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Progress and Direction in the Use of Stable Isotopes to Understand Complex Coral Reef Ecosystems: A Review



Coral reef ecosystems are exceptionally complex with a myriad of trophic pathways and consumer relationships. The application of stable isotopes (SIs) offers numerous advantages over traditional methods towards understanding these intricate systems. We summarize current knowledge derived from the rapidly increasing SI literature base and identify potential gaps and future directions for the use of SI in coral reef ecosystem studies. Using topic modelling, a form of text mining, on 236 identified published works, we determined that SI research on coral reefs broadly falls into five major topics. 1) Organic matter dynamics: SI analyses (SIA) have quantified substantial variability in autochthonous (internal) and allochthonous (external) fluxes across coral reefs. 2) Holobiont metabolism: Coral nutrient acquisition, translocation and partitioning, and coral responses to various endogenous and exogenous factors, have been explored through SIA. 3) Trophic niches: SIA has indicated that considerable variation in resource use facilitates co-occurrence of high densities of consumers, emphasising that many trophic categorisations on reefs are often too simplistic. 4) Fish diet variation and habitat connectivity: SIA has revealed how ontogenetic, larval, and mobile predator movements link adjacent ecosystems. 5) Environmental drivers (both natural and anthropogenic): SIA can track anthropogenic nutrient inputs, revealing impacts of human-derived pollutants on reef systems. There are a number of important knowledge gaps however. Few studies compare feeding strategies across guilds and the literature is biased towards reef fish and hard corals. Furthermore, few studies examine multiple taxonomic groups in situ or consider multiple environmental drivers. Studies also tend to ignore the underlying, but potentially substantial, spatiotemporal variation in SI baselines as demonstrated from 741 mean SI values extracted from the literature, making inferences based on small variations in SI values problematic. Given that coral reefs face global decline, knowledge gaps need to be addressed while acknowledging the limitations of SIA; careful application of SIs can enhance understanding of processes driving environmental change in these iconic marine ecosystems.
Oceanography and Marine Biology: An Annual Review, 2022, 60, 373-432
© S. J. Hawkins, A. J. Lemasson, A. L. Allcock, A. E. Bates, M. Byrne, A. J. Evans, L. B. Firth, C. H. Lucas,
E. M. Marzinelli, P. J. Mumby, B. D. Russell, J. Sharples, I. P. Smith, S. E. Swearer, and P. A. Todd, Editors
Taylor & Francis
C. SKINNER1, M. R. D. COBAIN2,3, Y. ZHU2,4, A. S. J. WYATT1, & N. V. C. POLUNIN2
1Department of Ocean Science and Hong Kong Branch of the Southern Marine
Science and Engineering, Guangdong Laboratory (Guangzhou), The Hong
Kong University of Science and Technology, Kowloon, Hong Kong.
2School of Natural and Environmental Sciences, Newcastle
University, Newcastle upon Tyne, NE1 7RU, UK.
3School of Natural Sciences, Trinity College Dublin, The University of Dublin, Dublin 2, Ireland.
4Institute of Marine Research, NO-5005 Bergen, Norway
Abstract Coral reef ecosystems are exceptionally complex with a myriad of trophic pathways
and consumer relationships. The application of stable isotopes (SIs) offers numerous advantages
over traditional methods towards understanding these intricate systems. We summarise current
knowledge derived from the rapidly increasing SI literature base and identify potential gaps and
future directions for the use of SIs in coral reef ecosystem studies. Using topic modelling, a form
of text mining, on 236 identied published works, we determined that SI research on coral reefs
broadly falls into ve major topics. (1) Organic matter dynamics: SI analyses (SIA) have quanti-
ed substantial variability in autochthonous (internal) and allochthonous (external) uxes across
coral reefs. (2) Holobiont metabolism: Coral nutrient acquisition, translocation and partitioning,
and coral responses to various endogenous and exogenous factors have been explored through SIA.
(3) Trophic niches: SIA has indicated that considerable variation in resource use facilitates co-
occurrence of high densities of consumers, emphasising that many trophic categorisations on reefs
are often too simplistic. (4) Fish diet variation and habitat connectivity: SIA has revealed how
ontogenetic, larval and mobile predator movements link adjacent ecosystems. (5) Environmental
drivers (both natural and anthropogenic): SIA can track anthropogenic nutrient inputs, revealing
impacts of human-derived pollutants on reef systems. There are a number of important knowledge
gaps, however. Few studies compare feeding strategies across guilds, and the literature is biased
towards reef sh and hard corals. Furthermore, few studies examine multiple taxonomic groups
in situ or consider multiple environmental drivers. Studies also tend to ignore the underlying, but
potentially substantial, spatiotemporal variation in SI baselines as demonstrated from 741 mean
SI values extracted from the literature, making inferences based on small variations in SI values
problematic. Given that coral reefs face global decline, knowledge gaps need to be addressed while
acknowledging the limitations of SIA; careful application of SIs can enhance the understanding of
processes driving environmental change in these iconic marine ecosystems.
Keywords: stable isotope analysis; food webs; organic matter; holobiont metabolism; trophic
niches; sh diet; habitat connectivity; environmental drivers
DOI: 10.1201/9781003288602-8
Knowledge of the energy uxes and networks of consumer relationships that constitute whole
ecosystems has long been considered crucial to understanding their structure (e.g. Lindeman 1942,
Teal 1962), functioning (e.g. Patten 1959, Slobodkin 1959, Ulanowicz 1972, Bellwood et al. 2019)
and sustainable use (e.g. Ryther 1969, Friedland et al. 2012, Link & Watson 2019). This is par-
ticularly challenging where the range of sources, diversity of consumers, and number of trophic
levels are large (Link 2002). The high species diversity of coral reefs, therefore, presents a huge
obstacle to any attempt to understand the ecosystem, especially as the ecologies of the majority of
species are known only from short bursts of research activity at particular locations and points in
time (e.g. Odum & Odum 1955, Hiatt & Strasburg 1960, Randall 1967, Vivien 1973, Hobson 1974,
Harmelin-Vivien 1981, Sano et al. 1984). This creates great uncertainty in understanding coral reef
Ecosystem function relies on the movement and storage of energy and nutrients. As such, the
exceptional productivity and biodiversity of coral reef ecosystems in mostly oligotrophic tropical
surface waters has long been considered a paradox (Darwin 1842). The array of potential path-
ways sustaining these iconic ecosystems are only now being explored in the detail that their pres-
ent plight demands – there is a plethora of threats to coral reefs, including multiple consequences
of climate change (Hughes et al. 2003, Graham et al. 2011, Hoegh-Guldberg et al. 2017, Hughes
et al. 2017) and impacts of shery exploitation (Newton et al. 2007, MacNeil et al. 2015, Bozec
et al. 2016).
Coral reef primary production sources (all bold words appear in the glossary, Table 1) can
include algae, phytoplankton, various sponges and cnidarians which are partially photosynthetic
or chemosynthetic, and suspended and sedimentary particulate and dissolved organic materials
derived from these. The nature of these sources is complex, so characterising consumer relation-
ships is non-trivial. For example, the macroalgal matrix that nominally herbivorous sh feed on
may also include microbes, detritus and animal material (Wilson & Bellwood 1997). Many herbi-
vores may also feed opportunistically on the faeces of zooplanktivorous shes (Robertson 1982).
Corallivores and spongivores, which include nominal herbivores (e.g. Burkepile et al. 2019), actu-
ally ingest material of mixotrophic origin. This is because the coral or sponge holobiont is com-
posed of not only the host animal tissue, but also symbiotic dinoagellates (often from the clade
Symbiodiniaceae) and other potential prokaryotic symbionts, hereafter referred to as ‘endosymbi-
onts’. Marine symbioses such as these are particularly common in nutrient-poor environments such
as coral reefs (Ferrier-Pagès & Leal 2019) and present another layer of complexity in understand-
ing these ecosystems. Zooplankton have long been considered an important resource for reefs,
but assessing their role is complicated by the fact that pelagic plankton are continuously advected
over reefs, in conjunction with distinct reef plankton living amongst the reef substrata, with some
only emerging at night (Hobson 1974). Free-living bacteria also represent an important resource
in coral reefs. They experience high rates of growth and production through feeding on abundant
dissolved organic matter, providing a food source to higher trophic level consumers including
zooplankton and corals, thereby transferring energy and contributing to reef productivity (Sorokin
1973a,b, Sorokin et al. 1985, Ferrier-Pagès & Gattuso 1998). While detritus constitutes an impor-
tant ux (e.g. Crossman et al. 2005), the origins and lability of the materials involved are diverse
and little studied.
Even at this low level, understanding these diverse and complex relationships is hedged with uncer-
tainty. Traditionally, tools used to tackle these knowledge gaps have included in situ behavioural and
stomach contents analyses, mass-balanced modelling, genetics, and ‘omics’ methods (i.e. proteomics
and metabolomics). Feeding observations offer considerable resolution in some aspects of a con-
sumer’s diet, but, without costly extension, provide data over only small temporal and spatial scales.
They also generally do not allow quantication of some hard to observe, but signicant dietary
components such as microbes and plankton, and they may provide only a modest measure of what
is assimilated into consumer tissues. Additionally, for interactions among marine symbioses, it is
not possible to track nutrient exchanges visually. For modelling approaches, the scope is vast but
severely constrained by the accuracy of parameterisation and key assumptions, such as the rate of
primary production and trophic transfer efciencies (e.g. Polovina 1984, Polunin & Klumpp 1990,
Arias-González et al. 1997). While ‘omics’ methods are important for disentangling metabolic rela-
tionships in marine symbioses, they cannot trace nutrient exchanges or identify original sources well
(Ferrier-Pagès & Leal 2019).
Although coral reef ecosystem functioning has been considered since the early 1800s (Darwin
1842), stable isotope (SI) approaches (see Text box 1) are a relatively recent addition to this endeav-
our, having only been applied readily since the early 1980s (e.g. Fry et al. 1982), although there are
some examples of earlier works (Stephens 1960, Sorokin 1973a, Goreau 1977). These approaches
Table 1 Glossary of the key terms used throughout the review. Terms appear in bold in the
Term Notes/explanation
Allochthonous/external sources Production sources that originate from places other than where they are found.
Autochthonous/internal sources Production sources that originate from where they are found.
Autotrophy The process through which an organism can synthesize its own food from inorganic
substances (e.g. photosynthesis).
Baseline The isotope baseline refers to the isotope ratios at the base of the food web, such as in
nutrients (e.g. nitrate, dissolved inorganic carbon) and xed organic matter (e.g. detritus,
primary producers) sources, which can vary sustainably with space and time over reefs.
Bulk stable isotope analysis (SIA) Measuring the SI values in a whole tissue (e.g. liver or muscle) or body (e.g. very
small organisms), see Text box 1.
Compound-specic SIA (CSIA) Measuring the SI values of individual biochemical compounds (e.g. fatty acids or
amino acids) within a tissue type, see Text box 1.
Connectivity The degree of movement and trophic interactions between different food web biota or
between different food web compartments, whether within or between ecosystems.
Diet-tissue discrimination factor Hereafter ‘trophic discrimination factor’ (TDF): change in relative abundances of the
stable isotopes of an element between diet and a consumer’s tissue, due to the
kinetics of the various metabolic and physiological processes that occur during
digestion and assimilation. Other synonyms may include fractionation factor (FF) or
trophic enrichment factor (TEF).
Heterotrophy The process through which an organism acquires external organic substances for nutrition.
Holobiont The assemblage of a host and the organisms living within or around it in symbiosis
(e.g. hard coral and Symbiodiniaceae).
Isotopic niche An area or volume (in δ-space) with isotopic values (δ-values) as coordinates
(Newsome et al. 2007).
Mixotrophy When an organism uses a mix of newly xed in situ and secondary production source
types for nutrition (e.g. may have photosynthetic symbionts, but also captures particles).
Production source The basal organic inputs sustaining a food web, formed from either primary (photo- or
chemosynthetic) xation of inorganic nutrients or secondary xation of recycled,
organic materials.
Trophic niche The various ecological aspects relating to energetic acquisition of the full array of food
items consumed by an organism and the strategies used to acquire them.
Trophic position (TP) The vertical position of an organism in the food web, akin to trophic level with the
exception that it need not be an integer value due to complex linkages within a food web.
fall into two categories: (1) measuring natural abundances of stable isotopes in a sample and (2) trac-
ing the articial addition of heavier isotopes through a system of interest, known as isotope labelling.
SI approaches have many strengths (Text box 1; Fry 2006). SI compositions are time-integrated, so
potentially represent material assimilation by consumers over timescales of days to months, whereas
behavioural and gut contents analyses capture at most hours to days. SI ratios in a consumer’s tissues
also contain information about what has been assimilated from the diet, not merely ingested. This
means the nutritional role of a particular source can be claried rather than having to be assumed.
This extends to quantifying the importance of materials such as gelatinous plankton and dissolved
organic matter, which may be estimated poorly, or not at all, via traditional gut contents analyses.
This also extends to primary producers, with tissue SIs relating to the nutrients taken up for xation
along with the xation pathway itself. SI analyses (SIA) offer ways of tracking distinct production
sources and testing ideas about how the importance of different pathways may vary in space and
time, or in relation to other factors such as body size. SI ratios can provide a chemical proxy of
trophic position (TP) and a means of estimating trophic niche widths and volumes, providing an
opportunity to test ideas about overlaps in these parameters. Because of their snapshot character,
gut contents analyses tend to require much larger sample sizes than those needed for SIA, while
SI data can be derived from non-lethal sampling. Inherent in each of these strengths are important
constraints, however. This includes those of the isotope ratio mass spectrometry technology involved
(e.g. Mill et al. 2008), the fact that SI ratios can only be used to track sources and trophic pathways
that are isotopically distinct, and that derived metrics such as TP rely on assumptions regarding
isotopic discrimination which can vary across space, time, and trophic levels (Hussey et al. 2014).
Stable isotopes are variations of the same element that differ in the number of neutrons in
their nuclei, and therefore their mass. Unlike radioisotopes, stable isotopes are energeti-
cally stable and therefore persist in nature indenitely. As they have the same number of
protons and electrons, isotopes of the same element have the same chemical properties. But,
because isotopes differ in their masses, different isotopes of the same element have differ-
ent kinetic behaviours. There are many physical processes in nature such as evaporation or
the movement of molecules, which result in the separation of isotopes due to differences
in kinetics. This results in variation in their natural abundances. It is this combination of
persistence and kinetic variability that makes stable isotopes so useful in ecological studies.
Isotopic composition of a material is measured using mass spectrometers, which provide
the ratio of the abundance of one isotope of an element relative to another, e.g. the ratio of 13C
to 12C atoms. As heavier isotopes are typically scarce compared to their lighter counterparts,
absolute isotope ratios are very small, making them impractical to work with. By convention,
isotopic composition is expressed relative to the internationally agreed standard for that ele-
ment (in delta,
, parts per mil,
, notation), according to the equation:
RR and
sample standard
are the respective ratios of heavy to light isotopes in the sample and
international standard, with higher values (
) equating to a composition enriched in the
heavier isotope.
Bulk stable isotope analyses, which are the most common form of analysis, refer to the mea-
surement of the isotopic composition of an element within the entire sample. This is typically in
the form of a tissue or tissue fraction (e.g. separated endosymbionts or the organic fraction of a
There are still many opportunities to add value to SI studies, including through: (1) the use of
elements other than carbon and nitrogen (such as sulfur); (2) the use of fast and slow turnover tissues
to represent feeding over different timescales; (3) the use of archived materials to test ideas about past
changes; (4) improved parameterisation of niche topology (Jackson et al. 2011); (5) development of SI
mixing models allowing better differentiation of different production sources and trophic pathways
(e.g. Parnell et al. 2013); (6) estimation of key processes such as food chain transfer efciency from
relationships between TP and body size (Jennings et al. 2002); and (7) accurate characterisation of
enrichment factors between consumers and their diet, especially for holobionts. The ability to gain
SI information on specic compounds rather than just bulk tissue homogenate has further expanded
our ability to understand coral reef ecosystems by better resolving different sources and pathways
(e.g. McMahon et al. 2016, Fox et al. 2019, Skinner et al. 2021). While important for contextual
understanding, the purpose of this review is not to summarise or explain recent advances in SI meth-
odologies and techniques (for that, we point readers to Text box 1 and, among others, e.g. Boecklen
et al. 2011, McMahon et al. 2013, Vander Zanden et al. 2015, Pethybridge et al. 2018, Ferrier-Pagès &
Leal 2019, McCormack et al. 2019, Whiteman et al. 2019, Shipley and Matich 2020, Tsui et al. 2020).
Instead, in light of the expanding, but often disparate research occurring on coral reefs that utilises
SIs and the lack of a comprehensive synthesis of general ndings, we sought to summarise the cur-
rent knowledge of coral reefs that has been advanced through the application of SI approaches.
Undertaking a more systematic approach to guide this review, we conducted an extensive litera-
ture search for studies utilising SI approaches in coral reef ecosystems and organisms. We screened
and extracted key information pertaining to each study, including the focal taxa, when and where the
study was conducted, along with SI measurements of baseline sources. We then analysed the text
sh otolith). This can either be to measure the natural abundance of the stable isotope found in the
sample, or in the case of isotope labelling pulse-chase experiments, to trace the articial addition
of heavier isotopes through a system of interest based on their excess abundance. The amount of
material required for these analyses is generally small, on the order of a few milligrams or less, but
depends upon the relative concentration of the element of interest within the tissue type of interest.
Technological advances mean that it is now readily possible to measure multiple stable isotopes
from a single sample and, coupled with the relatively low cost of sample runs, has resulted in bulk
stable isotope analyses becoming a regular feature within the ecological toolbox. Commonly used
stable isotopes in marine ecology are carbon (δ13C), for discriminating production sources, nitro-
gen (δ15N) for estimating nitrogen sources and trophic position, and oxygen (δ18O) which relates
to environmental information such as prevailing temperatures. Sulfur (δ34S) is also now being used
more frequently to further distinguish production sources and infer habitat use. In terrestrial and
freshwater systems, hydrogen (δ2H or δD) and strontium (δ87Sr) can be used to separate geographic
regions based on differences in hydrology/elevation and underlying geology, respectively.
More recently, compound-specic stable isotope analyses have been developed to
address some of the shortcomings associated with bulk approaches. That is, by derivatising
and subsequently separating specic compounds of interest, the stable isotope composition of
molecules can be determined within a sample. To date, this generally relates to the measure-
ment of stable isotope ratios within amino or fatty acids. However, the complex methodolo-
gies involved result in longer processing times and greater expense, which is reected in the
reduced number of samples that are generally analysed in such studies.
