“Biodiversity, structure and trophic functioning of marine ...

FACULTAD DE CIENCIAS DEL MAR

UNIVERSIDAD CATÓLICA DEL NORTE

DOCTORADO EN BIOLOGÍA Y ECOLOGÍA APLICADA

“Biodiversity, structure and trophic functioning of marine communities

in Rapa Nui (Easter Island)”

Germán Zapata Hernández

Profesor Guía: Dr. Javier Sellanes

COQUIMBO, 2019




“Biodiversity, structure and trophic functioning of marine communities

in Rapa Nui (Easter Island)”

Por: Germán Zapata Hernández

Departamento Biología Marina

Fecha:

Aprobado Comisión de Calificación

_______________________________ Juan Macchiavello Armengol

Decano Facultad Ciencia del Mar

_______________________________ _______________________________ Profesor Guía Profesor Patrocinante

_______________________________ _______________________________

Comité Tutorial Comité Tutorial

_______________________________ _______________________________

Comité tutorial Profesor Externo

Tesis entregada como un requisito para obtener el título de Doctor en Biología y Ecología Aplicada en la Facultad de Ciencias del Mar. Universidad Católica del Norte. Sede Coquimbo.

2019




Departamento de Biología Marina

“Biodiversity, structure and trophic functioning of marine

communities in Rapa Nui (Easter Island)”

Actividad de Titulación presentada

para optar al Título de Doctor en

Biología y Ecología Aplicada


Coquimbo, Octubre de 2019




DECLARACIÓN DEL AUTOR

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Firma

2019

Agradecimientos

Primero que todo, dedicar esta tesis a toda mi familia Zapata y Hernández, en especial a mi madre

Ignacia Hernández y mi hija Paloma Zapata que forman parte de mi motivación e inspiración.

Me gustaría agradecer a todas las personas que contribuyeron de alguna manera a que esta tesis

doctoral llegara a buen puerto, entre ellos mis amigos de Rapa Nui Ricardo Hitorangi, Petero

Hitorangi, Victor Icka “Lonto”, Poki Tane Ahoa, Enrique Hey “Taka”, Tiare Hereveri, Henry Garcia

(RIP), entre otros seres mas. Esta tesis es para su isla, deseando que contribuya al entendimiento de

su hermoso ecosistema marino y que sea una herramienta útil para el desarrollo sustentable de Rapa

Nui.

Tambien agradecer al proyecto ESMOI-UCN por el apoyo durante estos 5 años de estudios en islas

oceánicas, en especial a mi profesor y mentor Javier Sellanes quien ha sido un pilar importante en mi

carrera como Biologo Marino y con quien hemos explorado la biodiversidad de numerosos rincones

del océano Pacifico sur. A Carlos Gaymer, Naiti Morales, Erika Merhoff, Sergio Carrasco, Ivan

Hinojosa, Ignacio Petit, Matthias Gorny (Oceana) por su apoyo durante las campañas en Rapa Nui.

A la comisión evaluadora de esta tesis Bernardo Broitman, Moises Aguilera, Chris Harrod y Beatriz

Yanicelli por sus importantes comentarios y revisiones. A Rodrigo Rios por su amistad y enseñanza

sobre la ecología de comunidades y estadística multivariada. Ademas, agradecer al profesor Yves

Letourneur (Universite de la Nouvelle Caledonie) por recibirme en su laboratorio durante mi pasantía

doctoral y por darme la oportunidad de seguir explorando y estudiando los maravillos ecosistemas de

arrecifes de coral del mundo a través del proyecto IDEES (postdoctorado).

Por otro lado, me gustaría agrader a mis compañeros y amigos del doctorado BEA promoción 2015

(Myriam, Maibe, Juan, Solange y Cesar) con los cuales tuvimos extensas maratones de estudios,

intensas discusiones de ciencias y multiples asaditos anti-estrés. Tambien a mis amigos Felipe, Beto,

Pachichi, Juanana, Cesar-rulo, escuela Jiwasa Jatiña, Roberto y Pato Garcia, Victor Catelletto, JC,

Elmer, Thony, J. Naretto, Mitro, Brimar Ltda., a mis primos Rorro, Vito, Pablito, Karla y mis Tios

Carlos y Hector Zapata Avila quienes siempre estuvieron atentos a las distintas etapas de mis estudios,

viajes y aventuras, entregando siempre las buenas vibras necesarias para que todo saliera bien.

Finalmente dedicar esta tesis a toda la gente que lucha por la conservación de nuestros ecosistemas

naturales, quienes luchan contra el saqueo de nuestros recursos naturales, quienes luchan por una

sociedad más justa y por la dignidad de los “otros”, y a quienes durante las manifestaciones fueron

golpeados, torturados, violados, encarcelados, mutilados y asesinados en las calles por carabineros y

militares durante el estallido social iniciado desde el 18 Octubre de 2019.

Table of contents

Resumen i

Abstract ii

Chapter 1: INTRODUCTION 1.

Coral reef biodiversity and threats 1.1

Community structure dynamics 1.2

Trophic functioning in coral reefs 1.3

The Rapa Nui marine ecosystem 1.4

General goals 1.5

Chapter 2: Diel dynamics of fishes and mobile invertebrates at Rapa Nui

multiple use marine protected area. *Article submitted to: Aquatic

Conservation: Marine and Freshwater Ecosystems

2.

Introduction 2.1

Methods 2.2

Results 2.3

Discussion 2.4

Acknowledgements 2.5

References 2.6

Chapter 3: Diel changes in the structure and trophic functioning of mobile

benthic invertebrate assemblages in coral reefs of Rapa Nui (Easter

Island). *Article submitted to: Marine Biology

3.

Introduction 3.1

Materials and methods 3.2

Results 3.3

Discussion 3.4


References 3.6

Chapter 4: Tracing trophic pathways through the marine ecosystem of

Rapa Nui (Easter Island): A stable isotope approach. *Article submitted

to: Aquatic Conservation: Marine and Freshwater Ecosystems

4.

Introduction 4.1

Methods 4.2

Results 4.3

Discussion 4.4


References 4.6

Chapter 5: GENERAL CONCLUSIONS 5.

References 6.

Annexes 7.

Appendix 1 A.1

Appendix 2 A.2

i. RESUMEN

Los arrecifes de coral son ecosistemas marinos que albergan una alta biodiversidad a nivel

mundial, proveyendo una gran cantidad de servicios ecosistémicos. Rapa Nui es una isla

oceánica remota ubicada en el centro del océano Pacifico sur y sus arrecifes de coral

representan el limite oriental de la distribución de este tipo de ecosistemas. Esta isla es

considerada un “punto caliente” de biodiversidad, donde altos niveles de endemismo han

sido reportados en invertebrados y peces costeros. Sin embargo, su biodiversidad marina se

encuentra amenazada por diferentes factores humanos (e.g., sobrepresca, contaminación,

plactico, especies invasoras), pero aun ha sido escasamente estudiada en términos biologicos

y ecológicos.

Con el fin de conocer los patrones temporales (dia-noche) de organización comunitaria, sus

impactos en el funcionamiento trofico y las principales fuentes de materia organica que

sustentan a las comunidades marinas en Rapa Nui, este estudio consideró: i) determinar los

cambios dia-noche en la composición, riqueza, abundancia y biomasa de invertebrados y

peces de arrecife, ii) determinar como los cambios en la estructura comunitaria pueden

repercutir en el funcionamiento trófico de las comunidades de arrecifes de coral en Rapa Nui

y iii) determinar las posiciones tróficas de los consumidores y la importancia relativa de las

principales fuentes de materia organica (e.g., fitoplancton, macroalga y corales) sustentando

a los ensambles marinos en el ecosistema marino de Rapa Nui.

A través de buceo SCUBA se realizaron una serie de censos visuales (replicados durante el

dia y la noche) en seis sitios alrededor de Rapa Nui, para determinar eventuales cambios en

la estructura comunitaria (composición, riqueza, abundancia y biomasa) de arrecifes de coral

y como estos cambios podrían afectar la estructura trófica de los ensambles de invertebrados

y peces, y por ende en el funcionamiento del arrecife. Adicionalmente, mediante el uso de

análisis de isótopos estables (AIE) se estimaron las posiciones tróficas (PT) de diferentes

especies costeras, se compararon medidas de diversidad trófica en diferentes ensambles

marinos (i.e., mesozooplancton, invertebrados y peces de arrecife y peces pelagicos) y se

utilizaron modelos de mezcla Bayesianos para estimar la importancia relativa de diferentes

fuentes de materia orgánica (MO; i.e., corales, macroalgas y fitoplancton) en las

comunidades marinas.

Los resultados indican notables diferencias en la estructura de invertebrados y peces entre el

día y la noche. Un patrón inverso fue detectado entre los ensambles, donde valores altos de

riqueza, abundancia y biomasa fueron estimadas para peces durante el día, en contraste a

invertebrados que fueron estimados durante la noche. En términos funcionales, durante el día

los peces fueron dominados por especies herbívoras, carnívoras y planctívoras, mientras los

invertebrados por especies herbívoras y carnívoras. Sin embargo, durante la noche los peces

fueron dominados por solo dos especiea carnívoraa y otra planctívora, mientras los

invertebrados principalmente por especies detritívoras (ofiuroideos y holoturoideos). Por lo

tanto, debido a esta disminución en la abundancia de peces carnivoros y un aumento

importante en la abundancia de invertebrados crípticos durante la noche, se hipotetiza que

una disminución en el riesgo de depredación podría ser un factor importante determinando

los cambios en estructura comunitaria durante el día y la noche.

Por otro lado, pese a que los ensambles de invertebrados cambian de composición,

incrementan su riqueza, abundancia y biomasa durante la noche, estimaciones de índices de

diversidad funcional isotópica revelaron diferencias significativas en los valores del índice

de Unicidad isotópica (IUni), indicando que pese a un incremento en la biodiversidad durante

la noche, el ensamble nocturno tiende a ser tróficamente más redundante como respuesta a

los patrones de actividad de taxa detritívoras. Por lo tanto, debido a estas importantes

diferencias en la estructura y roles funcionales de las especies entre el día y la noche, es

necesario incluir a las comunidades nocturnas en el monitoreo, manejo y conservación de los

arrecifes de coral de Rapa Nui. Adicionalmente, las especies de invertebrados endémicas

tuvieron una abundancia y biomasa baja, ejerciendo una escasa influencia en el

funcionamiento trófico en los arrecifes de coral y potencialmente siendo vulnerables frente a

cambios o perturbaciones ambientales.

Los análisis de isótopos estables mostraron un claro enriquecimiento en 13C y 15N desde

especies de invertebrados (mesozooplancton, fauna emergente, macrobentos, invertebrados

de arrecife), peces de arrecife, peces pelágicos y aves marinas. Estimaciones de las posiciones

troficas de la especies indican que la mayoría de los invertebrados son consumidores

primarios and algunas taxa consumidores secundarios (PTrango=2.0–3.6); los peces de

arrecife tuvieron un amplio rango (PTrango=2.3–4.5), junto a los peces pelágicos (3.6–5.4)

y las aves marinas se solaparon con los depredadores pelágicos (PTrango=4.0–5.1). Las

medidas de diversidad trófica (SEA: área de elipses estándar) indican que los ensambles de

invertebrados y peces de arrecife tienen una amplia diversidad trófica (SEAc=13.1 y 10.6

‰2, respectivamente) en contraste al mesozooplancton y peces pelágicos (1.6 y 4.2 ‰2,

respectivamente).

Estimaciones desde los modelos de mezcla Bayesianos indican que la materia orgánica

derivada de los corales (e.g., pólipos o mucus) podría ser una importante fuente nutricional,

utilizadas por diversas especies costeras (e.g., macrobentos: 58 %, invertebrados: 67 %, peces

de arrecifes: 62 % y algunos grandes depredadores: 41 %). En el caso de la macroalgas estas

podrían ser importantes principalmente para especies herbívoras como erizos (51 %). Por

otro lado, en algunas especies de peces pelágicos (e.g., Mahi-mahi, pez volador) la señal de

la producción fitoplanctonica fue predominante (44–40 %). Por lo tanto, la evidencia

obtenida en este estudio sugiere que, debido a la importancia de los corales como sustento de

MO y como refugio para la biodiversidad marina en Rapa Nui, una parte sustancial de los

esfuerzos de conservación tienen que ser focalizados hacia este grupo de especies y su

biodiversidad criptica.

Palabras Claves: Rapa Nui; arrecifes de coral; cambios día-noche; funcionamiento trófico;

fauna críptica.

ii. ABSTRACT

Coral reef ecosystems harbor a high biodiversity around the world, supporting a large amount

of ecosystem services. Rapa Nui is a remote oceanic island situated in the Central South

Pacific Ocean, and its coral reefs represent the eastern limit of their distribution. This island

is considered a “hot spot” of biodiversity, where a high level of endemism has been reported

for invertebrates and coastal fishes. However, although it marine biodiversity is threatened

by different anthropic factors (e.g., overfishing, pollution, plastic, alien species), it remains

under-studied in biological and ecological terms.

In order to characterize the temporal patterns (day-night) of community organization, their

effects on trophic functioning and the main organic matter sources supporting marine

communities on Rapa Nui, this study aimed to: assess diel changes in the composition,

richness, density and biomass of mobile benthic invertebrates and reef fishes, ii) determine

how community structure changes could impact in the trophic functioning of coral reef

communities on Rapa Nui, and iii) estimate the trophic position of consumers and the relative

importance of different sources of organic matter (e.g., phytoplankton, macroalgae and

corals) supporting marine assemblages found on Rapa Nui.

Using SCUBA, a series of visual censuses were conducted (replicated during day and night)

at six sites around Rapa Nui to assess variation in community structure (composition,

richness, density and biomass) of coral reefs, and how these differences could impact the

trophic structure of invertebrate and fish assemblages, and hence the functioning of coral

reefs. Additionaly, employing stable isotope analyses (SIA), the trophic position (TP) of

different coastal species and trophic diversity in different marine assemblages (i.e.,

mesozooplankton, reef invertebrates and fishes and pelagic fishes) were estimated, and the

relative importance of different organic matter sources (OM; corals, macroalgae and

phytoplankton) in different taxa was inferred using Bayesian mixing models.

Results suggest marked differences in the structure of invertebrates and fishes assemblages

during the day and night. An inverse pattern was detected between assemblages, where higher

values of richness, density and biomass were estimated for fishes during day, in contrast with

invertebrates, which were predominant during night. In functional terms, during the day

fishes were dominated by herbivore, carnivore and planktivore taxa, while for invertebrates,

herbivore and carnivore species prevailed. However, at night, fishes were dominated by only

one carnivorous species and other planktivorous, and invertebrates were largely dominated

by detritivore species (e.g., ophiuroids and holothuroids). Therefore, due to this decrease in

the density of carnivore fishes and an important increase of cryptic invertebrates during night,

it is hypothesized that a reduction in the predation risk could be an important factor

determining these daily changes in the community structure.

Conversely, the macroinvertebrate assemblage showed a shift in composition, an increase in

richness, density and biomass during night. Furthermore, estimates of isotopic functional

diversity indexes reveal significant differences in the Isotopic Uniqueness (IUni) values,

suggesting that despite an increase in the biodiversity during night, nocturnal assemblages

tend to be trophically more redundant, as a response to the activity patterns of detritivore

taxa. Therefore, due to these important differences in the structure and functional roles of

species between day and night, it is necessary to include nocturnal communities in the

monitoring, management and conservation plans of coral reefs of Rapa Nui, and likely

elsewhere. In addition, endemic invertebrates had low densities and biomass exercising

limited influence in the trophic functioning of coral reefs and are thus potentially vulnerable

to environmental changes or disturbances.

SIA showed a clear pattern of 13C and 15N enrichment from invertebrates (mesozooplankton,

emergent fauna, macrobenthos and reef invertebrates), towards reef fishes, pelagic fishes and

seabirds. TP estimations of species indicate that most invertebrates are primary consumers

and some taxa secondary consumers (TPrange=2.0-3.6); reef fishes had a wide trophic

position ranges (TPrange=2.3-4.5), together with pelagic fishes (TPrange=3.6-5.4) and

seabirds TP overlapped with that of pelagic predators (TPrange=4.0-5.1). Measures of

trophic diversity (SEA: standard ellipse area) indicated that invertebrate and reef fish

assemblages have wider trophic diversity (13.1 and 10.6 ‰2, respectively), in contrast to

mesozooplankton and pelagic fishes (1.6 and 4.2 ‰2, respectively).

Bayesian mixing model estimations indicated that coral-derived organic matter (e.g., coral

polips and mucus) could be an important nutritional sources used by a diverse range of coastal

species (e.g., macrobenthos: 58 %, reef invertebrates: 67 %, reef fishes: 62 %, and some

pelagic fish predators: 41 %). Macroalgae could be important mainly for herbivore species

such as sea urchins (51 %). Conversely, in some pelagic fishes (e.g., Mahi-mahi and flying

fish) phytoplankton-derived energy dominated (44-40 %). Therefore, due to the importance

of corals as an OM source and refuge for marine biodiversity in Rapa Nui, conservation

efforts need to be focused on coral reefs and their cryptic biodiversity.

Key Words: Rapa Nui; coral reefs; diel changes; trophic functioning; nocturnal cryptic

fauna.

Chapter 1.

INTRODUCTION

1.1 Coral reef biodiversity and threats

The South Pacific Ocean harbors a great diversity of ecosystems and benthic habitats,

including estuaries, mangroves, rock intertidal, seagrass, kelp forest, rocky reefs and coral

reefs (Evans et al. 2016). Within these ecosystems, coral reefs are known as the most

productive and rich in biodiversity on earth (Reaka-Kudla, 1997). These ecosystems provide

a wide and valuable collection of goods and services for humans (Brander et al. 2007),

including fisheries, tourism, coastal protection, and provision of building materials, that

together support social and economic development (Hughes et al. 2003, Hoegh–Guldberg et

al. 2007).

However, due to human activities, coral reef ecosystems are highly threatened around the

world. Global studies indicate that almost half of all coral reefs currently experience

intermediate to very high impacts (Halpern & Floeter 2008), and that 60 % of reef builder

coral species currently face local extinction and could even be lost approaching the year 2030

(Carpenter et al. 2008; Chivers et al. 2016). The most relevant anthropogenic stressors

include overfishing, ocean warming, acidification, invasive species, eutrophication,

terrestrial runoff and sedimentation (Cortés & Reyes-Bonilla 2017). These factors often have

dramatical consequences for biodiversity and ecosystem functioning (Magurran & Dornelas

2010); for example, certain cryptic species (or cryptofauna) that live hidden within the coral

matrix (e.g., cracks and boreholes) and others that feed directly from the coral itself, reduce

their densities when corals are disturbed (Stella et al. 2011). This loss could disrupt the

functioning of coral reefs (Miller 2015), due to the loss of taxa performing different functions

in the ecosystem (e.g., decomposition, bioturbation, nutrients cycling), as well as organisms

that provide protection and specialized habitats for other species (Birkeland 2015).

In this sense, ecosystem management aims to ensure the maintenance of all biological

components, through conservation of biodiversity across different levels of organization

from genes to ecosystems, to ensure ecosystem integrity and stability (Palumbi et al. 2009;

Heiskanen et al. 2016). Hence, to understand the current state of biodiversity and to identify

potential conservation needs (e.g., management, restoration and prevention), it is imperative

to monitor biological parameters of biodiversity, both structural and functional (Strong et al.

2015; Heiskanen et al. 2016). Moreover, knowing which species are present in an ecosystem

and their respective densities allows the recognition of species or functional groups that could

be threatened or at risk of extinction (Costello, 2015).

1.2 Community structure dynamics

Studies of communities provide relevant information of composition and structure of biotic

assemblages, including changes in spatial and temporal patterns (Jackson & Blois 2015). In

this sense, is widely recognized that activity patterns of some species can fluctuate in a daily

scale (24 h cycle) as a response to temporal changes in predation risk or due to temporal

partition among competitor species (Kronfeld-Schor & Dayan, 2003). Most important

components of biodiversity and biomass in coral reefs correspond to the cryptic fauna, which

could also stablish key trophic links for the functioning of coral reefs (Reaka-Kudla 1997,

Enochs et al. 2011). However, visual surveys of marine communities are typically performed

during day hours due to logistical restrictions such as weather conditions, nocturnal-diving

limitations, among others (Yeager & Arias-Gonzalez 2008). Hence, nocturnal species are

commonly underestimated (or not included at all) in coral reef surveys and their importance

for ecosystem functioning remains poorly understood (Glynn & Enochs, 2011, Bierwagen et

al. 2018). Indeed, studies of diel activity patterns in marine environments have mainly

focused on fishes, typically targeting single species (e.g., Cartamil et al. 2003, Boaden &

Kingsfor, 2012) or fish assemblages (e.g., Galzin 1987, Azzurro et al. 2007). Few studies

have considered these factors at a community level (e.g., coupling mobile invertebrates and

fishes), in spite of the fact that remarkable differences in community and functional structure

have been reported for tropical reefs across the diel cycle (e.g., Brewin et al. 2016).

1.3 Trophic functioning in coral reefs

Knowledge of the structure of food webs provides valuable information about species

composition, trophic relationship, energy flux (biomass) and biogeochemical cycles (e.g., C,

N, S) (Dunne et al. 2002, Maureaud et al. 2017). Functioning of coral reefs is strongly linked

to the primary productivity sources available to consumers and their efficient transference

into upper trophic levels (McMahon et al. 2016). Hence, identifying the dominant organic

matter pathways fueling biodiversity result critical for understanding how marine

communities respond face to changes in the abundance of primary producers (Brown et al.

2010) or to predict how ecosystems respond face to environmental disturbances (Glynn &

Enochs 2011). Modelling of coral reef food webs has been performed at some sites of the

Pacific Ocean, including Hawaii (e.g., Polovina 1984), the Great Barrier Reef (Jhonson et al.

1995), French Polynesia (Arias-Gonzalez et al. 1997) and Panama (Glynn 2004). However,

due to differences in the community structure and environmental scenarios, it is expected that

food webs may vary between coral reefs ecosystems (Enochs & Glynn 2017). Despite this,

recent studies using stable isotopes analyses in coral reef ecosystems have provided novel

insights into organic matter pathways (Kolasinski et al. 2011, Letourneur et al. 2013), trophic

structure (Kolasinski et al. 2016, Briand et al. 2016) and trophic ecology of selected species

(Carassou et al. 2008, Letourneur et al. 2017). Therefore, their application in studies of

trophodynamics could provide better knowledge on energy transference in coral reef food

webs (Bierwagen et al. 2018), also being useful as a baseline for the development of

ecosystem and fisheries models (e.g., Brown et al. 2010).

1.4 The Rapa Nui marine ecosystem

Rapa Nui (Easter Island) is considered as one the most isolated places in the world, positioned

400 km west from Salas y Gomez islet and ~3700 km from continental Chile (Castilla et al.

2014). These islands have emerged from the numerous seamounts which conform the Salas

y Gomez Ridge (Rodrigo et al. 2014). Rapa Nui has a triangular shape and a surface of 163.6

km2 (Arana 2014) and together with the Salas y Gómez islet are positioned close the South

Pacific subtropical gyre, which drives the main circulation pattern and the ultraoligotrophic

features found around these islands (Andrade et al. 2014). The marine flora and fauna in Rapa

Nui are considered depauperate compared to other island in the Indo-Pacific region (e.g.,

Boyko 2003), but the species that form local communities are highly endemic (Glynn & Ault,

2000; Evans et al. 2016). In this sense, both the level of isolation and local oceanographic

features have led Rapa Nui to represent a global hotspot of endemism (Roberts et al. 2002).

Different marine taxa have high endemism levels, for example 34% in mollusks, 33% in

sponges, 12% in bryozoan and 22% in coastal fishes (reviewed by Fernández et al. 2014).

The Marine Protected Area of Rapa Nui (RN-MPA) was recently declared (2018), protecting

coastal (coral reefs) and deeper habitats (e.g., mesophotic reefs, seamounts and hydrothermal

vents). However, a considerable number of factors threaten local marine biodiversity,

including overfishing of coastal species (e.g., slipper and spiny lobsters, octopuses,

gastropods, coastal fishes and sharks), invasive species, coastal erosion, terrestrial runoff,

increased mass tourism, plastic pollution, absence of sewage treatment, among others

(Figueroa & Rotarou 2016). Despite recent advances in conservation awareness, numerous

information gaps still exist, precluding the development of an adequate management strategy

and conservation actions in the Rapa Nui marine ecosystem.

The current state of knowledge of marine community structure in Rapa Nui is based on

qualitative information described by DiSalvo et al. (1988) and more recently evaluated

quantitatively by Friedlander et al. (2013) and Wieters et al. (2014), who included some

functional features, contributing to the understanding of the current state of coral reefs in

Rapa Nui. However, marine biodiversity assessments to date have largely focused on fish

assemblages and have exclusively been conducted using diurnal surveys, hence the

composition, structure and functional roles of nocturnal assemblages are still unknown.

Hence, integrating diurnal and nocturnal surveys could reveal important diel dynamics of

coral reef communities (mobile invertebrates and reef fishes), providing more accurate

biodiversity assessment needs for an adequate management and conservation of coral reefs

in Rapa Nui (Chapter 1).

Cryptic invertebrates living on coral reefs often display nocturnal behavior and can represent

a large proportion of biomass of benthic mobile invertebrates, potentially contributing to the

trophic functioning of coral reefs. However, little is known regarding nocturnal assemblages

in Rapa Nui and the trophic roles of nocturnal and cryptic fauna still needs to be

characterized. Hence, integrating species composition, density, biomass and stable isotope

data, would allow increased understanding how the assemblage of mobile invertebrates

potentially shift their trophic structure in a daily scale, and the implications of such shifts on

the functioning of coral reefs. In addition, assessing the relative importance of endemic taxa

in the assemblage and trophic structure of mobile invertebrates would increase our

understanding of their present population state and potential importance for ecosystem

functioning of the coral reef at Rapa Nui (Chapter 2).

Dietary studies of the marine fauna in Rapa Nui have been scarcely considered and to date

they have focused in some conspicuous fish species (DiSalvo et al. 2007) and a few

invertebrate taxa (e.g., Khon 1978, Osorio et al. 1993). In addition, low phytoplankton

production associated to ultraoligotrophic conditions, together with an extensive dominance

of scleractinian corals and a low macroalgae cover, could enhance the importance of

zooxanthellate corals as organic matter sources for the marine biodiversity inhabiting coral

reefs on Rapa Nui. However, the main organic matter pathways supporting this marine

ecosystem and the trophic structure of communities are still unknown. Therefore,

determining the relative role of different organic matter pathways fueling the different marine

assemblages (e.g., soft-bottom, reef invertebrates, pelagic invertebrates, fishes and seabirds),

could contribute to understand the role of autochthonous (e.g., macroalgae and

zooxanthellae) and/or allochthones (phytoplankton) primary production sources in

supporting consumers, and hence helping to predict how different assemblages could respond

face to potential environmental changes in this remote island (Chapter 3). Hence, integrating

the biodiversity, temporal dynamics and trophic role of species in the ecosystem could

provide crucial understanding about the functioning of Rapa Nui marine ecosystem.

1.5 General goals

i) To evaluate diel dynamics in the community structure of coral reefs at Rapa Nui.

ii) Determine the effects of diel changes on the trophic structure of marine communities in

coral reef at Rapa Nui.

iii) Estimate the relative importance of different organic matter sources (e.g., zooxanthellae

corals, macroalgae and phytoplankton) in supporting marine assemblages of the coastal

marine ecosystem of Rapa Nui.

