upwelling areas, mangrove habitats and semi-enclosed bays are study systems where the surrounding seawater is subjected to a localized or widespread increase in either *pCO₂* and/or temperature, and in some cases decrease in dissolved oxygen (Camp et al., 2018) (Figure 1.4). For example, around CO₂ vents, the community structure changes, and only some acidification-tolerant species thrive in the presence of high *pCO₂* (e.g., Hall-Spencer et al., 2008; Kroeker et al., 2011, 2013; Fabricius et al., 2011, 2015; Hall-Spencer et al., 2022). The low biodiversity observed at these sites is linked to the loss of habitat-forming corals (Fabricius et al., 2013; Sunday et al., 2017). Some studies also showed that the structural integrity of any reef framework is compromised due to a loss of architectural complexity (Fabricius et al., 2011), increased rates of bioerosion (Enochs et al., 2016), lower coral growth (Fabricius et al., 2011) and reduced skeletal density (Fantazzini et al., 2015; Strahl et al., 2016). The ability of corals to maintain calcification under high *pCO₂* conditions appears to be species-specific (Rodolfo-Metalpa et al., 2011; Inoue et al., 2013).
<figure><img src="image_8.png" /><figcaption>**Figure 1.4.** Examples of extreme natural environments: (a) Nikko semi-enclosed bay; (b) Ambite Island CO2 seep (Papua New Guinea, © Tom Shlesinger); (c) Bouraké semi-enclosed lagoon (New Caledonia, © Serge Andrefouet); and (d) Kimberley Bay (Australia, © Zoe Richards).</figcaption></figure>

Upwelling environments have the potential to be OA hot spots (Feely et al., 2008; Manzello, 2010). For instance, corals of the Galápagos Islands and nearby Panamá reefs are also frequently exposed to the El Niño -Southern Oscillation (ENSO, +3-4°C during ENSO events for > 2 months), creating a unique opportunity to study the short-term effects of low pH (< 8.0) and thermal stress events (+1-3°C) on corals (Manzello et al., 2014). Manzello et al., (2014) showed that corals maintain their linear extension rates but experience a reduction in skeletal density. However, upwelling sites can be seasonal, meaning that the physicochemical conditions representative of future scenarios may be limited in time.

Mangrove habitats can also be important natural laboratories. These widespread reef-associated environments have recently received attention for their potential to minimize the negative impacts of elevated temperature and pCO₂ *via* increased primary production and carbon storage (Yates et al.,
2014; Camp et al., 2016; Sultana et al., 2016). They play a key role in the global carbon budget due to their high productivity, and intense carbon processing (e.g., Borges et al., 2003; Dittmar et al., 2006; Bouillon et al., 2014) and are considered one of the most important CO₂ sinks (Donato et al., 2012). Although mangrove forests represent critical habitat for many organisms (Yates et al., 2014; Stewart et al., 2021), they can also be an extreme habitat, with low pH and very variable temperature. This habitat could host selects stress-tolerant species and expose resident species to very different physico-chemical conditions compared to neighboring coral reefs (Camp et al., 2017; 2018; 2019). For example, in the Caribbean, Yates et al., (2014) suggested that mangroves could be a refuge for corals through physical shading and elevation of downstream total alkalinity (TA) because of carbonate-sediment dissolution (i.e., a buffering potential similar to seagrasses habitats). An increasing number of empirical studies document nested mangrove coral assemblages with corals establishing long-term and extensive communities within mangrove habitats (Rogers and Herlan, 2012). These include locations in the Caribbean (Rogers, 2017; Stewart et al., 2021), such as the extensive nested mangrove coral assemblage in Panama (Stewart et al., 2022), the Australian Great Barrier Reef (Camp et al., 2019), and sites in the Seychelles and Sulawesi (Camp et al., 2016) **(Figure 1.5)**.

Sponges can also be very abundant in mangrove systems, providing a particular opportunity to study sponge responses to multiple climate change factors. Most of what is known about sponges in mangrove ecosystems is from distribution, and taxonomic studies in the Caribbean (Diaz and Rützler, 2009; Guerra-Castro et al., 2011; Diaz, 2012). Only a few studies are available on mangrove sponges in the Indo-Pacific; for example, 115 sponge species have been recorded in the Berau region (Indonesia), 74 of which were attached to mangrove roots (Becking et al., 2013). Caribbean mangrove sponge communities contain species specifically adapted to survive “extreme” levels of salinity, temperature, and sedimentation (Rützler, 1995; Wulff, 2000, 2005; Engel and Pawlik, 2005; Pawlik et al., 2007; Nagelkerken et al., 2008). Mangrove-derived organic matter, leaching from roots and decaying litter, is the main source of carbon for sponges living in mangrove habitats (Granek et al., 2009), although oceanic particulate or dissolved organic matter may enter into the system (Letourneur et al., 2018).
<figure><img src="image_9.png" /><figcaption>**Figure 1.5.** Examples of mangrove-coral assemblages. (a) Bocas del Toro, Panamá (© Heather A. Stewart), and (b) mangrove lagoon near the Great Barrier Reef in Australia (© Emma Camp).</figcaption></figure>

Finally, semi-enclosed bays are also considered natural laboratories for studying future like climatic conditions. For example, the Nikko semi-enclosed bay in Palau, which is characterized by low pH (range 7.65-8.02) and high-temperature conditions (31.8°C), has high coral coverage (> 60%) and species diversity (21 scleractinian genera) (Van Woesik et al., 2012; Shamberger et al., 2014; Golbuu et al., 2016). In Nikko Bay, Kurihara et al., (2020) hypothesized that the corals had developed mechanisms to adapt to the site-specific conditions and maintain their fitness in the bay's warmer, more acidic conditions. The semi-enclosed bay of Bouraké in New Caledonia was first described as a regular mangrove system (e.g., Thollot, 1992; Thollot et al., 1999), without mentioning the presence of corals and other benthic organisms living in it and without reporting the incredible environmental variability that these species experience. The particularities of the Bouraké lagoon were highlighted by the study of Camp et al. (2017), thanks to some short-term monitoring and the study of the responses of the corals living there. Camp et al., (2017) described the Bouraké lagoon as a site characterized by the diel variation of temperature, pH, and oxygen, resulting in a warmer (> 33.0°C), acidified (< 7.3 pH<sub>T</sub>) and deoxygenated (< 2.3 mg L<sup>-1</sup>) seawater compared to the lagoon outside.
Camp et al. (2017) found that some of the 32 species of corals showed metabolic plasticity to cope with extreme environmental parameters. The study revealed the actual value of the Bouraké lagoon as a natural laboratory to study the responses of organisms to extreme environmental conditions. The recent studies in the Bouraké lagoon span from fish patterns and distribution (Komornicki, 1988; Dubuc et al., 2019a; 2019b) to coral physiology and recruitment (Jacquemont et al., 2022; Tanvet et al., 2022).

**1.6 Objectives of the study**

Sponges have a key role in coral reefs, supporting higher trophic levels through the conversion of DOM into detritus (sponge loop) or sponge biomass that becomes food for other reef organisms (e.g., De Goeij et al., 2013; McMurray et al., 2018; Rix et al., 2018). However, the effects that climate change may have on these ecological processes and, thus, on the reef as a whole still need to be better understood. This thesis aimed to address the gaps in our knowledge of the effects of extreme environmental conditions on sponge ecological responses (i.e., sponge carbon and nutrient cycling) and to provide insights into the consequences for future reefs. To this end, I used the natural laboratory of Bouraké, where sponges are particularly abundant and where environmental conditions are close to or even worse than projected for the future. It was essential to give a detailed physico-chemical description of this natural laboratory for which only a short monitoring was available (Camp et al. 2017). Then, in a series of experiments carried out *in-situ*, I exposed the sponge species *Rhabdastrella globostellata* (Carter, 1883) to both ‘normal’ and ‘extreme’ environmental conditions, which occur naturally in the lagoon of Bouraké during high and low tide, respectively. Finally, to distinguish the effects of warming from other environmental factors on the sponge carbon and nitrogen recycling, I carried out labeled <sup>13</sup>C and <sup>15</sup>N *ex-situ* experiments at the “Aquarium des lagons” (Nouméa, New Caledonia). The specific objectives of this thesis are divided into three main chapters:

1. *Long-term physico-chemical characterization and assessment of the distribution of benthic communities in the Bouraké natural laboratory*

In this chapter (chapter 2), I fully characterized the physico-chemical parameters and the distribution of the benthic communities. I also analyzed the stable isotopes signature of the Bouraké natural laboratory. Based on data collected from 2016 to 2020, I performed a long-term meta-analysis of temperature, pH<sub>T</sub>, and DO, as well as nutrients and organic matter concentrations, comparing the Bouraké stations and two reference sites. Photo-quadrat transects were used to assess the distribution of major benthic taxa living at the Bouraké lagoon. Finally, I measured the stable isotope signatures of δ<sup>13</sup>C and δ<sup>15</sup>N to highlight differences in the composition of carbon and nitrogen sources between
the outermost and innermost zone of the Bouraké lagoon, in selected benthic organisms, such as sponges and macroalgae. Part of this work began with my Master’s thesis (Maggioni, 2018). This chapter provides a full description of the study site, which was recognized as a natural laboratory for studying the effects of extreme environmental conditions on marine organisms (Maggioni et al., 2021).

## 2. Effects of extreme environmental conditions on R. globostellata nutrients and organic matter recycling, as well as its phototrophic activity

In this chapter (chapter 3), I performed 70 incubations *in-situ* using benthic respirometric chambers to assess the metabolic responses (i.e., nutrients and organic matter recycling) and the photosynthetic activity of *R. globostellata* during summer. Incubations were performed at high and low tides, representing “normal” and extreme environmental conditions. Changes in seawater nutrients and organic matter contents at the beginning and the end of incubations were used to evaluate their production and/or consumption in sponge metabolism. Dark incubations were performed during summer in both 2018 and 2020, the latter being the warmer, while dark/light incubations were only performed in 2020. This chapter provides a first information on the metabolic response of the sponge *R. globostellata* subjected to different environmental conditions such as those extreme (Maggioni et al., 2023).

## 3. Effects of temperature on R. globostellata carbon and nitrogen recycling

In this chapter (chapter 4), I performed an *ex-situ* experiment based on the results found in chapter 3, where summer temperature (> 31°C) was hypothesized as the main factor affecting the sponge carbon cycle. To specifically study the effect of temperature on sponge carbon and nitrogen recycling, I monitored the incorporation of labeled ¹³C and ¹⁵N into sponge tissue and detritus produced by the sponge during two temperature experiments at 28°C and 32°C. The discovery of the sponge *R. globostellata* outside the Bouraké lagoon (in 2021) allowed me to compare a “normal” population under constant temperature conditions with the presumably adapted sponges of Bouraké, which are subject to fluctuating temperature conditions that can reach the extreme value of 33°C. This chapter provides a first assessment of the consequences of high temperature on carbon (C) and nitrogen (N) recycling in the sponge *R. globostellata* adapted to high temperatures (Bouraké) and those that are not (control) (Maggioni et al., *under review in Limnology and Oceanography*).

In the last chapter (chapter 5), I first summarize the key findings that make the Bouraké lagoon one of the most suitable natural laboratory to study the responses of organisms to extreme environmental conditions. I discuss how the physiological and ecological processes of the sponge *R. globostellata*
might be affected under extreme environmental conditions, especially under high temperatures. I then focus on the effects of these conditions on the main ecological processes in sponges, such as the recycling of nutrients and organic matter. I outline the main strategies used by the sponge *R. globostellata* to adapt and thrive in such environmental conditions. I use my findings to better describe the ecological processes of sponges from a global perspective, assessing the future consequences for their role and, thus, for trophic interactions in future coral reefs.
CHAPTER 2:

THE BOURAKÉ SEMI-ENCLOSED LAGOON (NEW CALEDONIA) – A NATURAL LABORATORY TO STUDY THE LIFELONG ADAPTATION OF A CORAL REEF ECOSYSTEM TO EXTREME ENVIRONMENTAL CONDITIONS

<figure><img src="image_10.png" /><figcaption>The semi-enclosed lagoon of Bouraké (Nouméa, New Caledonia): the natural laboratory characterized and used in this study.</figcaption></figure>
Résumé

Selon les données expérimentales actuelles, les récifs coralliens pourraient être très fortement
impactés, voire possiblement disparaître, d'ici la fin du siècle si les émissions de CO2 restent
inchangées. Toutefois, les récentes découvertes de récifs diversifiés et à forte couverture de corail
vivant, dans des conditions extrêmes suggèrent que certains coraux pourraient bien se développer
dans une eau de mer chaude, à forte pCO2 et désoxygénée. Les cheminées volcaniques sous-marines
de CO2, les lagons semi-fermés et les estuaires de mangrove sont des sites d'étude où un ou plusieurs
paramètres écologiques importants pour la vie dans les océans sont proches ou même dépassent ceux
actuellement prévus pour l'année 2100. Bien qu'ils ne reproduisent pas parfaitement les conditions
futures, ces « laboratoires naturels » offrent des possibilités uniques d'explorer les mécanismes que
les espèces récifales pourraient utiliser pour suivre le rythme du changement climatique. Pour y
parvenir, il est essentiel de caractériser leur environnement dans son ensemble et de prendre en
compte de manière précise tous les facteurs environnementaux possibles qui pourraient différer de ce
qui est prévu dans le futur, modifiant éventuellement la réponse de l'écosystème.

Cette chapitre se concentre sur le lagon semi-fermé de Bouraké (Nouvelle-Calédonie, océan Pacifique Sud-Ouest) où un écosystème récifal sain prospère dans une eau chaude, à pH réduit et appauvrie en O2. Nous avons utilisé une approche multi-échelle pour caractériser les principaux paramètres physico-chimiques, cartographier la composition de la communauté benthique (i.e., coraux, les éponges et les macroalgues), et fournir des informations préliminaires sur la caractérisation isotopique des sources de matière organique (matière organique sédimentaire, macroalgues, phanérogames et feuilles de palétuviers) et d'organismes sessiles et de poissons en analysant les valeurs de δ13C et de δ15N dans la lagune de Bouraké. Les données ont révélé que la plupart des paramètres physiques et chimiques sont régulés par la marée, fluctuent fortement 3 à 4 fois par jour et sont entièrement prévisibles. Le pH de l'eau de mer et l'oxygène dissous diminuent à marée descendante et atteignent des valeurs extrêmement faibles à marée basse (7,2 pHT et 1,9 mg O2 L-1 à Bouraké, contre 7,9 pHT et 5,5 mg O2 L-1 sur les récifs de référence). L'oxygène dissous, la température et le pH fluctuent en fonction de la marée jusqu'à 4,91 mg O2 L-1, 6,50°C et 0,69 pHT en un seul jour. De plus, la concentration de la plupart des paramètres chimiques était jusqu'à cinq fois plus élevée dans la lagune de Bouraké, en particulier pour le carbone organique et inorganique et l'azote, mais aussi pour certains nutriments, notamment les silicates. De manière surprenante, malgré les conditions environnementales extrêmes et la composition chimique altérée de l'eau de mer mesurée à Bouraké, les résultats révèlent une communauté diversifiée et à couverture élevée de macroalgues, d'éponges et de coraux comptant respectivement 28, 11 et 66 espèces. De façon générale, les différents organismes ont montré une signature plus élevée en δ13C et plus faible en δ15N dans la partie intérieure
de la lagune de Bouraké que dans la partie extérieure. La variabilité environnementale et le
déséquilibre des nutriments pourraient contribuer à leur survie dans des conditions environnementales
aussi extrêmes. La dynamique naturelle de l'écosystème de Bouraké et sa pertinence a été décrit en
tant que laboratoire naturel pour étudier les réponses adaptatives des organismes benthiques à de
multiples conditions environnementales extrêmes.