For a more comprehensive introduction to stable isotope ecology, see Fry (2006). For
other comprehensive literature reviews, please see, among others, Boecklen et al. 2011,
McMahon et al. 2013, Vander Zanden et al. 2015, Pethybridge et al. 2018, McCormack et al.
2019, Whiteman et al. 2019, Shipley & Matich 2020, and Tsui et al. 2020.
in article abstracts using topic modelling (a form of text mining which identies clusters of words,
e.g. topics; Grifths & Steyvers 2004, Grün & Hornik 2011). This approach facilitates the objective
identication of recurring themes in the articles within the extensive literature (see Supplements S1
for detailed methods). Specically, here we (1) characterise the biological, geographical, and meth-
odological foci of SI applications in published works, (2) quantify the isotopic variability observed
among production sources across coral reef systems globally, and (3) identify the principal topics
to which SI data have been applied. We summarise the extent to which current knowledge of coral
reef ecosystems has been advanced through SIA, highlight the main areas for growth, emphasise
considerations that are essential when interpreting SI data from coral reef ecosystems, and identify
future challenges for obtaining fuller understanding of this complex system.
Key patterns and topics in SI approaches to coral reefs
By combining a traditional literature search with mining of pertinent information from identied
articles, and topic modelling of their abstracts, we were able to identify patterns and recurring
themes in the SI coral reef studies published to date (1980–2019 inclusive). Of 341 articles identied
through Web of Science and 964 identied through Google Scholar, a total of 238 were retained
after careful screening (Table S1). Of those, 236 had abstracts and were used in the subsequent topic
modelling analysis (see Supplements S1 for detailed methods). We also extracted key information
from all 238 articles (Table S1), including basic article information, study-specic information (e.g.
spatial and temporal information; Table S2 for denitions), sample information (e.g. single or multi-
tissue, tissue type, isotopes, and focal taxa; see Table S3 for denitions) and, when reported, SI
values of baseline sources (Table S6). It is worth noting here that although we combined extensive
literature searches across two different databases, the nal 238 articles are likely not an exhaustive
list of published SI studies on coral reefs. However, our literature search generated an extensive,
comprehensive, and representative suite of coral reef SI studies using an objective approach.
Topic modelling identied ve topics, which were named based on the highest weighted words
occurr ing within each (Table 2). Generally, similar numbers of art icles were assigned to each topic, with
Topic 2 (Holobiont metabolism) having the highest number of articles (n = 55) and Topic 1 (Organic
matter dynamics) the lowest number of articles (n = 41). Although topic popularity has uctuated over
time (Figure 1), the distribution of topics across regions is fairly equitable (Figure 2). These ve topics
Figure 1 Number of articles published in each of the ve identied topics over time (1980–2019).
were used as a guide to construct the remainder of this review. The topics appear in a logical order
which reects the structure of the coral reef ecosystem, starting from the basal production sources
(Topic 1: Organic matter dynamics), moving onto key primary producers and consumers (Topic 2:
Holobiont metabolism), food web and community structure (Topic 3: Trophic niches), higher-level
consumers and the energetic linkages they construct (Topic 4: Fish diet variation/Habitat connectiv-
ity), and nally considering external drivers of coral reef systems (Topic 5: Environmental drivers)
(Figure 3). It should be acknowledged, however, that there is some inherent crossover between topics.
In terms of SI approaches used, natural abundances of SIs of bulk tissue (i.e. measuring a
whole tissue type such as muscle or liver) dominate the literature (84% of articles; Figure 2B), with
dual analysis of carbon and nitrogen (i.e. δ13C and δ15N) the most popular approach (54% of articles;
Figure 2B), followed by nitrogen on its own (12% of articles; Figure 2B). While SI studies using
compound-specic stable isotope analysis (CSIA, i.e. proling individual compounds such as
amino acids or fatty acids) are less frequent, they are increasing as this methodology becomes more
accessible (6%; Figure 2B). Analyses on organism muscle tissue (n = 99), holobiont host soft tissue
10°E 50°E 90°E 130°E 170°E 150°W 110°W 70°W 70°S
10°E 50°E 90°E 130°E 170°E 150°W 110°W 70°W
Central Pacific
East Atlantic
East Indian
East Pacific
West Atlantic
West Indian
West Pacific
East Indian Central Pacific
West Pacific
West Atlantic
Figure 2 (A) Map of the locations of identied studies f rom the literature sea rch using stable isotope approaches
on coral reefs in the eld, partitioned into the seven major biogeographic regions across the globe (1980–2019).
(B) Plots showing the breakdown of different topics and stable isotope approaches utilised across ve regions
(East Atlantic and East Pacic excluded due to the small number of studies in each region, n = 1 and n = 2, respec-
tively). The left-hand side represents the assignment distribution of studies to the ve identied topics within each
region: FDH, sh diet variation/habitat connectivity; ED, environmental drivers; OM, organic matter dynamics;
HM, holobiont metabolism; TN, trophic niches. The right-hand side displays the breakdown of isotope method-
ology used for each region. Grey inner segments show the number of studies using natural bulk stable isotopes
(Bulk), isotopic tracer (Trc) or compound-specic and other (Oth) approaches. For bulk studies, overlaid is a
hierarchy of elemental identity of studies using carbon (C: δ13C), nitrogen (N: δ15N), sulfur (S: δ34S), or oxygen
(O: δ18O), and combinations of these (as demonstrated by the dashed lines on the bulk isotope key which show
combinations of different analyses, e.g. blue and green = CN, δ13C and δ15 N; blue and yellow = CO, δ13C and δ18O).
Other elements measured are recorded in Other. Note that as some studies use multiple methodologies, the sum
of the right-hand side of the plots is greater than the number of studies in each region (sum of left-hand side).
(n = 79) and their endosymbionts (n = 46), and algal tissues (n = 66), constitute the majority of studies,
but there is a huge diversity of tissues that have been analysed. In addition to various organs (liver
n = 7; gonad n = 3; skin n = 3; digestive tract n = 2; hea rt n = 2), analyses have been conducted on sh
scales (n = 2) and gills (n = 2), faeces (n = 2), bone (n = 2) and sea cucumber respiratory trees (n = 1) .
Most studies are eld based (75%), with few relying on laboratory experiments (22%), and fewer
still combining both eld and lab approaches (3%). While studies have been carried out around the
world, there is substantial disparity between regions (Figure 2): the eastern Atlantic and eastern
Pacic remain poorly represented (n = 1 and n = 2, respectively), likely due to a lack of expansive
coral reef systems in these regions. Instead, western Atlantic studies dominate (28%), followed by
Environmental Drivers
Depth &
/ Seasonal
Deplete 13C/15N
Recycling Mangrove Seagrass SOM Coral POM
Trophic Niches
Area Habitat Gradient -
Ecol. Opportunity
Habitat Reliance
Figure 3 A conceptual diagram of the mangrove–seagrass–coral reef–pelagic continuum surrounded by pan-
els showcasing the ve major research foci of coral reef stable isotope (SI) studies to date, identied through
topic modelling of identied published literature (1980–2019 inclusive, n = 236). (1) Organic matter dynamics:
relative δ13C and δ15N means and standard deviations of ve common reef sources are depicted (not to scale,
see Table 3). The arrows on the left side of the plot highlight factors which may result in more enriched or
depleted values. (2) Holobiont metabolism: SIs help trace the complex cycling of nutrients between holobiont
hosts and their endosymbionts. Various factors (depth, light) may inuence these relationships (Trans. = tran slo-
cation, Metab. = m etaboli sm, Stor. = storage). (3) Trophic niches: SI biplots (often δ13C and δ15N) generate an
isotopic ellipse for an animal that is used to infer their trophic niche area. Niche overlaps suggest competi-
tion for resources, while shifts suggest a change in resource use. The various factors that may inuence these
metrics are depicted on the right side of the biplot (Ecol. = ecological). (4) Fish diet variation and habitat con-
nectivity: SIs reveal how ontogenetic, larval, and mobile predator movements link adjacent ecosystems. (5)
Environmental drivers: SIs reveal both anthropogenic and natural drivers. They can track nutrient inputs and
provide evidence of thermal stress. Natural drivers such as seasonality, depth, and light can also be elucidated.
the western Pacic (21%) and the western Indian Ocean (20%), with notable foci localities in the
Caribbean and Florida Keys, the Great Barrier Reef, and the Red Sea, respectively.
Across the literature, a variety of sources have been sampled in the eld, ranging from water
nutrients and organic matter through to macrophytes, zooplankton, and holobionts, covering both the
pelagic and benthic and spanning the mangrove–seagrass–reef–offshore habitat continuum (Table 3).
Of the 741 extracted values, macroalgae were the most repeatedly measured for both δ13C and δ15N
(n = 145 and 203, respectively). Particulate organic matter (POM), zooplankton, algal turfs, sediment
organic matter (SOM), and coral (both homogenate and separated fractions) have also been well charac-
terised across studies (n > 45). The global variability observed in δ13C and δ15N across coral reef sources
is substantial (Figure 4), spanning from approximately 30‰ to 4‰ for δ13C and 5‰ to 15‰ for
δ15N, with macroalgae specically exhibiting considerable diversity in expressed SI compositions.
Sampling regimes of SI studies are dominated by limited temporal windows (single point,
period, or season, approximately 50% of screened articles), with only ~13% of studies designed to
observe changes, if any, between distinct seasons or years (multi-season, monthly, annually, and
interannual studies) (Figure 5A). Of considerable concern is that 17% of studies screened failed
to provide enough information to discern their sampling regime, with examples found across all
major regions of study. The focal taxa of studies are heavily, but unsurprisingly, skewed towards
reef sh and hard corals, which combined comprise over 60% of all SI studies globally. This bias
is particularly notable in the Western Indian region, whereas studies based in the Western Atlantic
appear to be more evenly dispersed across focal taxa groups (Figure 5B). Barring hard coral, there
is limited focus on other coral reef sources (although they are often measured within other studies,
Table 3, and Figure 4). Encouragingly however, studies that explore SIs in multiple components of
the ecosystem, thereby employing a more holistic approach to understanding whole coral reef sys-
tems, consist of over 5% of the observed literature.
Organic matter dynamics
The dynamics of organic matter and remineralised constituents over and within coral reef ecosys-
tems, and hence the food and dissolved nutrient resources available to reef consumers, have long
been enigmatic. Odum & Odum (1955) suggested that the “changes in dissolved organic matter
(DOM) in the vast ow of water crossing [a] reef” posed a central question in reef productivity.
Table 2 Assigned name, number of articles, and top 15 weighted stemmed words for the ve
topics identied through the model. Stemmed words have been reduced to their root.
articles Top 15 words (stemmed) in weighted order Assigned topic name
1 41 sourc, food, organ, product, benthic, sea, abund, matter, pattern,
contribut, base, spatial, higher, examin, island
Organic matter dynamics
2 55 carbon, nitrogen, tissu, nutrient, host, enrich, rate, alga, coloni,
algal, light, symbiont, metabol, heterotroph, assimil
Holobiont metabolism
3 48 speci, trophic, diet, feed, nich, ecolog, prey, resourc, predat, content,
function, group, forag, divers, dietari
Trophic niches
4 44 sh, habitat, differ, size, popul, seagrass, individu, juvenil, shift,
ecosystem, area, bodi, adult, muscl, marin
Fish diet variation/habitat
5 48 increas, chang, water, depth, high, site, communiti, rang, variat,
shallow, ocean, environment, decreas, environ, effect
Environmental drivers
Table 3 Summary of interstudy mean stable isotope values and their standard deviations for basal resources, extracted from across the 238
identied studies. Where studies were investigating pollution or anthropogenic nutrient inputs, no values were taken from the impacted sites.
Individual values, corresponding references, and specic details on extraction are provided in the supplements.
Mean SD nMean SD nMean SD n
DIC/DINa3.12 (8.59) 0.57 (0.34) 6, 6 1.30 (2.40) 1.48 (0.15) 2, 2
DOMb3.15 (0.07) 0.60 (0.42) 2, 2
POMc20.95 (2.74) 1.22 (1.03) 49, 39 4.69 (2.53) 1.15 (0.98) 50, 40
Phytoplanktonc20.81 (2.14) 0.63 (0.45) 10, 5 3.78 (2.79) 1.04 (0.59) 8, 5 20.80 1
Zooplanktonc19.21 (1.58) 1.00 (0.79) 54, 44 6.27 (2.67) 0.79 (0.60) 56, 47 18.65 (2.33) 1.33 (1.15) 2, 2
Mangroved28.24 (0.49) 2.25 (2.28) 5, 4 1.65 (0.30) 0.54 (0.36) 4, 4 12.90 0.53 1, 1
Seagrassd9.69 (2.98) 1.24 (0.87) 12, 10 2.78 (2.72) 0.73 (1.17) 32, 30 17.67 (2.32) 1.70 (0.99) 3, 2
Macroalgaee15.68 (4.87) 1.27 (1.23) 145, 120 3.93 (3.45) 0.76 (1.12) 203, 179 20.10 (0.71) 2
Benthic mix
Algal turff15.63 (3.48) 1.49 (0.90) 46, 43 2.44 (1.61) 0.64 (0.51) 46, 43
SOMg16.27 (3.26) 1.34 (1.22) 46, 44 4.69 (2.80) 0.65 (45) 47, 45
Holobiont 13.80 (2.19) 0.99 (0.59) 50, 45 5.27 (1.53) 0.51 (0.39) 50, 46
Tissue 15.47 (1.63) 1.16 (0.69) 71, 51 6.59 (3.67) 0.74 (0.48) 55, 35
Endosymbiont 14.64 (2.67) 1.22 (0.63) 54, 54 5.02 (3.42) 0.74 (0.42) 39, 39
Table 3 (Continued) Summary of interstudy mean stable isotope values and their standard deviations for basal resources, extracted from across
the 238 identied studies. Where studies were investigating pollution or anthropogenic nutrient inputs, no values were taken from the impacted sites.
Individual values, corresponding references, and specic details on extraction are provided in the supplements.
Mean SD nMean SD nMean SD n
Endosymbiont 17.25 (1.48) 2
Soft coralj16.31 (1.30) 0.70 (0.55) 54, 44 5.23 (2.86) 0.47 (0.51) 61, 49
Chemoautotrophk24.50 1.38 1, 1 0.40 1.96 1, 1 17.90 5.29 1, 1
a Dissolved inorganic carbon/nitrogen (DIC/N) quantied as seawater bicarbonate, nitrate, and/or ammonium.
b Dissolved organic matter (DOM) estimated as total dissolved nitrogen.
c Seawater ltrate of various size fractions dened as either particulate organic matter (POM), phytoplankton, or zooplankton by the authors.
d Leaf tissue only.
e All species of macroalgae, including epiphytic and calcifying species barring turf.
f Includes a matrix of various organic matter sources and is therefore kept separate from macroalgae. Studies perform varying degrees of matrix separation, but typically limited to
excluding macroinvertebrates.
g Sediment organic matter (SOM) covering various methods of sampling and fractions, including total organic matter; microphytobenthos; sedimentary bacteria/bacterial mats, coral
mucus, and detritus as dened by the authors.
h Measured either combined host/endosymbiont homogenate (holobiont) or measured separately as host (tissue) and endosymbionts, typically via centrifugation of homogenate prior to
stable isotope analysis. Asymbiotic species included in tissue.
i Excludes non-standard tissue types (skeletal material, gametes, and larvae) and bleached tissues.
j Includes both symbiotic homogenates and asymbiotic species.
k A single study with measurements from the lucinid bivalve, Codakia orbicularis, which host chemoautotrophic (sulfur) bacterial symbionts in their gill tissues.
Values are given as mean plus standard deviation in parentheses. n (x1,x2) denotes the number of means (x1) and standard deviations (x2) per source-stable isotope combination across
single, dual, and tri-isotope analyses.
Quantifying variability in material uxes into and within reefs was recognised in early studies as
essential to understanding how reefs function in oligotrophic oceanic settings (Sargent & Austin
1954, Odum & Odum 1955, Sorokin 1973b). However, reef food webs possess a large range of poten-
tial sources, both autochthonous (hereafter ‘internal’) and allochthonous (hereafter ‘external’),
and these are likely to vary spatially along with hydrodynamics and zonation of community structure
(Figures 3 and 4; Table 3). SI studies investigating these uxes have predominantly been conducted
in the western (n = 12) and central (n = 9) Pacic, western Atlantic (n = 11), and western Indian Ocean
(n = 10), with particular foci on Japan (n = 7), the Caribbean (n = 7), and the Red Sea (n = 5 ), re spec -
tively (Figure 2). The eastern Pacic, eastern Indian, and eastern Atlantic are poorly represented with
few, if any, studies conducted (n = 0 of the papers assigned to this topic from our literature search).
High reef productivity despite low ambient nutrient concentrations has been attributed to both
internal and external processes: high rates of internal recycling or atmospheric nitrogen xation, and
therefore nutrient retention (e.g. Odum & Odum 1955, Johannes et al. 1972, Webb et al. 1975), versus
ow-driven inputs of external oceanic nutrients (Odum & Odum 1955, Andrews & Gentien 1982,
Atkinson 1992, 2011, Wyatt et al. 2012a). The high rate of respiration, with net productivity often close
to zero, indicates effective recycling within reef systems (Kinsey 1985, Crossland et al. 1991, Tribble
et al. 1994). However, the uxes of materials over reefs (both internal and external) and their uses by
consumers have rarely been examined at ecosystem scales. This makes it difcult to make accurate pre-
dictions regarding the future function of reefs subject to change. Indeed, non-isotope studies, mostly in
mesocosms or incubations, have indicated that DOM may be a signicant resource (Tanaka et al. 2009,
Nakajima et al. 2010, Naumann et al. 2010a, 2012, Tanaka et al. 2011a). However, these are generally
Turf Macro-
algae POM Seagrass Coral Soft
Coral SOM Sponge Zoo-
Figure 4 Mean δ13C and δ15N values for nine commonly measured sources in coral reef systems, separated
into two panels for clarity (macrophytes and algae left, other sources right). A total of 741 single and dual
stable isotope observations were extracted from the literature (see Table 3 for breakdown by group and deni-
tions, only coral and sponge holobiont homogenate are plotted). Where studies were investigating pollution or
anthropogenic nutrient inputs, no values were taken from the impacted sites. Isotope measurements are plotted
as biplots with 95% ellipses. Single isotope measurements are plotted below (δ13C) or to the left of (δ15N) on
the corresponding biplot axis. Single isotope observation data are jittered for clarity. Kernel densities of total
isotope measurements by source are plotted above (δ13C) and to the right of (δ15N) on the biplot. Individual
values are given in Table S6.
hampered by a lack of understanding of hydrodynamic inuences on DOM uxes over natural reef
systems (but see Wild et al. 2012, Thibodeau et al. 2013). SI data offer great potential to identify organic
matter sources over natural reefs and measure the gross uxes of this material, providing insights into
reef functioning that are essential for predictions for the future. To date, the focal taxa of studies inves-
tigating these uxes (n = 41) are typically reef sh (n = 13), other invertebrates (n = 6), and hard corals
(n = 5). While seawater is also frequently sampled (n = 9), there has been little focus on benthic algae
(macroalgae n = 4; turf algae n = 0) regarding organic matter dynamics, despite their generally large
surface area, important role in nutrient uptake, and as a resource for many reef consumers (Figure 5B).