Chapter 2

Diel dynamics of fishes and mobile invertebrates at Rapa Nui multiple use

marine protected area

Iván A. Hinojosa1,2,3, German Zapata-Hernández2,3,4, Amelia E. Fowles5, Carlos F.

Gaymer2,3,6 & Rick D. Stuart-Smith5

1Departamento de Ecología, Facultad de Ciencias y Centro de Investigación en Biodiversidad y Ambientes

Sustentables (CIBAS), Universidad Católica de la Santísima Concepción, Chile. 2Universidad Católica del

Norte, Facultad de Ciencias del Mar, Departamento de Biología Marina, Coquimbo, Chile. 3Millennium

Nucleus for Ecology and Sustainable Management of Oceanic Islands (ESMOI), Departamento de Biología

Marina, Coquimbo, Chile. 4Programa de Doctorado en Biología y Ecología Aplicada, Universidad Católica

del Norte, Coquimbo, Chile. 5Institute for Marine and Antarctic Studies, University of Tasmania, Nubeena

Crescent, Taroona, Tasmania 7053, Australia. 6Centro de Estudios Avanzados en Zonas Áridas, Coquimbo,

Chile (CEAZA).

2.1 Abstract

Most research on the ecology of shallow reefs is based on diving activity that takes place

during daylight hours. However, there is a well described shift in community structure

between periods of darkness and light, with the marked differences in day and night activity

patterns of fishes and invertebrates being presumed to reflect trade-offs between feeding and

predation. However, quantitative data on the daily dynamics of reef fish and invertebrates

are scarce, and the addition of data from night surveys will likely make important

contributions to our understanding of biodiversity and ecological baselines.

This study is based on repeated and standardized day-night visual surveys of fishes and

mobile invertebrates across a series of fixed transect lines at Rapa Nui (Easter Island),

allowing the characterization of variation in diel patterns between taxonomic and functional

(trophic) groups.

Distinct differences between taxonomic groups were observed, with fish being more than

two times more abundant during the day, whilst invertebrate densities and richness showed

an opposite trend, being greater at night.

Analysis of trophic groups showed that herbivorous and planktivorous fishes were more

abundant during the day, while biomass differences in the biomass of planktivorous fishes

were less marked between day and night surveys. Carnivorous fishes did not show any trends

between day and night, and top predators were observed only on some surveys at very low

densities. However, a taxonomic replacement was clearly apparent among carnivorous fish

species between day and night, e.g. labrid fishes, were practically absent during night

surveys.

Our results show that the great bulk of mobile invertebrates on the reef remained concealed

during the day, likely influenced by predation risk, potentially including pressure from labrid

fishes. Our results emphasize the need for consideration of nocturnally active invertebrates

in ecological studies of reefs, which presently focus heavily on fishes and diurnal surveys.

Keywords: biodiversity, coral, fish, fishing, invertebrates, Marine Protected Areas, reef,

taxon richness.

2.2 Introduction

Ecological interactions and energy flow through the food web on rocky and coral reefs may

be influenced by diel cycles in the activity of the mobile fauna, typically dominated by fishes

and mobile invertebrates. Multiple environmental cycles related to sun and moon phases

modulate such activity patterns (i.e. circadian, circatidal, circalunar and seasonal) (Tessmar-

Raible, Raible, & Arboleda, 2011), but they are ultimately believed to be primarily related to

trade-offs between predation risk (Kronfeld-Schor & Dayan, 2003) and feeding (including

the activity patterns of prey). Sheltering in cracks and refuges of the reef during daylight

hours, followed by nocturnal emergence (Brewin, Brown, & Brickle, 2016) is a common

strategy among small-bodied species vulnerable to predation. Such species may play

important ecological roles and constitute an important component in the trophodynamics of

shallow benthic communities (Boaden & Kingsford, 2012; Holzman, Ohavia, Vaknin, &

Genin, 2007). However, these taxa are generally missed or underestimated by most survey

methods (Aguzzi et al., 2012; Azzurro, Pais, Consoli, & Andaloro, 2007), an issue that is

further complicated as most mobile reef surveys are conducted during daylight hours.

Most coral reef fish studies have only considered species that can be surveyed during daylight

hours, with only a few studies on nocturnal species (Annese & Kingsford, 2005; Bosiger &

McCormick, 2014; Galzin, 1987). Nevertheless, nocturnal fishes can constitute about 25-

44% of the species found in tropical reefs: hence, the richness of biodiversity associated with

coral reefs may therefore be consistently under-represented (Boaden & Kingsford, 2012;

Holzman et al., 2007). In general, nocturnal species typically feed on prey such as plankton

and/or macroinvertebrates that are active at night, while herbivorous species tend to be

largely diurnal (Hobson, 1965). Nevertheless, planktivorous fishes can be diurnal, nocturnal

or both (Hobson, 1965; Hobson, 1991). Some tropical fishes also exhibit daily movement

patterns across habitats (Hart, Clemons, Wakefield, & Heppell, 2010), with some species

alternating between reefs, sand, and seagrass to feed or rest (Hitt, Pittman, & Nemeth, 2011),

where the habitat configuration allows regular movements and spatial-temporal dynamics in

the fish assemblages (Kruse, Taylor, Muhando, & Reuter, 2016). Also, differences in fish

assemblages can reflect variation in refuge availability, prey abundances, predation risk, and

rearing behavior (Harvey, Dorman, Fitzpatrick, Newman, & McLean, 2012), creating

important changes in the composition and structure of assemblages (Azzurro et al., 2007).

For many mobile invertebrate reef taxa, nocturnal emergence plays an important role,

changing the structure and trophic relationships of communities on a daily basis (Blackmon

& Valentine, 2013). Generally, reduced predation risk at night has been suggested as the

primary reason for nocturnal emergence for many invertebrates, such as shrimps (Clark,

Ruiz, & Hines, 2003), urchins (Dee, Witman, & Brandt, 2012) and holothurians (Hammond,

1982). However, the influence of predation risk on the diel activities of coral reef mobile

invertebrates has rarely been tested (Ory, Dudgeon, Duprey, & Thiel, 2014). Moreover, there

are few studies that have evaluated changes in the whole community structure of mobile

invertebrates at a daily scale (e.g., Brewin et al., 2016).

The potential existence of diel changes in marine community structure has generally been

ignored due to standardized sampling procedures, due to a lack of adequate technology and/or

sufficient resources for perform replicates at different points across the diel cycle (Aguzzi et

al., 2012). This has likely been underestimated our understanding of diversity and trophic

interactions in marine communities (Myers, Harvey, Saunders, & Travers, 2016), leaving

important gaps in understanding the effects of anthropogenic impacts on the diversity of

fauna (diurnal and nocturnal) associated with coral reefs (Knowlton, 1992; Knowlton &

Jackson, 2008). This is a key issue when planning conservation measures such as marine

protected areas (MPA), as they are generally based on daily surveys that do not only

underestimate biodiversity, but also poorly explain the ecological processes that generate the

observed biodiversity patterns and thus, the conservation objects targeted with the

conservation strategies.

The primary aim of this study was to use standardized surveys of reef fishes and invertebrates

to evaluate day-night differences in richness, density and community structure, and in

relation to fish, functional feeding groups. We hypothesized that differences in light

conditions between day and night periods could translate to changes in the community

structure and biomass distribution among trophic groups of reef fishes.

Rapa Nui (Easter Island) is located at the eastern edge of the Polynesian Triangle and is the

southeastern limit of coral distribution in the Pacific. Coral composition in Rapa Nui is more

similar to that in the Eastern Pacific rather than the broader Indo-West Pacific (Glynn et al.,

2007). Biodiversity inventories have recorded a total of 605 invertebrates and 216 fish taxa

around the island, with 400 species of mollusks and crustaceans (Fernandez, Pappalardo,

Rodriguez-Ruiz, & Castilla, 2014). The reef fauna is considered depauperate compared to

other Polynesian islands, which typically have about 5-10 times more species (Randall &

Cea, 2011). Due to the geographical isolation of Rapa Nui, there are high levels of endemism:

34% in mollusks, 33% sponges, 12% bryozoans and 22% in coastal fishes (Fernandez et al.,

2014), which increases to over 75% when considered as biomass (Friedlander et al., 2013).

Coral cover is also quite high (>50%) in comparison to other subtropical areas with similar

ocean climates, but it is dominated by only two scleractinian species, Porites lobata and

Pocillopora verrucosa (nb. only thirteen species of coral have been recorded altogether at

Rapa Nui) (Glynn et al., 2007; Hubbard & Garcia, 2003). Both coral species are found in

depths of approximately 5-7 m, but with Pocillopora spp. dominating until approximately

10-15 m, where P. lobata starts to progressively dominate as the depth increases (Hubbard

& Garcia, 2003; Wieters, Medrano, & Perez-Matus, 2014). Although many species of

macroalgae are known, macroalgal cover is generally low around the island (Santelices &

Abbott, 1987). Recent surveys indicate that 10 % of the reef substrate is covered with

coralline crustose algae (CCA) (Friedlander et al., 2013), and temporal and spatial variability

in different algae groups (i.e. articulated, crustose, ephemeral and leathery) have been

documented (Fernandez et al., 2014; Wieters et al., 2014).

Recent surveys have documented that the long-spined sea urchin Diadema savignyi and the

violet coral shell Coralliophila violacea are the most abundant mobile benthic invertebrates

(Friedlander et al., 2013). The diurnal fish fauna is dominated by small individuals of

planktivorous and herbivorous species, while apex predators such as sharks (e.g.

Carcharhinus galapagensis) are practically absent close the coast (Friedlander et al., 2013),

or present in low densities at some sites (N. Morales et al., in review). Herbivorous fishes

tend to be associated with Pocillopora reefs, the invertebrate-feeding fishes with P. lobata,

and planktivore species with articulated and leathery algae (Wieters et al., 2014).

Despite much recent effort to understand the structure and function of Rapa Nui ecosystems,

the ecology of subtidal communities remains poorly understood (Wieters et al., 2014), with

very limited knowledge of the nocturnal communities (DiSalvo, Randall, & Cea, 1988) and

behavior of endemic species. Diel movements of individuals can influence the perception of

population sizes and community composition, depending on the sampling time (Aguzzi et

al., 2012). Present understanding of the reef communities at Rapa Nui may therefore be

poorer than the survey effort may suggest, particularly if many of the endemic species are

nocturnally-active and poorly covered in daytime surveys. A secondary aim of the study was

to provide a more comprehensive knowledge of the reef communities at Rapa Nui, adding

new information relevant to the potential contribution of nocturnally-active species to the

coral reef food webs.

2.3 Material and Methods

Change in the community structure between day and night was assessed at six sites from

Easter Island; four sites at the western coast (Hanga Roa Sth, Hanga Roa SW, Manavai and

Motu Tautara) and two sites at the north coast (Anakena E1 and Anakena E2) (Fig. 1, Table

1). Standardized underwater visual census methods were conducted in March 2016 to

estimate the fish and mobile benthic invertebrates (thereafter “invertebrates”) richness and

their densities (10 to 15 m depths, visibility > 20 m). One 50 m long transect was conducted

at each site during the day (between 1100h to1500h). Transects were then replicated at the

same GPS point (± 5 m), direction and depth at night (between 2100h to 1200h). Reef Life

Survey (RLS; Edgar and Stuart-Smith 2014) methods were used to estimate densities and

sizes of fish, and invertebrates (e.g., gastropods, sea cucumbers, sea stars, sea urchins,

decapods). Brittle stars and shrimps were also included in our visual census as they were

obviously an abundant and important component of the night invertebrate assemblage.

Briefly, fish species sighted within 5 m from the transect line on either side were recorded

by a diver who swam slowly in a round trip along the transect. The number and estimated

size-category of each species was recorded according with size (total length) categories of

25, 50, 75, 100, 125, 150, 200, 250, 300, 350, 400, 500, 625 and > 625 mm. Digital

photographs were taken of unidentified species to later confirm their identities. Invertebrates

were surveyed along the same 50 m transect lines. Another diver swam along the bottom

recording all mobile invertebrates on the reef surface within 1 m of the line on either side,

also in a round trip along transect (detailed descriptions of methods are provided online

www.reeflifesurvey.com and in Edgar & Stuart-Smith, 2014)

No specific permissions were required for this location and activity as it was an observational

study, and it did not involve manipulation of endangered or protected species.

Figure 1.1. Sampling sites at Rapa Nui (Easter Island) where day and night visual census were

conducted in March 2016. Sth = South, and SW = Southwest abbreviation, respectively.

Fish density was expressed as number of individuals 500 m-2 and biomass was expressed as

kg 500 m-2. The biomass of individual fish was estimated using the allometric length-weight

conversion: W = aTLb, where parameters “a” and “b” are species-specific constants, TL is

total length in mm, and W is mass in grams (or Weight). Weight-length fitting parameters

were obtained from FishBase (www.fishbase.org) and the cross-product of individual

weights and numerical densities was used to estimate biomass density by species. Fishes

were categorized into four trophic groups (Herbivores, Planktivores, Carnivores, and Apex

predators) after Friedlander et al. (2013) and Wieters et al. (2014). Invertebrate densities were

expressed as number of individuals 100 m-2. Fish and invertebrate species richness were

estimated as the total number of species recorded per transect by the diver.

Paired t-student tests based on Log (x+1) transformed data were used to examine differences

in fish and invertebrate density and richness, fish biomass, and in the fish trophic groups

between day and nights surveys. Paired tests were used to account for the lack of

independence between day and night surveys at the same sites (Quinn & Keough, 2002).

Each site was considered a replicate.

Multivariate analyses were conducted in PRIMER v6 with PERMANOVA (Primer-E Ltd,

Plymouth, UK). Fish and invertebrate species data were analyzed separately. A one-way

PERMANOVA on square root transformed density by species using a Bray Curtis similarity

resemblance matrix was conducted to test the null hypothesis that community structure was

not significantly different between day and night surveys (as a fixed factor) utilizing fish and

invertebrate density data. To test for difference in trophic groups (biomass) between day and

night surveys, a one-way PERMANOVA was conducted on fish trophic groups (Herbivores,

Planktivores, Carnivores and Apex predators). Type III sums of squares (SS) was used as the

design and calculations of the Pseudo-F ratio and P value were based on unrestricted

permutations of the residuals under an unreduced model (Anderson, Gorley, & Clarke, 2008).

Similarity of percentages (SIMPER) was used to determine the species most responsible for

the percentage dissimilarities between day and night surveys, using Bray-Curtis similarity

analysis of hierarchical agglomerative group average clustering. Principal coordinates

http://www.fishbase.org/

analysis (PCO) was conducted to examine the relative differences in community structure

between day and night surveys on square root transformed density by species using a Bray

Curtis similarity resemblance matrix. Eigenvectors of species most responsible for the

separation among sites in ordination space were calculated using Spearman’s correlation

coefficients and displayed using vector diagrams on the PCO ordination overlaid on plot

(Anderson, 2003; Anderson et al., 2008). Similarly, another PCO was conducted but

considering the fish trophic groups.

2.4 Results

A total of 43 fish and 33 invertebrate taxa where observed during transect surveys. Marked

differences were seen in both species richness and density between day and night surveys.

Fish were more than twice as abundant during day surveys (mean ± SE 285.0 ± 68.3 indiv.

500 m-2) than during nights (122.2 ± 30.9 indiv. 500 m-2) (Paired t = 3.22, df = 5; P = 0.024)

(Fig. 1.2), however, differences in fish richness (day: 18.2 ± 1.2 taxa; night: 14.0 ± 0.9 taxa)

(t = 2.49, df = 5, P = 0.055) (Fig. 1.2) and biomass (day: 30.2 ± 16.1 kg 500 m-2; night: 9.3 ±

1.6 kg 500 m-2) (t = 1.66, df = 5, P = 0.159) (Fig. 1.3) were smaller and not statistically

distinct. The opposite trend was observed in invertebrates where lower densities were

observed during daytime surveys (224.5 ± 79.4 indiv. 100 m-2) and higher densities at nights

(551.2 ± 56.8 indiv. 100 m-2) (t = -3.15, df = 5, P = 0.025) (Fig. 1.2), and lower richness in

diurnal surveys (5.8 ± 0.6 taxa 100 m-2) compared to nights (15.5 ± 1.3 taxa 100 m-2) (t = -

8.90, df = 5, p < 0.001) (Fig. 1.2).

Figure 1.2. Dendity and richness of a) fish and b) invertebrate assemblages during diurnal and

nocturnal surveys in six coral reef sites around Rapa Nui.

Multivariate analyses showed that fish and invertebrate densities showed clear changes

among day and night surveys (PERMANOVA: fish Pseudo-F = 77.199; df = 1; P = 0.001;

invertebrates Pseudo-F = 77.094; df = 1; P = 0.002; Figs. 1.4 & 1.5). SIMPER analyses

showed that similarity among day surveys was 56.7 % in fish assemblages (Table 1.2). The

sunset wrasse Thalassoma lutescens, the surgeonfish Acanthurus leucopareius, the

butterflyfish Chaetodon litus and Fuentesi’s wrasse Pseudolabrus fuentesi contributed the

most to the similarity (48.8 %) (Table 1.2). Similarity among night surveys was 51.4 % where

the hawkfish Itycirrhitus wilhelmi and the soldierfish Myripristis tiki contributed the most to

this similarity (43.7 %) (Table 1.2). Concordantly, relatively high dissimilarity between day

and night surveys was found (67.7 %) where T. lutescens, M. tiki, the damselfish Chrysiptera

rapanui, A. leucopareius, I. wilhelmi, P. fuentesi and the feminine wrasse Anampses

femininus contributed with 42 % of dissimilarity of the fish community structure (Table 1.2).

Table 1.1. Results of permutational multivariate analyses of variances (PERMANOVA) testing

differences in the density of fish (a) and invertebrate (b) assemblages between day and night surveys

at Rapa Nui, based on Bray Curtis similarity matrices performed on fourth root transformed data.

Density

Density

Figure 1.3. Mean (± SE) biomass of fish (a) and the average invertebrate density (b) during diurnal

and nocturnal surveys in coral reefs around Rapa Nui.

Invertebrate structure showed a similarity of 56.3 % among day surveys, in which urchins

Diadema savignyi and Echinostrephus aciculatus contributed 63.9 % of this similarity.

During nocturnal surveys the community structure had a 61.1% similarity, where the brittle

stars Breviturma dentata, the urchin D. savignyi and the crab Calcinus pascuensis contributed

with 43.8 % (Table 1.3). The dissimilarity between day and nights surveys was 60% where

brittle stars, B. dentata, the violet coral shell, C. violacea, the guardian crab, Trapezia

punctimanus, the rock shrimps, Cinetorhynchus sp. and the sea cucumber, Stichopus

monotuberculatus contributed with the most with the dissimilarity (37.5 %) (Table 1.2).

Table 1.2. Results of the similarity percentage analysis (SIMPER) on fish assemblage density (fourth

root of density) between day and night at Rapa Nui.

Group: Day surveys

Average similarity: 56.73

Species Trophic Av.Abund Av.Sim Sim/SD Contrib% Cum.%

Thalassoma lutescens Carnivore 2.95 8.57 8.22 15.11 15.11

Acanthurus leucopareius Herbivore 3.36 7.30 1.98 12.88 27.99

Chaetodon litus Carnivore 2.36 6.16 3.54 10.86 38.85

Pseudolabrus fuentesi Carnivore 1.96 5.67 5.55 9.99 48.84

Density

Chrysiptera rapanui Planktivore 2.70 4.48 1.23 7.90 56.74

Itycirrhitus wilhelmi Carnivore 1.86 4.02 1.71 7.09 63.83

Aulostomus chinensis Apex 1.27 2.89 3.69 5.10 68.93

Heteropriacanthus cruentatus Planktivore 1.29 2.85 2.73 5.02 73.95

Forcipiger flavissimus Carnivore 1.40 2.62 1.20 4.61 78.56

Coris debueni Carnivore 1.35 2.39 1.14 4.21 82.77

Anampses femininus Carnivore 1.55 1.94 0.73 3.43 86.20

Gymnothorax eurostus Carnivore 1.01 1.92 1.17 3.39 89.58

Mulloidichthys vanicolensis Carnivore 0.96 1.54 1.16 2.72 92.30

Group: Night surveys


Species Av.Abund Av.Sim Sim/SD Contrib% Cum.%

Itycirrhitus wilhelmi Carnivore 3.37 12.02 3.26 23.37 23.37

Myripristis tiki Planktivore 2.69 10.43 2.97 20.29 43.66

Chaetodon litus Carnivore 2.50 7.56 2.00 14.70 58.36

Acanthurus leucopareius Herbivore 1.15 2.87 1.09 5.59 63.94

Aulostomus chinensis Apex 0.91 2.48 1.12 4.82 68.77

Diodon holocanthus Carnivore 0.71 2.32 1.26 4.50 73.27

Forcipiger flavissimus Carnivore 0.93 2.08 0.76 4.04 77.31

Sargocentron wilhelmi Carnivore 1.29 1.80 0.48 3.50 80.81

Cantherhines rapanui Carnivore 0.73 1.49 0.72 2.90 83.71

Arothron meleagris Carnivore 0.65 1.33 0.75 2.59 86.30

Sargocentron hormion Carnivore 0.78 1.28 0.46 2.50 88.80

Lactoria diaphana Carnivore 0.53 1.26 0.78 2.45 91.25

Groups: Day & Night fish survey

Average dissimilarity = 67.67

Group day Group night

Species Av.Abund Av.Abund Av.Diss Diss/SD Contrib% Cum.%

Thalassoma lutescens Carnivore 2.95 0.00 5.52 6.25 8.16 8.16

Myripristis tiki Planktivore 0.12 2.69 4.94 2.80 7.29 15.45

Chrysiptera rapanui Planktivore 2.70 0.40 4.49 1.40 6.63 22.08

Acanthurus leucopareius Herbivore 3.36 1.15 4.44 1.40 6.56 28.65

Itycirrhitus wilhelmi Carnivore 1.86 3.37 3.18 1.45 4.69 33.34

Pseudolabrus fuentesi Carnivore 1.96 0.30 3.16 2.68 4.66 38.01

Anampses femininus Carnivore 1.55 0.00 2.70 1.24 3.99 42.00

Coris debueni Carnivore 1.35 0.00 2.46 1.62 3.64 45.64

Decapterus muroadsi Planktivore 1.38 0.00 2.40 0.72 3.55 49.18

Sargocentron wilhelmi Carnivore 0.18 1.29 2.31 1.01 3.41 52.59

Chaetodon litus Carnivore 2.36 2.50 2.14 1.40 3.16 55.75

Heteropriacanthus cruentatus Planktivore 1.29 0.38 1.97 1.61 2.92 58.67

Cantherhines rapanui Carnivore 0.75 0.73 1.82 1.24 2.69 61.36

Gymnothorax eurostus Carnivore 1.01 0.60 1.78 1.42 2.63 63.99

Forcipiger flavissimus Carnivore 1.40 0.93 1.76 1.41 2.60 66.59

Mulloidichthys vanicolensis Carnivore 0.96 0.00 1.72 1.41 2.54 69.13

Apogon kautamea Carnivore 0.00 0.97 1.71 0.69 2.53 71.67

Sargocentron hormion Carnivore 0.41 0.78 1.57 1.08 2.32 73.98

Thalassoma purpureum Carnivore 0.90 0.00 1.55 1.21 2.30 76.28

Pseudocaranx cheilio Apex 0.63 0.00 1.35 0.67 1.99 78.27

Aulostomus chinensis Apex 1.27 0.91 1.23 1.34 1.82 80.09

Chromis randalli Planktivore 0.18 0.60 1.22 0.94 1.80 81.89

Diodon holocanthus Carnivore 0.12 0.71 1.21 1.51 1.78 83.68

Lactoria diaphana Carnivore 0.23 0.53 1.11 1.33 1.64 85.31

Arothron meleagris Carnivore 0.48 0.65 1.10 1.14 1.62 86.93

Plectrypops lima Planktivore 0.00 0.53 1.00 1.20 1.47 88.41

Kyphosus sandwicensis Herbivore 0.53 0.12 0.91 1.18 1.35 89.75

Gymnothorax porphyreus Carnivore 0.30 0.30 0.90 0.60 1.33 91.08

The first axis of the principal coordinates analysis on the fish assemblage explained 45.2 %

of the total variation and separated diurnal surveys well in ordination space from nocturnal

surveys (Fig. 1.4). The species most responsible for this separation at day surveys were the

wrasses P. fuentesi and T. lutescens. The species which accounted for most of the separation

along Axis 1 of the PCO towards night surveys were the soldierfish Plectrypops lima and the

porcupinefish Diodon holocanthus. Relatively orthogonal to these species were the

damselfishes Chromis randalli and the hawkfish I. wilhelmi, more related to night surveys

(Fig. 1.4).

Figure 1.4. Plot of principal coordinates analyses (PCO) based on fish community structure using

density – with species vectors. Species and sites are indicated in black and grey characters,

respectively.

The principal coordinates analysis on the invertebrate assemblage also separated diurnal from

nocturnal surveys in ordination space, where the first axis explained 53.6 % of the total

variation (Fig. 1.5). Several species which appeared mostly during nocturnal surveys, such

as crustaceans, holothurians, some mollusks and echinoids were responsible for this

separation (Fig. 1.5).

Figure 1.5. Plot of Principal coordinates analyses (PCO) based on invertebrate density with species

vectors. Species and sites are indicated in black and grey characters, respectively.

The fish trophic structure also differed between day and night surveys (Pseudo-F = 3.901; P

= 0.015; Table 1.4). Herbivorous species were more abundant and contributed more biomass

during the day (t = 3.85, P = 0.012; t = 3.23, P = 0.023, respectively) (Fig. 1.6). However the

differences between day and night surveys were less evident in apex predators, carnivores

(secondary consumers) and planktivores, in both density (t = 1.14, P = 0.306; t = 0.09, P =

0.932; t = 1.30, P = 0.250, respectively) and biomass (t = 0.48, P = 0.634; t = 1.12, P = 0.312;

t = -0.87, P = 0.424, respectively) (Fig. 1.6).

Table 1.3. Results of the similarity percentage analysis (SIMPER) based on the density (fourth root

of densities) of invertebrate assemblages between day and night at Rapa Nui.