Ce chapitre à fait l'objet d'une publication dans la revue « *Biogeosciences* » (cf. ci-dessous). Seule la
partie sur les isotopes stables a été ajoutée dans ce thèse, du fait de résultats encore non acquis lors
de la publication de ces travaux.
<figure><img src="image_11.png" /></figure>

<figure><img src="image_12.png" /></figure>

# The Bouraké semi-enclosed lagoon (New Caledonia) – a natural laboratory to study the lifelong adaptation of a coral reef ecosystem to extreme environmental conditions

Federica Maggioni<fnref n="1" />, Mireille Pujo-Pay<fnref n="2" />, Jérôme Aucan<fnref n="1" />,<fnref n="3" />, Carlo Cerrano<fnref n="4" />, Barbara Calcinai<fnref n="4" />, Claude Payri<fnref n="1" />, Francesca Benzoni<fnref n="5" />, Yves Letourneur<fnref n="1" />, and Riccardo Rodolfo-Metalpa<fnref n="1" />

**Correspondence:** Federica Maggioni (federica.maggioni@ird.fr)

<footnote n="1">¹ENTROPIE, IRD, Université de la Réunion, CNRS, IFREMER, Université de Nouvelle-Calédonie, Nouméa 98800, New Caledonia</footnote>

<footnote n="2">²CNRS, UMR 7621, Laboratoire d'Océanographie Microbienne, Observatoire Océanologique de Banyuls, Sorbonne Université, Paris, France</footnote>

<footnote n="3">³Pacific Community Center for Ocean Science (SPC), Nouméa, New Caledonia</footnote>

<footnote n="4">⁴Department of Life and Environmental Sciences (DiSVA), Polytechnic University of Marche, Ancona, Italy</footnote>

<footnote n="5">⁵Red Sea Research Center, Division of Biological and Environmental Science and Engineering, King Abdullah University of Science and Technology, 23955-6900 Thuwal, Saudi Arabia</footnote>
**Abstract**

According to current experimental evidence, coral reefs could disappear within the century if CO2 emissions remain unabated. However, recent discoveries of diverse and high cover reefs that already live under extreme conditions suggest that some corals might thrive well under hot, high pCO2, and deoxygenated seawater. Volcanic CO2 vents, semi-enclosed lagoons and mangrove estuaries are unique study sites where one or more ecologically relevant parameters for life in the oceans are close or even worse than currently projected for the year 2100. Although they do not perfectly mimic future conditions, these natural laboratories offer unique opportunities to explore the mechanisms that reef species could use to keep pace with climate change. To achieve this, it is essential to characterize their environment as a whole, and accurately consider all possible environmental factors that may differ from what is expected in the future, possibly altering the ecosystem response.

This chapter focuses on the semi-enclosed lagoon of Bouraké (New Caledonia, SW Pacific Ocean) where a healthy reef ecosystem thrives in warm, acidified and deoxygenated water. A multi-scale approach was used to characterize the main physical-chemical parameters, mapped the benthic community composition (i.e., corals, sponges, and macroalgae), provide preliminary information on the isotopic characterization of organic matter sources (sedimentary organic matter, macroalgae, phanerogams, and mangrove leaves), sessile organisms and fish by analyzing δ¹³C and δ¹⁵N values in the Bouraké lagoon. The data revealed that most physical and chemical parameters are regulated by the tide, strongly fluctuate 3 to 4 times a day, and are entirely predictable. The seawater pH and dissolved oxygen decrease during falling tide and reach extreme low values at low tide (7.2 pHT and 1.9 mg O₂ L⁻¹ at Bouraké, vs 7.9 pHT and 5.5 mg O₂ L⁻¹ at reference reefs). Dissolved oxygen, temperature, and pH fluctuates according to the tide of up to 4.91 mg O₂ L⁻¹, 6.50°C, and 0.69 pHT units on a single day. Furthermore, the concentration of most of the chemical parameters was one to five times higher at the Bouraké lagoon, particularly for organic and inorganic carbon and nitrogen, but also for some nutrients, notably silicates. Surprisingly, despite extreme environmental conditions and altered seawater chemical composition measured at Bouraké, our results reveal a diverse and high cover community of macroalgae, sponges and corals accounting for 28, 11 and 66 species, respectively. In general, the different organisms showed a higher signature in δ¹³C and lower in δ¹⁵N in the inner part of the Bouraké lagoon than in the outer part. Both environmental variability and nutrient imbalance might contribute to their survival under such extreme environmental conditions. The natural dynamics of the Bouraké ecosystem and its relevance as a natural laboratory were described to investigate the benthic organism’s adaptive responses to multiple extreme environmental conditions.
This chapter has been published in the journal "Biogeosciences" (see below). Only the part on stable isotopes has been added in this thesis, because of results not yet acquired at the time of the publication of this work.
**2.1 Introduction**

Marginal and extreme environments, where some species persist under sub-optimal environmental conditions, have become a precious tool to investigate the potential resilience of marine organisms in the face of climate change (Camp et al., 2017, 2018). These sites may be used as natural laboratories where at least one or more environmental parameters naturally mimic extreme environmental conditions over a large area of the ecosystem. They provide an opportunity to simultaneously investigate changes in species responses and their ability to acclimatize and adapt to global environmental changes (Soares, 2020; Kurihara et al., 2020). General observation suggest ecosystem-level consequences of life-long exposure to extreme conditions, such as reduced biological diversity, especially among calcifying organisms, decreased rates of coral calcification, and high rates of bioerosion (e.g., Hall-Spencer et al., 2008; Manzello et al., 2008; Fabricius et al., 2011; Crook et al., 2013; Kroeker et al., 2011; Iglesias-Prieto et al., 2014; Milazzo et al., 2014; Paytan et al., 2014). However, some natural laboratories can host very rich reef communities. Examples of such sites have been documented in Palau (Golbuu et al., 2016; Barkley et al., 2017; Shamberger et al., 2018; Kurihara et al., 2021), Papua New Guinea (Pichler et al., 2019), the Kimberly region, Australia (Dandan et al., 2015; Schoepf et al., 2015), and in mangrove lagoons of New Caledonia (Camp et al., 2017) and the US Virgin Islands (Yates et al., 2014).

These natural laboratories have become a common experimental asset in climate change research. However, the lack of empirical characterization of the physical and biogeochemical conditions, including diurnal and seasonal fluctuations, have been argued to bias the interpretation of the biological mechanisms that trigger the responses of organisms (e.g., Vizzini et al., 2013; Camp et al., 2018; Aiuppa et al., 2021). Using limited environmental descriptors makes it difficult to unequivocally identify the main driver(s) of the biological response among the primary factors (i.e., acidification, warming and/or deoxygenation), the potential secondary factors (e.g., pollution, water flow, tide, seawater nutrients and organic content, turbidity, etc.), and their combination. Water temperature, pH and dissolved oxygen can also co-vary negatively or positively and combine with other secondary factors, acting synergistically or antagonistically with unknown effects on benthic community responses. Their extreme values and the extent to which organisms are exposed are crucial in shaping biological responses (Boyd et al., 2016; Rivest et al., 2017). For instance, early studies suggest that temperature fluctuations due to diel or tidal variations could expose corals to stressful temperatures long enough to induce acclimatization or adaptation, but short enough to avoid coral mortality (Craig et al., 2001; Oliver and Palumbi, 2011; Castillo et al., 2012; Palumbi et al., 2014; DeCarlo et al., 2019).
Coral reef organisms from such thermally variable environments are expected to respond positively to future heat events (Rivest et al., 2017). Besides, corals naturally subjected to high pCO2 variability have shown immune defences when experimentally exposed to high temperatures, thus buffering the magnitude of thermal stress during heat waves (Wall et al., 2020). The extreme tidal range in the Kimberly region (Northwest of Australia) exposes corals to short-term temperature maxima of up to 37°C, and fluctuations of up to 7°C daily. Despite the high temperature, also combined with strong currents and turbid waters, diverse and probably resilient coral reefs have been described there (Dandan et al., 2015; Schoepf et al., 2015). Overall, only parts of these natural laboratories' physical and biogeochemical parameters have been quantified and only during short periods of fieldwork due to logistic constraints. Long-term monitoring of seawater parameters and their fluctuation is essential to better understand the mechanisms used by resilient reef organisms in these natural laboratories and interpret how marine taxa will respond to future biogeochemical changes in the environment.

The semi-enclosed lagoon of Bouraké (New Caledonia, SW Pacific Ocean) has been considered one of the most suitable natural laboratories for future extreme environmental conditions (Camp et al., 2019). In a preliminary study, Camp et al., (2017) reported a series of compelling short-term data of seawater carbonate chemistry and a general survey of the coral populations. In this first assessment of the Bouraké lagoon, the authors measured diel fluctuations of temperature (ranging from 25.9 to 33.1°C), pH (ranging from 7.24 to 7.91 pHT units) and dissolved oxygen (DO) (ranging from 1.80 to 6.97 mg L⁻¹) regulated by a one-meter tide. They revealed that about 20 species of corals were exposed 44% of the time to a pH<sub>T</sub> of 7.7-7.8, and 71% of the time to temperatures predicted for the end of the century under the IPCC scenario RCP4.5 (IPCC, 2014). These striking preliminary findings qualified the Bouraké lagoon as a unique site where potentially adapted corals withstand extreme environmental conditions.

The extent to which the Bouraké species are exposed to sub optimal conditions remains unclear and the best way to assess these very encouraging findings is to start with fully characterizing the main environmental parameters and the daily and seasonal fluctuations to which reef species have been subjected during their entire life. In this chapter a multi-scale approach was used to map and describe the benthic community living in the Bouraké lagoon and report on new evidence based on three years of data. Because of the size of the area, the close vicinity of a dense mangrove forest, and the demonstrated tide effect on the local environmental conditions, it has been hypothesized that (1) environmental conditions fluctuate regularly but are spatially heterogeneous throughout the Bouraké lagoon, and (2) only a limited number of species can resist to the extreme physical and chemical conditions at the study site, when compared to adjacent bay-sheltered reefs.
**2.2 Methods**

**2.2.1 Study site**

Starting in February 2016, the semi-enclosed coral reef lagoon of Bouraké (South Province, Grande Terre, New Caledonia) and adjacent reference reefs (Figure 2.1) were studied. The mangrove of Bouraké is located in a semi-arid geographical area, and it lacks rivers input typical of mangrove estuaries.

<figure><img src="image_13.png" /></figure>

**Figure 2.1.** Map of the study site (top panel) showing the semi-enclosed mangrove lagoon of Bouraké and reference reefs (R1 and R2). Photos a and b (bottom panels) are aerial pictures (taken at 130 m above the Bouraké lagoon) of the inner (bottom) and middle reefs (a) and the outer reef (b). White dots and yellow squares indicate the sampling stations used for physical and chemical environmental monitoring, respectively. Georep New Caledonia database (https://georep.nc/) and QGis software were used to build the figure (top panel).
In Bouraké, a channel of more than 80 m wide and 0.5 m to 6 m deep penetrates a dense mangrove
forest made by Avicennia marina and Rhizophora stylosa. It expands into side pools and a large
reservoir in the inner part of the mangrove system. A preliminary calculation of its surface and
seawater volume of the main area (i.e., without the large seawater reservoir covered by the mangrove
forest) using the 3ds Max Model gives underestimated values of 192,100 m² and 246,060 m³,
respectively (Rodolfo-Metalpa et al., in prep.). Terraces extend from the mangrove, on both sides of
the channel and form diverse and compact reefs at their ends. Coral species are less abundant and
diverse near the mangrove roots, where the bottom substrate is composed of fine sediment and mud.
There, reefs are exposed to air only at low tide during the spring tides (1.1 m maximum tidal range).
We subdivided the lagoon into three main areas: an external, an intermediate, and an inner reef
(hereafter called outer, middle and inner reefs; panels a & b in **Figure 2.1**). A series of sampling
stations were selected, and some of the main seawater chemical and physical environmental
parameters were measured at the study site and two adjacent reference reefs, namely R1, a typical
fringing reef, and R2, a semi-enclosed shallow and relatively large bay. Both reefs were located 4.8
km and 3.2 km from the entrance of the Bouraké lagoon, respectively.

**2.2.2 Environmental monitoring**

**2.2.2.1 Oceanographic sensors deployment and short- to long-term measurements**

From February 2016 to December 2020 up to eight YSI 600 OMS-M, three Seabird SeaFET™ pH loggers, and four Hobo water temperature Pro V2 were set at 10-min logging intervals, and used individually or in combination to assess short-, medium-, or long-term variations across depth (as a proxy of the tide), temperature (T°C), dissolved oxygen concentration (DO, mg L⁻¹), seawater pH~T~ (total scale), and salinity (see Appendix A, Table A2.1). YSI dissolved oxygen optical sensors were calibrated against zero and 100% saturated seawater at 25°C. Two SeaFETs were calibrated by the manufacturer, while the third was corrected before deployment by measuring its deviation from the two others in the same seawater.

Short-term (i.e., 24h) spatial and depth-related variations in pH and DO were simultaneously
measured at several stations in the Bouraké lagoon in March and April 2018 (Figure 2.1). Spatial
variations were assessed *i*) within the inner (St A-C for pH, and A-G for DO), the middle (St H-N for
DO), and the outer (St O-Q for DO) reefs, *ii*) between the outer and the inner reefs (St B1, B2 for
pH), and *iii*) between the outer and the reef outside the semi-enclosed lagoon (St U vs T for pH). In
the Bouraké lagoon, we recorded differences between the surface (shallow) and the bottom water: *i*)
at the outer reef (St S for pH), *ii*) at the middle reef (St I and N for DO), and *iii*) at the inner reef (St
R for pH, and DO). Salinity was measured in July 2019 (St R1, R2, B1 and B2) and December 2020
(St R1, R2, T and B2).

Medium-term measurements (i.e., 2-3 weeks) of the DO and pH were recorded at the reference (St R1, R2) and Bouraké reefs (St B1, B2) between 2016 and 2019.

Long-term measurements (>1 year) of seawater temperature were recorded at R1 and R2 starting
from January 2019 and September 2017, respectively, and at B1 and B2 from October 2018 and
September 2017, respectively. Only temperature data between October 2018 and April 2020 were
compared between sites.

Short-term pH and DO data and long-term temperature data were compared between stations using General Linear Modelling (GLM), and the Tukey' HSD *post hoc* test was used when significant factor effects were found. When data did not conform to normality or homogeneity of variance, the Kruskal-Wallis test followed by the Dunn's multiple comparisons test (Bonferroni-adjusted) or the Wilcoxon test were performed. Statistical analyses were carried out using either Statistica® or R version 3.4.4 (R Core Team, 2018), the latter using "stats", "FSA", and "MASS" packages.

2.2.2.2 Phase averaged and tidal harmonic analyses for diurnal and semidiurnal oscillations

Medium-term pH and DO changes were investigated by averaging time and tidal phases for diurnal and semi-diurnal oscillations. To do this, all data were overlaid on a daily period and a tidal phase. First, we calculated a predicted tide for the study area using the Nouméa harbour tide (50 km south of our study site) modified with coefficients from the Naval Hydrographic and Oceanographic Service (SHOM; http://data.shom.fr). The predicted tide was used to assign a semidiurnal tidal phase (12 h) to each sampling time, and the data were averaged for each of these tidal phases. Similarly, the data were averaged for each hour of the day (24 h). Because tides at sea are a sequence of sinusoidal harmonic components that are different for each location, we performed a harmonic tidal analysis on the DO and pH data. The "UTide"-ut_solv() tidal analysis package (Codyga, 2011) with the principal semidiurnal lunar constituent (M2), principal semidiurnal solar constituent (S2), and solar diurnal constituent (S1) was used. For each parameter, the amplitudes of the tidal harmonics M2 (12.4 h), S2 (12 h), and S1 (24 h) were calculated with a 95% confidence interval based on the 200 Monte-Carlo simulations.
**2.2.2.3 Diel cycles of carbonate chemistry and chemical parameters**

Surface water samples were collected across a diel cycle in June 2017, and July 2019 for pH, total alkalinity ($A_T$), dissolved inorganic carbon (DIC), nutrients (orthosilicic acid [Si(OH)₄], nitrogen oxide [NOₓ], ammonium [NH₄]⁺, phosphate [PO₄]³⁻, dissolved organic carbon (DOC), particulate organic carbon (POC), and particulate organic nitrogen (PON) (see **Appendix A- Table A2.2** for a summary of data collected). A summary of the total sampling is given in Supplementary Table S2. Dissolved inorganic nitrogen (DIN) and total organic carbon (TOC) were calculated as [NOₓ] + [NH₄]⁺, and DOC + POC, respectively. The most important ratios were calculated (e.g., DOC:TOC; Si(OH)₄:DIN) and contrasted between stations to evaluate the availability of nutrients and organic matter in the Bouraké lagoon (Jacquet et al., 2006; Leopold et al., 2017).

In 2017, during three consecutive days (from May 31st to June 02nd), seawater was sampled six times: twice during both high and low tide and once at both rising and falling tide. In total, we sampled one reference station (R2), three stations at the outer reef of the Bouraké lagoon (Outer: St B01-B03), one at the middle reef (Middle: St B04), and one at the inner reef inside the lagoon (Inner: St B05) (**Figure 2.1**). The whole collection lasted about 30 minutes. In 2019, during three consecutive days (from July 16th to 18th), sampling was carried out every hour from 8 am to 3 pm. The B1 and B2 stations were sampled on the first day, R1 on the second and R2 on the third day.