Internal and external uxes of DOM and POM
Organic matter in the ocean is dominated by dissolved organic matter (DOM), concentrations of
which are far greater on average (1–2 orders of magnitude) than particulate organic matter (POM)
Figure 5 (A) Temporal sampling regime and (B) focal taxa of all 238 articles identied through the lit-
erature search (1982–2019). (A) Single point = all samples collected over one/several days; multi-point = a ll
samples collected at 2 distinct temporal points; single period = all samples collected over a period of several
weeks or more (>1 month, for logistical reasons), but no repetition of groups sampled. See Table S2 for all de-
nitions and notes on the different sampling regimes. EA, East Atlantic; WI, West Indian; EI, East Indian; WP,
West Pacic; CP, Central Pacic; EP, East Pacic; WA, West Atlantic; NR, No Region Specied.
(e.g. Libes 2009, Barrón & Duarte 2015). In contrast to the refractory nature and low availability of
oceanic DOM to reef consumers, much of the DOM produced by reef communities is labile and rap-
idly remineralised (e.g. 1 month for ~80% of total organic carbon in coral mucus to be mineralised;
Tanaka et al. 2011b). SI data have demonstrated that corals can release signicant amounts of DOM;
background concentrations of dissolved organic carbon (DOC) and nitrogen (DON) rose from 100
and 15 µM to 300–1700 and 120 µM, respectively, above coral colonies (Ferrier-Pagès et al. 1998b);
as well as POM (see below). Isotope labelling is often used to trace DOM uxes; highly isotopically
enriched nutrients are supplied and subsequently traced through the various metabolic pathways
within the holobiont. 13C-labelling of reef-building corals Porites cylindrica and Acropora pulchra
suggested that the DOC they release over reefs is derived from stored (>90% of total) rather than
from newly synthesized organic C (<10%) (Tanaka et al. 2008). One of the few ecosystem-scale
investigations of reef DON cycling used spatial patterns in δ15N to demonstrate that localised release
of DON (potentially supported by N2 xation in pristine benthic habitats) is an important means of
recycling N within reef communities (Thibodeau et al. 2013). The spatial arrangement (see ‘Spatial
and temporal variations’ below) of reef communities is therefore important in determining rates of
nutrient exchange across whole coral reef systems (Smith & Marsh 1973, Steven & Atkinson 2003,
Miyajima et al. 2007, Wyatt et al. 2012a, 2013).
While concentrations of DOM are greater, POM is more bioavailable (Lønborg et al. 2018),
and therefore, POM dynamics are more readily studied on coral reefs. Several studies, including
non-isotope approaches, have identied signicant inputs of external POM from the ocean by
analysing gross uxes of isolated components of the external POM pool (particularly the small-
est phyto- and bacterioplankton) (Genin et al. 2009, Wyatt et al. 2010b, Patten et al. 2011, Akhand
et al. 2021). While this may suggest a less prominent role for tight recycling within reefs, rates
of internal POM production have not been adequately quantied across reef systems. Therefore,
robust generalisations regarding the overall relative importance of external versus internal POM
inputs are lacking. Isotope labelling indicates that release of POM from corals may be of a simi-
lar order or higher than that of DOM (average ratios of 0.6 and 0.5 for P. cylindrica and A. pul-
chra, respectively) (Tanaka et al. 2008). Macroalgae can also produce large amounts of POM;
small incubation chambers over intact reef habitats in Moorea (French Polynesia) have shown a
dominance of algal material within POM, with increased POM δ13C (16.9‰ to 11.2‰) above
ambient (20.6‰) indicative of the contribution of algal exudates relative to 13C-depleted plank-
ton (Haas et al. 2010). More enriched nearshore δ13C values of POM samples (18.3‰) in the
Florida Keys were similarly taken to indicate the degradation of seagrass detritus, while more
depleted δ13C of the POM on the outer reef (21.4‰) suggested it was dominated by plankton
(Lamb & Swart 2008), cf. Figure 4. Few studies have quantied rates of POM production over a
natural reef. However, modelling of δ13C and δ15N data from Ningaloo Reef in Western Australia
supported the premise that external POM inputs were balanced by correspondingly high rates
of gross internal POM release into water owing over the reef crest and at (Wyatt et al. 2013).
Measuring net concentration changes of, for example bulk POM, may therefore obscure the
dynamics of organic matter uptake and release over reefs, making SI evidence indispensable for
disentangling internal from external organic matter uxes.
Organic mucus produced in abundance by corals may play a role in both internal cycling and
external inputs to reefs. Studies have used δ13C analyses to demonstrate that coral mucus can be both
exported from reefs, but also re-enter reef food webs due to uptake by reef consumers (Naumann et
al. 2010b, Wyatt et al. 2013). Mucus itself can be a signicant source of organic matter, especially
in inner reef habitats with decreased oceanic exposure (Wyatt et al. 2013). For example, it may
enhance the ux of external particles by trapping oceanic plankton in mucus aggregates, augment-
ing sedimentation rates onto reef habitats (Naumann et al. 2009). Moreover, internal sources within
reefs are not limited to the corals. For instance, 15N-labelling has shown signicant rates of POM
release from upside-down jellysh Cassiopea sp. (which can be abundant in some reef systems) and
subsequently assimilated by zooplankton (Niggl et al. 2010). Furthermore, non-isotope work has
highlighted the important role of sh communities in supplying (excretion) and storing (biomass)
nutrients on coral reefs and adjacent habitats (Allgeier et al. 2014), suggesting nutrient cycling is
prevalent even at higher trophic levels. To date, there is limited SI work exploring this aspect of
organic matter dynamics on reefs (but see ‘Habitat connectivity’).
Isotope labelling has been used to demonstrate a potentially major role for sponges in organic
matter uptake and retention within coral reefs. The combination of isotopic labelling (13C and 15N)
and nanoscale secondary ion mass spectrometry (NANOSIMS) has shown that sponge host tissues
are capable of directly utilising DOM in the water column through lter feeding (Achlatis et al.
2019). Indeed, some sponges are more heterotrophic, as i ndicated by their bulk δ15 N values (Figure 4)
(Weisz et al. 2007). For example, bulk δ13C and δ15N indicate that coral cavity sponges typically
feed on coral-derived materials (van Duyl et al. 2011, Slattery et al. 2013). Unlike other marine
organisms, a few sponges show differential assimilation mechanisms for different DOM sources, as
revealed by stable isotope pulse‐chase experiments (13C and 15N); for example, algal DOM is mainly
used by symbiotic bacteria, while coral DOM is assimilated by sponge cells (Rix et al. 2017). de
Goeij et al. (2008) used 13C-labelling to provide evidence that, in addition to POM, a coral reef
sponge, Halisarca caerulea, was able to incorporate DOM, thereby accessing an abundant source
of organic matter in reef waters. Later, using 13C- and 15N-labelled DOM, de Goeij et al. (2013)
demonstrated both in aquaria and in situ that DOM incorporation by sponges may facilitate DOM
transfer to higher trophic levels through detritus (POM) production. Using 13C- and 15N-labelling in
the laboratory, DOM uptake and POM production by sponges were further demonstrated to facili-
tate the transfer of coral-mucus-derived DOM to detritivores on both warm- and cold-water reefs
(e.g. ophiuroids and polychaetes) (Rix et al. 2016, 2018). These isotope studies on reef sponges have
revealed an additional mechanism by which organic matter produced on reefs may be internally
retained within the system.
Spatial and temporal variations
Organic matter uxes are likely to have strong spatial and temporal dynamics (Figure 4). These will
be inuenced by the hydrodynamic conditions and zonation of benthic communities over small spa-
tial scales of hundreds of metres or less (Haas et al. 2011, Kolasinski et al. 2011, Wyatt et al. 2012a),
and larger-scale stochastic events such as upwelling, storm disturbances, and coral bleaching events
(Leichter et al. 2007, Wild et al. 2008, Kolasinski et al. 2011, Radice et al. 2021). Further, large-
scale urbanisation-eutrophication gradients can be reected through reef food webs, particularly
as elevated δ15N (Kürten et al. 2014, Duprey et al. 2020; and see ‘Environmental drivers’). Broad-
scale SI data or ‘isoscapes’, i.e. a spatial pattern of isotopic values across a land or seascape (West
et al. 2008, Bowen 2010), can reveal geographic patterns in organic matter and nutrient dynamics
over reefs. For instance, in the Red Sea, where 11% of all coral reef SI studies have been conducted
(Figure 2), low organic matter δ15N values in the north (zooplankton δ15N: 1.3‰) reect the impor-
tance of N2 xation, while the higher δ15N of organic matter in the south (zooplankton δ15N: 5.8‰)
reects N inputs from the Indian Ocean (Kürten et al. 2014). Spatial and temporal variability of
organic matter over reefs is poorly understood, yet there is strong SI evidence of habitat-linked
variations in uxes of DOM (Thibodeau et al. 2013), POM (Wyatt et al. 2013), and dissolved nutri-
ents (Leichter et al. 2007). While these oceanographic drivers mean that external resource supply
can be highly variable in space and time (Wyatt et al. 2012a, 2013, Kürten et al. 2014), most SI reef
studies are based on just a single time point or period of sampling (44%), with few conducting repeat
samplings across multiple time points (19%) (Figure 5A).
Mass coral spawning can periodically increase POM concentrations several fold on many reefs,
and SI data have proven useful in examining the biogeochemical impact of these events. A lasting
inuence of spawning on POM δ15N was seen on the Great Barrier Reef over a period of about
10 days (increases of ~5 ‰, from 0.7‰ to 4.8‰–5.7‰), suggesting spawning-derived organic mat-
ter is rapidly transferred to higher trophic levels (Wild et al. 2008). Similarly, in Kane’ohe Bay,
Hawai’i, POM δ15N remained slightly elevated (2‰–3‰) after spawning (>10 days), indicating
incorporation of spawning-derived organic matter into higher trophic levels, but spawning impacts
on water- column POM δ13C were short-lived (2–4 days post-spawning returned to pre-spawning
values) (Briggs et al. 2013). Briggs et al. (2013) also found that the δ13C of tissues of the coral
Montipora capitata increased by ~ 1‰ (13.3‰ to 12.2‰) over the course of the spawning season,
with eggs having lower δ13C than host tissues (14.5‰). This temporal change could reect the
spawning physiology; the concentration of 13C-light wax esters and overall carbon content is higher
in M. capitata eggs compared to adults (Padilla-Gamiño et al. 2013), but it may also reect changes
in feeding or relative rates of autotrophy and heterotrophy. This underscores the importance of
having a good understanding of baseline isotope variations when assessing the impacts of stochas-
tic events like spawning using tissue SI data.
The high spatiotemporal variability in resources means that adequately quantifying the isoto-
pic composition of material supplied to reefs can be a non-trivial undertaking (Figure 4; Tables 3
and S6). For instance, variability in the isotopic composition of dissolved inorganic N (e.g. nitrate)
can be high across the water column (3.5–5.5‰ between 50 and 242 m) just due to small-scale
patchiness in N cycling (Leichter et al. 2007). Internal production can also be highly variable, with
organic carbon released by benthic algae on reefs at Moorea demonstrating distinct seasonality,
including δ13 C variation of ~ 5‰ (Haas et al. 2010). This variability is likely why few studies to date
have used isoscapes on coral reefs, or tropical waters in general (but see MacKenzie et al. 2019);
those in marine settings have mostly been conducted in temperate shelf regions (MacKenzie et al.
2014, Kurle & McWhorter 2017, St. John Glew et al. 2019). However, isoscapes can provide spatial
(and potentially temporal) context to more general questions about community ecology, animal
migration, and nutrient cycling (Hobson et al. 2010, McMahon et al. 2013, Cheesman & Cernusak
2016). In one of the few studies employing an isoscape approach on coral reefs, δ15N values of long-
lived benthic bivalves were used to create a nitrogen isoscape in New Caledonia that highlighted
regions of eutrophication (δ15 N of 11.7‰ compared to 4.3‰ in lagoon), characterising the anthro-
pogenic nitrogen footprint of the area (Thibault et al. 2020). Thus, isoscapes of coral reef ecosys-
tems that account for sufcient natural variation could offer insight into the complex processes that
might inuence coral reef trophodynamics and SI values across various locations (Figures 3 and 4;
Table 3). Given that environmental conditions are uctuating due to climate change, isoscape stud-
ies would further benet from the inclusion of SI data across both space and time where possible
(McMahon et al. 2013).
Isotopic insights into the role of detritus
Detritus (i.e. non-living organic matter) is an abundant and potentially signicant food resource
over reefs, but its variable lability makes it challenging to characterise (Figure 4; Tables 3 and S6).
Isotopes offer an opportunity to better trace and quantify uxes of this material. Indeed, there is sub-
stantial isotopic evidence of a prominent role for detritus in reef food webs. While detrital pools are
higher (1.6 times) in low-energy back reef habitats where benthic material accumulates (evidenced by
enriched mean δ13C 16.83‰), input rates are higher (1.7–2.9 times) over dynamic fore reefs due to
oceanic detritus supply (evidenced by depleted mean δ13C 19.84‰) (Max et al. 2013). Thus, while
detritus can be a nutritious food source, its availability uctuates with hydrodynamics (Max et al.
2013). Isotope labelling (13C and 15N) has demonstrated that detritivores, such as ophiuroid brittle
stars, can play an important role in the recycling of nutritionally poor detritus to higher trophic lev-
els (Rix et al. 2018). There is also increasing evidence of a high degree of detritivory in reef shes
previously assumed to be largely herbivorous. For instance, parrotsh such as Chlorurus sordidus
are often classied as herbivores. Stomach and feeding observations have suggested that this species
may be better described as a detritivore (Choat et al. 2002), and bulk and CSIA data conrm it to be
principally detritivorous across both oceanic and inshore reefs (Wyatt et al. 2012b, McMahon et al.
2016). In agreement with observational and morphological studies (Choat et al. 2002, 2004), CSIA
data identied that the surgeonsh Ctenochaetus striatus is also predominantly detritivorous (73%;
McMahon et al. 2016). Dietary plasticity at the individual level (McMahon et al. 2016), or spatial
changes in the importance of detritivory (Wyatt et al. 2012b), require more detailed investigation.
However, it appears likely that the importance of detritus, and therefore microbial reworking, in reef
food webs has been underestimated (McMahon et al. 2016). As described in detail in ‘Internal and
external uxes of DOM and POM’, sponges also play a key role in reworking detritus on coral reefs
through the ‘sponge loop’: coral mucus carbon and nitrogen are transferred into sponge tissues and
subsequently released as detritus (de Goeij et al. 2013, Rix et al. 2016).
Holobiont metabolism
Hermatypic (reef-building) scleractinian corals play a foundational role in providing essential
habitat for reef organisms (Coker et al. 2014), so it is only natural that considerable efforts have
focused on their ecology and the metabolic dependency between them and their symbiotic dino-
agellates in the family Symbiodiniaceae (Figure 3). Holobiont metabolism had the largest num-
ber of studies principally assigned to it (n = 55) among SI coral reef topics. Likewise, of all 238
identied SI studies, 26% (n = 62) have had coral as their focal taxa, second only to shes (36%,
n = 85) (Figure 5B). Studies focusing on this topic contributed a major proportion of the earliest SI
works on coral reefs (Figure 1). As SIs act as natural (or articial) tracers for elucidating energetic
pathways, they are ideally placed to resolve questions regarding nutrient acquisition, transloca-
tion, and utilisation within and between holobionts and their symbiotic microbiomes (Figure 3).
This is highlighted by the fact that most isotope labelling studies were assigned to the topic of
Holobiont metabolism’ (28 of 37 total). Geographically, there has been a particular focus on
holobiont metabolism regionally in the western Indian Ocean (notably experimental work in the
Red Sea) and the western Pacic (Figure 2B and 5B). Key aspects revolve around the nature of
nutrients that are taken up by holobionts; how they are proportioned internally between hosts
and symbionts; and drivers of variation in the relative utilisation of photo- or chemosynthetically
xed material (autotrophy) and secondarily sourced production (heterotrophy), known as mix-
otrophy. Here we expand upon these ideas to demonstrate the understanding achieved using SIs,
before considering studies whose focus is on the symbiotic relationships found in organisms other
than those of hermatypic corals.
External nutrient acquisition
As highlighted in the previous section, there is a wealth of external nutrient sources that are poten-
tially available to corals and other holobionts to underpin their metabolism, as well as those of their
endosymbionts to form photosynthates. This is despite coral reef ecosystems traditionally being
viewed as restricted to oligotrophic tropical surface waters (Darwin 1842). Early work by Risk
et al. (1994) suggested increasing reliance on terrigenous carbon sources by corals and their endo-
symbionts after observing increasing δ13C tissue values (from 16‰ to 11‰) with increasing dis-
tance from shore on the Great Barrier Reef. Spatially varying nutrient acquisition has also been
observed with reef zonation, with varying coral tissue δ15N values along an offshore to mid-shelf
to inshore barrier reef transect attributed to cold-water upwellings, algae-based nitrogen xation,
and terrigenous sources, respectively (Sammarco et al. 1999, Erler et al. 2014). Elsewhere, across a
reef atoll system in the Maldives, nitrates from deep ocean water that are enriched in 15N have been
shown to be incorporated into coral tissues via seasonal upwelling (Radice et al. 2019). In the Cook
Islands in the South Pacic Subtropical Gyre, nitrogen inputs to corals also vary seasonally, with
δ15N in coral skeletons suggesting nitrogen sources originate from groundwater during wet seasons
and from N2 xation during dry seasons (Erler et al. 2019). These studies highlight the environ-
mental and temporal context dependency of patterns in coral nutrient uptake, but it is worth noting
that increases in coral and endosymbiont δ13C values may also be related to spatial gradients in, for
example, turbidity affecting coral photosynthesis rates or endosymbiont genera.
Direct nutrient uptake from the water column is likely inuenced by its form; nitrogen is primarily
available as nitrate or ammonium, where ammonium appears to be principally taken up by the endo-
symbiotic algae. Eight-week-long 15N-labelled ammonium enrichment experiments revealed a tenfold
increase in ammonium uptake rates by hosted dinoagellates compared to coral tissue (Grover et al.