Group: Day surveys



Diadema savignyi 2.85 21.56 3.19 38.28 38.28

Echinostrephus aciculatus 2.06 14.41 3.35 25.58 63.86

Holothuria cinerascens 1.30 7.46 1.30 13.24 77.09

Coralliophila violacea 1.86 6.86 0.70 12.18 89.27

Calcinus pascuensis 0.91 3.65 0.78 6.48 95.75

Group: Night surveys



Breviturma dentata 3.84 12.39 4.78 20.28 20.28

Diadema savignyi 2.60 8.05 2.86 13.18 33.46

Calcinus pascuensis 1.97 6.28 7.81 10.29 43.75

Coralliophila violacea 1.87 5.24 3.26 8.58 52.33 Stichopus

monotuberculaatus 1.55 5.11 5.63 8.37 60.70

Echinostrephus aciculatus 2.04 4.26 1.05 6.98 67.68

Cinetorhynchus sp. 1.40 3.16 1.26 5.18 72.86

Naria englerti 1.11 2.96 1.36 4.84 77.70

Trapezia punctimanus 1.47 2.42 0.77 3.96 81.66

Polyplectana kefersteinii 0.90 2.30 1.36 3.77 85.43

Diadema sp. 1.43 2.18 0.70 3.57 89.01

Holothuria difficilis 1.17 1.80 0.79 2.94 91.95

Groups: Day & Night invertebrate survey

Average dissimilarity = 59.96

Group day Group night

Species Av.Abund Av.Abund Av.Diss Diss/SD Contrib% Cum.%

Breviturma dentata 0.70 3.84 8.31 2.26 13.86 13.86

Coralliophila violacea 1.86 1.87 3.80 1.71 6.35 20.21

Trapezia punctimanus 0.00 1.47 3.49 1.31 5.82 26.02

Cinetorhynchus sp. 0.00 1.40 3.46 1.86 5.77 31.80

Stichopus monotuberculatus 0.25 1.55 3.44 2.19 5.74 37.54

Diadema sp. 0.00 1.43 3.41 1.22 5.69 43.23

Holothuria cinerascens 1.30 1.22 3.28 1.47 5.47 48.70

Echinostrephus aciculatus 2.06 2.04 3.09 1.52 5.15 53.85

Calcinus pascuensis 0.91 1.97 2.91 1.52 4.85 58.71

Naria englerti 0.00 1.11 2.79 2.15 4.66 63.36

Holothuria difficilis 0.51 1.17 2.70 1.16 4.51 67.88

Ophidiaster easterensis 0.17 1.01 2.30 1.06 3.83 71.71

Polyplectana kefersteinii 0.00 0.90 2.21 2.13 3.69 75.39

Diadema savignyi 2.85 2.60 1.92 1.26 3.21 78.60

Conus miliaris 0.00 0.61 1.57 0.93 2.62 81.22

Holothuria nobilis 0.00 0.56 1.40 0.98 2.33 83.56

Ophiocoma longispina 0.00 0.50 1.19 0.68 1.99 85.54

Cinetorhynchus sp. 0.00 0.40 0.93 0.70 1.55 87.09

Holothuria sp. 0.00 0.36 0.85 0.69 1.42 88.52

Tripneustes gratilla 0.33 0.00 0.83 0.69 1.38 89.90

Calcinus imperialis 0.17 0.17 0.68 0.61 1.13 91.03

The principal coordinates analysis separated data on fish functional groups from day and

night surveys, with 57.5 % of the total variation was explained in the first axis (Fig. 1.7).

Herbivorous fish drove the separation of day surveys and planktivorous fish the separation

during night surveys. Data from HangaRoa SW collected during the night survey (see Fig

1.7) was relatively isolated (orthogonal to first axis) relative to other data, reflecting the

presence of apex predators and carnivores.

Figure 1.6. Diel changes in the trophic groups of fishes in terms of the average density and average

biomass. Apex = apex or top predator, Carnivores = invertivores. Error bars represent the standard

error.

Table 1.4. Results of permutational multivariate analyses of variances (PERMANOVA) testing

differences in the biomass of trophic groups of fish assemblage between day and night surveys at

Rapa Nui based on Bray Curtis similarity matrices performed on fourth root transformed data.

Trophic fish structure

Source df SS MS Pseudo-F P(perm)

Day/night 1 548.1 548.1 3.901 0.015

Res 10 1405.3 140.5

Total 11 1953.4

Density

Figure 1.7. Plot of Principal coordinates analyses (PCO) based on the biomass of trophic groups of

fish assemblage). Species and sites are indicated in black and grey characters, respectively.

2.5 Discussion

This study clearly shows an opposed activity pattern of fish and mobile invertebrate

communities in the shallow reefs of Easter Island. Fish were more active during the day, but

at this time invertebrates were less active, likely sheltering within the complex structure

provided by the coral reef. In contrast, invertebrate communities were more active during the

night, when fish were less abundant.

Diel variation in shallow water reef community dynamics

We have shown clear differences in the density of fish assemblages between day and night

surveys at Rapa Nui, where fish were more than twice as abundant during the day than at

night. A similar trend has been reported in others studies in the Mediterranean sea (Azzurro

et al., 2007), Western Australia (Harvey et al., 2012; Myers et al., 2016), South Atlantic

(Brewin et al., 2016), and Virgin Islands (Collette & Talbot, 1972). However, in our study,

the richness and biomass of nocturnal fishes were not significantly different from diurnal

surveys, because some diurnal species (i.e. mainly carnivores and herbivores) were replaced

by others that are strictly nocturnal (i.e. carnivores and planktivores) (Figs. 1.2 and 1.6),

specialized for detecting and capturing prey at the dark (Hobson, 1981).

Fish community structure changed notably among day and night surveys, where

predominantly diurnal species such as T. lutescens, P. fuentesi, A. femininus (carnivores), C.

rapanui (planktivore), A. leucopareius (herbivore), and nocturnal fishes as M. tiki

(planktivore) and I. wilhelmi (carnivore) contributed 42 % of the dissimilarity (Table 1.2).

M. tiki and I. wilhelmi contributed to the higher similarity among sites at nocturnal survey

(43.7 %), being the most common among the sites studied. The hawkfish I. wilhelmi has been

seen immobile during the day on Porites reefs and their stomach contents contained small

benthic crustaceans (DiSalvo, Randall, & Cea, 2007). This is similar to observations from

the Mediterranean rocky reefs, where common prey of nocturnal predators are small mobile

benthic invertebrates and planktivore fishes that feed on large zooplankton close to substrate

(Azzurro et al., 2007).

The invertebrate community was more than three times richer and more abundant at night

than in the day (Fig. 1.2b). Most invertebrates remain inactive during the day, secreted under

rocks, within the sand or coral cracks and then emerge at night to feed (Brewin et al., 2016).

A release of the predation pressure by fish at night has been used as an explanation of such

increase in invertebrate densities, as the activity of visually-feeding carnivorous fishes

decreases during night (Fig. 1.6) (Aguzzi et al., 2012; Azzurro et al., 2007; Tessmar-Raible

et al., 2011). However, some carnivore fishes are specialized for feeding in the dark,

including species of the families Apogonidae, Holocentridae, Pomadasyidae, Farangidae,

Clupeidae, Lutjanidae, Sciaenidae and Serranidae (Azzurro et al., 2007).

Different studies report that predators can exert strong selective pressure on their prey,

determining a variety of different biological characteristics including morphology, life

history and behaviors (Bosiger & McCormick, 2014 and references therein). Some studies

that report shifts in increased nocturnal activity in invertebrates are only based on single

species (MacArthur, Hyndes, Babcock, & Vanderklift, 2008; Oppenheim & Wahle, 2013;

Ory et al., 2014), assemblages of decapods (Aguzzi & Company, 2010; Aguzzi, Sbragaglia,

Tecchio, Navarro, & Company, 2015; Nickell & Sayer, 1998), shrimps (Bauer, 1985),

echinoderms (Nelson & Vance, 1979; Savy, 1987; Tuya, Martin, & Luque, 2004; Verling,

Crook, Barnes, & Harrison, 2003), mollusks (Rueda, Urra, & Salas, 2008), urchins and

holothurians (Azzurro et al., 2007). Reports of diel changes in the whole invertebrate

communities are less common, likely reflecting the technical difficulties associated with

nocturnal diving (Aguzzi et al., 2012). However, in a study conducted in Ascension island´s

by Brewin et al. (2016), a similar trend was reported, with several invertebrate species

appearing only during the nights. These authors pointed out that several invertebrate species

are simply hidden from view during the day but are present around the reef in refuges that

are sub-optimal for accessing food resources. These authors suggested that the trophic

ecology of reef species may be roughly partitioned between day and night and it may be a

common trend in several places.

Among the most important invertebrates at night, the brittle star B. dentata notably increased

their densities, emerging from their cryptic habitats (e.g. cracks provided mainly by Porites

corals), probably to feed on detritus deposited on corals and coral mucus (Brewin et al.,

2016). In addition, this species has been found in stomachs of diurnal carnivores (e.g. Coris

debueni, T. purpureum and Forcipiger flavissimus) and other nocturnal fishes (Cantherhines

spp. and Arothron meleagris) (DiSalvo et al., 2007), therefore it is likely an important prey

for diurnal and nocturnal predators in coral reef at Rapa Nui.

Other uncommon invertebrate species were observed emerging at night, such as the echinoid

Lissodiadema lorioli, the shrimp Cinetorhynchus sp., the crab T. punctimanus, two

unidentified nudibranchs and two holothurians (Polyplectana kefersteinii and S.

monotuberculatus). These holothurians are important components of the reef ecosystem,

emerging at night from their cryptic refuges to forage on the substrate (Brewin et al., 2016;

Hammond, 1982). In addition, is recognized that some holothurians can be strictly nocturnal,

as has been reported for Euapta lappa at Discovery Bay, Jamaica (Hammond, 1982), and

Ascension Island (Brewin et al., 2016). These holothurians have soft-bodies and slow-

movement, and are hence susceptible to predation attack. Their nocturnal emergence could

feasibly be hypothesized to be related to reducing predation risk from visual predators

(Brewin et al., 2016; Hammond, 1982).

Conversely, temporal niche partitioning has been put forward as an alternative mechanism to

predator avoidance, allowing reduced competition among similar taxa and permitting

coexistence (Bosiger & McCormick, 2014; Brewin et al., 2016; Tessmar-Raible et al., 2011).

Additionally, one lobster (Panulirus pascuensis) and two slipper lobsters (Parribacus

perlatus and Scyllarides roggeveeni) also appeared only at night but they were only present

outside of our quantitative transects. In the past, these three carnivore species were common

(DiSalvo et al., 1988), but were widely exploited during recent decades to supply demands

by tourists to Rapa Nui, reducing their densities in shallow and deeper waters (Gaymer et al.,

2013). The effect of the fishery removing these carnivore species on the community structure

has not been tested in Easter Island, but these trophic changes are probably generating strong

impacts on the ecosystem dynamics, as it has been observed elsewhere (Ling, Johnson,

Frusher, & Ridgway, 2009; Mann & Breen, 1972).

Fish trophic structure

Fish likely have greatest effects on the benthic community structure and dynamics

(Friedlander et al., 2013). In this study, clear differences were found in the fish trophic

structure between day and night, and as such, it is likely that the top down impacts should

differ accordingly. Other studies have suggested differences in fish predatory impact between

day and night is due to the replacement of some trophic groups by others (Collette & Talbot,

1972). Exceptionally, fish trophic structure at Hanga Roa SW during night was different to

the other sites, due to a single observation of the top predator conger Conger cinereus that

accounted for most of this difference due to its large biomass.

Despite the lower richness of herbivorous fishes in this study, this trophic group was the most

abundant, showed the greatest biomass, and was mainly associated with daytime surveys.

The surgeon fish A. leucopareius explained most of the density, followed by the pacific

rudderfish or chub Kyphosus sandwicensis. Also A. leucopareius contributed importantly in

the similarity of diurnal surveys among sites. These results are similar to the observations of

Friedlander et al. (2013) at Rapa Nui, where both species were the most important herbivores

in terms of density and biomass. The herbivore fishes from the Acanthuridae family, such as

A. leucopareius, graze on turf algae during the day (Easton, Gaymer, Friedlander, & Herlan,

2018). In contrast, K. sandwicensis is a browser, typically seen forming schools and feeding

on macroalgae such as Lobophora variegata and Sargasum sp. (Easton et al., 2018).

Diurnal and nocturnal planktivorous possess different functional roles: diurnal fishes

typically feed on small prey of oceanic origin while nocturnal fishes feed on large plankton

usually of coral reef origin (Marnane & Bellwood, 2002 and references therein). Among the

planktivorous fishes, the Rapanui damselfish C. rapanui was an important consumer in

diurnal surveys, a characteristic of planktivorous pomacentrids (Hobson, 1991). This species

showed important densities and biomass in previous diurnal surveys made at Rapa Nui

(Friedlander et al., 2013), and is usually seen in aggregations feeding near the substrate, from

tide pools to at least 60 m in depth on volcanic walls.

In contrast to C. rapanui, the soldierfish M. tiki was the most abundant planktivorous fish at

night, contributing 7.29 % of the dissimilarity among diurnal and nocturnal fish community.

This fish has been reported forming small aggregations hiding in caves during the day and

emerging at night to feed upon zooplankton (DiSalvo et al., 2007; Randall & Cea, 2011), a

common feature of holocentrid fishes (Gladfelter & Johnson, 1983). Previous surveys

conducted at Rapa Nui (DiSalvo et al., 1988; DiSalvo et al., 2007) suggested that nocturnal

planktivores of the families Holocentridae, Priacanthidae and Apogonidae were the most

important fishes around Rapa Nui. During the night, demersal zooplankton (e.g., amphipods,

isopods, decapod larvaes, polychaetes) regularly emerge from coral reefs, and are important

food sources for nocturnal planktivorous fishes (Jacoby & Greenwood, 1989), playing an

important role in coral reef trophodynamics (Carleton, 1993).

Invertivorous fishes such as the wrasses (Labridae family) T. lutescens, P. fuentesi, A.

femininus, C. debueni and Thalassoma purpureum were only recorded during daytime

surveys. This group of fishes forage close to the substrate on a diverse group of small hard-

bodied invertebrates (e.g. brachyuran crabs, hermit crabs, mollusks, sea urchins, and brittle

stars) (DiSalvo et al., 2007). Stomach content analyses conducted at Rapa Nui in wrasses

such as T. lutescens, P. fuentesi, A. femininus and C. debueni revealed mainly crustacean

fragments, ophiuroid spines and mollusc shell fragments among other invertebrate fragments.

The porcupinefish D. holocanthus was more abundant during night surveys but was present

in lower numbers during the day. This species mainly feeds on molluscs, hermit crabs (e.g.

Calcinus spp.), and also on xanthid crabs, sea stars (Ophidiaster easterensis and Leiaster

leachi) and polychaetes (DiSalvo et al., 2007) that have cryptic behavior (DiSalvo et al.,

1988). Similarly, the hawkfish, I. wilhelmi, that was mostly found during nocturnal surveys,

frequently feeds on small crustaceans (DiSalvo et al., 2007).

Fish apex predators at Rapa Nui were found in relatively low density in the present study, as

observed by Friedlander et al. (2013) and Easton et al. (2018). This can be explained by high

fishing pressure around the island associated with increased tourism in the last three decades

(Gaymer et al., 2013). In contrast, apex predators represent almost half of the fish biomass at

Salas & Gómez Island (Easton et al., 2018; Friedlander et al., 2013), where little fishing

occurs and the ecosystem is protected by a marine park. With apex predators being scarcer

at Rapa Nui than at Salas & Gómez, lower trophic level carnivorous and planktivorous fish

have a greater biomass at the former. In turn, this likely results in increased predation risk

for small invertebrates at Rapa Nui, which could in turn help explain the shift in invertebrate

activity at night. Additionally, nocturnal surveys with remotely operated vehicles (ROV) in

adjacent sediment close to coral reefs, have reported aggregations of the carnivore fish

Aulostomus chinensis, considered an apex predator in Rapa Nui (M. Gorny, Comm. Pers).

This could represent a diel movement of fishes from coral reefs to adjacent sediments, that

should be studied to understand dynamics of energy exchange (i.e. food sources) and habitat

use of this species for reproduction, feeding, refuge and resting (reviewed in Hammerschlag

et al., 2017).

Future directions

Due to technical difficulties associated with night diving, most benthic surveys of coral reefs

both on Rapa Nui and across the world have been conducted during the day, providing only

a partial view of the ecology of shallow coral reef communities. Night surveys allow access

to cryptic fauna that live in refuges during the day. Comparing day and night surveys has

allowed us to have a more complete understanding of shallow benthic community structures

and the likely interspecific interactions that shape them. This is the first attempt to evaluate

the daily dynamic of community change at Rapa Nui. Future studies should extend these

initial results to include seasonal variability of the benthic community structure, the effects

of moon phases on the activity patterns of benthic and pelagic communities and potential

changes in the ability of predators to detect prey (Hammerschlag et al., 2017). Nocturnal

evaluation of benthic communities at Salas y Gomez would also provide useful insights,

given the density of apex predators in this pristine marine ecosystem, and their potential

effects on daily dynamics.

Due to the increased population and touristic activity at Rapa Nui during recent decades, and

the increase the fishing pressure for some marine resources, and increased coastal light-

pollution, it may have important impacts on nocturnal taxa both in the intertidal and shallow

subtidal communities, as it has been reported in the Bahamas (Szekeres et al., 2017).

Evaluating these impacts should be an important challenge at Rapa Nui for future research

and management strategies of marine resources.

This study provides important scientific information for the management planning and

implementation of the recently created Rapa Nui Multiple-Uses Marine Coastal Protected

Area (MUMCPA) (Paredes, Flores, Figueroa, Gaymer, & Aburto, 2019), as it shows realistic

scenarios to understand benthic communities functioning and helps proposing effective

management strategies. This type of approach could be very helpful for MPA planning

worldwide.

2.6 Acknowledgments

Our thanks to Ricardo Hito, Enrique Hey and Matias Atamu for coordinating our field trip at the

Island, and also to ORCA Diving Centre for providing key supplies for the development of this study.

We also appreciate the hospitality from Tiare Hereveri family that provide us a nice accommodation

site. We also thank the funding by the Chilean Millennium Initiative, ESMOI, and from FONDECYT

through grant 3170392 (IHT). GZ-H was supported by CONICYT-PCHA/Doctorado Nacional/2015-

21151249. This manuscript is dedicated to the memory of the brothers Henry and Michel Garcia who

were the scuba diver pioneers at Rapa Nui. Michel provided very constructive advices to decide the

dive sites for this study.

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Chapter 3

Diel changes in the structure and trophic functioning of mobile benthic

invertebrate assemblages on coral reefs at Rapa Nui (Easter Island)

Germán Zapata-Hernández1,2,3*, Iván Hinojosa2,4, Javier Sellanes1,2, Rodrigo S. Rios5,6

and Yves Letourneur7

1Departamento de Biología Marina, Facultad de Ciencias del Mar, Universidad Católica del Norte (UCN),

Coquimbo, Chile. 2Millennium Nucleus for Ecology and Sustainable Management of Oceanic Islands (ESMOI),

Coquimbo, Chile. 3Programa de Doctorado en Biología y Ecología Aplicada (BEA), Facultad de Ciencias del

Mar, Universidad Católica del Norte (UCN), Coquimbo, Chile. 4Departamento de Ecología, Facultad de

Ciencias y Centro de Investigación en Biodiversidad y Ambientes Sustentables (CIBAS), Universidad Católica

de la Santísima Concepción, Concepción, Chile. 5Departamento de Biologia, Universidad de la Serena (ULS),

Coquimbo, Chile. 6Instituto de Investigación Multidisciplinario en Ciencia y Tecnología, Universidad de La

Serena, La Serena, Chile. 7University of New Caledonia, Institut ISEA and LabEx “Corail”, BP R4, 98851

Nouméa cedex, New Caledonia.

3.1 Abstract

Coral reef ecosystems are structurally complex habitats that provide diverse refugia for

mobile invertebrate taxa; some invertebrates also display cryptic behaviors and nocturnal

activity to minimize predation risk. Hence, standard daytime surveys likely underestimate

the abundance of benthic communities. In this study, we analyzed the diel changes in the

structure (composition, density and biomass) and functionality (trophic groups and isotopic

diversity indices) of mobile benthic invertebrates (MBI) on coral reefs from Rapa Nui (Easter

Island), central South Pacific. Diurnal and nocturnal surveys (March 2016), revealed that

echinoderms were the most important mobile benthic invertebrate group in terms of density,

biomass and trophic role. Significant diel changes were detected in community structure of

MBI and trophic groups: the sea urchins Diadema savignyi and Echinostrephus aciculatus

and the gastropod Coraliophilla violacea dominated the diurnal assemblage, while sea

cucumbers Holothuria cinerascens and Stichopus monotuberculatus and the brittle star

Breviturma dentata dominated the nocturnal assemblage. In trophic terms, diurnal

assemblages were characterized mainly by herbivorous and carnivorous taxa, and the

nocturnal assemblages by detritivorous taxa. Although nocturnal assemblages had higher

density and biomass compared to diurnal assemblages, the isotopic uniqueness index (IUni)

indicates that nocturnal MBI were trophically more redundant than diurnal counterpart,

therefore an increase of nocturnal biodiversity could not necessarily imply an increase in the

trophic diversity. Finally, endemic taxa represented around a quarter of species composition

(26%), but had low density and biomass during both periods studied, suggesting a modest

influence on the current trophic functioning on coral reefs at Rapa Nui and likely making its

more vulnerable to extinction.

Keywords: Cryptic fauna, nocturnal behavior, trophic structure, stable isotopes analyses,

predation risk.

3.2 Introduction

Coral reefs are one of the most productive and diverse ecosystems found on the earth (Reaka-

Kudla 1997). Most coral reef research to-date has focused on visually dominant taxa such as

corals, algae and reef fishes (Stella et al. 2011). However, a large amount of benthic fauna

also lives in association with coral reefs – these taxa are largely understudied reflecting their

cryptic behavior (the so-called “cryptofauna”), but can dominate biodiversity and make

considerable contributions to the structure and function of reef communities (Stella et al.

2010; Glynn 2011; Enochs and Manzello 2012a). Cryptofauna remain difficult to study for

several reasons, including their individual small sizes, their use of structurally complex

habitats (e.g., cracks and holes) during the day that are difficult to access, and the nocturnal

behavior of several taxa (Ameziane 2006; Enochs 2010). These organisms also establish

crucial trophic links for energy transfer through food webs (Enochs and Manzello 2012a) and

play a critical role in overall functioning of coral reef ecosystems (Glynn and Enochs 2011),

capturing suspended and dissolved organic matter, feeding on corals, grazing on benthic

algae, preying on or being preyed upon by other organisms (e.g., epibenthic fauna, nekton

and reef fishes) (Enochs et al. 2011; Enochs and Manzello 2012b; Briand et al. 2016).

Notably, some species that depend trophically on corals and live hidden within the benthic

coral matrix will diminish in density when corals are disturbed (Stella et al. 2011). Therefore,

the loss of coral-associated fauna in response to natural and anthropogenic stressors could

disrupt the functioning of coral reefs, due to loss of key functions for the ecosystem such as

decomposition, bioturbation, nutrient recycling, protection and availability of specialized

habitats (Miller 2015). This can have negative impacts on coral reef food webs, with cascade

effects through many trophic levels even reaching apex predators (Birkeland 2015).

On coral reefs, mobile benthic invertebrate assemblages (MBI) typically include polychaetes,

mollusks, decapods and echinoderms (Cortés et al. 2017). Most species belonging to these

groups constitute potential or preferential prey for many other species on the coral reef

system (Glynn and Enochs, 2011; Stella et al. 2011). However, predation-risk can alter prey

activity patterns, and prey-species tend to be most active when predators are inactive, poorly

efficient or at low densities (Dee et al. 2012). In this sense, important diel changes in fish

assemblages have been recorded in tropical reef environments, where diurnal assemblages

are typically dominated by carnivorous, zooplanktivorous and herbivorous, in contrast to the

night, where planktivorous fishes tend to be more conspicuous (e.g., Hobson 1972; Galzin,

1987; Azzurro et al. 2007; Brewin et al. 2016; Holzman et al. 2007). Therefore, some benthic

invertebrate taxa could display nocturnal behavior in order to minimize temporal overlap

with visual predators (Nelson and Vance 1979), thus reducing their detectability and potential

consumption (Ory et al. 2014).

By displaying different diel activity patterns, perception of real population size, composition,

community structure and functional roles of some taxa could be strongly biased depending

on sampling times (Aguzzi et al. 2012). Unfortunately, existing information on diel activity

patterns remains scarce for most coral reef taxa and, when available, is mainly focused on

fish (e.g., Hobson 1965, 1972; Galzin 1987; Marmane and Bellwood 2002; Holzman et al.

2007; Myers et al. 2016) and zooplankton assemblages (e.g., Loose and Dawidowicz 1994;

Hays et al. 2001; Yahel et al. 2005). Therefore, evaluate of diel activity patterns of MBI

would greatly improve our knowledge of coral reef community structure and functioning,

allowing us to generate a more representative understanding of biodiversity (Boyko 2003).

Additionally, coral reef structure and function is closely associated with different energy

sources and nutrient pathways that play different roles in associated food webs (Briand et al.

2015, 2016; McMahon et al. 2016). Stable isotopes analysis (SIA) has emerged as an

important tool by which to trace energy and matter fluxes (Middelburg 2013). It is also

possible to explore various ecological attributes of the trophic structure of food webs, using

community isotopic metrics based in species distribution on isotopic δ-space (Newsome et

al. 2007; Layman et al. 2007, 2011; Jackson et al. 2011) and more recently isotopic functional

indices that quantify different functional facets from food webs based on biomass-weighted

stable isotope data (Coucherousset and Villéger 2015; Rigolet et al. 2015), integrating

information of community structure, species interactions and energy transference within

communities (Comte et al. 2016). Due to their potential utility for the study of coral reef food

webs (Yamamuro et al. 1995; Bierwagen et al. 2018), in recent decades SIA has been

increasingly used for various taxonomic groups, such as scleractinian corals (Aharon 1991;

Nahon et al. 2013; Tremblay et al. 2015), clams and calcareous algae (Aharon 1991), urchins

(Cabanillas–Terán et al. 2016), fishes (e.g., Wyatt et al. 2012; Letourneur et al. 2013; Briand

et al. 2016; McMahon et al. 2016) and invertebrate assemblages (e.g., Page et al. 2013; Davis

et al. 2015; Kolasinski et al. 2016).

The Rapa Nui Marine Protected Area (MPA) was created in June 2008, and cover an area of

579.368 km2 in the south east Pacific around Rapa Nui island (Diario oficial, 2018),

protecting shallow to deep-water environments (including shallower and mesophotic coral

reefs, as well as nearby seamounts and hydrothermal vents). Despite this achievement in

marine conservation, ecological studies in the different environments around Rapa Nui have,

until only recently (Fernández et al. 2014) been very limited, and deeper environments (> 80

m depth) are only just beginning to be studied (e.g., Friedlander et al. 2013; Easton et al.

2016, 2018; Hoeksema et al. 2019). For example, a pioneer study conducted by DiSalvo et

al. (1988) at Rapa Nui qualitatively described the shallow benthic community (between 15-

60 m depth). More recently, the works of Friedlander et al. (2013) and Wieters et al. (2014)

have described some community and functional features of larger animals of diurnal reef

communities (focused mainly on fish assemblages), while Gusmao et al. (2018) studied

ecological aspects of shallow (~10 m depth) soft bottom infauna (meio- and macrofauna).

Due to its level of isolation, geologic history and oceanographic features, Rapa Nui is a global

hotspot for endemism (Roberts et al. 2002; Boyko 2003), with levels of endemism of 34 %

for mollusks, 33 % for sponges, 12 % for bryozoans and 22 % for coastal fishes (Fernández

et al. 2014). Despite this, biodiversity is impoverished compared to other Pacific islands (e.g.,

Hawaii and Galapagos Island; Boyko, 2003; Fernandez et al. 2014; Cortes et al. 2017). It

should be noted however that a limited sampling effort and a lack of taxonomic studies may

have resulted in an underestimation of current endemism levels, especially in certain

taxonomic groups (e.g., annelida, peracarida, ascidacea; Boyko 2003). Endemic taxa are

commonly assumed to have high probabilities of extinction due to their small geographic

range and low abundances (Gaston, 1998). However, the abundance of endemic benthic

invertebrate taxa in Rapa Nui has only been estimated during daylight surveys, with only two

endemic species evaluated (Friedlander et al. 2013). Moreover, their abundance in nocturnal

assemblages is still unknown and their trophic role needs to be evaluated.