During diel cycles, at each station and sampling time, pH and temperature were measured at the surface (0.5 m deep) using a portable pH-meter (913, Metrohm) calibrated with TRIS buffer (Dickson lab, batch #T28). A subsample (50 mL) was filtered through 0.45 µm Whatman™ Puradisc CA filters using a syringe and poisoned with 20 µL saturated HgCl₂ to further measure $A_T$. Two 20 mL subsamples were analysed using an auto titrator (EcoTitrator, Metrohm), and $A_T$ was calculated from the Gran function. Results were corrected against $A_T$ standards (A. Dickson, batch #155, Scripps, USA). The seawater carbonate parameters $pCO_2$, $CO_3^{2-}$, and aragonite saturation state ($\Omega_{ara}$) were then calculated from the $pH_T$, $A_T$, temperature, and mean salinity (35) using the free-access $CO_2$SYS package (Pierrot et al., 2006).

Ammonium concentration was determined on a 40 mL subsample of unfiltered seawater, collected using a 60 mL Schott bottle and stored in the dark. Samples were processed using a fluorimeter (Turner Designs) between six and 18 h after two mL of OPA reagent (o-phthal dialdehyde) was added (Holmes et al., 1999).

The sampling of nutrients was performed using two replicate 20 mL polypropylene vials, rinsed three times using filtered seawater (Whatman™ Puradisc CA syringe filters 0.45 µm), filled with the
sample and immediately poisoned with 20 µL saturated HgCl₂. Measurements of PO₄³⁻, NOₓ, and
Si(OH)₄ nutrients were performed by colourimetry (Seal Analytical).

Seawater samples for DIC were collected in two replicate glass vials (20 mL), filled with unfiltered
water and poisoned with 10 µL saturated HgCl₂. The vials were immediately closed, the absence of
bubbles was visually checked, and the samples were stored in the dark at room temperature for later
analysis on a Shimadzu TOC-L analyser (Non-Dispersive Infrared, NDIR). Typical analytical
precision was less than ± 2 µmol kg⁻¹. The accuracy was verified using regular measurements of
reference material (CRM) from A. Dickson's laboratory.

Seawater samples for DOC were collected in two pre-combusted (4 h at 450°C) glass ampoules filled
with water filtered using a glass syringe filtration system (SGE™) with two pre-combusted 25-mm
GF/F Whatman™ filters. Samples were then acidified with ultrapure orthophosphoric acid (H₃PO₄),
sealed, and stored in the dark at room temperature for later analysis by high-temperature catalytic
oxidation (HTCO) (Sugimura and Suzuki, 1988; Cauwet, 1994) on a Shimadzu TOC-L analyser.
Typical analytical precision was ± 0.1-0.5 µM C (SD). Consensus reference materials
([http://www.rsmas.miami.edu/groups/biogeochem/CRM.html](http://www.rsmas.miami.edu/groups/biogeochem/CRM.html)) were injected every 12 to 17 samples
to ensure stable operating conditions. DOC concentrations are only available for the 2017 sampling
because of a sample's pollution in 2019.

Finally, one litre of unfiltered seawater was collected in a borosilicate glass bottle and stored on ice
during sampling for later measurement of POC and PON contents. In the lab, particulate matter was
collected on pre-combusted (4 h at 450°C) Whatman™ GF/F filters using a Nalgene® vacuum
system. The filters were dried at 60°C in the oven for 24 h and stored in airtight glass vials at 4°C in
the dark until analysis on a CHN Perkin Elmer 2400. All glass bottles and vials used were pre-
combusted, washed with HCl solutions (10%) and rinsed using milliQ water.

Seawater chemistry data were pooled by sampling area (R1, R2, Outer, Middle, Inner), and
differences were tested using the Kruskal-Wallis test followed the Conover Multiple comparison test
(Benjamini-Hochberg-adjusted). The effect of the tidal phases (i.e., falling and rising tide) on the
seawater chemical composition in the Bouraké lagoon only was assessed by attributing each sample
a tidal phase between 0 h (high tide) and 6 h (low tide), and between 6 h and 12 h (high tide). Multiple
linear regression was used to assess the adjusted R² and significance (*p* < 0.05) of the data from 0 h
to 6 h (falling tide) and from 6 h to 12 h (rising tide) separately. Statistical analyses were performed
using either Statistica® or R (version 3.2.4, R Core Team, 2018), the latter using the "FSA", "stats",
and "Conover.test" packages.
**2.2.3 Benthic community characterization and distribution**

The benthic community and bottom substrate of the Bouraké lagoon, referred hereafter as biotic and abiotic descriptors, respectively, were assessed in April 2018. Twenty-four 30 m-long geo-referenced transects (T1-T24) were laid in the lagoon along the terraces' edge at similar depths (i.e., ~1 m), targeting coral dominated benthic assemblages. On each transect, a 0.5 m x 0.5 m PVC quadrat was placed every meter, and a picture was taken with a waterproof photo-camera (Nikon AW 130) parallel to the substrate. A general description of the bottom (i.e., the various substrates) and a list of the most common and identifiable sessile species for each transect were made. For each of the 835 pictures collected, the cover of abiotic (i.e., mud, sand, rock, rubble, dead corals and unreadable) and biotic descriptors (i.e., branching, massive and soft corals, sponges, macroalgae and "others") with photoQuad software both by automatic multi-scale image segmentation regions and manual grid cell counts when necessary was estimated.

Photos of quadrats, the many other pictures collected during fieldwork, and laboratory morphological
observations on collected samples were used to produce a non-exhaustive species list of corals,
macroalgae and sponges. Corals were comprehensively sampled throughout the Bouraké lagoon and
on the reference reef R2, while dominant macroalgal and sponges species were collected in the
Bouraké lagoon alone and only if they were encountered at least three times along a transect, likely
leading to an underestimation of their diversity. Coral diversity was assessed through photographic
and sampling during time-based open search swims and SCUBA dives (Hill and Wilkinson, 2004).
Whenever possible, scleractinian corals were identified to species level *in-situ* by photographic
sampling only. When identification was doubtful *in vivo*, or when taxa were characterized by small
corallite size (< 1 mm in diameter) and required additional morphological examination of the skeleton
to confirm identification (e.g. genera *Acropora*, *Montipora* and *Porites*), a fragment of the colony
was collected, tagged, cleaned in sodium hypochlorite overnight, rinsed in freshwater and dried. The
reference collection is housed at IRD Nouméa. Microscopic examination of the skeletal features
allowed species-level identification following the reference literature (Veron, and Wallace, 1984;
Wallace, 1999; Veron, 2000). Sponges were identified based on their spicules’ morphological
characteristics (i.e., shape, length and width), or using a series of morphological descriptors (e.g.,
shape, size, colour, texture, surface ornamentations, fibres) for species without spicules. In the lab, a
subsample of the collected sponges was immediately digested using HNO<sub>3</sub>, and spicules were
measured with an optical stereomicroscope. For species without spicules, hand-cut sections of the
choanosome and ectosome were observed under a stereomicroscope. Species were identified using
the taxonomical keys of Rützler (1978), Hooper and Van Soest (2002), and Pons et al. (2017).
Macroalgae and corals identification were based on morphological and anatomical observations
following the dedicated literature and referring to specimens housed at IRD Noumea.

Abiotic and biotic cover percentages averaged per transect, and species richness, calculated as the number of species in the transect, were plotted using non-metric multidimensional scaling (nMDS) based on Bray-Curtis dissimilarities (“vegan” package in R) of square-root transformed data. Finally, the best number of clusters for the whole Bouraké lagoon was determined using the gap statistic method (“cluster” and “factorextra” packages in R) and used for the hierarchical clustering representation (Ward, 1963). The cluster separation was verified with a two-way analysis of similarity ANOSIM. Within each cluster, the benthic community and bottom substrate were averaged between transects, and the dominant biotic and abiotic descriptors were selected and used to define the cluster.

Principal component analysis (PCA) was used to visualize the correlation between environmental parameters and the benthic descriptors of transects inside the Bouraké lagoon. The analysis was performed in R (package “FactorMineR”, version 3.2.4, R Core Team, 2018) using data of biotic descriptors (averaged per transect) and the seawater parameters averaged for each sampling area (i.e., outer, middle and inner reefs).

2.2.4 Stable isotopes analyses

Stable isotope analysis of ¹³C and ¹⁵N was performed to provide information on organic matter sources and trophic relationships. Carbon and nitrogen stable isotopes ratios were used to highlight differences in the composition of carbon source and nitrogen between the outermost (B02) and innermost (B05) zone of the Bouraké lagoon, in some benthic organisms.

Samples for stable isotopes analyses were collected in the summer season (March 2019 and December 2020). In 2019, 6 fishes species (tot samples = 19), 5 macroalgae species (tot samples = 6), 1 sponge species (Rhabdastrella globostellata) were sampled in the Bouraké inner zone (B05). Only for fish, 5 of the 6 species were collected at the reference site R1. Specifically, 3 Dascyllus aruanus in site B02 and 2 in R1, 2 Amblygyphidon ternatensis at R1, 3 Chaetodon lunulatus at R1, 1 Chaetodon bennetti at R1, 5 Stegastes nigricans at R1, and 3 Apogon cf. crassiceps at R1. Macroalgae are 1 Caulerpa serrulata, 1 Sargassum sp., 2 Stypopodium sp., 1 Halimeda discoidea and 1 H. distorta. In 2020, 4 different species of macroalgae (Turbinaria conoides, Stypopodium sp., Sargassum sp., Dyctiota sp.) and 4 different species of sponges (Callyspongia sp., Haliclona sp., Dysidea sp., and Hyrtios sp.) with two sample per species were sampled in both the outer (B02) and the inner (B05) zone. Padina sp. (n samples = 2), 4 mangrove leaf, and 1 undertermined seagrass species (n samples = 2) were only sampled at B05.
Samples were freeze-dried and ground into a fine powder using a mortal pestle. Sample (1 mg) of
macroalgae, sponges and fish were analysed with no prior treatment. Samples with calcareous
components, such as *Halimeda* sp. is treated for ¹³C analyses after acidification by 1% HCL solution
to remove carbonates, rinsed with distilled water and oven-dried at 40°C for 24 h. The ¹³C:¹²C and
¹⁵N:¹⁴N ratios were analysed by continuous- flow isotope-ratio mass spectrometry. The spectrometer
(IRMS Sercon, UAR IMAGO, Nouméa, New Caledonia) was used for isotopes analysis. The
analytical precision was 0.4‰ for N and 0.15‰ for C, estimated from standards analysed along with
the samples. Isotope ratios were expressed as parts per 1000 (‰) differences from a standard
reference material: δ¹³C and δ¹⁵N = [(Rsample / Rstandard) – 1] × 1000; where R sample and R
standard are the ratio of ¹³C/¹²C or ¹⁵N/¹⁴N in the sample and in the standard reference materials,
respectively. The international standard references are Vienna Pee Dee Belemnite for carbon and
atmospheric N₂ for nitrogen.

These data were represented using point graph to get an overview of the different isotopic signatures
in fish, sponges and macroalgae between the outer and inner zone of Bouraké and R1. Given the small
number of samples, only for sampling in 2020, isotopic signatures for all sponge species and
macroalgae species were pooled and differences between Bouraké outer (B02) and inner (B05) were
compared, as well as average isotopic signatures of *Dascyllus aruanus* between Bouraké and
reference reef (R1). Differences were tested by Wilcoxon test using R package “stats” (R Core Team,
2019).
**2.3 Results**

**2.3.1 Variability of physical environmental parameters**

*Tidal phases*. The predicted tide in the study area (SHOM data) is close to what measured at R1 and R2 (Figure 2.2). It is semidiurnal with a diurnal inequality ($M_2$ = 0.44 m, $S_2$ = 0.16 m) and has a small diurnal component ($S_1$ = 0.15 m). It varies between 0.4 m and 1.7 m, depending on the phase of the moon, with a mean of 1.1 m. The tidal range inside the Bouraké lagoon is lower and varies between 0.4 m and 1.2 m, with a mean of 0.9 m. At B1 and B2, the tidal signal lags the predicted and measured tide at the reference stations by an average of 1.5 h for low tide and up to 45 min for high tide.

<figure><img src="image_14.png" /><figcaption>**Figure 2.2.** Temporal shift between the averaged tides recorded at the reference (St R1 and R2) and at the Bouraké reefs (St B1 and B2) and the predicted tide calculated for the study area (see SHOM: http://data.shom.fr for the Nouméa harbour).</figcaption></figure>
*Temperature.* Results indicate that the water temperature has an annual cycle with lower values during winter (May-October) and higher values in summer (November-April). Daily averaged temperatures at R2, B1 and B2 were not significantly different, while the temperature at R1 was cooler in summer and warmer in winter (**Figure 2.3a; Table 2.1**) compared to the other stations. On a weekly basis, the averaged diel temperature variation was significantly different between stations: 1.34 ± 0.39°C at R1 and 3.73 ± 0.74°C at B2 (**Figure 2.3b; Table 2.1**). In a single day, we recorded temperature fluctuations of up to 3.4°C at R1 and 6.5°C at B2.