2002). However, overall ammonium uptake is reduced in fed versus starved hosts (Grover et al. 2002),
which may suggest secondary reliance on ammonium as a nitrogen source compared to heterotrophic
feeding. Similar patterns were found for nitrate using 15N-labelled nitrate and ammonium; nitrate is
principally taken up by the endosymbionts, with uptake rate independent of prior nutrient acclima-
tisation, but signicantly lower under high ammonium regimes (Grover et al. 2003). The metabolic
response of dinoagellate endosymbionts to external nutrient enrichment is rapid; signicant uptake
occurs within an hour of exposure to either ammonium or nitrate 15N-enriched seawater (Pernice et
al. 2012, Kopp et al. 2013). This suggests direct uptake and xation of ammonium by endosymbionts
from seawater lling the coelenteron rather than nutrient transfer from hosts to algae (Pernice et al.
2012, Kopp et al. 2013). Such a rapid response is facilitated by temporary nitrogen storage in intracel-
lular uric acid crystals that can then be remobilised in the following hours (Kopp et al. 2013). Similar
temporary intracellular storage structures have also been identied for carbon using pulse-chase iso-
topic labelling of 13C-bicarbonate, whereby seawater bicarbonate is rapidly (~15 minutes) taken up by
dinoagellates and xed into lipid droplets and starch granules (Kopp et al. 2015).
The uptake of water column nutrients can be further facilitated by recycling pathways, as has
been revealed by isotope tracer experiments using articially 15N-labelled bacteria to track their
incorporation into coral larvae (Ceh et al. 2013). Isotopic labelling (15N) has further shown that
nitrogen-xing diazotrophic bacteria may also be taken up directly into the epidermal layers of
coral larvae (Lema et al. 2016), potentially helping to meet their nitrogen demands. Nitrogen xa-
tion can also occur within the endolithic diazotrophs found between coral tissues and their carbon-
ate skeleton, as demonstrated with 15N-labelling (Grover et al. 2014, Yang et al. 2019). However, the
importance of this pathway varies according to coral metabolic status (i.e. whether they are more
auto- or heterotrophic) and with depth (Bednarz et al. 2017). Bulk SI work (δ13C and δ15N) has,
however, shown a lack of nutrient exchange between coral polyps and adjoining epilithic algal turfs,
demonstrating that at least some potential nutrient pathways are not utilised (Titlyanov et al. 2008).
Heterotrophic feeding by coral polyps further expands the potential nutrient sources available
for these holobionts, with a diversity of trophic interactions being observed (see Houlbrèque &
Ferrier-Pagès 2009 for a detailed review on coral heterotrophy). Lai et al. (2013) used 15N-labelled
seagrass to experimentally show that corals can directly consume seagrass material, in both par-
ticulate and dissolved form. This highlights a direct nutritional link between corals and adjacent
seagrass meadows, which can export large quantities of fresh and detrital material. Other experi-
mental bulk SI work (δ13C and δ18O) has highlighted how grazing on zooplankton can lead to sub-
stantial increases in various measures of coral tness, such as tissue chlorophyll concentrations,
compared to when heterotrophic feeding is restricted (e.g. Reynaud et al. 2002). Furthermore,
grazing experiments using 3H-labelled bacteria and ciliates showed that although coral grazing
rates decrease as light intensity increases, heterotrophy still contributes to coral nutrition, sug-
gesting it complements autotrophy even under high light conditions in Stylophora sp. (Ferrier-
Pagès et al. 1998a). More recent SI ngerprinting techniques using δ13C of essential amino acids
(CSIA) demonstrate the signicant contribution of heterotrophic feeding to coral hosts, with an
average of 41% contribution to assimilated material determined for the widespread Indo-Pacic
scleractinian coral Pocillopora meandrina (Fox et al. 2019). Similar proportions of heterotrophic
nutrient uptake have also been veried experimentally using 15N-labelled rotifers to quantify nitro-
gen incorporation rates in another common Indo-Pacic coral Porites lutea (Rangel et al. 2019).
However, the degree of heterotrophic feeding may be a species-specic trait; paired bulk (δ13C
and δ15N) and amino acid CSIA (δ13CAA, δ15NAA) revealed that Montipora capitata did not change
their nutritional strategies under different experimental nutrition regimes (Wall et al. 2021), sug-
gesting a lack of trophic plasticity.
Internal nutrient translocation and partitioning
The fate of nutrients once assimilated into host tissues underpins the symbiotic relationship between
coral and Symbiodiniaceae – basal products need to be supplied to algal cells for autotrophy and
likewise photosynthates shuttled elsewhere for energetic demands of the host (Figure 3). Isotopic
labelling experiments tracing the various metabolic pathways within the holobiont constitute some
of the earliest uses of SIs on coral reefs. For example, feeding experiments with 14C revealed that
six species of coral were able to feed on DOM and planktonic bacteria, actively consuming organic
phosphorus bound in the cells of the latter (Sorokin 1973a). Other studies have attempted to under-
stand carbon translocation and turnover within coral colonies. Crossland et al. (1980) saw a 50%–
60% loss of photosynthetically xed 14C from isotopically labelled and replanted coral colonies
during their rst 40 hours back on the reef. However, rather than the coral colonies translocat-
ing xed carbon from outer branches to basal regions, the authors suggested that the coral tissues
had released mucus and dissolved organic carbon into the environment (Crossland et al. 1980).
Similarly, Rinkevich & Loya (1983) used 14C sodium bicarbonate in the eld to demonstrate limited
translocation of photosynthetic products across coral colonies over the course of a month (from
bases to branch tips), despite lower incorporation rates in the growing tip regions.
Under more controlled laboratory settings, high precision tracing can be conducted to eluci-
date internal translocation of metabolites over short timescales, further revealing the complexities
of this symbiotic relationship. Following 13C-labelled bicarbonate enriched seawater incubation,
Tremblay et al. (2012) calculated that 60% of carbon xed by endosymbionts in the scleractinian
Stylophora pistillata is translocated to host tissue within 15 minutes, with approximately 50% of
xed carbon being respired by the holobiont as a whole. Whole nitrogen budgets have also been
determined through 15N enrichment, showing that a majority (50%–83%) of nitrogen utilised by
endosymbionts is derived from coral hosts, with host species-level differences attributed to differ-
ent N-biomasses per unit surface area of coral host species (Tanaka et al. 2015, 2018). One of the
few studies to combine both δ13CAA and δ15NAA to explore the nutritional exchanges between coral
hosts and their endosymbionts conrmed that endosymbionts do benet from host heterotrophy
(Ferrier-Pagès et al. 2021). Furthermore, this relationship is not one way but tightly coupled.
Combining 13C- and 15N-labelling showed that the coral host derived 99% of its total nitrogen
from the endosymbiont, suggesting the host ‘farms’ the endosymbionts to efciently exploit both
C and N (Tanaka et al. 2018).
Interestingly, the fate of acquired nutrients appears to depend upon the source of the material.
Isotope labelling (13C and 15N) reveals that heterotrophic sources exhibit considerable internal
exchange and retention within the coral-algae symbiosis, whereas inorganic nutrients (that are pho-
tosynthetically xed by endosymbionts) are rapidly used and respired to meet more immediate
metabolic demands (Hughes et al. 2010, Tremblay et al. 2015). The release of DOM by corals can
constitute a considerable loss of xed material, corresponding to approximately 5% of net photosyn-
thetic production of endosymbionts as shown by 13C tracer accumulation experiments (Tanaka et al.
2009). This has been corroborated elsewhere; similar work has estimated coral carbon losses due to
DOM release is equivalent of 28% of gross carbon xation (Tremblay et al. 2012).
With the advent of ever more sophisticated technology, exploring the spatial structuring of
metabolic processes within coral tissues is now possible. Notably, the combination of isotopic label-
ling and nanoscale secondary ion mass spectrometry (i.e. NANOSIMS) has revealed the varia-
tion in net carbon xation rates between individual cells of Symbiodiniaceae, with an average
sixfold decrease between upper and lower tissue layers within individual polyps (Wangpraseurt
et al. 2016). These combined technologies have also helped disentangle the rapid nutrient uptake
dynamics within endosymbionts (Kopp et al. 2013, 2015). Such approaches can be further expanded
with, for example, simultaneous immunouorescent microscopy to correlate the presence of isotopi-
cally labelled labile nutrients with associated proteins and enzymes to further elucidate metabolic
pathways (Loussert-Fonta et al. 2020). These technological advances have the potential to greatly
expand the current understanding of the molecular-level underpinning of coral-algae symbioses.
Drivers of mixotrophy
The mechanisms that inuence the strength of coral-algae symbiosis are key to the wider coral reef
ecosystem. Therefore, understanding how coral mixotrophy changes with different factors provides
insight into how they may be best managed and conserved in a changing world. SI studies that
explore potential drivers of mixotrophy in corals can generally be categorised by the nature of the
driver(s) of interest: whether mixotrophy is impacted by the external environment (exogenous) or
inuenced by traits that are particular to the studied host or symbiont (endogenous).
Exogenous factors
Given the photosynthetic underpinning of coral-algae symbiosis, depth represents a strong natural
abiotic gradient which can impact autotrophic efciency due to, among other things, diminishing
ambient light levels (see ‘Environmental drivers: natural drivers’). The nutritional history of host cor-
als (fed versus starved), which is driven by the temporal dynamics of prey availability, may also play
a role in mixotrophy. In isolation, 15N-labelling indicates that nutritional history does not appear to
affect the assimilation efciency of heterotrophic feeding by corals (Piniak & Lipschultz 2004).
However, δ13C of fatty acids reveals that recent starvation, when compounded with thermal stress,
leads to reductions in chlorophyll and maximal photosynthetic efciency in coral tissues, resulting in
respiration of storage fatty acids in order to maintain coral metabolism (Tolosa et al. 2011). This high-
lights the compounding nature of environmental factors (see ‘Environmental drivers: natural drivers’).
Bleaching events, which are induced by a variety of external stresses, are projected to continue
to increase with ongoing climate change (Hughes et al. 2017). Given the loss of the autotrophic
symbionts during such episodes, the impact on host energetics is likely to be signicant. Early
SI work suggested, however, that bleaching does not alter the ratio of heterotrophic to autotro-
phic dependency. This was inferred from similar δ13C values in two corals (Porites compressa
and Montipora verrucosa) and their endosymbionts taken from paired samples of bleached and
non-bleached tissue in the eld in Hawai’i (Grottoli et al. 2004). This was in contrast to pulse-chase
experiments (13C) on the same species (P. compressa) and a congener (Montipora verrucosa cf. M.
capitata) that showed reduced assimilation of autotrophically derived carbon in bleached corals,
but with assimilation of heterotrophic sources remaining similar in bleached versus non-bleached
corals (Hughes et al. 2010). More recent work using bulk SI data (δ13C and δ15N) on the same two
species also did not indicate increased heterotrophic nutrition post-bleaching (Wall et al. 2019).
The δ13C data also suggest corals may undergo biomass compositional changes when bleached
and directly after (Wall et al. 2019), possibly as they catabolise their stores of 13C-enriched lipids
(Grottoli and Rodrigues 2011). Heterotrophic carbon sources are likely important for coral recov-
ery as they are predominantly used to replenish coral lipids (Baumann et al. 2014), which are used
to maintain metabolism during thermal stresses (Tolosa et al. 2011). For longer-term responses of
corals to bleaching, see ‘Environmental drivers: natural drivers.
Endogenous factors
The diversity in form observed across Scleractinia, and even within species across, for example,
depth gradients (Einbinder et al. 2009), suggests ecological trade-offs associated with different
host morphologies. Previous non-SI work exploring coral morphology-feeding relationships sug-
gested that coral surface-to-volume ratio (S/V) and polyp size might determine the importance of
light or zooplankton capture. Branching corals have maximum S/V ratios and small polyps and
are best suited for light capture, while corals with lower S/V ratios generally have larger polyps
suiting them to zooplankton capture (Porter 1974, 1976). Subsequent non-SI work by Wellington
(1982) corroborated that tentacle size was important for determining the degree of hetero- or
autotrophy (i.e. corals with larger tentacles use more zooplankton), but could not conrm the
coral morphology-feeding relationships. Some SI data have now supported this hypothesis. δ13C
values in coral tissues and endosymbionts from 14 Red Sea coral species indicated increased
relative rates of autotrophy in branching corals with smaller polyps compared to massive species
with larger polyps, attributed to reductions in carbon limitation associated with increasing sur-
face area (Levy et al. 2006). Such a trend with host morphology has been further corroborated by
Xu et al. (2020) using δ13C. However, in contrast, a non-isotope feeding study found no relation-
ship between coral feeding rates and polyp size (Palardy et al. 2005), while Hoogenboom et al.
(2015) using bulk δ13C and δ15N found that feeding rates were instead highest in branching corals
with smaller polyp sizes. This suggests more research is needed to disentangle coral morphology-
feeding relationships. More recently, corals that were more autotrophic, implied by similarity in
host tissue and symbiont bulk δ13C and δ15N, had a negative relationship with polyp size, but also
bleaching resistance, suggesting they may be more susceptible to increasing water temperatures
(Conti-Jerpe et al. 2020).
While less conspicuous, the different genera within Symbiodiniaceae that form symbioses with
corals can also inuence host metabolism due to their differing functional responses to environmen-
tal conditions. For example, isotope labelling (13C and 15N) revealed that holobionts hosting former
clade C (genus Cladocopium) have increased uptake rates of inorganic nitrogen under non-thermal
stress conditions compared to holobionts with former clade D (genus Durusdinium) (Baker et al.
2013a). This can lead to the competitive exclusion of clade D under normal conditions despite this
clade resulting in increased carbon acquisition during periods of thermal stress (Baker et al. 2013a).
Similarly, Ezzat et al. (2017) demonstrated increased carbon acquisition by holobionts with clade
C symbionts compared to clade A under low irradiance levels using isotope labelling (13C and
15N), but this appeared to be due to increased heterotrophic capacity by corals hosting clade C
endosymbionts. However, other non-isotope studies did not nd an inuence of symbiont genus on
host metabolism (Matthews et al. 2020). Endosymbiont communities do inuence coral SI values
though. Coral colonies dominated by clade D have lower δ13C in both host and symbiont tissues
compared to colonies dominated by clade C (clade C host and endosymbiont δ13C 1.6‰ and 1.5‰
higher than clade D in summer), but these differences were inferred to be driven by light availability
rather than coral feeding (Wall et al. 2020).
The strong focus on adult coral colonies can ignore the importance of vulnerable larval stages
that support the maintenance of coral reefs through successful recruitment and ontogenetic develop-
ment. In an effort to better understand planktonic coral larvae metabolism, Alamaru et al. (2009b)
conducted feeding experiments with various potential food sources – phytoplankton, zooplankton,
and bacteria – but failed to observe active feeding or heterotrophic uptake via δ13C and δ15N SI
data. This is despite planulae larvae having an oral opening. They therefore inferred that coral lar-
vae rely wholly on lipid reserves or photosynthates from symbionts that are already present in the
endoderm. This was further elaborated by pulse-chase experiments using labelled 13C-bicarbonate
and 15N-nitrate conducted by Kopp et al. (2016), who determined that there is minimal contribu-
tion by symbionts to host metabolism, demonstrating that coral larvae are essentially lecithotrophic
Metabolism in non-hard coral symbioses
A signicant number of SI studies have explored the metabolic underpinning of other non-coral
symbiotic groups, revealing complex physiologies. Sponges possess an intricate symbiotic system
due to the diversity of the microbiomes they can host, including photosymbionts (Davy et al. 2002,
Weisz et al. 2010). However, the strength of the symbiotic dependency appears to vary between
host sponge species, with both tight and weak metabolic couplings being observed (Freeman et al.
2015). Isotopically enriched seawater with 13C and 15N tracers has been used to demonstrate nutri-
ent transfer between microbes and host sponges, the rate of which appears dependent on symbiont
identity and irradiance rather than overall symbiont abundance (Freeman et al. 2013). Interestingly,
labelled 15N-ammonium and 13C-bicarbonate revealed that coral-excavating sponges often host both
Symbiodiniaceae and prokaryotic symbionts, with the former undertaking signicant inorganic
nutrient xation and transfer to host bioeroding sponges, but the latter not contributing to nutrient
assimilation (Achlatis et al. 2018). Conversely, 13C- and 15N-enriched DOM show that sponge hosts
can directly take up and utilise DOM and subsequently transfer signicant dissolved organic waste
products to symbionts (Achlatis et al. 2019). This can constitute the entire nitrogen budget of hosted
algae (Davy et al. 2002), in a similar fashion to coral hosts. Pulse-chase experiments with isotopi-
cally labelled 13C‐ and 15N‐enriched coral‐ and algal‐derived DOM show that various sources of
DOM are utilised by sponges, but algal-derived sources are predominantly transferred to the micro-
biome while coral-derived DOM is used directly by the sponge host (Rix et al. 2017). Interestingly,
bulk SI (δ13C and δ15N) and isotope labelling (13C and 15N) revealed that the encrusting sponge,
Terpios hoshinota, which kills corals by overgrowing them, does so for space, not for food; in the
new sponge tissues, only 9.5% of the C and 16.9% of the N was derived from the corals underneath
(Syue et al. 2021). In contrast, contact association with macroalgae appears to competitively inhibit
sponges, with SI enrichment experiments (13C and 15N) demonstrating nitrogen transfer from sponge
to macroalgae (Easson et al. 2014). As with coral holobionts, changes in the surrounding environ-
ment can alter the dependency of sponge hosts on photoautotrophic symbiont production. Recent
bulk and amino acid CSIA work in the Caribbean demonstrated increasing heterotrophy with
depth for sponges, but highlighted species-specic trends in host utilisation of POM and DOM, and
internal translocation of these (Macartney et al. 2020).
The host-symbiont relationship in gorgonians has been the focus of more recent interest in
holobiont metabolism utilising SIs, likely due to their increasing presence in some coral reef
systems (Rossi et al. 2020). While overall autotrophic reliance varies seasonally and with spe-
cies, endosymbionts can deliver the majority of energetic demands (>95%), with heterotrophically
acquired carbon sources contributing less than 5% year-round for gorgonian species examined in
the Caribbean (Rossi et al. 2020). Conversely, gorgonians examined in Taiwan appear to be highly
dependent on heterotrophic inputs based on host and symbiont δ13C and δ15N values, with relatively
little energetic benet garnered from their endosymbionts (Hsu et al. 2020). Similarly, recent work
on Antipatharian soft corals (black corals) using isotope labelling (13C and 15N) has demonstrated
that they can use a range of different food sources, likely allowing them to exploit seasonal uctua-
tions in prey concentrations (Rakka et al. 2020). These studies highlight the diversity in energy
acquisition within this group. While environmental sensitivities to gorgonian symbioses have yet
to be thoroughly explored, depth appears to have little impact on gorgonian tissue δ15N values
(change in only 1.4‰ over 20 m), implying limiting physiological effects associated with ambient
light (Baker et al. 2011). Further, short-term (seven day) nutrient enrichment does not appear to sig-
nicantly impair the symbiosis between gorgonians and their dinoagellate endosymbionts, but can
result in increased chlorophyll content and algal densities within hosts (McCauley & Goulet 2019).