Here, we present the first study to quantitatively analyze the diel structure of MBI on coral

reefs around Rapa Nui, combining measures of species composition, density, and biomass

with stable isotope measurements of benthic species to characterize key structural and

ecological features of Rapa Nui coral reef communities. As such, we examine the utility of

diel surveys of marine fauna to provide more comprehensive information about benthic

communities, cryptic fauna and potentially threatened endemic species. This information is

potentially key for our understanding of the ecological role of invertebrates and energy

contribution of diverse species in coral reefs (Bierwagen et al. 2018) and for biodiversity

management, monitoring of marine communities and development of ecosystem modeling

of the new MPA surrounding Rapa Nui, potentially threatened by exacerbated touristic

activity, overfishing, terrestrial runoff and wastewater pollution. Due to a potential relaxation

of predation risk at night due to a decrease of carnivorous fishes and a greater dominance of

planktivorous fishes on temperate and coral reefs (Galzin, 1987; Azzurro et al. 2007; Brewin

et al. 2016; Holzman et al. 2007), we hypothesize that the nocturnal MBI assemblage on

Rapa Nui coral reefs would shift their taxonomic composition and increase their density and

biomass compared to diurnal assemblages, which translates to different trophic functionality

in both periods. Therefore, the aims of this study are: i) to quantify diel changes in the

structure of MBI (composition, density and biomass) from coral reefs at Rapa Nui, ii) to

determine how diel differences in the MBI structure could impact functional facets of coral

reef communities, and iii) to evaluate the contribution of endemic taxa to the MBI structure

and trophic functioning of coral reefs in this remote island.

3.3 Materials and methods

Study sites

Rapa Nui (Easter Island; Lat. -27.12°, Long. -109.37°) in the south central Pacific is one of

the most isolated inhabited places of the world. It is located ~3800 km west of continental

Chile and over 2200 km from Pitcairn Islands, the nearest inhabited place (Boyko 2003). The

island has a triangular shape and a surface area of 163.6 km2 (Arana 2014). It is located close

to the center of the South Pacific Sub tropical Gyre, which drives most of the important

circulation features around the island (Andrade et al. 2014). Shallow reef communities are

mainly dominated by two scleractinian corals with a wide distribution range, i.e., Porites

lobata and Pocillopora verrucosa, which together currently contribute to ~80 % of benthic

cover (Wieters et al. 2014). Fish fauna is comprised of ~220 species and considered

depauperate in comparison with other Pacific sites which harbor between ~1000-~2100

species, depending on the region (Allen 2008).

Fig. 2.1. Location of sampling sites at Rapa Nui (Easter Island). HRS: Hanga Roa South, HRSW:

Hanga Roa South-West, HR: Manavai, MT: Motu Tautara, AK1: Anakena T1, AK2: Anakena T2.

Stars represent sample sites and the color palette depth ranges on the map. Maps created with Ocean

Data View software (Schlitzer 2018).

Structure of invertebrate assemblages

To assess the MBI structure of coral reefs at Rapa Nui, sampling was conducted in March

2016 at six sites via SCUBA diving. Four sites were selected based sea weather conditions,

accessibility and presence of coral reefs, and positioned at the western coast (HRS: Hanga

Roa Sth, HRSW: Hanga Roa SW, HR: Manavai and MT: Motu Tautara) and two sites at the

north coast (AK1: Anakena T1 and AK2: Anakena T2) (Fig. 2.1). Reef Life Survey (RLS)

methods (Edgar and Stuart-Smith 2014) were used to estimate the density of MBI (> 2 cm;

e.g., gastropods, crustaceans, echinoderms). Because there were no significant differences in

the community structure of coral reef between 10 and 20 m (Friedlander et al. 2013), two 50

m long x 1 m wide transects (blocks) were conducted parallel to the shore (10 or 20 m depth)

at each site during the day (between 1100-1500 h) and then replicated at the same GPS point

(identified from the boat), depth and direction at night (between 2100-2400 h). MBI were

surveyed along the same transect lines and density was estimated by counting all individuals

within 1 m on either side of the line. Then, total density was summed for both blocks per

transect and expressed as individuals 100 m-2. To assess energy fluxes and partitioning of

organic matter within MBI, samples of invertebrates were manually collected by divers,

stored in plastic vials or bags and once in the laboratory facility at Hanga Roa, Rapa Nui (no

later than 2 h after collection) wet weight was estimated with a digital balance and wet

biomass for each species per transect expressed in g 100 m-2. Sampled fauna was assigned to

putative trophic functional categories based on classification from Enochs & Glynn (2017):

herbivores, suspension feeders, detritivores (include detritus-feeders and deposit-feeders)

and carnivores (include predators and corallivores). Assignments were based on literature

data on the trophic ecology of the species, genus or closest relative (e.g., Stella et al. 2011),

making allowances that some species can incidentally ingest a wide spectrum of food items

(e.g., algae, small invertebrates, corals, etc.); thus, implying that trophic categories should be

considered to be broad. Additionally, geographic distribution range of species (i.e., endemic,

Indo-Pacific and unknown) were included for each taxon for determinate its contribution to

the assemblage structure and functional groups.

Sample collection and preparation

In total, 84 samples of mobile benthic invertebrates were collected and kept frozen at -20 °C

until processing for SIA. To characterize the isotopic functional diversity (IFD) of MBI, for

every sample ~10 mg of wet tissue was dissected under a stereomicroscope, washed with

Milli-Q water, placed in pre-combusted vials and dried in an oven (40 °C) for 48 h, then

stored in a desiccator until analyzed. Between each processed sample, dissection materials

were rinsed with methanol. Dried tissue samples were ground into a fine powder with an

agate mortar and small amounts (~ 0.5 mg) were placed in pre-weighed tin capsules and

stored in a desiccator until SIA. Care was taken to use carbonate-free samples (e.g., cheliped

and abdominal muscles of decapods, tube feet of sea stars, foot of gastropods) (Zapata-

Hernández et al. 2016). However, samples of species containing calcium carbonate (i.e.,

holothurians) were split, and a subsample was acidified (solution of PtCl2 in 1 N HCl) to

remove inorganic carbonates. Nitrogen values were obtained from untreated subsamples.

The isotopic composition was analyzed at the School of Biological Sciences, Washington

State University, using a Eurovector elemental analyzer (EA3000, Milan, Italy), coupled to

an Isoprime isotope ratio mass spectrometer (IRMS, Micromass, Manchester, UK). The daily

reference material was calibrated against the NIST (National Institute of Standards and

Technology) standard reference material Bovine Liver SRM 1577. Daily reference material

was analyzed between analysis of unknowns and the values from the references in the sample

run were used to calculate the values for the unknowns. Stable isotope ratios are reported in

the δ notation as the deviation relative to international standards (Vienna Pee Dee Belemnite

for carbon and air N2 for nitrogen), so δ13C or 𝛿15𝑁 = [(𝑅 𝑠𝑎𝑚𝑝𝑙𝑒/ 𝑅 𝑠𝑡𝑎𝑛𝑑𝑎𝑟𝑑) − 1],

where R is 13C/12C or 15N/14N, respectively. The precision of the analysis based on the

standard deviation of ten replicate reference material analyses was ± 0.1 ‰ for δ15N and δ13C.

Since lipids are 13C-depleted relative to protein (DeNiro and Epstein 1977), lipid-

normalization was applied using C:N ratios (molar) as a proxy. This correction was applied

to all animal samples with C:N values > 3.5 (>5 % lipid content) according to the following

equation (Post et al. 2007):

𝛿13𝐶′ = 𝛿13𝐶 + (0.99) × (𝐶: 𝑁) − 3.32

Voucher specimens of collected taxa were preserved in 95% ethanol and catalogued at Sala

de Colecciones Biologicas Universidad Católica del Norte (SCBUCN).

Statistical analyses

To test for significant differences in species composition between day and night assemblages

(as a fixed factor), a permutational multivariate analyses of variance (PERMANOVA) was

run for all taxa present in each transect using Euclidean distances as a dissimilarity measure

and the “strata” option (i.e., the randomizations are restricted only within each site and not

across sites) to use sites as strata given that day and night data at each site are not fully

independent. We used matrices of wet biomass (g 100 m-2), density (ind. 100 m-²) and

putative trophic group data. In all cases, non-metric multidimensional scaling analyses

(NMDS) based on the Bray-Curtis dissimilarity metrics with square root transformation were

performed to visualize multivariate patterns of gradient variation across day and night. Since

results based on biomass integrate aspects related to metabolism and organic matter

transference (Rigolet et al. 2015), we have chosen to present results based on species and

putative trophic group gradients. Significant differences in density and biomass of individual

taxa present both day and night, and on the total density and biomass of MBI were tested

with Welch´s t-test (parametric) or Mann-Whitney U-test (non-parametric), based on

previous analysis of normal distribution of data (Shapiro-Wilk test).

Additionally, a series of metrics that quantify the isotopic functional diversity (IFD) in δ-

space (Cucherousset and Villéger 2015) were calculated for each block by transect (i.e.,

diurnal and nocturnal) to determinate the effects of MBI diel changes in functional structure.

Isotopic Divergence (IDiv) is calculated using the sum of deviances and absolute biomass-

weighted deviances of distances between all species and the gravity center of convex hull

vertices (Villéger et al. 2008; Cucherousset and Villéger 2015). Isotopic Dispersion (IDis) is

calculated using the biomass-deviation to the average position of species in the δ-space

divided by the maximal distance to the gravity center filled by the assemblage (Mouillot et

al. 2013; Cucherousset and Villéger 2015). Isotopic Evenness (IEve) quantifies the regularity

of species distribution and biomass along the shortest minimum spanning tree linking all

species in δ-space (Villéger et al. 2008; Mouillot et al. 2013; Cucherousset and Villéger

2015). Isotopic Uniqueness (IUni) is quantified using the biomass-weighted average of the

nearest neighbor distance of each species divided by the maximum distance between two

nearest neighbors (Cucherousset and Villéger 2015). These metrics are mathematically

independent from the species number used in estimations and account for species biomass,

hence integrating organic matter transfer and distribution through the food web structure

(Cucherousset and Villéger 2015; Rigolet et al. 2015).

All indices were calculated based on density, biomass and stable isotope composition (δ13C

and δ15N) of species from each transect. When stable isotope data were not available for

specific taxa at a particular site (e.g., West side: Hanga Roa or North side: Anakena; see Fig

1), data from other sites were used. Additionally, before IFD calculations were done, the

isotopic axes were scaled into a standardized multidimensional space to have the same range

(e.g., 0 to 1; Cucherousset and Villéger 2015). Subsequently, to test for the fixed-effects of

time (day and night) on IFD indices, taking random effects (1|block/transect) into account,

generalized linear mixed models (GLMMs) with a Gamma error distribution (link function

“log”) were fit using maximum likelihood (Laplace approximation). Because GLMMs

combine both fixed-effects parameters and random effects in a linear predictor via maximum

likelihood (Bates et al. 2015), they are useful for ecological studies that include proportional

data replicated across sites (Bolker et al. 2008). The effect of time in the models was assessed

using likelihood ratio tests (LRT), which compare the difference in likelihood between a

model with the factor and a model in which the factor is removed. This difference has a Chi-

square distribution, thus a p-value can be assigned. All analyses were performed in the R

statistical environment (R Core Team 2018), using the “adonis()” function for the

PERMANOVA and “metaMDS()” function for the NMDS analyses from the “vegan”

package (Oksanen 2018). For IFD indices calculations, we used the “IDiversity()” function

(Cucherousset and Villéger 2015) and the “glmer()” function was used to run GLMMs using

the “lme4” package (Bates et al. 2015). Where errors are reported, we use mean ± SD

throughout the text.

3.4 Results

MBI encountered during the transects included only three phyla (i.e., Mollusca, Arthropoda

and Echinodermata), totaling 27 taxa, including 13 echinoderms (i.e., five holothurians, four

echinoids, two asteroids and two ophiuroids), six gastropods, one cephalopod and seven

crustaceans (Table 2.1). Of them, only one taxon was exclusively recorded during the day

(i.e., Tripneustes gratilla), 16 taxa exclusively during the night and 10 taxa both during day

and night (Table 2.1). Furthermore, seven of these species were endemic to Rapa Nui (i.e.,

26 %), 15 with a distribution around the Indo-Pacific region and four with unknown

distribution ranges due to their unspecified taxonomic status (Table 2.1).

Total density and biomass of MBI were significantly higher (M-W test, P < 0.05, Table 2.1)

during nocturnal surveys (density: mean ± SD = 550 ± 138 ind. 100 m-2; biomass: 12,154 ±

8,670 g 100 m-2) in comparison to diurnal surveys (225 ± 194 ind. 100 m-2; 5,851 ± 3,115 g

100 m-2). In diurnal assemblages, both the sea urchin Diadema savignyi and the gastropod

Coralliophila violacea had the highest densities (87.8 ± 64.0 ind. 100 m-2 and 85.2 ± 148.8,

respectively) followed by the urchin Echinostrephus aciculatus (27.7 ± 26.8 ind. 100 m-2;

Table 2.2). In the nocturnal assemblage, the brittle star Breviturma dentata had the highest

densities (253.5 ± 172.9 ind. 100 m-2), followed by D. savignyi (80.8 ± 48.7 ind. 100 m-2), E.

aciculatus (63.2 ± 88.8 ind. 100 m-2) and Holothuria cinerascens (42.3 ± 95.5 ind. 100 m-2;

Table 2.1).

D. savignyi displayed the highest biomass in diurnal assemblages (2,970 ± 2,163 g 100 m-2),

followed by C. violacea (1,149 ± 2,007 g 100 m-2) and H. cinerascens (919 ± 1,631 g 100 m-

2; Table 2.1). In nocturnal assemblages, H. cinerascens had the highest biomass (3,957 ±

8,923 g 100 m-2), followed by Stichopus monotuberculatus (2,223 ± 1,125 g 100 m-2), D.

savignyi (2,170 ± 1,694 g 100 m-2) and B. dentata (1,268 ± 865 g 100 m-2; Table 2.1).

However, considering the density and biomass of species present both day and night, only B.

dentata showed significant differences (Welch´s t-test, P < 0.05, Table 2.1). For diurnal and

nocturnal assemblages, the proportion of endemic species was 1.8 % and 5.7 % of total

density and 0.2 % and 4.7 % of total biomass, respectively (Table 2.1).

Based on density, diurnal MBI assemblages largely consisted of carnivores and herbivores

(both 39.9 %), followed by suspension feeders (16.7 %) and detritivores (4.2 %) (Table 2.1).

In marked contrast, nocturnal assemblages were characterized mainly by detritivores and

suspension feeders (36.9 % and 33.6 %, respectively), followed by herbivores (22.6 %) and

carnivores (6.9 %) (Table 2.1). Additionally, endemic taxa made a minor contribution to the

proportion of carnivore densities and biomass in diurnal assemblages (4.5 % and 0.9 %,

respectively). In contrast, during nocturnal surveys, endemic taxa made a low contribution to

the density and biomass of herbivores (3.2 % and 0.5 %, respectively) and more important

proportion in carnivores (36.4 % and 66.1 %, respectively).

Table 2.1. Summary of taxonomic composition, densities (ind. 100 m-2) and wet biomass (g 100 m-

2) of MBIA (diurnal and nocturnal) evaluated for six coral reefs in Rapa Nui (abundance and biomass

were averaged from six transects each one). The species codes, standard deviation (SD), samples number (n) are included. Significant differences for species densities and biomass using *Welch´s

test (p<0.05) and **M-W U test (p<0.05).

The PERMANOVA analysis showed differences for species biomass between day and night

assemblages (F = 0.995, P = 0.031), with NMDS plots showed a high dissimilarity of species

among adjacent sites in diurnal surveys and a less dissimilarity in nocturnal assemblages

(Fig. 2.2a). Moreover, a clear species gradient across both assemblages, mainly due to D.

savignyi, E. aciculatus and C. violacea closely associated with diurnal surveys and B.

dentata, S. monotuberculatus, Conus miliaris and P. perlatus associated to nocturnal surveys

(Fig. 2.2a). In addition, the biomass for putative trophic groups between diurnal and nocturnal

assemblages indicated significant differences (PERMANOVA, F = 1.630, P = 0.031; Fig.

Abundance Biomass

Day Night Day Night Endemism

Taxa Code Mean SD Mean SD p -value Mean SD Mean SD p -value

Mollusca

Gastropoda

Conus miliaris Cmi 1.3 2.0 0.8 1.2 Indo-Pacific

Coralliophila violacea Cvi 85.2 148.8 20.2 23.1 0.30 1148.6 2006.8 271.7 311.0 0.41 Indo-Pacific

Naria englerti Nen 2.7 1.5 12.3 6.7 Endemic

Pascula citrica Pci 0.3 0.8 0.2 0.4 Endemic

Opistobranch

Opistobrach sp. 1 Opi1 0.2 0.4 0.1 0.1 Unknown

Opistobrach sp. 2 Opi2 0.2 0.4 0.1 0.1 Unknown

Cephalopoda

Callistoctopus rapanui Cra 0.2 0.4 - - Endemic

Arthropoda

Decapoda

Calcinus imperialis Cim 0.2 0.4 0.2 0.4 0.1 0.3 0.3 0.4 Indo-Pacific

Calcinus pascuensis Cpa 3.8 6.6 20.7 11.0 0.07 2.5 4.3 11.5 9.0 0.07 Endemic

Cinetorhynchus sp. Cin 9.8 9.9 11.8 12.0 Unknown

Parribacus perlatus Ppe 0.5 0.5 21.5 23.6 Endemic

Panulirus pascuensis Ppa 0.2 0.4 - - South Pacific

Trapezia punctimanus Tpu 18.3 26.6 19.5 23.3 South Pacific

Majidae sp. Maj 0.2 0.4 - - Unknown

Echinodermata

Echinoidea

Diadema savignyi Dsa 87.8 64.0 80.8 48.7 0.84 2970.5 2163.4 2170.2 1694.4 0.84 Indo-Pacific

Echinostrephus aciculatus Eac 27.7 26.8 63.2 88.8 0.32 54.7 52.9 124.7 175.1 0.33 Indo-Pacific

Lissodiadema lorioli Llo 0.2 0.4 0.7 1.6 Pacific

Tripneustes gratilla Tgr 0.5 0.8 101.7 170.1 Indo-Pacific

Asteroidea

Astrostole paschae Apa 0.5 1.2 43.3 106.1 Endemic

Ophidiaster easterensis Oea 0.2 0.4 10.0 22.1 7.6 18.6 456.2 1006.4 Endemic

Holothuroidea

Polyplectana kefersteinii Pke 1.0 0.9 10.0 8.9 Indo-Pacific

Holothuria cinerascens Hci 9.8 17.5 42.3 95.5 0.25 919.2 1631.3 3957.0 8923.1 0.25 Indo-Pacific

Holothuria difficilis Hdi 1.8 3.0 17.2 37.7 7.0 11.3 65.0 142.7 Indo-Pacific

Stichopus monotuberculatus Smo 0.8 2.0 6.3 3.2 292.5 716.5 2223.0 1124.7 Indo-Pacific

Holothuria nobilis Hno 0.8 1.0 907.2 1070.2 Indo-Pacific

Ophiuroidea

Breviturma dentata Bde 6.8 10.9 253.5 172.9 0.02* 34.2 54.4 1267.5 864.6 0.02* Indo-Pacific

Breviturma longispina Blo 1.8 3.3 5.5 9.8 Indo-Pacific

Ʃ Total 1350 3297 33279 72922

Mean±DS 225 194 550 138 0.03** 5851 3115 12154 8670 0.04**

Endemism (%) 1.8 5.7 0.2 4.7

2.2b), with herbivorous taxa more associated with diurnal surveys and detritivorous taxa

more associated with nocturnal surveys. Moreover, a similar pattern of dissimilarity between

adjacent sites was displayed for during diurnal and nocturnal assemblages (Fig. 2.2b).

Regarding stable isotopes values among MBI, lowest δ13C values were recorded for Naria

englerti (mean ± SD = ˗17.0 ± 2.5 ‰, n = 7), Lissodiadema lorioli (˗16.6 ‰, n = 1), Trapezia

punctimanus (˗16.6 ‰, n = 1), Cinetorhynchus sp. (˗16.0 ‰, n = 1) and the highest for T.

gratilla (˗12.0 ± 1.6 ‰, n = 6), B. dentata (mean = ˗12.3 ‰, n = 2) and E. aciculatus (˗12.6

± 1.9 ‰, n = 4; Table 2.2). The lowest δ15N values were for T. gratilla (4.8 ± 1.6 ‰, n = 6),

E. aciculatus (4.9 ± 1.6 ‰, n = 4) and D. savignyi (5.5 ± 0.5 ‰, n = 7), while the highest

were for Cinetorhynchus sp. (10.1 ‰, n = 1), Conus miliaris (10.5 ± 1.2 ‰, n = 3), T.

puntimanus (10.5 ‰, n = 1) and Parribacus perlatus (11.1 ± 0.9, n = 3; Table 2.2).

Fig. 2.2. Non-metric multidimensional scaling (NMDS) based on A) biomass matrix of diurnal and

nocturnal mobile benthic invertebrate assemblages (MBI; stress=0.107) and B) biomass of putative

trophic groups (stress=0.045). Black dots represent position of transects in the multidimensional

space and ellipses the standard deviation (SD) from the centroid that represent the mean value for all

transects (day or night). Black and red ellipses represent diurnal and nocturnal assemblages,

respectively. Species codes and sampling sites are summarized in Table 2.1 and Fig. 2.1, respectively.

Table 2.2. Summary of stable isotopes composition (δ13C and δ15N) and putative trophic groups of

MBIA (diurnal and nocturnal) evaluated for six coral reefs in Rapa Nui. The lipid-corrected δ13C

values (δ13C´), standard deviations (SD), samples number (n) are included.

Overall, the effect of time (day and night) on the isotopic diversity indices did not show

significant differences for IDiv, IDis and IEve (GLMMs, P > 0.05, Table 2.3). Therefore,

both diurnal and nocturnal assemblages had higher IDiv values, which indicate that the

biomass of taxa are similarly distributed toward the borders of convex hull in the δ-space

(Fig. 2.3a, b). The lower IDis values indicate low variation in biomass of the taxa in relation

to the gravity center represented for all taxa in δ-space (Fig. 2.3c, d). The IEve index values

indicate that in both cases biomass values tend to be packaged in small regions of the δ-space

(Fig. 2.3e, f). The IUni index, however, showed significant differences (GLMMs, P < 0.001,

Table 2.3) between diurnal and nocturnal assemblages, indicating that biomass of diurnal

Stable isotopes

Trophic Group

Taxa δ13C SD δ13C´ SD δ15N SD n

Mollusca

Gastropoda

Conus miliaris -14.9 0.7 -13.9 0.6 10.5 1.2 3 Carnivore

Coralliophila violacea -14.6 0.4 -13.9 0.3 7.4 1.0 7 Carnivore

Naria englerti -18.0 2.7 -17.0 2.5 8.4 0.4 7 Herbivore

Pascula citrica -15.5 0.6 -14.7 0.9 8.9 0.8 4 Carnivore

Arthropoda

Decapoda

Calcinus imperialis -14.1 - -13.5 - 7.6 - 1 Carnivore

Calcinus pascuensis -17.0 1.4 -15.1 1.8 7.2 2.1 10 Carnivore

Cinetorhynchus sp. -16.7 - -16.0 - 10.1 - 1 Carnivore

Parribacus perlatus -14.7 0.7 -14.1 0.8 11.1 0.9 3 Carnivore

Trapezia punctimanus -17.4 - -16.6 - 10.5 - 1 Carnivore

Echinodermata

Echinoidea

Diadema savignyi -17.7 2.6 -15.3 3.1 5.5 0.5 7 Herbivore

Echinostrephus aciculatus -16.8 1.8 -12.6 1.9 4.9 1.6 4 Suspension feeder

Lissodiadema lorioli -19.5 - -16.6 - 8.1 - 1 Herbivore

Tripneustes gratilla -13.3 1.3 -12.0 1.6 4.8 1.6 6 Herbivore

Asteroidea

Astrostole paschae -14.6 2.1 -13.9 1.8 9.1 3.1 3 Carnivore

Ophidiaster easterensis -15.0 1.4 -13.9 1.2 8.5 0.2 4 Carnivore

Holothuroidea

Polyplectana kefersteinii -15.0 0.4 -14.2 0.8 9.1 1.1 3 Detritivore

Holothuria cinerascens -14.7 0.9 -13.5 0.6 5.8 1.8 6 Suspension feeder

Holothuria difficilis -15.3 0.4 -13.7 1.1 5.9 1.5 6 Detritivore

Stichopus monotuberculatus -15.3 0.8 -14.4 0.8 7.9 0.9 3 Detritivore

Holothuria nobilis -13.6 - -13.1 - 6.9 - 2 Detritivore

Ophiuroidea

Breviturma dentata -16.2 - -12.3 - 8.8 - 2 Detritivore

taxa are isolated from each other in δ-space, in contrast to nocturnal assemblages where

species biomass is isotopically similar (Fig. 2.3g, h).

Table 2.3. Summary of isotopic functional diversity indices and results of Generalized Linear Mixed

Models (GLMMs). The standard deviation (SD), degrees of freedom (df), log-likelihoods function

(logLik), Akaike´s Informative Criterion (AIC), Chi-square (Chi-sq) and p-values are showed.

Fig. 2.3. Summary of isotopic functional diversity (IFD) indices on scaled isotopic space (δ13C and

δ15N) for diurnal (upper panels) and nocturnal (lower panels) mobile benthic invertebrate assemblages

(MBI). Isotopic Divergence (a, b), Isotopic Dispersion (c, d), Isotopic Evenness (e, f) and Isotopic

Uniqueness (g, h). Standard deviations (SD) are included in the figures and size of each point (species)

represent the magnitude of mean value of their relative biomass (%). For taxa with higher relative

biomass (> 10%) codes are included in Table 2.1.

Index GLMMs

Mean SD Mean SD d.f. logLik AIC Chi-sq p

IDiv 0.72 0.3 0.7 0.21 5 -5.7 21.4 0.02 0.896

IDis 0.38 0.25 0.35 0.18 5 7.63 -5.25 0.55 0.459

IEve 0.5 0.31 0.32 0.23 5 -0.42 10.84 2.41 0.121

IUni 0.7 0.1 0.46 0.19 5 7.22 -4.44 9.99 < 0.001

Day Night

3.5 Discussion

The first qualitative study of shallow benthic communities at Rapa Nui described zonation

patterns and composition of conspicuous taxa on coral reefs, and described the presence of

Protozoa and invertebrate taxa such as Porifera, Cnidaria, Polychaeta, Crustacea, Mollusca

and Echinodermata in detail (DiSalvo et al. 1988). Thirty years later, our study is the first to

quantify diel differences in the structure of MBI, as well as the functional importance of Indo-

Pacific and endemic invertebrate taxa on coral reefs at Rapa Nui. MBI showed marked diel

differences in terms of composition, density, biomass and trophic function, where nocturnal

taxa tend to be more abundant and diverse than their diurnal counterparts. However, high

variability among adjacent sites during day in contrast to night could reflect different relative

composition of live and death coral substrates (e.g., P. lobata and Pocillopora spp.) that

provide structural complexity to coral reefs (Graham and Nash, 2013), and hence an excellent

refuge for cryptic taxa against predators (Stella et al. 2010; Enochs and Manzello, 2012).

Moreover, fishing pressure on predatory fishes or lobsters can increase the abundance of

habitat-modifying macroinvertebrates (e.g., sea urchins) with important cascade effects on

the community structure of coral reefs (Edgar et al. 2011).