<figure><img src="image_15.png" /><figcaption>**Figure 2.3.** Long-term temperature monitoring from October 2018 to April 2020 at the reference (St R1 and R2) and Bouraké reefs (St B1 and B2). Data are plotted using weekly averaged temperature (a) and weekly averaged diel changes (b).</figcaption></figure>
<table><caption>**Table 2.1.** Summary of the statistical analyses applied to the seawater physical and chemical parameters collected between 2016 and 2020 at the Bouraké lagoon (St B1, B2, St A-R, outer, middle and inner) and at reference reefs (St R1 and R2). Differences in temperature, salinity and chemical parameters between the Bouraké lagoon and reference reefs and spatial and vertical differences in pH and DO inside the Bouraké lagoon. K-W: Kruskal-Wallis's test; W: Wilcoxon test; GLM: General Linear Model; D: Dunn's test; T: Tukey's test; C: Conover's test.</caption><thead><tr><th>Parameters</th><th>(n)</th><th>K-W</th><th>W</th><th>GLM</th><th>p</th><th>post hoc (test)</th></tr></thead><tbody><tr><td colspan="7"><strong>Seawater temperature (St R1, R2, B1, B2)</strong></td></tr><tr><td>Daily means</td><td>2968</td><td>68.46</td><td></td><td></td><td>&lt; 0.001</td><td>(D) p &lt; 0.001 R1 &lt; R2 = B1 = B2</td></tr><tr><td>Weekly oscillations</td><td>305</td><td>234.63</td><td></td><td></td><td>&lt; 0.001</td><td>(D) p &lt; 0.01 R1 &lt; R2 &lt; B1 &lt; B2</td></tr><tr><td colspan="7"><strong>Seawater pH (Stations)</strong></td></tr><tr><td>Spatial INNER (A-C)</td><td>711</td><td></td><td>5.32</td><td>0.005</td><td></td><td>(T) p &lt; 0.01 A &lt; C</td></tr><tr><td>Spatial (B1 vs B2)</td><td>1820</td><td></td><td>17.62</td><td>&lt; 0.001</td><td></td><td></td></tr><tr><td>Spatial (U vs T)</td><td>7280</td><td></td><td>189.8</td><td>&lt; 0.001</td><td></td><td></td></tr><tr><td>Surface vs deep (R)</td><td>664</td><td></td><td>26.88</td><td>&lt; 0.001</td><td></td><td></td></tr><tr><td>Surface vs deep (S)692</td><td></td><td></td><td>41.48</td><td>&lt; 0.001</td><td></td><td></td></tr><tr><td colspan="7"><strong>Seawater DO (Stations)</strong></td></tr><tr><td>Spatial INNER (A-G)</td><td>1031</td><td></td><td>1.145</td><td>0.330</td><td></td><td></td></tr><tr><td>Spatial MIDDLE (H-N)</td><td>700</td><td></td><td>0.636</td><td>0.636</td><td></td><td></td></tr><tr><td>Spatial OUTER (O-Q)</td><td>399</td><td></td><td>1.636</td><td>0.196</td><td></td><td></td></tr><tr><td>Surface vs deep (I)</td><td>280</td><td></td><td>0.000</td><td>0.994</td><td></td><td></td></tr><tr><td>Surface vs deep (N)</td><td>280</td><td></td><td>22.05</td><td>&lt; 0.001</td><td></td><td></td></tr><tr><td>Surface vs deep (R)</td><td>258</td><td></td><td>0.443</td><td>0.839</td><td></td><td></td></tr><tr><td colspan="7"><strong>Seawater Salinity (Stations)</strong></td></tr><tr><td>Winter (R1, R2, B1, B2)</td><td>1732</td><td></td><td>463.5</td><td>&lt; 0.001</td><td></td><td>(T) p&lt;0.01 R1&lt;R2&lt;B1&lt;B2</td></tr><tr><td>Summer (R1, R2, T, B2)</td><td>5105</td><td></td><td>1583</td><td>&lt; 0.001</td><td></td><td>(T) p&lt;0.01 R1&lt;R2&lt;T&lt;B2</td></tr><tr><td>Winter vs Summer (R1)</td><td>1872</td><td>287264</td><td></td><td>&lt; 0.001</td><td></td><td></td></tr><tr><td>Winter vs Summer (R2)</td><td>1728</td><td>253060</td><td></td><td>&lt; 0.001</td><td></td><td></td></tr><tr><td>Winter vs Summer (B2)</td><td>1872</td><td>150175</td><td></td><td>&lt; 0.001</td><td></td><td></td></tr><tr><td colspan="7"><strong>Seawater carbonate chemistry (St R1, R2, outer, middle, and inner)</strong></td></tr><tr><td>pH<sub>T</sub></td><td>66</td><td>36.48</td><td></td><td>&lt; 0.001</td><td></td><td>(C) p &lt; 0.05 R1 &gt; R2 &gt; Inn = Mid = Out</td></tr><tr><td>pCO<sub>2</sub></td><td>66</td><td>36.48</td><td></td><td>&lt; 0.001</td><td></td><td>(C) p &lt; 0.01 R1 = R2 &lt; Inn = Mid = Out</td></tr><tr><td>CO<sub>3</sub><sup>2-</sup></td><td>66</td><td>33.54</td><td></td><td>&lt; 0.001</td><td></td><td>(C) p &lt; 0.05 R1 &gt; R2 &gt; Inn = Mid = Out</td></tr><tr><td>Ω<sub>ara</sub></td><td>66</td><td>33.27</td><td></td><td>&lt; 0.001</td><td></td><td>(C) p &lt; 0.05 R1 &gt; R2 &gt; Inn = Mid = Out</td></tr><tr><td>DIC</td><td>66</td><td>25.95</td><td></td><td>&lt; 0.001</td><td></td><td>(C) p &lt; 0.01 R1 = R2 &lt; Inn = Mid = Out</td></tr><tr><td>A<sub>T</sub></td><td>66</td><td>20.94</td><td></td><td>&lt; 0.001</td><td></td><td>(C) p &lt; 0.05 All ≠; Mid = R1;<br/>Mid = R2; Out = Inn; R1 = R2</td></tr><tr><td colspan="7"><strong>Seawater chemical parameters (St R1, R2, outer, middle, inner)</strong></td></tr><tr><td>SiOH<sub>4</sub></td><td>66</td><td>45.37</td><td></td><td>&lt; 0.001</td><td></td><td>(C) p &lt; 0.05 R1 &lt; R2 &lt; Out = Mid = Inn;<br/>Inn &gt; Out</td></tr><tr><td>NO<sub>x</sub></td><td>66</td><td>26.46</td><td></td><td>&lt; 0.001</td><td></td><td>(C) p &lt; 0.05; R1 &lt; R2 = Inn = Mid;<br/>Inn &lt; Out; Out &gt; R1; Out &gt; R2</td></tr><tr><td>NH<sub>4</sub><sup>+</sup></td><td>66</td><td>26.46</td><td></td><td>&lt; 0.001</td><td></td><td>(C) p &lt; 0.01 R1 &lt; Inn = Mid = Out = R2</td></tr><tr><td>PO<sub>4</sub><sup>3-</sup></td><td>66</td><td>29.43</td><td></td><td>&lt; 0.001</td><td></td><td>(C) p &lt; 0.05 All ≠; R2 = Mid</td></tr><tr><td>DOC</td><td>36</td><td>16.12</td><td></td><td>0.001</td><td></td><td>(C) p &lt; 0.05 All ≠; Mid = Out</td></tr><tr><td>POC</td><td>66</td><td>52.46</td><td></td><td>&lt; 0.001</td><td></td><td>(C) p &lt; 0.05 R1 = R2 &lt; Out &lt; Mid &lt; Inn</td></tr><tr><td>PON</td><td>66</td><td>43.79</td><td></td><td>&lt; 0.001</td><td></td><td>(C) p &lt; 0.05 R1 = R2 &lt; Out &lt; Mid &lt; Inn</td></tr><tr><td>DIN</td><td>66</td><td>20.13</td><td></td><td>&lt; 0.001</td><td></td><td>(C) p &lt; 0.01 R2 &lt; R1 &lt; Inn = Mid = Out</td></tr><tr><td>TOC</td><td>36</td><td>19.48</td><td></td><td>&lt; 0.001</td><td></td><td>(C) p &lt; 0.01 All ≠; Mid = Out</td></tr><tr><td>DIC:DIN</td><td>66</td><td>17.40</td><td></td><td>&lt; 0.001</td><td></td><td>(C) p &lt; 0.01 R1 &gt; R2 = Inn = Mid = Out</td></tr><tr><td>POC:PON</td><td>66</td><td>44.87</td><td></td><td>&lt; 0.001</td><td></td><td>(C) p &lt; 0.01 R1 = R2 &lt; Inn = Mid = Out</td></tr><tr><td>POC:DOC</td><td>36</td><td>18.47</td><td></td><td>&lt; 0.001</td><td></td><td>(C) p &lt; 0.05 All ≠; Inn = Mid</td></tr><tr><td>DOC TOC</td><td>36</td><td>18.21</td><td></td><td>&lt; 0.001</td><td></td><td>(C) p &lt; 0.01 R2 &lt; Out &lt; Inn &lt; Mid;<br/>Inn = Mid; Inn = Out</td></tr><tr><td>Si(OH)<sub>4</sub>:DIN</td><td>66</td><td>43.77</td><td></td><td>&lt; 0.001</td><td></td><td>(C) p &lt; 0.01 R2 &lt; Inn &gt; Mid;<br/>Mid = Out; R1 = R2</td></tr><tr><td>DIN:DIP</td><td>65</td><td>24.59</td><td></td><td>&lt; 0.001</td><td></td><td>(C) p &lt; 0.05 R1 &lt; R2 &gt; Inn;<br/>R2 = Out = Mid; Inn = Mid</td></tr><tr><td>Si(OH)<sub>4</sub>:DIP</td><td>65</td><td>36.62</td><td></td><td>&lt; 0.001</td><td></td><td>(C) p &lt; 0.01 R1 &lt; R2 &lt; Inn = Mid = Out</td></tr></tbody></table>
Seawater pH. During the entire study period, pH was measured during 22, 72, 31, and 72 semidiurnal tidal cycles at R1, R2, B1, and B2, respectively. We overlaid all data on a single tidal phase of 12 h (Figure 2.4a) and a 24 h cycle (Figure 2.4b).

<figure><img src="image_16.png" /><figcaption>**Figure 2.4.** Seawater pH<sub>T</sub> (**a**), (**b**) and dissolved oxygen (**DO**) (**c**), (**d**) variations recorded at the reference (St R1 and R2) and Bouraké reefs (St B1 and B2). Data were overlaid in a single tidal phase (12 h) (**a**), (**c**); and in a 24 h cycle (**b**), (**d**). Data are 22, 72, 31, and 72 semidiurnal tidal cycles for pH, and 36, 79, 34 and 42 semidiurnal tidal cycles for DO, for R1, R2, B1 and B2, respectively.</figcaption></figure>

The pH differed significantly between stations. During the studied period, we recorded means of 8.01 ± 0.04 and 7.89 ± 0.08 pH<sub>T</sub> units at R1 and R2, and 7.80 ± 0.22 and 7.67 ± 0.23 pH<sub>T</sub> units at B1 and B2, respectively. At both B1 and B2, pH was strongly correlated with the tidal cycle (Figure 2.4a, 82% and 73% of the total variance were explained by the tidal harmonic analysis, respectively). In contrast, it was only marginally correlated with the 24 h cycle (Figure 2.4b). During each tidal phase, the pH changed on average by about 0.6 units and reached a minimum of 7.23 and a maximum of 8.06 at B2 at low and high tide, respectively. The pH oscillations were mainly semidiurnal (M<sub>2</sub> = 0.27
± 0.01, S₂ = 0.05 ± 0.01 pHT units, for B1; M₂ = 0.24 ± 0.01, S₂ = 0.09 ± 0.01 pHT units for B2). At stations R1 and R2, pH changed on average by about 0.1 pHT units and was mostly dependent on the 24 h cycle **(Figure 2.4b)**, S₁ = 0.058 ± 0.004 and S₁ = 0.049 ± 0.007 pHT units for R1 and R2, respectively).

Simultaneous short-term pH measurements showed significant spatial differences (Figure 2.5; Table 2.1), between i) stations A and C, ii) stations B1 and B2, and iii) the outer reef in the Bouraké lagoon (St U) and the station outside the system (St T). There were also significant depth-related differences between shallow reefs and bottom water at stations R and S. In both spatial and depth-related analyses, differences were approximately 0.05 to 0.1 pH<sub>T</sub> units, and we found the lowest values at stations C and B2 and the bottom of the channel (St R and S).

<figure><img src="image_17.png" /></figure>

**Figure 2.5.** Spatial and depth-related short-term changes (24 h) in pH<sub>T</sub> at stations in the Bouraké lagoon (see Figure 2.1 for the stations' location). Spatial variations were assessed: (a) within the inner reef (St A-C); (b) between the inner and the outer reefs (St B1, B2); (c) between the outer reef (but still inside the Bouraké lagoon), and the reef outside the semi-enclosed lagoon (St U vs T). Depth-related variations were assessed between shallow reefs and the bottom of the channel: (d) at the inner reef (St R); and (e) at the outer reef (St S). Tide (black line) refers to St B2.
Dissolved oxygen (DO). DO was measured during 36, 79, 34 and 42 semidiurnal tidal cycles at R1, R2, B1 and B2, respectively. All data were overlaid on a single tidal phase of 12 h (Figure 2.4c) and a 24 h cycle (Figure 2.4d). As with pH, the mean diel DO was higher at the reference reefs than in the Bouraké lagoon. During the studied period, mean DO values were 4.89 ± 1.18 and 5.23 ± 0.89 mg L⁻¹ at B1 and B2, respectively, and 6.45 ± 0.95 and 6.48 ± 1.05 mg L⁻¹ at R1 and R2, respectively. At stations B1 and B2, DO was strongly correlated with the tidal cycle (Figure 2.4c, 82 and 72% of the total DO variance were explained by the tidal harmonic analysis, respectively), and only marginally with the 24 h cycle (Figure 2.4d). DO oscillations were mainly semidiurnal (M₂ = 1.17 ± 0.08 mg L⁻¹, and M₂ = 0.83 ± 0.09 mg L⁻¹ for B1 and B2, respectively) with a substantial diurnal component (S₁ = 1.12 ± 0.04 mg L⁻¹, and S₁ = 0.681 ± 0.04 mg L⁻¹ for B1 and B2, respectively). During a semidiurnal tidal cycle, DO was lower at low tide (Figure 2.4c, 3.7 mg L⁻¹ and 4.6 mg L⁻¹ at B1 and B2, respectively) and higher at high tide (Figure 2.4c, 6.0 mg L⁻¹ and 6.1 mg L⁻¹ at B1 and B2, respectively). The minimum (1.89 mg L⁻¹), and the maximum (7.24 mg L⁻¹) DO value were both measured at B1 during low and high tide, respectively. During a 24 h cycle, DO was lower in the early morning (Figure 2.4d, 4.0 and 4.3 mg L⁻¹ at B1 and B2, respectively) and higher in the middle of the day (Figure 2.4d, 5.8 and 5.4 mg L⁻¹ at B1 and B2, respectively). In a single day, DO fluctuations were up to 6.37 mg L⁻¹ at R1 and 4.91 mg L⁻¹ at B2. At stations R1 and R2, DO was mostly dependent on the 24-hour cycle (S₁ = 1.34 ± 0.06 mg L⁻¹ and S₁ = 1.53 ± 0.09 mg L⁻¹ for R1 and R2, respectively) with lower values during the night (Figure 2.4d, 5.5 mg L⁻¹ at both stations), and higher values in the middle of the day (Figure 2.4d, 7.8 mg L⁻¹, both stations). Simultaneous short-term DO measurements (Figure 2.6; Table 2.1) did not show significant differences over a 24 h cycle at the inner (St A-G; except for some specific deviations, e.g., St A), the middle (St H-N) or the outer reef (St O-Q). Dissolved oxygen did not change on a vertical gradient at stations R and I, but the bottom DO was significantly lower at station N.
<figure><img src="image_18.png" /><figcaption>**Figure 2.6.** Spatial and depth-related short-term measurements (24 h) of dissolved oxygen (DO) at stations in the Bouraké lagoon (see Figure 1 for the location of the stations). Spatial variations were assessed on (a) the inner reef (St A-G), (b) the middle reef (St H-N), and (c) the outer reef (St O-Q). Depth-related variations between shallow reefs and bottom water within the Bouraké lagoon were assessed (d) at the inner reef (St R) and (e, f) at the middle reef (St I and N). Tide (black line) refers to St B2.</figcaption></figure>

Salinity (S). Salinity was measured only during two short-term periods in winter 2019 and summer 2020 (Figure 2.7). Salinity variations in the Bouraké lagoon were strongly correlated with the tidal cycle, and the highest mean values were measured during both winter and summer. Salinity was lower at reference reefs during both the winter and summer seasons (Figure 2.7a-b). The mean salinity during the winter of 2019 was 35.49 ± 0.04 at R1, 35.67 ± 0.10 at R2, 36.00 ± 0.35 at B1, and 36.17 ± 0.47 at B2 with significant differences between stations (Table 2.1). Salinity in the Bouraké lagoon peaked at 37.22 at B2 during low tide, while it was 35.65 at R1. During the summer of 2020, the mean salinity increased significantly in the Bouraké lagoon, with 37.22 ± 0.53 at B2 reaching 39.37, while it remained lower at R1 with 35.42 ± 0.10 and R2 with 35.71 ± 0.16. During summer 2020, we
also measured short-term variations in salinity at station T, which is outside the Bouraké system.
Although its distance from the lagoon entrance, the water mass discharged during falling tide
increased seawater salinity also at this station where a maximum value of 37.33 during low tide was
measured.

<figure><img src="image_19.png" /><figcaption>**Figure 2.7.** Short-term salinity monitoring during (a) the winter of 2019 (from 15/07/2019 to 18/07/2019) at the reference (St R1 and R2) and Bouraké reefs (St B1 and B2); (b) the summer of 2020 (from 29/11/2020 to 04/12/2020) at the reference (St R1 and R2) and Bouraké reefs (St T and B2). Tide (black line) refers to St B2.</figcaption></figure>

**2.3.2 Diel cycles of carbonate chemistry and chemical parameters**

We monitored diel cycles in June 2017 and July 2019 at two reference reefs and three reefs within the semi-enclosed lagoon of Bouraké (i.e., the outer, the middle and the inner reefs). The seawater carbonate chemistry differed significantly between the reference and the Bouraké lagoon reefs (Figure 2.8a-c; Table 2.1, Table 2.2; Appendix A- Figure A2.1). The reference reefs R1 and R2 had higher pH, CO3²⁻ and Ωara, and lower DIC and pCO2 than the outer, middle or inner reefs in the Bouraké lagoon. The range of values in the lagoon was similar to previous measurements (see above), with levels of pCO2 > 2000 µatm and levels of Ωara < 1. By assigning a tidal phase (from 0 to 12 h) to each sample taken in the Bouraké lagoon (all reefs combined), the diel measurements showed significant regressions, either positive or negative, depending on the seawater carbonate parameter and the tide phase (Figure 2.8d-f; Appendix A- Figure A2.1; Table A2.3). For example, the DIC reached the highest value of 2635 µmol L⁻¹ during low tide on the inner reef with an average of 2315.1 ± 168.1 µmol L⁻¹, while CO3²⁻ reached the lowest value of 50.10 µmol kg⁻¹ during low tide on the inner reef with an average of 109.02 ± 45.59 µmol kg⁻¹.
<figure><img src="image_20.png" /></figure>