Other forms of symbiotic relationships, while lesser studied, are likely commonplace on coral
reefs and constitute important components to ecosystem functioning (Pinnegar & Polunin 2006).
Anemones may also host Symbiodinium as a source of autotrophic nutrition; however, SI labelling
(13C and 15N) highlights the competitive nature of resource acquisition by both host and endosym-
biont, implying a less stable symbiotic association compared to true coral holobionts (Radecker
et al. 2018). Carbon and nitrogen SI data from both lab and eld isotope labelling feeding experiments
have been used to demonstrate nutrient transfer from anemoneshes to both sh-hosting anemones
and their endosymbionts forming a tripartite symbiosis (Cleveland et al. 2011). Parmentier & Das
(2004) examined relationships between four species of apparently parasitic carapid shes and their
echinoderm hosts using bulk SIs, but only found evidence for feeding on host tissues for one spe-
cies (Echeliophis gracilis), suggesting commensal associations for the other three shes. Similarly,
while shallow-water black corals host a variety of macrosymbionts, bulk δ13C and δ15N reveal that
they do not use their host as a main food source, but instead use the coral’s structure to access
nutrition from the water column (Terrana et al. 2019). True parasitic-host relationships have also
been explored using bulk SIs in reef sh and gnathiid ectoparasites (Demopoulos & Sikkel 2015).
Finally, upscaling from individual metabolic processes to whole community metabolic functioning
can be facilitated through SI approaches. Spatial differences in isotopic discrimination of overlying
seawater DIC are attributable to the varying ratio of calcication:primary production of the underly-
ing ecological community, e.g. ~5‰ higher δ13CDIC discrimination for portions of the reef with more
non-calciers compared to portions of the reef with more calciers (Koweek et al. 2019).
Trophic niches
Ecological niches are multidimensional spaces dened by environmental conditions and resource
utilisations that are occupied by an organism (or population) where their survival curves are optimised
(Hutchinson 1957). The trophic niche relates to the array of food items consumed by an organism,
which constitutes a subset of its overall ecological niche. Understanding an animal’s resource use,
and how this varies within and among species and guilds, helps determine its trophic function within
an ecosystem and how this might respond to environmental change. Increasingly, studies are using
SIs to estimate an animal’s trophic niche. Isotope data are typically presented on a biplot using the
isotope values (δ‐values) as coordinates (Figure 3) (however, note that tri-isotope plots are now being
used; Skinner et al. 2019a). The area (δ‐space) of these coordinates is determined to be the animal’s
isotopic niche, providing an understanding of its trophic ecology by reecting some aspects of their
trophic niche (Figure 3) (Newsome et al. 2007). For example, the size of the isotopic niche and
position of the individual coordinates indicate intraspecic variation in resource use, known as the
niche width (Bearhop et al. 2004). SI approaches to trophic niche determination are the newest of
our dened topics to emerge in SIs on coral reefs (rst paper published in 2007), and it has expanded
rapidly since then (n = 48; Figure 1). This is likely due to the instrumental Layman et al. (2007)
and Jackson et al. (2011) papers which have brought community SIA into the foreground. However,
although related, trophic niches and isotopic niches are not interchangeable, and care should be
taken when using these terms (see Reddin et al. 2018, Hette-Tronquart 2019). In some cases, variation
in SI values may be independent of diet, e.g. where habitat-derived isotopic baselines differ (Figures
3 and 4). Organism foraging behaviour and habitat use must also be considered before converting an
isotopic niche to an ecological or trophic niche (Flaherty & Ben-David 2010).
Isotopic niches
To date, coral reef isotopic niche studies have predominantly explored resource partitioning within
guilds, likely as the high densities of species with seemingly similar functional roles raises questions
as to the mechanisms of their coexistence. This can be elucidated by SI data, revealing dietary vari-
ation and intricacies which were previously overlooked. For example, while traditional techniques
suggest that herbivorous surgeonsh and parrotsh consume similar production sources on reefs,
bulk δ13C and δ13N SI data reveal complex trophic ecologies, indicating a high level of functional
diversity (Plass-Johnson et al. 2013, Dromard et al. 2015). Similarly, isotopic niche overlap (see
Figure 3) among sympatric spotted (Panulirus guttatus) and Caribbean (P. argus) spiny lobsters is
minimal, with each utilising different food sources and occupying unique TPs (evidenced by δ15N) in
the food web (Segura-García et al. 2016). Higher up the food chain, coral reefs have high biomasses
of predators with seemingly similar traits and trophic ecologies. Yet, δ13C and δ13N reveal that sym-
patric species of coral trout Plectropomus laevis and P. leopardus have resource uses that differ
(Matley et al. 2017, 2018). They likewise also vary from other predatory teleosts (Lethrinus miniatus
and Lutjanus carponotatus), implying degrees of trophic specialisation in coral reef mesopredators
(Frisch et al. 2014). Indeed, in the Maldives, the resource uses of seven sympatric teleost reef preda-
tors across multiple families vary both within and among species and spatially, with δ34S acting as
a useful third isotope further differentiating individual feeding behaviours (Skinner et al. 2019a).
Furthermore, on Bahamian reefs, while isotope biplot data (δ13C and δ15N) of the invasive lionsh
(Pterois spp.) and a native snapper Lutjanus griseus appeared to overlap considerably, their core
isotopic niches did not, suggesting competition was not as high as initially perceived (Layman &
Allgeier 2012). These predators appear to occupy the same functional roles within their guilds, but
by partitioning trophic resources both spatially and temporally, inter- and intraspecic competition is
likely reduced, thereby facilitating their coexistence and altering previously assumed ecological roles
(Dale et al. 2011, Gallagher et al. 2017, Matich et al. 2017, Curnick et al. 2019, Skinner et al. 2019a).
Individual specialisation within a population is a mechanism through which sympatric indi-
viduals within an age or size class may reduce competition for resources by focusing on a narrower
set of resources than that of the population as a whole (Bolnick et al. 2003, Araújo et al. 2007,
2011). Occurrences of individual specialisation are expected to be greater where resource diversity
is high, as there is increased ecological opportunity (Semmens et al. 2009, Araújo et al. 2011). Coral
reefs, with their high rates of biodiversity, should therefore be prime locations for occurrences of
individual specialisation. This is compounded for populations with access to two or more adjacent
resource pools (e.g. benthic and pelagic) or habitats (e.g. reef and seagrass), as there is a greater
array of potential resources (Araújo et al. 2011, Matich et al. 2019). SIs are a powerful tool which
can quantify these specialisations and are less costly and labour-intensive than long-term dietary
records (Newsome et al. 2009). To date, studies investigating individual specialisation using SI on
coral reefs have concentrated on elasmobranchs and large predatory teleosts (Shipley et al. 2018,
Shiffman et al. 2019, Skinner et al. 2019a, Wyatt et al. 2019). The degree of specialisation across
lower trophic levels is little explored. However, 34% of SI coral reef studies involve a single species,
which suggests there is sufcient opportunity to investigate individual specialisation more generally
on coral reefs. Indeed, there is some evidence of such specialisation at lower trophic levels; bulk
δ13C and δ13N SI show that damselsh, Dascyllus aruanus, are more specialised when colonies
are larger, suggesting local abundances drive intra-group competition, which is then modulated by
individual specialisation (Frédérich et al. 2010). Groups of damselsh with narrower trophic niches
(evidenced by their isotopic niches using δ13C, δ13N, and δ34S) also have lower genetic diversity, high-
lighting potential links between population and trophic ecology (Gajdzik et al. 2018). Exceptional
variation in feeding strategies from heterotrophy to autotrophy at scales of metres to kilometres
among colonies of the hard coral Pocillopora meandrina has also been identied using δ13C of essen-
tial amino acids, showing no relationship with site or depth (Fox et al. 2019). Although consumer
dietary specialisation does not occur in all systems or between all species (Gallagher et al. 2017),
it warrants further study, particularly in systems where resources are uctuating. If consumers par-
tition resources, their ecological roles may be vastly different, which could be masked by traditional
species- or guild-level categorisations.
Attempts by ecologists to categorise species functional traits to better understand ecosystem
function conicts with the natural variability inherent in complex systems such as coral reefs. SI data
have successfully been used to refute some strict dietary classications of reef organisms derived
from traditional ecological studies using gut contents data and in situ observations. For example,
in Papua New Guinea, of seven damselsh species sampled, their δ13C and δ15N SI values and cor-
responding isotopic niches, indicated that none were strict herbivores, despite traditionally being
classied as such (Eurich et al. 2019). In fact, using δ13C and δ13N damselsh have relatively distinct
isotopic niches, reecting varying degrees of planktonic to benthic reliance (Frédérich et al. 2009,
Lepoint et al. 2016, Olivier et al. 2019). Similarly, cardinalshes, thought to be generalist carnivores
based on stomach contents data, are sustained by production sources from across a benthic-plank-
tonic gradient, and δ13C and δ13N indicate distinct species-specic isotopic niches (Frederich et al.
2017). Indeed, community-wide δ13C and δ15N data show that many strictly categorised reef sh rely
on production sources outside their putative diet source and this spans multiple trophic levels (Zhu
et al. 2019), highlighting how narrow functional group categorisations should be applied with cau-
tion. However, care should be taken when interpreting isotopic spread as solely due to diet variation;
spatiotemporal differences in production source isotopic baselines and a myriad of other drivers
may also cause such variations (Figures 3 and 4; and see ‘Environmental drivers’).
In some cases, there may be greater redundancy among different guilds rather than within them;
δ13C and δ15N SI values of muscle tissue from reef sharks and large teleost mesopredators indicated
that they occupy the same isotopic niche on the Great Barrier Reef, suggesting they perform similar
functional roles (Frisch et al. 2016). Similarly, in the Hawaiian archipelago, there was consider-
able overlap in the δ13C and δ15N values of reef sharks and larger teleosts, highlighting a degree of
functional redundancy which could contribute to ecosystem stability (Hilting et al. 2013, Roff et al.
2016). However, a study further north on the Great Barrier Reef using multi-tissue δ13C and δ13N
data (muscle, blood, and plasma) to compare resource use of reef sharks and large predatory tele-
osts identied signicant trophic separation (Espinoza et al. 2019). While Frisch et al. (2016) call
for apex predator reef sharks to be reassigned as high-level mesopredators, Espinoza et al. (2019)
suggested there is substantial diversity in their trophic ecologies and likely wider functional roles.
This suggests that different localities may have populations with different behaviours. Beyond these
studies of reef mesopredators, few studies compare isotopic niches among differing guilds on coral
reefs, likely because they are expected to have different dietary strategies. For example, overall,
the structure of the reef sh assemblage remains fairly consistent, with herbivores occupying lower
trophic levels (reected by low δ15N), while carnivores and piscivores feed across a broader range of
trophic levels and resources (Carassou et al. 2008, Yang et al. 2012). Most studies comparing niches
and categorisations do so across similar species groups; of the 47 articles assigned to the Trophic
Niche topic, 64% focus on reef sh and 15% on elasmobranchs. Few, if any, compare resource use
across broader groupings (e.g. some invertebrates may feed on the same prey as some reef sh;
Zapata-Hernández et al. 2021), so wider competitive feeding relationships may be missed.
Multi-tissue SI data can reveal detailed feeding strategies and how these uctuate over different
timescales, particularly regarding individual specialisation within a population (Bond et al. 2016). For
example, a multi-tissue (plasma, cartilage and faeces), multi-isotope approach identied consistent
individual specialisation on either oceanic or coastal prey in whale sharks, Rhincodon typus (Wyatt
et al. 2019). Yet, multi-tissue approaches are infrequently utilised on coral reefs. Of the 29% of identi-
ed SI reef studies employing a multi-tissue approach, only 9% measure multiple whole tissue types,
e.g. muscle and liver, of the same individual consumer to elucidate short- and longer-term uctuations
in resource use. Instead, 20% of multi-tissue studies focus on exploring the trophic niches of mixo-
trophic holobionts, e.g. host soft tissue and endosymbionts. For example, the degree of overlap in the
isotopic niches (determined using bulk δ13C and δ15N) of seven different genera of coral hosts and
their endosymbionts was linked to coral trophic strategy; higher overlap indicated resource sharing
between host and endosymbionts (i.e. greater host autotrophy), while lower overlap indicated less
resource sharing (i.e. greater host heterotrophy) (Conti-Jerpe et al. 2020). While multi-tissue analyses
may offer additional insight, comparing isotopic niches among guilds helps in the understanding of
how resource use and partitioning are structured within the wider community. One of the few studies
using SIA to investigate trophic interactions at the community level conrmed previous hypotheses
that the sea cucumber Stichopus herrmanni has a top-down inuence (consistently higher δ15N across
seasons) on its meiobenthic prey in a lagoon system on the Great Barrier Reef (Wolfe et al. 2021).
For inferences to be made about resource use and trophic positions with condence, knowledge
on diet-tissue discrimination factors (hereafter ‘trophic discrimination factor’ (TDF), usual nota-
tion is Δ) between a consumer and their diet are necessary (see reviews referenced in ‘Introduction’;
Boecklen et al. 2011, McCormack et al. 2019, Whiteman et al. 2019). The standard TDFs that are
typically applied to bulk carbon (~0.5) and nitrogen (~3.4) are averages drawn from broader syn-
theses of laboratory experiments, but are known to vary among species, by life stage, and season,
among other factors (Wyatt et al. 2010a, 2019). For example, the estimated Δ15N between the hard
coral Porites lutea and its food source is only 1‰ (Rangel et al. 2019), three times lower than the
commonly applied value. Average TDF values may be appropriate for studies at the ecosystem level,
but greater resolution specicity is required for individual species. To date, very few studies (n 5)
have empirically determined species-specic TDF for coral reef organisms, despite a call for more
lab studies to do so over a decade ago (Wyatt et al. 2010a). Evidence suggests that typically employed
TDFs may not be wholly applicable to coral reef ecosystems: feeding observations and modelling
indicated that three herbivorous reef sh have consistently higher Δ15N (model estimates ranged from
4.30‰ to 5.68‰) than the accepted value of 3.4‰ (Mill et al. 2007). Furthermore, a comprehensive
study using CSIA of >200 samples from 47 species of marine teleosts including many reef sh found
that the estimated TDFAA was signicantly lower (2‰) than previously accepted values for CSIA
(Bradley et al. 2015). Given the huge diversity of organisms on coral reefs, a greater understanding
of how these values vary among species and compounds, and with other factors such as seasonality,
is required (Whiteman et al. 2019) to improve the understanding of coral reef trophic interactions.
One such avenue might involve parasites (an understudied group on coral reefs), which often reect
their host’s feeding ecology and TP (indicated by their δ13C and δ15N values) (Jenkins et al. 2018).
This suggests future research could explore this relationship to better understand the complex trophic
interactions and feeding strategies that could affect reef organism’s TDF values, but SI data between
sh hosts and their parasites are likely to be complicated (Pinnegar et al. 2001).
As time-integrated values of the major source reliance and TP of an organism in the food web,
SI data cannot generally be used to identify specic prey. For example, while bulk δ13C and δ15N
values were similar across four species of mesopredatory teleosts, stomach contents data revealed
substantial differences in the types of prey taxa consumed (Ashworth et al. 2014). Similarly, among
21 species of butterysh, gut contents data and in situ feeding observations were required to resolve
ner-scale differences in prey items (Nagelkerken et al. 2009). SIs are therefore not necessarily suit-
able at differentiating ecological niche differences that vary over smaller scales, especially when
isotopic differences between sources are small. SIs are also unable to distinguish between behav-
ioural differences in feeding: two sympatric species of sh that have approximately the same diet,
but with one feeding nocturnally while the other diurnally, would occupy the same position in
isotopic space (given the same TDFs). It is therefore often useful to combine multiple methodolo-
gies to obtain a comprehensive overview of the complexities of an organism’s feeding strategies
across different temporal and spatial scales on coral reefs. As researchers become more accustomed
to using SI data to understand food webs, the number of isotopic niche studies on coral reefs is
increasing, but other data, including traditional techniques, often complement and add to the infer-
ences deduced from SI data alone (e.g. inclusion of fatty acids; see Dethier et al. 2013).
Drivers of isotopic niche variation
Isotopic niches may vary spatially, particularly in diverse systems such as coral reefs, helping to
explain how species partition resources (Figure 3). This variation can occur across relatively large
scales: across the Southern Line Islands, isotopic niche widths (from δ13C and δ15N) of reef sh
populations change in relation to available primary production (Miller et al. 2019). They may also
change at much smaller scales: bulk δ13C and δ15N data show that several reef shark species have
different patterns of resource use among coastal areas of Florida (Shiffman et al. 2019) and dolphins
have varying levels of coastal vs offshore resource use in Panama (Barragan-Barrera et al. 2019).
While isotopic niche variation can be driven by factors other than dietary preference (Figure 3),
understanding the relationships between SI values and these drivers is non-trivial. For example,
predator biomass inuences the dietary diversity (represented by the δ13C and δ15N isotopic niche
area) of two herbivorous reef sh in the Florida Keys, likely by causing a change in their group for-
aging activities and perceived predation risk (Catano et al. 2014). Other biotic inuences on isotopic
niches include the presence of parasites: ectoparasitic isopods affect the resource use (inferred
through δ13C and δ15N) of grunts, likely causing them to feed in different localities to uninfected
sh, and changing their condition (Welicky et al. 2017). On reefs in New Caledonia, partitioning of
resources indicated by bulk δ13C and δ15N data by two species of sea krait indicated habitat-based
dietary divergence (Brischoux et al. 2010). Environmental conditions may also inuence isotopic
niches: various ow conditions led to differing physiological adaptations of two sympatric bone-
sh species based on δ13C and δ18O data (Haak et al. 2018). These studies highlight how a range
of factors may inuence an organism’s isotopic niche at any one time and underline the inherent
difculty in extrapolating ndings from one location to another. Other factors which may inuence
isotopic niches include growth rate, metabolism, and diet quality; however, to our knowledge, there
are no studies investigating these relationships on coral reefs to date. With few studies investigating
the effect of multiple variables or drivers, or the indirect relationships occurring between them, the
ability to generalise such patterns across coral reef ecosystems is limited.