Currently, few studies exist in other parts of the world describing these structural differences

in MBI assemblages. In spite of such paucity in information related to MBI, it is well accepted

that several shallow benthic taxa show marked diel changes in their activity patterns, e.g. the

nocturnal behavior reported for shrimps (Ory et al. 2014), lobsters (MacArthur et al. 2008),

gastropods and cephalopods (Rueda et al. 2008), urchins (Dee et al. 2012), and holothurians

(Hammond 1982). In Rapa Nui in the 1980s, it was recognized that the nocturnal reef fauna

mainly consisted of echinoderms (DiSalvo et al. 1988) and our study confirms this finding,

although taxa such as D. savignyi and E. aciculatus had similar densities and biomass in

diurnal and nocturnal surveys. A strictly nocturnal behavior has been observed for the sea

urchin Diadema antillarum in the South Atlantic (Tuya et al. 2004; Brewing et al. 2016) and

for Diadema setosum in the Red Sea (Lawrence and Hughes-Games, 1972), where D.

antillarum has a homing behavior and moves short distances (range 1 to 5.1 m) from their

holes (Tuya et al. 2004). Diadema savignyi does not show such extreme cryptic behavior,

since some individuals can be seen moving around during the day, but there is an evident

contrast with nocturnal surveys where individuals are clearly more active. Birkeland (1988)

mentions that both in areas where their predators (e.g., fishes, lobster and gastropods) are

scarce, or where the echinoids are very abundant, urchins will forage freely during the day.

Only the ophiuroid B. dentata showed a significant diel increase in density and biomass,

being dominant during the night, but also showed high variability among sites (256 ± 173

ind. 100 m-2). Brittle stars are important components of the cryptofauna on coral reefs

ecosystems (Aronson 1998), living in coral crevices and displaying nocturnal activity

(Birkeland 1988). In some cases, species can have higher densities (e.g., Ophiocoma

erinaceus with 150 to 15,000 ind. m-2; Chartock 1983), hence contributing significantly to

the overall community biomass (Granja-Fernández et al. 2014). Likewise, holothurians are

important nocturnal consumers that emerge from their cryptic and/or sandy habitats to feed

during the night (Hammond 1982). For both ophiuroids and holothurians, cryptic and

nocturnal behavior is usually considered a response to reduced predation risk (Hammond

1982; Birkeland 1988). This could also be the case for coral reef communities at Rapa Nui,

where planktivorous fishes dominate the nocturnal fish assemblage and carnivorous fishes

(invertivorous) were most abundant during the day (Hinojosa et al. chapter 2). Therefore, diel

changes in predation risk may influence the structure of MBI, although further research is

required to better understand predator-prey interactions and to evaluate their effects on

specific invertebrate prey.

In functional terms, the biomass of MBI has noticeable diel changes, moving from a diurnal

assemblage predominantly composed of by herbivores and carnivores to a nocturnal

assemblage largely composed of detritivorous (Fig. 2.2b). Herbivorous species (mainly D.

savignyi) were an important component of diurnal assemblages, while detritivorous species

(S. monotruberculatus, H. nobilis and B. dentata) dominated nocturnal assemblages (Fig.

2.2a). Both diurnal and nocturnal assemblages play important trophic roles in Rapa Nui reef

ecosystem dynamics, associated with the transfer of energy and nutrients from macroalgae,

corals and detritus to upper trophic levels. In this sense, D. savignyi has an important

functional role as an herbivorous feeding on algae, but also can consumes corals,

invertebrates and detritus (Muthiga and McClanahan 2007). Lower δ15N values of this

species and other echinoid herbivores (e.g., T. gratilla) on Rapa Nui reefs suggest that it

mainly incorporates organic matter from basal sources (e.g., algae) and potentially transfers

it to upper trophic levels, such as some reef fishes, i.e., Coris debueni, Bodianus vulpinus and

Thalassoma lutescens, known to be occasional echinoid predators (DiSalvo et al. 2007).

Nocturnal detritivore holothurians likely emerge from their refuges to consume

microorganisms, small metazoans and detritus deposited on and between rocks and corals

(Glynn and Enochs 2011). Similarly, the brittle star B. dentata emerges from cryptic habitats

within P. lobata reefs to feed at night (G. Zapata-Hernández, pers. obs.). This species is

trophically versatile, feeding on detritus, suspended particles, algae or carrion (Chartock

1983; Glynn and Enochs 2011). Its δ15N values are similar to other endemic carnivore sea

stars (e.g., O. easterensis and Astrostole paschae), likely reflecting a diet based on small

metazoans (Glynn and Enochs 2011), demersal plankton (Kramer et al. 2013) or highly

recycled organic matter. Ophiuroids can also be occasional prey for other macroinvertebrates

(e.g., decapods and asteroids; Drolet et al. 2004) and reef fishes (Randall 1967; Glynn and

Enochs 2011), and ophiuroid fragments are occasionally found in fish stomachs of both

diurnal predators such as Forcipiger flavissimus, Coris debueni, Pseudolabrus fuentesiand

nocturnal as Arothron meleagris (DiSalvo et al. 2007). Therefore, these abundant nocturnal

taxa could be indispensable for the organic matter uptake, nutrient cycling and energy

transfer to consumers at higher trophic levels (Birkeland 1989; Uthicke 2001), and therefore

are notable facets of the trophic functioning of coral reef systems (Granja-Fernández et al.

2014). Only two putative suspension feeder taxa (H. cinerascens and E. aciculatus) were

represented in the MBI and were the most important members of the nocturnal assemblage.

The echinoid E. aciculatus is known for its sedentary behavior and is usually observed in

boreholes catching drift algae (Birkeland 1988). During nocturnal surveys, however, some

mobile individuals (~ 4 cm test diameter) were observed out of their refugia. This rarely

documented behavior was previously observed by Kobayashi and Tokiota (1976), who found

individuals browsing on algae-covered rocks. Therefore, juveniles individuals (< ~ 4 cm) can

also leave their holes to feed on benthic algae, and not exclusively on drifting algae as is

sometimes suggested (e.g., Asgaard and Bromley 2008), likely as response to a reduced

predation risk from other invertebrates and reef fishes predators.

Despite nocturnal assemblages displaying higher species composition, density and biomass

in comparison to diurnal assemblages, only the IUni showed significant low values for

nocturnal assemblages. This suggests a higher degree of trophic redundancy among their

dominant taxa (Cucherousset and Villéger 2015; Rigolet et al. 2015). The higher density of

nocturnal detritivore can explain this pattern, where other trophic groups were less

represented in terms of density and biomass. This pattern is consistent with communities

where certain species are removed (e.g., predators; Cucherousset and Villéger 2015) and

where the remaining species tend to share their functional roles more closely with other

species (Mouillot et al. 2013).

In this study, endemic taxa represented ca. 25 % of the community assessed and were slightly

more prevalent during nocturnal surveys. However, endemic taxa contributed less by density

and biomass while Indo-Pacific taxa were the main determinants of changes in structure and

isotopic diversity metrics. Hence, our results suggest that endemic taxa likely play a minor

role in trophic transfer by MBI in Rapa Nui coral reefs. Comparative results reported from

extensive assessments in the Galapagos Islands also indicated a low contribution by endemic

invertebrate taxa and an elevated presence of Indo-Pacific fauna (Edgar et al. 2004).

However, it is important to note that at Rapa Nui, endemic nocturnal carnivores such as the

spiny lobster Panulirus pascuensis, slipper lobsters (e.g., P. perlatus) and cephalopods

(Octopus rapanui), were scarcely seen during visual surveys. This potentially reflect intense

fishing pressure that has led to marked population decreases in recent decades (Friedlander

et al. 2013; Zylich et al. 2014) or alternatively due to avoidance behavior to diver lights

during nocturnal surveys (McArthur et al. 2008 and references therein). Palinurid lobsters

are important predators on sea urchin and small invertebrates on coral reefs (Sonnenholzner

et al. 2009) and exercise strong top-down control on benthic communities (Butler and

Kintzing 2016). Hence, their limited presence in nocturnal assemblages could have important

effects on the current structure and distribution of biomass through the food web (Costello

2015).

Our study demonstrates that the structure and trophic functioning of MBI change in the short

term (24-h cycles). Hence, the roles of diurnal and nocturnal assemblages are of great

importance for coral reef functioning, exploiting diverse and, to some degree, complementary

trophic resources (e.g., macroalgae, corals and detritus) allowing a more efficient energy

transference to upper trophic levels. However, this study represent a “snapshot” of diel cycles

in a short period, hence still is necessary determinate diel changes in a wider period and the

influence of other cycles (e.g., lunar, seasonal and inter-annual) on the activity patterns of

mobile invertebrates. Therefore, future assessments of the effects of the new MPA at Rapa

Nui over marine biodiversity should consider the implementation of diurnal and nocturnal

long-term monitoring (e.g., monthly, seasonal and inter-annual) of whole benthic

communities, in order to acknowledge community dynamics and the response to potential

environmental changes.

Moreover, studies examining the effect of different substrate type providing refuge to

nocturnal cryptic fauna could contribute to improved understanding of spatial changes in the

density and biomass within coral reefs. In addition, more knowledge regarding predator-prey

interactions is necessary to determine the effects of fishing pressure (and potential predation-

risk relaxation) on activity patterns of select taxa that display higher densities (e.g., echinoids,

ophiuroids). In this sense, the extension of similar studies to Salas y Gomez islet could

provide an important baseline for contrast the diel patterns of MBI in a scenario without

fishing pressure and dominated by diurnal and nocturnal predators (Friedlander et al. 2013).

Finally, more information is needed on the basic biology and ecology of endemic taxa (e.g.,

lobsters and cephalopods), which are currently overexploited, given their potential ecological

importance as predators and influence on the functioning of coral reefs at Rapa Nui.

Furthermore, their current reduced density and constrained distribution could increase their

extinction risk when faced with environmental changes (Gaston 1998), and conservation

efforts must be directed to this group of species.

3.6 Acknowledgments

Our thanks to Ricardo Hito, Victor Icka and Enrique Hey from Rapa Nui for their collaboration in

field activities. To Tortuga and Orca dive centers from Rapa Nui for providing support with scuba

diving equipment. To Amelia Fowles for their collaboration during field work. To Jorge Avilés and

Camila Henriquez from Sala de Colecciones Biológicas UCN (SCBUCN) for their help with the

curation of voucher specimens and Kaitlin McConnell for manuscript revision and comments.

Funding: GZ-H was funded by CONICYT-PCHA/Doctorado Nacional/2015-21151249.

FONDECYT 1181153, 1180694 and the Chilean Millennium Initiative ESMOI provided funding.

Compliance with ethical standards

Conflict of interest: On behalf of both authors, the corresponding author states that there is no

conflict of interest.

Ethical statement: Sampling was performed under permission Res. Ext N°41/2016 from

SERNAPESCA (Chile) to Universidad Católica del Norte and approved by the scientific ethics

committee from Universidad Catolica del Norte, F.M. N°70/2017.

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Chapter 4

Tracing trophic pathways through the marine ecosystem of Rapa Nui

(Easter Island): A stable isotope approach

Germán Zapata-Hernández*1,2, Javier Sellanes1, Yves Letourneur3, Chris Harrod4,5,6, Naiti

Morales1,2, Paula Plaza1,2,7, Erika Meerhof8, Beatriz Yannicelli8, Sergio A. Carrasco1, Ivan

Hinojosa1,9 & Carlos Gaymer1,7

1Millennium Nucleus for Ecology and Sustainable Management of Oceanic Islands (ESMOI), Coquimbo, Chile,

Departamento de Biología Marina, Facultad de Ciencias del Mar, Universidad Católica del Norte, Coquimbo,

Chile. 2Programa de Doctorado en Biología y Ecología Aplicada (BEA), Coquimbo, Chile. 3University of New

Caledonia, Institut ISEA and LabEx “Corail”, BP R4, 98851 Nouméa cedex, New Caledonia. 4Instituto de

Ciencias Naturales Alexander von Humboldt, Universidad de Antofagasta, Antofagasta, Chile. 5Universidad

de Antofagasta Stable Isotope Facility (UASIF), Instituto Antofagasta, Universidad de Antofagasta, Chile.

6Millenium Nucleus of Invasive Salmonids (INVASAL), Concepción, Chile. 7Centro de Estudios Avanzados en

Zonas Áridas (CEAZA), Coquimbo, Chile. 8UNDECIMAR, Facultad de Ciencias, Universidad de la República,

Uruguay. 9Departamento de Ecología, Facultad de Ciencias y Centro de Investigación en Biodiversidad y

Ambientes Sustentables (CIBAS), Universidad Católica de la Santísima Concepción, Concepción, Chile.

4.1 Abstract

The trophic structure of food webs provides important insight on the biodiversity, trophic

relationships, organic matter (OM) pathways, and ecosystem functioning.

Using stable isotopes analysis (δ13C and δ15N) of primary producers and consumers from

different trophic levels and functional feeding groups, we examined the trophic structure and

main organic matter pathways supporting the food webs of the Rapa Nui marine ecosystem.

The trophic position of consumers and isotopic niche metrics were estimated for different

marine assemblages (i.e., mesozooplankton, emergent zooplankton, reef invertebrates, reef

fishes, pelagic fishes and seabirds). Furthermore, the relative importance of different primary

producers (i.e., zooxanthellate corals, macroalgae and phytoplankton) was assessed for

heterotrophic consumers using Bayesian mixing models (MixSiar).

Results show a clear pattern of 13C and 15N enrichment from small-sized invertebrates (i.e.,

pelagic and benthic) to reef and pelagic fishes, and seabirds. Most invertebrates (i.e.,

mesozooplankton, emergent zooplankton, macrobenthos, and reef invertebrates) were

classified as primary consumers, reef fishes as secondary consumers and pelagic predators

and seabirds as tertiary consumers.

Isotopic niche metrics indicate a low trophic diversity for pelagic assemblages

(mesozooplankton and pelagic fishes), in contrast to reef fauna (invertebrates and fishes),

whose higher trophic diversity suggests the exploitation of a wider range of trophic resources.

Overlapping of standard ellipses areas between reef invertebrates and reef fishes indicates

that both assemblages could be sharing trophic resources.

Mixing models indicate that coral-derived OM of zooxanthellate scleractinian corals was the

most important trophic source for the different assemblages (e.g., macrobenthos, reef

invertebrates and fishes) of the reef ecosystem in Rapa Nui. In contrast, phytoplankton-

derived organic matter was more important for mesozooplankton and pelagic fishes, but was

scarcely reflected in stable isotopes signatures of benthic consumers.

Keywords: Bayesian mixing models, coral reefs, cryptic fauna, energy transference organic,

food web, matter fluxes, subtropical south Pacific, trophic structure.

4.2 Introduction

Coral reef ecosystems have high primary production (PP) rates in comparison with other

marine ecosystems, which is usually considered a paradox since most coral reefs thrive in

oligotrophic and ultraoligotrophic environments (Polovina, 1984). Since the early works of

Odum & Odum (1955), coral reef ecosystems are considered autonomous in relation to their

PP, where benthic algae (including zooxanthellae coral symbionts) support a high proportion

of this productivity, while phytoplankton inputs could be marginal (Jhonson, Klumpp, Field,

& Bradbury, 1995). Moreover, zooxanthellae-derived production can explain up to 50–70 %

of PP of many coral reefs (Douglas, 2009), which combined with coralline crustose algae

(CCA), provide the bulk of energy fueling food webs in pristine coral reefs (Wild et al.,

2004). Conversely, phytoplankton production driven by upwelling is increasingly recognized

as an important source of energy and nutrients across a range of coral reef environments (e.g.,

Andrews & Gentien, 1982; Gove et al., 2016; Wyatt et al., 2013). Nevertheless, the relative

importance between benthic and pelagic sources could change spatial and temporally (within

and between reefs) due to changes in structure of primary producers (e.g., corals, macroalgae,

cyanobacteria and seagrass; Johnson et al., 1995) and environmental change (e.g., upwelling,

eddies; Stuhldreier et al., 2015). Therefore, food web models differ between coral reef

systems, and such information is still not available for most reefs, including those in the

oligotrophic Eastern tropical Pacific (Enochs & Glynn, 2017).

Food web structure is a central issue in ecology (Glibert, Middelburg, McClelland, & Vander

Zanden, 2019), providing information on species interactions, diversity, structure and

ecosystem functioning (Dunne, Williams, & Martinez, 2002). Stable isotopes analysis (SIA)

is an important tool allowing the assessment of the trophic structure of food webs (Layman

et al., 2011), being a robust method to trace the flow of energy and matter through the

ecosystems (Middelburg, 2013), integrating animal consumption patterns over a range of

different time scales (e.g., from days to years; Nielsen, Clare, Hayden, Brett, & Kratina,

2017; Thomas & Crowther, 2015). Typically carbon stable isotope ratios (13C/12C) are used

for tracing organic matter (OM) fluxes through food webs (Michener & Kaufman, 2008),

while nitrogen stable isotope ratios (15N/14N) are used to estimate consumer trophic position

(Post, 2002). However, both isotopes provide useful information that can be used in studies

on animal migration, resource partitioning, host-parasite interactions and ecophysiological

processes (reviewed by Boecklen, Yarnes, Cook, & James 2011). Recent advances in the

implementation of Bayesian modeling for incorporating uncertainty in estimations, has

allowed a series of tools to be developed in order to convert stable isotope data into robust

derived metrics that allow the reconstruction of animal diets (Parnell, Inger, Bearhop, &

Jackson, 2010; Stock & Semmens, 2016), measures of isotopic niche of populations and

communities (Jackson, Parnell, Inger, & Bearhop, 2011), the estimation of trophic position

(Quezada-Romegialli et al., 2018), and the evaluation of entire food webs (Kayoda, Osada,

& Takimoto, 2012).

Contrary to the typical global trend of phase-shifts from coral- to macroalge-dominated

systems (Fung, Seymour, & Jhonson, 2011), available evidence suggests that since the early

1980s, the subtidal marine ecosystem of Rapa Nui (Easter Island) has experienced an

important shift from a macroalgae-dominated system (mainly Sargassum) to a coral-

dominated system (Hubbard & Garcia, 2003). Currently, extensive coral reef habitats on

Rapa Nui are dominated by two species of zooxanthellate scleractinian corals (Porites lobata

and Pocillopora verrucosa; Glynn et al., 2007; Wieters, Meldrano, & Perez–Matus, 2014).

Both species provide between 40 % and 80 % of benthic cover at shallow depths (0 to 30 m

depth) in the western and northeastern coasts (Glynn et al., 2017), but also dominate the

upper mesophotic zone from 40 to 65 m depth (benthic cover 95%; Easton et al., 2019).

Macroalgae cover tends to be low around the island (Glynn et al., 2007), even though

macroalgal species richness is relatively high (143 taxa; Santelices & Abbott, 1987), and

rhodophytes are particularly well represented (57 % of total species) (Fernández, Pappalardo,

Rodriguez-Ruiz, & Castilla, 2014). However, the brown algae Lobophora variegata is the

most abundant species between 10-20 m depth (7.3 to 12%), followed by CCA (6.8 to 4.2%)

and turf algae (3.3 to 4.3%) (Friedlander et al., 2013). Conversely, pelagic PP in Rapa Nui is

typically low, with surface chlorophyll values (Chl–a) <0.1 mg m–3, reflecting oligotrophic

environmental conditions derived from the South Pacific Subtropical Gyre (SPSG), where

Chl–a values are extremely low (<0.001 mg m–3) (Andrade, Hormazabal, & Correa-Ramirez,

2014).

As recorded for other islands located in oligotrophic marine environments, the presence of

Rapa Nui promotes increases in local phytoplankton biomass (Andrade et al., 2014). This

reflects the Island Mass Effect (IME), where interactions between island topography, winds

and currents can cause an increase of macro- and micronutrients into the photic layer,

stimulating biological productivity in surface waters (Doty & Ogury, 1956). Estimates from

coral reefs from western and central Pacific islands indicate that phytoplankton biomass

could increase by more than 85% in comparison to nearby oceanic areas (Gove et al., 2016),

with positive implications for secondary production, and the provision of ecosystem services

for human populations such as local fisheries (Tweddle, Gybbins, & Scott, 2018).

In this context, information on the trophic ecology of marine species inhabiting the Rapa Nui

marine ecosystem (RNME) is extremely limited, with only two gastropod species being

investigated in detail (e.g., Conus miliaris pascuensis and Monetaria caputdraconis; Khon,

1978; Osorio, Jara, Ramirez, 1993, respectively). Other studies conducted to date have only

provided qualitative information on feeding behavior for some invertebrates (e.g.,

holothurians; Massin, 1996) and reef fishes (DiSalvo, Randall, & Cea, 1988), with only one

study providing semi-quantitative information from stomach contents analysis of reef fishes

(DiSalvo, Randall, & Cea, 2007). Recently, new quantitative analyses performed in pelagic

species such as the amberstripe scad Decapterus muroadsi, the flying fish Cheilopogon

rapanouiensis, and the yellowfin tuna Thunnus albacares, have determined the presence of

microplastic ingestion and transference through pelagic consumers (Chagnon et al., 2018;

Ory, Sobral, Ferreira, & Thiel, 2017). Nevertheless, there is little information on the wider

coastal food web, for instance the relative trophic position of consumers (required to build

ecosystem models), the overall trophic structure of the system, or the main energetic

pathways (benthic and pelagic) supporting biodiversity (and human populations) in the

RNME. Therefore, quantifying the relative importance of primary producers in Rapa Nui

coral reefs could improve our understanding on main OM pathways used by different

assemblages in this remote and ultraoligotrophic ecosystem, as well as how this energy could

be transferred to upper trophic levels.

Due to the higher cover of zooxanthellate scleractinian corals around RNME, and their

potential importance for benthic and pelagic assemblages, it is expected that coral-derived

primary production will dominate OM supply to invertebrates and fish consumers from coral

reefs, generating a marked contrast with pelagic consumers, which are expected to assimilate

pelagic-derived OM. Through stable isotope analysis the aims of this study are to: i)

determine the relative importance of different primary production modes (phytoplankton,

macroalgae and zooxanthellae corals) in the supply of organic matter to different marine

assemblages from Rapa Nui Marine Ecosystem, ii) estimate the trophic position of

heterotrophic consumers, and iii) evaluate trophic diversity measures from different animal

assemblages.

4.3 Methods

Sample collections

A range of different techniques were used to collect samples from the diverse assemblages

forming the RNME food web. The dominant macroalgae, corals and reef invertebrates

(sessile and mobile) were mainly collected by SCUBA diving, during both day and night

(Table 3.1). Soft-bottom invertebrates (hereafter macrobenthos) were also collected through

SCUBA diving by inserting PVC cores (13 mm diameter), down to 10 cm in the sediment at

10, 20, 30 and 40 m depth. Emergent zooplankton (sensu Kramer, Bellwood, & Bellwood,

2013) associated with coral reefs (i.e., mainly early life stages of benthic reef fauna) were

sampled by deploying two light traps between 15-20 m depth and moored at 1–2 m from the

reef bottom; Table 3.1). In all cases, traps were employed for one night (i.e., light attracting

effectively from approximately 21:00 to 09:00 h; see Carrasco, Vandecasteele, Rivadeneira,

Fernández, & Pérez-Matus, 2017). Zooplankton samples were collected in the coastal zone

around Rapa Nui using a 300 μm mesh Bongo net (i.e., Omohi and Apolo fishing ground;

Table 3.1). Reef and pelagic fishes were collected around the island through spearfishing,

fishing lines or directly from the local fish market. Seabird feathers were collected from

breeding individuals nesting close to the island on the “Motu Nui” islet (Table 3.1). Samples

included the seven conspecific petrels belonging to the Pterodroma genus and from the

Christmas shearwater Puffinus nativitatis. As a proxy for phytoplankton, particulate organic

matter (POM) samples were collected from three sites close to the island (<1 nm from the

coast) between 0-50 m depth (Table 3.2) and from the “Apolo” fishing ground (~8 nm)

between 0-100 m depth (Table 3.2) using a Niskin bottle (1.8 L). Approximately, 2-3 L of

water were pre-sieved through a 150 μm mesh to remove large-sized zooplankton and large

detrital particles, and then filtered through pre-combusted (500 °C for 4 h) Whatman GF/F

filters (0.7 μm nominal pore size). All samples (i.e., macroalgae, animal tissues, feathers,

filters, etc.) were frozen at –20 °C until further processing in the laboratory.

Table 3.1. Summary of sites and sampling gear used during scientific campaigns (2014-2018) to characterize the different assemblages included in

this study.

Assemblages Sampling period Sampling gear Depth range Sites

Macroalgae March 2016 Scuba diving 10-30 m Hanga Roa, Anakena, Motu Tautara, Laperouse

POM Nov 2014/March 2016 Niskin bottles 10-100 m Hanga Roa, Anakena, Apolo

Shallow corals March 2016 Scuba diving 10-30 m Hanga Roa, Anakena, Motu Tautara

Mesophotic corals March 2016 Trawl 80 m off Hanga Piko

Mesozooplankton Sept 2015/March 2016 Bongo net 20-100 m Omohi, Apolo, SE Rano Raraku

Emergent zooplankton August 2018 Nocturnal light-traps 10 m Hanga o Teo, Poike

Reef invertebrates March 2016 Day-night Scuba diving 10-30 m Hanga Roa, Anakena, Motu Tautara

Macrobenthos August 2018 PVC core/scuba diving 10-40 m Hanga Roa, Hanga o Teo

Reef fishes 2016-2017 Speargun/fishing lines 0-30 m Motu Nui, Hanga Roa, Anakena, Motu Tautara

Pelagic fishes 2016-2017 Fishing lines 0-100 m Apolo, Omohi, Mataveri

Seabirds January/ July 2015 Manually 0 m Motu Nui islet

Sample preparation

For benthic fauna, macroalgae and fishes, ~10 mg of wet tissue (in order to obtain ~1 mg dry

mass) was dissected, washed with Milli-Q water, placed in pre-combusted vials and dried in

an oven (60 °C) for 48 h, and stored in a desiccator until analysis. When necessary, dried

tissue samples were grounded into a fine powder with an agate mortar and small amounts

(~0.5 mg) were placed in pre-weighed tin capsules and stored in a desiccator until SIA. In all

cases, samples were selected to be as free of potential inorganic C contamination as possible

(e.g., dorsal muscle of fishes, cheliped and abdominal muscles of decapods, tube feet of sea-

stars, among others).

Samples of species containing calcium carbonate (i.e., crustaceans and echinoderms) were

split, and a subsample was acidified (solution of PtCl2 in 1 N HCl) to remove any inorganic

carbonates. Nitrogen stable isotope values were obtained from untreated subsamples. Coral

samples were processed with a buccal irrigator under pressure (Waterpik®), obtaining a

solution with organic coral pieces (e.g., soft tissues and zooxanthellaes) and then filtered

through pre-combusted (500 °C for 4 h) Whatman GF/F filters (0.45 μm nominal pore size).

In the case of seabird feathers, a 2:1 chloroform: methanol solvent rinse was used to remove

surface oils and associated contaminants (Hobson et al., 2014). When possible, voucher

specimens were preserved in 95 % ethanol and deposited at Sala de Colecciones Biológicas

Universidad Católica del Norte (SCBUCN) for further taxonomic corroboration and genetic

analyses. Such specimens are also suitable for future isotopic analyses (Pauli et al., 2017).

Stable isotopes analyses

Analyses of carbon (δ13C) and nitrogen (δ15N) stable isotope ratios were conducted at the

School of Biological Sciences, Washington State University, using a Eurovector elemental

analyzer, coupled to a Micromass Isoprime isotope ratio mass spectrometer. Stable isotope

ratios were reported in the δ notation as the deviation relative to international standards

(Vienna Pee Dee Belemnite for δ13C and atmospheric N2 for δ15N), so δ13C or δ15N = [ (R

sample /R standard ) – 1 ], where R is 13C/12C or 15N/14N, respectively. Typical precision of the

analyses was ± 0.1 ‰ for both δ15N and δ13C.