**Figure 2.8.** Seawater carbonate chemistry measured (pH<sub>T</sub>) and calculated (DIC and Ω<sub>ara</sub>) during diel cycles in 2017 and 2019 (pooled data, see also Appendix A Figure A2.1.) at R1, R2 and the Bouraké reefs (outer, middle and inner) (**a-c**). Boxes (n = 6-14) represent the interquartile range (25th and 75th percentile); the horizontal line is the median, and the whiskers represent the data range (i.e., minimum and maximum). Changes are illustrated across a 12 h tidal phase in the Bouraké lagoon (**d-f**). Linear regression lines are plotted for each falling (HT to LT) and rising tide (LT to HT). Shaded boxes have only a graphical significance and only suggest the tide changes during measurements.
<table><caption>**Table 2.2.** Summary of the seawater physical and chemical data (mean ± SD) measured in July 2017 and June 2019 and calculated using the CO2SYS package. Data were pooled and averaged per station. nd = not determined. Reference reefs: St R1 and R2; Bouraké lagoon stations: outer, middle and inner.</caption><thead><tr><th></th><th>R1</th><th>R2</th><th>Outer</th><th>Middle</th><th>Inner</th></tr></thead><tbody><tr><td colspan="6"><em>Measured</em></td></tr><tr><td>Temp (°C)</td><td>22.54 ± 0.31</td><td>22.69 ± 1.50</td><td>23.57 ± 1.31</td><td>24.05 ± 1.20</td><td>23.00 ± 1.46</td></tr><tr><td>pH<sub>T</sub></td><td>8.09 ± 0.01</td><td>8.02 ± 0.07</td><td>7.66 ± 0.25</td><td>7.73 ± 0.22</td><td>7.68 ± 0.24</td></tr><tr><td>DO (mg L<sup>-1</sup>)</td><td>7.20 ± 0.64</td><td>6.91 ± 1.01</td><td>6.11 ± 0.68</td><td>nd</td><td>5.98 ± 0.67</td></tr><tr><td>A<sub>T</sub> (µmol kg<sup>-1</sup>)</td><td>2294.1 ± 0.3</td><td>2261.2 ± 0.04</td><td>2357.8 ± 0.1</td><td>2256.3 ± 0.06</td><td>2393.7 ± 0.08</td></tr><tr><td>Si(OH)<sub>4</sub> (µmol L<sup>-1</sup>)</td><td>0.71 ± 0.42</td><td>2.86 ± 1.41</td><td>8.22 ± 3.14</td><td>8.88 ± 2.72</td><td>11.93 ± 4.27</td></tr><tr><td>No<sub>x</sub> (µmol L<sup>-1</sup>)</td><td>0.21 ± 0.05</td><td>0.51 ± 0.16</td><td>0.65 ± 0.20</td><td>0.54 ± 0.09</td><td>0.54 ± 0.12</td></tr><tr><td>PO<sub>4</sub><sup>3-</sup> (µmol L<sup>-1</sup>)</td><td>0.63 ± 0.08</td><td>0.19 ± 0.05</td><td>0.26 ± 0.13</td><td>0.19 ± 0.01</td><td>0.42 ± 0.23</td></tr><tr><td>NH<sub>4</sub><sup>+</sup> (µmol L<sup>-1</sup>)</td><td>0.08 ± 0.06</td><td>0.23 ± 0.09</td><td>0.27 ± 0.12</td><td>0.34 ± 0.12</td><td>0.23 ± 0.14</td></tr><tr><td>DOC (µmol L<sup>-1</sup>)</td><td>nd</td><td>81.15 ± 5.49</td><td>96.89 ± 10.78</td><td>95.70 ± 8.38</td><td>112.82 ± 14.41</td></tr><tr><td>DIC (µmol L<sup>-1</sup>)</td><td>2117.7 ± 39.4</td><td>2092.4 ± 42.9</td><td>2251.1 ± 132.2</td><td>2282.5 ± 112.0</td><td>2315.1 ± 168.1</td></tr><tr><td>POC (µmol L<sup>-1</sup>)</td><td>9.28 ± 1.47</td><td>11.15 ± 1.97</td><td>24.07 ± 5.31</td><td>29.37 ± 7.03</td><td>38.11 ± 10.43</td></tr><tr><td>PON (µmol L<sup>-1</sup>)</td><td>1.24 ± 0.46</td><td>1.21 ± 0.22</td><td>1.64 ± 0.22</td><td>1.98 ± 0.35</td><td>2.43 ± 0.52</td></tr><tr><td colspan="6"><em>Calculated</em></td></tr><tr><td>pCO<sub>2</sub> (µatm)</td><td>353.42 ± 7.24</td><td>467.76 ± 112.03</td><td>1402.92 ± 896.42</td><td>1047.06 ± 599.07</td><td>1318.95 ± 819.79</td></tr><tr><td>CO<sub>3</sub><sup>2-</sup> (µmol kg<sup>-1</sup>)</td><td>211.92 ± 9.79</td><td>176.80 ± 30.05</td><td>105.84 ± 46.46</td><td>115.57 ± 46.18</td><td>109.02 ± 45.59</td></tr><tr><td>Ω<sub>aragonite</sub></td><td>3.35 ± 0.16</td><td>2.80 ± 0.49</td><td>1.68 ± 0.73</td><td>1.84 ± 0.73</td><td>1.72 ± 0.71</td></tr><tr><td>TOC (µmol L<sup>-1</sup>)</td><td>nd</td><td>93.22 ± 6.18</td><td>121.63 ± 14.07</td><td>125.07 ± 13.32</td><td>144.72 ± 17.5</td></tr><tr><td>DIN (µmol L<sup>-1</sup>)</td><td>0.29 ± 0.07</td><td>0.74 ± 0.24</td><td>0.85 ± 0.33</td><td>0.88 ± 0.12</td><td>0.77 ± 0.24</td></tr><tr><td>DIC:DIN</td><td>7371.9 ± 1940.8</td><td>3132.9 ± 999.1</td><td>4068.5 ± 4621.8</td><td>2625.3 ± 318.8</td><td>3276.9 ± 1031.0</td></tr><tr><td>POC:PON</td><td>8.10 ± 2.41</td><td>9.26 ± 1.07</td><td>14.64 ± 2.04</td><td>14.70 ± 1.42</td><td>15.55 ± 1.33</td></tr><tr><td>POC:DOC</td><td>nd</td><td>0.15 ± 0.02</td><td>0.26 ± 0.06</td><td>0.31 ± 0.06</td><td>0.28 ± 0.05</td></tr><tr><td>DOC:TOC</td><td>nd</td><td>0.87 ± 0.01</td><td>0.80 ± 0.03</td><td>0.77 ± 0.02</td><td>0.78 ± 0.03</td></tr><tr><td>Si(OH)<sub>4</sub>:DIN</td><td>2.43 ± 1.31</td><td>4.14 ± 2.18</td><td>12.17 ± 8.99</td><td>9.90 ± 2.10</td><td>16.34 ± 6.38</td></tr><tr><td>DIN:DIP</td><td>0.47 ± 0.12</td><td>4.22 ± 1.28</td><td>nd</td><td>4.65 ± 0.52</td><td>2.78 ± 1.21</td></tr><tr><td>Si(OH)<sub>4</sub>:DIP</td><td>1.11 ± 0.63</td><td>15.11 ± 6.36</td><td>37.01 ± 17.16</td><td>46.79 ± 14.23</td><td>37.51 ± 24.46</td></tr></tbody></table>

Most of the chemical parameters were, in general, more concentrated (up to 5-times) in the Bouraké lagoon than at the reference reefs R1 and R2, and increased from the outer to the inner reef (Figure 2.9a-d; Table 2.1, Table 2.2; Appendix A -Figure A2.2). In addition, despite the Bouraké lagoon receives new seawater during the rising tide, only Si(OH)<sub>4</sub> had a decent regression coefficient showing either positive and negative correlation with the falling and the rising tide (Figure 2.9e-h; Appendix A - Figure A2.2; Table A2.3.). It reached the highest value of 16.74 µmol L<sup>-1</sup> during low tide on the inner reef with an average of 11.93 ± 4.27 µmol L<sup>-1</sup>, and the lowest value of 3.38 µmol L<sup>-1</sup> during high tide on the outer reef with an average of 8.22 ± 3.14 µmol L<sup>-1</sup>, 3- to 6-time higher than at the reference stations R2 and R1. The lack of a clear effect of the tide for the other chemicals causes their accumulation inside the lagoon system. Ratios of organic and inorganic carbon, nitrogen, and nutrients showed significant differences between the Bouraké lagoon and the reference reefs (Table 2.1, Table 2.2) with higher average POC:PON, POC:DOC, Si(OH)<sub>4</sub>:DIN, Si(OH)<sub>4</sub>:DIP and DIN:DIP (PO<sub>4</sub><sup>3-</sup>), and lower average DIC:DIN and DOC:TOC in the Bouraké lagoon compared to reference reefs.
<figure><img src="image_21.png" /><figcaption>**Figure 2.9.** Orthosilicic acid, organic carbon and nitrogen parameters measured during diel cycles in 2017 and 2019 (pooled data, see also Appendix A Figure A2.2.) at R1, R2 and the Bouraké reefs (outer, middle and inner) (a-d). Boxes (n = 6-14) represent the interquartile range (25th and 75th percentile); the horizontal line is the median, and the whiskers represent the data range (i.e., minimum and maximum). Changes are illustrated across a 12 h tidal phase in Bouraké (e-h). Linear regression lines are plotted for each falling (HT to LT) and rising tide (LT to HT). Shaded boxes have only a graphical significance and only suggest the tide changes during measurements.</figcaption></figure>

**2.3.3 Benthic community distribution and species identification**

*Benthic community distribution.* The cluster analysis and nMDS allowed grouping the 24 transects in the Bouraké lagoon in six clusters corresponding to habitat descriptors, namely clusters A, B1, B2,
C1, C2, and C3 (Figure 2.10a; Appendix A - Figure A2.3 for details of the community descriptors, and Table A2.4 for transect averaged data). The nMDS produced an exhaustive representation of the Bouraké lagoon benthic communities and abiotic features (2-dimensional stress = 0.136) confirmed by ANOSIM (Global R = 0.948, *p* = 0.001). For the benthic community distribution, a clear separation (95% confidence interval represented by the ellipse in Figure 2.10a) was found for cluster A and B2, including most transects located on the middle and inner reefs (Figure 2.10b). For both, branching corals were the dominant biotic descriptor with an average of 81% and 31% coverage, respectively (Appendix A - Figure A2.3), with a maximum of 96% in cluster A (T23, Appendix A - Table A2.4).

Among branching corals, the two most abundant genera were *Acropora* and *Montipora*. For the abiotic features of the substrate, dead corals and rubbles characterized transects in clusters A and B2, respectively. Species richness (Figure 2.10a) was high in all transects of the Bouraké lagoon, except T13 and T24, both found at the middle and inner reefs' limits. The abiotic substrate of cluster C1 was characterized by 66% mud, 12% rocks and 10% sand (Appendix A - Table A2.4 for detailed cover data per transect). Only a few branching corals (< 10%) were found, but species richness was relatively high (6 at T9 and 10 at T10). Cluster C2 was distinct, which is not surprising due to its location in a relatively shallow convergence zone that divides the lagoon into two parts. There, the substrate is made of coarse sand (13%) and rocks (12%) and is mainly colonized by macroalgae and sponges (31% and 32%, respectively). Species richness in the area was heterogeneous and ranged from 4 to 12. *Dictyota* spp. and *Halimeda discoidea* were the main macroalgal species, while *Rhabdastrella globostellata* was the dominant sponge species in the area. Cluster B1, located on the outer reef, is characterized by an abundance of soft corals (48%) and rubbles (21%), and high biological richness (Figure 2.10a).
<figure><img src="image_22.png" /><figcaption>**Figure 2.10.** Benthic community and bottom substrate characterization in the Bouraké lagoon. Hierarchical Ward's method cluster dendrogram (top) and non-metric multidimensional scaling (nMDS) of abiotic and biotic percent cover and species richness per transect (T1-T24) (a). Colored circles represent clusters of transects identified in the dendrogram; circle size corresponds to species richness. Ellipses represent 95% confidence intervals. Dominant biotic and abiotic descriptors were used to describe the benthic community and bottom substrate for each cluster in (b). The satellite image is from georep New Caledonia database (https://georep.nc/), and the QGis software was used for transect georeferencing.</figcaption></figure>

Cluster C3 is characterized by coarse sand (49%), rocks (17%) and a few benthic organisms such as macroalgae (10%) and soft corals (8%). Principal component analysis (PCA) reduced the multicollinearity problem and the first two Principal Components accounted for a cumulative 71.2% of the dataset variance. In particular. The PCA plot (Figure 2.11) allowed to assign the transects to three distinct groups depending on their position in the study area. The distinction among transects groups in the biplot is clear and they are grouped based on their location in the outer, middle or inner lagoon reefs. The outer reef sites are characterized by sponges, macroalgae and soft corals, which appear to correlate with NOx. Conversely, branching corals are the shared and characteristic feature
of the middle and inner reef sites. However, these two reef groups differ in their major correlation to
NH₄⁺ for middle reef sites and POC, DOC, Si(OH)₄, and PO₄³⁻ for the inner sites.

<figure><img src="image_23.png" /><figcaption>**Figure 2.11.** Principal component analysis (PCA) between benthic community (macroalgae, sponges, corals, branching corals and massive corals) data and environmental parameters (PON, POC, DOC, Si(OH)₄, PO₄³⁻, NOx, and NH₄⁺) measured for each transect (n = 24). The length of the vectors indicates the contribution of each parameter. The first dimension explains 48.1% of the variance, and the second dimension explains 23.1% of the variance. Colours refer to the cluster subdivision (Figure 2.10).</figcaption></figure>

*Species identification.* A total of 66 coral species were identified from the Bouraké lagoon (**Appendix A - Table A2.5**). Most of the species belong to the family Acroporidae (17 *Acropora* species, 2 *Anacropora* and 4 *Montipora*) and Merulinidae (15 species). In total, 58 species were identified from the reference reef R2, 29 of which were also found in the Bouraké lagoon. Overall, the hard coral fauna within the lagoon was characterized by species commonly found around the Grande Terre, with some of them typically found in turbid coastal environments such as *Pseudosiderastrea tayamai* and *Heliofungia actiniformis*. They were not encountered at the reference site. Remarkably, two New Caledonia endemic coral species, *Cantharellus noumeae* and *Polycyathus fulvus*, both described from coastal habitats characterized by terrigenous sediment inputs (Noumea lagoon and Prony Bay, respectively), were common in the innermost reef of the Bouraké lagoon. The Bouraké lagoon also had 28 species of macroalgae (14 Phaeophyceae, 9 Chlorophyta and 5 Rhodophyta), including the crustose coralline algae *Lithothamnium* sp., *Lithophyllum* sp., and *Hydrolithon reinboldii*, and 11 sponge species belonging to eight families of the class Demospongiae (**Appendix A - Tables A2.5; A2.6**), which were found mainly in the coral matrix and sediment.
**2.3.4 Stable isotope signatures**

Mean δ¹³C and δ¹⁵N values were significantly different between Bouraké outer (B02) and Bouraké inner (B05) considering pooled macroalgae species (δ¹³C: W = 1, p < 0.01; δ¹⁵N: W = 6, p < 0.05) and pooled sponges species (δ¹³C: W = 10, p < 0.05; δ¹⁵N: W = 0, p < 0.001). Samples from Bouraké (B05) showed ¹³C-depleted and ¹⁵N-depleted values and were mostly plotted in the bottom left of the plot, while sample from Bouraké (B02) showed ¹³C-enriched and ¹⁵N-enriched and were mostly plotted in the top right of the plot (Figure 2.12).

<figure><img src="image_24.png" /><figcaption>**Figure 2.12.** Plot of δ¹³C versus δ¹⁵N (mean ± SD when more than 1 sample) of macroalgae, sponges, fish, mangrove leaf and seagrasses collected at Bouraké outer (B02), Bouraké inner (B05), and Reference site (R1). Label with * refer to sample collected in March 2019, while the other were collected in December 2020.</figcaption></figure>

For fish, the δ¹³C values ranged from -20.37 ± 0.17 ‰ to -13.20 ± 0.42 ‰, while δ¹⁵N values ranged
from 6.95 ± 0.14‰ to 8.53 ± 0.35‰ depending on species. For *Dascyllus aruanus*, differences
between R1 and B02 were relatively moderate (Table 2.3, Figure 2.12) without statistical significant
differences (δ¹³C: W = 6, p = 0.2; δ¹⁵N: W = 0, p = 0.2). Considering all sponge species the δ¹³C
signature ranged from -18.70 ± 2.39‰ to -11.95 ± 0.70‰ at Bouraké (B02), while from -21.81 ±
0.26‰ to -15.36 ± 0.36‰ at Bouraké (B05), while sponge δ¹⁵N signature ranged from 8.29 ± 1.28‰
to 15.16 ± 0.52‰ at Bouraké (B02), while from 2.01 ± 1.69‰ to 3.93 ± 0.84‰ at Bouraké (B05)
(Table 2.3). The δ¹⁵N signature of *Hyrtios* sp. *Callyspongia* sp. and *Dysidea* sp., at B02 showed also higher values compared to fish in the same zone and at reference reef R1 (Table 2.3). Macroalgae δ¹³C signature ranged from -17.03‰ to -10.19 ± 1.76‰ at Bouraké (B02), while from -22.63 ± 2.11‰ to -17.22 ± 1.08‰ at Bouraké (B05), while Macroalgae δ¹⁵N signature ranged from 0.53 ± 1.26‰ to 7.98 ± 2.53‰ at Bouraké (B02), while from -0.49‰ to 3.10‰ at Bouraké (B05) (Table 2.3). Mangrove leafs showed the lowest δ¹³C values with -28.02 ± 1.13‰ (Table 2.3, Figure 2.12).