Anthropogenic impacts can inuence isotopic niches and resource use, as habitats degrade or
prey groups uctuate, but such responses vary among species. For example, corallivores had smaller
δ13C and δ15N isotopic niches at a degraded reef site compared to a healthy reef site, likely reect-
ing a narrower pool of available resources from a loss of live coral cover (Letourneur et al. 2017).
In contrast, invertivores had larger isotopic niches, and herbivores and zooplanktivores displayed
no difference (Letourneur et al. 2017). Similarly, δ15N in spiny lobster muscle tissue did not differ
between reefs of different levels of degradation, with no apparent trend with the loss of habitat struc-
tural complexity (Lozano-Álvarez et al. 2017). The impact of reef habitat degradation on organic
matter sources and the trophic ecology of reefs in the Caribbean (where 14% of SI reef studies have
been conducted; Figure 2) was quantied by Morillo-Velarde et al. (2018), on the basis of switches
or widening in carbon sources as evidenced by reef sh δ13C in degraded habitats. This indicates
that there is a degree of trophic plasticity, with some groups adapting to degradation while others do
not, but there may be a cost to this adaptation. As the biomass of planktonic damselsh decreased
on a degraded reef, δ13C and δ15N of the spotted coral grouper, Plectropomus maculatus, indicated it
switched to foraging on herbivorous damselsh. This switch was linked to long-term declines in the
groupers’ growth rate, fecundity and survivorship (Hempson et al. 2017, 2018), highlighting potential
negative, long-term consequences of anthropogenic impacts across the wider coral reef food web.
Fish diet variation and habitat connectivity
In coral reef SI studies, reef sh are the dominant focal taxa (36% of all articles; Figure 5B) and a
major area of research involves using SIs to determine how their habitat and resource use varies spa-
tially and throughout their life cycle (n = 44 identied studies; Figure 3). Although this topic includes
one of the earliest known papers using SIs on coral reefs (Fry 1982), much of the bulk of the work
on sh trophodynamics was conducted from the late 2000s onwards, with a focus on the western
Atlantic (n = 16) (Figure 2B). While there are thousands of sh species living on coral reefs, only a
few have been the focus of multiple SI studies, namely the whitetail damselsh Dascyllus aruanus
(n = 5), leopard coral grouper Plectropomus leopardus (n = 6), blackspot snapper Lutjanus ehrenber-
gii (n = 5), and the red lionsh Pterois volitans (n = 5). Similarly, coral reef SI studies tend to focus on
common groups (e.g. damselsh, surgeonsh, groupers, snappers), with few to none investigating the
trophodynamics of poorly understood and often cryptic groups such as blennies and gobies.
Ontogenetic habitat shifts
Ontogenetic habitat shifts are common in marine organisms as they strive to maximise their tness
strategies (Schmitt & Holbrook 1985, Holbrook & Schmitt 1988, Dahlgren & Eggleston 2000). In
coral reef ecosystems, it is common for juvenile reef shes to spend time in a nursery habitat, such
as mangroves or seagrass meadows, prior to migrating to the reef (Figure 3). SIA can be a cost-
effective tool to pinpoint when and how these changes occur by analysing the SI values of juveniles
through to adults across the nursery and reef habitats. This allows the timing of the ontogenetic
habitat and diet shifts to be estimated (Cocheret de la Morinière et al. 2003, Frédérich et al. 2012,
McMahon et al. 2012, Berkström et al. 2013). For example, the δ13C of juvenile snappers in man-
groves reect mangrove habitat (23‰ to 17‰), while individuals on the reef shift to a reef δ13C
signature with increasing body size (16‰ to 8‰), indicating that the smaller individuals within
reefs have migrated there from the mangroves (Nakamura et al. 2008). Acoustic telemetry can
be used to further support inferences from SI data; δ13C of n tissue and acoustic tracking of the
schoolmaster snapper, Lutjanus apodus, revealed that they move from bays to coral reefs as they get
larger (i.e. smaller sh mean δ13C 16.7‰, larger sh 12.2‰) (Huijbers et al. 2015).
Fish otoliths, as an incrementally grown, metabolically inert biological structure, provide the
ability to determine when ontogenetic shifts occur within a single individual, and have been uti-
lised across several coral reef SI studies (n = 13). As surface otolith material is continuously depos-
ited with age, a time series of SI data can be derived by sampling progressive segments from the
core (reecting larval life stages) to the edge (age of the sh just prior to otolith sampling). Changes
in SI values will reect potential changes in habitat, diet, or physiology. In the Red Sea, otolith δ13C
essential amino acid values of the blackspot snapper, Lutjanus ehrenbergii, across a gradient from
coral reefs to seagrass were inuenced by the habitats the sh resided in, offering an opportunity to
track their movements across the isoscape (McMahon et al. 2011). In addition to δ13C, some studies
(6%; Figure 2B) use oxygen isotopes (δ18O) in otolith segments (Blamart et al. 2002), as they vary
with temperature and salinity, thus providing information on the external environment. Both δ13C
and δ18O in otolith core and edge segments of the trumpet emperor, Lethrinus miniatus, on the
Great Barrier Reef revealed contrasting movements of juveniles across different latitudes and cor-
responding isotopic environments (Currey et al. 2014). Similarly, δ13C and δ18O of grey, Lutjanus
griseus, and yellowtail, Ocyurus chrysurus, snapper sub-adult otoliths in Florida determined the
distinct nursery areas in the Florida Bay that the sh had migrated to the reef from (Gerard et al.
Otolith SI values can be incorporated into spatial simulation models, revealing that the geo-
graphic distribution of the nursery areas plays an important role in driving the spatial distribution
of the adults on the reefs (Hujibers et al. 2013). Recently, sh eye lenses have also been advocated
as an alternate, metabolically stable, incrementally grown structure with which to track resource
and habitat use shifts with SIs across different life stages (Quaeck-Davies et al. 2018, Curtis et al.
2020, Vecchio and Peebles 2020). Clearly, SI data can be used to delineate sh movement patterns,
tracking animal movements in the absence of electronic tagging, and identifying nursery habitats
that should be prioritised for management; habitat impacts may disproportionately affect certain life
stages thus inuencing populations elsewhere, e.g. recruitment of juveniles to reefs. However, if the
animals move through the habitat before an isotopic signature can be recorded, or if the habitats are
isotopically indistinguishable, then movement information may be missed (McMahon et al. 2013).
As such, the use of traditional approaches in conjunction such as tagging (e.g. Huijbers et al. 2015),
spatial simulation (e.g. Hujibers et al. 2013), and sh size distribution modelling (e.g. Mumby et al.
2004) should be considered.
Body size
Multiple studies indicate that variation in resource use may occur as a function of body size (e.g.
Layman et al. 2005, Romanuk et al. 2011). Indeed, many predatory shes across various biomes
tend to feed at higher TP (evidenced by higher δ15N) as body size increases, a pattern that also holds
true for coral reef systems (Layman et al. 2005, Greenwood et al. 2010). For example, in Moorea,
French Polynesia, plasma of blacktip reef sharks, Carcharhinus melanopterus, was enriched in δ15N
with increasing body size, but there was no change in δ13C, suggesting they were feeding on higher
trophic-level prey, but reliant on the same basal production sources (Matich et al. 2019). Such
trends are, however, far from ubiquitous in coral reefs. For blacktip reef sharks at Palmyra Atoll,
there was a positive relationship between body size and δ15N in one lagoon, but no relationship with
body size at all in another, suggesting that the two shark populations have different trophic ecolo-
gies despite their proximity to one another (Papastamatiou et al. 2010). Similarly, in the Caribbean
reef shark Carcharhinus perezii, there was no relationship between δ15N and body size, but a sig-
nicant positive relationship with δ13C, implying larger individuals relied more on lagoonal food
sources with increasing size rather than feeding at higher trophic levels (Bond et al. 2018). Clearly,
relationships between predator TP and body size are not always positive or absolute (Gallagher et al.
2017, Matley et al. 2017, Shipley et al. 2018, Skinner et al. 2019a, Eddy et al. 2020). This is demon-
strated by the invasive lionsh in the Caribbean, which are smaller than native Nassau groupers, yet
occupy the highest TP in the study region (represented isotopically by higher δ15N) (O’Farrell et al.
2014). These studies highlight how trophic ecology of shes can vary with body size, indicating that
an organism’s ecological role may be complex and life stage- as well as species-specic. However,
for most herbivorous reef sh, TP (represented by δ15N) remains relatively unchanged as body size
increases (Cocheret de la Morinière et al. 2003, Greenwood et al. 2010, Plass-Johnson et al. 2013,
2015a). This is likely as, although they may access different resources with increasing body size, the
δ15N of these basal production sources remains fairly similar.
Despite being lesser studied, similar trends with body size have also been observed in inver-
tebrates. The reworm, Hermodice carunculata, a facultative corallivore, is enriched in δ15N and
has uctuating δ13C with increasing body size, potentially reecting feeding at higher trophic levels
while diversifying resource use across ontogeny (Wolf et al. 2014). It should be noted, however,
that body size relationships with SIs assume there is minimal change in isotopic baselines and
growth/metabolic inuences on isotopes independent of diet (e.g. constant TDFs across ontogeny).
Intraspecic and life-stage feeding specialisations, such as these, may help promote population
resilience to environmental change, as individuals and populations are reliant on a wider range of
resources across ontogeny. However, given that many of the anthropogenic impacts on reef shes
are size- and species-selective, with many targeted sh often larger and functionally important
(Benoît & Swain 2008, Lokrantz et al. 2009, Plass-Johnson et al. 2015a), this may have serious
consequences for the trophodynamics of the coral reef food web.
Residency and population connectivity
SIA can reveal an organism’s residency within a habitat at various life stages, representing a more
cost-effective approach than tagging or tracking. This can be useful for the management of certain
species when assessing the efcacy of protected areas. In Australia, δ13C and δ15N values of reef
sh liver and muscle revealed three species were resident in the area, while others had migrated
from coastal riverine habitats (Davis et al. 2015). In western Australia, δ13C and δ15N of muscle
tissue of several reef sharks in coastal habitats conrmed residency was high across four species
(Speed et al. 2012). Examination of δ13C and δ15N in lionsh, Pterois volitans, muscle tissue showed
they did not move between mangroves and reefs; in fact, there was no overlap in habitat or resource
use of lionsh between habitats, conrming them as site-attached opportunistic foragers (Pimiento
et al. 2015). SI data can also help assess the importance of different habitats to more mobile consum-
ers that have larger home ranges; for example, one of the few studies to use δ13C, δ15N, and δ34S to
examine habitat residency determined that the reef manta ray, Manta alfredi, was heavily depen-
dent on lagoonal resources, suggesting long periods of residency in the lagoon (McCauley et al.
2014). Combining SI data with fatty acids further revealed that M. alfredi are secondary consumers
that rely on both epipelagic and demersal zooplankton, reecting their ability to access disparate
resources through vertical and horizontal movements (Couterier et al. 2013). While SI data can
provide much needed insight into movement patterns and habitat usage, it should be noted that con-
nectivity ultimately depends on the spatial conguration of the seascape (Nagelkerken et al. 2008,
Rooker et al. 2018).
Larval population dynamics are inherently more difcult to study; larvae are hard to follow
due to their high natural mortality and rapid dispersal by ocean currents (Cowen & Sponaugle
2009). Nevertheless, SI approaches provide an opportunity to track larval dispersal and understand
population connectivity more easily. Transgenerational isotope labelling involves injecting adult
female sh with labelled isotopes (137Ba) and results in consistently and permanently marked larvae
throughout a reproductive season. This method has minimal impact on the sh, their eggs and lar-
vae as they develop, or on those that consume them (Williamson et al. 2009a,b, Roy et al. 2012, Cuif
et al. 2014). By analysing the SI values of the otolith cores of the new cohorts, the degree of connec-
tivity and self-recruitment within a population can be determined. In New Caledonia, this approach
revealed that self-recruitment of damselsh Dascyllus aruanus varied signicantly between months
and years, but was independent of the proportion of self-recruits within the population (Cuif et al.
2015). This suggests that self-recruitment can successfully indicate population openness, but may
not relate to population persistence (Cuif et al. 2015).
Habitat connectivity
There are important exchanges of organisms and energetic material between coral reefs and other
adjacent habitats that can be difcult to measure (Polis & Strong 1996, Huxel & McCann 1998).
SI data offer distinct opportunities to identify these cross-system linkages and quantify uxes
across habitat boundaries; the ow of nutrients into and across shallow coral reef ecosystems is
increasingly being documented (Figure 3). In shallow-water reef habitats in the Caribbean, δ13C
suggests that benthic algae and seagrass contribute 48%–76% of carbon to reef sh (Fry et al.
1982), but in Moreton Bay, in eastern Australia, dietary proportions vary with distance to adjacent
mangrove and seagrass habitats (Davis et al. 2014). Such patterns are not necessarily surprising;
however, they highlight that contributions of various exogenous materials to reefs are likely to be
site-dependent due to varying seascapes (Briand et al. 2015). Nevertheless, looking at the wider
spatial context can reveal less intuitive habitat linkages. In the Chagos Archipelago, rats interrupt
nutrient ows between pelagic, coral reef, and island ecosystems. Rat-free islands had signi-
cantly greater densities of seabirds and therefore larger deposits of nitrogen and subsequent run-
off, leading to higher δ15N in the soil, macroalgae, turf algae and reef sh compared to rat-infested
islands where seabird densities were lower (Graham et al. 2018). Sulfur isotopes (δ34S) have rarely
been applied to infer habitat connectivity, but they may be well placed to distinguish and identify
sources produced under anaerobic conditions, e.g. decomposition of mangrove organic matter, due
to the strong fractionations that occur during such processes (Okada & Sasaki 1998, Granek et al.
2009). More widely, mangrove, microalgae, macroalgae, and seagrass exhibited greater separation
in δ34S compared to δ13C in a study conducted in Bocas del Toro (Panama) (Granek et al. 2009).
Used together, δ34S and δ13C suggested that mangrove-coral reef nutrients contributed up to 57%
to the biomass of sessile reef invertebrates (Granek et al. 2009). SI data thus point to mangroves
as an important source of nutrients for adjacent reef consumers (Carreón-Palau et al. 2013, Briand
et al. 2015) despite their apparent low labile organic matter content and nutritional quality (Granek
et al. 2009).
While common in the deep sea, chemosynthesis has rarely been explored as a potential source
of nutrient exchange for shallow water marine food webs (Table 3), yet SI data point to chemosyn-
thesis being important for some consumer species on coral reefs. δ34S, together with δ13C and δ15N,
provides evidence that chemosynthesis in lucinid clams supports 20% of the diet of Caribbean spiny
lobster (Higgs et al. 2016). They therefore play an important part in transferring the chemosyn-
thetically xed carbon into reef food webs (Higgs et al. 2016). While there are undoubtedly many
energetic connections between coral reefs and adjacent habitats, the intricacies of many have yet to
be fully identied. This should be addressed going forward given that such subsidies are expected
to contribute to wider ecosystem resilience and stability (Bascompte et al. 2005).
Predators, typically being more mobile, often have greater opportunity to feed across ecosystem
boundaries, playing an important ecological role in connecting distinct food webs (Figure 3). While
tracking studies can identify these predator movements (e.g. Papastamatiou et al. 2009, Heupel &
Simpfendorfer 2015), they cannot in isolation dene the role of predators in nutrient cycling. This
is in contrast to SI data that offer an opportunity to track these energetic linkages. In Palmyra atoll,
δ13C and δ15N from muscle tissue of blacktip reef sharks, Carcharhinus melanopterus, grey reef
sharks, C. amblyrhynchos, and red snapper, Lutjanus bohar, indicated they relied on pelagic pro-
duction sources from outside their primary fore reef habitats, playing a key role in providing eco-
logical coupling as cross-system foragers (McCauley et al. 2012). The reef manta ray, Manta alfredi,
also constructs an important link between adjacent pelagic and reef/lagoonal systems (evidenced by
δ13C and δ15N) by feeding on pelagic zooplankton, which is then excreted over shallow reefs (Peel
et al. 2019). In fact, many reef predators are similarly subsidised by pelagic inputs (evidenced by
δ13C, δ15N, and δ34S), likely arising through their feeding on reef-based planktivorous sh, suggest-
ing they play an important role in reef-pelagic connectivity (Frisch et al. 2014, 2016, Matley et al.
2018, Skinner et al. 2019b).
Energetic connections across depth ranges have also been identied using δ13C, δ15N and δ15NAA
in combination with acoustic telemetry. Galapagos sharks, Carcharhinus galapagensis, and giant
trevally, Caranx ignobilis, forage in both shallow- and deep-water mesophotic reef habitats, trans-
porting nutrients between them (Papastamatiou et al. 2015). In some cases, these energetic linking
movements may be nocturnal. δ13C and δ15N data combined with acoustic telemetry revealed that
the grunt, Haemulon plumierii, in the Caribbean is predominantly sustained by organic matter from
habitats they visit at night, likely to minimise encounters with barracuda (Rooker et al. 2018). These
studies highlight the potential for SIs to complement and enhance inferences from acoustic telem-
etry or tracking data, by providing detailed information on energy uxes which may help elucidate
organism movements. Although SI studies documenting cross-system linkages are increasing, only
13% of the studies in this topic have focused on sharks, despite their acknowledged important role
in nutrient transfer (Williams et al. 2018b). There is therefore much that remains to be understood
about energy subsidies to and from coral reefs, particularly the generality of the role that these
mobile organisms play in establishing them.
Production source use in coral reef consumers can be difcult to dene compared to other,
simpler systems with fewer energy pathways. A signicant overlap between the myriad of reef-
associated sources (Figure 4; Table 3; and see ‘Organic matter dynamics’) often makes it impossible
to clearly identify, for example, carbon sources over a reef using bulk δ13C data. As such, isotope
modelling to condently assign consumers to energy sources in such ‘underdetermined’ systems
becomes impractical (Fry 2013). The use of CSIA of amino acids (CSIA-AA), particularly essential
amino acid carbon isotopes (δ13CEAA), which exhibit minimal discrimination between resources
and consumers across the food web, has great potential to help resolve carbon resources over reefs
due to the increased dimensionality of the data. This technique effectively separates benthic versus
planktonic pathways, further separating the latter into distinct nearshore reef-associated plankton
and offshore pelagic plankton groups (Skinner et al. 2021). Analysis of consumer tissue δ13CEAA
allows the source of primary productivity supporting consumers to be identied with more preci-
sion than is possible with bulk δ13C. Less consideration of variations in isotopic baselines and
TDFs is required when interpreting δ13CEAA data, which can often confound inferences from bulk
SI data. Surprisingly, δ13CEAA data suggest that even highly mobile top predators may rely predomi-
nantly on a single carbon source at the base of the food web. For instance, in the Red Sea, δ13CEAA
data suggested that the snapper, Lutjanus ehrenbergii, and giant moray, Gymnothorax javanicus,
may receive >70% of their C from a single end-member, phytoplankton, indicating quite tightly
linked food chains supporting these predators (McMahon et al. 2016). Similarly, in the Maldives,
several species of grouper were primarily supported by offshore pelagic plankton across an oceanic
atoll (73%–86%; Skinner et al. 2021). Contrasting δ13CEAA within more wide-ranging apex predators
like the tiger shark, Galeocerdo cuvier, could provide important information on the role of mobility
in integrating across ocean and reef food webs (Hilting et al. 2013, Frisch et al. 2016).