Lipid normalization

Since lipids are 13C-depleted relative to protein (DeNiro & Epstein, 1977), lipid

normalization was applied for invertebrate taxa using C:N ratios (molar) (Eq. (3) in Post et

al., 2007). This correction was applied to all invertebrates samples with C:N values > 3.5 (>

5% lipid content) according to the following equation:

δ13C′ = δC + (0.99) × (C:N) − 3.32

For fish samples, an additional model for lipid normalization was applied according to (Eq.

(5) in Kiljunen et al., 2006) and defined as:

δ13C′ = δ13C + D × (I + 3.90 / (1 +287/L))

L = 93/ 1 + (0.246 × (C:N) − 0.775-1

Where L is the proportional lipid content of the sample (equation above); δ13C is the isotopic

value of the sample analyzed; D is the isotopic difference between protein and lipid

(7.018±0.263) and I is a constant (0.048±0.013).

Statistical comparison assemblages

For determining differences in carbon and nitrogen enrichment patterns through the food

webs, δ13C and δ15N values were independently compared from the different assemblages.

Comparison were made between OM sources of organic matter, and between corals including

the mesophotic mushroom coral Cycloceris vaughani. ANOVA tests were run to compare

δ13C values of OM sources and δ13C and δ15N values of corals. In addition, a non-parametric

equivalent Kruskal-Wallis test was used to compare δ15N values of OM sources. Parametric

post-hoc Tukey tests (multiple comparison of mean) were used for δ13C values of corals,

whereas non-parametric Tukey and Kramer (Nemenyi) test (T-K) were used for δ15N values

of OM sources. All statistical analyses were run in RStudio (R Core Team, 2018). Where

summary statistics are reported, we use mean ± SD.

Estimating trophic position (tRophicPosition package)

We estimated trophic position of different consumer taxa using “oneBaseline” model,

incorporating uncertainty in the trophic discrimination factor (TDF) for nitrogen (mean ± SD

Δ15N = 2.9 ± 0.3 ‰; McCutchan, Lewis, Kendall, & McGrath, 2003), as well as baseline and

consumer δ15N values through Bayesian inference with the tRophicPosition package

(Quezada-Romegialli et al., 2018).

Assuming that the RNME is likely supported mainly by benthic N2-fixation pathways (e.g.,

benthic N2-fixing cyanobacteria and diazotrophic symbionts in corals, sponges and

macroalgae), the corallivorous gastropod Coraliophilla violacea was used as a benthic

baseline. The Δ15N and Δ13C were taken from global meta-analyses and corresponded to

muscle tissue values (mean ± SD Δ15N =2.9 ± 0.3 ‰) (McCutchan et al., 2003). For birds,

TDF values were estimated as the average from different bird species (Δ15N =3.8 ± 1.2 ‰;

summarized in Caut, Angulo, & Courchamp (2009). Models were run with 2 chains, 20 000

adaption samples and 20 000 iterations.

Isotopic niche of marine assemblages

To determine isotopic diversity between marine assemblages, the sample-size corrected

version of the standard ellipse area (SEAc) was utilized as a measure of the mean core of the

isotopic niche occupied by different taxa in each assemblage (Jackson et al., 2011). This

metric represents a measure of the total amount of niche occupied in isotopic space and

allows for robust statistical comparisons between data sets with different sample sizes and

corrects for bias when sample sizes are small (Jackson et al., 2011). Moreover, this metric

allows the calculation of the isotopic overlap of the Bayesian standard ellipses area (SEAB)

between assemblages (employing 95 % of data), and this was used as a measure of isotopic

partitioning between different assemblages. Additionally, two measurements of isotopic

niche widths and trophic structure (see Layman, Arrington, Montaña, & Post, 2007) were

calculated for each assemblage: (1) Mean distance to centroid (CD): average Euclidean

distance of each species to the δ13C and δ15N centroid, where the centroid is the mean δ13C

and δ15N value for all species in the food web, giving additional information about the

isotopic niche amplitude and spacing between species within the assemblage or trophic guild

and (2) Standard deviation of nearest neighbor distance (SDNND): a measure of the evenness

of species packing in isotopic bi-plot space. These metrics were estimated using the SIBER

package available in R (Jackson et al., 2011).

Using Bayesian mixing models to examine contributions to assimilated diet (MixSIAR)

To evaluate the relative contribution of the three main putative primary producers (i.e.,

zooxanthellae, macroalgae and phytoplankton) to different assemblages of consumers around

Rapa Nui (i.e., zooplankton, emergent macrobenthos, reef invertebrates, macrobenthos, reef

fishes, pelagic fishes and birds), Bayesian stable isotope mixing models were used. We used

the MixSiar R package (Stock et al., 2018), where δ13C and δ15N values from POM were

used as proxy of phytoplankton production, the dominant scleractinian corals (P. lobata and

Pocillopora spp.) as proxy of zooxanthellae production and the dominant macroalgae species

(i.e., L. variegata, Halimeda sp., Ulva sp., Liagora sp., Codium sp. Spatoglossum stipitatum,

Stipodium flaveliforme and Sargassum obstusifolium) as proxy for macroalgae production.

The error term “Process* Residual” was selected for the mixture (i.e., consumers) where n >

2 and only “Process” when mixture samples were n=1. The residual error incorporates the

potential variation associated with consumers (e.g., different metabolic rate, assimilation

efficiency or digestibility), whereas the process error incorporates the variation associated to

sampling process and consumer specialization (Stock & Semmens, 2016). Uninformative

priors (all values between 0 and 1 are likely equally) were used for all models. Models were

run using a “normal” chain length through Markov Chain Monte Carlo (MCMC) and “long”

or “very long” options until model convergence was reached, as assessed through Gelman-

Rubin and Geweke diagnostic test (Stock & Semmens, 2016).

The TDF values for muscle (see above) were taken from global meta-analyses (McCutchan

et al., 2003) and considering a constant trophic fractionation between consumer and diet

through the food web, therefore multiplying the TDF values by the number of trophic levels

estimated for each taxon (Phillips et al., 2014). Relatively wide SD values (1.3 ‰) were used

for both Δ13C and Δ15N TDFs, allowing the inclusion of a range of likely fractionation values

and solutions through mixing models. Prior to running mixing models, a detailed analysis of

simulations of Bayesian mixing polygons (Smith, Mazumder, Suthers, & Taylor, 2013) was

performed for all consumers (MCMC simulation with 15 000 iterations). This analysis was

used to explore models with potential solutions, and for the selection of individuals of each

taxa to include in mixing models (those inside the 95% mixing polygon region).

4.4 Results

Stable isotope composition

Macroalgae

The stable isotope composition of subtidal macroalgae showed considerable variation for

both δ13C (range 14.9 ‰; Fig 3.2a, Table 3.2) and δ15N values (11.1 ‰; Fig 3.2b, Table 3.2).

δ13C values were lower for Rhodophyta sp. (-29.9 ‰, n = 1) and higher for the brown algae

S. stipitatum (mean ± SD = -15.0 ± 1.8 ‰, n = 3). In addition, mean δ15N values were lower

for brown macroalgae L. variegata (3.6 ‰, n = 1) and higher for S. obtusifolium (13.3 ‰, n

= 1; Table 3.2).

Zooxanthellate corals

The stable isotope composition (δ13C and δ15N) for shallow scleractinian corals (P. lobata

and Pocillopora spp.) showed limited variation between species, with massive coral P. lobata

showing lower mean δ13C and δ15N values (mean ± SD = -16.2 ± 1.2 and 5.4 ± 1.4 ‰, n = 6)

and branching corals Pocillopora spp. slightly higher mean higher values (-15.3 ± 2.0 and

6.1 ± 3.3 ‰, n = 7), but these values were not statistically significant (ANOVA, F = 0.27, df

= 2, P = 0.77). Additionally, δ13C values (-16.9 ± 1.8 ‰, n = 3) from the mesophotic coral

C. vaughani collected from 80 m depth were similar to shallow corals (ANOVA, F = 0.27,

df = 0.47, P = 0.767). However, δ15N values were significantly different between species

(ANOVA, F = 5.34, df = 2, P = 0.026), with C. vaughani being 15N enriched (8.5 ± 3.4 ‰, n

= 4) compared to Pocillopora spp. corals (6.1 ± 3.3 ‰, n = 7) (Tukey, P = 0.021).

Particulate organic matter (POM)

POM δ13C values were constant (-23.9 ± 0.5, n = 8; range = 1.1 ‰; Fig. 3.2a, b), with the

most negative values (-24.5 ± 0.8 ‰, n = 3) reported from off the Rano Raraku volcano site

(0 to 50 m depth) and slightly higher values (-23.4 ‰, n = 1) reported from Motu Nui islet

(30 m depth) (Table 3.2). In addition, variation in δ15N values was higher (range = 5.3 ‰),

with lower δ15N values (4.5 ‰, n = 1) from Motu Nui (30 m depth) and higher values (9.8

±1.0 ‰, n = 3) from the Apolo fishing ground (0-100 m depth; Table 3.2). Comparison of

mean δ13C values between SE Rano Raraku volcano site and Apolo did not differ statistically

(ANOVA, df = 2, F = 0.591, P = 0.477). However, δ15N values were significantly higher in

Apolo fishing ground (ANOVA, df =2, F=13.87, P = 0.014).

The three different organic matter sources (zooxanthellate corals, macroalgae and POM) had

distinct δ13C values (K-W, df = 2, p < 0.001). Coral δ13C values (-16.2 ± 0.7 ‰) were more

13C enriched than macroalgae (-19.6 ± 5.0; T-K, P = 0.032) and POM (-23.9 ± 0.5 ‰; T-K,

p < 0.001). Differences between macroalgae and POM were on the threshold of statistical

significance (T-K, P = 0.047). However, δ15N values did not differ (ANOVA, F = 1.61, df =

2, P = 0.218) between the sources (macroalgae: 6.2 ± 4.0 ‰, POM: 6.5 ± 2.4 ‰, and corals:

6.6 ± 1.7 ‰).

Figure 1. Stable isotope biplot showing variation in δ15N and δ13C (with marginal density plots) based

on isotopic mean values of taxa comprising the different assemblages in RNME. Error bars were not

included to simplify interpretation.

Table 3.2. Summary of stable isotope (δ13C and δ15N) values of primary producers (macroalgae, zooxanthellate corals, and particulate organic matter)

in RNME. Lipid-correction (δ13C ́values) were only considered for scleractinian corals.

δ13C (‰)

δ13C´ (‰)

δ15N (‰) C/N

Taxon Mean SD Mean SD n Mean SD n Range

Macroalgae

Halimeda sp. -19.5 2.8 - - 4 2.2 0.7 5 15.3-87.5

Lobophora variegata -16.1 - - - 1 3.6 - 1 16.6

Ulva sp. -21.9 - - - 1 3.7 - 1 12

Codium sp. -17.6 - - - 2 4.4 - 2 12.7-17.4

Rhodophyta sp. -29.9 - - - 1 4.9 - 1 8.9

Liagora sp. -15.1 - - - 1 5.9 - 1 24.7

Spatoglossum stipitatum -15.0 1.8 - - 3 11.4 - 1 16.4-33.9

Sargassum Obtusifolium -21.3 - - - 1 13.3 - 1 21.6

Mean ± SD -19.6 5.0 6.2 4.0

Zooxanthellate corals

Porites lobata -19.7 1.0 -16.2 1.2 6 5.4 1.4 6 6.1-8.3

Pocillopora spp. -19.3 1.5 -15.3 2.0 7 6.1 3.3 7 6.2-8.7

Cycloseris vaughani -21.1 1.4 -16.9 1.8 3 8.5 3.4 4 6.3-8.9

Mean ± SD -20.0 0.9 -16.2 0.7 6.6 1.7

Particulate organic matter (POM)

SE Rano Raraku 0-50 m (Nov 2014) -24.5 0.8 - - 3 6.7 1.2 3 -

Motu Nui 30 m (Dic 2014) -23.4 - - - 1 4.5 - 1 -

Apolo Seamount 0-100 m (Nov 2014) -24.0 1.0 - - 3 9.8 1.0 3 -

Motu Tautara 0 m (March 2016) -23.7 - - - 1 5.0 - 1 -

Mean ± SD -23.9 0.49 6.5 2.4

Zooplankton (mesozooplankton and emergent zooplankton)

Mesozooplankton δ13C values were relatively similar (-19.7±1.2 ‰; range = 4.8 ‰) and more

constrained for δ15N values (4.7 ± 0.4 ‰; range = 1.4 ‰) (Fig. 3.1, Fig. 3.2a, b). Comparisons

between taxa showed lower mean δ13C values for Stomatopoda larvae (-21.7 ‰, n = 1) and

higher for brachyuran larvae (-16.8 ± 0.4 ‰, n = 4) (Appendix 1). However, δ15N values

measures were lower for chaetognatha sp. (3.9 ± 0.3 ‰, n = 5) and higher for cyclopoid

copepods (5.3 ± 0.3 ‰, n = 5; Appendix 1). In contrast, emergent zooplankton showed higher

δ13C and δ15N variation than zooplankton (-17.9 ± 2.0, range = 5.8 ‰ and 6.3 ± 2.8, range =

8.7 ‰, respectively; Fig. 3.2a, b). The lowest δ13C values were recorded in barnacle cypris

larvae (-20.7 ‰, n = 1) and highest values in Amphipoda sp. 1 (-15.0 ‰; n = 1; Appendix

1). However, lower δ15N values were measured for Isopoda sp. 1 (mean = 3.5 ‰, n = 2) and

higher in Amphipoda sp. 2 (12.2 ‰, n = 1; Appendix 1).

Fig. 3.2. Boxplot of stable isotope composition for a) δ13C and b) δ15N values for putative sources

(left panel) and different marine assemblages (right panel). Box limits represent the first (low limit)

and third quartile (upper limit) and the horizontal line inside represent the median. Whiskers represent

the minimum and maximum values. Mean values are also represented by red dots. Outliers are

included. Letters denote significant differences among functional groups (P<0.05).

Benthic invertebrates (macrobenthic and reef invertebrates)

Reef invertebrates showed considerable variation in δ13C values (-14.8 ± 1.9 ‰, range =7.3

‰) and δ15N values (7.8 ± 2.1 ‰, range = 7.5 ‰; Figs. 1; 2a, b) with the range in δ15N values

being the highest seen in any of the assemblages examined here (Fig. 3.2b). The gastropod

Monetaria caputdraconis displayed the lowest δ13C values (-18.4 ‰, n = 1), whereas the

highest were observed in the orange ascidian (-11.1 ‰, n = 1; Appendix 1). δ15N values were

lowest in needle-spined urchin Echinostrephus aciculatus (4.1 ± 1.5 ‰, n = 8) and highest

in the brachyuran crab Liomera sp. (11.6 ‰, n = 1; Appendix 1). In contrast, macrobenthos

showed reduced variation in δ13C (-16.9 ± 1.7 ‰, range = 2.7 ‰) and δ15N (7.9 ± 1.4 ‰,

range = 4.8 ‰) relative to reef invertebrates (Fig. 3.2a, b). Within this assemblage, the

cephalochordate Amphioxus sp. had lower values (-20.5 ‰, n = 1) while the polychaete

Syllidae sp. showed the most 13C enriched values (-15.3 ± 1.9 ‰, n = 13; Appendix 1). In

addition, δ15N values were lowest in Syllidae sp. (5.7 ± 1.4 ‰, n = 13) and highest for another

unidentified Polychaeta sp. 2 (10.5 ‰, n = 1; Appendix 1).

Fishes

Reef fishes showed more variation in δ13C values (-13.8 ± 2.4 ‰, range = 8.3 ‰) relative to

the other assemblages examined (Fig. 3.1, Fig. 3.2a); however δ15N variation was narrower

(11.9 ± 1.4 ‰, range = 6.5 ‰; Fig. 3.1, Fig. 3.2a). Lower δ13C values were recorded in the

deep-dwelling moray Gymnothorax bathyphilus (mean = -18.6 ‰, n = 2) and the highest

values in the Plessis´ morwong Goniistius plessisi (mean = -10.3 ‰, n = 2; Appendix 1). In

contrast, δ15N values were lower for whitebar surgeonfish Acanthurus leucopareius (8.4 ±

1.3 ‰, n = 4) and higher for the blunthead puffer Sphoeroides pachygaster (mean = 14.9 ‰,

n = 2; Appendix 1). Pelagic fishes showed less variation in δ13C values (-13.8 ± 2.4‰, range

= 2.4 ‰) and δ15N values (11.9 ±1.4 ‰, range = 5.5 ‰; Fig. 3.1, Fig. 3.2a, b) compared to

the reef fish assemblage. Within the pelagic fish assemblage, the yellowtail amberjack

Seriola lalandi had the lowest δ13C values (-16.1 ± 1.5 ‰, n = 4) and the Pacific halfbeak

Hyporhamphus acutus the highest (-13.7 ‰, n = 1; Appendix 1). D. muroadsi had the lowest

δ15N values (12.0 ‰ ± 0.7, n = 4), and the mahi-mahi Coryphaena hippurus the highest (17.5

‰ ± 0.9, n = 7; Appendix 1).

Seabirds

Variation in seabird δ13C values was limited (-16.2 ± 0.8 ‰, range = 2.2 ‰) and slightly

wider for δ15N (16.7 ± 1.6 ‰, range = 4.0 ‰) (Fig. 3.1, Fig. 3.2a, b). Lower mean δ13C values

were measured in the Muphy´s petrel Pterodroma ultima (-17.6 ± 0.7 ‰, n = 7; Appendix 1)

and higher values in the Phoenix petrel Pterodroma alba (-15.4 ± 0.5 ‰, n = 5; Appendix

1). The black-winged petrel Pterodroma nigripennis had the lowest δ15N values (15.2 ± 1.5

‰, n = 7), while P. alba was the most 15N enriched 19.2 ± 3.3 ‰, n = 5) seabird species.

Statistical comparisons between assemblages

There was a clear positive shift in δ13C values displayed from pelagic taxa such as

mesozooplankton and emergent zooplankton, followed by macrobenthos, seabirds, and

pelagic fishes, through to increasing 13C enriched values seen invertebrates and fishes

collected from the coral reef (Fig. 3.2a). Statistical comparison between assemblages

evidenced significant differences (ANOVA, F= 18.11, p < 0.001). Multiple comparison test

showed that mesozooplankton had significant lower mean δ13C values than most assemblages

(Tukey, p < 0.05, Table 3.3), except compared with emergent zooplankton (Tukey, P =

0.430). Emergent zooplankton had significant lower mean δ13C values relative to reef

invertebrates and reef fishes (Tukey, p < 0.05, Table 3.3). In addition, reef fishes exhibited

higher δ13C values than macrobenthos, reef invertebrates, emergent zooplankton and

mesozooplankton (Tukey, p < 0.05, Table 3.3).

Comparison of δ15N values showed a clear increase from mesozooplankton and emergent

zooplankton, to reef invertebrates, macrobenthos, reef fishes, pelagic fishes and seabirds

(Fig. 3.2b). Statistical comparison indicated significant differences between their values (K-

W, P < 0.001). Multiple comparisons indicated that mesozooplankton, emergent zooplankton

and reef invertebrates had significant low δ15N values than reef fishes, pelagic fishes and

seabirds (T-K, p < 0.05, Table 3.3). Macrobenthos showed significant lower values than

pelagic fishes and seabirds (T-K, p < 0.05, Table 3.3).

Table 3.3. Summary of multiple comparison for carbon (upper section data) and nitrogen (lower section data) stable isotopes between different

assemblages in RNME.

Mesozooplankton Emergent

zooplankton Macrobenthos Reef

invertebrates Reef fishes Pelagic fishes Seabirds

Mesozooplankton - 0.43 0.01* <0.01* <0.01* <0.01* <0.01*

Emergent zooplankton 1.00 - 0.93 <0.01* <0.01* 0.05 0.58

Macrobenthos 0.33 0.80 - 0.05 <0.01* 0.40 0.99

Reef invertebrates 0.10 0.73 1.00 - 0.46 0.97 0.37

Reef fishes <0.01* <0.01* 0.17 <0.01* - 0.22 0.02*

Pelagic fishes <0.01* <0.01* <0.01* <0.01* 0.52 - 0.88

Seabirds <0.01* <0.01* <0.01* <0.01* 0.35 1.00 -

* denote significant differences (p < 0.05).

Trophic position

Zooplankton

Mesozooplankton taxa largely encompassed two trophic levels (TP range = 2.1 to 3.5), with

only stomatopod larvae taxon show higher trophic position (TP mode = 3.5, 95% Bayesian

confidence interval (BCI) = 2.0–9.4; Appendix 2). Similar to mesozooplankton, the emergent

zooplankton was represented by seven taxa encompassing two trophic levels (TP range = 2.0

to 3.6), with only Amphipoda sp.2 show higher trophic position (TP mode = 3.6, BCI = 2.0–

9.4) (Appendix 2).

Benthic invertebrates

Reef invertebrates were represented by 33 taxa and comprised two trophic levels (TPs range

= 2.0 to 3.5). Trophic positions (TP) estimations determined 28 taxa as primary consumers

and others five taxa as secondary consumers (Appendix 2). The higher trophic positions were

estimated in the brachyuran crab Liomera sp. (TP mode =3.5; BCI = 2.0 – 9.4) the Easter

Island spiny lobster Panulirus pascuensis (TP mode = 3.4, BCI = 2.0 – 9.3), and the seastar

Astrotole paschae (TP mode = 3.2, BCI = 2.0 – 7.4; Appendix 2). In addition, the

macrobenthos was represented by eight taxa (mainly polychaetes) comprising two trophic

levels (TL = 2 and 3). Most taxa were classified as primary consumers, except the Polychaeta

sp. 2 that was classified as secondary consumers (TP mode = 3.1, BCI = 2.0 – 9.3; Appendix

2).

Fishes

The reef fishes were represented by 33 taxa, mainly encompassing three trophic levels (TP

range = 2.3 to 4.5), with only A. leucopareius and Blenidae sp. showed low trophic positions

(TP mode = 2.3, BCI = 2.0 – 3.3 and TP mode = 2.7, BCI = 2. – 9.3, respectively). 18 taxa

were classified as secondary consumers (TP range = 3.2 to 3.9), while other four taxa (i.e.,

Synodus sp., S. pachygaster, Myripristis tiki and Pseudocaranx dentex) were classified as

tertiary consumers (TP range = 4.0 to 4.5; Appendix 2).

Pelagic fishes were represented by 14 taxa and comprised three trophic levels (TP range =

3.6 to 5.4). Three lower TPs were in D. muroadsi (TP mode = 3.6, BCI = 2.8 – 4.5), H. acutus

(TP mode = 3.9, BCI = 2.0 – 9.3) and the violet warehou Schedophilus velaini (TP mode =

3.6, BCI = 2.4 – 5.3), six have intermediate TPs and three higher TPs including the wahoo

Acanthocibyum solandri (TP mode = 5.0, BCI = 4.3 – 6.2), C. rapanouiensis (TP mode =

5.1, BCI = 4.3 – 6.4) and C hippurus (TP mode = 5.4, BCI = 4.6 – 6.6; Appendix 2).

Seabirds

The seabird assemblage was represented by eight species involving two trophic levels (TP

range= 4.0 to 5.1). The lower TPs were estimated in two congeners P. nigripennis (TP mode

= 4.0, BCI = 3.5 – 4.7), P. neglecta (TP mode = 4.1, BCI = 3.6 – 4.8) and also in P. nativitatis

(TP mode = 4.1, BCI = 3.5 – 4.7). Higher TPs were estimated in P. heraldica (TP mode =

5.1, BCI = 4.4 – 5.8) and P. alba (TP mode = 5.1, BCI = 3.5 – 4.7; Appendix 2).

Trophic Diversity of assemblages

Bayesian ellipses area estimations indicated differences in the trophic diversity between

different assemblages, with pelagic assemblages (i.e., zooplankton and pelagic fishes)

evidencing lower SEAc values (1.6 and 4.2 ‰2, respectively), compared with coral reef

assemblages (i.e., reef-invertebrates and reef-fishes) which showed far higher levels of

isotopic variation (13.1 and 10.6 ‰2) (Fig. 3.3a, b, Table 3.4). Furthermore, the level of

ellipse overlap between different assemblages was generally low. For example, zooplankton

and reef-invertebrates had a 2.5 % overlap, reef-fishes and pelagic-fishes had an overlap of

13.7 %, with the highest overlap being estimated between reef-invertebrates and reef-fishes

(27.6 %) (Fig. 3.3a, Table 3.4). Layman metrics showed a similar pattern, with low CD values

in zooplankton and pelagic fish assemblages (0.9 ‰ and 1.7 ‰, respectively) and higher

values in reef invertebrates (2.6 ‰; Table 3.4). The SDNND values were similarly low (0.3

‰ to 0.6 ‰; Table 3.4).

Table 3.4. Summary of mean and 95% Bayesian credible intervals for trophic structure metrics.

Metrics Zooplankton Reef invertebrates Reef fishes Pelagic fishes

CD (‰) 0.8(0.2-1.4) 1.8 (1.5-2.1) 1.2(0.8-1.6) 1.7(1.0-2.5)

SDNND (‰) 0.4(0-1.0) 0.9(0.1-1.5) 0.5(0-1.1) 1.0(0-2.1)

SEAc (‰2) 1.6 (0.8-2.6) 13.1(8.8-17.8) 10.6(6.9-15.4) 4.3(2.1-6.8)

Ellipse overlap (%) Zooplankton Reef invertebrates Reef fishes Pelagic fishes

Zooplankton 0 2.5 0.0 0.0

Reef invertebrates - 0 27.6 6.2

Reef fishes - - 0 13.7

Pelagic fishes - - - 0 CD: Centroid distance, SDNND: Standard deviation of nearest neighbor distance. SEAc: sample size-corrected standard ellipse area.

Figure 3. a) Bayesian standard ellipses area (SEAB) plotted in δ15N-δ13C isotopic space and b) boxplot

of SEAc metrics estimated for different assemblages of invertebrates (zooplankton and reef

invertebrates) and fishes (reef fishes and pelagic fishes). The Bayesian ellipses were built including

95% of the total data. The outer light gray boxes represent the 95% Bayesian confidence interval

(BCI) and the slightly larger and darker boxes 75 % and 50 % BCI. Black dots and crosses represent

the median and mean estimates, respectively.

Bayesian mixing models

Zooplankton

For mesozooplankton assemblages phytoplankton and coral-derived OM were on average

important (mean ± SD = 40 ± 8.9 % and 39 ± 13.3 %, respectively), with coral-derived OM

being important for brachyuran larvae and Siphonophora (mean = 67 %, BCI = 50 – 80 %

and mean = 51 %, BCI = 5 – 71 %, respectively; Fig. 3.4, Appendix 2). Phytoplankton-

derived OM was important for calanoid copepods (mean = 47, BCI = 1 – 68 %) and

Hidromedusae (mean = 46, BCI = 1 – 77 %) (Fig. 3.4, Appendix 2). In contrast, macroalgae-

derived organic matter was on average less important (mean = 21 ± 6.0 %; Appendix 2).

Mixing models indicated that macroalgae- and coral-derived OM, were more important on

average for emergent zooplankton (mean ± SD = 51 ± 14.9 % and 30 ± 9.5 %, respectively).

The mixing models indicated that macroalgae –derived OM was important for Nereidae sp.

(mean = 68 %, BCI = 3 – 98 %) and caridea larvae (mean = 60, BCI = 2 – 98 %; Fig. 3.4,

Appendix 2). Additionally coral-derived OM was important for brachyuran larvae (mean =

44 %, BCI = 3 – 80 %) and Amphipoda sp. 2 (mean = 36, BCI = 3 – 78 %) (Fig. 3.4, Appendix

2). Phytoplankton-derived OM contribution was in general less important (mean= 19 ± 8.6%)

(Fig. 3.4, Appendix 2).