<table><caption>**Table 2.3.** Summary of isotopic signature (mean ± SD, when more than 1 sample) in carbon (δ¹³C ‰) and nitrogen (δ¹⁵N ‰) for macroalgae, fish, sponges, mangrove leaf and seagrasses collected in March 2019 (Mar-19) and December 2020 (Dec-20) at R1, Bouraké outer (B02), and Bouraké inner (B05).</caption><thead><tr><th>Year</th><th>Site</th><th>Type</th><th>Genus/Species</th><th>δ <sup>15</sup>N ‰</th><th>δ <sup>13</sup>C ‰</th></tr></thead><tbody><tr><td>Mar-19</td><td>R1</td><td>Fish</td><td>Stegastes nigricans (n = 5)</td><td>7.15 ± 0.33</td><td>-14.66 ± 0.46</td></tr><tr><td>Mar-19</td><td>R1</td><td>Fish</td><td>Amblyglyphidon ternatensis (n = 2)</td><td>8.19 ± 0.39</td><td>-15.44 ± 0.17</td></tr><tr><td>Mar-19</td><td>R1</td><td>Fish</td><td>Chaetodon lunulatus (n = 3)</td><td>7.25 ± 0.23</td><td>-13.20 ± 0.42</td></tr><tr><td>Mar-19</td><td>R1</td><td>Fish</td><td>Dascyllus aruanus (n = 2)</td><td>8.53 ± 0.35</td><td>-15.58 ± 0.12</td></tr><tr><td>Mar-19</td><td>B02</td><td>Fish</td><td>Dascyllus aruanus (n = 3)</td><td>7.25 ± 0.23</td><td>-13.20 ± 0.42</td></tr><tr><td>Mar-19</td><td>R1</td><td>Fish</td><td>Apogon cf. crassiceps (n = 3)</td><td>6.95 ± 0.14</td><td>-20.37 ± 0.17</td></tr><tr><td>Mar-19</td><td>R1</td><td>Fish</td><td>Chaetodon bennetti (n = 1)</td><td>8.06</td><td>-13.54</td></tr><tr><td>Mar-19</td><td>B05</td><td>Sponge</td><td>Rhabdastrella globostellata (n = 3)</td><td>5.28 ± 0.37</td><td>-20.73 ± 0.73</td></tr><tr><td>Mar-19</td><td>B05</td><td>Macroalgae</td><td>Caulerpa serrulata (n = 1)</td><td>1.70</td><td>-21.04</td></tr><tr><td>Mar-19</td><td>B05</td><td>Macroalgae</td><td>Sargassum sp. (n = 2)</td><td>0.97 ± 0.70</td><td>-26.37 ± 0.58</td></tr><tr><td>Mar-19</td><td>B05</td><td>Macroalgae</td><td>Stypopodium sp. (n = 1)</td><td>0.98</td><td>-21.24</td></tr><tr><td>Mar-19</td><td>B05</td><td>Macroalgae</td><td>Halimeda discoidea (n = 1)</td><td>-1.38</td><td>-26.42</td></tr><tr><td>Mar-19</td><td>B05</td><td>Macroalgae</td><td>Halimeda distorta (n = 1)</td><td>1.24</td><td>-27.28</td></tr><tr><td>Dec-20</td><td>B02</td><td>Sponge</td><td>Hyrtios sp. (n = 2)</td><td>13.64 ± 1.96</td><td>-11.95 ± 0.70</td></tr><tr><td>Dec-20</td><td>B02</td><td>Sponge</td><td>Callyspongia sp. (n = 2)</td><td>15.16 ± 0.52</td><td>-18.35 ± 0.35</td></tr><tr><td>Dec-20</td><td>B02</td><td>Sponge</td><td>Haliclona sp. (n = 2)</td><td>8.29 ± 1.28</td><td>-15.25 ± 4.73</td></tr><tr><td>Dec-20</td><td>B02</td><td>Sponge</td><td>Dysidea sp. (n = 2)</td><td>13.76 ± 1.26</td><td>-18.70 ± 2.39</td></tr><tr><td>Dec-20</td><td>B05</td><td>Sponge</td><td>Hyrtios sp. (n = 2)</td><td>3.93 ± 0.84</td><td>-15.36 ± 0.36</td></tr><tr><td>Dec-20</td><td>B05</td><td>Sponge</td><td>Callyspongia sp. (n = 3)</td><td>2.70 ± 0.56</td><td>-21.50 ± 0.14</td></tr><tr><td>Dec-20</td><td>B05</td><td>Sponge</td><td>Haliclona sp. (n = 2)</td><td>2.01 ± 1.69</td><td>-21.81 ± 0.26</td></tr><tr><td>Dec-20</td><td>B05</td><td>Sponge</td><td>Dysidea sp. (n = 2)</td><td>2.94 ± 2.46</td><td>-21.71 ± 0.77</td></tr><tr><td>Dec-20</td><td>B02</td><td>Macroalgae</td><td>Stypopodium sp. (n = 2)</td><td>7.98 ± 2.53</td><td>-14.08 ± 1.15</td></tr><tr><td>Dec-20</td><td>B02</td><td>Macroalgae</td><td>Turbinaria conoides (n = 2)</td><td>0.53 ± 1.26</td><td>-10.19 ± 1.76</td></tr><tr><td>Dec-20</td><td>B02</td><td>Macroalgae</td><td>Sargassum sp. (n = 1)</td><td>3.31</td><td>-15.23</td></tr><tr><td>Dec-20</td><td>B02</td><td>Macroalgae</td><td>Dictyota sp. (n = 1)</td><td>4.78</td><td>-17.06</td></tr><tr><td>Dec-20</td><td>B05</td><td>Macroalgae</td><td>Stypopodium sp. (n = 1)</td><td>3.10</td><td>-21.04</td></tr><tr><td>Dec-20</td><td>B05</td><td>Macroalgae</td><td>Turbinaria conoides (n = 1)</td><td>-0.81</td><td>-18.28</td></tr><tr><td>Dec-20</td><td>B05</td><td>Macroalgae</td><td>Sargassum sp. (n = 1)</td><td>-0.49</td><td>-17.99</td></tr><tr><td>Dec-20</td><td>B05</td><td>Macroalgae</td><td>Dictyota sp. (n = 3)</td><td>-0.71 ± 0.25</td><td>-22.63 ± 2.11</td></tr><tr><td>Dec-20</td><td>B05</td><td>Macroalgae</td><td>Padina sp. (n = 2)</td><td>2.95 ± 0.11</td><td>-17.22 ± 1.08</td></tr><tr><td>Dec-20</td><td>B05</td><td>Mangrove leaf</td><td>Mangrove leaf (n = 4)</td><td>-1.26 ± 1.95</td><td>-28.02 ± 1.13</td></tr><tr><td>Dec-20</td><td>B05</td><td>Plant</td><td>Seagrass (n = 2)</td><td>-4.61 ± 1.07</td><td>-21.67 ± 0.39</td></tr></tbody></table>
**2.4 Discussion**

**2.4.1 Physical and chemical characteristics of the Bouraké lagoon**

The Bouraké lagoon covers an estimated area of ca. 20 ha that penetrates a mangrove forest, large enough to assess the combined effects of extreme environmental conditions on an established coral reef ecosystem. The multi-scale approach confirmed previous findings (Camp et al., 2017), showing that the Bouraké lagoon is hottest (ranging from 17.5 to 33.8°C), deoxygenated (ranging from 1.87 to 7.24 mg L⁻¹), and acid (ranging from 7.23 to 7.92 pHT units) when compared to neighboring reefs. Besides, salinity was significantly higher than at the reference reefs during both winter and summer (with maxima of 37.22 and 39.37, respectively).

Several marked differences in the environmental conditions between the Bouraké lagoon and the reference reefs, both in the absolute range, and in the variability of the measured environmental parameters. First, the seawater temperature is higher in summer in the Bouraké lagoon (Figure 2.3), but it is also colder during winter, resulting in an annual temperature range of 17.5-33.8°C. We compared temperatures recorded at Bouraké lagoon to those of the reference St R2, which showed the most typical temperature range for shallow water temperatures in the south of New Caledonia (i.e., 22-28°C, Varillon et al., 2021). We notice that in Bouraké, temperatures were 40% of the time above 28°C during the summer of 2020, while winter temperatures were on average 46.5% of the time lower than 22°C. While warming is considered the main threat for coral reefs, low temperatures (< 20°C) can cause coral bleaching by inducing responses similar to high temperatures, including a reduction in the *Symbiodiniaceae* cell density and chlorophyll a content (e.g., Saxby et al., 2003; Hoegh-Guldberg and Fine, 2004; Hoegh-Guldberg et al., 2005; Kemp et al., 2011; Bellworthy and Fine, 2021). The negative effect of cold temperatures is even more substantial during neap tides when colonies on the reef crest are exposed to air for hours at low temperatures during cold winters. For example, Porter et al. (1982) and Davis (1982) reported > 90% coral mortality in shallow (< 2 m) reefs of the Dry Tortugas following the winter of 1976-1977 when temperatures reached 14°C. This is consistent with observations (data not shown) during the cold winter of 2019 when the upper 12-20 cm of several massive and branching corals had died.

Second, in the Bouraké lagoon, benthic assemblages are continuously exposed to large fluctuations in the main environmental parameters, toward sub-optimal values. Some of these environmental fluctuations are entirely predictable. For instance, marine organisms are exposed to a temperature fluctuation of about twice the reference reefs' amplitude (up to 6.5°C vs 3.5°C) in a single day. Dissolved oxygen fluctuations were similar between stations but in a significantly different range: 3.7 to 6.8 mg L⁻¹ at B2 and 5.4 to 7.8 mg L⁻¹ at the reference stations. According to the organisms
tolerance to DO fluctuation, which is quite unknown in corals, low DO concentrations can change
fish tidal migration in the mangrove (Dubuc et al., 2019a). Besides, tidal modelling revealed that, at
the reference reefs, pH, DO (Figure 2.4), and temperatures slightly increased in the afternoon and
decreased during the night. This finding agrees with what should be expected from reef metabolic
activities and daily cycles but, in the Bouraké lagoon, these parameters, including salinity (Figure
2.7), are entirely driven by tides. Here, seawater pH and DO varied between extremely low values at
low tide and close-to-normal values during high tide (see also Figure 2.8a-c for pH). Finally, the
timing of the tide was out of phase between sites, with a delay of about 45 minutes at high tide and
1.5 h at low tide in the Bouraké lagoon (Figure 2.2).

The unique environmental conditions measured in the Bouraké lagoon are linked to its unique
topographical and geomorphological characteristics, the resulting water circulation and the direction
of the tide. New water from the lagoon enters through the channel at each rising tide and flows into
the semi-enclosed lagoon towards the large mangrove area behind it. This water initially had ambient
values of pH, temperature and DO, but, during the trip, it mixes with the acidic, warm and
deoxygenated water in the system and the mangrove area, therefore gradually changing from its
original values. Inside the mangrove forest, we hypothesize that the water chemistry further changes
due to the metabolic reactions in the sediments, and mangrove roots (e.g., Alongi et al., 2004;
Bouillon et al., 2007; Gleeson et al., 2013; Call et al., 2015). Conversely, on a falling tide, the seawater
becomes gradually more acidic, hot and oxygen-depleted because the water that resided in the
mangrove area gradually drains out of the system. This takes about 6 h, during which the vast
reservoir of shallow mangrove water continues to be chemically altered, becoming increasingly
acidic, oxygen-depleted and hot. As a result, significant spatial differences in pH between the outer
reef (the entry of the lagoon) and the inner reef (near the mangrove forest), as well as a considerable
delay in the synchronization of the tidal shift were measured (Figure 2.5b). Interestingly, because
the volume of seawater discharged in 6 h is so large, it affects also the area outside the system where
we measured similar seawater conditions as inside, even if it mixes with the main lagoon's water (see
Figure 2.5c, St U vs St T). It means that the area (and the organisms) affected by the suboptimal
parameters is larger than previously thought. The species living in this area have likely developed
specific mechanisms to withstand the very fluctuating environmental conditions, and as such, they
warrant further attention. Since the fluctuations are linked to tidal phases, it could be argued that
organisms living in the Bouraké lagoon may benefit from periods of normal conditions at high tide,
during which they can recover from the stress they have experienced at low tide (e.g., Rivest et al.,
2017). While this could be partially the case for species living on the outer reef, close to the main
lagoon, the pH and DO inside the Bouraké lagoon rarely reach normal values, and persist longer as
the low tide is delayed by 1.5 h compared to the reference reef (Figure 2.2).

Preliminary results from a hydrodynamic model of the study site suggest that tide-associated water mass movements are spatially heterogeneous and likely to play an essential role in shaping coral resilience to extreme conditions (see discussion below). Indeed, one can imagine a single water mass moving with the same physical characteristics from the mangrove area towards the outer reefs or in the opposite direction depending on the tide. However, the complex geomorphology of the Bouraké lagoon, its bottom topography and the complex web of coral reefs and mangrove trees on the edges deviate and probably change the seawater physical and chemical properties. Significant spatial differences in pH within each reef area (inner, middle and outer reefs; **Figure 2.5a, b**), as well as throughout the water column were measured (i.e., between the surface and the bottom; **Figure 2.5d, e**). In general, bottom seawater was 0.1-0.2 pHT units lower than the surface, probably due to a pumping mechanism by the water mass of more acidic pore water from the sediments. The pH also differed spatially within the inner reef, by up to 0.3 pHT units (for instance St. A vs St. C; **Figure 2.5a**), perhaps due to the influence of stagnant water on the mangrove edges or a more intense metabolic activity by the local benthic community. Dissolved oxygen concentrations between the surface and the bottom were only significantly different at St. N on the middle reef (**Figure 2.6f**). This station is mainly characterized by mud as the current is lower than anywhere else in the Bouraké lagoon. Here, the sediment's biological activity possibly traps the oxygen making it less available to the water column.