Environmental drivers
It is intuitive following the identication of spatial and temporal patterns in data for scientists to try
and elucidate the underlying processes and mechanisms that give rise to them. Despite the complex-
ity of coral reefs, SI-based studies focusing on particular components of these ecosystems often infer
the key drivers at play that underpin observed trends. This is evident in all of the preceding topics,
where studies attribute the importance of inherent environmental and biological factors (see, for
example, ‘Organic matter dynamics: spatial and temporal variations’ and ‘Holobiont metabolism:
drivers of mixotrophy’). However, there are a collective of SI studies that specically investigate the
general role spatial and temporal forcings play on coral reefs, providing context for other studies
utilising SI approaches (n = 48 identied topics). These environmental drivers can be broadly sepa-
rated into two categories: natural drivers and anthropogenic drivers (Figure 3). The rst category
investigates how the isotopic composition of various components of coral reef ecosystems responds
to a range of natural variables such as depth, resource availability, and salinity. Hard coral (n = 17 )
and reef sh (n = 5) are the dominant focal taxa in this regard, with most studies conducted in the
Caribbean (n = 10), the Red Sea (n = 6), or the Central Pacic (n = 6) (Figure 2B). The second category
almost exclusively focuses on measuring SIs in structure forming organisms, that is marine plants
(n = 9), soft corals (n = 6), and hard corals (n = 6), to explore anthropogenic nutrient inputs to coral
reef communities, but also considers the impacts of thermal stress. These are conducted mostly in
the Caribbean (n = 7) or the western Pacic (n = 6) (Figure 2B).
Natural drivers
Environmental conditions and nutrient availability uctuate across both ne and broad spatial and
temporal scales. Much like those of the holobionts (see ‘Holobiont metabolism’), primary producer
and higher consumer SI values may reect this variability (Figure 4; Tables 3 and S6), as organ-
isms alter their resource use accordingly and/or integrate isotopic differences in production base-
lines. For example, gradients in resource availability exist across coral reef habitats depending on
their proximity to open ocean resources (Wyatt et al. 2013). Primary producers have higher δ15N
baseline values on outer reefs compared to lagoon regions (Page et al. 2013), and many reef sh
are increasingly reliant on oceanic nutrients with proximity to the open ocean (Wyatt et al. 2012b,
Gajdzik et al. 2016, McMahon et al. 2016). In New Caledonia, δ13C provided clear evidence of spa-
tial changes in the primary sources of carbon across a reef habitat, with increased oceanic inputs on
the outer slopes (grouped teleosts mean δ13C 17.9‰) compared to increased internal subsidies in
the lagoon (grouped teleosts mean 14.8‰) (Le Bourg et al. 2017). Interestingly, δ15N data did not
demonstrate any differences in food chain length or trophic level, supporting the idea of consistent
food web structure across the reef scale despite differences in production sources supporting that
structure (Le Bourg et al. 2017). At a regional spatial scale, Zgliczynski et al. (2019) similarly did
not nd strong isotopic evidence of shifts in foraging patterns in a range of species and functional
groups across the central Pacic. Isotopic changes were attributed to baseline changes across the
~1000 km scale oceanographic gradient studied and taken as indicative of regional consistency in
foraging (Zgliczynski et al. 2019). This demonstrates that coral reef food webs will often reect
uctuations in resource availability and illustrates how SI data can be used to test ideas about spatial
and temporal variation in key trophodynamic processes at different scales, and the factors likely to
be driving these.
If assessed in the context of well quantied temporal and spatial isotope baselines, SI data
can demonstrate spatial changes in organic resource use that have signicant implications for
reef food web structure (Glass et al. 2020). Such changes can be exceedingly difcult to observe
with traditional techniques such as feeding studies. As an example, bulk δ13C and δ15N data sug-
gested a switch between planktivory and herbivory between fore and back reef environments for
both nominally planktivorous and herbivorous species (Ho et al. 2009, Wyatt et al. 2012b). At
Ningaloo Reef (western Australia), δ13C and δ15N modelling suggested that nominally herbivo-
rous Stegastes spp. derived over half their diet from the plankton in more oceanic habitats while
planktivores increased herbivory in the back reef (Wyatt et al. 2012b). On a reef at in Okinawa
(Japan), δ13C, δ15N, and fatty acid data showed that the algal gardening damselsh Stegastes
nigricans supplemented its diet with unexpectedly large amounts of animal material for a her-
bivore (Hata & Umezawa 2011). This suggests that notions of resource reliance in reef consum-
ers may need to be more exible. Using δ13CEAA, McMahon et al. (2016) showed that while S.
nigricans gained the majority (75%) of their dietary C from macroalgae, in more oceanic habitats
13%, and up to 30% for some individuals, came from phytoplankton. Importantly, the error on
the estimates from the δ13CEAA data was much lower than from bulk SIA observations. It is not
clear whether such changes reect real spatial differences in actual food web structure, however
(McMahon et al. 2016), as SI data cannot distinguish between active consumption or incidental
ingestion of particular sources that can be inuenced by exposure rates and therefore spatial
proximity and foraging strategies.
Interactions between the complex topography of reefs and hydrodynamic processes that alter
physical and biogeochemical conditions such as internal waves and upwelling can lead to highly
variable isotope ratios in reef organisms across depth ranges at the same location. As light avail-
ability decreases with depth so, generally, does coral autotrophy; coral host tissue δ13C values
become closer to oceanic carbon values through feeding (Muscatine et al. 1989, Gattuso et al. 1993,
Lesser et al. 2010, Crandall et al. 2016). Coral skeletal δ13C values also reect uctuations in light
and heterotrophy because they are inuenced by metabolic fractionation; decreasing light and
zooplankton levels resulted in signicant decreases in coral skeleton δ13C (Grottoli & Wellington
1999, Grottoli 2000). Furthermore, both host and endosymbionts are depleted in 15N with depth,
with impacts on endosymbiont growth rates (Muscatine & Kaplan 1994).
This pattern of trophic zonation (i.e. where coral heterotrophy increases with depth) is not
always consistent, however. Some evidence suggests that increasing depth does not necessarily result
in increased heterotrophy as is typically expected (Einbinder et al. 2009), with observed changes in
δ13C along depth axes potentially driven by internal carbon cycling processes once other biological
traits are accounted for. Controlled feeding experiments of Reynaud et al. (2009) found no effect of
ambient light levels on internal nutrient metabolism. They did, however, identify increased nitrogen
cycling of host metabolic waste products to endosymbionts when heterotrophic feeding was
limited, by tracing bulk δ15N through different tissues. This is in contrast to carbon metabo-
lism, which appears to change with irradiance levels when heterotrophic feeding occurs, with
increasing rates of photosynthesis and carbon translocation from endosymbionts to coral host
under high light conditions (Tremblay et al. 2014). At Palmyra Atoll, δ13C and δ15N data sug-
gested that increases in coral heterotrophy with depth were absent at sites where resources were
assumed to be readily available from extensive water mixing (Williams et al. 2018a). Similarly,
in one of the few studies to use both δ13CAA and δ15NAA, while autotrophy was the dominant
source of carbon to the hard coral Stylophora pistillata, heterotrophic energy contributions
were equal across shallow (5 m) and deep (60 m) reefs (Martinez et al. 2020). Furthermore, SI
data reveal that some species are heterotrophs throughout their depth ranges (Alamaru et al.
2009a, Crandall et al. 2016, Radice et al. 2019) or vary in their degree of heterotrophy across
depths based on sampling region (Santos et al. 2021). Even within the same genus and at the
same location, SI values (δ13C and δ18O) show that three species of Madracis differ in their
depth adaptations and ecological plasticity (Maier et al. 2003), indicating that this phenom-
enon could depend on prey encounter, resource availability, and resource acquisition (Maier
et al. 2010, Plass-Johnson et al. 2015b, Fox et al. 2018, Santos et al. 2021). Indeed, Leichter
et al. (2007) suggested that depth gradients in reef macroalgal SI values can reect gradients of
exposure to offshore nutrient sources, such as increased use of deep-water nitrate by macroalgae
exposed to high-frequency upwelling. Conversely, variability in SI values (δ13C, δ15N, and δ18O)
in two abundant macroalgal species over scales of 10s of metres were perhaps independent of
depth and instead reected large amounts of spatial heterogeneity (Stokes et al. 2011). Clearly,
there are limited universal trends with depth that can be identied thus far on coral reefs, which
suggests that biological traits and their plasticity may play a signicant role in buffering effects
of physical drivers over a species’ observed distribution.
CSIA can be especially powerful in examining variability in resource use across environ-
mental gradients that could inuence tissue SI signatures independent of diet changes. While pri-
mary producer bulk SI values vary across regions and seasons (Figure 4; Tables 3 and S6), which
can confound interpretation of dietary changes, CSIA measures individual compounds which are
shaped by the biochemical processes of the primary producers and are thought not to vary spa-
tially, temporally, or with growth rates (Whiteman et al. 2019). Using CSIA, Papastamatiou et al.
(2015) were able to discount the isotope baseline as a source of variation in the bulk SI data of
giant trevally (Caranx ignobilis) from deep-water reefs on a Pacic atoll; differences were due to
individual trophic exibility, with trophic positions determined with CSIA-AA ranging from 3.5
to 4.6. Acoustic tracking demonstrated individual variability in diel migration and feeding behav-
iour leading to a range of trophic positions, perhaps reecting individual foraging preferences
and intraspecic competition (Papastamatiou et al. 2015). By demonstrating changes in δ15NAA
derived TP of spiny and slipper lobsters across large spatial scales in the north-western Hawaiian
Islands, which were thus independent of baseline isotope variation, O’Malley et al. (2012) robustly
demonstrated that spatial variability in growth was due to different responses between the two
species to limited prey availability. Resource availability across spatial gradients thus may be
a driver of consumer SI values. Of two obligate corallivore butterysh that both preferentially
feed on Acropora coral, δ13CAA reveal that the specialist Chaetodon baronessa is more selective
with depth and continually seeks out Acropora despite decreased availability, while the generalist
Chaetodon octofasciatus becomes more exible with depth (MacDonald et al. 2019). Furthermore,
while planktivores have a consistent feeding strategy across shallow to mesophotic reefs, benthic
invertivores and omnivores have signicantly broader niches (with benthic invertivores also occu-
pying a higher TP) (Bradley et al. 2016). These studies highlight the trophic versatility of many
reef organisms along spatial gradients.
Anthropogenic drivers
Land and seascapes are under increasing pressure from human activities worldwide, and shallow coral
reef ecosystems are particularly vulnerable to these threats (Figure 3); coral bleaching events are now
occurring every six years or less (Hughes et al. 2017). Bulk δ18O SI values can reveal when a coral
has been subjected to extreme thermal stress by directly relating the δ18O values to in situ temperature
(Porter et al. 1989, Mayal et al. 2009). SIs can also identify how the coral animal host and endosym-
bionts alter their trophic strategies and resource use in response to bleaching events (see ‘Holobiont
metabolism: exogenous factors’). Over the longer term, pulse-chase experiments using 13C-labelled
bicarbonate revealed that some corals may increase their use of heterotrophic carbon for up to a year
after bleaching, but it is not known whether this is a sign of resilience or prolonged stress (Hughes
& Grottoli 2013). Generally, it seems that different coral species have different bleaching responses,
with some maintaining energy reserves or heterotrophic capacity, but most recovering within a year
if the bleaching is a mild and isolated event (Grottoli et al. 2017, Levas et al. 2018). There is currently
little understanding of how coral and endosymbionts trophic strategies will change through successive
bleaching events, despite predictions that these will occur ever more frequently. Furthermore, studies
assessing thermal stress effects using SIs have focused on corals, with few, if any, investigating these
impacts on other holobionts. For non-symbiotic organisms, Vaughan et al. (2021) suggested increases
in δ15N (~1 ‰) in natural and transplanted macroalgae, Sargassum mangarevense, were linked to the
release of coral-derived nutrients post-bleaching. While a better understanding of SI changes in reef
biogeochemical cycles post-bleaching is required (but see Radice et al. 2021), it is crucial to under-
stand and measure the underlying natural variation in SI source data when making inferences, i.e. by
measuring the underlying δ15N baseline.
Global bleaching events and declines in live coral cover have been linked to declines in struc-
tural complexity, coral biodiversity, and the abundance and diversity of reef-associated shes
(Jones et al. 2004, Carpenter et al. 2008, Pratchett et al. 2018). Overshing also contributes to the
latter, while simultaneously reducing sh-mediated storage and supply of nutrients by up to 50%
(Allgeier et al. 2016). These drivers may be reected in consumer SI values. For example, as the
amount of rubble increases along a habitat disturbance gradient, there are signicant differences
in the δ13C and δ15N ranges and the isotopic niche area of the parrotsh Chlorurus bleekeri,
the foraging of which varies according to the surrounding habitat (Plass-Johnson et al. 2018).
Similarly, as prey densities uctuate in response to declines in structural complexity, the peacock
grouper Cephalopholis argus maintains their TP (as indicated by their δ15N) by switching forag-
ing modes from ambush to widely active foraging (Karkarey et al. 2017). Loss of habitat struc-
tural complexity is predicted to cause a threefold reduction in shery productivity (Rogers et al.
2014). However, some species such as the peacock grouper may be more resilient to habitat loss
than previously thought, as their foraging plasticity may enable them to adapt to coral degradation
(Karkarey et al. 2017). In addition to habitat loss, ocean acidication (i.e. reductions in oceanic
pH through elevations in partial pressure of seawater CO2 (pCO2) due to increasing global carbon
emissions) may negatively impact calcifying marine organisms. By studying coral skeleton δ13C
and δ18O values, Zhou et al. (2016) determined that Acropora gemmifera photosynthesis and cal-
cication were only impaired at the highest pCO2 treatment, with their microbial communities
remaining stable. More recently, benthic communities have been exposed to increased pCO2 and
warming in mesocosms to determine how trophic architecture (represented by organism δ13C
and δ15N) would respond under future scenarios (Nagelkerken et al. 2020). While trophic pyra-
mids and community structure (i.e. biomass and productivity) shifted, the food web architecture
remained inexible and stabilising processes were absent, suggesting a lack of adaptive capac-
ity in the ecosystem (Nagelkerken et al. 2020). SIs therefore offer a unique opportunity to study
potential impacts of changing environmental conditions on organism and whole food web trophic
ecology (Plass-Johnson et al. 2018).
SI data offer great potential for exploring other anthropogenic impacts on coral reef food webs,
notably the role of human-derived pollutants in reef systems. By measuring SI values of various
reef organisms, these nutrient inputs can be identied to determine the extent of their impact on
the local reef communities (Yamamuro et al. 2003). Elevated δ15N values in sampled organisms
have suggested articial nutrient inputs to reef communities pertaining to aquaculture (Herbeck
et al. 2014), shoreline sewage (Todd et al. 2009, Baker et al. 2017, Abaya et al. 2018, Lachs et al.
2019), stormwater discharge (Lapointe and Bedford 2011), seepage water (Mwaura et al. 2017), river
plume pollution (Risk et al. 2014), and even wood pulp efuent (Schleyer et al. 2006). This high-
lights how spatially explicit context is required to determine the role of pollution in nutrient cycling
of nearshore reefs and ow on effects for other taxa like coral (Umezawa et al. 2002, Huang et al.
2013, Adam et al. 2021). While most of these studies use macroalgae as bio-indicators of pollution,
seagrass δ15N has also been proposed as a tool to monitor time-integrated changes over coral reef
habitats; there are fewer seagrass species than the diverse macroalgae that are found across reefs,
facilitating both identication and standardisation (Yamamuro et al. 2003). Indirect incorporation
of anthropogenic inputs can result from connectivity to the pelagic food chain and reef planktivore
grazing. Lower δ13C and higher δ15N in two damselshes demonstrated how POM released from
nearby sh farms in southern Taiwan can enter coral reef food webs (Jan et al. 2014). One of the
few studies to employ sulfur isotopes to examine anthropogenic inputs attributed decreasing δ34S
in coral skeletons off Yoron Island to rain-driven inputs of low δ34S terrestrial material from sugar
cane-dominated farmland (Otani & Nakanishi 2019). Oxygen isotopes may also be useful in anthro-
pogenic impact monitoring, with shifts in δ13C and δ18O in coral skeleton correlating with local oil
spills (Xu et al. 2018). However, studies need to be cautious when using taxon-specic variations in
tissue isotopes to infer nutrient uxes based on SI data, especially across small ranges that might be
explained by metabolic or hydrodynamic variations (see ‘Natural drivers’), which is especially the
case for coral skeleton. Relationships between anthropogenic nutrient inputs and SI data, and subse-
quent ecological effects may be more nuanced. For example, a long-term experiment involving δ13C
and δ15N in the hard corals Acropora palmata and Porites porites showed that moderate doses of
anthropogenic nutrients had no additional effects and the corals continued growing (Allgeier et al.
2020). However, models revealed that nutrient and carbon ows were dominated by the symbiont,
leading to algal dominance in the holobiont and greater algal demand on coral resources, likely
increasing the corals’ future vulnerability to bleaching due to stress (Allgeier et al. 2020).
It should be emphasised that elevated δ15N values alone are insufcient evidence of anthro-
pogenic impacts over reef ecosystems. There is an extensive range in natural isotope abundances
in the ocean in the absence of anthropogenic inputs; isotope effects across the marine nitrogen
cycle span approximately 0.5‰ to +38‰ (Sigman et al. 2009). Increased macroalgal δ15N with
depth can be indicative of upwelling increasing dissolved nitrogen availability, rather than a sewage
impact (Huang et al. 2013). Instead of anthropogenic sources (e.g. Lapointe 1997, Lapointe et al.