Benthic invertebrates

Bayesian mixing models indicate that coral production is incorporated to a greater degree by

macrobenthos and reef invertebrates (mean ± SD = 58 ± 11.5 % and 67 ± 13.3 %,

respectively), followed by macroalgae-derived OM (mean ± SD =28 ± 5.3 % and 24 ± 9.9

%, respectively) and phytoplankton-derived OM (mean ± SD= 14 ± 7.1 % and 9 ± 6.0 %,

respectively; Appendix 2). For the macrobenthos assemblage, the polychaetes Lumbrineridae

and Syllidae sp. had the higher contribution of coral-derived OM (mean = 74 %, BCI = 23 –

96 % and mean = 71 %, BCI = 28 – 94 %, respectively; Fig. 3.4, Appendix 2). Among the

reef invertebrates, the maximum contribution of coral-derived OM was estimated for the

gastropods Pascula citrica (mean = 89 %, BCI = 69 – 99 %), Conus miliaris (mean = 85 %,

BCI = 48 – 98 %) and the sea cucumber Stichopus monotuberculatus (mean = 80 %, BCI =

45 – 98 %) (Fig. 3.4, Appendix 2). Macroalgae-derived OM was important only for sea urchin

Diadema savignyi (mean = 51 %, BCI = 1–92 %) (Fig. 3.4, Appendix 2).

Fishes

Bayesian mixing models for reef fishes suggest an important contribution of coral-derived

OM (mean ± SD = 62 ± 17.6 %), followed by phytoplankton-derived OM (mean ± SD = 19

± 13.1 %) and to a lesser amount by macroalgae-derived OM (mean ± SD = 16 ± 8.7 %). The

maximum contribution for coral-derived OM were reported in Pacific chub Kyphosus

sandwicensis (mean = 83 %, BCI = 54–97 %) and Wilhelm´s hawkfish Itycirrhitus wilhelmi

(mean = 83 %, BCI = 38–98%) (Fig. 3.5; Appendix 2). Phytoplankton-derived OM made

important contributions for G. bathyphilus (mean = 50 %, BCI = 2–74 %) and the glasseye

Heteropriacanthus cruentatus (mean = 43, BCI = 21–74 %) (Fig. 3.5; Appendix 2).

Bayesian mixing models also suggest an important contribution of coral-derived OM to

pelagic fishes, (mean ± SD =41 ± 8.8 %), followed by phytoplankton-derived OM (mean ±

SD = 34 ± 7.8 %) and to a lesser amount macroalgae-derived OM (mean ± SD = 24 ± 6.1

%). The coral-derived OM was the most important source for D. muroadsi (mean = 51 %,

BCI = 10–82%) and S. velaini (mean = 51 %, BCI = 19–73 %; Appendix 2). However,

phytoplankton-derived OM was most important C. hyppurus (mean = 44 %, BCI = 18–64

%), C. rapanouisensis (mean = 40 %, BCI = 2–60 %), A. solandri (mean = 38 %, BCI = 15–

56 %) and S. lalandi (mean = 39 %, BCI = 5–74 %; Appendix 2).

Figure 4. Summary of mean relative contribution of scleractinian corals, macroalgae and phytoplankton (POM) to heterotrophic invertebrates

(mesozooplankton, emergent zooplankton, macrobenthos and reef invertebrates) from Rapa Nui Marine Ecosystem. Detailed outputs from Bayesian

mixing models are summarized in Appendix 2.

Figure 5. Summary of average relative contributions of scleractinian corals, macroalgae and phytoplankton (POM) to reef fishes and pelagic fishes

from Rapa Nui Marine Ecosystem. Detailed outputs from Bayesian mixing models are summarized in Appendix 2.

4.5 Discussion

C and N incorporation into food webs

The isotopic composition of aquatic primary production largely depends on the isotopic value

of dissolved C and N pools and isotopic fractionation (Montoya, 2007), but also on consumer

growth rates, species and water temperature (Dethier, Sosik, Galloway, Duggins, &

Simenstad, 2013; Magozzi, Yool, Vander Zanden, Wunder, & Trueman 2017). In this sense,

the wide variation in macroalgae δ13C values likely partly reflects the differential use of DIC

sources (i.e., CO2 or HCO3-) and differences in their respective carbon isotopic fractionation,

with more negative values (-40 to -11 ‰) when dissolved CO2 is taken up and more positive

(-21 to -11 ‰) when HCO3- is assimilated (Mayr et al., 2012). In addition, δ13C values for

phytoplankton depended of the concentration and isotopic values of dissolved CO2 and

different community features (e.g., growth rates, cell dimensions and taxonomy; see

Trueman, MacKenzie, & Palmer, 2012). However, very negative δ13C values from pico-

POM samples are typical of subtropical gyres where phytoplankton growth is nutrient-

limited (Trueman et al., 2012), agreeing with the values and fraction-size reported for

oligotrophic systems in the Mediterranean Sea (Hunt et al., 2018). In addition, carbon

isotopic fractionation in corals can show higher variability (-30 to -10 ‰), but generally show

more positive values than the fractionation of macroalgae (Koweek et al., 2019), as recorded

in this study (~-16 ‰).

In contrast, low δ15N values in primary producers (i.e., corals, macroalgae and POM) could

reflect the incorporation of nitrogen derived from N fixation (Yamamuro, Kayanne, &

Minagawa, 1995). The Rapa Nui Marine Ecosystem is located near to the South Pacific

Subtropical Gyre, with ultra-oligotrophic waters and where the presence of pelagic N2-fixing

microorganisms (diazotrophs) has been established (von Dassow & Collado-Fabbri, 2014).

Therefore, values from primary producers could be associated with local N2-fixation through

OM remineralization generating a DIN pool (i.e., NO3-, NO2

-, or NH4+) with low δ15N values,

which subsequently is taken up and assimilated by primary producers (Montoya, 2007).

However, in coral reef ecosystems, benthic N2-fixation can be ubiquitous, being found also

in microbial mats, scleractinian corals, macroalgae, algal turfs, limestone, dead corals and

seagrass (Cardini, Bednarz, Foster, & Wild 2014), therefore local benthic N2-fixation could

be also an important source of new nitrogen for the RNME.

Energy transference mechanisms

Consumer δ13C and δ15N values showed a clear pattern of 13C and 15N enrichment from

benthic (zooxanthellate corals and macroalgae) and pelagic (POM) organic sources, where

benthic invertebrates (macrobenthos and reef invertebrates) and pelagic assemblages

(mesozooplankton and demersal zooplankton) are likely important links for energy transfer

into upper consumers (i.e., reef and pelagic fishes and seabirds). In this sense, Bayesian

mixing model results indicated that benthic sources (largely zooxanthellate coral, and

macroalgae to a lesser degree) were the most important OM sources for different animal

assemblages from the RNME. These results agreed with others results from theoretical

network analysis for the Great Barrier Reef, where in corals dominated systems the PP and

carbon fluxes to consumer is dominated by zooxanthellae and coral-derived OM was thought

to be the most important source supporting upper trophic level consumers (Johnson, et al.,

1995). Indeed, the dominance of scleractinian corals P. lobata and Pocillophora spp. from

shallow to mesophotic depths (Easton et al., 2019; Wieters et al., 2014) is likely an important

factor controlling locally OM availability around Rapa Nui, especially given the low levels

of pelagic primary productivity in the region.

Coral-derived OM is known to be an important source fueling invertebrates (e.g., C. violacea)

and fishes (e.g., Thalasoma lutescens, Arothron meleagris), which can feed directly on coral

tissues (Disalvo et al., 2007). However, coral mucus production is increasingly recognized

as an important nutritional pathway that can contribute to corallivory, albeit indirectly

(Nakajima, Tanaka, Guillemette, & Kurihara, 2017; Naumann, Mayr, Struck, & Wild, 2010)

and has been showed to provide energetic inputs to zooplankton (Gottfried & Roman, 1983),

coral reef invertebrates (Stella, Pratchett, Hutchins, & Jones, 2011), macrobenthic fauna in

sediments (Wild et al., 2004) and reef fishes (Benson & Muscatine, 1974). Also, coral mucus

can serve as a trap for OM and microorganisms, which in turn can be consumed by

detritivore, herbivore and filter-feeding taxa (Enochs & Glynn, 2017).

Recent studies using stomach content metabarcoding of reef fishes indicate a higher

prevalence of crustaceans (brachyuran and caridea), annellids and fish larvae in their diets

(Casey et al., 2019). In this study, brachyuran, caridea larvae, and nereid polychaetes were

important component of the emergent zooplankton assemblage, and mixing models indicated

distinct contributions from different organic matter sources (corals and macroalgae mainly;

Fig. 3.4), emphasizing the potential trophic role of cryptofaunal adults and larval stages

transferring OM through coral reefs (Kramer et al., 2013).

Macroalgae-derived materials are considered important energetic sources in eastern Pacific

coral reefs (Enochs & Glynn, 2017). Here, Bayesian mixing models confirmed their

importance for some invertebrate taxa in the RNME, including sea urchins (e.g., D. savignyi)

and polychaetes (e.g., Nereidae) (Fig. 3.4, 3.5, Appendix 2). Recent studies in Rapa Nui

reported lower cover of ephemeral (e.g., Lobophora sp.), articulated (e.g., Halimeda sp.) and

leathery (Padina sp.) macroalgae compared to scleractinian corals (Wieters et al., 2014).

However, coralline calcareous algae are reported to be important primary producers and

trophic resources for coral reef consumers (Chisholm, 2003), and have been documented to

depths of 220 m in the RNME (Easton et al., 2019). In this context, the detritus produced and

retained by macroalgae can be important for detritivore and herbivore taxa (Enoch & Glynn

2017). Although detritus samples were not directly sampled in this study, its organic pathway

could be an important trophic source for those species where mixing models were

undetermined (e.g., Tripneustes gratilla, Holothuria nobilis, Breviturma dentata,

Polyplectana kefersteinii, A. leucopareus), likely due to the influence of detritus sources from

macroalgae with more positive δ13C and lower δ15N values (Max, Hamilton, Gaines, &

Warner, 2013; Plass-Jhonson, McQuaid, & Hill, 2013) or due to some other source not

sampled.

Our results indicate that the contribution of phytoplankton (as POM) to reef invertebrates and

fishes was minimal and only dominant in some zooplanktivore and piscivore species (i.e., H.

cruentatus and G. bathyphilus, respectively). Similar results using stable isotopes were

reported for coral reef food webs in Papahānaumokuākea marine national monument, where

phytoplankton contribution to upper consumers was marginal (Hilting et al., 2013). However,

cryptobenthic invertebrates and reef fishes can be an important trophic link (e.g., during their

larval stages) subsidizing coral reef invertebrates and fishes with pelagic-derived materials

(Brandl et al., 2019; Casey et al., 2019).

In contrast, pelagic predatory fishes and seabirds clearly showed lower δ13C values compared

to reef invertebrates and fishes, suggesting the incorporation of pelagic-derived carbon, even

though they were considerably 13C enriched relative to POM. These differences could be

associated to temporal changes in δ13C values from regional phytoplankton or due to that

predators could be integrating δ13C values from spatio-temporal gradients associated to

migratory dynamics (Magozzi et al., 2017). Reduced maximum chl-a values (0.05 mg m-3)

have been reported for surface waters around Rapa Nui (using remote sensing) during the

austral winter (Andrade et al., 2014), whereas the deep chlorophyll maximum (DCM: ~1 mg

m-3) has been recorded to be located between 150-200 m depth, where the mixed layer depth

remains stable throughout the year associated a null mixing periods (Mignot et al., 2014).

Nonetheless, mesopelagic micronekton can undertake extensive diel vertical migration

(DVM) from the pelagic deep layer to surface waters (0-200 m depth) at dusk, transferring

energy to higher trophic level consumers such as tunas, swordfish and seabirds (Annasawmy

et al., 2018). Moreover, predatory fishes in Rapa Nui (e.g., T. albacares, S. lalandi) are

commonly captured from fishing grounds (e.g., Apolo and Pukao seamount) at relatively

shallow depths (150-165 m). High densities of juvenile reef fishes have been reported from

mesophotic reefs (Zapata-Hernandez, pers. obs), and are therefore accessible to pelagic

predators (Bertrand, Bard, & Josse, 2002) providing a route for the assimilation of benthic-

derived carbon as indicated by our mixing model results.

Trophic structure

Estimating consumer trophic position allowed the identification of structural features within

each assemblage. The zooplanktivore groups (mesozooplankton and emergent zooplankton)

showed lower variability in both stable isotope ratios and fed at low trophic positions

(primary consumers). The isotopic metrics suggested a higher trophic packaging and

evenness and reduced isotopic niche (e.g., CD, SDNND and SEAc, respectively) (Layman

et al., 2007). The lower δ15N values from zooplankton in contrast to POM could be due to a

mixture of different phytoplankton-size (pico-, nano- and microplankton) contained in POM-

δ15N values. However, a progressive increment of δ15N-POM values has been observed from

pico- to microfractions, which is associated to differential fractionation during ammonium

and urea uptake (Hunt et al., 2018). However, most POM values available in this study were

taken one year before than mesozooplankton samples, and likely can respond faster to

environmental shift than the zooplankton (O'Reilly, Hecky, Cohen, & Plisnier, 2002).

Reef invertebrates displayed higher variability in δ13C and δ15N values than most taxa

classified as primary and secondary consumers (both TP models). CD and SDNND values

were also higher, indicating a lower level of trophic packaging and evenness, respectively,

and suggesting reduced trophic redundancy between taxa (BrindÁmour & Dubois, 2013).

Moreover, SEAc values confirmed the higher trophic diversity within these assemblages,

likely reflecting the use of multiple carbon sources by invertebrates using different feeding

mechanisms (e.g., filter-feeding, grazing, herbivory, carnivory, deposit-feeding and

detritivory). Preliminary surveys of the study sites suggest that grazing invertebrates (e.g.,

urchin and gastropods) are the most important (in terms of biomass) trophic group during the

day, being replaced by cryptic detritus-feeder such as holothurians and ophiuroids at night.

It is therefore likely that detritus inputs (e.g., of coral mucus) into the food web could be

important during the night (Zapata-Hernández et al., Chapter 3). In contrast, reef fishes

displayed similar patterns in stable isotopes values to reef invertebrates, showing higher

variability in δ13C values and low δ15N values, with most species being classified as

secondary consumers. However, metrics indicated an elevated trophic diversity for these

assemblages (SEAc values). Additionally, considerable overlap in SEAB ellipses indicated

that reef fishes likely share trophic resources with invertebrates (28 %), but only with higher

trophic level invertebrates (i.e., octopuses, sea stars, lobsters, crabs and gastropods) that were

largely nocturnal. This provides a further indication of the existence of a distinct nocturnal

invertebrate assemblage (See previous chapter), which will need further study to better

understand their role in the flow of organic matter through coral reef food webs.

Pelagic fishes had similar δ13C values but varied widely in terms of their δ15N values, with

species comprising the three upper trophic levels. The lower δ15N values corresponded to

pelagic species more closely associated with coastal environments (e.g., H. acutus and D.

muroadsi) that may be important prey for higher trophic level pelagic fishes. The Layman

metrics suggested lower species packaging and trophic evenness; however, the SEAc values

suggested less isotopic diversity within the assemblage compared to reef fishes, likely

indicating that a single (pelagic) carbon source dominated supply (e.g., of small fishes and

squids). In addition, δ15N values (15.9 ± 1.7 ‰, n = 40) and trophic position estimated for

yellowfin tuna T. albacares (mean = 4.7, BCI = 4.3–6.0) were comparable with other

estimates made from South Pacific subtropical region between Fiji and French Polynesia

(mean = 4.6 ± 1.1; Houssard et al., 2017). Stable isotope values of pelagic predators are

influenced by changes in micronekton prey including gelatinous taxa, crustaceans, small

fishes and cephalopods (Young et al., 2015). In this study, nekton was poorly represented,

with only two samples of pelagic squid (δ13C = -18.3 ‰ and δ15N =10.4 ‰, n = 2), even

though they are considered as important nutritional links between lower trophic levels to

large pelagic predators (Young et al., 2015). Therefore, increased efforts are required to fully

characterize the stable isotope composition of micronekton in order to understand the

importance of this assemblage in supporting commercial pelagic fishes in the RNME.

Study limitations and future research

Although this study represents a considerable advance in our understanding of ecological

function of the RNME, it is still a first approach, and future studies are needed which can

build on our work. The use of TDF values from meta-analysis for estimates of consumer

trophic position and contribution of different energy pathways using mixing models are

undoubtedly a simplification of trophic fractionation in a complex system like a coral reef

food web. However, the slightly wide standard deviation values (1.3 ‰) were used to

propagate the uncertainty in TDF values through the mixing models, allowing a range of

likely fractionation values from different sources (Docmac, Araya, Hinojosa, Dorador, &

Harrod, 2016; Phillips et al., 2014). Also, the Bayesian mixing model implemented in

MixSiar incorporated error measures (e.g., residual and process) that were propagated

through the modeling process (Stock & Semmens, 2016). In addition, the absence of some

unsampled trophic sources (e.g., detritus and turf algae) may have affected mixing model

results, since some models were underdetermined and generated bias in the contributions for

putative sources choices (Phillips et al., 2014).

Therefore, future studies should include an increased focus on sampling detritus and more

detailed characterization of pelagic food sources in order to strengthen the estimates from

reef fauna and pelagic predators. Increasing the sampling size in several taxa could also

reduce the uncertainty, improving the estimations from some Bayesian models that resulted

sensitive to low sampling size (e.g., BrindÁmour & Dubois, 2013; Jackson et al., 2011;

Quedaza-Romegialli et al., 2016); therefore, Bayesian models presented in this study need to

be interpreted with caution. Another potential approach is to use amino acid δ13C to identify

the source of carbon fueling consumers (Elliott Smith, Harrod, Newsome, 2018; Larsen

Taylor, Leigh, & O'Brien, 2009) and amino acid δ15N to estimate trophic position

(Chikaraishi et al., 2009).

POM δ13C and δ15N values were not depleted in 13C and 15N relative to zooplankton,

suggesting a breakdown in the generally reliable isotopic shift between consumer

(zooplankton) and prey (POM). This may reflect spatial differences (e.g., zooplankton

feeding on POM from a different pool) or temporal shifts in POM isotope values relative to

the zooplankton. It is well known that phytoplankton can respond rapidly to oceanographic

shifts, while upper trophic levels require longer times to reflect changes in the isotope values

of their food (O'Reilly et al., 2002). Future studies should include POM collected over an

extended period to allow for the identification of isotopic variation.

In order to improve the understanding of the ecology of pelagic predators, it will be necessary

to develop a better understanding on the nutrient dynamics to characterize the isotopic

composition of pelagic food web (e.g., size-fractionated phytoplankton and zooplankton,

micronekton and nekton). The use of isoscape models (Wunder, 2010) and telemetry

(electronic tagging) in vertebrate predator taxa also could improve the knowledge on their

movement patterns (Hobson, Barnett-Johnson, Cerling, 2010), habitat requirements and prey

types (Young et al., 2015), and about the direction and magnitude of nutrient and organic

matter transport between shallow and mesophotic habitats (Papastamatiou, Meyer, Kosaki,

Wallsgrove, & Popp, 2015). Moreover, future studies on the trophic ecology of species and

OM fluxes in RNME could incorporate traditional ecological knowledge (Drew, 2005) from

Rapa Nui fishermen and classical stomach-content analysis to guide mixing models (specify

prior knowledge on food sources) (Nielsen et al., 2017). Also, the implementation of other

approaches as fatty-acids analysis (Wan et al., 2010), compound-specific stable isotopes

(McMahon, Thorrold, Houghton, & Berumen, 2016) and stomach content metabarcoding

(Casey et al., 2019) could increase the resolution on organic matter transference and trophic

relationships.

Implications for marine conservation and resource management

Zooxanthellate coral reefs in Rapa Nui provide habitat and refuge for many different species,

but this study provides the first evidence that it also acts as a critical source of energy and

nutrients that invertebrates and reef fishes can exploit and transfer into upper trophic levels.

Moreover, different larval stages of cryptic fauna (e.g., brachyuran and caridean larvae) that

constitute the emergent zooplankton from Rapa Nui coral reefs, could be a main pathway of

OM transference between pelagic and benthic ecosystem (Casey et al., 2019). The scarce

knowledge about the ecology of invertebrates and fishes, including the role of endemic taxa

(e.g., the cowry Naria englerti, the octopus Octopus rapanui and the slipper lobster

Parribacus perlatus), need to be studied in detail due to their potential role in food webs (as

predator or prey), but also due to their vulnerability to face environmental changes (Polidoro

et al., 2012). In this sense, global (e.g., climate change) and local stressors (e.g., terrestrial

runoff, wastewater management, overfishing and alien species, among others) can act in

synergy to produce important negative effects on coral species (e.g., annual coral bleaching),

shifting community structure (Glynn et al., 2017) and impacting the provision of coastal

marine resources (Förster, McCleod, Bruton-Adams, & Wittmer 2019). Therefore,

conservation efforts need be focused into coral reefs, their cryptic biodiversity, and the

subsequent management plans of new Rapa Nui marine protected area (RN-MPA), including

actions that integrate both marine and terrestrial environments.

The RNME system, unlike many coral reefs, has large amounts of hard coral cover. However,

it has been subject to considerable human impacts, e.g., through the removal of upper trophic

level fishes. It would be very useful to undertake a comparison of the heavily human-

influenced RNME versus the relatively pristine marine ecosystem in Motu Motiro Hiva

(Salas y Gomez Island) (sensu Friedlander et al., 2013) and determinate future targets for the

newly stablished RN-MPA. Finally, this study could be considered as a baseline of

biodiversity, isotopic composition, trophic structure and main C and N pathways from small-

size cryptic organisms to large pelagic predator and seabirds. A permanent isotope-based

monitoring of coral reefs and their biodiversity (i.e., benthic and pelagic) could contribute to

improve insights on temporal dynamics of coral reefs and their impact on ecosystem

functioning, providing adequate guidelines for their conservation and management through

time.

4.6 Acknowledgments

We thank to Ricardo Hito, Petero Hito (Tortuga diving center), Enrique Hey, Mathias Luna, Henry

Garcia (R.I.P.), Michel Garcia (R.I.P.) and Loti Garcia (Orca dive center), Ucko Tongariki, Poki Tane

Haoa, Victor and Tanga Icka for field support. To Consejo del Mar de Rapa Nui and Sergio Rapu of

the Rapanui Heritage Foundation for their permanent support. To Tiare Hereveri for her great

hospitality during field works. To E. Macaya and C. Sandoval providing macroalgae samples. To

Jorge Avilés and Camila Henriquez from Sala de Colecciones Biológicas UCN (SCBUCN) for their

help with the curation of voucher specimens. GZ-H was supported by CONICYT-PCHA/Doctorado

Nacional/2015-21151249 and the Chilean Millennium Initiative ESMOI. Partial support to GZ-H and

JS was provided by FONDECYT 1181153 and 1180694 projects. SC was supported by FONDECYT

11170617 and FONDECYT REDES proyect #180194. CH was supported by Millenium Nucleus of

Invasive Salmonids (INVASAL) funded by Chile's government program, Iniciativa Cientifica

Milenio from the Ministerio de Economia, Fomento y Turismo. EM was supported by Postdoctoral

FONDECYT 3150419 and Comisión Académica de Postgrado (CAP) UdelaR.

Compliance with ethical standards

Conflict of interest: On behalf of both authors, the corresponding author states that there is no

conflict of interest.

Ethical statement: Sampling was performed under permission Res. Ext N°41/2016 from

SERNAPESCA (Chile) to Universidad Católica del Norte and approved by the scientific ethics

committee from Universidad Catolica del Norte, F.M. N°70/2017.

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Chapter 5

GENERAL CONCLUSIONS

Significant changes between day and night were observed in the community structure of coral

reefs in Rapa Nui, with fish being more than two times more abundant during the day, whilst

mobile benthic invertebrates (MBI) density and biomass showed an opposite trend with

higher values at night. Dissimilarity in the assemblage structure between day and night was

important for MBI and reef fishes (60 % and 68 %, respectively), with an important

biodiversity shift (e.g., composition and richness) during both periods, while shifts in their

respective densities were also noted (Chapter 2).

In coral reefs most MBI remain hidden during the day, likely associated with circadian

rhythms as a potential mechanism against the predation risk (Kronfeld-Schor & Dayan 2003).

Although diel activity patterns are assumed to be fixed and unlikely to change in the short

term (Fox & Bellwood 2011), human activity has reduced the abundance of predators (Madin

et al. 2016), relaxing predation risk and extending the activity patterns of nocturnal species

including fishes into daylight hours (Fox & Bellwood 2011, McCauley et al. 2012) and sea

urchins (Muthiga & McClanahan 2007). In this sense, the sea urchins D. savignyi and E.

aciculatus were important during diurnal surveys, even though these species commonly

display nocturnal activity patterns (Tuya et al. 2004). These high abundances of sea urchins

are typically related to sites with intensive fishing pressure and/or with low predator

abundance (Edgar et al. 2011). A turnover among carnivore fishes between day and night

was clearly observed, where labrid fishes (e.g., T. lutescens, P. fuentesi, A. femeninus) were

practically absent during the night and replaced by other carnivorous taxa such as

Sargocentron whilhelmi (nocturnal) and C. litus (likely cathemeral), albeit in low densities

and biomass (Chapter 2 and 3).

In functional terms, herbivorous, planktivorous and carnivorous fishes were more abundant

during the day, but obvious differences in biomass were limited to herbivorous species.

Herbivorous fish likely contribute to the prevention of algal overgrowing (e.g., turf and

macroalgae) on coral reefs, maintaining available space for coral recruitment and providing

resilience (Chung et al. 2019). Therefore, their high abundance and biomass (together with

the sea urchins) could be contributing to current low algal abundances and extensive corals

cover around Rapa Nui. In contrast, the biomass of the nocturnal assemblage was dominated

by zooplanktivorous fishes that can exploit demersal zooplankton (e.g., polychaetes,

crustacean larvae, amphipods, isopods) that emerge during the night from cryptic habitats

within the coral reef matrix, contributing to the capture and recycling of organic matter within

the coral reef ecosystem.

The diurnal MBI assemblage included large contributions from herbivorous, suspension-

feeding and corallivorous taxa, while the nocturnal MBI assemblage was largely comprised

of detritivorous taxa. Similar to herbivorous reef fishes, herbivorous sea urchins may be

important in the maintenance of the coral-dominated phase (Chung et al. 2019) and represent

a prevalent trophic source for fish and invertebrate predators. However, nocturnal

detritivorous taxa have a key role in the transfer of organic matter, nutrients and carbonate

recycling in coral reefs (Schneider et al. 2013), supporting secondary production available to

upper consumers (Hagen et al. 2012). Indeed, is recognized that substantial primary

productivity in coral reefs is processed and recycled through detritus and microbial food webs

(Arias-González et al. 1997), therefore the role of dominant nocturnal detritivore taxa could

be crucial for trophic functioning of coral reef in Rapa Nui (Chapter 3).

Additionally, although nocturnal assemblages had higher densities and biomass, compared

to diurnal assemblages, the isotopic uniqueness index (IUni) indicates that nocturnal MBI

were trophically more redundant, therefore an increase of nocturnal richness does not

necessarily imply an increase in the trophic diversity. This trophic redundancy of nocturnal

MBI could be important for maintaining detritus recycling in coral reefs and eventually

compensating the loss of any species, providing an ecological insurance against biodiversity

loss (Nyström 2006).