Throughout the Bouraké lagoon, organisms are exposed to extreme and fluctuating suboptimal
physical parameters, such as pH, and DO which are more pronounced on the bottom and last longer,
and with more extreme values, on the inner reefs. It is also true for some of the seawater chemical
parameters measured, which show higher concentrations in the Bouraké lagoon than on the reference
reefs (see Table 2.2). For instance, orthosilicic acid, phosphate, dissolved and particulate organic
carbon, and particulate organic nitrogen were 1.4 to 4.2-fold more concentrated on the inner reef than
at station R2. Within the Bouraké lagoon in general, chemicals increased from the outer to the inner
reef, and except for [NOx], [NH4]⁺, [PO4]³⁻, they never return to “normal” values despite the Bouraké
system receives new seawater during the rising tide. The high concentrations in orthosilicic acid and
organic compounds, both dissolved and particulate are due to the combined effect of more acidic and
organic-rich water coming out of the mangrove forest during a falling tide (Figure 2.9) and the
system’s particular morphology, limiting the complete renewal of the seawater, especially at the inner
reefs.
2.4.2 Stable carbon and nitrogen isotope signature of the Bouraké lagoon

Light intensity, temperature or nutrient concentrations (and their incorporation rates) may change productivity rates of primary producers and, therefore, their δ¹³C signatures. At the same time, variation in ammonium and nitrate concentrations in seawater can modify δ¹⁵N signatures of the organic matter sources (Hemminga and Mateo, 1996, Briand et al., 2015; Fey et al., 2021). Similarly, spatial fluctuation on isotopic signatures of sponges and macroalgae in the Bouraké lagoon, between the outer zone (B02) and the inner zone (B05) was found. In the specific, sponges and macroalgae in the outer zone of the Bouraké lagoon were ¹⁵N-enriched and ¹³C-enriched compared to the inner zone. This trend could be due to recycling of N between the host and the symbionts (e.g., Weisz et al., 2007; Southwell et al., 2008; Mohamed et al., 2010), utilization of other nitrogen sources (i.e., bacteria, phytoplankton, Fey et al., 2021), or higher capacity to take up organic N from POM (Sitnikova et al., 2016). Differences between inner and outer in Bouraké could also be explained by the different concentration of nutrients in the site. Although with not significant differences, [NOₓ] and [NH₄]⁺ were more concentrated in the outer part of the lagoon, while organic matter such as DOC and POC were significantly more concentrated in the inner part of the lagoon. This suggest that the inner zone was more influenced by terrestrial and mangroves inputs, while the outer zone were more influenced by marine sources. This hypothesis is supported by a recent study showing higher enrichment in ¹⁵N for macroalgae, which incorporate more marine nitrogen sources depending on seasonal variations in nitrogen stock characteristics (Fey et al., 2021). Although, no spatial and/or temporal differences were found in invertebrate and fish between estuary and mouth of the mangrove forest at Foa (New Caleodnia) (Letourneur et al., 2018), this result strengthen with study showing strong spatial variability in δ¹³C (higher) and δ¹⁵N (lower) in intermediate reefs in New Caledonia (Briand et al., 2015). Furthermore, in agreement with the results of this chapter, a gradient in C and N isotopic values was also found from the entrance to the end of two bay in French Polynesia, where lower δ¹³C values and higher δ¹⁵N values were measured at the end of each bay, compared with the entrance for POM and algae turf (Letourneur et al., 2013). Similarly, macroalgae in the inner zone of the Bouraké lagoon incorporated dissolved nutrients of terrestrial and mangrove origin, and sponges filtered mainly detritus and enriched seawater carbon. This mangrove inputs could also confirm by the stable signature of mangrove leaf in Bouraké lagoon, which are ¹³C depleted and ¹⁵N depleted. Although stable isotopes should be used with caution in this study due to the moderate sampling effort, they provided a first global assessment of OM sources and how various organisms in such an extreme coral reefs ecosystem could incorporate this OM.
**2.4.3 Effects of physical and chemical conditions on species distribution**

Extreme environmental conditions, such as those measured in the Bouraké lagoon, are known to strongly affect the metabolism, growth and even survival of several marine organisms, particularly those tolerating only a narrow range of environmental changes such as scleractinian corals (e.g., Coles and Jokiel, 1977; Hoegh-Guldberg and Smith, 1989; Hoegh-Guldberg, 1999; Fitt et al., 2001). For instance, *in-situ* studies at volcanic CO₂ seeps have shown that chronic exposure to ocean acidification (near-future pCO₂ levels) can cause a reduction in coral diversity and lower the recruitment and abundances of structurally complex hermatypic corals. Moreover, shifts in competitive interactions between taxa and a decrease in cover and richness of soft corals and sponges were also observed (e.g., Fabricius et al., 2011; Enochs et al., 2015; Sunday et al., 2017; Agostini et al., 2018). However, the Bouraké lagoon features high coral, sponge, macroalgae and CCA cover and species richness, adding at the check-list proposed by Camp et al. (2017) an additional 46 coral species (totaling 66 species and 33 genera), 28 species of macroalgae and 11 species of sponges (**Appendix A-Table A2.5**). Such a high number of species has never been reported for mangrove systems characterized by marginal conditions, at least concerning the three major benthic groups taxa investigated here (e.g., Yates et al., 2014; Camp et al., 2019).

In general, given the extensive literature demonstrating the negative effects of suboptimal abiotic conditions on corals, these findings are unexpected and suggest that corals in the Bouraké lagoon may have developed unique survival and adaptive mechanisms. Some studies have reported similar findings, but none has ever reported such high coral species diversity (e.g., Yates et al., 2014; Schoepf et al., 2015; Shamberger et al., 2018; Camp et al., 2019). For instance, in Palau (Micronesia), the highest coral cover (> 60%) and species diversity (21 scleractinian genera) were found at the lowest pH study site of the Nikko Bay station (Barkley et al., 2015). Studies in the Virgin Islands' mangrove system have reported over 30 coral species growing in marginal conditions (Yates et al., 2014; Rogers, 2017). Similarly, in a recent study of two Australian mangrove lagoons, characterized by relatively extreme environmental conditions (low pH, low oxygen and high temperature), Camp et al., (2019) identified 12 and 29 scleractinian coral species in the Woody Isles and at Howick Island, respectively. Among the 66 species identified, 29 of the most abundant coral species in New Caledonia were found at both the reference reef and in the Bouraké lagoon, indicating that species living at our study site are not very different from a typical bay-sheltered fringing reef. There is not an apparent selection in the coral form since massive (e.g., *Porites* spp.), corymbose (e.g., *Pocillopora digitata*), phaceloid (*Galaxea fascicularis*) and branching (*Acropora* spp.) species are equally abundant, as well as in their thermal and pH tolerance. Further experiments are underway at both the
molecular and phenotypic level to better understand the mechanisms of resilience used by the corals
from Bouraké.

Remarkably, the two coral species, currently considered New Caledonia endemics, thrive in the innermost benthic assemblages of the Bouraké lagoon, making it not only a unique natural laboratory as well as a potential conservation priority site. In the Bouraké lagoon, benthos species richness was very high throughout the system and the distribution of branching and massive corals was spatially heterogeneous (Figure 2.10b; Appendix A - Figure A2.3). Coral cover decreased near the mangrove, where the accumulation of fine sediments and exposure to air during low tide do not allow corals' survival (Appendix A - Figure A2.3). Branching corals were particularly abundant on the inner and middle reefs, with the highest cover of 96% in the inner reef (T23, Appendix A - Table A2.4). They became sparse on the outer reef, even absent at the system's entrance where soft and massive corals dominated. Macroalgae and sponges, including CCA, were quite cryptic throughout the Bouraké lagoon but found almost everywhere in the coral matrix and buried in the sediment. They are particularly abundant in a shallow area that divides the lagoon into two parts (transects T6-T8). There, a Venturi effect generates a strong current, and the substrate consists of coarse sand and rocks. The high flow and the bottom characteristics are both likely to promote macroalgae and sponge occurrences (averaged 30% and 32% cover, respectively). The sponge *Rhabdastrella globostellata* is particularly abundant (up to 40% cover) and forms massive banks embedding adjacent coral colonies. In general, macroalgae and sponges diversity was not particularly rich, with only 28 and 11 species, respectively, likely due to the sampling method. However, in the Indo-pacific mangrove systems, sponge diversity is, in general, not extremely high, especially if compared to the Caribbean (Nagelkerken et al., 2008). Few studies are available from Indo-Pacific mangrove sponges. The highest diversity was reported in a study in the mangrove of Banka Island (North Sulawesi, Indonesia), where 19 species were found (Calcinai et al., 2017). These findings on mangrove sponges in such a unique mangrove area in New Caledonia add to the limited knowledge of sponge species diversity in Pacific mangrove systems.

Water flow may play a critical role in the response of organisms to acidification (Cornwall et al., 2014; Hurd, 2015; Comeau et al., 2019), warming (Schoepf et al., 2018) and deoxygenation (Hughes et al., 2020). It has been reported to affect the diffusion boundary layer (i.e., a thin layer of stagnant water located around aquatic organisms) of corals, CCA and other calcareous macroalgae, altering their ability to calcify at low pH and to excrete metabolic wastes (reviewed in Nelson and Altieri, 2019). Knowing that flow speed could play a critical role and that deserves further investigations and measurements at the study site, two hypotheses can be made to explain the high diversity of the
Bouraké species and their resilience to suboptimal parameters: i) the species may benefit from the constant fluctuations of the physical and chemical parameters, ii) the species may benefit from heterotrophic inputs of the mangrove (in term of nutrients and organic matter).

Regarding environmental fluctuations, averaged daily variations in temperature, DO, and pH of about 3.79°C, 3.80 mg L⁻¹, and 0.63 pHT units, respectively. The temperature fluctuated by up to 6.55°C in a single day. Frequent exposure to stressful temperatures can induce acclimatization or adaptation in corals if the period of exposure is short enough to avoid mortality (Oliver and Palumbi, 2011; Palumbi et al., 2014; Schoepf et al., 2015; Rivest et al., 2017; Safaie et al., 2018). For example, in the Kimberly region (Australia), corals regularly exposed to temperatures up to 37°C, with daily variations of up to 7°C, appear less prone to bleaching and grow and calcify at rates comparable to corals in more thermally stable environments (Dandan et al., 2015; Schoepf et al., 2015; 2020). However, they are not immune to extreme heat stress events (Le Nohaïc et al., 2017). Another example is the corals in the back reef and shallow pools around the island of Ofu (American Samoa), which despite occasional daily fluctuations of up to 6°C, and an average daily temperature of 29°C in summer (Piniak and Brown, 2009; Oliver and Palumbi, 2011) sustain reasonable levels of coral cover (25-26%) and high diversity (Craig et al., 2001). Some studies tend to indicate that corals depended on the *a priori* 'frontloading' of genes involved in heat resistance in the coral host and/or the host's ability to adjust its physiology during short-term (weeks) environmental changes (Barshis et al., 2013; Palumbi et al., 2014). However, physiological adjustments have an energetic cost that corals cannot sustain in the long term, affecting other metabolic functions such as calcification. It could explain in part the lower calcification rates observed in some coral species, as seems to be the case for corals in the Bouraké lagoon (e.g., Camp et al., 2017).

There is also evidence that exposure to short-term oscillations in low pH, alone or in combination
with high temperature, can mitigate the impact of extreme environmental stressors on corals (Warner
et al., 1996; Oliver and Palumbi, 2011; Dufault et al., 2012; Schoepf et al., 2015; Safaie et al., 2018).
Species in the Bouraké lagoon appear to be thriving despite the large seawater pH variability (up to
0.6 pHT units). In general, species exposed to pCO₂ fluctuations above 500 µatm in their natural
environment display enhanced plasticity to future ocean acidification scenarios (Vargas et al., 2017;
Carstensen and Duarte, 2019). For example, fluctuations in pH could increase CCA tolerance to ocean
acidification by providing respite periods at ambient pH (Rivest et al., 2017), during which organisms
can calcify at a standard rate, compensating for decreased calcification during periods of lower pH
(Comeau et al., 2013; Cornwall et al., 2018). Diurnal variability in pH, typical of more variable pH
habitats, may confer tolerance to resident calcifying species via the selection of individuals better
adapted to survive in these environments (Rivest et al., 2017; Kapsenberg and Cyronak, 2019),
although transgenerational acclimatization is required (Cornwall et al., 2020).

In addition to changes in temperature and pH, which are the two most commonly tested environmental parameters, oxygen must also be considered. Despite the impact of reduced oxygen levels and its natural fluctuations on coral reefs has yet to be established, low DO (2-4 mg L⁻¹) seems to increase the sensitivity of branching corals, resulting in a decline in coral health, bleaching, and tissue loss (Haas et al., 2014; Hughes et al., 2020; Alderdice et al., 2021). This chapter shows that although the Bouraké system can reach conditions close to hypoxia for several coral species (< 3 mg L⁻¹; **Figure 2.4**), these latter seem to have promoted compensation mechanisms that allow them to survive in these conditions. The natural laboratory of Bouraké, where DO fluctuates with the tide, in combination with other environmental stressors, offers a perfect setting to test the practically unknown effects of deoxygenation in reef-building corals exposed to acid and hot conditions (Nelson and Altieri, 2019; Hughes et al., 2020).

Although corals appear to possess cellular mechanisms to counteract short-term osmotic changes (Mayfield and Gates, 2007), high and fluctuating salinity is possible additional stress that corals living in the Bouraké lagoon have to face daily, adding up to the already long list of suboptimal environmental parameters. *In-situ* studies have demonstrated that acute and prolonged decrease in salinity can affect the coral photosynthetic efficiency, resulting in a reduction of the amount of energy transferred to corals (Muthiga and Szmant, 1987; Manzello and Lirman, 2003) and induce coral death (e.g., Jokiel et al., 1993). The response of corals to a change in salinity is related to the strength and duration of the hypo-hypersaline exposure and the species tolerance. For example, *Stylophora pistillata* seems able to acclimate more effectively to hypo- rather than to hyper-saline conditions (Ferrier-Pagès et al., 1999). Further experiments are needed to assess the effect of high and fluctuating salinity on the physiology of corals in Bouraké.

Besides the hypothesis that environmental variability improves the metabolism of organisms,
particularly their resilience to extreme conditions, a series of other physical (e.g., current flow) and
chemical parameters (e.g., organic matter) in the Bouraké lagoon may work in combination to offset
or enhance these effects. Mangrove habitats are highly productive ecosystems and are sites of intense
carbon processing, with a high potential impact on the global carbon budget (e.g., Borges et al., 2003;
Dittmar et al., 2006; Bouillon et al., 2014). In the Bouraké lagoon, benthic communities might have
access to a range of heterotrophic inputs, nutrients, carbon, and nitrogen sources. These sources can
be metabolized by the species to increase their energy budget and cope with the suboptimal
parameters, but they can also become toxic if too concentrated or depleted, leading to functional
limitations. Exceptionally, high concentrations of organic and inorganic carbon and nitrogen were
measuered, but also of some nutrients, notably silicates and phosphorus, and we confirmed the
potential contribution of the mangrove in those inputs, especially during the falling tide **(Figure 2.8 and Figure 2.9; Table 2.2; Appendix A- Figure A2.1 and Figure A2.2)**. Dissolved organic carbon
contributes significantly to the TOC pool (POC+DOC), with a concentration increase between the
reference sites and the Bouraké lagoon, reaching maximum values on the inner reef. High OM content
can increase DOC availability to corals, providing the sustainable energy to withstand extreme
environmental conditions (Levas et al., 2015). Some studies showed that the high OM of turbid reefs
can support elevated coral heterotrophy that can facilitate energy maintenance during periods of stress
(Anthony and Fabricius, 2000).

Nutrients could partially explain the distribution of organisms throughout the Bouraké lagoon (Figure 2.11). Indeed, NOₓ concentrations were higher on the outer reef, dominated by sponges, macroalgae and soft corals, while NH₄⁺ was high on the middle reef and POC, DOC, Si(OH)₄, and PO₄³⁻ were higher on the inner reef. Both the middle and inner reefs are characterized by the highest branching coral cover. Nitrates can accumulate inside the host cells, possibly favoring sponges and macroalgae, while ammonium is the preferred source used by coral symbionts (Raven et al., 1992). However, the nutrient negative or positive effect on corals' physiology is difficult to demonstrate experimentally (Atkinson et al., 1995; Szmant, 2002; Bongiorni et al., 2003). Van De Waal et al., (2009) have shown that the performance of organisms depends on concentrations of, and ratios between, different nutrients, and between organic and inorganic matter/components and the possible imbalance due to environmental changes. Bouraké lagoon is mostly N-limited (DIN:DIP < 10 and Si(OH)₄:DIN > 1), which confirms the findings of Justić et al. (1995) and is similar to the conditions observed in other New Caledonian mangroves (Jacquet et al., 2006). Nutrients limitation has been demonstrated to lower the temperature effect at which coral bleaching occurs (Wiedenmann et al., 2013; Ezzat et al., 2016b; 2019), which contrasts with the resilience of Bouraké corals to the warming in the summer of 2016 (10-20% bleaching only) compared to other reefs in New Caledonia (up to 90% bleaching) (Benzoni et al., 2017). Corals symbionts recycle their host's metabolic wastes and take up dissolved inorganic nitrogen (DIN) and phosphorus (DIP) from seawater (Grover et al., 2003; Pernice et al., 2012; Rosset et al., 2015), both of which are used to produce vital organic molecules. Nutrient starvation can occur when the availability of one type of essential nutrient decreases, resulting in an imbalanced N:P ratio of inorganic nutrients in seawater (Wiedenmann et al., 2013; D'Angelo and Wiedenmann, 2014). The N:P ratio in the Bouraké lagoon was 2.8:1 and 4.6:1 at the middle and the reference reefs, respectively, which is lower than the range calculated for average reef waters of 4.3:1 to 7.2:1 (Crossland et al., 1984, Furnas et al., 1995). Although these data should be considered
cautiously, they suggest that the Bouraké lagoon seawater is not limited in phosphorus, an essential
nutrient in coral resilience to bleaching (Ezzat et al., 2016a; Rosset et al., 2017). Seawater in the
Bouraké lagoon was not limited in Si (Si(OH)₄:DIP > 10 and Si(OH)₄:DIN > 1; Justić et al., 1995),
and Si was six times more abundant on the inner reef than elsewhere in the system **(Figure 2.9; Table
2.2)**. Silicates are an important source of nutrition and skeletal construction for primary producers
such as sponges. Orthosilicic acid is a biologically available form of silicon that is poorly soluble at
a very low pH. In the Bouraké lagoon, pH fluctuates with the tide, and one can expect that orthosilicic
acid would rise during the falling tide. This elevated concentration of orthosilicic acid could be
involved in the growth and persistence of the Bouraké large banks of *Rhabdastrella globostellata*, as
previously reported for other sponges in the shallow hydrothermal vents in the Pacific Ocean
(Maldonado et al., 1999; Cárdenas and Rapp, 2013; Bertolino et al., 2017).