2005), POM isotopic variations may reect mineralisation of organic material and nitrication
along with inputs of DIN from upwelling, run-off, sediments, and the atmosphere (Lamb & Swart
2008). Natural N cycling and resultant isotopic variation could account for δ15N variations in ben-
thic components of the reef. For instance, Lapointe et al. (2005) reported algal δ15N elevated by
+2‰ as indicative of land-based pollution; however, the range in POM δ15N across the Florida Keys
varies over a 20‰ range with a standard deviation of ±3.6 ‰, apparently independent of human
inuences (Lamb & Swart 2008). This underscores the importance of understanding spatial and
temporal variations in potential source isotopes (Figure 4; Table 3), due to, for example, water
column sources and upwelling (Leichter et al. 2007), before invoking anthropogenic perturbation.
This is especially important where the variations are small (e.g. a few per mil or less) relative to a
potential natural range of SI data variations.
Due to their incremental growth, corals, and in particular gorgonians, provide an opportu-
nity to investigate long-term trends in anthropogenic nutrient inputs. The biochemistry of skeletal
banding reects the ambient nutrient levels and can therefore be used to infer long-term pollution
trends (Ward-Paige et al. 2005). Indeed, gorgonian δ15N values accurately reect tourism levels
over multiple years, with declines in δ15N linked to declines in tourism and increases in δ15N linked
to its recovery (Baker et al. 2013b). Hard coral skeletons can track anthropogenic nitrogen uc-
tuations over decades with 15N enrichment linked to increasing sewage levels and population den-
sity (Duprey et al. 2017, 2020). Archived museum samples may provide another means to monitor
human pollution levels over longer time spans. Gorgonian samples from a 143-year time span had
δ13C and δ15N values which reected increasing atmospheric CO2 and use of agricultural fertilisers,
respectively (Baker et al. 2010), while samples in Bermuda spanning 50 years reected changes in
management policies which were effective in reducing local pollution levels (Baker et al. 2017).
Despite the wealth of information they can convey on prior isotopic baselines, the use of archival
samples is exceedingly low across SI reef studies (n 3).
Knowledge gaps, caveats, limitations, and future directions
Throughout this review, we have summarised the key ndings of studies that have used SIs to under-
stand coral reef ecosystems. In doing so, we have highlighted that there are still areas where research,
knowledge, and understanding are lacking. This should be taken as an opportunity to focus future
research. Below, we have included a numbered list of identied gaps and opportunities for future SI
studies. Given the logistical ease for researchers to now obtain and analyse SI data, we also emphasise
why care must be taken not to misuse or overinterpret SI data. The Knowledge gaps and opportuni-
ties section is followed by important Caveats and limitations which must be considered. We hope that
these points serve as a roadmap to direct future research involving SIs on coral reefs.
Knowledge gaps and opportunities
1. Improve characterisation of basal sources. Corals have been the focus of much SI research
due to their foundational importance, but the living proportion of whole reefs that they cover
is generally low. Conversely, ‘turf algae’ cover a greater surface area and are intensively
grazed, but there is sparse understanding of the fate of turf-derived uxes in the ecosystem.
Similarly, substantial uxes of detritus are derived from benthic reef sources both directly
(e.g. exudates) and secondarily (e.g. grazer defecation), but the detrital pool, its origins and
uxes are little resolved. SI data, both bulk and CSIA, have a lot to offer well-focused
investigations which can advance our understanding of these lesser studied uxes on reefs.
2. Extend sampling over longer time frames. Resource availability on coral reefs uctuates
through time a nd consumer resource use may vary accordingly. However, to date, ma ny coral
reef SI studies sample during a single time point or limited temporal window (Figure 5A).
Future studies exploring the dynamics and stability of coral reef ecosystems should con-
sider longer time periods over which inferences can be made. Multi-tissue approaches are
one technique which may reveal dietary variations across a range of timescales from a
single individual, yet currently, only 9% of studies measured multiple tissues within the
same individual organism. Employing a multi-tissue approach by sampling faster turnover
tissues, e.g. organs and blood, in addition to slower turnover tissues, e.g. muscle tissue,
could better discriminate dietary consistency or the lack thereof (Wyatt et al. 2019).
3. Employ an isoscape approach. To date, and likely due to their inherent complexity, there
are few studies employing an isoscape approach on coral reefs. However, isoscapes of coral
reef ecosystems could offer valuable insight into the complex processes that might inuence
coral reef trophodynamics and SI values across various locations (Figure 4; Table 3). For
example, spatial variations in the relative importance of different production sources to reef
food webs are evident. Given that environmental conditions are uctuating due to climate
change, there is a need for studies examining the drivers of these likely differences in coral
reef ecosystems, which could be facilitated by a broadening of the spatial scale across which
studies are conducted. Isoscapes provide a solid isotopic foundation of a region, providing the
context upon which other avenues of research can be conducted (McMahon et al. 2013).
4. Explore trophodynamics across the wider community. SI data have helped to highlight
that categorising reef consumers into simple trophic groups masks dietary specialisations
and the complexities of this dynamic system. However, few studies compare niche dynam-
ics and resource partitioning outside of species groups or guilds. For example, most stud-
ies that focus on reef sh do not consider how invertebrates occupying the same TP may
share similar resources (but see Zapata-Hernández et al. 2021). A better understanding of
trophic interactions across the wider reef community is required. This will help understand
the importance of potential competitiveness among disparate taxa on coral reefs. Given
increased feasibility, this body of knowledge is expected to grow, and it will be important
for greater resolution to be assimilated into whole ecosystem models.
5. Quantify species-specic TDF and tissue turnover rates. To date, few studies have accu-
rately quantied species-specic TDF and isotopic turnover rates (i.e. the time it takes for
a given consumer tissue to reect the isotopic composition of its diet) across different tis-
sue types for coral reef consumers. While this will be challenging to determine for species
with longer turnover times (e.g. hard coral; Tanaka et al. 2008), it is highly recommended
that more laboratory feeding studies be conducted. Where environment- and species-
specic TDF are not available, analyses must rely on TDF across a range of values to
account for uncertainty surrounding the inherent variability (e.g. likely 1‰ SD for Δ15N).
6. Consider parasites. Parasites may be involved in >50% of food web links, but they are
rarely considered in food web science (Dunne et al. 2013). Indeed, on coral reefs, there
are estimated to be ten times more parasite species than sh species (Justine et al. 2012).
In addition to their huge biodiversity, parasites can affect food web structure indirectly
by modifying their host’s behaviour and subsequent resource use (Welicky et al. 2017).
Despite their important ecological role in shaping trophic interactions in coral reef eco-
systems, parasite trophodynamics on reefs are poorly understood. While several more
recent studies are beginning to address this knowledge gap (e.g. Jenkins et al. 2018, 2020,
Riekenberg et al. 2021), few have considered parasite life-stage dietary shifts.
7. Measure other isotopes. Despite limited application on coral reefs to date, bulk δ34S
shows promise for distinguishing among reef production sources and revealing consumer
habitat use (Connolly et al. 2004, Granek et al. 2009, Skinner et al. 2019a). Moreover,
recent advances in SI technology mean that δ13C, δ15N, and δ34S can now be measured from
the same sample aliquot with a high level of precision (Fourel et al. 2015). Similarly, to
our knowledge, there are currently no coral reef SI studies that utilise mercury isotopes
(δ202Hg), which can characterise resource partitioning and identify foraging depth separa-
tion among predators in marine environments (Besnard et al. 2021). Given the myriad
of co-occurring predators on coral reefs, δ202Hg may offer a useful tool to understand
resource partitioning across depths. Finally, copper (δ65Cu) and zinc (δ66Zn) isotopes have
recently been suggested as a proxy for coral stress, as both increase in coral host and
symbiont tissue at higher temperatures (Ferrier-Pagès et al. 2018). Given the difculty in
disentangling the production sources and consumer resource use on reefs, studies incor-
porating such additional isotopes are strongly encouraged.
8. Apply compound-specic SIA (CSIA). The number of studies employing CSIA on coral
reefs is rapidly increasing (of coral reef SI studies >5 in 2020 alone, compared to 15 between
1982 and 2019). This advance will certainly offer new insights into the complexities of the
coral reef ecosystem. Although multiple isotope approaches show signicant potential for
better elucidation of organic matter uxes and resource use in this complex ecosystem, few
studies combine CSIA of both carbon and nitrogen in the compounds of interest. Given
the depth of information they can provide on production sources and trophic interactions,
studies combining both are likely to provide a more holistic understanding of the specic
systems of interest.
9. Incorporate and explore relationships with environmental drivers. Laboratory studies
generally focus on manipulating one aspect of the environment, while eld studies use
SIs as indicators rather than testing what drives changes in their values. Few studies con-
sider the effect of multiple environmental drivers, whether natural or anthropogenic, or the
interactions occurring between them. Measuring multiple environmental variables (e.g.
nutrients, pH, temperature, and salinity) and linking those with SI values is a multi-method
approach which could better explain spatial gradients (of human impacts) on reef ecosys-
tems (Teichberg et al. 2018).
10. Utilise archival samples. Analysis of archival samples, held in museums and other institu-
tions across the globe, can provide additional information on prior isotopic baselines and
how they have shifted over time. Soft and hard corals are common, slow-growing, benthic
organisms, which may comprise important baselines against which current pollution lev-
els can be monitored. This gives the historical context against which the signicance of
contemporary isotope values can be compared. Archival specimen preservation is a con-
siderable cause for concern; however, improved mass spectrometer technology means that
very little material is physically required to obtain SI data. Where possible, we encourage
researchers to incorporate archival or historical baseline samples. Such approaches are
particularly powerful when drawing conclusions about current anthropogenic impacts.
11. Conduct multiple analyses on the same sample material. There are considerable logistical
efforts involved with collecting samples on coral reefs and conservation concerns involved
with intensive sampling, especially of threatened species. As such, we advocate for mul-
tiple analyses on the same sample material. Not only would this facilitate more collabora-
tion between different regions (which at present tend to specialise on particular elds of
research), but it would maximise the information derived from each individual sample.
12. Adopt a multi-regional, aggregative research approach. There are now many SI studies
(and therefore data) conducted on coral reefs, but almost all are isolated to a single area.
Further still, there are regional disparities in research focus. Here, it is worth acknowl-
edging that collecting SI data often requires extensive sampling to which there may be
substantial limitations, particularly in coral reef regions (i.e. lack of access, funding, infra-
structure, requiring specialist vessels or equipment, sampling during extreme conditions
to assess seasonality). Regardless, generality at the regional to global scale is currently
lacking. Moreover, inferences from different studies can be contradictory (e.g. see ‘Trophic
niches: isotopic niches’). Given the number of studies now published, a more aggregative
research approach (i.e. meta-analyses) may help discern ubiquity in patterns and drivers of
these. Complementary to this, we advocate for larger, multi-region studies to detect, if any,
general trends in SIs (e.g. variability in production sources cf. Figure 4) on coral reefs to
act as ecological baselines. This could help generate mechanistic theory of overall ‘typi-
cal’ coral reef SI functioning. Deviations from this may point to interesting, but currently
not-yet-realised avenues of further study.
Caveats and limitations
1. Provide enough detail for SI data to be useful to others. Researchers should strive to clearly
report their sampling design and SI data so that they can be used by others. Over 15% of
identied articles did not report when or over what period samples were taken (Figure 5A),
despite the high spatiotemporal variability of SI data on coral reefs. Furthermore, when
extracting SI baseline data (i.e. Table 3), we found that many articles only published data
in Figures and/or did not provide sample sizes that are required to understand data spread
and error. More rigorous reporting will facilitate point 12 above, allowing researchers to
employ an aggregative approach to future coral reef SI studies.
2. Interpret SI data within the context of underlying SI baselines. Variation in SI baselines (v al-
ues at the base of the food web) must be considered when assessing variation in resource and
nutrient use using isotopes. There is a tendency to extrapolate from taxon-specic variations
in tissue SI data to infer biogeochemical rates or anthropogenic impacts, which is especially
concerning across small ranges in isotope values. These variations may be within ranges of
a few per mille or less, which alone can be explained by discrimination and metabolic varia-
tions, or uctuations in isotopic baselines. This presents a high risk of overinterpretation,
especially given the dynamic uxes present on coral reefs. Understanding natural variation
in SI values is also needed when analysing the inuence of stochastic events (e.g. coral
spawning, coral bleaching) with SIs, especially when SI perturbations are small relative
to the magnitude of the natural variance in SI baselines (see Figure 4). We urge research-
ers to take careful consideration when interpreting spatial and temporal heterogeneity in
reef organism SI values and to measure isotopic baselines wherever possible. This might
involve comprehensive source sampling for bulk SIA or the application of more source-
specic CSIA. Complementary data, e.g. acoustic telemetry or nutrient concentrations, and
data simulations prior to SIA (to estimate the likely impact, for example, TDF variability
could have on observed data) could also be hugely benecial for considering SI variation in
context. In some cases, it may not be possible to measure baseline source values in situ. As
a rst estimate, researchers should consider the source SI values presented herein (Figure
4 and Table 3 for interstudy means; Table S6 for study-specic values). The presented val-
ues integrate differences attributable to spatiotemporal dynamics, biodiversity, and inter-
laboratory differences, highlighting the variability that has been observed across studies.
For example, macroalgae SI values show high variance (mean ± S.D. for δ13C = 15.68 ± 4.87
and δ15N = 3.93 ± 3.45; Table 3), especially between species, and, as such, authors should
consider some form of abundance weighting by species.
3. Isotopic niche trophic nich e. While variability in SI data within a population may indicate
there are individuals with consistent differences in trophic ecology, low variability in SI
data in a population does not necessarily indicate a narrow trophic niche. In the latter case,
because of the time integrating character of the SI signatures, there are two possibilities:
(1) individuals could be constantly feeding on one production source or (2) they could
be feeding on different sources in proportions or combinations that happen to integrate to
the same SI value. Specically, how equivalent is the isotopic niche to the trophic niche?
What is the magnitude of isotopic variation expected from processes independent of feeding
variation (e.g. growth rates, diet quality)? Given the diversity of production sources avail-
able on coral reefs, these questions and the discrepancy between the trophic niche and the
isotopic niche may be more of a problem in this ecosystem compared to others with less
diversity in available sources for consumers. Consequently, care must be taken when mak-
ing inferences regarding trophic niches based on isotopic niches on coral reefs.
SIA are an important tool that have elucidated many of the diverse and complex processes and
relationships occurring on coral reef ecosystems. By combining a traditional literature search of
databases with topic modelling of article abstracts, we identied recurring patterns and themes in
the SI coral reef studies published to date. Summarising how SIs have advanced our understanding
of coral reefs is challenging due to the inherent crossover between studies, but the topic modelling
approach partitioned the article text data to generate non-biased categories, providing a clear guide
on the most logical structure for the review.
One of the fundamental components of SI advances for coral reef ecology, and also one of the
challenges, involves identifying the available energy uxes to reef food webs and how these vary
across different scales. SIA have been used to successfully identify and quantify inputs to reefs, and
releases of material from reef organisms, showing that both are closely linked to the spatial arrange-
ment of organisms and hydrodynamics across reefs. Fluctuations in available resources, related to
the structure and layout of the seascape, are reected in reef primary producer and consumer SI
values. This is highlighted by the global variability in reported SI baselines across the literature
(Table 3, Figure 4), emphasising the importance of considering variations in these when studying
trophodynamics across coral reef food webs.
Corals represent one of the most studied organisms on coral reefs due to their instrumental role
as ecosystem engineers. SI studies have revealed just how complex their nutrient uptake and feed-
ing strategies are, often with stark contrasts between species and little consistency in their reliance
on auto- or hetero-trophic resources spatially and temporally. SI studies have also highlighted the
importance of previously underappreciated holobiont groups to the overall coral reef ecosystem,
notably sponges that underpin diverse pathways of in situ DOM and POM recycling. The myriad of
interactions occurring between the vast numbers of reef primary producers and consumers is chal-
lenging to explore, but SI data have begun to disentangle some of these. For example, many isotopic
niche studies have shown that traditional dietary classications mask individual-level variations
in resource use. They suggest that many reef organisms have more varying and exible functional
roles than those inferred from traditional techniques. Such insight also points to the fact that a bet-
ter understanding of wider feeding relationships across guilds, not only within guilds, is required,
particularly among invertebrates.
Coral reef ecosystems do not persist in isolation, and SI studies demonstrate energetic link-
ages with adjacent habitats. These linkages are formed not only from ontogenetic shifts in habitat
use of reef shes, from their nursery grounds in mangroves and seagrass beds to the reef, but also
through the movement patterns of larger, mobile predators. SIs also reveal vertical movement pat-
terns across depth gradients, highlighting the extent of connectivity between shallow and deeper
reefs. Connectivity is not only determined by energy ows, however, with SIs providing a method-
ological means of transgenerational tagging to follow larval distributions, highlighting the diversity
of research questions that can be addressed using SI techniques.
SIA have become an increasingly important tool for exploring anthropogenic impacts on coral
reef food webs; they can highlight nutrient inputs, ocean acidication effects, and thermal stress,
although care is needed not to conate such effects with natural SI baseline variations. Climate
change is increasing global water temperatures, resulting in catastrophic bleaching of coral reefs
worldwide. Such a loss of live coral can impact associated food webs by reducing biodiversity and
degrading habitats, resulting in lower trophic complexity across the community (Gabara et al. 2021),
as well as reduced ecological stability due to loss of functional redundancy. SIA represents a crucial
tool to increase our understanding of the complex trophic interactions occurring on coral reefs that
are modulated by environmental drivers and their associated dynamics, including human-induced
climate change.
The number of SI reef studies has been increasing rapidly in recent years. By objectively draw-
ing on the published literature, we have synthesized the current knowledge and understanding
acquired through the application of SIA on coral reefs into ve broad bodies of research focus. In
doing so, we have highlighted potential research avenues that warrant further exploration, includ-
ing increasing the scale at which SI studies are conducted (both through time and across space) in
the hope of identifying more general patterns and processes that underpin coral reef structure and
functionality. While acknowledging the considerations that need to be made when utilising SIs,
we hope this review acts as a useful synthesis and will serve to bolster the expanding literature on
ecological applications of SI approaches to coral reef ecosystems.
CS and ASJW were supported by funding from the Hong Kong Branch of the Southern Marine
Science and Engineering Guangdong Laboratory (Guangzhou) (SMSEGL20SC01) and the Research
Grants Council (RGC) of Hong Kong (RGC Project No. 26100120). MRDC was supported by the
NERC-BMBF CAO Coldsh project (NE/R012520/1) at Newcastle University and was funded by Irish
Research Council Laureate Award IRCLA/2017/186 to Andrew L Jackson, Trinity College Dublin. We
thank Dr Veronica Radice, one other anonymous reviewer, and the editor, Prof Peter Mumby, for their
constructive comments. The rst two authors, CS and MRDC, contributed equally to this work.
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