I showed a clear pattern of 13C and 15N enrichment from small-sized invertebrates (i.e.,

pelagic and benthic) to reef and pelagic fishes, and seabirds (Chapter 4). Most invertebrates

(i.e., mesozooplankton, emergent zooplankton, macrobenthos, and reef invertebrates) were

classified as primary consumers (except by some predator taxa), reef fishes mainly as

secondary consumers and pelagic fishes and seabirds as tertiary and quaternary consumers.

This pattern reflects the structure of coral reefs food web in Rapa Nui and confirms that

different invertebrate assemblages prevail at lower trophic levels (Glynn & Enochs 2011). In

addition, the wide range in δ13C values in invertebrate assemblages suggest that they exploit

a range of different organic matter pools, transferring energy and nutrients to upper trophic

level consumers such as reef fishes.

Conversely, isotope niche metrics indicated a low trophic diversity for the pelagic

assemblages (mesozooplankton and pelagic fishes), in contrast to reef fauna (invertebrates

and fishes), whose higher trophic diversity suggests the exploitation of a wider range of

trophic resources. In addition, the overlap observed in Bayesian standard ellipses areas

(trophic similarity measure) among reef invertebrates and fishes indicates that some species

within both assemblages could be sharing trophic resources. However, the most invertebrate

species could be key in transferring energy and supporting upper consumers such as reef

fishes.

Bayesian stable isotopes mixing models indicate that coral-derived OM of zooxanthellate

scleractinian corals was the dominant source of energy and nutrients for the different

assemblages (e.g., macrobenthos, reef invertebrates and fishes) making up the Rapa Nui reef

ecosystem. Therefore, scleractinian corals are likely fueling a large component of the reef

fauna and also providing trophic support to adjacent habitats, such as soft-bottoms, via coral

mucus production and detritus recycling (Wild et al. 2004). In contrast, phytoplankton-

derived organic matter was more important for mesozooplankton and some pelagic fishes,

but it made only a very limited contribution to benthic consumers, therefore suggesting that

local primary production in coral reefs could be more important than allochthonous

production (e.g., phytoplankton).

Therefore, conservation efforts should be focused on scleractinian coral species, nocturnal

fauna and endemic species, due to their role as nutritional sources, their importance for

ecosystem functioning and to minimize extinction risk. It is likely that regulation of the local

anthropogenic stressors (e.g., overfishing, terrestrial runoff, wastewater and mass tourism)

that individually, and synergistically threaten the marine biodiversity of Rapa Nui are

required to restore community structure and function of the currently altered coral reef (cf.

Salas y Gomez Islet), thus ensuring its preservation and the maintenance of ecosystem

services for the Rapa Nui people through time.

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7. Annexes

A.1 Appendix 1. Summary of mean and standard deviation (SD) of stable isotopes values (δ13C and δ15N), δ13C’ = lipid-corrected δ13C values,

n=sampling size, and C/N ratio for heterotrophic consumers from RNME.

δ13C (‰)

δ13C´ (‰)

δ15N (‰) C/N


Mesozooplankton

Chaetognatha -19.0 - -19.3 - 2 3.9 0.3 5 3.6-4.3

Epigonichthys maldivensis -20.0 - -20.0 - 1 4.2 1 4.2

Calanoidea copepods -20.8 0.5 -20.6 0.6 7 4.4 0.3 7 4.1-4.8

Caridea crustacean -20.0 0.7 -19.8 0.5 8 4.4 0.3 8 4.0-4.7

Euphausidae -20.1 0.7 -19.8 0.6 8 4.4 0.3 8 3.9-4.9

Siphonophora -19.6 0.4 -18.8 0.7 5 4.8 0.4 5 4.4-5.4

Hydromedusae -21.2 - -20.3 - 1 4.8 - 1 4.8

Polychaeta -21.0 - -20.2 - 1 4.8 - 1 4.8

Stomatopod larvae -22.6 - -21.7 - 1 4.9 - 1 4.9

Sergestidae crustacean -20.5 - -19.6 - 1 5.0 - 1 5.0

Brachyura crustacean -18.0 0.6 -16.8 0.4 4 5.1 0.3 5 4.9-5.3

Cyclopoid copepods -21.2 0.8 -20.0 0.8 5 5.3 0.3 5 5.0-5.7

Mean ± SD -20.3 1.2 -19.7 1.2 4.7 0.4

Emergent zooplankton

Isopoda sp. 1 -20.1 - -19.4 - 2 3.5 2 3.2-4.9

Amphipoda sp. 1 -15.8 1.4 -15.0 1.4 5 4.4 0.3 5 3.8-4.7

Caridea orange larvae -19.9 0.3 -19.1 0.5 4 5.3 0.3 4 3.8-4.8

Cypris larvae -22.7 - -20.7 - 1 5.4 1 5.3

Nereidae -16.9 3.8 -16.2 4.0 16 6.1 0.9 16 3.8-4.6

Brachyura zoea larvae -18.6 0.4 -17.3 0.4 4 6.8 0.7 4 4.2-4.9

Amphipoda sp. 2 -18.3 - -17.3 - 1 12.2 1 4.3

Mean ± SD -18.9 2.26 -17.9 2.0 6.3 2.8

Macrobenthos

Syllidae sp. -16.2 1.5 -15.3 1.9 13 5.7 1.4 13 2.3-4.7

Nematoda sp. -18.9 0.7 -18.0 0.4 3 7.1 1.2 3 3.9-4.6

Polychaeta indet -17.2 - -16.5 - 1 7.4 - 1 3.8-4.1

Amphioxus sp. -20.5 - - - 1 7.6 - 1 3.4

Lumbrineridae sp. -16.1 1.1 -15.5 1.0 3 7.6 0.5 3 3.9-4.0

Glyceridae sp. -17.6 0.5 -17.2 0.3 3 8.4 1.0 3 3.5-4.0

Polynoidae sp. -16.7 0.3 -16.6 0.1 3 9.1 0.6 3 3.4-3.8

Polychaeta sp. 2 -16.6 - -15.5 - 1 10.5 - 1 4.5

Mean ± SD -17.5 1.5 -16.9 1.7 7.9 1.4

δ13C (‰)

δ13C´ (‰)

δ15N (‰) C/N


Reef invertebrates

Echinostrephus aciculatus -16.8 1.5 -12.6 1.9 4 4.1 1.5 8 6.8-8.1

Ascidian sp. -19.1 - -17.3 - 1 4.3 - 1 5.2

Asteropus sp. -18.9 - -17.8 - 1 4.8 - 1 4.5

Tripneustes gratilla -13.6 1.4 -12.2 1.6 7 4.8 1.6 6 4.4-5.0

Ascidian sp. (orange) -19.1 - -11.1 - 1 5.3 - 1 11.4

Diadema savignyi -17.7 2.6 -15.3 3.1 7 5.5 0.5 7 4.6-10.1

Carpilus convexus -18.4 - -18.0 - 1 5.7 - 1 3.7-4.0

Holothuria cinerascens -14.7 0.9 -13.5 0.6 6 5.8 1.8 6 3.7-6.7

Porifera sp. (brown) -18.3 - -15.6 - 1 5.9 - 1 6.0

Holothuria difficilis -15.8 1.0 -14.1 1.4 12 6.5 1.4 12 2.6-6.0

Tedania sp. -18.0 1.8 -14.3 2.6 5 6.7 0.8 7 5.0-19.0

Cribrocalina dura -19.0 - -17.1 - 2 6.7 - 2 4.9-5.5

Holothuria nobilis -13.6 - -13.1 - 2 6.9 - 2 3.7-4.0

Calcinus pascuensis -17.0 1.4 -15.1 1.8 10 7.2 2.0 11 3.8-7.5

Stichopus monotuberculatus -15.5 0.8 -14.8 1.2 4 7.2 1.2 5 4.1-4.5

Coraliophylla violacea -14.7 0.4 -14.0 0.5 8 7.4 0.9 8 3.7-4.7

Lissodiadema lorioli -19.5 - -16.6 - 1 8.1 - 1 6.3

Breviturma dentata -16.2 - -12.3 - 2 8.3 2.2 4 3.9-10.5

Naria englerti -19.0 0.4 -17.9 0.3 6 8.4 0.4 6 4.1-4.7

Ophidiaster easterensis -15.0 1.4 -13.9 1.2 4 8.5 0.2 4 17.9

Polyplectana kefersteinii -14.8 0.5 -14.0 0.8 4 8.8 1.1 5 0.1-4.6

Calcinus imperialis -14.1 - -13.5 - 1 8.8 - 2 3.5-3.9

Pascula citrica -15.5 0.6 -14.7 0.9 4 8.9 0.8 4 3.8-4.6

Nodochila pascua -15.7 - -12.9 - 1 8.9 - 1 6.2

Monetaria caputdraconis -19.6 - -18.4 - 1 9.1 - 1 4.4-4.7

Callistoctopus rapanui -15.4 0.9 - - 3 9.6 0.2 3 -

Parribacus perlatus -13.0 1.72 -12.7 1.422 7 9.8 1.262 8 3.1-4.3

Cinetorhynchus sp. -16.7 - -16.0 - 1 10.1 - 1 4.1

Conus miliaris -14.9 0.7 -13.9 0.6 3 10.5 1.2 3 4.1-4.6

Trapezia punctimanus -17.4 - -16.6 - 1 10.5 - 1 4.1

Astrotole paschae -14.0 - -13.2 - 2 10.8 0.3 3 3.8-4.5

Panulirus pascuensis -16.1 - -15.0 - 1 11.4 - 1 4.4

Liomera sp. -16.6 - -15.8 - 1 11.6 - 1 4.1

Pelagic squid -18.3 - - - 2 10.4 2 -

Mean ± SD -16.5 2.0 -14.8 1.9 7.8 2.1

δ13C (‰)

δ13C´ (‰)

δ15N (‰) C/N


Reef fishes

Acanthurus leucopareius -13.8 2.1 -10.9 2.0 4 8.4 1.3 4 3.8-3.9

Blenidae sp. -17.5 - - - - 9.2 - 1 -

Kuhlia nutabunda -16.5 1.2 -14.2 0.2 5 10.7 0.1 5 3.6-4.1

Cantherhines rapanui -16.9 - -14.1 - 2 10.9 - 2 3.8-4.0

Aseraggodes bahamondei -14.7 - -12.0 - 2 11.0 - 2 4.1-4.2

Thalassoma purpureum -13.6 1.3 -10.8 1.2 3 11.1 0.5 3 4.0-4.2

Trachypoma macracanthus -15.4 - -12.6 - 1 11.3 - 1 3.8

Goniistius plessisi -13.1 - -10.3 - 2 11.4 - 2 4.0-4.2

Aulostomus chinensis -17.7 - -14.8 - 1 11.6 - 1 3.7

Thalassoma lutescens -13.3 0.5 -10.6 0.5 3 11.7 2.3 3 4.0-4.5

Cookeolus japonicus -19.7 2.3 -17.1 2.5 4 11.8 4.8 4 3.7-5.2

Forcipiger flavissimus -14.2 -11.5 - 1 11.9 - 1 4.2

Gymnothorax bathyphIlus -18.6 - -18.6 - 2 12.0 - 2 2.8-3.3

Pseudolabrus fuentesi -15.9 - -13.2 - 2 12.0 - 2 4.1-4.2

Apogon rubrifuscus -17.6 - -14.7 - 1 12.1 - 1 3.7

Itycirrhitus wilhelmi -16.5 - -13.6 - 1 12.5 - 1 3.7

heteropriacanthus cruentatus -18.2 - - - 1 12.6 - 1 3.5

Synodussp. -18.4 - -15.6 - 1 12.8 - 1 4.0

Kyphosus sandwicensis -16.2 1.5 -13.8 1.6 12 12.8 2.1 12 3.7-5.1

Acanthistius fuscus -13.5 - -11.0 1.0 2 12.8 0.3 3 3.7-6.0

Sargocentron wilhelmi -16.1 - -13.1 - 1 12.9 - 1 3.6

Myripristis tiki -17.4 - -14.4 - 1 13.3 - 1 3.6

Sphoeroides pachygaster -17.7 - -14.8 - 2 14.9 - 2 3.7

Pseudocaranx dentex -17.2 1.4 -14.5 1.5 18 13.7 1.7 20 3.7-6.6

Mean ± SD -16.2 1.9 -13.8 2.4 11.9 1.4

Pelagic fishes

Decapterus muroadsi -17.8 0.2 -15.6 1.3 4 12.0 0.7 4 3.4-3.7

Hyporhamphus acutus -16.5 - -13.7 - 1 12.1 - 1 3.6-3.9

Schedophilus velaini -18.3 0.9 -15.9 0.6 5 12.3 2.5 5 3.0-4.0

Seriola lalandi -18.1 0.3 -16.1 1.5 4 14.1 2.5 4 33-6.1

Seriolella sp. -17.8 0.3 -15.0 0.3 3 15.1 0.5 3 3.9-4.0

Tetrapturus audax -17.3 0.4 -14.8 0.6 5 15.7 1.3 5 4.0-5.8

Thunnus albacares -18.6 1.8 -16.0 1.9 37 15.9 1.7 40 3.6-7.5

Katsuwonus pelamis -18.4 1.3 -15.8 1.7 19 15.9 1.6 19 3.9-11.9

Acanthocybium solandri -17.8 1.0 -15.3 1.5 29 16.2 1.3 28 3.7-10.4

Thyrsites atun -18.2 1.1 -15.5 1.5 7 16.2 0.8 7 3.6-7.8

Cheilopogon rapanouiensis -17.9 0.6 -15.2 0.7 7 16.4 1.3 7 3.8-4.9

Coryphaena hippurus -17.8 0.9 -15.1 1.1 7 17.5 0.9 7 3.9-5.9

Mean ± SD -17.9 0.5 -15.3 0.7 15.0 1.9

Seabirds

Pterodroma nigripennis -16.3 0.5 - - 7 15.2 1.5 7 1.0-1.2

Pterodroma neglecta -15.8 0.6 - - 15 15.5 3.0 15 0.6-1.4

Pterodroma ultima -17.6 1.6 - - 7 16.1 2.5 7 0.7-1.4

Pterodroma sp. -16.0 1.0 - - 18 16.5 2.6 18 0.7-1.3

Pterodroma atrata -15.8 0.3 - - 10 16.6 2.3 10 0.8-1.2

Pterodroma heraldica -15.6 0.7 - - 29 19.1 4.1 29 0.6-2.9

Pterodroma alba -15.4 0.5 - - 5 19.2 3.3 5 0.7-1.0

Puffinus nativitatis -17.4 2.8 - - 9 15.3 1.7 9 -

Mean ± SD -16.2 0.8 16.7 1.6

A.2 Appendix 2. Summary of outputs from trophic positions model “oneBaseline” and dietary relative contribution estimated from Bayesian mixing

models (MixSiar). Mode and mean values and 95% Bayesian confidence interval (95 % BCI) are presented. Bold number indicate maximum

contributions estimated by mixing models.

Output Mixing

models

TP Macroalgae Phytoplankton Corals

Taxon Mode 95 % BCI Mean 95 % BCI Mean 95 % BCI Mean 95 % BCI

Mesozooplankton

Chaetognatha 2.8 2.0-7.5 - - - - - - **

Epigonichthys maldivensis 2.4 2.0-9.4 - - - - - - **

Calanoidea copepods 2.3 2.0-2.7 22 0.3-43.7 47 0.5-67.8 31 8.3-46.5 +

Caridea crustacean 2.2 2.0-2.6 - - - - - - **

Euphausidae 2.4 2.0-2.8 18 0.3-85.2 45 0.4-64.9 37 12.1-52.5 +

Siphonophora 2.4 2.0-3.0 14 0.3-70.3 36 0.4-52.8 51 4.8-70.5 +

Hydromedusae 2.7 2.0-9.4 23 0.4-87.9 46 0.6-76.5 31 6.9-55.8 +

Polychaeta sp. 2.3 2.0-9.4 22 0.3-86.9 45 0.5-74.7 33 1.1-76.8 +

Stomatopod larvae 3.5 2.0-9.4 - - - - - - **

Sergestidae crustacean 2.5 2.0-9.4 22 0.3-81.1 39 0.5-67.1 39 12.1-64.4 +

Brachyura crustacean 2.1 2.0-2.9 13 0.8-43.7 20 1.2-33.2 67 50.1-79.5 +

Cyclopoidea copepods 2.5 2.0-3.0 32 0.7-85.6 41 1.9-61.8 27 7.3-44.6 +

Mean±SD 2.5 0.4 21 6.0 40 8.9 39 13.3

Emergent zooplankton

Isopoda sp. 1 2.2 2.0-9.0 - - - - - - **

Amphipoda sp. 1 2.0 2.0-3.5 - - - - - - **

Caridea orange larvae 2.0 2.0-3.4 60 2.4-98.2 18 0.1-69.3 22 0.6-80.3 +

Cypris larvae 2.9 2.0-9.4 56 4.6-92.8 18 0.4-61.3 26 2.4-72.3 +

Nereidae 2.0 2.0-2.3 68 2.8-97.8 10 0.2-39.3 23 0.6-76.7 +

Brachyura zoea larvae 2.0 2.0-3.0 40 2.9-88.6 16 0.3-44.2 44 2.6-80.5 +

Amphipoda sp. 2 3.6 2.0-9.4 31 1.1-79.6 33 2.0-71.8 36 2.5-77.6 +

Mean±SD 2.4 0.6 51 14.9 19 8.6 30 9.5

Macrobenthos

Syllidae sp. 2.0 2.0-2.4 23 0.5-69.1 6 0.2-19.8 71 27.9-94.1 +

Nematoda sp. 2.1 2.0-4.9 31 2.2-73.8 26 2.6-57.4 43 8.0-72.6 +

Polychaeta indet 2.3 2.0-9.4 31 0.5-87.2 10 0.2-35.2 59 7.4-94.4 +

Amphioxus indet. 2.3 2.0-9.3 35 1.3-73.6 16 0.4-50.9 50 21.6-85.5 +

Lumbrineridae sp. 1 2.1 2.0-3.3 21 0.4-71.6 6 0.1-20.1 74 23.4-96.3 +

Glyceridae sp. 2.3 2.0-4.0 29 0.8-80.2 15 0.2-37.6 56 14.6-86.8 +

Polynoidae sp. 2.6 2.0-3.7 23 0.6-73.8 10 0.2-29.8 67 21.0-93.1 +

Polychaeta sp. 2 3.1 2.0-9.3 33 1.5-81.0 21 1.1-54.7 46 3.8-87.0 +

Mean±SD 2.4 0.4 28 5.3 14 7.1 58 11.5

Output Mixing

models



Reef invertebrates

Echinostrephus aciculatus 2.1 2.0-5.2 - - - - - - **

Ascidian sp. 2.6 2.0-9.3 - - - - - - **

Asteropus sp. 2.5 2.0-9.3 24 1.9-58.6 6 1.0-16.2 69 36.7-91.6 +

Tripneustes gratilla 2.0 2.0-3.2 - - - - - - **

Ascidian sp. (orange) 2.4 2.0-9.4 - - - - - - **

Diadema savignyi 2.0 2.0-2.5 51 0.9-91.7 6 0.2-19.8 44 5.3-95.4 +

Carpilus convexus 2.5 2.0-9.4 39 0.9-89.8 10 0.3-37.1 50 6.8-94.5 +

Holothuria cinerascens 2.0 2.0-3.0 19 0.5-75.9 4 0.2-14.0 78 20.0-98.2 +

Porifera sp. (brown) 2.5 2.0-9.4 24 0.6-81.6 5 0.2-18.1 72 13.9-97.9 +

Holothuria difficilis 2.0 2.0-2.3 22 0.6-74.6 4 0.2-12.7 74 23.1-97.8 +

Tedania tepitootehenuaensis 2.0 2.0-2.6 37 0.9-83.8 7 0.3-23.9 56 11.6-95.0 +

Cribrocalina dura 2.0 2.0-2.4 33 1.0-82.0 10 0.3-30.9 57 13.4-93.4 +

Holothuria nobilis 2.1 2.0-8.4 - - - - - - **

Calcinus pascuensis 2.1 2.0-2.6 26 1.2-70.9 9 0.4-23.0 66 23.8-92.5 +

Stichopus monotuberculatus 2.0 2.0-2.8 16 0.6-51.3 4 0.2-14.7 80 44.9-97.9 +

Coraliophylla violacea 2.0 - 20 0.5-74.2 4 0.2-15.9 76 20.1-98.0 +

Lissodiadema lorioli 2.3 2.0-9.3 26 0.8-77.1 8 0.3-28.0 66 17.0-96.8 +

Breviturma dentata 2.6 2.0-8.2 - - - - - - **

Naria englerti 2.3 20-2.6 22 1.6-60.4 27 2.0-51.5 51 28.3-68.8 +

Ophidiaster easterensis 2.3 2.0-2.7 17 0.4-72.1 4 0.2-164 78 23.5-98 +

Polyplectana kefersteinii 2.4 2.0-3.3 - - - - - - **

Calcinus imperialis 2.7 2.0-9.4 - - - - - - **

Pascula citrica 2.5 2.0-3.2 8 0.4-28.6 3 0.1-9.3 89 68.8-98.8 +

Nodochila pascua 2.5 2.0-9.3 - - - - - - **

Monetaria caputdraconis 2.6 2.0-9.3 35 1.1-85.2 18 0.3-48.6 47 9.9-91.6 +

Octopus rapanui 2.8 2.2-3.5 16 0.5-58.7 6 0.2-19.8 79 37.8-97.6 +

Parribacus perlatus 2.8 2.3-3.5 - - - - - - **

Cinetorhynchus sp. 2.9 2.0-9.3 18 0.6-74.5 6 0.2-22.7 76 21.5-97.7 +

Conus miliaris 3.0 2.0-4.8 9 0.3-44.5 5 0.3-18.3 85 48.4-98.3 +

Trapezia punctimanus 3.0 2.0-9.4 28 0.6-79.3 20 0.6-47.0 52 11.6-89.2 +

Astrotole paschae 3.2 2.0-7.4 19 1.3-55.3 13 1.4-31.0 68 31.1-88.3 +

Panulirus pascuensis 3.4 2.0-9.3 17 0.4-66.1 11 0.4-34.7 72 3.9-87.7 +

Liomera sp. 3.5 2.0-9.4 21 0.5-76.1 15 0.6-40.8 64 19.6-96.3 +

Pelagic squid 3.0 2.0-6.5 32 0.6-84.8 36 0.9-66.0 32 7.1-63.2 +

Mean±SD 2.5 0.4 24 9.9 9 6.0 67 12.7

Output Mixing

models



Reef fishes

Acanthurus leucopareius 2.3 2.0-3.3 - - - - - - **

Blenidae sp. 2.7 2.0-9.3 33 1.3-82.9 26 0.9-64.8 41 2.9-83.8 +

Kuhlia nutabunda 3.2 2.7-3.8 11 0.1-42.2 8 0.6-20.0 82 51.2-97.5 +

Cantherhines rapanui 3.2 2.0-7.7 10 0.1-50.9 8 0.5-22.3 82 41.9-98.0 +

Aseraggodes bahamondei 3.2 2.0-6.2 - - - - - - **

Thalassoma purpureum 3.2 2.2-4.3 - - - - - - **

Trachypoma macracanthus 3.4 2.0-9.3 - - - - - - **

Goniistius plessisi 3.3 2.0-6.9 - - - - - - **

Aulostomus chinensis 3.4 2.0-9.3 11 0.1-54.9 13 0.7-34.5 75 3.1-86.8 +

Thalassoma lutescens 3.4 2.0-6.4 - - - - - - **

Cookeolus japonicus 3.5 2.0-6.5 14 0.1-67.5 29 1.1-56.3 57 17.9-91.6 +

Forcipiger flavissimus 3.5 2.0-9.3 - - - - - - **

Gymnothorax bathyphilus 3.5 2.0-8.4 15 0.2-79.4 50 2.1-73.7 35 9.0-58.7 +

Pseudolabrus fuentesi 3.6 2.0-7.6 10 0.1-50.8 10 0.6-29.3 80 38.4-97.8 +

Apogon rubrifuscus 3.7 2.0-9.3 11 0.3-46.0 17 2.5-33.6 73 41.3-90.1 +

Itycirrhitus wilhelmi 3.8 2.0-9.3 9 0.1-54.8 9 0.5-26.0 83 37.5-98.4 +

heteropriacanthus cruentatus 3.9 2.0-9.3 15 0.1-75.1 43 1.7-73.7 42 11.7-80.9 +

Synodussp. 4.0 2.0-9.3 - - - - - - **

Kyphosus sandwicensis 3.8 3.2-4.8 8 0.1-41.8 9 0.8-22.0 83 53.6-97.1 +

Acanthistius fuscus 3.9 2.0-7.4 - - - - - - **

Sargocentron wilhelmi 3.9 2.0-9.3 - - - - - - **

Myripristis tiki 4.0 2.0-9.4 28 1.8-71.9 19 1.2-46.7 53 17.8-83.2 +

Sphoeroides pachygaster 4.5 2.0-8.2 25 0.7-83.1 17 0.5-44.8 58 9.8-92.1 +

Pseudocaranx dentex 4.2 3.6-5.0 30 1.1-72.6 16 0.6-34.5 54 22.6-76.3 +

Mean±SD 3.5 0.5 16 8.7 19 13.1 64 17.4

Pelagic fishes

Decapterus muroadsi 3.6 2.8-4.5 24 1.1-66.9 25 1.6-61.0 51 10.2-82.4 +

Hyporhamphus acutus 3.9 2.0-9.3 - - - - - - **

Schedophilus velaini 3.6 2.4-5.3 27 1.5-66.1 22 2.8-48.8 51 18.6-73.0 +

Seriola lalandi 4.3 2.6-6.5 31 1.9-75.8 39 5.3-74.0 31 2.5-65.7 +

Seriolella sp. 4.6 3.4-6.3 26 1.3-65.1 28 3.6-62.6 47 9.8-74.7 +

Tetrapturus audax 4.8 3.9-6.2 26 1.2-68.3 24 2.2-55.7 50 13.3-76.8 +

Thunnus albacares 4.9 4.3-6.0 13 0.4-43.4 41 24.4-53.5 47 26.1-61.0 +

Katsuwonus pelamis 4.9 4.1-5.9 15 0.6-51.5 41 20.7-57.8 44 18.7-61.5 +

Acanthocybium solandri 5.0 4.3-6.2 33 2.8-72.5 38 15.1-55.6 29 5.8-48.1 +

Thyrsites atun 4.9 4.3-6.2 25 1.1-68.9 37 5.2-74.4 38 4.7-72.4 +

Cheilopogon rapanouiensis 5.1 4.3-6.4 30 2.0-72.5 40 2.0-60.2 30 6.0-50.3 +

Coryphaena hippurus 5.4 4.6-6.6 22 1.2-61.1 44 18.2-64.3 35 9.9-55.4 +

Mean±SD 4.6 0.6 24 6.1 34 7.8 41 8.8

Seabirds

Pterodroma nigripennis 4.0 3.5-4.7 - - - -

Pterodroma neglecta 4.1 3.6-4.8 - - - -

Pterodroma ultima 4.3 3.6-5.2 - - - -

Pterodroma sp. 4.4 3.8-5.1 - - - -

Pterodroma atrata 4.4 3.8-5.2 - - - -

Pterodroma heraldica 5.1 4.4-5.8 - - - -

Pterodroma alba 5.1 3.6-6.6 - - - -

Puffinus nativitatis 4.1 3.5-4.7 - - - -

Mean±SD 4.4 0.4

+: Indicate that consumers selected fall inside of mixture polygon simulated for food sources and that it has mathematical solution. **: Denote

undeterminated models where individuals fall outside of mixture polygon simulated