Information about light, turbidity, current, bacteria biomass, phytoplankton sources as well as other
biological communities still lacking to fully understand this complex and dynamic system and the
functioning of this complex and dynamic coral ecosystem. However, data of this chapter already
demonstrate that the Bouraké lagoon's uniqueness as a natural laboratory for studying the adaptive
responses of corals and other reef species to the combination of multiple suboptimal environmental
parameters, which are, to some extent, worse than those projected for the future. The investigations
of this chapter indicate that the geomorphology of this unique site has not changed for the last 80 to
100 years, certainly longer. With this in mind, at least in the previous century, the environmental
conditions remained unchanged, and the corals of the Bouraké lagoon could have experienced the
current extreme conditions for several generations. Most importantly, the species found in the
Bouraké lagoon are not unique to the mangrove habitat. They are common throughout New Caledonia
and the SW Pacific region, suggesting that they have used specific strategies to cope with the
suboptimal environmental conditions.

**2.5 Conclusion**

A multi-scale approach was used to characterize the physical and chemical environmental parameters
of one of the most realistic natural laboratory for extreme environmental conditions, the semi-
enclosed lagoon of Bouraké (New Caledonia), and accurately map its benthic community for the first
time. In this chapter several physical and chemical parameters such as pH, DO, temperature, and
salinity, but also nutrients and organic matter were studied and result showed that: i) they fluctuate
between low and high tides, ranging from suboptimal-extreme to near normal values; ii) although
predictable according to the tide, they differed spatially, and iii) suboptimal values persisted longer
and were more acute on the inner reef. Results clearly show that fluctuations are: i) predictable, at
least for some of the physical parameters for which enough data were collected (i.e., pH, DO,
temperature and salinity); ii) mainly driven by the tide; and iii) that seawater nutrient imbalance and
organic inputs increase during the falling tide and originate from the mangrove forest and associated
sediments. Although several studies suggest that ocean acidification, warming and, to some extent,
deoxygenation will lead to a reduction in biodiversity, increase in bleaching and reef dissolution, in
the Bouraké lagoon, a healthy reef with high coral cover and species richness, but also sponges and
macroalgae (including CCA) was found. It was beyond the scope of this study to assess the
contribution of environmental variability and nutrient imbalance to the organism' stress tolerance
under extreme conditions. However, both coexist in the Bouraké lagoon, suggesting evidence of their
contribution to the survival of organisms in extreme environmental conditions. This chapter provides
evidence that this is possible in existing natural habitats, giving a glimmer of hope for the future of
coral reefs. Further experiments are needed to reveal the mechanisms involved in the organisms'
resilience to such conditions. Finally, the compelling basis for using this site as a natural laboratory
for study the multitude of complex stressors acting together on life-long adapted coral reefs were
provided.
CHAPTER 3:
SPONGE ORGANIC MATTER RECYCLING: REDUCED
DETRITUS PRODUCTION UNDER EXTREME
ENVIRONMENTAL CONDITIONS

<figure><img src="image_25.png" /></figure>

The fieldwork in the Bouraké lagoon, where all *in-situ* sponge incubations were undertaken
## Resumé

Le chapitre précédent a mis en évidence les caractéristiques du site unique de la lagune de Bouraké en Nouvelle-Calédonie, caractérisé par des fluctuations du pH (7.23-8.10 unités), de la température (17.5-33.8°C) et de l'oxygène (1.87-7.24 mg L⁻¹), qui atteignent des valeurs extrêmes à marée basse. Malgré ces caractéristiques extrêmes, la lagune abrite 66 espèces de coraux, 11 espèces d'éponges et 28 espèces de macroalgues. Ce site est désormais reconnu pour l'étude des réponses des organismes aux conditions extrêmes. Parmi les différentes éponges qui peuplent Bouraké, une en particulier et qui est de loin la plus abondante, *Rhabdsastrella globostellata* s'avère être la plus massive. Cette éponge a été choisie comme modèle d'étude pour comprendre les mécanismes qui lui permettent d'être aussi abondante malgré des conditions extrêmes. Ce troisième chapitre met en évidence la manière dont le métabolisme de l'éponge évolue en fonction des conditions environnementales, notamment la forte température, l'acidification et la désoxygénation.

Les éponges constituent un élément clé des écosystèmes coralliens et jouent un rôle important dans les cycles du carbone et des nutriments. En convertissant le carbone organique dissous (COD) en détritus cellulaires (i.e., la «boucle de l'éponge»), et en assimilant le COD en biomasse, les éponges soutiennent le fonctionnement des récifs coralliens, et maintiennent une productivité et une biodiversité élevées dans un environnement oligotrophe. Malgré l'importance de cette «boucle», on sait peu de choses sur la façon dont ces cycles seront affectés par les conditions environnementales futures. Ici, nous avons utilisé le laboratoire naturel de Bouraké, dont les caractéristiques ont été décrites dans le chapitre précédent et où les organismes ont été exposés pendant des siècles à des conditions environnementales variables et extrêmes, pour étudier les effets de l'acidification, du réchauffement et de la désoxygénation des océans sur le carbone organique, le recyclage des nutriments et l'activité photosynthétique de l'éponge *R. globostellata*. Des incubations *in-situ* ont été réalisées dans différentes conditions environnementales. Les données suggèrent que les valeurs extrêmes d'acidification et de désoxygénation, seules ou en interaction, n'affectaient pas substantiellement le métabolisme de l'éponge. Cependant, lorsque ces conditions sont combinées à une température élevée (> 31°C), il y a un changement dans le recyclage du carbone organique de l'éponge avec une diminution de la production de détritus, bloquant la voie de la «boucle de l'éponge». Ce chapitre est la première étude qui analyse les conséquences *in-situ* de conditions extrêmes sur le métabolisme d'une espèce d'éponge et sa capacité à recycler la matière organique ainsi que sur son activité phototrophique. Les résultats de ce chapitre pourraient mettre en évidence la façon dont les voies trophiques peuvent être affectées par les conditions océaniques changeantes.
Le travail présenté dans ce chapitre a été publié dans la revue *Marine Pollution Bulletin*.
Marine Pollution Bulletin 190 (2023) 114869

<figure><img src="image_26.png" /></figure>

Contents lists available at ScienceDirect

Marine Pollution Bulletin

journal homepage: www.elsevier.com/locate/marpolbul

<figure><img src="image_27.png" /></figure>

# Sponge organic matter recycling: Reduced detritus production under extreme environmental conditions

<figure><img src="image_28.png" /></figure>

Federica Maggioni<sup>a, b, *</sup>, James J. Bell<sup>c</sup>, Mireille Pujo-Pay<sup>d</sup>, Megan Shaffer<sup>c</sup>, Carlo Cerrano<sup>e</sup>, Hugues Lemonnier<sup>a</sup>, Yves Letourneur<sup>a</sup>, Riccardo Rodolfo-Metalpa<sup>a, b</sup>

DOI: https://doi.org/10.1016/j.marpolbul.2023.114869

<footnote><sup>a</sup> ENTROPIE, IRD, Université de la Réunion, CNRS, IFREMER, Université de Nouvelle-Calédonie, Nouméa 98800, New Caledonia</footnote>

<footnote><sup>b</sup> Labex ICONA International CO₂ Natural Analogues Network, JSPS, Japan</footnote>

<footnote><sup>c</sup> School of Biological Sciences, Victoria University of Wellington, P.O. Box 600, Wellington, New Zealand</footnote>

<footnote><sup>d</sup> Sorbonne Université, CNRS, Laboratoire d'Oceanographie Microbienne, LOMIC, F-66650 Banyuls-sur-Mer, France</footnote>

<footnote><sup>e</sup> Department of Life and Environmental Sciences (DiSVA), Polytechnic University of Marche, Ancona, Italy</footnote>
**Abstract**

Sponges are a key component of coral reef ecosystems and play an important role in carbon and nutrient cycles. Many sponges are known to consume dissolved organic carbon and transform this into detritus, which moves through detrital food chains and eventually to higher trophic levels via what is known as the sponge loop. Despite the importance of this loop, little is known about how these cycles will be impacted by future environmental conditions. During two years (2018 and 2020), the organic carbon, nutrient recycling, and photosynthetic activity of the massive HMA, photosymbiotic sponge *Rhabdastrella globostellata* were measured at the natural laboratory of Bouraké in New Caledonia, where the physical and chemical composition of seawater regularly change according to the tide. Main result showed that while sponges experienced acidification and low dissolved oxygen at low tide in both sampling years, a change in organic carbon recycling whereby sponges stopped producing detritus (i.e., the sponge loop) was only found when sponges also experienced higher temperature in 2020. The findings of this chapter provide new insights into how important trophic pathways may be affected by changing ocean conditions.

The work presented in this chapter was published in the journal *Marine Pollution Bulletin*.
**3.1 Introduction**

Exponentially increasing carbon dioxide emissions are causing major changes in the Earth's climate (IPCC, 2021). Ocean acidification (OA), ocean warming (OW) and ocean deoxygenation (OD) will have wide-ranging biological effects on marine organisms (IPCC, 2013). Coral reef survival is predicted to be compromised by climate change (Hughes et al., 2017), with impacts on reef structure and associated communities including biodiversity loss, ecosystem shifts, reduced habitat complexity, and declines in overall reef productivity (i.e., IPCC, 2013; Hoey et al., 2016).

Sponges are an important component of coral reefs across the world, and while corals are predicted to be generally negatively impacted by climate change (i.e., Hughes et al., 2003; Hoegh-Guldberg and Bruno, 2010), some sponges may increase in abundance and in some cases, become functionally dominant on coral reefs (Bell et al. 2013; Bennett, 2017; Bell et al., 2018b). For example, the combined effects of OA and OW have been shown to have no impact on growth, survival, or secondary metabolite biosynthesis in many sponge species (e.g., Pansini et al., 2000; Vicente et al., 2016; Lesser et al., 2016; Bennett et al., 2017). However, some studies have shown that sponges are negatively affected under future climate change scenarios with greater impacts on mortality rates and symbionts (e.g., López-Legentil et al., 2008; Massaro et al., 2012; Fan et al., 2013). Although these earlier studies mainly focused on stress responses and tolerance of sponges to climate change impacts, no studies have investigated to what extent future environmental changes will affect sponge nutrient and organic matter cycling.

The complex association of sponges with microbes, which includes photosynthetic symbionts, have resulted in one of the most diverse and complex holobionts (i.e., the host plus its associated microbes) in the marine environment (Pita et al., 2018). Based on the abundance and diversity of microbes in tissues, sponges can be classified into high microbial abundance (HMA) or low microbial abundance (LMA) (10⁵-10⁶ bacteria per g of sponge wet weight; Hentschel et al., 2006). While sponges are mainly heterotrophic organisms, many species form relationships with photosynthetic symbionts, where their energy budget depends on associated cyanobacteria or dinoflagellates (Taylor et al., 2008). Sponges play a key role in both carbon recycling and nutrient fluxes (e.g., sink and/or source of nitrogen, phosphate and silicate) in reef ecosystems, and in the movement of carbon between the benthos and higher trophic levels (e.g., Wulff, 2006; Bell, 2008; De Goeij et al., 2008; McMurray et al., 2016). By both converting dissolved organic carbon (DOC) into cellular detritus (i.e., the sponge loop pathway; De Goeij et al., 2013), and by assimilating DOC into biomass (Pawlik et al., 2016; McMurray et al., 2016; 2018), sponges support the coral reef functioning, and support high
productivity and biodiversity in otherwise oligotrophic environments (De Goeij et al., 2013, Rix et al., 2016, Pawlik and McMurray, 2020). Although the importance of these two different organic matter-recycling pathways has been identified, it is unknown how they will be impacted by predicted future changes in environmental conditions or whether sponges can switch between the sponge loop pathway and the production of biomass.

The largest organic resource in the oceans is dissolved organic matter (DOM) (Benner et al., 1992), which is released by primary producers. However, DOM is deemed biologically unavailable to most heterotrophic organisms directly (Carlson et al., 2002), and needs to be recycled in order to be available to higher trophic levels. In the water column, DOM is efficiently recycled by bacterioplankton through the microbial loop (Azam et al., 1983). In the same way, in shallow-water coral reefs, benthic species, particularly corals, release a large amount of DOM in the form of mucus, which can be recycled by sponges (Yahel et al., 2003; De Goeij et al., 2013; Mueller et al., 2014; Rix et al., 2016; 2018; Achlatis et al., 2018; Hoer et al., 2018). The sponge loop was first demonstrated for cryptic sponges, which transform DOM into a source of energy that is more readily available to other benthic reef fauna, particulate organic matter (POM) in the form of detritus (e.g., De Goeij et al., 2013; Alexander et al., 2014; Rix et al., 2017; Archer et al., 2017). This detritus subsequently feeds the detrital food chain. Therefore, sponges not only generate food for their associated detritivores through the production of detritus, but also provide a critical trophic link between corals and sponge-associated detritivores, allowing them access to the energy- and nutrient-rich DOC produced by corals (e.g., Rix et al., 2018). However, not all sponges participate in the sponge loop, nor produce detritus. For such sponges, it seems that DOM is preferentially stored as biomass and eventually transferred to higher trophic levels only via direct predation on sponge tissue (McMurray et al., 2018; Pawlik and McMurray, 2020). While the sponge loop pathway is now well reported for some cryptic encrusting species (e.g., De Goeij et al., 2013; 2017), and in both encrusting and massive sponges living in deep-sea habitats (e.g., Rix et al., 2016; Bart et al., 2021), no studies have reported this pathway in massive Caribbean sponges inhabiting shallow reefs, for which only minor detritus production (i.e., no sponge loop pathway) has been reported in both LMA and HMA sponges (e.g., McMurray et al., 2018, Wooster et al., 2019). For such emergent sponges, it seems that DOM is preferentially stored as biomass and eventually transferred to higher trophic levels only via direct predation on sponge tissue (McMurray et al., 2018; Pawlik and McMurray, 2020). This apparent discrepancy in the detritus production may be due to the different methodologies used to assess the sponge loop. The two most commonly used methods are either: 1) incubations with isotopically enriched DOC, and following its release into the detritus (e.g., De Goeij et al., 2013; Rix et al., 2016;
2017; 2018); and 2) the In/Ex method where sponge recycling is measured by tracking the change in the composition of seawater as it is filtered by the sponges (e.g., McMurray et al., 2018; Wooster et al., 2019). Elements of both methodologies have been criticized (De Goeij et al., 2017), and further comparisons are needed for different sponge morphologies.

Natural laboratories where seawater physical and chemical values deviate from the normal coastal conditions are increasingly being used to study the responses of marine organisms to future climate change (e.g., Hall-Spencer et al., 2008; Camp et al., 2016; 2018; Burt et al., 2020; Maggioni et al., 2021). In this study, I used the semi-enclosed lagoon of Bouraké, New Caledonia (21°56′58.43″S; 165°59′29.46″E; **Appendix B – Figure B3.1**), that is a natural laboratory, characterized by regular tidal fluctuations of pH (8.10–7.23 pHT units), dissolved oxygen (DO, 7.34–1.87 mg L⁻¹), and temperature (from +1°C to +3°C). These parameters regularly change from close-to-normal conditions (high tide, HT) to extreme conditions (low tide, LT) (Camp et al., 2017; Maggioni et al., 2021). When averaged (pHT = -0.3 units, T = +2°C, DO = -26 %, compared to nearby control sites), environmental values are close to future climate predictions (RCP 8.5, IPCC, 2014). These fluctuating environmental conditions occur with chronically high concentrations of nutrients, and both dissolved and particulate organic matter, especially during low tide (Maggioni et al., 2021). At Bouraké, despite these extreme environmental conditions, a diverse and abundant benthic community was found, with coral species composition and richness similar to the local control reefs where environmental conditions are at ambient levels (Maggioni et al., 2021). Among sponges, the massive *Rhabdastrella globostellata* (Carter, 1883) is the most abundant species at Bouraké, reaching up to 40 % cover (Maggioni et al., 2021). The massive sponge *R. globostellata* (Carter, 1883) is among the most abundant species at Bouraké, reaching up to 40% cover (Maggioni et al., 2021). This Indo-Pacific high microbial abundance (HMA) species (Moitinho-Silva et al., 2017a) has been demonstrated to efficiently filter bacteria cells and remove DOM from surrounding seawater (Hildebrand et al., 2022), fundamentally altering its composition.

The main aim of this chapter was to assess how the metabolism of *R. globostellata* (i.e., nutrient and organic carbon cycles) is affected by extreme environmental conditions, specifically, the three main drivers of future climate change: acidification, deoxygenation and warming. The effects of extreme conditions on the autotrophic and heterotrophic processes of the sponge holobiont were also assessed. Extreme conditions have been hypothesized to negatively affect the metabolism of sponges and their autotrophic and heterotrophic rates.